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
Anthropogenic Effects on Biogenic Secondary Organic Aerosol Formation
Li Xu, Lin Du, Narcisse TSONA, Maofa Ge
, Available online   , Manuscript accepted  17 November 2020, doi: 10.1007/s00376-020-0284-3
Anthropogenic emissions alter biogenic secondary organic aerosol (SOA) formation from naturally emitted volatile organic compounds (BVOCs). We review the major laboratory and field findings with regard to effects of anthropogenic pollutants (NOx, anthropogenic aerosols, SO2, NH3) on biogenic SOA formation. NOx participate in BVOCs oxidation through changing the radical chemistry and oxidation capacity, leading to a complex SOA composition and yield sensitivity towards NOx level for different or even specific hydrocarbon precursors. Anthropogenic aerosols act as an important intermedium for the gas-particle partition and particle-phase reactions, processes of which are influenced by the particle phase state, acidity, water content and thus associated with biogenic SOA mass accumulation. SO2 modifies biogenic SOA formation mainly through sulfuric acid formation and accompanies new particle formation and acid-catalyzed heterogeneous reactions. Some new SO2-involved mechanisms for organosulfates formation have also been proposed. NH3/amines as the most prevalent base species in the atmosphere, influences biogenic SOA composition and modify the optical properties of SOA. The response of SOA formation behavior to these anthropogenic pollutants varies among different BVOCs precursors. Investigations on anthropogenic-biogenic interactions in some areas of China that are simultaneously influenced by anthropogenic and biogenic emissions are summarized. Based on this review, some recommendations are made for a more accurate assessment of controllable biogenic SOA formation and its contribution to the total SOA budget. This study also highlights the importance of controlling anthropogenic pollutant emissions with effective pollutants mitigation policies to reduce regional and global biogenic SOA formation.
Rainfall Algorithms Using Oceanic Satellite Observations from MWHS-2
Ruiyao Chen, Ralf Bennartz
, Available online   , Manuscript accepted  13 November 2020, doi: 10.1007/s00376-020-0258-5
This paper describes three algorithms for retrieving precipitation over oceans from brightness temperatures (TBs) of the Micro-Wave Humidity Sounder-2 (MHWS-2) onboard Fengyun-3C (FY-3C). For algorithm development, scattering-induced TB depressions (ΔTBs) of MWHS-2 at channels between 89 and 190 GHz were collocated to rain rates derived from measurements of the Global Precipitation Measurement’s (GPM) Dual-frequency Precipitation Radar (DPR) for the year 2017. ΔTBs were calculated by subtracting simulated cloud-free TBs from bias-corrected observed TBs for each channel. These ΔTBs were then related to rain rates from DPR using (1) multi-linear regression (MLR). The other two algorithms, (2) range searches (RS) and (3) nearest neighbor searches (NNS), are based on k-dimensional trees. While all three algorithms produce instantaneous rain rates, the RS also provides the probability of precipitation and can be understood in a Bayesian framework. Different combinations of MWHS-2 channels were evaluated using the MLR and results suggest that adding 118 GHz improves retrieval performance. The optimal combination of channels excludes high-peaking channels but includes 118 GHz channels peaking in the mid and high troposphere. MWHS-2 observations from another year were used for validation purposes. The annual mean 2.5°x2.5° gridded rain rates from the three algorithms are consistent with those from the Global Precipitation Climatology Project (GPCP) and DPR. Their correlation coefficients with GPCP are 0.96 and their biases are less than 5%. The correlation coefficients with DPR are slightly lower and the maximum bias is ~8%, partly due to the lower sampling density of DPR compared to that of MWHS-2.
Long-term regional dynamic sea-level changes from CMIP6 projections
Bruno Ferrero, Marcos Toneli, Fernanda Marcello, Ilana Wainer
, Available online   , Manuscript accepted  11 November 2020, doi: 10.1007/s00376-020-0178-4
Anthropogenic climate forcing will cause the global mean sea-level to rise over the 21st century. However, regional sea-level is expected to vary across ocean basins, superimposed by the influence of natural internal climate variability. Here we address the detection of dynamic sea-level (DSL) changes by combining the perspectives of a single and a multi-model ensemble approach (the 50-member CanESM5 and a 27-model ensemble, respectively, all retrieved from the CMIP6 archive), under 3 CMIP6 projected scenarios: SSP1-2.6, SSP3-7.0 and SSP5-8.5. The ensemble analysis takes into account four key metrics: Signal (S), Noise (N), S/N ratio and Time of Emergence (ToE). The results from both sets of ensembles agree in the fact that regions with higher S/N (associated with smaller uncertainties) also reflect earlier ToEs. The DSL signal is projected to emerge in the Southern Ocean, Southeast Pacific, Northwest Atlantic, and the Arctic. Results common for both sets of ensemble simulations show that while S progressively increases with increased projected emissions, N, in turn, does not vary substantially among the SSPs suggesting that uncertainty arising from internal climate variability has little dependence on changes in the magnitude of external forcing. Projected changes are greater and quite similar for the SSP3-7.0 and SSP5-8.5 scenarios and considerably smaller for the SSP1-2.6, highlighting the importance of public policies towards lower emission scenarios and of keeping emissions below a certain threshold.
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
The 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 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 March 12, 2018 to April 30, 2018 were first used to estimate the hourly turbulent heat fluxes over the TP. The time series data of in situ measurements from Tibetan Observation and Research Platform (TORP) 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, and upwelling shortwave radiation flux, and the downwelling, and upwelling longwave radiation flux were 138.87 W·m-2, 32.78 W·m-2, 51.55 W·m-2, and 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.
The Northern Hemisphere Sudden Stratospheric Warming and Its Downward Impact in Four Chinese CMIP6 Models
Jian Rao, Siming Liu, Yuanhao Chen
, Available online   , Manuscript accepted  10 November 2020, doi: 10.1007/s00376-020-0250-0
Using the World Meteorological Organization (WMO) definition and a threshold-based classification technique, simulations of vortex displacement and split sudden stratospheric warmings (SSWs) are evaluated for four Chinese models (BCC-CSM2-MR, FGOALS-f3-L, FGOALS-g3, and NESM3) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) with the Japanese 55-year reanalysis (JRA-55) as a baseline. Compared with 6 or 7 SSWs in a decade in JRA-55, three models underestimate the SSW frequency by ~50%, while NESM3 doubles the SSW frequency. SSWs mainly appear in midwinter in JRA-55, but one-month climate drift is simulated in models. Composite of splits is stronger than displacements in both reanalysis and most models due to the longer pulse of positive eddy heat flux before onset of split SSWs. A wave-1-like temperature anomaly pattern (cold Eurasia, warm North America) before onset of displacement SSWs are simulated, but cold anomalies are mainly confined to North America after displacement SSWs. Although the lower tropospheric temperature also displays a wave-1-like pattern before split SSWs, most parts of Eurasia and North America are covered by cold anomalies after split SSWs in JRA-55. Models have different degrees of fidelity for the temperature anomaly pattern before split SSWs, but the wave-2-like temperature anomaly pattern is well simulated after split SSWs. The center of the negative height anomalies in the Pacific sector before SSWs is sensitive to the SSW type in both JRA-55 and models. A negative NAO is simulated after both types of SSWs in models, although it is only observed for split SSWs.
Vertical evolution of boundary layer VOCs in summer over the North China Plain and differences between winter and summer
Shuang Wu, Guiqian Tang, Yinghong Wang, Rong Mai, Dan Yao, Yanyu Kang, Qinglu Wang, Yuesi wang
, Available online   , Manuscript accepted  06 November 2020, doi: 10.1007/s00376-020-0254-9
The vertical observation of volatile organic compounds (VOCs) is an important means to clarify the mechanisms of ozone formation. To explore the vertical evolution characteristics of VOCs, a field campaign using a tethered balloon during summer photochemical pollution was conducted in Shijiazhuang from June 8 to July 3, 2019. A total of 192 VOC samples were collected, 23 vertical profiles were obtained, and the concentrations of 87 VOCs were measured. The range of the TVOC concentration was 41-48 ppbv below 600 m; it slightly increased above 600 m and rose to 58 ± 52 ppbv at 1000 m. The proportion of alkanes increased with height while the proportions of alkenes, halohydrocarbons, and acetylene decreased. The proportion of aromatics remained almost unchanged. A comparison with the results of a winter field campaign from January 8 to 16, 2019, showed that the concentrations of VOCs except for halohydrocarbons in winter were more than twice those in summer. Alkanes accounted for the same proportion in winter and summer. Alkenes, aromatics, and acetylene accounted for higher proportions in winter, while halohydrocarbons accounted for a higher proportion in summer. There were five VOC sources in the vertical direction. The proportions of gasoline vehicular emissions + industrial sources and coal burning were higher in winter. The proportions of biogenic sources + long-range transport, solvent usage, and diesel vehicular emissions were higher in summer. From the surface to 1000 m, the proportion of gasoline vehicular emissions + industrial sources gradually increased.
Monthly variations of atmospheric circulations associated with haze pollution in the Yangtze-River Delta and North China
Xinyu Zhang, zhicong Yin, Hui-Jun WANG, Mingkeng Duan
, Available online   , Manuscript accepted  05 November 2020, doi: 10.1007/s00376-020-0227-z
Haze pollution of early winter (December and January) in the Yangtze-River Delta (YRD) and in North China (NC) were both severe, however, their monthly variations were significantly different. In this study, dominant large-scale atmospheric circulations, local meteorological conditions were investigated and compared over the YRD and NC in each month. The YRD (NC) was dominated by the Scandinavia (East Atlantic/West Russia) pattern in December, and these circulations weakened in January. East Asian December (January) monsoon over the YRD and NC had negative correlations with haze days. The local sinking motion facilitated less removal of haze pollution over the YRD while the local ascending motion facilitated less removal of haze pollution over NC in January, despite weaker relationship in December. Additionally, the monthly variations of atmospheric circulations showed that adverse meteorological conditions restricted the vertical (horizontal) dispersion of haze pollution in December (January) over the YRD, while the associated local weather conditions were similar in two months over NC.
Growing operational use of FY-3 data in the ECMWF system
Niels Bormann, David Duncan, Stephen English, Sean Healy, Katrin Lonitz, Keyi Chen, Heather Lawrence, Qifeng Lu
, Available online   , Manuscript accepted  04 November 2020, doi: 10.1007/s00376-020-0207-3
The paper reviews the data quality and impact of observations from the FY-3 satellite series used operationally in the ECMWF system. This includes data from passive microwave radiometers MWHS-1, MWHS-2, and MWRI, as well as observations from the radio occultation receiver GNOS. Evaluations against background equivalents show that the quality of the observations is broadly comparable to that of similar instruments on other polar-orbiting satellites, even though biases for the passive microwave observations can be somewhat larger and more complex for some channels. An observing system experiment shows that the FY-3 instruments jointly contribute significantly to the forecast skill in the ECMWF system. Positive impact of up to 2% is seen for most variables out to the day 2 forecasts over hemispheric scales, with significant benefits for total column water vapour or for temperature and wind in the stratosphere out to day 4.
Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models using satellite data
Shengzhe Chen, Jiping Liu, Yifan Ding, Yuanyuan Zhang, Xiao Cheng, Yongyun Hu
, Available online   , Manuscript accepted  02 November 2020, doi: 10.1007/s00376-020-0213-5
Snow depth over sea ice is an essential variable for understanding the Arctic energy budget. In this study, we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) against recent satellite retrievals. The CMIP6 models capture some aspects of the observed snow depth climatology and variability. The observed variability lies in the middle of the model’s simulations. All the models show negative trends of snow depth during 1993-2014. However, substantial spatiotemporal discrepancies are identified. Compared to the observation, most models have late seasonal maximum snow depth (by two months), remarkably thinner snow for seasonal minimum, the incorrect transition from the growth to decay period, and greatly underestimate interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice. A majority of models cannot reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic. Future projections suggest that snow depth in the Arctic would continue to decrease from 2015 to 2099. Under SSP5-8.5 scenario, the Arctic would be almost snow-free during the summer and fall and the accumulation of snow starts from January. Further discussions of possible causes of the issues for the simulated snow depth by some models based on the same family of models suggest that resolutions, the inclusion of high-top atmospheric model and biogeochemistry processes are important factors for snow depth simulation.
Numerical simulation to evaluate the effects of upward lightning discharges on thunderstorm electrical parameters
Tianxue Zheng, Yongbo Tan, Yiru Wang
, Available online   , Manuscript accepted  21 October 2020, doi: 10.1007/s00376-020-0154-z
A theoretical discussion of the discharge effects of upward lightning simulated with a fine-resolution two-dimensional thunderstorm model is performed in this paper, and the results reveal that the estimates of the total induced charge on the upward lightning discharge channels range from 0.67 to 118.8 C, and the average value is 19.0 C, while the ratio of the induced charge on the leader channels to the total opposite-polarity charge in the discharge region (Ric) ranges from 5.9% to 47.3%, with an average value of 14.7%. Moreover, the average value of the space electrostatic energy consumed by upward lightning is 1.06∙109 J. The above values are lower than those related to intracloud (IC) lightning discharges. The density of the deposited opposite-polarity charge is comparable in magnitude to that of the preexisting charge in the discharge area, and the deposition of these opposite-polarity charges rapidly destroys the original space potential well in the discharge area and greatly decreases the space electric field strength. In addition, these opposite-polarity charges are redistributed with the development of thunderstorms. The space charge redistribution caused by lightning discharges partly accounts for the complexity of the charge structures in a thunderstorm, and the complexity gradually decreases with the charge neutralization process.
Inter-model Diversity of Simulated Long-term Changes in Austral Winter Southern Annular Mode: Role of the Southern Ocean Dipole
Fei Zheng, Jianping Li, Shuailei Yao
, Available online   , Manuscript accepted  20 October 2020, doi: 10.1007/s00376-020-0241-1
The Southern Annular Mode (SAM) plays an important role in regulating Southern Hemisphere extratropical circulation. State-of-the-art models exhibit inter-model spread in simulating long-term changes in the SAM. Results from Atmospheric Model Intercomparison Project (AMIP) experiments from 28 models archived in Coupled Model Intercomparison Project version 5 (CMIP5) show that the inter-model spread in linear trend in austral winter (June-July-August, JJA) SAM is significant, with an inter-model standard deviation of 0.28/decade, larger than the multi-model ensemble mean of 0.18/decade. This study explores potential factors underlying the model difference from the aspect of extratropical sea surface temperature (SST). Extratropical SST anomalies related to the SAM exhibit a dipole-like structure between middle and high latitudes, referred to as the Southern Ocean Dipole (SOD). The role of SOD-like SST anomalies in influencing SAM is found in the AMIP simulations. Model performance in simulating SAM trend is linked with model skill in reflecting the SOD-SAM relationship. Models with stronger linkage between the SOD and the SAM tend to simulate a stronger SAM trend. The explained variance is about 40% in the AMIP runs. These results suggest improved simulation of the SOD-SAM relationship may help reproduce long-term changes in the SAM.
Hybrid method to identify second-trip echoes using phase modulation and polarimetric technology
shuai zhang, Jinzhong Min, chian zhang, Xingyou Huang, jun liu, kai hua wei
, Available online   , Manuscript accepted  19 October 2020, doi: 10.1007/s00376-020-0223-3
For pulse Doppler radars, the widely used method for identifying second-trip echoes (STs) on the signal processing level yields significant misidentifications in regions of high turbulence and severe wind shear. On the data processing level, although the novel algorithm for ST identification does not yield significant misidentifications in specific regions, its overall identification performance is not ideal. Therefore, in this paper, a hybrid method is proposed for the identification of STs using phase modulation (signal processing) and polarimetric technology (data processing). Through this approach, most of the STs are removed, whereas most of the first-trip echoes (FTs) remain untouched. Compared with a signal quality index filter with an optimized threshold, the hybrid method exhibits superior performance (Heidke skill scores of 0.98 vs. 0.88) on independent test datasets, especially in high-turbulence and severe-wind-shear regions, for which misidentifications are significantly reduced.
Future precipitation extremes in China under climate change and their physical quantification based on a regional climate model and CMIP5 model simulations
Peihua Qin, Zhenghui Xie, Jing Zou, Shuang LIU, Si CHEN
, Available online   , Manuscript accepted  19 October 2020, doi: 10.1007/s00376-020-0141-4
The atmospheric water holding capacity will increase with temperature according to Clausius–Clapeyron (C–C) scaling and affects precipitation. The rates of change in future precipitation extremes are quantified with changes in air surface temperature (tas). Precipitation extremes in China are determined for 21st century in six simulations using regional climate model (RCM) RegCM4 and 17 global climate models (GCM) which participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5). First of all, we assess the performance of the CMIP5 and RCM models in simulation of extreme precipitation for the current period (RF: 1982-2001). CMIP5s and RCMs could capture the spatial variations in the precipitation extremes, as well as those based on observations: OBS and XPP. Precipitation extremes over four subregions in China are predicted to increase in the mid-future (MF: 2039–2058) and far-future (FF: 2079–2098) relative to those for the RF period based on both CMIP5 ensemble mean and RCM ensemble mean. The secular trends in the extremes by CMIP5s are predicted to increase from 2008 to 2058 and RCMs show higher inter-annual variability relative to those by CMIP5s. Then we quantify the increasing rates of changes in precipitation extremes in the MF and FF periods in the subregions of China with the changes in tas. Finally, based on water vapor equation, changes in precipitation extremes in China for the MF and FF periods are found positive correlation with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity and significant at p < 0.1 level.
Skill assessment of seasonal ensemble precipitation forecasts of C3S dataset in Iran
Masoud Nobakht, bahram saghafian, saleh aminyavari
, Available online   , Manuscript accepted  19 October 2020, doi: 10.1007/s00376-020-0025-7
Medium to long-term precipitation forecast plays a pivotal role in water resource management and development of warning systems. Recently, Copernicus Climate Change Service (C3S) database has been releasing monthly forecasts for up to three-month lead time for public use. This study evaluated the ensemble forecasts of three C3S models over the 1993-2017 period in Iran's eight classified precipitation clusters for one to three-month lead times. Probabilistic and non-probabilistic criteria were used for evaluation. Furthermore, the skill of selected models was analyzed in dry and wet periods in different precipitation clusters. The results indicated that the models performed best in western precipitation clusters while those of northern humid cluster had negative skill score. All models better forecasted upper tercile events in dry seasons and lower tercile events in wet seasons. Moreover, with increasing lead times, the models' forecast skill worsened. As far as forecasting in dry and wet years is concerned, the models' forecast was generally close to observations, although they underestimated a number of severe dry periods and overestimated a few wet periods. Moreover, the multi-model generated via multivariate regression of the three forecast models yielded better results compared with those of individual models. In general, European Centre for Medium-Range Weather Forecast (ECMWF) and United Kingdom Met Office (UKMO) models were found appropriate for 1-month ahead precipitation forecasting in most clusters of Iran. For study clusters and for long range system versions considered, the MF (Météo France) model had lower skill than other models.
Sensitivity of snowfall characteristics to meteorological conditions in the Yeongdong region of Korea
Yoo-Jun Kim, So-Ra IN, Hae-Min Kim, Jin-Hwa Lee, Kyu Rang Kim, Seungbum Kim, Byung-Gon Kim
, Available online   , Manuscript accepted  13 October 2020, doi: 10.1007/s00376-020-0157-9
This study investigates the characteristics of cold clouds and snowfall in both the Yeongdong coast and mountainous regions under different meteorological conditions based on the integration of numerical modeling and 3-hourly rawinsonde observations with snow crystal photographs for a snowfall event that occurred on 29–30 January, 2016. We found that rimed particles predominantly observed turned into dendrite habits in the latter period of the episode when the 850 hPa temperature decreased at the coastal site, whereas the snow crystal habits at the mountainous site were largely needle or rimed needle. Rawinsonde soundings showed a well-defined, two-layered cloud structure along with distinctive wind directional shear, and an inversion in the equivalent potential temperature above the low-level cloud layer. The first experiment with a decrease in lower layer temperature showed that the low-level cloud thickness was reduced to less than 1.5 km, and the accumulated precipitation was decreased by 87% compared with the control experiment. The difference in precipitation amount between the single-layered experiment and control experiment (two-layered) was not so significant to attribute it to the effect of the seeder–feeder mechanism. The precipitation in the last experiment by weakening wind directional shear was increased by 1.4 times greater than the control experiment specifically at the coastal site, with graupel particles accounting for the highest proportion (~62%). The current results would improve snowfall forecast in the complicated geographical environments such as Yeongdong in terms of snow crystal habit as well as snowfall amount in both time and space domains.
Determination of surface precipitation type based on data-fusion approach
Marek Półrolniczak, Leszek Kolendowicz, Bartosz Czernecki, Mateusz Taszarek, Gabriella Tóth
, Available online   , Manuscript accepted  09 October 2020, doi: 10.1007/s00376-020-0165-9
Hazardous events related to atmospheric precipitation depend not only on the intensity of surface precipitation, but also on its type. Uncertainty related to determination of the precipitation type (PT) leads to financial losses in many areas of human activity such as power industry, agriculture, transportation, and many more. In this study, we use machine learning (ML) algorithms with the data fusion approach to more accurately determine surface PT. Based on surface synoptic observations, ERA5 reanalysis, and radar data, we distinguish between liquid, mixed, and solid precipitation types. The study domain considers the entire area of Poland and a period from 2015 to 2017. The purpose of this work is to address the question: “How ML techniques applied in observational and NWP data can help to improve the recognition of the surface PT?” Despite testing 33 parameters, it was found that a combination of a near-surface air temperature and the depth of the warm layer in the 0–1000 m above ground level (AGL) contains most of the signal needed to determine surface PT. The accrued probability of detection for liquid, solid, and mixed PTs according to the developed random forests (RF) model is 98.0%, 98.8%, and 67.3%, respectively. The application of ML technique and data fusion approach allows to significantly improve the robustness of PT prediction compared to commonly used baseline models and provides promising results for operational forecasters.
Classification of Northeast China Cold Vortex Activity Paths in Early Summer Based on K-means Clustering and Their Climate Impact
Yihe FANG, Haishan CHEN, Yi LIN, Chunyu ZHAO, Yitong LIN, Fang ZHOU
, Available online   , Manuscript accepted  09 October 2020, doi: 10.1007/s00376-020-0118-3
The classification of the Northeast China Cold Vortex (NCCV) activity paths is an important way to analyze its characteristics in detail. Based on the daily precipitation data of the northeastern China (NEC) region, and the atmospheric circulation field and temperature field data of ERA-Interim for every six hours, the NCCV processes during the early summer (June) seasons from 1979 to 2018 were objectively identified. Then, the NCCV processes were classified using a machine learning method (k-means) according to the characteristic parameters of the activity path information. The rationality of the classification results was verified from two aspects, as follows: (1) the atmospheric circulation configuration of the NCCV on various paths; and (2) its influences on the climate conditions in the NEC. The obtained results showed that the activity paths of the NCCV could be divided into four types according to such characteristics as the generation origin, movement direction, and movement velocity of the NCCV. These included the generation-eastward movement type in the east of the Mongolia Plateau (eastward movement type or type A); generation-southeast long-distance movement type in the upstream of the Lena River (southeast long-distance movement type or type B); generation-eastward less-movement type near Lake Baikal (eastward less-movement type or type C); and the generation-southward less-movement type in eastern Siberia (southward less-movement type or type D). There were obvious differences observed in the atmospheric circulation configuration and the climate impact of the NCCV on the four above-mentioned types of paths, which indicated that the classification results were reasonable.
Increases in anthropogenic heat release from energy consumption lead to more frequent extreme heat events in urban cities
Bin LIU, Zhenghui Xie, Peihua Qin, Shuang LIU, Ruichao LI, Longhuan WANG, Yan WANG, Binghao Jia, Si CHEN, Jinbo Xie, Chunxiang Shi
, Available online   , Manuscript accepted  09 October 2020, doi: 10.1007/s00376-020-0139-y
With economic development and rapid urbanization, increases in Gross Domestic Product and population in fast-growing cities since the turn of the 21st Century have led to increases in energy consumption. Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environment and severe extreme temperature events. To investigate the effects of energy consumption on urban extreme temperature events, including extreme heat and cold events, a dynamic representation scheme of anthropogenic heat release (AHR) was implemented in the Weather Research and Forecasting model (WRF-ARW), and AHR data were developed based on energy consumption and population density in a case study of Beijing, China. Two simulations during 1999–2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme. It was shown that the mean temperature increased with the increase of AHR, and more frequent extreme heat events were produced, with an annual increase of 0.02–0.19 days, as well as less frequent extreme cold events, with an annual decrease of 0.26–0.56 days based on seven extreme temperature indices (ETIs) in the city center. AHR increased the sensible heat flux and led to surface energy budget changes, strengthening the boundary atmosphere dynamic processes that reduce AHR heating efficiency more in summer than in winter. In addition, it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons. The similar simulation can be applied to other cities to get a global result.
Improvement of Soil Moisture Simulation in Eurasia by the Beijing Climate Center Climate System Model from CMIP5 to CMIP6
Yinghan SANG, Hong-Li REN, Xueli SHI, Xiaofeng XU, Haishan CHEN
, Available online   , Manuscript accepted  29 September 2020, doi: 10.1007/s00376-020-0167-7
This study provides a comprehensive evaluation of historical surface soil moisture simulation (1979–2012) over Eurasia at annual and seasonal time scales between two medium-resolution versions of the Beijing Climate Center Climate System Model (BCC-CSM)—one that is currently participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6), i.e., BCC-CSM2-MR, and the other, BCC-CSM1.1m, which participated in CMIP5. We show that BCC-CSM2-MR is more skillful in reproducing the climate mean states and standard deviations of soil moisture, with pattern correlations increased and biases reduced significantly. BCC-CSM2-MR performs better in capturing the first two primary patterns of soil moisture anomalies, where the period of the corresponding time series is closer to that of reference data. Comparisons show that BCC-CSM2-MR performs at a high level among multiple models of CMIP6 in terms of centered pattern correlation and “amplitude of variation” (relative standard deviation). In general, the centered pattern correlation of BCC-CSM2-MR, ranging from 0.61 to 0.87, is higher than the multi-model mean of CMIP6, and the relative standard deviation is 0.75, which surmounts the overestimations in most of the CMIP6 models. Due to the vital role played by precipitation in land–atmosphere interaction, possible causes of the improvement of soil moisture simulation are further related to precipitation in BCC-CSM2-MR. The results indicate that a better description of the relationship between soil moisture and precipitation and a better reproduction of the climate mean precipitation by the model may result in the improved performance of soil moisture simulation.
Understanding the Soil Temperature Variability at Different Depths: Effects of Surface Air Temperature, Snow Cover, and the Soil Memory
Haoxin ZHANG, Naiming YUAN, Zhuguo MA, Yu HUANG
, Available online   , Manuscript accepted  24 September 2020, doi: 10.1007/s00376-020-0074-y
The soil temperature (ST) is closely related to the surface air temperature (AT), but their coupling may be affected by other factors. In this study, significant effects of the AT on the underlying ST were found, and the time taken to propagate downward to 320 cm can be up to 10 months. Besides the AT, the ST is also affected by memory effects—namely, its prior thermal conditions. At deeper depth (i.e., 320 cm), the effects of the AT from a particular season may be exceeded by the soil memory effects from the last season. At shallower layers (i.e., < 80 cm), the effects of the AT may be blocked by the snow cover, resulting in a poorly synchronous correlation between the AT and the ST. In northeastern China, this snow cover blockage mainly occurs in winter and then vanishes in the subsequent spring. Due to the thermal insulation effect of the snow cover, the winter ST at layers above 80 cm in northeastern China were found to continue to increase even during the recent global warming hiatus period. These findings may be instructive for better understanding ST variations, as well as land−atmosphere interactions.
High-resolution Simulation of an Extreme Heavy Rainfall Event in Shanghai Using the Weather Research and Forecasting Model: Sensitivity to Planetary Boundary Layer Parameterization
Rui WANG, Yiting ZHU, Fengxue QIAO, Xin-Zhong LIANG, Han ZHANG, Yang DING
, Available online   , Manuscript accepted  21 September 2020, doi: 10.1007/s00376-020-9255-y
In this study, an extreme rainfall event that occurred on 25 May 2018 over Shanghai and its nearby area was simulated using the Weather Research and Forecasting model, with a focus on the effects of planetary boundary layer (PBL) physics using double nesting with large grid ratios (15:1 and 9:1). The sensitivity of the precipitation forecast was examined through three PBL schemes: the Yonsei University Scheme, the Mellor−Yamada−Nakanishi Niino Level 2.5 (MYNN) scheme, and the Mellor−Yamada−Janjic scheme. The PBL effects on boundary layer structures, convective thermodynamic and large-scale forcings were investigated to explain the model differences in extreme rainfall distributions and hourly variations. The results indicated that in single coarser grids (15 km and 9 km), the extreme rainfall amount was largely underestimated with all three PBL schemes. In the inner 1-km grid, the underestimated intensity was improved; however, using the MYNN scheme for the 1-km grid domain with explicitly resolved convection and nested within the 9-km grid using the Kain−Fritsch cumulus scheme, significant advantages over the other PBL schemes are revealed in predicting the extreme rainfall distribution and the time of primary peak rainfall. MYNN, with the weakest vertical mixing, produced the shallowest and most humid inversion layer with the lowest lifting condensation level, but stronger wind fields and upward motions from the top of the boundary layer to upper levels. These factors all facilitate the development of deep convection and moisture transport for intense precipitation, and result in its most realistic prediction of the primary rainfall peak.
Precipitation Microphysical Processes in the Inner Rainband of Tropical Cyclone Kajiki (2019) over the South China Sea Revealed by Polarimetric Radar
Hepeng ZHENG, Yun ZHANG, Lifeng ZHANG, Hengchi LEI, Zuhang WU
, Available online   , Manuscript accepted  16 September 2020, doi: 10.1007/s00376-020-0179-3
Polarimetric radar and 2D video disdrometer observations provide new insights into the precipitation microphysical processes and characteristics in the inner rainband of tropical cyclone (TC) Kajiki (2019) in the South China Sea for the first time. The precipitation of Kajiki is dominated by high concentrations and small (< 3 mm) raindrops, which contribute more than 98% to the total precipitation. The average mass-weighted mean diameter and logarithmic normalized intercept are 1.49 mm and 4.47, respectively, indicating a larger mean diameter and a lower concentration compared to the TCs making landfall in eastern China. The ice processes of the inner rainband are dramatically different among different stages. The riming process is dominant during the mature stage, while during the decay stage the aggregation process is dominant. The vertical profiles of the polarimetric radar variables together with ice and liquid water contents in the convective region indicate that the formation of precipitation is dominated by warm-rain processes. Large raindrops collect cloud droplets and other raindrops, causing reflectivity, differential reflectivity, and specific differential phase to increase with decreasing height. That is, accretion and coalescence play a critical role in the formation of heavy rainfall. The melting of different particles generated by the ice process has a great influence on the initial raindrop size distribution (DSD) to further affect the warm-rain processes. The DSD above heavy rain with the effect of graupel has a wider spectral width than the region without the effect of graupel.
Assimilation of Doppler Radar Data with an Ensemble 3DEnVar Approach to Improve Convective Forecasting
Shibo GAO, Haiqiu YU, Chuanyou REN, Limin LIU, Jinzhong MIN
, Available online   , Manuscript accepted  16 September 2020, doi: 10.1007/s00376-020-0081-z
An ensemble three-dimensional ensemble-variational (3DEnVar) data assimilation (E3DA) system was developed within the Weather Research and Forecasting model’s 3DVar framework to assimilate radar data to improve convective forecasting. In this system, ensemble perturbations are updated by an ensemble of 3DEnVar and the ensemble forecasts are used to generate the flow-dependent background error covariance. The performance of the E3DA system was first evaluated against one experiment without radar DA and one radar DA experiment with 3DVar, using a severe storm case over southeastern China on 5 June 2009. Results indicated that E3DA improved the quantitative forecast skills of reflectivity and precipitation, as well as their spatial distributions in terms of both intensity and coverage over 3DVar. The root-mean-square error of radial velocity from 3DVar was reduced by E3DA, with stronger low-level wind closer to observation. It was also found that E3DA improved the wind, temperature and water vapor mixing ratio, with the lowest errors at the surface and upper levels. 3DVar showed moderate improvements in comparison with forecasts without radar DA. A diagnosis of the analysis revealed that E3DA increased vertical velocity, temperature, and humidity corresponding to the added reflectivity, while 3DVar failed to produce these adjustments, because of the lack of reasonable cross-variable correlations. The performance of E3DA was further verified using two convective cases over southern and southeastern China, and the reflectivity forecast skill was also improved over 3DVar.
Variations in Wave Energy and Amplitudes along the Energy Dispersion Paths of Nonstationary Barotropic Rossby Waves
Yaokun LI, Jiping CHAO, Yanyan KANG
, Available online   , Manuscript accepted  16 September 2020, doi: 10.1007/s00376-020-0084-9
The variations in the wave energy and the amplitude along the energy dispersion paths of the barotropic Rossby waves in zonally symmetric basic flow are studied by solving the wave energy equation, which expresses that the wave energy variability is determined by the divergence of the group velocity and the energy budget from the basic flow. The results suggest that both the wave energy and the amplitude of a leading wave increase significantly in the propagating region that is located south of the jet axis and enclosed by a southern critical line and a northern turning latitude. The leading wave gains the barotropic energy from the basic flow by eddy activities. The amplitude continuously climbs up a peak at the turning latitude due to increasing wave energy and enlarging horizontal scale (shrinking total wavenumber). Both the wave energy and the amplitude eventually decrease when the trailing wave continuously approaches southward to the critical line. The trailing wave decays and its energy is continuously absorbed by the basic flow. Furthermore, both the wave energy and the amplitude oscillate with a limited range in the propagating region that is located near the jet axis and enclosed by two turning latitudes. Both the leading and trailing waves neither develop nor decay significantly. The jet works as a waveguide to allow the waves to propagate a long distance.
Profiles and Source Apportionment of Nonmethane Volatile Organic Compounds in Winter and Summer in Xi’an, China, based on the Hybrid Environmental Receptor Model
Jian SUN, Zhenxing SHEN, Yue ZHANG, Wenting DAI, Kun HE, Hongmei XU, Zhou ZHANG, Long CUI, Xuxiang LI, Yu HUANG, Junji CAO
, Available online   , Manuscript accepted  09 September 2020, doi: 10.1007/s00376-020-0153-0
Summer and winter campaigns for the chemical compositions and sources of nonmethane hydrocarbons (NMHCs) and oxygenated volatile organic compounds (OVOCs) were conducted in Xi’an. Data from 57 photochemical assessment monitoring stations for NMHCs and 20 OVOC species were analyzed. Significant seasonal differences were noted for total VOC (TVOC, NMHCs and OVOCs) concentrations and compositions. The campaign-average TVOC concentrations in winter (85.3 ± 60.6 ppbv) were almost twice those in summer (47.2 ± 31.6 ppbv). Alkanes and OVOCs were the most abundant category in winter and summer, respectively. NMHCs, but not OVOCs, had significantly higher levels on weekends than on weekdays. Total ozone formation potential was higher in summer than in winter (by 50%) because of the high concentrations of alkenes (particularly isoprene), high temperature, and high solar radiation levels in summer. The Hybrid Environmental Receptor Model (HERM) was used to conduct source apportionment for atmospheric TVOCs in winter and summer, with excellent accuracy. HERM demonstrated its suitability in a situation where only partial source profile data were available. The HERM results indicated significantly different seasonal source contributions to TVOCs in Xi’an. In particular, coal and biomass burning had contributions greater than half in winter (53.4%), whereas traffic sources were prevalent in summer (53.1%). This study’s results highlight the need for targeted and adjustable VOC control measures that account for seasonal differences in Xi’an; such measures should target not only the severe problem with VOC pollution but also the problem of consequent secondary pollution (e.g., from ozone and secondary organic aerosols).
Characterization of organic aerosol at a rural site in North China Plain: sources, volatility and organonitrates
Qiao Zhu, Li-Ming Cao, Meng-Xue Tang, Xiao-Feng Huang, Eri Saikawa, L. -Y. He
, Available online   , Manuscript accepted  09 September 2020, doi: 10.1007/s00376-020-0127-2
The North China Plain (NCP) is the region that experiences serious aerosol pollution. A number of studies focus on aerosol pollution in urban regions in NCP, however, research on characterizing aerosols in rural NCP areas is comparatively limited. In this study, we deployed a thermodenuder high-resolution aerosol mass spectrometer (TD-HR-AMS) system at a rural site in NCP region in summer 2013 to characterize the chemical compositions and volatility of submicron aerosols (PM1). The average PM1 mass concentration was 51.2 ± 48.0µg m-3 and organic aerosol (OA) contributed most (35.4%) to PM1. Positive matrix factorization (PMF) analysis of OA measurements identified four OA factors including hydrocarbon-like OA (HOA, accounting for 18.4%), biomass burning OA (BBOA, 29.4%), less-oxidized oxygenated OA (LO-OOA, 30.8%) and more-oxidized oxygenated OA (MO-OOA, 21.4%). The volatility sequence of the OA factors was HOA > BBOA > LO-OOA > MO-OOA, consistent with their oxygen-to-carbon (O:C) ratios. Additionally, the mean concentration of organonitrates (ON) was 1.48–3.39 µg m-3, contributing 8.1–19% of OA based on cross validation of two estimated methods with the HR-ToF-AMS measurement. The correlation analysis shows that ON were more correlated with BBOA and black carbon emitted from biomass burning but poorly correlated with LO-OOA. And the volatility analysis for ON further confirms that particulate ON formation might be highly associated with primary emissions in rural NCP.
Evaluation of Arctic Sea-ice Cover and Thickness Simulated by MITgcm
Fei ZHENG, Yue SUN, Qinghua YANG, Longjiang MU
, Available online   , Manuscript accepted  09 September 2020, doi: 10.1007/s00376-020-9223-6
A regional Arctic Ocean configuration of the Massachusetts Institute of Technology General Circulation Model (MITgcm) is applied to simulate the Arctic sea ice from 1991 to 2012. The simulations are evaluated by comparing them with observations from different sources. The results show that MITgcm can reproduce the interannual and seasonal variability of the sea-ice extent, but underestimates the trend in sea-ice extent, especially in September. The ice concentration and thickness distributions are comparable to those from the observations, with most deviations within the observational uncertainties and less than 0.5 m, respectively. The simulated sea-ice extents are better correlated with observations in September, with a correlation coefficient of 0.95, than in March, with a correlation coefficient of 0.83. However, the distributions of sea-ice concentration are better simulated in March, with higher pattern correlation coefficients (0.98) than in September. When the model underestimates the atmospheric influence on the sea-ice evolution in March, deviations in the sea-ice concentration arise at the ice edges and are higher than those in September. In contrast, when the model underestimates the oceanic boundaries’ influence on the September sea-ice evolution, disagreements in the distribution of the sea-ice concentration and its trend are found over most marginal seas in the Arctic Ocean. The uncertainties of the model, whereby it fails to incorporate the atmospheric information in March and oceanic information in September, contribute to varying model errors with the seasons.
Influence of the Eastern Pacific and Central Pacific Types of ENSO on the South Asian Summer Monsoon
Fangxing FAN, Renping LIN, Xianghui FANG, Feng XUE, Fei ZHENG, Jiang ZHU
, Available online   , Manuscript accepted  07 September 2020, doi: 10.1007/s00376-020-0055-1
Based on observational and reanalysis data, the relationships between the eastern Pacific (EP) and central Pacific (CP) types of El Niño−Southern Oscillation (ENSO) during the developing summer and the South Asian summer monsoon (SASM) are examined. The roles of these two types of ENSO on the SASM experienced notable multidecadal modulation in the late 1970s. While the inverse relationship between the EP type of ENSO and the SASM has weakened dramatically, the CP type of ENSO plays a far more prominent role in producing anomalous Indian monsoon rainfall after the late 1970s. The drought-producing El Niño warming of both the EP and CP types can excite anomalous rising motion of the Walker circulation concentrated in the equatorial central Pacific around 160°W to the date line. Accordingly, compensatory subsidence anomalies are evident from the Maritime Continent to the Indian subcontinent, leading to suppressed convection and decreased precipitation over these regions. Moreover, anomalously less moisture flux into South Asia associated with developing EP El Niño and significant northwesterly anomalies dominating over southern India accompanied by developing CP El Niño, may also have been responsible for the Indian monsoon droughts during the pre-1979 and post-1979 sub-periods, respectively. El Niño events with the same “flavor” may not necessarily produce consistent Indian monsoon rainfall anomalies, while similar Indian monsoon droughts may be induced by different types of El Niño, implying high sensitivity of monsoonal precipitation to the detailed configuration of ENSO forcing imposed on the tropical Pacific.
Water Vapor Retrievals from Near-infrared Channels of the Advanced Medium Resolution Spectral Imager Instrument onboard the Fengyun-3D Satellite
Ling WANG, Xiuqing HU, Na XU, Lin CHEN
, Available online   , Manuscript accepted  07 September 2020, doi: 10.1007/s00376-020-0174-8
Water vapor plays a key role in weather, climate and environmental research on local and global scales. Knowledge about atmospheric water vapor and its spatiotemporal variability is essential for climate and weather research. Because of the advantage of a unique temporal and spatial resolution, satellite observations provide global or regional water vapor distributions. The advanced Medium Resolution Spectral Imager (MERSI) instrument—that is, MERSI-II—onboard the Fengyun-3D (FY-3D) meteorological satellite, has been one of the major satellite sensors routinely providing precipitable water vapor (PWV) products to the community using near-infrared (NIR) measurements since June 2018. In this paper, the major updates related to the production of the NIR PWV products of MERSI-II are discussed for the first time. In addition, the water vapor retrieval algorithm based on the MERSI-II NIR channels is introduced and derivations are made over clear land areas, clouds, and sun-glint areas over the ocean. Finally, the status and samples of the MERSI-II PWV products are presented. The accuracy of MERSI-II PWV products is validated using ground-based GPS measurements. The results show that the accuracies of the water vapor products based on the updated MERSI-II instrument are significantly improved compared with those of MERSI, because MERSI-II provides a better channel setting and new calibration method. The root-mean-square error and relative bias of MERSI-II PWV products are typically 1.8–5.5 mm and −3.0% to −14.3%, respectively, and thus comparable with those of other global remote sensing products of the same type.
Extensive Cold-Precipitation-Freezing Events in Southern China and Their Circulation Characteristics
Jing-Bei PENG, Cholaw BUEH, Zuo-Wei XIE
, Available online   , Manuscript accepted  03 September 2020, doi: 10.1007/s00376-020-0117-4
Concurrence of low temperature, precipitation and freezing weather in an extensive area would cause devastating impacts on local economy and society. We call such a combination of concurrent disastrous weather “extensive cold-precipitation-freezing” events (ECPFEs). In this study, the ECPFEs in southern China (15°−35°N, 102°−123°E) are objectively defined by using daily surface observational data for the period 1951−2013. An ECPFE in southern China is defined if the low temperature area, precipitation area and freezing area concurrently exceed their respective thresholds for at least three consecutive days. The identified ECPFEs are shown to be reasonable and reliable, compared with those in previous studies. The circulation anomalies in ECPFEs are characterized by a large-scale tilted ridge and trough pairing over mid- and high-latitude Eurasia, and the intensified subtropical westerlies along the southern foot of the Tibetan Plateau and the anomalous anticyclonic circulation over the subtropical western Pacific. Comparative analysis reveals that the stable cold air from the north and the warm and moist air from the south converge, facilitating a favorable environment for the concurrence of extensive low-temperature, precipitation and freezing weather.
Surface Temperature Changes Projected by FGOALS Models under Low Warming Scenarios in CMIP5 and CMIP6
Shang-Min LONG, Kai-Ming HU, Gen LI, Gang HUANG, Xia QU
, Available online   , Manuscript accepted  20 August 2020, doi: 10.1007/s00376-020-0177-5
To meet the low warming targets proposed in the 2015 Paris Agreement, substantial reduction in carbon emissions is needed in the future. It is important to know how surface climates respond under low warming targets. The present study investigates the surface temperature changes under the low-forcing scenario of Representative Concentration Pathways (RCP2.6) and its updated version (Shared Socioeconomic Pathways, SSP1-2.6) by the Flexible Global Ocean–Atmosphere–Land System (FGOALS) models participating in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). In both scenarios, radiative forcing (RF) first increases to a peak of 3 W m−2 around 2045 and then decreases to 2.6 W m−2 by 2100. Global mean surface air temperature rises in all FGOALS models when RF increases (RF increasing stage) and declines or holds nearly constant when RF decreases (RF decreasing stage). The surface temperature change is distinct in its sign and magnitude between the RF increasing and decreasing stages over the land, Arctic, North Atlantic subpolar region, and Southern Ocean. Besides, the regional surface temperature change pattern displays pronounced model-to-model spread during both the RF increasing and decreasing stages, mainly due to large intermodel differences in climatological surface temperature, ice-albedo feedback, natural variability, and Atlantic Meridional Overturning Circulation change. The pattern of tropical precipitation change is generally anchored by the spatial variations of relative surface temperature change (deviations from the tropical mean value) in the FGOALS models. Moreover, the projected changes in the updated FGOALS models are closer to the multi-model ensemble mean results than their predecessors, suggesting that there are noticeable improvements in the future projections of FGOALS models from CMIP5 to CMIP6.
Simulated Relationship between Wintertime ENSO and East Asian Summer Rainfall: From CMIP3 to CMIP6
Yuanhai FU, Zhongda LIN, Tao WANG
, Available online   , Manuscript accepted  05 August 2020, doi: 10.1007/s00376-020-0147-y
El Niño–Southern Oscillation (ENSO) events have a strong influence on East Asian summer rainfall (EASR). This paper investigates the simulated ENSO–EASR relationship in CMIP6 models and compares the results with those in CMIP3 and CMIP5 models. In general, the CMIP6 models show almost no appreciable progress in representing the ENSO–EASR relationship compared with the CMIP5 models. The correlation coefficients in the CMIP6 models are relatively smaller and exhibit a slightly greater intermodel diversity than those in the CMIP5 models. Three physical processes related to the delayed effect of ENSO on EASR are further analyzed. Results show that, firstly, the relationships between ENSO and the tropical Indian Ocean (TIO) sea surface temperature (SST) in the CMIP6 models are more realistic, stronger, and have less intermodel diversity than those in the CMIP3 and CMIP5 models. Secondly, the teleconnections between the TIO SST and Philippine Sea convection (PSC) in the CMIP6 models are almost the same as those in the CMIP5 models, and stronger than those in the CMIP3 models. Finally, the CMIP3, CMIP5, and CMIP6 models exhibit essentially identical capabilities in representing the PSC–EASR relationship. Almost all the three generations of models underestimate the ENSO–EASR, TIO SST–PSC, and PSC–EASR relationships. Moreover, almost all the CMIP6 models that successfully capture the significant TIO SST–PSC relationship realistically simulate the ENSO–EASR relationship and vice versa, which is, however, not the case in the CMIP5 models.
Insights into the Microwave Instruments Onboard the Fengyun 3D Satellite: Data Quality and Assimilation in the Met Office NWP System
Fabien CARMINATI, Nigel ATKINSON, Brett CANDY, Qifeng LU
, Available online   , Manuscript accepted  28 May 2020, doi: 10.1007/s00376-020-0010-1
This paper evaluates the microwave instruments onboard the latest Chinese polar-orbiting satellite, Fengyun 3D (FY-3D). Comparing three months of observations from the Microwave Temperature Sounder 2 (MWTS-2), the Microwave Humidity Sounder 2 (MWHS-2), and the Microwave Radiation Imager (MWRI) to Met Office short-range forecasts, we characterize the instrumental biases, show how those biases have changed with respect to their predecessors onboard FY-3C, and how they compare to the Advanced Technology Microwave Sounder (ATMS) onboard NOAA-20 and the Global Precipitation Measurement Microwave Imager (GMI). The MWTS-2 global bias is much reduced with respect to its predecessor and compares well to ATMS at equivalent channel frequencies, differing only by 0.36 ± 0.28 K (1σ) on average. A suboptimal averaging of raw digital counts is found to cause an increase in striping noise and an ascending—descending bias. MWHS-2 benefits from a new calibration method improving the 183-GHz humidity channels with respect to its predecessor and biases for these channels are within ± 1.9 K to ATMS. MWRI presents the largest improvements, with reduced global bias and standard deviation with respect to FY-3C; although, spurious, seemingly transient, brightness temperatures have been detected in the observations at 36.5 GHz (vertical polarization). The strong solar-dependent bias that affects the instrument on FY-3C has been reduced to less than 0.2 K on average for FY-3D MWRI. Experiments where radiances from these instruments were assimilated on top of a full global system demonstrated a neutral to positive impact on the forecasts, as well as on the fit to the background of independent instruments.
Data Description Article
BCC-ESM1 Model Datasets for the CMIP6 Aerosol Chemistry Model Intercomparison Project (AerChemMIP)
Jie ZHANG, Tongwen Wu, Fang ZHANG, Kalli FURTADO, Xiaoge XIN, Xueli Shi, Jianglong Li, min chu, Li Zhang, Qianxia Liu, Jinghui YAN, Min Wei, Qiang MA
, Available online   , Manuscript accepted  10 November 2020, doi: 10.1007/s00376-020-0151-2
BCC-ESM1 is the first version of the Beijing Climate Center’s Earth System Model (ESM) developed by the Beijing Climate Center, China Meteorological Administration (BCC/CMA), and has participated in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is the only CMIP6-endorsed MIPs that BCC-ESM1 involved in. All AerChemMIP experiments in priority 1 and seven experiments in priorities 2 and 3 have been conducted. The DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations are also run as the entry card of CMIP6. The AerChemMIP outputs from BCC-ESM1 have been widely used in recent atmospheric chemistry studies. To facilitate the usage of BCC-ESM1 datasets, this study describes the experiment settings and summarizes the model outputs in detail. The preliminary evaluations on BCC-ESM1 are also shown: climate sensitivities of BCC-ESM1 are well within the likely ranges suggested by IPCC AR5; the spatial structures of annual mean surface air temperature and precipitation can be reasonably captured, despite some common precipitation biases in CMIP5 and CMIP6 models; a spurious cooling bias from the 1960s to 1990s is evident in BCC-ESM1 as in most of the other ESMs; mean states of surface sulfate concentrations can also be reasonably reproduced as well as the time-evolving at regional scales.
CAS-ESM2.0 Model Datasets for CMIP6 Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP)
Jiangbo Jin, He Zhang, Xiao Dong, Hailong LIU, minghua Zhang, Xin Gao, Juanxiong He, Zhaoyang Chai, Qing-Cun Zeng, Guangqing Zhou, Zhaohui LIN, Yi Yu, Pengfei LIN, Ruxu Lian, Yongqiang Yu, Mirong SONG, Dongling Zhang
, Available online   , Manuscript accepted  29 October 2020, doi: 10.1007/s00376-020-0188-2
The second version of the Chinese Academy of Science Earth System Model (CAS-ESM2.0) is participating in the Flux–Anomaly-Forced Model Intercomparison Project (FAFMIP) experiments in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The purpose of FAFMIP is to understand and reduce the uncertainty of ocean climate changes in response to increased CO2 forcing in the Atmosphere-Ocean General Circulation Model (AOGCM), including the simulations of ocean heat content (OHC) change, ocean circulation change, and sea level rise due to thermal expansion. FAFMIP experiments (including faf-heat, faf-stress, faf-water, faf-all, faf-passiveheat, faf-heat-NA50pct and faf-heat-NA0pct) have been conducted. All of the experiments were integrated over a 70-year period and the corresponding data have been uploaded to the Earth System Grid (ESG) data server for CMIP6 users to download. This paper describes the experimental design and model datasets and evaluates the preliminary results of CAS-ESM2.0 in the simulations of ocean climate changes in the FAFMIP experiments. The simulations of the changes in global ocean temperature, Atlantic meridional overturning circulation (AMOC), OHC and dynamic sea level (DSL) are reasonably reproduced.
NUIST ESM v3 data submissions to CMIP6
Jian Cao, Libin Ma, Fei Liu, Jing Chai, Haikun Zhao, Qiong He, Bo Wang, Yan Bao, Juan Li, Young‐Min Yang, Hua Deng, Bin Wang
, Available online   , Manuscript accepted  29 October 2020, doi: 10.1007/s00376-020-0173-9
This paper introduces the experimental designs and outputs of the Diagnostic, Evaluation and Characterization of Klima (DECK), historical, Scenario Model Intercomparison Project (MIP), and Paleoclimate MIP (PMIP) experiments from Nanjing University of Information Science and Technology Earth System Model version 3 (NESM3). Results show that NESM3 reasonably simulates the modern climate and the major internal modes of climate variability. In the Scenario MIP experiment, changes in the projected surface air temperature (SAT) show a robust “Northern Hemisphere (NH)-warmer than-Southern Hemisphere (SH)” and “land-warmer than-ocean” patterns, as well as an El Niño-like warming over the tropical Pacific. Changes in the projected precipitation exhibit an “NH-wetter than-SH” and an “eastern hemisphere gets wetter and western hemisphere gets drier” patterns over the tropics. These precipitation patterns are driven by circulation changes owing to the inhomogeneous warming patterns. Two PMIP experiments show enlarged seasonal cycles of SAT and precipitation over the NH due to the seasonal redistribution of solar radiation. Changes in the climatological mean SAT, precipitation, and El Niño–Southern Oscillation (ENSO) amplitudes are consistent with the results from PMIP4 models. The NESM3 outputs are available on the Earth System Grid Federation nodes for data users.
Western North Pacific Tropical cyclone database created by the China Meteorological Administration
Xiaoqin LU, Hui Yu, Ming Ying, Bingke Zhao, Shuai Zhang, Limin Lin, Lina Bai, Rijin Wan
, Available online   , Manuscript accepted  22 October 2020, doi: 10.1007/s00376-020-0211-7
This paper describes the access to, and the content, characteristics, and potential applications of the tropical cyclone (TC) database that is maintained and actively developed by the China Meteorological Administration (CMA), with the aim of facilitating its use in scientific research and operational services. This database records data relating to all TCs that have passed through the western North Pacific (WNP) and South China Sea (SCS) since 1949. TC data collection has expanded over recent decades via continuous TC monitoring using remote sensing and specialized field detection techniques, allowing collation of a multi-source TC database for the WNP and SCS that covers a long period, with wide coverage and many observational elements. This database now comprises a wide variety of information related to TCs,such as historical or real-time locations (i.e., best track and landfall), intensity, dynamic and thermal structures, wind strengths, precipitation amounts, and frequency. This database will support ongoing research into the processes and patterns associated with TC climatic activity and TC forecasting.
The CMIP6 Historical Simulation Datasets Produced by the Climate System Model CAMS-CSM
Xinyao RONG, Jian LI, Haoming CHEN, Jingzhi SU, Lijuan· HUA, Zhengqiu ZHANG, Yufei XIN
, Available online   , Manuscript accepted  15 October 2020, doi: 10.1007/s00376-020-0171-y
This paper describes the historical simulations produced by the Chinese Academy of Meteorological Sciences (CAMS) climate system model (CAMS-CSM), which are contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6). The model description, experiment design and model outputs are presented. Three members’ historical experiments are conducted by CAMS-CSM, with two members starting from different initial conditions, and one excluding the stratospheric aerosol to identify the effect of volcanic eruptions. The outputs of the historical experiments are also validated using observational data. It is found that the model can reproduce the climatological mean states and seasonal cycle of the major climate system quantities, including the surface air temperature, precipitation, and the equatorial thermocline. The long-term trend of air temperature and precipitation is also reasonably captured by CAMS-CSM. There are still some biases in the model that need further improvement. This paper can help the users to better understand the performance and the datasets of CAMS-CSM.
Datasets for the CMIP6 Scenario Model Intercomparison Project (ScenarioMIP) Simulations with the Coupled Model CAS FGOALS-f3-L
Shuwen ZHAO, Yongqiang YU, Pengfei LIN, Hailong LIU, Bian HE, Qing BAO, Yuyang GUO, Lijuan HUA, Kangjun CHEN, Xiaowei WANG
, Available online   , Manuscript accepted  08 September 2020, doi: 10.1007/s00376-020-0112-9
The datasets for the tier-1 Scenario Model Intercomparison Project (ScenarioMIP) experiments from the Chinese Academy of Sciences (CAS) Flexible Global Ocean–Atmosphere–Land System model, finite-volume version 3 (CAS FGOALS-f3-L) are described in this study. ScenarioMIP is one of the core MIP experiments in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Considering future CO2, CH4, N2O and other gases’ concentrations, as well as land use, the design of ScenarioMIP involves eight pathways, including two tiers (tier-1 and tier-2) of priority. Tier-1 includes four combined Shared Socioeconomic Pathways (SSPs) with radiative forcing, i.e., SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, in which the globally averaged radiative forcing at the top of the atmosphere around the year 2100 is approximately 2.6, 4.5, 7.0 and 8.5 W m−2, respectively. This study provides an introduction to the ScenarioMIP datasets of this model, such as their storage location, sizes, variables, etc. Preliminary analysis indicates that surface air temperatures will increase by about 1.89°C, 3.07°C, 4.06°C and 5.17°C by around 2100 under these four scenarios, respectively. Meanwhile, some other key climate variables, such as sea-ice extension, precipitation, heat content, and sea level rise, also show significant long-term trends associated with the radiative forcing increases. These datasets will help us understand how the climate will change under different anthropogenic and radiative forcings.
CAS-ESM2.0 Model Datasets for the CMIP6 Ocean Model Intercomparison Project Phase 1 (OMIP1)
Xiao DONG, Jiangbo JIN, Hailong LIU, He ZHANG, Minghua ZHANG, Pengfei LIN, Qingcun ZENG, Guangqing ZHOU, Yongqiang YU, Mirong SONG, Zhaohui LIN, Ruxu LIAN, Xin GAO, Juanxiong HE, Dongling ZHANG, Kangjun CHEN
, Available online   , Manuscript accepted  04 September 2020, doi: 10.1007/s00376-020-0150-3
As a member of the Chinese modeling groups, the coupled ocean–ice component of the Chinese Academy of Sciences’ Earth System Model, version 2.0 (CAS-ESM2.0), is taking part in the Ocean Model Intercomparison Project Phase 1 (OMIP1) experiment of phase 6 of the Coupled Model Intercomparison Project (CMIP6). The simulation was conducted, and monthly outputs have been published on the ESGF (Earth System Grid Federation) data server. In this paper, the experimental dataset is introduced, and the preliminary performances of the ocean model in simulating the global ocean temperature, salinity, sea surface temperature, sea surface salinity, sea surface height, sea ice, and Atlantic Meridional Overturning Circulation (AMOC) are evaluated. The results show that the model is at quasi-equilibrium during the integration of 372 years, and performances of the model are reasonable compared with observations. This dataset is ready to be downloaded and used by the community in related research, e.g., multi-ocean–sea-ice model performance evaluation and interannual variation in oceans driven by prescribed atmospheric forcing.
Invited Review
Integrative Monsoon Frontal Rainfall Experiment (IMFRE): A Mid-Term Review
chunguang cui, Xiquan Dong, Bin Wang, Baike Xi, Yi Deng, Yihui Ding
, Available online   , Manuscript accepted  02 November 2020, doi: 10.1007/s00376-020-0209-1
Meiyu, typically occurring from mid-June to mid-July, on average, contributes to 32% of the annual precipitation over the Yangtze–Huai Rivers Valley (YHRV) and represents one of the three heavy-rainfall periods in China. Here we briefly review the large-scale background, synoptic organization, moisture transport and cloud and precipitation characteristics of the Meiyu frontal systems in the context of the ongoing Integrative Monsoon Frontal Rainfall Experiment (IMFRE) field campaign. Phase one of the campaign, IMFRE-I, was conducted from June 10 to July 10, 2018 in the middle reaches of the YHRV. Led by the Wuhan Institute of Heave Rain (IHR) with primary support from the National Natural Science Foundation of China, IMFRE-I maximizes the use of our observational capacity enabled by a suite of ground-based and remote sensing instruments, most notably the IHR Mesoscale Heavy Rainfall Observing System (MHROS), including different wavelengths of radars, microwave radiometer and disdrometers. The ShanXi King-Air (KA350) aircraft participating in the campaign is equipped with Ka-band cloud radar and different probes. The comprehensive datasets from both the MHROS and Aircraft instruments are combined with available satellite observations and model simulations to answer the three science questions of IMFRE-I. Some highlights from the JGR-IMFRE special issue are included in this review and we also briefly introduce the IMFRE-II field campaign to be conducted during June-July 2020, where the focus will be on the spatiotemporal evolutions of the Meiyu frontal systems over the middle and lower reaches of the YHRV.
News & Views
Phase Two of the Integrative Monsoon Frontal Rainfall Experiment (IMFRE-II) over the Middle and Lower Reaches of the Yangtze River in 2020
Chunguang CUI, Xiquan DONG, Bin WANG, Hao YANG
, Available online   , Manuscript accepted  30 September 2020, doi: 10.1007/s00376-020-0262-9
Phase Two of the Integrative Monsoon Frontal Rainfall Experiment (IMFRE-Ⅱ) was conducted over the middle and lower reaches of the Yangtze River during the period 16 June to 19 July 2020. This paper provides a brief overview of the IMFRE-II field campaign, including the multiple ground-based remote sensors, aircraft probes, and their corresponding measurements during the 2020 mei-yu period, as well as how to use these numerous datasets to answer scientific questions. The highlights of IMFRE-II are: (1) to the best of our knowledge, IMFRE-II is the first field campaign in China to use ground-based, airborne, and spaceborne platforms to conduct comprehensive observations over the middle and lower reaches of the Yangtze River; and (2) seven aircraft flights were successfully carried out, and the spectra of ice particles, cloud droplets, and raindrops at different altitudes were obtained. These in-situ measurements will provide a “cloud truth” to validate the ground-based and satellite-retrieved cloud and precipitation properties and quantitatively estimate their retrieval uncertainties. They are also crucial for the development of a warm (and/or cold) rain conceptual model in order to better understand the cloud-to-rain conversion and accretion processes in mei-yu precipitation events. Through an integrative analysis of ground-based, aircraft, and satellite observations and model simulations, we can significantly improve our cloud and precipitation retrieval algorithms, investigate the microphysical properties of cloud and precipitation, understand in-depth the formation and dissipation mechanisms of mei-yu frontal systems, and improve cloud microphysics parameterization schemes and model simulations.
A New TanSat XCO2 Global Product towards Climate Studies
Dongxu YANG, Yi LIU, Hartmut BOESCH, Lu YAO, Antonio DI NOIA, Zhaonan CAI, Naimeng LU, Daren LYU, Maohua WANG, Jing WANG, Zengshan YIN, Yuquan ZHENG
, Available online   , Manuscript accepted  21 September 2020, doi: 10.1007/s00376-020-0297-y
The 1st Chinese carbon dioxide (CO2) monitoring satellite mission, TanSat, was launched in 2016. The 1st TanSat global map of CO2 dry-air mixing ratio (XCO2) measurements over land was released as version 1 data product with an accuracy of 2.11 ppmv (parts per million by volume). In this paper, we introduce a new (version 2) TanSat global XCO2 product that is approached by the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS), and the European Space Agency (ESA) Climate Change Initiative plus (CCI+) TanSat XCO2 product by University of Leicester Full Physics (UoL-FP) retrieval algorithm. The correction of the measurement spectrum improves the accuracy (−0.08 ppmv) and precision (1.47 ppmv) of the new retrieval, which provides opportunity for further application in global carbon flux studies in the future. Inter-comparison between the two retrievals indicates a good agreement, with a standard deviation of 1.28 ppmv and a bias of −0.35 ppmv.
From China’s Heavy Precipitation in 2020 to a “Glocal” Hydrometeorological Solution for Flood Risk Prediction
Huan WU, Xiaomeng LI, Guy J.-P. SCHUMANN, Lorenzo ALFIERI, Yun CHEN, Hui XU, Zhifang WU, Hong LU, Yamin HU, Qiang ZHU, Zhijun HUANG, Weitian CHEN, Ying HU
, Available online   , Manuscript accepted  10 September 2020, doi: 10.1007/s00376-020-0260-y
The prolonged mei-yu/baiu system with anomalous precipitation in the year 2020 has swollen many rivers and lakes, caused flash flooding, urban flooding and landslides, and consistently wreaked havoc across large swathes of China, particularly in the Yangtze River basin. Significant precipitation and flooding anomalies have already been seen in magnitude and extension so far this year, which have been exerting much higher pressure on emergency responses in flood control and mitigation than in other years, even though a rainy season with multiple ongoing serious flood events in different provinces is not that uncommon in China. Instead of delving into the causes of the uniqueness of this year’s extreme precipitation-flooding situation, which certainly warrants in-depth exploration, in this article we provide a short view toward a more general hydrometeorological solution to this annual nationwide problem. A “glocal” (global to local) hydrometeorological solution for floods (GHS-F) is considered to be critical for better preparedness, mitigation, and management of different types of significant precipitation-caused flooding, which happen extensively almost every year in many countries such as China, India and the United States. Such a GHS-F model is necessary from both scientific and operational perspectives, with the strength in providing spatially consistent flood definitions and spatially distributed flood risk classification considering the heterogeneity in vulnerability and resilience across the entire domain. Priorities in the development of such a GHS-F are suggested, emphasizing the user’s requirements and needs according to practical experiences with various flood response agencies.
Letters & Notes
Seasonal Forecast of South China Sea Summer Monsoon Onset Disturbed by Cold Tongue La Niña in the Past Decade
Ning JIANG, Congwen ZHU
, Available online   , Manuscript accepted  10 September 2020, doi: 10.1007/s00376-020-0090-y
It has been suggested that a warm (cold) ENSO event in winter is mostly followed by a late (early) onset of the South China Sea (SCS) summer monsoon (SCSSM) in spring. Our results show this positive relationship, which is mainly determined by their phase correlation, has been broken under recent rapid global warming since 2011, due to the disturbance of cold tongue (CT) La Niña events. Different from its canonical counterpart, a CT La Niña event is characterized by surface meridional wind divergences in the central-eastern equatorial Pacific, which can delay the SCSSM onset by enhanced convections in the warming Indian Ocean and the western subtropical Pacific. Owing to the increased Indian−western Pacific warming and the prevalent CT La Niña events, empirical seasonal forecasting of SCSSM onset based on ENSO may be challenged in the future.
Meeting Summary
The First Fengyun Satellite International User Conference
Di XIAN, Peng ZHANG, Meng FANG, Chang LIU, Xu JIA
, Available online   , Manuscript accepted  09 March 2020, doi: 10.1007/s00376-020-2011-5