In Press

Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes/issues, but are citable by Digital Object Identifier (DOI).
Display Method:
Original Paper
High-resolution simulation dataset of hourly PM2.5 chemical composition in China (CAQRA-aerosol) from 2013 to 2020
Lei Kong, Xiao Tang, Jiang Zhu, Zifa Wang, Bing LIU, Yuanyuan ZHU, Lili Zhu, Duohong CHEN, Ke Hu, Huangjian Wu, Qian WU, Jin Shen, Yele Sun, Zirui Liu, Jinyuan Xin, Dongsheng Ji, Mei Zheng
, Available online   , Manuscript accepted  07 June 2024, doi: 10.1007/s00376-024-4046-5
Scientific knowledge on the chemical compositions of fine particulate matter (PM<sub>2.5</sub>) is essential for properly assessing its health and climate effects, and for decision makers to develop efficient mitigation strategies. A high-resolution PM<sub>2.5</sub> chemical composition dataset (CAQRA-aerosol) is developed in this study which provides hourly maps of organic carbon, black carbon, ammonium, nitrate and sulfate in China from 2013 to 2020 with a horizontal resolution of 15 km. This paper describes the method, access and validation results of this dataset. It shows that the CAQRA-aerosol has good consistency with the observations that achieves higher or comparable accuracy with previous PM<sub>2.5</sub> composition datasets. Based on CAQRA-aerosol, spatiotemporal changes of different PM<sub>2.5</sub> compositions were investigated from a national viewpoint, which emphasizes different changes of nitrate from other compositions. The estimated annual rate of population-weighted concentrations of nitrate is 0.23 μg∙m<sup>-3</sup>∙a<sup>-1</sup> from 2015 to 2020, compared with the −0.19 to −1.1 μg∙m<sup>-3</sup>∙a<sup>-1</sup> for other compositions. The whole dataset is freely available from the China Air Pollution Data Center (
Characteristics of sensible and latent heat fluxes and cold front effects over a boreal lake
Lujun Xu, Huizhi Liu, Aki Vähä, Joonatan Ala-Könni, Ivan Mammarella, xuefei Li, Qun Du, Yang Liu, vesala timo
, Available online   , Manuscript accepted  06 June 2024, doi: 10.1007/s00376-024-3214-y
Understanding characteristics of heat exchange and evaporation variation of lakes is important for regional water resource management and sustainable development. Based on eddy covariance measurement over Lake Vanajavesi in southern Finland, characteristics of energy fluxes and cold fronts effects on energy exchange were investigated. The lake acted as a heat sink in spring and summer and a heat source in winter. The latent heat flux reached minimum value in the morning, and peaked in the afternoon. The diurnal variation of sensible heat flux was opposite to that of latent heat flux. Impact factors for the sensible heat flux were mainly the lake-air temperature difference, and lake-air temperature difference multiply by wind speed. The latent heat flux was mainly affected by vapor pressure deficit, and vapor pressure deficit multiply by wind speed. The annual mean values of bulk transfer coefficients for momentum, heat, and water vapor were 1.98×10-3, 1.62×10-3, and 1.31×10-3 respectively. Bulk transfer coefficients for heat and water vapor were not equal, indicating parameterization of energy exchange in numerical models, where assume heat coefficient equals to water vapor coefficient, need to be improved. During ice-free season, cold fronts resulted in 28 sensible heat pulse and 17 latent heat pulse, contributing to 50.59% and 34.89% of sensible and latent heat exchange in Lake Vanajavesi. The results indicated cold fronts have significant impacts on the surface energy budget and evaporation over lakes.
Causes of Winter Persistent Extreme Cold Events in Northeastern China
Ming Yang, Qingjiu Gao, Tim Li
, Available online   , Manuscript accepted  05 June 2024, doi: 10.1007/s00376-024-4060-7
Persistent (5-day or longer) extreme cold events (ECEs) over northeastern China during the boreal winter of 1979-2020 are investigated using daily minimum temperature (Tmin) from the China Meteorological Data Network. The extreme cooling area and intensity indices associated with the ECEs exhibit a dominant 10-40-day periodicity. The link of the ECEs to atmospheric intraseasonal oscillations (ISOs) is further examined. The ECEs may be categorized into W- and N- type. In the former, the low-frequency cooling associated with the ISO mode first penetrates into the western boundary of the northeastern China region and gradually occupies over the entire domain at its peak phase. The upper-tropospheric circulation associated with this type is characterized by a northwest-southeast oriented Rossby wave train, expanding from the Ural Mountains to the western Pacific Ocean. In the latter, the cooling invades over the northern boundary first and then penetrates into the entire region. The precursory signal in the upper troposphere associated with this type is a zonally oriented negative geopotential height anomaly, which moves southward. A downward-propagating signal was observed in the stratospheric potential vorticity field prior to the peak cooling, implying a possible stratospheric impact. In addition to the aforementioned W- and N- types, ECEs may occur in a local region over either northern or southern northeastern China.
Water−Heat Synergy Shapes Evapotranspiration−Precipitation Coupling Patterns Across Northern China
Zesu Yang, qiang zhang, Yu Zhang, YUE Ping, Jian Zeng, Lixia Meng, Yulei Qi
, Available online   , Manuscript accepted  04 June 2024, doi: 10.1007/s00376-024-3256-1
Northern China is a prominent "hotspot" for land−atmosphere interactions, with substantial gradients in both moisture and thermal conditions. Previous studies identified a link between land−atmosphere coupling and the individual roles of each factor, but the synergistic effect of the two factors remains unclear. This study considered the co-variation of evapotranspiration and precipitation to assess evapotranspiration−precipitation (ET−P) coupling across northern China, exploring its spatial variations and their linkage to water and heat factors. Our findings reveal a transition from strongly positive coupling in the northwest to weakly negative coupling in the southeast, peaking in spring. These spatial variations were attributed to water (soil moisture) and heat (air temperature), which explained 39% and 25% of the variability, respectively. The aridity index (AI), a water−heat synergy factor, was the dominant factor, explaining 66% of the spatial variation in ET−P coupling. As the AI increased, ET−P coupling shifted from strongly positive to weakly negative, with an AI around 0.7. This shift was determined by a shift in the evapotranspiration−lifting condensation level (LCL) coupling under an AI change. Regions with an AI below 0.7 experienced water-limited evapotranspiration, where increased soil moisture enhanced evapotranspiration, reduced sensible heat (H), and lowered LCL, resulting in a negative ET-LCL coupling. Conversely, regions with an AI above 0.7 experienced energy-limited evapotranspiration, where the positive ET−LCL coupling reflected a positive H−LCL coupling or a positive impact of LCL on evapotranspiration. This analysis advanced our understanding of the intricate influences of multi-factor surface interactions on the spatial variations of land−atmosphere coupling.
Characteristics and Formation Mechanisms of Low‐Level Jets in Northeastern China
Shu Hailong, Fan Zhang, Yu Du, Yue Wang, Huichuang Guo, Zhen Song, Qinghong Zhang
, Available online   , Manuscript accepted  03 June 2024, doi: 10.1007/s00376-024-3209-8
This study examines low-level jets (LLJs) across Northeastern China during both warm (June to September) and cold seasons (December to March) from 1957 to 2021, using fifth generation European Centre for Medium-Range Weather Forecasts reanalysis data with 25-km resolution. LLJs manifest in two prominent regions: one along the leeward flank of the Greater Khingan Mountains in the cold season and another at the center of Northeastern China in the warm season. The intricate interplay between ambient circulation and terrain shapes LLJ distribution, altitudes, wind directions, diurnal cycles, and seasonal diversities. During the warm season, prevailing southwesterly LLJs are found at 925 hPa, while the cold season features stronger and more frequent northwesterly LLJs at 875 hPa. Analysis of the diurnal patterns reveals distinctive behaviors of LLJs between the cold and warm seasons. During the warm season, the single peak in LLJ occurrence emerges around midnight, conversely, in the cold season, LLJs are most frequent shortly before midnight with an additional sub-peak in the morning. A momentum budget analysis establishes mechanisms underlying these two distinct diurnal variations. In both seasons, the diurnal variation of LLJs is predominately driven by inertial oscillation and mountain-valley circulation. However, the sub-peak observed in the cold-season morning arises from the (thermo-)dynamic interaction between the low-level atmosphere and complex terrain.
The Evolution of Microphysical Structures and Cloud-to-ground Lightning in A Deep Compact Thunderstorm over the Nanjing Area
Ji Yang, Kun Zhao, Ping Song, Long Wen, Fanchao Lyu, Jie Ming, Yuanyuan Zhen
, Available online   , Manuscript accepted  03 June 2024, doi: 10.1007/s00376-024-3377-6
In this study, we examined the dynamics and microphysical structures of a deep compact thunderstorm event driving cloud-to-ground (CG) lightning over the Nanjing area located within the Yangtze-Huai River Basin (YHRB) during the monsoon break period. The microphysical structures combined with the dynamics in the glaciated, mixed-phase, and warm phase layers during the formative, intensifying, and mature stages of the thunderstorm were first investigated using C-band polarimetric radar and CG lightning observations. The results showed thunderstorm during the mature stage produced a local cold pool, which collided with southerly warm wind, resulting in strong updraft. The strong updraft favored the lifting of raindrops to the mixed-phase region to form abundant supercooled liquid water and graupel. From the formative stage to the developing stage and further to the mature stage, increased ZH and reduced ZDR within the mixed-phase region has been found, especially within the strong updraft region (> 5 m s-1). This phenomenon suggested the evolution process of supercooled raindrops to large hydrometeors (graupel and hail), indicating strong riming process. These signatures showed a favorable environment for thunderstorm electrification, and resulting in most frequent lightning during the thunderstorm life cycle.
AI-based Correction of Wave Forecasts Using the Transformer-enhanced UNet Model
YanZhao Cao, Shouwen Zhang, Guannan Lv, Mengchao Yu, Bo Ai
, Available online   , Manuscript accepted  03 June 2024, doi: 10.1007/s00376-024-3319-3
Grid forecasting can be used to effectively enhance the spatial and temporal density of forecast products, thereby improving the capability of short-term marine disaster forecasting and warnings in terms of proximity. The traditional method that relies on forecasters' subjective correction of station observation data for forecasting has been unable to meet the practical needs of refined forecasting. To address this problem, this paper proposes a transformer-enhanced UNet (TransUNet) model for wave forecast artificial intelligence (AI) correction, which fuses wind and wave information. The Transformer structure is integrated into the encoder of the UNet model, and instead of using the traditional upsampling method, the dual-sampling module is employed in the decoder to enhance feature extraction capability. This paper compares the TransUNet model with the traditional UNet model using wind speed forecast data, wave height forecast data, and significant wave height reanalysis data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The experimental results indicate that the TransUNet model yields smaller root-mean-square errors, mean errors, and standard deviations of the corrected results for the next 24-hour forecasts than does the UNet model. Specifically, the root-mean-square error decreased by more than 21.55% compared to its precorrection value. According to the statistical analysis, 87.81% of the corrected wave height errors for the next 24-hour forecast were within ±0.2 m, with only 4.56% falling beyond ±0.3 m. This model effectively limits the error range and enhances the ability to forecast wave heights.
Development of Asymmetric Convection in Tropical Cyclone under Environmental Uniform Flow and Vertical Wind Shear
Yubin Li, Yuncong Jiang, Johnny CHAN, Kevin Cheung
, Available online   , Manuscript accepted  27 May 2024, doi: 10.1007/s00376-024-3344-2
Idealized numerical simulations have been carried out to reveal the complexity in the development of asymmetric convection in a tropical cyclone (TC) under the influence of an environment with either uniform flow, vertical wind shear (VWS), or both. Results show that rainwater is enhanced to the right of the motion in the outer rainband but upshear-left in the inner-core region. Further, due to the asymmetries introduced by the environment flow, wavenumber-1 temperature and height anomalies develop at a radius of ~1000 km at the upper levels. A sub-vortex aside from the TC center encompassing the wavenumber-1 warm center appears, and asymmetric horizontal winds emerge, which in turn changes the storm-scale (within 400 km) VWS. Deep convection in the inner core follows closely the changing storm-scale VWS when its magnitude is larger than 2 m s-1 and is located downshear of storm-scale VWS in all the experiments with environmental flow. In the outer rainbands, the maximum boundary layer convergence is mostly controlled by the motion direction and located in the rear-right quadrant. These results extend the previous studies on three aspects: (1) The discovery of the roughly linear combination effect from uniform flow and large-scale VWS. (2) The development of upper-level asymmetric winds on a thousand-kilometer scale through the interaction between the TC vortex and environmental flow, resulting in changes in the storm-scale VWS pattern within the TC area. (3) The revelation that TC asymmetric convection closely aligns with the direction-varying storm-scale VWS instead of the initially designated VWS.
Unveiling Cloud Vertical Structures over the Interior Tibetan Plateau through Anomaly Detection in Synergetic Lidar and Radar Observations
Zhao Wei, Yinan Wang, Yongheng BI, Xue Wu, Yufang Tian, Lingxiao Wu, Jingxuan Luo, Xiaoru Hu, Zhengchao Qi, Jian Li, Yubing Pan, Daren Lu
, Available online   , Manuscript accepted  27 May 2024, doi: 10.1007/s00376-024-3221-z
Cloud vertical structure (CVS) strongly affects atmospheric circulation and cloud radiative transfer, yet long term ground-based observations are scarce over the Tibetan Plateau (TP) despite its vital role in global climate. This study utilizes ground-based lidar and Ka-band cloud profiling radar (KaCR) measurements at Yangbajing (YBJ), TP, from October 2021 to September 2022, to characterize cloud properties. A novel anomaly detection algorithm (LevelShiftAD) is proposed for lidar and KaCR profiles to identify cloud boundaries, demonstrating satisfactory performance. Cloud base heights (CBH) retrieved from KaCR and lidar observations show good consistency, with a correlation coefficient of 0.78 and a mean difference of -0.06 km. Cloud top heights (CTH) derived from KaCR match well with FengYun-4A and Himawari-8 products. Thus, KaCR measurements serve as the primary dataset for investigating CVSs over the TP. Different diurnal cycles occur in summer and winter. Diurnal cycle exhibits pronounced increase of cloud occurrence frequency in the afternoon and decrease in early morning in winter, while cloud amount remains high all the day, with scattered increases at night in summer. Summer features more frequent clouds with larger geometrical thickness, higher multi-layer ratio, and greater inter-cloud spacing. Around 26% of cloud bases occur below 0.5 km. Winter exhibits bimodal distribution of cloud base heights at 0-0.5 km and 2-2.5 km. Single-layer and geometrically thin clouds prevail at YBJ. This study enriches long-term measurements of CVS over the TP, and the robust anomaly detection method helps quantify cloud macro-physical properties via synergistic lidar and radar observations.
Subsurface Temperature and Salinity Structures Inversion Using a Stacking-Based Fusion Model from Satellite Observations in the South China Sea
Can LUO, Mengya HUANG, Shoude GUAN, Wei ZHAO, Fengbin TIAN, Yuan YANG
, Available online   , Manuscript accepted  21 May 2024, doi: 10.1007/s00376-024-3312-x
The three-dimensional ocean subsurface temperature and salinity structures (OST/OSS) in the South China Sea (SCS) play crucial roles in oceanic climate research and disaster mitigation. Traditionally, the real-time OST and OSS are mainly obtained through in-situ ocean observations and simulation by ocean circulation models, which are usu-ally challenging and costly. Recently dynamical, statistical or machine learning models are proposed to invert the OST/OSS from sea surface information, however, these models mainly focused on the inversion of monthly OST and OSS. To address this issue, we apply clustering algorithms and employ a stacking strategy to ensemble three models (XGBoost, Random Forest, and LightGBM), to invert the real-time OST/OSS based on satellite-derived data and Argo dataset. Subsequently, a fusion of temperature and sa-linity is employed to reconstruct the OST and OSS. In the validation dataset, the depth-averaged Correlation (Corr) of estimated OST (OSS) is 0.919 (0.83) and an av-erage Root Mean Square Error (RMSE) is 0.639℃ (0.087 psu), with a depth-averaged coefficient of determination (R^2) of 0.84 (0.68). Notably, at the thermocline where the base models exhibit maximum error, stacking-based fusion model exhibited significant performance enhancement, with a maximum enhancement in OST and OSS inversion exceeding 10%. We further found that the estimated OST and OSS exhibits good agreement with the HYCOM data and BOA_Argo dataset during the passage of a mesoscale eddy. This study shows that the model we proposed can effectively invert the real-time OST and OSS, thereby potentially en-hancing the understanding of multi-scale oceanic processes in the SCS.
Precipitation controls on Carbon Sinks in an Artificial Green Space in the Taklimakan Desert
Yingwei Sun, Fan Yang, Jianping Huang, Xinqian Zheng, Ali Mamtimin, Chenglong Zhou, Silalan Abudukade, Jiacheng Gao, Chaofan Li, Mingjie Ma, Wen Huo, Xinghua Yang
, Available online   , Manuscript accepted  21 May 2024, doi: 10.1007/s00376-024-3367-8
Control of desertification can not only ameliorate the natural environment of arid regions but also convert desertified land into significant terrestrial carbon sinks, thereby bolstering the carbon sequestration capacity of arid ecosystems. However, longstanding neglect of the potential carbon sink benefits of desertification management, and its relationship with environmental factors has limited the exploration of carbon sequestration potential. Based on CO2 flux and environmental factors of artificial protective forest in Taklamakan Desert (TD) from 2018 to 2019, we found that the carbon storage capacity of the desert ecosystem increased approximately 140-fold after the establishment of an artificial shelter forest in the desert, due to plant photosynthesis. Precipitation levels < 2 mm had no impact on carbon exchange in the artificial shelter forest, whereas a precipitation level of approximately 4 mm stimulated a decrease in the vapour pressure deficit over a short period of about three days, promoting photosynthesis and enhancing the carbon absorption of the artificial shelter forest. Precipitation events > 8 mm stimulated soil respiration to release CO2 and promoted plant photosynthesis. In the dynamic equilibrium where precipitation stimulates both soil respiration and photosynthesis, there is a significant threshold value of soil moisture at 5 cm (0.12 m3 m-3), which can serve as a good indicator of the strength of the stimulatory effect of precipitation on both. These results provide important data support for quantifying the contribution of artificial afforestation to carbon sequestration in arid areas, and provide guidance for the development and implementation of artificial forest management measures.
Short-Term Rolling Prediction of Tropical Cyclone Intensity Based on Multi-Task Learning with Fusion of Deviation-Angle Variance and Satellite Imagery
Wei Tian, Ping Song, Yuanyuan Chen, Yonghong Zhang, Liguang Wu, Haikun Zhao, Kenny Thiam Choy Lim Kam Sian, Chunyi Xiang
, Available online   , Manuscript accepted  21 May 2024, doi: 10.1007/s00376-024-3301-0
Tropical cyclone (TC) is one of the greatest natural disasters. Accurate TC activity predictions are key to disaster prevention and mitigation. Recently, TC track prediction has made significant progress, but the improvement in intensity prediction is obviously lagging behind. At present, research on TC intensity prediction takes atmospheric reanalysis data as the research object and mines the relationship between TC-related environmental factors and intensity through deep learning. However, the reanalysis data are non-real-time in nature, which does not meet the requirements for operational forecasting applications. Therefore, a TC intensity prediction model named Inten-Pre is proposed, which can simultaneously extract the symmetry degree of strong TC convective cloud and convection intensity, and fuse the deviation-angle variance with satellite images to construct the correlation between TC convection structure and intensity. For TCs’ complex dynamic processes, a convolution neural network (CNN) is used to learn their temporal and spatial features. For real-time intensity estimation, multi-task learning acts as an implicit time-series enhancement. The model is designed with a rolling strategy that aims to moderate the long-term dependent decay problem and improve accuracy for short-term intensity predictions. Since multiple tasks are correlated, the loss function of 12 h and 24 h are corrected. After testing on a sample of TCs in the Northwest Pacific, with a 4.48 kts root mean square error (RMSE) of 6 h intensity prediction, 5.78 kts for 12 h and 13.94 kts for 24 h. TC records from official agencies are used to assess the validity of the Inten-Pre.
Joint Retrieval of PM2.5 Concentration and Aerosol Optical Depth over China Using Multi-Task Learning on FY-4A AGRI
Bo Li, Disong Fu, Ling YANG, Xuehua Fan, Dazhi Yang, Hongrong Shi, Xiang-Ao XIA
, Available online   , Manuscript accepted  21 May 2024, doi: 10.1007/s00376-024-3222-y
Aerosol optical depth (AOD) and fine particulate matter with a diameter of less than 2.5μm (PM2.5) play crucial roles in air quality, human health, and climate change. However, the complex correlation of AOD–PM2.5 and the limitations of existing algorithms pose a significant challenge in realizing the accurate joint retrieval of these two parameters at the same location. On this point, a multi-task learning (MTL) model, which enables the joint retrieval of PM2.5 concentration and AOD, is proposed and applied on the top-of-the-atmosphere reflectance (TOAR) data gathered by the Fengyun-4A Advanced Geosynchronous Radiation Imager (FY-4A AGRI), and compared to that of two single-task learning (STL) models, namely, random forest (RF) and deep neural network (DNN). Specifically, The MTL model achieved a coefficient of determination (R2) of 0.88 and a root mean square error (RMSE) of 0.10 in AOD retrieval. In comparison to the RF model, the R2 increased by 0.04, the RMSE decreased by 0.02, and the percentage of retrieval results falling within the expected error range (Within-EE) rose by 5.55%. The R2 and RMSE of PM2.5 retrieval by MTL model are 0.84 and 13.76 μg·m–3, respectively. Compared with the RF model, the R2 increased by 0.06, the RMSE decreased by 4.55 μg·m–3, and the Within-EE increased by 7.28%. Additionally, compared to the DNN model, the MTL model showed an increase of 0.01 in R2 and a decrease of 0.02 in RMSE in AOD retrieval, with a corresponding increase of 2.89% in Within-EE. ......
Applying the dark target aerosol algorithm to MERSI-II: retrieval and validation of aerosol optical depth over the ocean
Xin Pei, Leiku Yang, Weiqian Ji, Shuang Chen, Xiaoqian Cheng, Xiaofeng Lu, Hongtao Wang
, Available online   , Manuscript accepted  21 May 2024, doi: 10.1007/s00376-024-4032-y
The Medium-Resolution Spectral Imager-II (MERSI-II) instrument aboard China's Fengyun-3D satellite shares similarities with NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, enabling the retrieval of global aerosol optical depth (AOD). However, there are currently no officially released operational MERSI-II aerosol products over the ocean. This study focuses on adapting the MODIS dark target (DT) ocean algorithm to the MERSI-II sensor. A retrieval test is conducted on the 2019 MERSI data over the global ocean, and the retrieved AODs are validated against ground-based measurements from the automatic Aerosol Robotic Network (AERONET) and the shipborne Maritime Aerosol Network (MAN). The operational MODIS DT aerosol products are also used for comparison purposes. The results show that MERSI-II AOD granule retrievals are in good agreement with MODIS products, boasting high correlation coefficients (R) of up to 0.96 and consistent spatial distribution trends. Furthermore, the MERSI-II retrievals perform well when compared to AERONET and MAN measurements, with high R values (>0.86). However, the low-value retrievals from MERSI-II tend to be slightly overestimated compared to MODIS, despite both AODs displaying a positive bias. Notably, the monthly gridded AODs over the high latitudes of the northern and southern hemispheres suggest that MERSI-II exhibits greater stability in space and time, effectively reducing unrealistically high-value noise in the MODIS products. These results illustrate that the MERSI-II retrievals meet specific accuracy requirements by maintaining the algorithmic framework and most of the algorithmic assumptions, providing a crucial data supplement for aerosol studies and climate change.
Droughts in homogeneous areas of South America and associated processes during months of austral spring and summer
Mariah Gomes, Iracema Cavalcanti, Gabriela Müller
, Available online   , Manuscript accepted  09 May 2024, doi: 10.1007/s00376-024-3217-8
Droughts that occurred in selected areas located in homogeneous regions of South America during the austral springs (SON) and summers (DJF) of the period 1982‒2019 are identified using SPI. Four areas were analyzed for droughts in SON and three areas in DJF. The areas in the Amazon suffered the majority of droughts in El Niño years while most of the droughts that occurred in the area of south Brazil, Uruguay, and north Argentina occurred during La Niña years. In the areas that comprise southeast and central west Brazil, the droughts occurred during both phases of El Niño-Southern Oscillation (ENSO) and in neutral years. Thus, other processes besides ENSO can be related to the observed droughts. The droughts were looked for in each area and month, and composites of atmospheric and oceanic variables during both seasons were analyzed for the selected cases. Regional and large-scale field composites were examined to identify the main processes associated with dry conditions in the different areas. Regional features were related to the influence of high pressure over south and southeast areas and divergence of humidity flux in all areas. Meridional circulations contributed to subsidence over the dry regions. The large-scale characteristics include SST anomalies, wavetrains over the South Pacific Ocean with centers of action over South America that produced subsidence in the study areas, and convection anomalies in the Maritime continent and surroundings. Therefore, the droughts were associated with a combination of regional and large-scale features that produced subsidence over the analyzed regions.
Impact of Assimilating FY-4A Lightning Data with a Latent Heat Nudging Method on Short-Term Forecasts of Severe Convective Events in Eastern China
Yanqing Gao, Xiaofeng Wang, Wei Guo
, Available online   , Manuscript accepted  09 May 2024, doi: 10.1007/s00376-024-3339-z
In this study, a latent heat nudging lightning data assimilation (LDA) method independent of the flash rate was developed and tested with data from the Lightning Mapping Imager (LMI) onboard the Feng-Yun-4A (FY-4A) satellite based on the Weather Research and Forecasting (WRF) model. In this LDA method, the positive temperature perturbations at the lightning location are first calculated by the difference between the moist adiabatic temperature of a lifted air parcel and the model temperature. Then the positive temperature perturbations in the mixed-phase region are assimilated by a nudging method to adjust the latent heat within the convective system. Meanwhile, the water vapor mixing ratio is adapted to the temperature perturbations accordingly to maintain the relative humidity unchanged. This method considers the physical nature of the convective system, in contrast with other LDA methods that establish the empirical or statistical relationship between the lightning flash rates and model variables. The impact of this LDA method on short-term (≤6 h) forecasts was evaluated using two severe convective events in eastern China: a multi-region heavy rainfall event and a thunderstorm high wind event. The results showed that LDA could add thermodynamic information associated with the convective system to the WRF model during the nudging period, leading to a more reasonable storm environment. In the forecast fields, the simulations with LDA produced more realistic convective structures, resulting in an improvement in forecasts of precipitation and high winds.
Parameterization of tree and shrub stem wood density adaptions to multiple climate and soil factor gradients
Xiang Song, Jinxu Li, Xiaodong Zeng
, Available online   , Manuscript accepted  08 May 2024, doi: 10.1007/s00376-024-4034-9.
Wood density (WD) is an important wood quality and functional trait. Despite the relationships between WD and abiotic factors being important to model or predict spatial distributions of functional traits as well as responses of vegetation to climate changes, in current Earth System Models (ESMs) or Dynamic Global Vegetation Models (DGVMs), WD is often oversimplified, being defined as a globally uniform constant either for all plant functional types (PFTs) or for each individual PFT. Such oversimplifications may lead to simulation biases in the morphology of woody PFTs, as well as ecosystem transition and vegetation–atmosphere interactions. Moreover, existing conclusions about the relationships between WD and abiotic factors drawn from field observations remain mixed, making model parameterization improvements difficult. This study systematically investigated the influences of climate and soil factors on WD across various PFTs. Optimal fitting models for predicting WD within each PFT were then constructed by utilizing our collated global database of 138,604 observations. For WDs of tree PFTs, climate emerges as a more influential factor than soil characteristics, whereas for shrub PFTs the effects of climate and soil are of equivalent significance. Across all six PFTs, correlation coefficients between predictions by fitting models and observed WD range from 0.49 to 0.93. The predicted and observed WD exhibit good agreement across climate space. It is expected that the incorporation of our research findings into DGVMs will improve the simulation of tree height and forest fractional coverage, particularly in the central forest areas and forest transition zones.
Enhanced East Asian Summer Monsoon over Northeast Asia in Recent Two Decades
Song Jiang, Shuangmei Ma, Congwen Zhu, Boqi Liu, Ting Wang, Wanyi Sun
, Available online   , Manuscript accepted  08 May 2024, doi: 10.1007/s00376-024-3370-0
The East Asian summer monsoon in Northeast Asia (NEA) shows an enhanced trend with increased summer rainfall and delayed rainy season after 2000. Based on the data analyses during 1979–2022, our results show that the increased rainfall amount is associated with the enhancement of Mongolian cyclone (MC) in July–August, as a portion of the Eurasian barotropic Rossby wave train. This wave train is regulated by the sea surface temperature (SST) anomaly in North Atlantic (NA), amplified by the increased warming SST in NA. While the delayed rainy season in September is related to the enhanced anticyclone over the Kuril Islands (ACKI) in Russian Far East. The anticyclone originated from Arctic region, which is possibly induced by the Sea-Ice loss in the East Siberian Sea, which can be detected 2-months in advance. The stronger MC and ACKI jointly resulted in the enhanced East Asian summer monsoon in NEA since 2000, via the ascending motion and moisture supply. Therefore, the SST anomaly in NA is responsible for the intensified rainfall in rainy season in NEA, and the Sea-Ice in the East Siberian Sea provides a potential source for the prediction of rainy season retreat.
Extreme Meteorological Drought Events over China (1951—2022): migration pattern, diversity of temperature extremes, and decadal variations
Zhenchen LIU, Wen Zhou, Xin Wang
, Available online   , Manuscript accepted  08 May 2024, doi: 10.1007/s00376-024-4004-2
Recently, extreme meteorological droughts hit China and caused terrible socioeconomic influences. Despite previous research on the spatiotemporal characteristics and mechanisms, the two crucial issues remain seldom explored: On one hand, an event-oriented drought set with detailed spatiotemporal evolutions is urgently required. On the other hand, complex migration patterns and diversity of synchronous temperature extremes need to be quantitatively investigated. Accordingly, the main achievements are concluded as follows: First, we applied the newly developed 3D DBSCAN-based detection method to produce an event-oriented set of extreme meteorological droughts over China (deposited on, which have been verified with historical atlas and monographs case by case. Second, distinctive migration patterns (i.e., stationary/propagation types) are identified and ranked, considering differences in latitudinal zones and coastal/inland locations. Third, we analyzed the diversity of synchronous temperature extremes (e.g., hotness and coldness). An increasing trend in hot droughts has been observed over China since the late 1990s, predominantly appearing to the south of 30°N and the north of 40°N. All the drought events and synchronous temperature extremes are ranked using a comprehensive magnitude index, with the 2022 summer-autumn Yangtze River hot drought the hottest. Furthermore, the Liang-Kleeman information flow-based causality analysis emphasizes key areas where PDO and AMO influence decadal variations in coverages of droughts and temperature extremes. We believe that achievements in this study may offer new insights into sequential mechanism exploration and prediction-related issues.
A Spatial-dependent Nudging Method and Its Application to Global Tide Assimilation
li liu, Xueen Chen
, Available online   , Manuscript accepted  07 May 2024, doi: 10.1007/s00376-024-4062-5
Tides, as a crucial dynamic process in the ocean, play a vital role in both the marine and atmospheric studies, thus accurate simulation of tidal processes is of utmost importance in tidal circulation models. Based on the sequential data assimilation method and the concept of the Kalman gain matrix, this paper proposes a new Nudging method with spatial-dependent coefficients for the tidal assimilation. The spatial-dependent Nudging method not only retains the advantages of the traditional Nudging method but also facilitates the direct determination of a more reasonable spatial distribution of Nudging coefficients. Utilizing the M2 tidal constituent as an illustration, we conducted the assimilation experiments of sea level data to the barotropic circulation and tide model to assess the global harmonic constants of the M2 constituent. The results demonstrate that the spatial-dependent Nudging method successfully mitigates deviations of tidal phase lag. Following assimilation using the new method, the deviations of the M2 tidal amplitude and phase lag can be reduced by 47% and 18%, respectively, compared to the no-assimilation case, and up to 9% and 11%, respectively, in comparison to the traditional Nudging method. We also applied the S-Nudging method to realistic tidal simulations, and its effectiveness relative to traditional methods is significantly enhanced, making it highly valuable for the modeling of oceanic tidal circulation.
Spatial-Temporal Evaluation and Future Projection of Diurnal Temperature Range over the Tibetan Plateau in CMIP6 Models
Suguo ZHANG, Qin Hu, Xianhong Meng, Yaqiong Lu, Xianyu Yang
, Available online   , Manuscript accepted  07 May 2024, doi: 10.1007/s00376-024-3346-0
The Diurnal Temperature Range (DTR) serves as a vital indicator reflecting both natural climate variability and anthropogenic climate change. This study investigates the historical and projected multi-temporal DTR variations over the Tibetan Plateau. It assesses 23 climate models from the Coupled Model Intercomparison Project 6 (CMIP6) using CN05.1 observational data as validation, evaluating their ability to simulate DTR over the Tibetan Plateau. Then, the evolution of DTR over the Tibetan Plateau under different shared socioeconomic path (SSP) scenarios for the near, middle, and long term of future projection are analyzed using eleven selected robustly performing models. Key findings reveal: (1) Among the models examined, BCC-CSM2-MR, EC-Earth3, EC-Earth3-CC, EC-Earth3-Veg, EC-Earth3-Veg-LR, FGOALS-g3, FIO-ESM-2-0, GFDL-ESM4, MPI-ESM1-2-HR, MPI- ESM1-2-LR, and INM-CM5-0 exhibit superior integrated simulation capability for capturing the spatial-temporal variability of DTR over the Tibetan Plateau. (2) Projection indicates a slightly increasing trend in DTR on the Tibetan Plateau in the SSP1-2.6 scenario, and decreasing trends in the SSP2-4.5, SSP3-7.0, and SPP5-8.5 scenarios. Certain areas, such as southeastern edge Tibetan Plateau, western hinterland Tibetan Plateau, the southern Kunlun, and the Qaidam basins, the changes in DTR are relatively large. (3) Notably, the warming rate of maximum temperature under SSP2-4.5, SSP3-7.0, and SPP5-8.5 scenarios is slower compared to that of minimum temperature, and it emerges as the primary contributor to the projected decrease in DTR over the Tibetan Plateau in the future. Key words: Tibetan Plateau; CMIP6 models; daily temperature range; model assessment; historical period; future projection
Enhanced cooling efficiency of urban trees on hotter summer days in 70 cities of China
Limei YANG, Jun Ge, Yipeng CAO, Yu LIU, Xing LUO, Shiyao WANG, Weidong Guo
, Available online   , Manuscript accepted  29 April 2024, doi: 10.1007/s00376-024-3269-9
Increasing the urban tree cover percentage (TCP) is widely recognized as an efficient way to mitigate the urban heat island effect. The cooling efficiency of urban trees can be either enhanced or attenuated on hotter days, depending on the physiological response of urban trees to rising ambient temperature. However, the response of urban trees’ cooling efficiency to rising urban temperature remains poorly quantified for China’s cities. In this study, we quantify the response of urban trees’ cooling efficiency to rising urban temperature at noontime (~13:30 local time) in 17 summers (June, July, and August) from 2003–2019 in 70 economically developed cities of China based on satellite observations. The results show that urban trees have stronger cooling efficiency with increasing temperature, suggesting additional cooling benefits provided by urban trees on hotter days. The response of urban trees’ cooling efficiency to rising urban temperature ranges from 0.002 to 0.055 ℃∙%^(-1) per 1 ℃ increase in temperature across the selected cities, with larger values for the low-TCP-level cities. The response is also regulated by background temperature and precipitation, as the additional cooling benefit tends to be larger in warmer and wetter cities at the same TCP level. The positive response of urban trees’ cooling efficiency to rising urban temperature is explained mainly by the stronger evapotranspiration of urban trees on hotter days. These results have important implications for alleviating urban heat risk by utilizing urban trees, particularly considering that extreme hot days are becoming more frequent in cities under global warming.
Limited sea surface temperature cooling due to the barrier layer promoting Super Typhoon Mangkhut (2018)
Huipeng Wang, Jiagen Li, Junqiang Song, Liang Sun, Fu Liu, Han Zhang, Kaijun Ren, Huizan Wang, Chunming Wang, Jinrong Zhang, Hongze Leng
, Available online   , Manuscript accepted  29 April 2024, doi: 10.1007/s00376-024-3268-x
This study investigates the impact of the salinity barrier layer (BL) on the upper ocean response to Super Typhoon Mangkhut (2018) in the western North Pacific. After the passage of Mangkhut, a noticeable increase (~0.6 psu) in sea surface salinity (SSS) and a weak decrease (<1 ℃) in sea surface temperature (SST) were observed on the right side of the typhoon track. Mangkhut-induced SST change can be divided into the three stages, corresponding to the variations in BL thickness and SST before, during and after the passage of Mangkhut. During the pre-typhoon stage, SST slightly warmed due to the entrainment of BL warm water, which suppressed the cooling induced by surface heat fluxes and horizontal advection. During the forced stage, SST cooling was controlled by entrainment, and the preexisting BL reduced the total cooling by 0.89 ℃/day, thus significantly weakening the overall SST cooling induced by Mangkhut. During the relaxation stage, the SST cooling primarily was caused by the disappearance of BL. Our results indicate that the preexisting BL can limit typhoon-induced SST cooling by suppressing the entrainment of cold thermocline water, which is contributed to Mangkhut becoming the strongest typhoon in 2018.
Improving satellite-retrieved cloud base height with ground-based cloud radar measurements
Zhonghui Tan, ju wang, Jianping Guo, Chao Liu, miao zhang, Shuo Ma
, Available online   , Manuscript accepted  29 April 2024, doi: 10.1007/s00376-024-4052-7
Cloud base height (CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a look-up table (LUT) of effective cloud water content (ECWC), which represents the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness (CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparison analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar (MMCR) measurements, and results show that the mean bias (correlation coefficient) is 0.18±1.79 km (0.73), which is lower (higher) than 0.23±2.11 km (0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar (i.e., CloudSat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing network, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.
Identifying Three Shapes of Potential Vorticity Streamers Using Mask R-CNN
Luqiang HAO, Zuowei Xie, Yuanfa Gong, Jinfang Yin
, Available online   , Manuscript accepted  24 April 2024, doi: 10.1007/s00376-024-3266-z
Potential vorticity (PV) streamers are elongated filaments of high PV intrusions that generally exhibit three distinct shapes: ordinarily southwestward, hook and treble-clef shapes, each with significant weather influences. These PV streamers were most frequent over arid and semi-arid Central Asia in the mid-high latitude region. This study applied Mask R-CNN to PV streamers on the dynamical tropopause during the warm season (May to September) over the years 2000–2004 to train a weighted variational model capable of identifying these different shapes. The trained model demonstrated a strong ability to distinguish between the three shapes. A climatology analysis of PV streamers over Central Asia spanning 2000 to 2021 revealed that it featured an increasingly deep and pronounced reversal circulation from ordinary to treble-clef shapes. The treble-clef shape featured a PV tower and distinct cut-off low in the troposphere, but the associated upward motions and precipitation were confined within approximately 1200 km to the east of the PV tower. Although the hook-shape PV streamers were linked to a weaker cut-off low, the extent of upward motion and precipitation was nearly double that of the treble-clef category. In contrast, the ordinary PV streamer was primarily associated with tropopause Rossby wave breaking and exhibited relatively shallow characteristics, which resulted in moderate upward motion and precipitation to 500 km to its east.
Improving Seasonal Forecast of Summer Precipitation in Southeastern China using CycleGAN Deep Learning Bias Correction
Song Yang, Fenghua Ling, Jing-Jia Luo, Lei Bai
, Available online   , Manuscript accepted  24 April 2024, doi: 10.1007/s00376-024-4003-3
Accurate seasonal precipitation forecasts, especially for extreme events, are crucial to preventing meteorological hazards and its potential impacts on national development, social activity and security. However, the intensity of summer precipitation is often largely underestimated in many current dynamical models. This study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks (CycleGAN) to improve the seasonal forecasts by Nanjing University of Information Science and Technology Climate Forecast System (NUIST-CFS 1.0) for predicting June-July-August precipitation in southeastern China. The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to traditional quantile mapping (QM) method. Using the unpaired bias-correction model, we can also obtain advanced forecasts of the frequency, intensity, and duration of extreme precipitation events over the dynamical model predictions. This study expands the potential applications of deep learning models to improving seasonal precipitation forecasts.
The Influence of Airflow transport Path on Precipitation during the Rainy Season in the Liupan Mountain of Northwest China
Qujun Qiu, Chunsong Lu, Shu zhiliang, Peiyun Deng
, Available online   , Manuscript accepted  23 April 2024, doi: 10.1007/s00376-024-3162-6
Utilizing observational data from seven ground gradient stations located on the eastern slope, western slope, and mountaintop of Liupan Mountains (LM) during the rainy seasons from 2020 to 2022, combined with backward trajectory cluster analysis, this study investigated the influence of airflow transport paths on the seasonal rainfall in this mountainous region. The results indicate: (1) LM’s rainy season, characterized by overcast and rainy days, is mainly influenced by cold and moist airflows (CMA) from the westerly direction and warm and moist airflows (WMA) from a slightly southern direction. The precipitation amounts under four airflow transport paths are ranked from largest to smallest as follows: WMA, CMA, warm dry airflows (WDA), and cold dry airflows (CDA). (2) WMA contribute significantly more to the intensity of regional precipitation than the other three types of airflows. During localized precipitation events, warm airflows have higher precipitation intensities at night than cold airflows, while the opposite is true during the afternoon. (3) During regional precipitation events, water vapor content is a primary influencing factor. Precipitation characteristics under humid airflows are mainly affected by high water vapor content, whereas during dry airflow precipitation, dynamic and thermodynamic factors have a more pronounced impact than for humid airflows. (4) During localized precipitation events, the influence of dynamic and thermodynamic factors is more complex than during regional precipitation, with precipitation characteristics of the four airflows closely related to their water vapor content, air temperature and humidity attributes, and orographic lifting. (5) Compared to regional precipitation, the influence of topography is more prominent in localized precipitation processes.
Effectiveness of Precursor Emission Reductions for the Control of Summertime Ozone and PM2.5 in the Beijing–Tianjin–Hebei Region under Different Meteorological Conditions
Jing QIAN, Hong LIAO
, Available online   , Manuscript accepted  23 April 2024, doi: 10.1007/s00376-024-4071-4
We used observed concentrations of air pollutants, reanalyzed meteorological parameters, and results from the Goddard Earth Observing System Chemical Transport Model to examine the relationships between concentrations of maximum daily 8-h average ozone (MDA8 O3), PM2.5 (particulate matter with diameter of 2.5 µm or less), and PM2.5 components and 2-m temperature (T2) or relative humidity (RH), as well as the effectiveness of precursor emission reductions on the control of O3 and PM2.5 in Beijing–Tianjin–Hebei (BTH) under different summertime temperature and humidity conditions. Both observed (simulated) MDA8 O3 and PM2.5 concentrations increased as T2 went up, with linear trends of 4.8 (3.2) ppb °C−1 and 1.9 (1.5) µg m−3 °C−1, respectively. Model results showed that the decreases in MDA8 O3 from precursor emission reductions were more sensitive to T2 than to RH. Reducing a larger proportion of volatile organic compound (VOC) emissions at higher T2 was more effective for the control of summertime O3 in BTH. For the control of summertime PM2.5 in BTH, reducing nitrogen oxides (NOx) combined with a small proportion of VOCs was the best measure. The magnitude of reduction in PM2.5 from reducing precursor emissions was more sensitive to RH than to T2, with the best efficiency at high RH. Results from this study are helpful for formulating effective policies to tackle O3 and PM2.5 pollution in BTH.
A New method for deriving the high-vertical-resolution Wind Vector data from L-band radar sounding system in China
Fang Yuan, Zijiang Zhou, LIAO Jie
, Available online   , Manuscript accepted  10 April 2024, doi: 10.1007/s00376-024-3163-5
High-vertical-resolution radiosonde wind data is highly valuable for describing the dynamics of the meso- and micro-scale atmosphere. However, the current algorithm used in China's L-band radar sounding system for calculating high-vertical-resolution wind vectors excessively smooth the data, resulting in significant underestimation of the calculated kinetic energy of gravity waves compared to similar products from other countries, greatly limiting the effective utilization of the data. To address this issue, this study proposes a novel method to calculate high-vertical-resolution wind vectors that utilizes elevation angle, azimuth angle, and slant range from L-band radar. In order to obtain wind data with stable quality, a two-step automatic quality control procedure, including the root mean square error F (RMSE-F) test and elemental consistency test are first applied to the slant range data, to eliminate continuous erroneous data caused by unstable signals or radar malfunctions. Then a wind calculation scheme based on a sliding second-order polynomial fitting is utilized to derive the high-vertical-resolution radiosonde wind vectors. The evaluation results demonstrate that the wind data obtained through the proposed method shows a high level of consistency with the high-resolution wind data observed using the Vaisala Global Positioning System (GPS) and the data observed by the new Beidou Navigation Sounding System. The calculation of kinetic energy of gravity waves in the recalculate wind data also reaches a level comparable to the Vaisala observations.
On the optimal initial inner-core size for tropical cyclone intensification: An idealized numerical study
Rong FEI, Yuqing Wang
, Available online   , Manuscript accepted  09 April 2024, doi: 10.1007/s00376-024-3296-6
Recent observational and numerical studies have revealed the dependence of the intensification rate on the inner-core size of tropical cyclones (TC). In this study, with the initial inner-core size (i.e., the radius of maximum wind—RMW) varied from 20–180 km in idealized simulations using two different numerical models, we found a nonmonotonic dependence of the lifetime maximum intensification rate (LMIR) on the inner-core size. Namely, there is an optimal inner-core size for the LMIR of a TC. Tangential wind budget analysis shows that compared to large TCs, small TCs have large inward flux of absolute vorticity due to large absolute vorticity inside the RMW. However, small TCs also suffer from strong lateral diffusion across the eyewall, which partly offsets the positive contribution from large inward flux of absolute vorticity. These two competing processes ultimately lead to the TC with an intermediate initial inner-core size having the largest LMIR. Results from sensitivity experiments show that the optimal size varies in the range of 40–120 km and increases with higher sea surface temperature, lower latitude, larger horizontal mixing length, and weaker initial TC intensity. The 40–120 km RMW corresponds to the inner-core size most commonly found for intensifying TCs in observations, suggesting the natural selection of initial TC size for intensification. This study highlights the importance of accurate representation of TC inner-core size to TC intensity forecast by numerical weather prediction models.
Understanding Simulated Causes of Damaging Surface Winds in a Derecho-Producing Mesoscale Convective System near the East China Coast based on Convection-Permitting Simulations
LIPING LUO, Ming Xue, Xin Xu, Lijuan Li, Qiang Zhang, Ziqi Fan
, Available online   , Manuscript accepted  09 April 2024, doi: 10.1007/s00376-024-3314-8
A mesoscale convective system (MCS) occurred over east China coastal provinces and the East China Sea on 30 April 2021, producing damaging surface winds near coastal city Nantong with observed speeds reaching 45 m s-1. A simulation using the Weather Research and Forecasting model at 1.5-km grid spacing generally reproduces the development of convective system and the subsequent organization into an MCS, with an eastward protruding bow segment over the sea. In the simulation, an east-west-oriented high wind swath is generated behind the gust front of the MCS. Descending dry rear-to-front inflows behind the bow and trailing gust front are found to feed the downdrafts in the main precipitation regions. The inflows help establish spreading cold outflows and enhance the downdrafts through evaporative cooling. Meanwhile, front-to-rear inflows from the south are present, associated with severely rearward-tilted updrafts initially forming over the gust front. Such inflows descend behind (north of) the gust front, significantly enhancing the downdrafts and near-surface winds within the cold pool. Consistently, calculated trajectories show that these parcels contributing to the derecho primarily originate from the region ahead (south) of the east-west-oriented gust front, and dry southwesterly flows at mid-lower levels contribute to strong downdrafts within the MCS. Moreover, momentum budget analyses reveal that large westward-directed horizontal pressure gradient force within the simulated cold pool produce rapid flow acceleration towards Nantong. The analyses enrich the understanding of damaging wind characteristics over the East China coast and will be helpful to operational forecasters.
Comparison of Adaptive Simulation Observation Experiments of the Heavy Rainfall in South China and Sichuan Basin
Linbin He, Weiyi Peng, Yu Zhang, Shiguang Miao, Siqi Chen, Jiajing Li, Duanzhou Shao, Xutao Zhang
, Available online   , Manuscript accepted  09 April 2024, doi: 10.1007/s00376-024-3114-1
This study examines the effectiveness of adaptive observation experiments using the ensemble transformation sensitivity (ETS) method to improve precipitation forecasts during heavy rainfall events in South China and the Sichuan Basin. High-resolution numerical models are employed to simulate adaptive observations. By identifying sensitive areas of key weather system positions 42 hours before heavy rainfall events, the adaptive observations help improve the prediction of jet streams, strong winds and shear lines, which are essential for accurate heavy rainfall forecasting. This improvement is reflected in both the precipitation structure and location accuracy within the verification region. In South China, targeted observations enhance rainfall predictions by improving water vapor transformation. In the Sichuan Basin, adaptive observations refine water vapor and vortex dynamics adjustments. The research highlights the importance of accurately predicting shear lines and jet streams for forecasting heavy rainfall in these areas. Overall, this study found that adaptive observation enhances the precipitation forecast skills of the structure and location for heavy rainfall in South China and the Sichuan Basin, emphasizing their potential utility in operational numerical weather prediction.
Assessment of Seasonal Rainfall Prediction in Ethiopia: Evaluating a Dynamic Recurrent Neural Network to Downscale ECMWF-SEAS5 Rainfall
Abebe Kebede, Kirsten Warrach-sagi, Thomas Schwitalla, Volker Wulfmeyer, Tesfaye Amdie, Markos Ware
, Available online   , Manuscript accepted  09 April 2024, doi: 10.1007/s00376-024-3345-1
Seasonal rainfall plays a vital role in both environmental dynamics and decision-making for rainfed agriculture in Ethiopia, a country often impacted by extreme climate events such as drought and flooding. Predicting the onset of the rainy season and providing localized rainfall forecasts for Ethiopia is challenging due to the changing spatiotemporal patterns and the country's rugged topography. The CHIRPS, ERA5-Land total precipitation and temperature data are used since 1981-2022 for prediction of spatial rainfall by applying artificial neural network (ANN). The recurrent neural network (RNN) is a nonlinear autoregressive network with exogenous input (NARX), includes feedforward connections and multiple network layers, employing the Levenberg Marquart algorithm. This method is applied to downscale data from European Centre for Medium-range Weather Forecasts fifth-generation seasonal forecast system (ECMWF-SEAS5) and the Euro-Mediterranean Centre for Climate Change (CMCC) to the specific locations of rainfall stations in Ethiopia for the period spanning from 1980 to 2020. Across the stations the results of NARX shows strong association and reduced error. The statistical results indicate that, except for the southwestern Ethiopian highlands, the downscaled monthly precipitation data exhibits high skill scores when compared to the station records, demonstrating the effectiveness of the NARX approach for predicting local seasonal rainfall in Ethiopia's complex terrain. In addition to this spatial ANN of the summer season precipitation, temperature and combined of these two variables shows a promising results compared with CHIRPS products.
Quantification of CO2 emissions from three power plants in China using OCO-3 satellite measurements
Yang Yang, Minqiang Zhou, Wei Wang, Zijun Ning, Feng Zhang, Pucai Wang
, Available online   , Manuscript accepted  09 April 2024, doi: 10.1007/s00376-024-3293-9
Coal fired power plants are a major carbon source in China. In order to assess the evaluation of China’s carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO2 emissions from point sources based on the Orbiting Carbon Observatory-2 and -3 (OCO-2 and OCO-3) satellite measurements, but the factors affecting CO2 flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO2 emissions from three power plants in China based on OCO-3 XCO2 measurements. Moreover, flux uncertainties resulting from wind information, background value, satellite CO2 measurement and atmospheric stability are investigated. Our satellite-based CO2 emission estimates at the Tuoketuo and Nongliushi power plants are generally smaller than the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) inventory, but larger than ODIAC at Baotou. This study highlights the CO2 flux uncertainty derived from the satellite measurements.
Comparison and Verification of Coherent Doppler Wind Lidar and Radiosonde in Beijing Urban Area
Zexu Luo, Xiaoquan Song, Jiaping Yin, Zhichao Bu, Yubao Chen, Yongtao Yu, Zhenlu Zhang
, Available online   , Manuscript accepted  02 April 2024, doi: 10.1007/s00376-024-3240-9
As a new type of wind field detection equipment, coherent Doppler wind lidar (CDWL) still needs more relevant observation experiments to compare and verify whether it can achieve the accuracy and precision of traditional observation equipment in urban areas. In this experiment, a self-developed CDWL was used to observe for 4 months in the Beijing southern area. After the data acquisition time and height match, the wind profile data obtained based on the Doppler beam swinging (DBS) five-beam inversion algorithm were compared with the radiosonde data released from the same location. The standard deviation (SD) of wind speed is 0.8m s-1, and the coefficient of determination R2 is 0.95. The SD of the wind direction is 17.7° and the coefficient of determination R2 is 0.96. Below the height of the roughness sublayer (about 400m), the error in wind speed and wind direction is significantly greater than the error above the height of the boundary layer (about 1500m). In the case of wind speed less than 4 m s-1, the error of wind direction is more significant and is affected by the distribution of surrounding buildings. Averaging at different height levels using suitable time windows can effectively reduce the effects of turbulence and thus reduce the error caused by different measurement methods of the two devices.
A New Algorithm of Rain Type Classification for GPM Dual-Frequency Precipitation Radar in Summer Tibetan Plateau
Yunfei Fu, Yang Liu, Peng Zhang, Songyan Gu, Lin Chen, Sun Nan
, Available online   , Manuscript accepted  02 April 2024, doi: 10.1007/s00376-024-3384-7
In this study, a new rain type classification algorithm for the DPR suitable over the TP was proposed by analyzing Global Precipitation Measurement (GPM) DPR Level-2 data in summer from 2014 to 2020. It was found that the DPR rain type classification algorithm (simply called DPR algorithm) has mis-identification problems in two aspects in summer TP. In the new algorithm of rain type classification in summer TP, four rain types are classified by using new thresholds, such as the maximum reflectivity factor, the difference between the maximum reflectivity factor and the background maximum reflectivity factor, and the echo top height. In the threshold of the maximum reflectivity factors, 30dBZ and 18dBZ are the both thresholds to separate strong convective precipitation, weak convective precipitation and weak precipitation. The results illustrate obvious differences of radar reflectivity factor and vertical velocity among the three rain types in summer TP, such as the reflectivity factor of most strong convective precipitation distributes from 15dBZ to near 35dBZ from 4km to 13km, and increases almost linearly with the decrease of height. For most weak convective precipitation, the reflectivity factor distributes from 15dBZ to 28dBZ with height from 4km to 9km. For weak precipitation, the reflectivity factor mainly distributes in range of 15~25dBZ with height within 4~10km. It is also shows that weak precipitation is the dominant rain type in summer TP, accounting for 40%~80%, followed by weak convective precipitation (25%~40%), and strong convective precipitation has the least proportion (less than 30%).
Retrieval of Volcanic Sulphate Aerosols Optical Parameters from AHI Radiometer Data
Filei Andrei, Girina Olga, Sorokin Aleksei
, Available online   , Manuscript accepted  28 March 2024, doi: 10.1007/s00376-024-3105-2
This paper presents a method for retrieving volcanic sulphate aerosols optical parameters from the AHI radiometer on board the Himawari-8 satellite. The proposed method is based on optical models for various mixtures of the volcanic cloud’s aerosol components, including ash particles, ice crystals, water drops, and sulphate aerosol droplets. The application of multicomponent optical models of various aerosol compositions allowed the optical thickness and mass loading of sulphate aerosol to be estimated in the sulfuric cloud formed after the Karymsky volcano eruption on November 3, 2021. A comprehensive analysis of the brightness temperatures of the sulfuric cloud in the infrared bands was performed, which revealed that the cloud composed a mixture of sulphate aerosol and water droplets. The use of the models of various aerosol composition allows the satellite-based estimation of optical parameters not only for sulphate aerosol but also for the whole aerosol mixture.
Convection-permitting simulations of current and future climates over the Tibetan Plateau
Liwei ZOU, Tian-Jun ZHOU
, Available online   , Manuscript accepted  26 March 2024, doi: 10.1007/s00376-024-3277-9
The Tibetan Plateau (TP) region, known as “Asian water tower”, provides a vital water resource for downstream regions. Previous studies of water cycle changes over the TP have been conducted with climate models of coarse resolution in which deep convection should be parameterized. In this study, we present results from a first set of high-resolution climate change simulations that permit convection at approximately 3.3-km grid spacing with focus on the TP using the Icosahedral Nonhydrostatic Weather and Climate Model (ICON). Two 12-year simulations were performed, consisting of a retrospective simulation (2008-2020) with initial and boundary conditions from ERA5 reanalysis and a pseudo-global warming projection driven by modified reanalysis-derived initial and boundary conditions by adding the monthly CMIP6 ensemble-mean climate change under the SSP5-8.5 scenario. The retrospective simulation shows overall good performance in capturing the seasonal precipitation and surface air temperature. Over the central and eastern TP, the average biases in precipitation (temperature) are less than -0.34 mm/day (-1.1 °C) throughout the year. The simulated biases over the TP are height dependent. Cold (wet) biases are found in summer (winter) above 5500 m. The future climate simulation suggests that the TP will be wetter and warmer under the SSP5-8.5 scenario. The general features of projected changes in ICON are comparable to the CMIP6 ensemble projection, but the added value from kilometer-scale modeling is evident in both precipitation and temperature projections over complex topographic regions. These ICON-downscaled climate change simulations provide a high-resolution dataset to the community for study of regional climate changes and impacts over the TP.
Changes in BSISO under Global Warming in CMIP6 Models
Zhefan Gao, Chaoxia Yuan
, Available online   , Manuscript accepted  25 March 2024, doi: 10.1007/s00376-024-3300-1.
Changes in the boreal summer intraseasonal oscillation (BSISO) activities at the end of 21st century under the SSP5-8.5 scenario are assessed here by adopting 17 CMIP6 models and the weak-temperature-gradient assumption. Results show that the intraseasonal variations become more structured. The BSISO related precipitation anomaly shows a larger zonal scale and propagates further northward. However, there has no broad agreement among models on the changes in the eastward and northward propagation speeds and the frequency of individual phases. In the western North Pacific (WNP), the BSISO precipitation variance is significantly increased at 4.62% K-1 due to the significantly increased efficiency of vertical moisture transport by per unit BSISO apparent heating. The vertical velocity variance is significantly decreased at -3.51% K-1 in the middle troposphere due to the significantly increased mean-state static stability. Changes in the lower-level zonal wind variance are relatively complex with a significant increase stretching from northwestern to southeastern WNP but the opposite in other regions. This is probably due to the combined impacts of northeastward shift of the BSISO signals and the reduced BSISO vertical velocity variance under global warming. Changes in strong and normal BSISO events in the WNP are also compared. They show same-signed changes in precipitation and large scale circulation anomalies but opposite changes in the vertical velocity anomalies. This is probably because the precipitation anomaly of strong/normal events changes at a rate much larger/smaller than that of the mean-state static stability, causing enhanced/reduced vertical motion.
Environmental conditions conducive to the formation of Multiple Tropical Cyclones over the Western North Pacific
Yining Gu, Ruifen Zhan, Xiaomeng Li
, Available online   , Manuscript accepted  25 March 2024, doi: 10.1007/s00376-024-3237-4
Limited understanding exists regarding the formation of multiple tropical cyclones (MTCs). This study explores the environmental conditions conductive to MTC formation by objectively determining the atmospheric circulation patterns favorable for MTC formation over the western North Pacific. Based on 199 MTC events occurring from June to October in 1980-2020, four distinct circulation patterns are identified: the monsoon trough (MT) pattern, accounting for 40.3% of occurrences, the confluence zone (CON) pattern at 26.2%, the easterly wave (EW) pattern at 17.8%, and the monsoon gyre (MG) pattern at 15.7%. The MT pattern mainly arises from the interaction between the subtropical high and the monsoon trough, with MTCs forming along the monsoon trough and its flanks. The CON pattern is affected by the subtropical high, the South Asian high and the monsoon trough, with MTCs emerging at the confluence zone where the prevailing southwesterly and southeasterly flows converge. The EW pattern is dominated by easterly flows, with MTCs developing along the easterly wave train. MTCs in the MG pattern arise within a monsoon vortex characterized by strong southwesterly flows. A quantitative analysis further indicates that MTC formation in the MT pattern is primarily governed by mid-level vertical velocity and low-level vorticity, while mid-level humidity and vertical velocity are significantly important in the other patterns. The meridional shear and convergence of zonal winds are important in converting barotropic energy from the basic flows to disturbance kinetic energy, acting as the primary source for eddy kinetic energy growth.
Distinct interannual variability and physical mechanisms of snowfall frequency over the Eurasian continent during autumn and winter
Siyu Zhou, Bo Sun, Huijun Wang, Yi Zheng, Jiarui Cai, Huixin Li, Botao Zhou
, Available online   , Manuscript accepted  25 March 2024, doi: 10.1007/s00376-024-3327-3
This study investigated the dominant modes of interannual variability of snowfall frequency over the Eurasian continent during autumn and winter, and explored the underlying physical mechanisms. The first EOF mode (EOF1) of snowfall frequency during autumn is mainly characterized by positive anomalies over Central Siberian plateau (CSP) and Europe, and the opposite over Central Asia (CA). EOF1 during winter is characterized by positive anomalies in Siberia and negative anomalies in Europe and East Asia (EA). During autumn, EOF1 is associated with the anomalous sea ice in the Kara–Laptev seas (KLS) and sea surface temperature (SST) over the North Atlantic. Increased sea ice in the KLS may cause increased meridional air temperature gradient resulting in increased synoptic–scale wave activity, thereby inducing increased snowfall frequency over Europe and CSP. Anomalous increased sea ice in the KLS and SST in North Atlantic may both stimulate downstream propagation of Rossby waves and induce anomalous high in CA corresponding to decreased snowfall frequency. In contrast, EOF1 is mainly affected by the anomalous atmospheric circulation during winter. In the positive phase of the North Atlantic Oscillation (NAO), anomalous deep cold low (warm high) occurs over Siberia (Europe), and hence increased (decreased) snowfall frequency over Siberia (Europe). The synoptic-scale wave activity excited by the positive NAO can induce Rossby wave propagating downstream and contribute to anomalous high and descending motion over EA, which may inhibit snowfall. The NAO in winter may be modulated by the Indian Ocean dipole and sea ice in Barents-Kara-Laptev Seas in autumn.
Numerical Study on the Impacts of Hydrometeor Processes on the “21.7” Extreme Rainfall in Zhengzhou Area of China
Wenhua GAO, Chengyin LI, Lanzhi TANG
, Available online   , Manuscript accepted  21 March 2024, doi: 10.1007/s00376-024-3365-x
The impacts of hydrometeor-related processes on the development and evolution of the “21.7” extremely heavy rainfall in Zhengzhou were investigated using WRF simulations. Surface precipitation was determined by the hydrometeor microphysical processes (all microphysical source sink terms of hydrometeors) and macrophysical processes (local change and flux convergence of hydrometeors). The contribution of hydrometeor macrophysical processes was commonly less than 10%, but could reach 30%–50% in the early stage of precipitation, which was largely dependent on the size of the study area. The macrophysical processes of liquid-phase hydrometeors always presented a promotional effect on rainfall, while the ice-phase hydrometeors played a negative role in the middle and later stages of precipitation. The distributions of microphysical latent heat corresponded well with those of buoyancy and vertical velocity (tendency), indicating that the phase-change heating was the major driver for convective development. Reasonable diagnostic buoyancy was obtained by choosing an area close to the convective size for getting the reference state of air. In addition, a new dynamic equilibrium involving hydrometeors with a tilted airflow was formed during the heavy precipitation period (updraft was not the strongest). The heaviest instantaneous precipitation was mainly produced by the warm-rain processes. Sensitivity experiments further pointed out that the uncertainty of latent heat parameterization (±20%) did not significantly affect the convective rainfall. While when the phase-change heating only altered the temperature tendency, its impact on precipitation was remarkable. The results of this study help to deepen our understanding of heavy rainfall mechanisms from the perspective of hydrometeor processes.
Four- to Six-Year Periodic Variation of Arctic Sea-Ice Extent and Its Three Main Driving Factors
Ping CHEN, Jinping ZHAO, Xiaoyu WANG
, Available online   , Manuscript accepted  18 March 2024, doi: 10.1007/s00376-024-3104-3
Besides the rapid retreating trend of Arctic sea-ice extent (SIE), this study found the most outstanding low-frequency variation of SIE to be a 4–6-year periodic variation. Using a clustering analysis algorithm, the SIE in most ice-covered regions was clustered into two special regions: Region-1 around the Barents Sea and Region-2 around the Canadian Basin, which were located on either side of the Arctic Transpolar Drift. Clear 4–6-year periodic variation in these two regions was identified using a novel method called “running linear fitting algorithm”. The rate of temporal variation of the Arctic SIE was related to three driving factors: the regional air temperature, the sea-ice areal flux across the Arctic Transpolar Drift, and the divergence of sea-ice drift. The 4–6-year periodic variation was found to have always been present since 1979, but the SIE responded to different factors under heavy and light ice conditions divided by the year 2005. The joint contribution of the three factors to SIE variation exceeded 83% and 59% in the two regions, respectively, remarkably reflecting their dynamic mechanism. It is proven that the process of El Niño–Southern Oscillation (ENSO) is closely associated with the three factors, being the fundamental source of the 4–6-year periodic variations of Arctic SIE.
Decadal Changes in Dry and Wet Heatwaves in Eastern China: Spatial Patterns and Risk Assessment
, Available online   , Manuscript accepted  18 March 2024, doi: 10.1007/s00376-024-3261-4
Under global warming, understanding the long-term variation in different types of heatwaves is vital for China’s preparedness against escalating heat stress. This study investigates dry and wet heatwave shifts in eastern China over recent decades. Spatial trend analysis displays pronounced warming in inland midlatitudes and the Yangtze River Valley, with increased humidity in coastal regions. EOF results indicate intensifying dry heatwaves in northern China, while the Yangtze River Valley sees more frequent dry heatwaves. On the other hand, Indochina and regions north of 25°N also experience intensified wet heatwaves, corresponding to regional humidity increases. Composite analysis is conducted based on different situations: strong, frequent dry or wet heatwaves. Strong dry heatwaves are influenced by anticyclonic circulations over northern China, accompanied by warming SST anomalies around the coastal midlatitudes of the western North Pacific (WNP). Frequent dry heatwaves are related to strong subsidence along with a strengthened subtropical high over the WNP. Strong and frequent wet heatwaves show an intensified Okhotsk high at higher latitudes in the lower troposphere, and a negative circumglobal teleconnection wave train pattern in the upper troposphere. Decaying El Niño SST patterns are observed in two kinds of wet heatwave and frequent dry heatwave years. Risk analysis indicates that El Niño events heighten the likelihood of these heatwaves in regions most at risk. As global warming continues, adapting and implementing mitigation strategies toward extreme heatwaves becomes crucial, especially for the aforementioned regions under significant heat stress.
Optimal Assimilation of Microwave Upper-Level Sounding Data in CMA-GFS
Changjiao DONG, Hao HU, Fuzhong WENG
, Available online   , Manuscript accepted  12 March 2024, doi: 10.1007/s00376-024-3323-7
Various approaches have been proposed to minimize the upper-level systematic biases in global numerical weather prediction (NWP) models by using satellite upper-air sounding channels as anchors. However, since the China Meteorological Administration Global Forecast System (CMA-GFS) has a model top near 0.1 hPa (60 km), the upper-level temperature bias may exceed 4 K near 1 hPa and further extend to 5 hPa. In this study, channels 12–14 of the Advanced Microwave Sounding Unit A (AMSU-A) onboard five satellites of NOAA and METOP, whose weighting function peaks range from 10 to 2 hPa are all used as anchor observations in CMA-GFS. It is shown that the new “Anchor” approach can effectively reduce the biases near the model top and their downward propagation in three-month assimilation cycles. The bias growth rate of simulated upper-level channel observations is reduced to ±0.001 K d–1, compared to –0.03 K d–1 derived from the current dynamic correction scheme. The relatively stable bias significantly improves the upper-level analysis field and leads to better global medium-range forecasts up to 10 days with significant reductions in the temperature and geopotential forecast error above 10 hPa.
Optical Modeling of Sea Salt Aerosols Using in situ Measured Size Distributions and the Impact of Larger Size Particles
Wushao LIN, Lei BI
, Available online   , Manuscript accepted  07 March 2024, doi: 10.1007/s00376-024-3351-3
Sea salt aerosols play a critical role in regulating the global climate through their interactions with solar radiation. The size distribution of these particles is crucial in determining their bulk optical properties. In this study, we analyzed in situ measured size distributions of sea salt aerosols from four field campaigns and used multi-mode lognormal size distributions to fit the data. We employed super-spheroids and coated super-spheroids to account for the particles’ non-sphericity, inhomogeneity, and hysteresis effect during the deliquescence and crystallization processes. To compute the single-scattering properties of sea salt aerosols, we used the state-of-the-art invariant imbedding T-matrix method, which allows us to obtain accurate optical properties for sea salt aerosols with a maximum volume-equivalent diameter of 12 μm at a wavelength of 532 nm. Our results demonstrated that the particle models developed in this study were successful in replicating both the measured depolarization and lidar ratios at various relative humidity (RH) levels. Importantly, we observed that large-size particles with diameters larger than 4 μm had a substantial impact on the optical properties of sea salt aerosols, which has not been accounted for in previous studies. Specifically, excluding particles with diameters larger than 4 μm led to underestimating the scattering and backscattering coefficients by 27%~38% and 43%~60%, respectively, for the ACE-Asia field campaign. Additionally, the depolarization ratios were underestimated by 0.15 within the 50%~70% RH range. These findings emphasize the necessity of considering large particle sizes for optical modeling of sea salt aerosols.
A New Merged Product Revealed Precipitation Features over Drylands in China
Min Luo, Yuzhi Liu, Jie Gao, Run Luo, Jinxia Zhang, Ziyuan Tan, Siyu Chen, Khan Alam
, Available online   , Manuscript accepted  06 March 2024, doi: 10.1007/s00376-024-3159-1
Due to the considerable uncertainties inherent in the datasets describing the spatiotemporal distributions of precipitation in the drylands of China, this study presents a new merged monthly precipitation product with a spatial resolution of approximately 0.2° × 0.2° (latitude × longitude) during the period of 1980–2019. The newly developed precipitation product was validated at different temporal scales (e.g., monthly, seasonally and annually). The results showed that the new product aligned consistently with the spatiotemporal distributions reported by the Chinese Meteorological Administration Land Data Assimilation System (CLDAS) product and Multi-Source Weighted Ensemble Precipitation (MSWEP). The merged product exhibited exceptional quality in describing the drylands of China, with a bias of -2.19 mm/month relative to MSWEP. In addition, the annual trend of the merged product (0.09 mm/month per year) also closely aligns with that of the MSWEP (0.11 mm/month per year) during 1980–2019. The increasing trend indicates that the water cycle and wetting process intensified in the drylands of China during this period. In particular, there was an increase in wetting during the period from 2001–2019. Generally, the merged product exhibits potential value for improving our understanding of the climate and water cycle in the drylands of China.
Regional Climate Damage Quantification and Its Impacts on Future Emission Pathways Using the RICE Model
Shili YANG, Wenjie DONG, Jieming CHOU, Yong ZHANG, Weixing ZHAO
, Available online   , Manuscript accepted  05 March 2024, doi: 10.1007/s00376-024-3193-z
This study quantified the regional damages resulting from temperature and sea level changes using the Regional Integrated of Climate and Economy (RICE) model, as well as the effects of enabling and disabling the climate impact module on future emission pathways. Results highlight varied damages depending on regional economic development and locations. Specifically, China and Africa could suffer the most serious comprehensive damages caused by temperature change and sea level rise, followed by India, other developing Asian countries (OthAsia), and other high-income countries (OHI). The comprehensive damage fractions for China and Africa are projected to be 15.1% and 12.5% of gross domestic product (GDP) in 2195, with corresponding cumulative damages of 124.0 trillion and 87.3 trillion United States dollars (USD) from 2005 to 2195, respectively. Meanwhile, the comprehensive damage fractions in Japan, Eurasia, and Russia are smaller and projected to be lower than 5.6% of GDP in 2195, with cumulative damages of 6.8 trillion, 4.2 trillion, and 3.3 trillion USD, respectively. Additionally, coastal regions like Africa, the European Union (EU), and OHI show comparable damages for sea level rise and temperature change. In China, however, sea level-induced damages are projected to exceed those from temperature changes. Moreover, this study indicates that switching the damage modules on or off affects the regional and global emission trajectories, but the magnitude is relatively small. By 2195, global emissions under the experiments with all of the damage modules switched off, only the sea level damage module switched on, and only the temperature damage module switched on, were 3.5%, 2.3% and 1.2% higher than those with all of the damage modules switched on, respectively.
Contrast of Secondary Organic Aerosols in the Present Day and the Preindustrial Period: the importance of nontraditional sources and the changed atmospheric oxidation capability.
yingchuan yang, Wenyi Yang, xueshun chen, Jiawen Zhu, huansheng chen, Wang Yuanlin, Wending Wang, Lianfang Wei, Ying Wei, Ye Qian, Huiyun Du, Wu Zichen, wang zhe, jie li, Xiaodong Zeng, Zifa Wang
, Available online   , Manuscript accepted  05 March 2024, doi: 10.1007/s00376-024-3281-0
Quantifying differences in secondary organic aerosols (SOAs) between the preindustrial period and the present day is crucial to assess climate forcing and environmental effects resulting from anthropogenic activities. The lack of vegetation information for the preindustrial period and the uncertainties in describing SOA formation are two leading factors preventing simulation of SOA. This study calculated the online emissions of biogenic volatile organic compound (VOC) in the Aerosol and Atmospheric Chemistry Model of Institute of Atmospheric Physics (IAP-AACM) by coupling the Model of Emissions of Gases and Aerosols from Nature, where the input vegetation parameters were simulated by the IAP Dynamic Global Vegetation Model (IAP-DGVM). The volatility basis set approach was adopted to simulate SOA formation from the nontraditional pathways, i.e., the oxidation of intermediate VOCs and aging of primary organic aerosol. Although biogenic SOAs (BSOAs) were dominant in SOAs globally in the preindustrial period, the contribution of nontraditional anthropogenic SOAs (ASOAs) to the total SOAs was up to 35.7%. In the present day, the contribution of ASOAs was 2.8 times larger than that in the preindustrial period. The contribution of nontraditional sources of SOAs to SOA was as high as 53.1%. The influence of increased anthropogenic emissions in the present day on BSOA concentrations was greater than that of increased biogenic emission changes. The response of BSOA concentrations to anthropogenic emission changes in the present day was more sensitive than that in the preindustrial period. The nontraditional sources and the atmospheric oxidation capability greatly affect the global SOA change
Wintertime Arctic Sea Ice Decline Related to Multi-Year La Niña Events
Wenxiu Zhong, Qian Shi, Jiping Liu, Qinghua Yang, Song Yang
, Available online   , Manuscript accepted  26 February 2024, doi: 10.1007/s00376-024-3194-y
Arctic sea ice has undergone a significant decline in the Barents–Kara Seas (BKS) since the late 1990s. Previous studies have shown that the decrease in sea ice caused by increased poleward moisture transport is modulated by tropical sea temperature changes (mainly referring to La Niña events). The occurrence of multi-year La Niña (MYLA) events has increased significantly in recent decades, and their impact on Arctic sea ice needs to be further explored. In this study, we investigate the relationship between sea ice variation and different atmospheric diagnostics during MYLA and other La Niña (OTLA) years. The decline in BKS sea ice during MYLA winters is significantly stronger than that during OTLA years. It is because the MYLA event tends to accompany the warm Arctic-cold continent pattern with a barotropic high-pressure blocked over the Ural region. Consequently, more frequent northward atmospheric rivers intrude into the BKS, intensifying long-wave radiation downward to the underlying surface and melting the BKS sea ice. However, in the early OTLA winter, negative North Atlantic Oscillation presents in the North Hemisphere high latitudes, which obstructs the atmospheric rivers to the south of Iceland. We infer that such a different response of BKS sea ice decline to different La Niña events is related to stratospheric processes. Under the climate change background, to a certain extent, the more frequent MYLA events account for substantial Arctic sea ice loss in recent decades.
Application of Conditional Nonlinear Local Lyapunov Exponent to the Second Kind Predictability
Ming ZHANG, Ruiqiang DING, Quanjia ZHONG, Jianping LI, Deyu LU
, Available online   , Manuscript accepted  18 February 2024, doi: 10.1007/s00376-024-3297-5
In order to quantify the influence of external forcings on the predictability limit using observational data, the author introduced an algorithm of the conditional nonlinear local Lyapunov exponent (CNLLE) method. The effectiveness of this algorithm is validated and compared with the nonlinear local Lyapunov exponent (NLLE) and signal-to-noise ratio (SNR) methods using a coupled Lorenz model. The results show that the CNLLE method is able to capture the slow error growth constrained by external forcings, as such, it can quantify the predictability limit induced by the external forcings. On this basis, a preliminary attempt was made to apply this method to measure the influence of ENSO on the predictability limit for both atmospheric and oceanic variable fields. The spatial distribution of predictability limit induced by ENSO is similar to that arising from the initial conditions calculated by the NLLE method. This similarity supports ENSO as the major predictable signal for weather and climate prediction. In addition, a ratio of predictability limit (RPL) calculated by the CNLLE method to that calculated by the NLLE method was proposed. The RPL larger than 1 indicates that the external forcings can significantly benefit the long-term predictability limit. For instance, ENSO can effectively extend the predictability limit arising from the initial conditions of sea surface temperature (SST) over the tropical Indian Ocean by approximately four months, as well as the predictability limit of sea level pressure (SLP) over the eastern and western Pacific Ocean. Moreover, the impact of ENSO on geopotential height (GHT) predictability limit is primarily confined to the troposphere.
Quantifying the Role of the Eddy Transfer Coefficient in Simulating the Response of the Southern Ocean Meridional Overturning Circulation to Enhanced Westerlies in a Coarse-resolution Model
Yiwen LI, Hailong LIU, Pengfei LIN, Eric P. CHASSIGNET, Zipeng YU, Fanghua WU
, Available online   , Manuscript accepted  18 February 2024, doi: 10.1007/s00376-024-3278-8
This study assesses the capability of a coarse-resolution ocean model to replicate the response of the Southern Ocean Meridional Overturning Circulation (MOC) to intensified westerlies, focusing on the role of the eddy transfer coefficient (\begin{document}$\kappa $\end{document}). \begin{document}$\kappa $\end{document} is a parameter commonly used to represent the velocities induced by unresolved eddies. Our findings reveal that a stratification-dependent \begin{document}$\kappa $\end{document}, incorporating spatiotemporal variability, leads to the most robust eddy-induced MOC response, capturing 82% of the reference eddy-resolving simulation. Decomposing the eddy-induced velocity into its vertical variation (VV) and spatial structure (SS) components unveils that the enhanced eddy compensation response primarily stems from an augmented SS term, while the introduced VV term weakens the response. Furthermore, the temporal variability of the stratification-dependent \begin{document}$\kappa $\end{document} emerges as a key factor in enhancing the eddy compensation response to intensified westerlies. The experiment with stratification-dependent \begin{document}$\kappa $\end{document} exhibits a more potent eddy compensation response compared to the constant \begin{document}$\kappa $\end{document}, attributed to the structure of \begin{document}$\kappa $\end{document} and the vertical variation of the density slope. These results underscore the critical role of accurately representing \begin{document}$\kappa $\end{document} in capturing the response of the Southern Ocean MOC and emphasize the significance of the isopycnal slope in modulating the eddy compensation mechanism.
Effects of Initial and Boundary Conditions on Heavy Rainfall Simulation over the Yellow Sea and the Korean Peninsula: Comparison of ECMWF and NCEP Analysis Data Effects and Verification with Dropsonde Observation
Jiwon HWANG, Dong-Hyun CHA, Donghyuck YOON, Tae-Young GOO, Sueng-Pil JUNG
, Available online   , Manuscript accepted  07 February 2024, doi: 10.1007/s00376-024-3232-9
This study evaluated the simulation performance of mesoscale convective system (MCS)-induced precipitation, focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula. The evaluation was conducted for the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP) analysis data, as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting model. Particularly, temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation data. Results showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis, which exhibited a cold and dry bias in the lower levels below 850 hPa. The model, in terms of the precipitation simulations, particularly for high-intensity precipitation over the Yellow Sea, demonstrated higher accuracy when applying ECMWF analysis data as the initial condition. This advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features (i.e., warm and humid lower-level atmosphere) over the Yellow Sea. In conclusion, this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation data. Furthermore, it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future.
Synergistic Impacts of Indian Ocean SST and Indo-China Peninsula Soil Moisture on the 2020 Record-breaking Mei-yu
Yinshuo DONG, Haishan CHEN, Xuan DONG, Wenjian HUA, Wenjun ZHANG
, Available online   , Manuscript accepted  05 February 2024, doi: 10.1007/s00376-024-3204-0
The Yangtze River basin (YRB) experienced a record-breaking mei-yu season in June‒July 2020. This unique long-lasting extreme event and its origin have attracted considerable attention. Previous studies have suggested that the Indian Ocean (IO) SST forcing and soil moisture anomaly over the Indochina Peninsula (ICP) were responsible for this unexpected event. However, the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event, especially their linkage with atmospheric circulation changes, remain unclear. By using observations and numerical simulations, this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020. Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds. The intensification of the warm condition further magnified the land thermal effects, which in turn facilitated the westward extension of the western North Pacific subtropical high (WNPSH) in June‒July. The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB, thereby contributing to the 2020 mei-yu. In contrast, the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture. The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model. Their synergistic impacts yield a notable 32% increase in YRB precipitation. Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.
The Predictability Limit of Oceanic Mesoscale Eddy Tracks in the South China Sea
Hailong LIU, Pingxiang Chu, Yao Meng, Mengrong DING, Pengfei LIN, Ruiqiang Ding, Pengfei Wang, Weipeng ZHENG
, Available online   , Manuscript accepted  01 February 2024, doi: 10.1007/s00376-024-3250-7
This study uses the nonlinear local Lyapunov exponent (NLLE) method to quantitatively estimate the predictability limit of oceanic mesoscale eddy (OME) tracks using three eddy datasets for both annual and seasonal mean. The results show that the predictability limit of OME tracks is about 39 days for cyclonic eddies (CEs) and 44 days for anticyclonic eddies (AEs) in the South China Sea (SCS). The predictability limit is related to the OME properties and seasons. The long-lived, large-amplitude, and -radius OMEs tend to have a higher predictability limit. The predictability limit of AE (CE) tracks is highest in autumn (winter) with 52 (53) days and lowest in spring (summer) with 40 (30) days. The spatial distribution of the predictability limit of OME tracks also varies with seasons, and we found that the higher predictability limits area often overlaps with periodic OMEs. Additionally, the predictability limit of periodic OME tracks is about 49 days for both CEs and AEs, which is 5-10 days higher than the mean values. Usually, in the SCS, OMEs with high predictability limit values often show extender and smoother trajectories and often move along the northern slope of SCS.
Refining the Factors Affecting N2O Emissions from Upland Soils with and without Nitrogen Fertilizer Application at a Global Scale
Wenqian JIANG, Siqi LI, Yong LI, Meihui WANG, Bo WANG, Ji LIU, Jianlin SHEN, Xunhua ZHENG
, Available online   , Manuscript accepted  01 February 2024, doi: 10.1007/s00376-024-3234-7
Nitrous oxide (N2O) is a long-lived greenhouse gas that mainly originates from agricultural soils. More and more studies have explored the sources, influencing factors and effective mitigation measures of N2O in recent decades. However, the hierarchy of factors influencing N2O emissions from agricultural soils at the global scale remains unclear. In this study, we carry out correlation and structural equation modeling analysis on a global N2O emission dataset to explore the hierarchy of influencing factors affecting N2O emissions from the nitrogen (N) and non-N fertilized upland farming systems, in terms of climatic factors, soil properties, and agricultural practices. Our results show that the average N2O emission intensity in the N fertilized soils (17.83 g N ha–1 d–1) was significantly greater than that in the non-N fertilized soils (5.34 g N ha−1 d−1) (p< 0.001). Climate factors and agricultural practices are the most important influencing factors on N2O emission in non-N and N fertilized upland soils, respectively. For different climatic zones, without fertilizer, the primary influence factors on soil N2O emissions are soil physical properties in subtropical monsoon zone, whereas climatic factors are key in the temperate zones. With fertilizer, the primary influence factors for subtropical monsoon and temperate continental zones are soil physical properties, while agricultural measures are the main factors in the temperate monsoon zone. Deploying enhanced agricultural practices, such as reduced N fertilizer rate combined with the addition of nitrification and urease inhibitors can potentially mitigate N2O emissions by more than 60% in upland farming systems.
Microphysical Characteristics of Rainfall Based on Long-Term Observations with 2DVD in Yangbajing, Tibet
Ming LI, Yongheng BI, Yonghai SHEN, Yinan Wang, Ciren Nima, Tianlu CHEN, Daren Lu
, Available online   , Manuscript accepted  23 January 2024, doi: 10.1007/s00376-024-3299-3
Raindrop size distribution (DSD) plays a crucial role in enhancing the accuracy of radar quantitative precipitation estimation in the Tibetan Plateau (TP). However, there is a notable scarcity of long-term, high-resolution observations in this region. To address this issue, long-term observations from a two-dimensional video disdrometer (2DVD) were leveraged to refine the radar and satellite-based algorithms for quantifying precipitation in the hinterland of the TP. It was observed that weak precipitation (R < 1 mm h-1) accounts for 86% of the total precipitation time, while small raindrops (D < 2 mm) comprise 99% of the total raindrop count. Furthermore, the average spectral width of the DSD increases with increasing rain rate. The DSD characteristics of convective and stratiform precipitation were discussed across five different rain rates, revealing that convective precipitation in the Yangbajing (YBJ) exhibits characteristics similar to maritime-like precipitation. The constrained relations between the slope Λ and μ, and of gamma DSDs were derived. Additionally, we establish a correlation between the equivalent diameter and drop axis ratio found that raindrops on the TP are closer to spherical shapes. Lastly, the application of the rainfall retrieval algorithms of the dual-frequency precipitation radar in the TP is improved based on the statistical results of the DSD.
Spatiotemporal Variability and Environmental Controls of Temperature Sensitivity of Ecosystem Respiration Across the Tibetan Plateau
Danrui SHENG, Xianhong MENG, Shaoying WANG, Zhaoguo LI, Lunyu SHANG, Hao CHEN, Lin ZHAO, Mingshan DENG, Hanlin NIU, Pengfei XU, Xiaohu WEN
, Available online   , Manuscript accepted  08 January 2024, doi: 10.1007/s00376-024-3167-1
Warming-induced carbon loss via ecosystem respiration (Re) is probably intensifying in the alpine grassland ecosystem of the Tibetan Plateau owing to more accelerated warming and the higher temperature sensitivity of Re (Q10). However, little is known about the patterns and controlling factors of Q10 on the plateau, impeding the comprehension of the intensity of terrestrial carbon–climate feedbacks for these sensitive and vulnerable ecosystems. Here, we synthesized and analyzed multiyear observations from 14 sites to systematically compare the spatiotemporal variations of Q10 values in diverse climate zones and ecosystems, and further explore the relationships between Q10 and environmental factors. Moreover, structural equation modeling was utilized to identify the direct and indirect factors predicting Q10 values during the annual, growing, and non-growing seasons. The results indicated that the estimated Q10 values were strongly dependent on temperature, generally, with the average Q10 during different time periods increasing with air temperature and soil temperature at different measurement depths (5 cm, 10 cm, 20 cm). The Q10 values differentiated among ecosystems and climatic zones, with warming-induced Q10 declines being stronger in colder regions than elsewhere based on spatial patterns. NDVI was the most cardinal factor in predicting annual Q10 values, significantly and positively correlated with Q10. Soil temperature (Ts) was identified as the other powerful predictor for Q10, and the negative Q10Ts relationship demonstrates a larger terrestrial carbon loss potentiality in colder than in warmer regions in response to global warming. Note that the interpretations of the effect of soil moisture on Q10 were complicated, reflected in a significant positive relationship between Q10 and soil moisture during the growing season and a strong quadratic correlation between the two during the annual and non-growing season. These findings are conducive to improving our understanding of alpine grassland ecosystem carbon–climate feedbacks under warming climates.
Different ENSO Impacts on Eastern China Precipitation Patterns in Early and Late Winter Associated with Seasonally-Varying Kuroshio Anticyclonic Anomalies
Jingrui YAN, Wenjun ZHANG, Suqiong HU, Feng JIANG
, Available online   , Manuscript accepted  04 January 2024, doi: 10.1007/s00376-023-3196-1
Winter precipitation over eastern China displays remarkable interannual variability, which has been suggested to be closely related to El Niño–Southern Oscillation (ENSO). This study finds that ENSO impacts on eastern China precipitation patterns exhibit obvious differences in early (November–December) and late (January–February) winter. In early winter, precipitation anomalies associated with ENSO are characterized by a monopole spatial distribution over eastern China. In contrast, the precipitation anomaly pattern in late winter remarkably changes, manifesting as a dipole spatial distribution. The noteworthy change in precipitation responses from early to late winter can be largely attributed to the seasonally varying Kuroshio anticyclonic anomalies. During the early winter of El Niño years, anticyclonic circulation anomalies appear both over the Philippine Sea and Kuroshio region, enhancing water vapor transport to the entirety of eastern China, thus contributing to more precipitation there. During the late winter of El Niño years, the anticyclone over the Philippine Sea is further strengthened, while the one over the Kuroshio dissipates, which could result in differing water vapor transport between northern and southern parts of eastern China and thus a dipole precipitation distribution. Roughly the opposite anomalies of circulation and precipitation are displayed during La Niña winters. Further analysis suggests that the seasonally-varying Kuroshio anticyclonic anomalies are possibly related to the enhancement of ENSO-related tropical central-eastern Pacific convection from early to late winter. These results have important implications for the seasonal-to-interannual predictability of winter precipitation over eastern China.
Future changes in various cold surges over China in CMIP6 projection
Li Ma, Zhigang Wei, Xianru Li, Shuting Wu
, Available online   , Manuscript accepted  03 January 2024, doi: 10.1007/s00376-023-3220-5
Cold surges (CSs) often occur in the mid-latitude regions of the Northern Hemisphere and have enormous effects on socioeconomic development. We report that the occurrences of CSs and persistent CSs (PCSs) have rebounded since the 1990s, but the frequencies of strong CSs (SCSs) and extreme CSs (ECSs) changed from increasing to decreasing trends after 2000. The highest-ranked model ensemble approach was used to project the occurrences of various CSs under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. The frequencies of the total CSs showed overall decreasing trends. However, under the SSP1-2.6 scenario, SCSs and ECSs showed slight increasing trends in China. The anomalous anticyclonic circulation with a significant positive anomaly of 500 hPa geopotential height (Z500) at high latitudes and significant negative anomalies in China were favourable for the intrusion of cold air into China. In addition, the frequencies of all CS types under the SPP5-8.5 scenario greatly decreased in the long term (2071-2100), which was related to the negative anomalies in the sea surface temperature (SST) in central and western North Pacific, differences in sea level pressure (SLP) between high- and mid-latitude regions, and a weaker East Asian trough. In terms of ECSs, the decreasing trends observed in the historical period were maintained until 2024 under the SSP1-2.6 scenario. Compared to the SSP1-2.6 scenario, Z500 showed trends of strengthening ridges over the Ural region and northern East Asia and weakening ridges over Siberia under the SSP2-4.5 and SSP5-8.5 scenarios, contributing to the shift to increasing trends of ECSs after 2014
The Global Energy and Water Exchanges Project in Central Asia; The Case for a Regional Hydroclimate Project
Michael Brody, Maksim Kulikov, Sagynbek Orumbaev, Peter van Oevelen
, Available online   , Manuscript accepted  02 January 2024, doi: 10.1007/s00376-023-3384-z
Central Asia consists of the former Soviet Republics, Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan. The region’s climate is continental, mostly semi-arid to arid. Agriculture is a significant part of the region’s economy. By its nature of intensive water use, agriculture is extremely vulnerable to climate change. Population growth and irrigation development have significantly increased the demand for water in the region. Major climate change issues include melting glaciers and shrinking snowpack that are the foundation of the region’s water resources and a changing precipitation regime. Most glaciers are located in Kyrgyzstan and Tajikistan, leading to transboundary water resource issues. Summer already has extremely high temperatures. Analyses indicate that Central Asia has been warming and precipitation might be increasing. The warming is expected to increase, but its spatial and temporal distribution depends upon specific global scenarios. Forecasts of future precipitation show significant uncertainties in type, amount, and distribution. Regional Hydroclimate Projects (RHP) are an approach to studying these issues. Initial steps to develop a RHP began in 2021 with a widely distributed online survey about these climate issues. It was followed up with an online workshop and then in 2023, an in-person workshop, held in Tashkent, Uzbekistan. Priorities for GEWEX for the region include both observations and modeling, development of better and additional precipitation observations, all topics of the next workshop. A well-designed RHP should lead to reductions in critical climate uncertainties in policy relevant time frames that can influence decisions on necessary investments in climate adaptation.
Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during Monsoon Season. Part II: Numerical Experiments
Lanqiang BAI, Dan YAO, Zhiyong MENG, Yu ZHANG, Xianxiang HUANG, Zhaoming LI
, Available online   , Manuscript accepted  27 December 2023, doi: 10.1007/s00376-023-3096-4
As demonstrated in the first part of this study (Part I), wind-shift boundaries routinely form along the west coast of the Pearl River Delta due to the land–sea contrast of a “trumpet” shape coastline in the summer monsoon season. Through multiple numerical simulations, this article (Part II) aims to examine the roles of the trumpet-shaped coastline in the mesovortex genesis during the 1 June 2020 tornadic event. The modeling reproduced two mesovortices that are in close proximity in time and space to the realistic mesovortices. In addition to the modeled mesovortex over the triple point where strong ambient vertical vorticity was located, another mesovortex originated from an enhanced discrete vortex along an airmass boundary via shear instability. On the fine-scale storm morphology, finger-like echoes preceding hook echoes were also reproduced around the triple point. Results from sensitivity experiments suggest that the unique topography plays an essential role in modifying the vorticity budget during the mesovortex formation. While there is a high likelihood of an upcoming storm evolving into a rotating storm over the triple point, the simulation's accuracy is sensitive to the local environmental details and storm dynamics. The strengths of cold pool surges from upstream storms may influence the stretching of low-level vertically oriented vortex and thus the wrap-up of finger-like echoes. These findings suggest that the trumpet-shaped coastline is an important component of mesovortex production during the active monsoon season. It is hoped that this study will increase the situational awareness for forecasters regarding regional non-mesocyclone tornadic environments.
The Performance of Downward Shortwave Radiation Products from Satellite and Reanalysis over the Transect of Zhongshan Station to Dome A, East Antarctica
Jiajia JIA, Zhaoliang ZENG, Wenqian ZHANG, Xiangdong ZHENG, Yaqiang WANG, Minghu DING
, Available online   , Manuscript accepted  27 December 2023, doi: 10.1007/s00376-023-3136-0
The downward shortwave radiation (DSR) is an important part of the Earth's energy balance, driving Earth's system's energy, water, and carbon cycles. Due to the harsh Antarctic environment, the accuracy of DSR derived from satellite and reanalysis has not been systematically evaluated over the transect of Zhongshan station to Dome A, East Antarctica. Therefore, this study aims to evaluate DSR reanalysis products (ERA5-Land, ERA5, MERRA-2) and satellite products (CERES and ICDR) in this area. The results indicate that DSR exhibits obvious monthly and seasonal variations, with higher values in summer than in winter. The ERA5-Land (ICDR) DSR product demonstrated the highest (lowest) accuracy, as evidenced by a correlation coefficient of 0.988 (0.918), a root-mean-square error of 23.919 (69.383) W m–2, a mean bias of –1.667 (–28.223) W m–2 and a mean absolute error of 13.37 (58.99) W m–2. The RMSE values for the ERA5-Land reanalysis product at seven stations, namely Zhongshan, Panda 100, Panda 300, Panda 400, Taishan, Panda 1100, and Kunlun, were 30.938, 29.447, 34.507, 29.110, 20.339, 17.267, and 14.700 W m–2, respectively; with corresponding bias values of 9.887, –12.159, –19.181, –15.519, –8.118, 6.297, and 3.482 W m–2. Regarding seasonality, ERA5-Land, ERA5, and MERRA-2 reanalysis products demonstrate higher accuracies during spring and summer, while ICDR products are least accurate in autumn. Cloud cover, water vapor, total ozone, and severe weather are the main factors affecting DSR. The error of DSR products is greatest in coastal areas (particularly at the Zhongshan station) and decreases towards the inland areas of Antarctica.
Spatial Variation in CO2 Concentration Improves the Simulated Surface Air Temperature Increase in the Northern Hemisphere
Jing PENG, Li DAN, Xiba TANG
, Available online   , Manuscript accepted  20 December 2023, doi: 10.1007/s00376-023-3249-5
The increasing concentration of atmospheric CO2 since the Industrial Revolution has affected surface air temperature. However, the impact of the spatial distribution of atmospheric CO2 concentration on surface air temperature biases remains highly unclear. By incorporating the spatial distribution of satellite-derived atmospheric CO2 concentration in the Beijing Normal University Earth System Model, this study investigated the increase in surface air temperature since the Industrial Revolution in the Northern Hemisphere (NH) under historical conditions from 1976–2005. In comparison with the increase in surface temperature simulated using a uniform distribution of CO2, simulation with a nonuniform distribution of CO2 produced better agreement with the Climatic Research Unit (CRU) data in the NH under the historical condition relative to the baseline over the period 1901–30. Hemispheric June–July–August (JJA) surface air temperature increased by 1.28°C ± 0.29°C in simulations with a uniform distribution of CO2, by 1.00°C ± 0.24°C in simulations with a non-uniform distribution of CO2, and by 0.24°C in the CRU data. The decrease in downward shortwave radiation in the non-uniform CO2 simulation was primarily attributable to reduced warming in Eurasia, combined with feedbacks resulting from increased leaf area index (LAI) and latent heat fluxes. These effects were more pronounced in the non-uniform CO2 simulation compared to the uniform CO2 simulation. Results indicate that consideration of the spatial distribution of CO2 concentration can reduce the overestimated increase in surface air temperature simulated by Earth system models.
Differences in Precipitation and Related Wind Dynamics and Moisture and Heat Features in Separate Areas of the South China Sea before and after Summer Monsoon Onset
Chunyan ZHANG, Donghai WANG, Kaifeng ZHANG, Wanwen HE, Yanping ZHENG, Yan XU
, Available online   , Manuscript accepted  18 December 2023, doi: 10.1007/s00376-023-3141-3
Using surface and balloon-sounding measurements, satellite retrievals, and ERA5 reanalysis during 2011–20, this study compares the precipitation and related wind dynamics, moisture and heat features in different areas of the South China Sea (SCS) before and after SCS summer monsoon onset (SCSSMO). The rainy sea around Dongsha (hereafter simply referred to as Dongsha) near the north coast, and the rainless sea around Xisha (hereafter simply referred to as Xisha) in the western SCS, are selected as two typical research subregions. It is found that Dongsha, rather than Xisha, has an earlier and greater increase in precipitation after SCSSMO under the combined effect of strong low-level southwesterly winds, coastal terrain blocking and lifting, and northern cold air. When the 950-hPa southwesterly winds enhance and advance northward, accompanied by strengthened moisture flux, there is a strong convergence of wind and moisture in Dongsha due to a sudden deceleration and rear-end collision of wind by coastal terrain blocking. Moist and warm advection over Dongsha enhances early and deepens up to 200 hPa in association with the strengthened upward motion after SCSSMO, thereby providing ample moisture and heat to form strong precipitation. However, when the 950-hPa southwesterly winds weaken and retreat southward, Xisha is located in a wind-break area where strong convergence and upward motion centers move in. The vertical moistening and heating by advection in Xisha enhance later and appear far weaker compared to that in Dongsha, consistent with later and weaker precipitation.
The Forecast Skills and Predictability Sources of Marine Heatwaves in the NUIST-CFS1.0 Hindcasts
Jing MA, Haiming XU, Changming DONG, Jing-Jia LUO
, Available online   , Manuscript accepted  18 December 2023, doi: 10.1007/s00376-023-3139-x
Using monthly observations and ensemble hindcasts of the Nanjing University of Information Science and Technology Climate Forecast System (NUIST-CFS1.0) for the period 1983–2020, this study investigates the forecast skill of marine heatwaves (MHWs) over the globe and the predictability sources of the MHWs over the tropical oceans. The MHW forecasts are demonstrated to be skillful on seasonal-annual time scales, particularly in tropical oceans. The forecast skill of the MHWs over the tropical Pacific Ocean (TPO) remains high at lead times of 1–24 months, indicating a forecast better than random chance for up to two years. The forecast skill is subject to the spring predictability barrier of El Niño-Southern Oscillation (ENSO). The forecast skills for the MHWs over the tropical Indian Ocean (TIO), tropical Atlantic Ocean (TAO), and tropical Northwest Pacific (NWP) are lower than that in the TPO. A reliable forecast at lead times of up to two years is shown over the TIO, while a shorter reliable forecast window (less than 17 months) occurs for the TAO and NWP. Additionally, the forecast skills for the TIO, TAO, and NWP are seasonally dependent. Higher skills for the TIO and TAO appear in boreal spring, while a greater skill for the NWP emerges in late summer-early autumn. Further analyses suggest that ENSO serves as a critical source of predictability for MHWs over the TIO and TAO in spring and MHWs over the NWP in summer.
Large Eddy Simulation of Vertical Structure and Size Density of Deep Layer Clouds
Bangjun CAO, Xianyu YANG, Jun WEN, Qin HU, Ziyuan ZHU
, Available online   , Manuscript accepted  11 December 2023, doi: 10.1007/s00376-023-3134-2
In a convective scheme featuring a discretized cloud size density, the assumed lateral mixing rate is inversely proportional to the exponential coefficient of plume size. This follows a typical assumption of −1, but it has unveiled inherent uncertainties, especially for deep layer clouds. Addressing this knowledge gap, we conducted comprehensive large eddy simulations and comparative analyses focused on terrestrial regions. Our investigation revealed that cloud formation adheres to the tenets of Bernoulli trials, illustrating power-law scaling that remains consistent regardless of the inherent deep layer cloud attributes existing between cloud size and the number of clouds. This scaling paradigm encompasses liquid, ice, and mixed phases in deep layer clouds. The exponent characterizing the interplay between cloud scale and number in the deep layer cloud, specifically for liquid, ice, or mixed-phase clouds, resembles that of shallow convection, but converges closely to zero. This convergence signifies a propensity for diminished cloud numbers and sizes within deep layer clouds. Notably, the infusion of abundant moisture and the release of latent heat by condensation within the lower atmospheric strata make substantial contributions. However, this role in ice phase formation is limited. The emergence of liquid and ice phases in deep layer clouds is facilitated by the latent heat and influenced by the wind shear inherent in the middle levels. These interrelationships hold potential applications in formulating parameterizations and post-processing model outcomes.
Improving the Short-Range Precipitation Forecast of Numerical Weather Prediction Through a Deep Learning-Based Mask Approach
Jiaqi ZHENG, Qing LING, Jia LI, Yerong FENG
, Available online   , Manuscript accepted  06 December 2023, doi: 10.1007/s00376-023-3085-7
Due to various technical issues, existing numerical weather prediction (NWP) models often perform poorly at forecasting rainfall in the first several hours. To correct the bias of an NWP model and improve the accuracy of short-range precipitation forecasting, we propose a deep learning-based approach called UNetMask, which combines NWP forecasts with the output of a convolutional neural network called UNet. The UNetMask involves training the UNet on historical data from the NWP model and gridded rainfall observations for 6-hour precipitation forecasting. The overlap of the UNet output and the NWP forecasts at the same rainfall threshold yields a mask. The UNetMask blends the UNet output and the NWP forecasts by taking the maximum between them and passing through the mask, which provides the corrected 6-hour rainfall forecasts. We evaluated UNetMask on a test set and in real-time verification. The results showed that UNetMask outperforms the NWP model in 6-hour precipitation prediction by reducing the FAR and improving CSI scores. Sensitivity tests also showed that different small rainfall thresholds applied to the UNet and the NWP model have different effects on UNetMask's forecast performance. This study shows that UNetMask is a promising approach for improving rainfall forecasting of NWP models.
Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir based on Triple-Nested Dynamical Downscaling
Yanxin ZHENG, Shuanglin LI, Noel KEENLYSIDE, Shengping HE, Lingling SUO
, Available online   , Manuscript accepted  07 September 2023, doi: 10.1007/s00376-023-3118-2
Spring consecutive rainfall events (CREs) are key triggers of geological hazards in the Three Gorges Reservoir area (TGR), China. However, previous projections of CREs based on the direct outputs of global climate models (GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF (Weather Research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6 (Model for Interdisciplinary Research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6, indicating larger uncertainties in the CREs projected by MIROC6.
Relative Impacts of Sea Ice Loss and Atmospheric Internal Variability on the Winter Arctic to East Asian Surface Air Temperature Based on Large-Ensemble Simulations with NorESM2
Shengping HE, Helge DRANGE, Tore FUREVIK, Huijun WANG, Ke FAN, Lise Seland GRAFF, Yvan J. ORSOLINI
, Available online   , Manuscript accepted  21 June 2023, doi: 10.1007/s00376-023-3006-9
To quantify the relative contributions of Arctic sea ice and unforced atmospheric internal variability to the “warm Arctic, cold East Asia” (WACE) teleconnection, this study analyses three sets of large-ensemble simulations carried out by the Norwegian Earth System Model with a coupled atmosphere–land surface model, forced by seasonal sea ice conditions from preindustrial, present-day, and future periods. Each ensemble member within the same set uses the same forcing but with small perturbations to the atmospheric initial state. Hence, the difference between the present-day (or future) ensemble mean and the preindustrial ensemble mean provides the ice-loss-induced response, while the difference of the individual members within the present-day (or future) set is the effect of atmospheric internal variability. Results indicate that both present-day and future sea ice loss can force a negative phase of the Arctic Oscillation with a WACE pattern in winter. The magnitude of ice-induced Arctic warming is over four (ten) times larger than the ice-induced East Asian cooling in the present-day (future) experiment; the latter having a magnitude that is about 30% of the observed cooling. Sea ice loss contributes about 60% (80%) to the Arctic winter warming in the present-day (future) experiment. Atmospheric internal variability can also induce a WACE pattern with comparable magnitudes between the Arctic and East Asia. Ice-loss-induced East Asian cooling can easily be masked by atmospheric internal variability effects because random atmospheric internal variability may induce a larger magnitude warming. The observed WACE pattern occurs as a result of both Arctic sea ice loss and atmospheric internal variability, with the former dominating Arctic warming and the latter dominating East Asian cooling.
The Role of Underlying Boundary Forcing in Shaping the Recent Decadal Change of Persistent Anomalous Activity over the Ural Mountains
Ting LEI, Shuanglin LI
, Available online   , Manuscript accepted  21 June 2023, doi: 10.1007/s00376-023-2365-6
Observational analyses demonstrate that the Ural persistent positive height anomaly event (PAE) experienced a decadal increase around the year 2000, exhibiting a southward displacement afterward. These decadal variations are related to a large-scale circulation shift over the Eurasian Continent. The effects of underlying sea ice and sea surface temperature (SST) anomalies on the Ural PAE and the related atmospheric circulation were explored by Atmospheric Model Intercomparison Project (AMIP) experiments from the Coupled Model Intercomparison Project Phase 6 and by sensitivity experiments using the Atmospheric General Circulation Model (AGCM). The AMIP experiment results suggest that the underlying sea ice and SST anomalies play important roles. The individual contributions of sea ice loss in the Barents-Kara Seas and the SST anomalies linked to the phase transition of the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) are further investigated by AGCM sensitivity experiments isolating the respective forcings. The sea ice decline in Barents-Kara Seas triggers an atmospheric wave train over the Eurasian mid-to-high latitudes with positive anomalies over the Urals, favoring the occurrence of Ural PAEs. The shift in the PDO to its negative phase triggers a wave train propagating downstream from the North Pacific. One positive anomaly lobe of the wave train is located over the Ural Mountains and increases the PAE there. The negative-to-positive transition of the AMO phase since the late-1990s causes positive 500-hPa height anomalies south of the Ural Mountains, which promote a southward shift of Ural PAE.
Time-lagged Effects of the Spring Atmospheric Heat Source over the Tibetan Plateau on Summer Precipitation in Northeast China during 1961–2020: Role of Soil Moisture
Yizhe HAN, Dabang JIANG, Dong SI, Yaoming MA, Weiqiang MA
, Available online   , Manuscript accepted  21 June 2023, doi: 10.1007/s00376-023-2363-8
The spring atmospheric heat source (AHS) over the Tibetan Plateau (TP) has been suggested to affect the Asian summer monsoon and summer precipitation over South China. However, its influence on the summer precipitation in Northeast China (NEC) remains unknown. The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study. Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation, and higher soil moisture in the Yellow River Valley‒North China region (YRVNC) acts as a bridge. During spring, the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC. Thus, soil moisture increases, which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat. Owing to the memory of soil moisture, the lower spring sensible heat over the YRVNC can last until mid-summer, decrease the land–sea thermal contrast, and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific. This modulates the East Asia–Pacific teleconnection pattern, which leads to a cyclonic anomaly and excessive summer precipitation over NEC.
Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence
Jiazhen ZHAO, Shengping HE, Ke FAN, Huijun WANG, Fei LI
, Available online   , Manuscript accepted  06 May 2023, doi: 10.1007/s00376-023-2393-2
Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice, changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project (CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models’ performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario. Thereafter, it may decrease (or remain stable) if the Arctic warming crosses a threshold (or is extensively constrained).
The asymmetric connection of SST in the Tasman Sea with respect to the opposite phases of ENSO in austral summer
Xueqian Sun, Shuanglin Li, Stefan Liess
, Available online   , Manuscript accepted  11 February 2022, doi: 10.1007/s00376-022-0421-y
Using linear regression and composite analyses, this study identifies a pronounced asymmetric connection of sea surface temperature (SST) in the Tasman Sea with the two opposite phases of El Niño-Southern Oscillation (ENSO) during austral summer. In El Niño years, the SST anomalies (SSTAs) in the Tasman Sea exhibit a dipolar pattern with weak warmth in the northwest and modest cooling in the southeast, while during La Niña years the SSTAs exhibit a basin-scale warmth with greater amplitude. Investigations on the underlying mechanism suggest that this asymmetry arises from the oceanic heat transport, especially the anomalous Ekman meridional heat fluxes induced by the zonal wind stress anomalies, rather than the surface heat fluxes on the air-sea interface. A further analysis demonstrates that the asymmetry of oceanic heat transport between El Niño and La Niña years is driven by the asymmetric atmospheric circulation over the Tasman Sea stimulated by the asymmetric diabatic heating in the tropical Pacific between the two opposite ENSO phases.
Effect of the vertical diffusion of moisture in the planetary boundary layer on an idealized tropical cyclone
Hongxiong Xu, Dajun Zhao
, Available online   , Manuscript accepted  01 June 2021, doi:
Previous numerical studies have focused on the combined effect of momentum and scalar eddy diffusivity on the intensity and structure of tropical cyclones. The separate impact of each eddy diffusivity estimated by planetary boundary layer (PBL) parameterization on the tropical cyclones has not yet been systematically examined. We therefore examined the separate impacts of moisture eddy diffusion on idealized tropical cyclones using Advanced Research Weather Research and Forecasting model with the Yonsei University PBL scheme. Our results show nonlinear effects of moisture eddy diffusivity on the simulation of idealized tropical cyclones. Increasing the moisture eddy diffusion increases the moisture content of the PBL, with three different effects on tropical cyclones: (1) an increase in the depth of the PBL; (2) an increase in convection in the inner rain band and eyewall; (3) drying of the lowest region of the PBL and then increasing the surface latent heat flux. These three processes have different effects on the intensity and structure of the tropical cyclone through various physical mechanisms. The increased surface latent heat flux is mainly responsible for the decrease in pressure. Results show that moisture eddy diffusivity has clear effects on the pressure in tropical cyclones, but contributes little to the wind intensity. This largely influences the wind–pressure relationship, which is crucial in tropical cyclones simulation. These results improve our understanding of moisture eddy diffusivity in the PBL and its influence on tropical cyclones and provides guidance for interpreting the variation of the PBL moisture in tropical cyclone simulations.
Estimations of Land Surface Characteristic Parameters and Turbulent Heat Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data
Nan GE, Lei ZHONG, Yaoming MA, Yunfei FU, Mijun ZOU, Meilin CHENG, Xian WANG, Ziyu HUANG
, Available online   , Manuscript accepted  10 November 2020, doi: 10.1007/s00376-020-0169-5
Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land–atmosphere interaction. In this study, Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) satellite data and the China Land Data Assimilation System (CLDAS) meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo, land surface temperature (LST), radiation flux components, and turbulent heat fluxes over the Tibetan Plateau (TP). The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP. The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves—one for developing retrieval algorithms for broadband albedo and LST based on FY-4A, and the other for the cross validation. Results show the root-mean-square errors (RMSEs) of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K, respectively, which verifies the applicability of the retrieval method. The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m−2 and 51.55/17.92 W m−2, respectively, and the RMSEs of net radiation flux, sensible heat flux, and latent heat flux were 58.88 W m−2, 82.56 W m−2 and 72.46 W m−2, respectively. The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail.
News & Views
Extreme Antarctic Cold of Late Winter 2023
, Available online   , Manuscript accepted  16 May 2024, doi: 10.1007/s00376-024-4139-1
Extreme cold temperatures were observed in July and August 2023, coinciding with the WINFLY (winter fly-in) period of mid to late August into September 2023, meaning aircraft operations into McMurdo Station and Phoenix Airfield were adversely impacted. Specifically, with temperatures below −50°C, safe flight operation was not possible because of the risk of failing hydraulics and fuel turning to gel onboard the aircraft. The cold temperatures were measured across a broad area of the Antarctic, from East Antarctica toward the Ross Ice Shelf, and stretching across West Antarctica to the Antarctic Peninsula. A review of automatic weather station measurements and staffed station observations revealed a series of sites recording new record low temperatures. Four separate cold phases were identified, each a few days in duration and occurring from mid-July to the end of August 2023. A brief analysis of 500-hPa geopotential height anomalies shows how the mid-tropospheric atmospheric environment evolves in relation to these extreme cold temperatures. The monthly 500-hPa geopotential height anomalies show strong negative anomalies in August. Examination of composite geopotential height anomalies during each of the four cold phases suggests various factors leading to cold temperatures, including both southerly off-content flow and calm atmospheric conditions. Understanding the atmospheric environment that leads to such extreme cold temperatures can improve prediction of such events and benefit Antarctic operations and the study of Antarctic meteorology and climatology.
A Newly Established Air Pollution Data Center in China
Mei ZHENG, Tianle ZHANG, Yaxin XIANG, Xiao TANG, Yinan WANG, Guannan GENG, Yuying WANG, Yingjun LIU, Chunxiang YE, Caiqing YAN, Yingjun CHEN, Jiang ZHU, Qiang ZHANG, Tong ZHU
, Available online   , Manuscript accepted  08 April 2024, doi: 10.1007/s00376-024-4055-4
Air pollution in China covers a large area with complex sources and formation mechanisms, making it a unique place to conduct air pollution and atmospheric chemistry research. The National Natural Science Foundation of China’s Major Research Plan entitled “Fundamental Researches on the Formation and Response Mechanism of the Air Pollution Complex in China” (or the Plan) has funded 76 research projects to explore the causes of air pollution in China, and the key processes of air pollution in atmospheric physics and atmospheric chemistry. In order to summarize the abundant data from the Plan and exhibit the long-term impacts domestically and internationally, an integration project is responsible for collecting the various types of data generated by the 76 projects of the Plan. This project has classified and integrated these data, forming eight categories containing 258 datasets and 15 technical reports in total. The integration project has led to the successful establishment of the China Air Pollution Data Center (CAPDC) platform, providing storage, retrieval, and download services for the eight categories. This platform has distinct features including data visualization, related project information querying, and bilingual services in both English and Chinese, which allows for rapid searching and downloading of data and provides a solid foundation of data and support for future related research. Air pollution control in China, especially in the past decade, is undeniably a global exemplar, and this data center is the first in China to focus on research into the country’s air pollution complex.
Deep Learning Shows Promise for Seasonal Prediction of Antarctic Sea Ice in a Rapid Decline Scenario
Xiaoran DONG, Yafei NIE, Jinfei WANG, Hao LUO, Yuchun GAO, Yun WANG, Jiping LIU, Dake CHEN, Qinghua YANG
, Available online   , Manuscript accepted  25 January 2024, doi: 10.1007/s00376-024-3380-y
The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South’s latest call, this study presents the reforecast results of Antarctic sea-ice area and extent from December to June of the coming year with a Convolutional Long Short-Term Memory (ConvLSTM) Network. The reforecast experiments demonstrate that ConvLSTM captures the interannual and interseasonal variability of Antarctic sea ice successfully, and performs better than the European Centre for Medium-Range Weather Forecasts. Based on this, we present the prediction from December 2023 to June 2024, indicating that the Antarctic sea ice will remain at lows, but may not create a new record low. This research highlights the promising application of deep learning in Antarctic sea-ice prediction.
Recent Ventures in Interdisciplinary Arctic Research: The ARCPATH Project
Astrid E. J. OGILVIE, Leslie A. KING, Noel KEENLYSIDE, François COUNILLON, Brynhildur DAVIÐSDÓTTIR, Níels EINARSSON, Sergey GULEV, Ke FAN, Torben KOENIGK, James R. MCGOODWIN, Marianne H. RASMUSSON, Shuting YANG
, Available online   , Manuscript accepted  21 December 2023, doi: 10.1007/s00376-023-3333-x
This paper celebrates Professor Yongqi GAO’s significant achievement in the field of interdisciplinary studies within the context of his final research project Arctic Climate Predictions: Pathways to Resilient Sustainable Societies - ARCPATH ( The disciplines represented in the project are related to climatology, anthropology, marine biology, economics, and the broad spectrum of social-ecological studies. Team members were drawn from the Nordic countries, Russia, China, the United States, and Canada. The project was transdisciplinary as well as interdisciplinary as it included collaboration with local knowledge holders. ARCPATH made significant contributions to Arctic research through an improved understanding of the mechanisms that drive climate variability in the Arctic. In tandem with this research, a combination of historical investigations and social, economic, and marine biological fieldwork was carried out for the project study areas of Iceland, Greenland, Norway, and the surrounding seas, with a focus on the joint use of ocean and sea-ice data as well as social-ecological drivers. ARCPATH was able to provide an improved framework for predicting the near-term variation of Arctic climate on spatial scales relevant to society, as well as evaluating possible related changes in socioeconomic realms. In summary, through the integration of information from several different disciplines and research approaches, ARCPATH served to create new and valuable knowledge on crucial issues, thus providing new pathways to action for Arctic communities.
Scaling Laws Behind Penetrative Turbulence: History and Perspectives
Zijing DING, Ruiqi HUANG, Zhen OUYANG
, Available online   , Manuscript accepted  11 May 2024, doi: 10.1007/s00376-024-4014-0
An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection, which is crucial to many physical processes and has been thought of as a key factor for extreme weather conditions. Past theoretical, numerical, and experimental studies on penetrative convection are reviewed, along with field studies providing insights into turbulence modeling. The physical factors that initiate penetrative convection, including internal heat sources, nonlinear constitutive relationships, centrifugal forces and other complicated factors are summarized. Cutting-edge methods for understanding transport mechanisms and statistical properties of penetrative turbulence are also documented, e.g., the variational approach and quasilinear approach, which derive scaling laws embedded in penetrative turbulence. Exploring these scaling laws in penetrative convection can improve our understanding of large-scale geophysical and astrophysical motions. To better the model of penetrative turbulence towards a practical situation, new directions, e.g., penetrative convection in spheres, and radiation-forced convection, are proposed.