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2024-4 Contents
2024, 41(4): 1-1.
Abstract:
News & Views
Severe Global Environmental Issues Caused by Canada’s Record-Breaking Wildfires in 2023
Zhe WANG, Zifa WANG, Zhiyin ZOU, Xueshun CHEN, Huangjian WU, Wending WANG, Hang SU, Fang LI, Wenru XU, Zhihua LIU, Jiaojun ZHU
2024, 41(4): 565-571. doi: 10.1007/s00376-023-3241-0
Abstract:
Due to the record-breaking wildfires that occurred in Canada in 2023, unprecedented quantities of air pollutants and greenhouse gases were released into the atmosphere. The wildfires had emitted more than 1.3 Pg CO2 and 0.14 Pg CO2 equivalent of other greenhouse gases (GHG) including CH4 and N2O as of 31 August. The wildfire-related GHG emissions constituted more than doubled Canada’s planned cumulative anthropogenic emissions reductions in 10 years, which represents a significant challenge to climate mitigation efforts. The model simulations showed that the Canadian wildfires impacted not only the local air quality but also that of most areas in the northern hemisphere due to long-range transport, causing severe PM2.5 pollution in the northeastern United States and increasing daily mean PM2.5 concentration in northwestern China by up to 2 μg m–3. The observed maximum daily mean PM2.5 concentration in New York City reached 148.3 μg m–3, which was their worst air quality in more than 50 years, nearly 10 times that of the air quality guideline (i.e., 15 μg m–3) issued by the World Health Organization (WHO). Aside from the direct emissions from forest fires, the peat fires beneath the surface might smolder for several months or even longer and release substantial amounts of CO2. The substantial amounts of greenhouse gases from forest and peat fires might contribute to the positive feedback to the climate, potentially accelerating global warming. To better understand the comprehensive environmental effects of wildfires and their interactions with the climate system, more detailed research based on advanced observations and Earth System Models is essential.
CAS-ESM2.0 Successfully Reproduces Historical Atmospheric CO2 in a Coupled Carbon−Climate Simulation
Jiawen ZHU, Juanxiong HE, Duoying JI, Yangchun LI, He ZHANG, Minghua ZHANG, Xiaodong ZENG, Kece FEI, Jiangbo JIN
2024, 41(4): 572-580. doi: 10.1007/s00376-023-3172-9
Abstract:
The atmospheric carbon dioxide (CO2) concentration has been increasing rapidly since the Industrial Revolution, which has led to unequivocal global warming and crucial environmental change. It is extremely important to investigate the interactions among atmospheric CO2, the physical climate system, and the carbon cycle of the underlying surface for a better understanding of the Earth system. Earth system models are widely used to investigate these interactions via coupled carbon–climate simulations. The Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2.0) has successfully fixed a two-way coupling of atmospheric CO2 with the climate and carbon cycle on land and in the ocean. Using CAS-ESM2.0, we conducted a coupled carbon–climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment. This paper examines the modeled CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 at the two baseline sites, as well as over northern high latitudes. These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon–climate interactions, even though uncertainties remain in the processes involved. This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate, which will provide significant scientific support for climate research and China’s goal of carbon neutrality.
Will the Globe Encounter the Warmest Winter after the Hottest Summer in 2023?
Fei ZHENG, Shuai HU, Jiehua MA, Lin WANG, Kexin LI, Bo WU, Qing BAO, Jingbei PENG, Chaofan LI, Haifeng ZONG, Yao YAO, Baoqiang TIAN, Hong CHEN, Xianmei LANG, Fangxing FAN, Xiao DONG, Yanling ZHAN, Tao ZHU, Tianjun ZHOU, Jiang ZHU
2024, 41(4): 581-586. doi: 10.1007/s00376-023-3330-0
Abstract:
In the boreal summer and autumn of 2023, the globe experienced an extremely hot period across both oceans and continents. The consecutive record-breaking mean surface temperature has caused many to speculate upon how the global temperature will evolve in the coming 2023/24 boreal winter. In this report, as shown in the multi-model ensemble mean (MME) prediction released by the Institute of Atmospheric Physics at the Chinese Academy of Sciences, a medium-to-strong eastern Pacific El Niño event will reach its mature phase in the following 2−3 months, which tends to excite an anomalous anticyclone over the western North Pacific and the Pacific-North American teleconnection, thus serving to modulate the winter climate in East Asia and North America. Despite some uncertainty due to unpredictable internal atmospheric variability, the global mean surface temperature (GMST) in the 2023/24 winter will likely be the warmest in recorded history as a consequence of both the El Niño event and the long-term global warming trend. Specifically, the middle and low latitudes of Eurasia are expected to experience an anomalously warm winter, and the surface air temperature anomaly in China will likely exceed 2.4 standard deviations above climatology and subsequently be recorded as the warmest winter since 1991. Moreover, the necessary early warnings are still reliable in the timely updated medium-term numerical weather forecasts and sub-seasonal-to-seasonal prediction.
Southern Hemisphere Volcanism Triggered Multi-year La Niñas during the Last Millennium
Shangrong ZHOU, Fei LIU
2024, 41(4): 587-592. doi: 10.1007/s00376-023-3254-8
Abstract:
To explain the recent three-year La Niña event from 2020 to 2022, which has caused catastrophic weather events worldwide, Fasullo et al. (2023) demonstrated that the increase in biomass aerosol resulting from the 2019–20 Australian wildfire season could have triggered this multi-year La Niña. Here, we present compelling evidence from paleo-proxies, utilizing a substantial sample size of 26 volcanic eruptions in the Southern Hemisphere (SH), to support the hypothesis that ocean cooling in the SH can lead to a multi-year La Niña event. This research highlights the importance of focusing on the Southern Ocean, as current climate models struggle to accurately simulate the Pacific response driven by the Southern Ocean.
Original Paper
The 2022 Extreme Heatwave in Shanghai, Lower Reaches of the Yangtze River Valley: Combined Influences of Multiscale Variabilities
Ping LIANG, Zhiqi ZHANG, Yihui DING, Zeng-Zhen HU, Qi CHEN
2024, 41(4): 593-607. doi: 10.1007/s00376-023-3007-8
Abstract:
In the summer of 2022, China (especially the Yangtze River Valley, YRV) suffered its strongest heatwave (HW) event since 1961. In this study, we examined the influences of multiscale variabilities on the 2022 extreme HW in the lower reaches of the YRV, focusing on the city of Shanghai. We found that about 1/3 of the 2022 HW days in Shanghai can be attributed to the long-term warming trend of global warming. During mid-summer of 2022, an enhanced western Pacific subtropical high (WPSH) and anomalous double blockings over the Ural Mountains and Sea of Okhotsk, respectively, were associated with the persistently anomalous high pressure over the YRV, leading to the extreme HW. The Pacific Decadal Oscillation played a major role in the anomalous blocking pattern associated with the HW at the decadal time scale. Also, the positive phase of the Atlantic Multidecadal Oscillation may have contributed to regulating the formation of the double-blocking pattern. Anomalous warming of both the warm pool of the western Pacific and tropical North Atlantic at the interannual time scale may also have favored the persistency of the double blocking and the anomalously strong WPSH. At the subseasonal time scale, the anomalously frequent phases 2–5 of the canonical northward propagating variability of boreal summer intraseasonal oscillation associated with the anomalous propagation of a weak Madden–Julian Oscillation suppressed the convection over the YRV and also contributed to the HW. Therefore, the 2022 extreme HW originated from multiscale forcing including both the climate warming trend and air–sea interaction at multiple time scales.
The Unprecedented Extreme Anticyclonic Anomaly over Northeast Asia in July 2021 and Its Climatic Impacts
Xingyan ZHOU, Riyu LU
2024, 41(4): 608-618. doi: 10.1007/s00376-023-3026-5
Abstract:
This study investigates the evolution of an extreme anomalous anticyclone (AA) event over Northeast Asia, which was one of the dominant circulation systems responsible for the catastrophic extreme precipitation event in July 2021 in Henan, and further explores the significant impact of this AA on surface temperatures beneath it. The results indicate that this AA event over Northeast Asia was unprecedented in terms of intensity and duration. The AA was very persistent and extremely strong for 10 consecutive days from 13 to 22 July 2021. This long-lived and unprecedented AA led to the persistence of warmer surface temperatures beyond the temporal span of the pronounced 500-hPa anticyclonic signature as the surface air temperatures over land in Northeast Asia remained extremely warm through 29 July 2021. Moreover, the sea surface temperatures in the Sea of Japan/East Sea were extremely high for 30 consecutive days from 13 July to 11 August 2021, persisting well after the weakening or departure of this AA. These results emphasize the extreme nature of this AA over Northeast Asia in July 2021 and its role in multiple extreme climate events, even over remote regions. Furthermore, possible reasons for this long-lasting AA are explored, and it is suggested to be a byproduct of a teleconnection pattern over extratropical Eurasia during the first half of its life cycle, and of the Pacific–Japan teleconnection pattern during the latter half.
Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases
Yating ZHAO, Ming XUE, Jing JIANG, Xiao-Ming HU, Anning HUANG
2024, 41(4): 619-638. doi: 10.1007/s00376-023-2353-x
Abstract:
Assessment of past-climate simulations of regional climate models (RCMs) is important for understanding the reliability of RCMs when used to project future regional climate. Here, we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km, named WRFG, from the North American Regional Climate Change Assessment Program (NARCCAP) in simulating wet season precipitation over the Central United States for a period when observational data are available. The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer, although it tends to underestimate the magnitude of precipitation. This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation. Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor. The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between, leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains. The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence, for the development of moist convection as well. Therefore, a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.
The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity
Ming YING, Xiaoqin LU
2024, 41(4): 639-654. doi: 10.1007/s00376-023-3040-7
Abstract:
This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone (TC) best track data for the seasons 1949–1987 generated by the China Meteorological Administration (CMA). The evaluation of the reconnaissance data shows that the minimum central sea level pressure (MCP) data are relatively homogeneous, whereas the maximum sustained wind (MSW) data show both overestimations and spurious abrupt changes. Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset. Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data, two spurious changepoints were identified in the remainder of the best-track MCP data. Furthermore, the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance, which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind “observations”. In addition, the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades, which reflects the important influence of reconnaissance data on the CMA TC best track dataset. The wind–pressure relationship (WPR) used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW, which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.
Alignment of Track Oscillations during Tropical Cyclone Rapid Intensification
Tong XIE, Liguang WU, Yecheng FENG, Jinghua YU
2024, 41(4): 655-670. doi: 10.1007/s00376-023-3073-y
Abstract:
Recent studies on tropical cyclone (TC) intensity change indicate that the development of a vertically aligned TC circulation is a key feature of its rapid intensification (RI), however, understanding how vortex alignment occurs remains a challenging topic in TC intensity change research. Based on the simulation outputs of North Atlantic Hurricane Wilma (2005) and western North Pacific Typhoon Rammasun (2014), vortex track oscillations at different vertical levels and their associated role in vortex alignment are examined to improve our understanding of the vortex alignment during RI of TCs with initial hurricane intensity. It is found that vortex tracks at different vertical levels oscillate consistently in speed and direction during the RI of the two simulated TCs. While the consistent track oscillation reduces the oscillation tilt during RI, the reduction of vortex tilt results mainly from the mean track before RI. It is also found that the vortex tilt is primarily due to the mean vortex track before and after RI. The track oscillations are closely associated with wavenumber-1 vortex Rossby waves that are dominant wavenumber-1 circulations in the TC inner-core region. This study suggests that the dynamics of the wavenumber-1 vortex Rossby waves play an important role in the regulation of the physical processes associated with the track oscillation and vertical alignment of TCs.
A Tri-mode of Mock-Walker Cells
Han QIN, Ji NIE, Zhiyong MENG
2024, 41(4): 671-679. doi: 10.1007/s00376-023-3032-7
Abstract:
This work uses cloud-resolving simulations to study mock-Walker cells driven by a specified sea surface temperature (SST). The associated precipitation in the mock-Walker cells exhibits three different modes, including a single peak of precipitation over the SST maximum (mode 1), symmetric double peaks of precipitation straddling the SST maximum (mode 2), and a single peak of precipitation on one side of the SST maximum (mode 3). The three modes are caused by three distinct convective activity center migration traits. Analyses indicate that the virtual effect of water vapor plays an important role in differentiating the three modes. When the SST gradient is large, the virtual effect may be strong enough to overcome the temperature effect, generating a low-level low-pressure anomaly below the ascending branch of the Walker cell off the center. The results here highlight the importance of the virtual effect of water vapor and its interaction with convection and large-scale circulation in the Walker circulation.
Cloud Top Pressure Retrieval Using Polarized and Oxygen A-band Measurements from GF5 and PARASOL Satellites
Lesi WEI, Huazhe SHANG, Jian XU, Chong SHI, Gegen TANA, Kefu CHAO, Shanhu BAO, Liangfu CHEN, Husi LETU
2024, 41(4): 680-700. doi: 10.1007/s00376-023-2382-5
Abstract:
Cloud top pressure (CTP) is one of the critical cloud properties that significantly affects the radiative effect of clouds. Multi-angle polarized sensors can employ polarized bands (490 nm) or O2 A-bands (763 and 765 nm) to retrieve the CTP. However, the CTP retrieved by the two methods shows inconsistent results in certain cases, and large uncertainties in low and thin cloud retrievals, which may lead to challenges in subsequent applications. This study proposes a synergistic algorithm that considers both O2 A-bands and polarized bands using a random forest (RF) model. LiDAR CTP data are used as the true values and the polarized and non-polarized measurements are concatenated to train the RF model to determine CTP. Additionally, through analysis, we proposed that the polarized signal becomes saturated as the cloud optical thickness (COT) increases, necessitating a particular treatment for cases where COT < 10 to improve the algorithm's stability. The synergistic method was then applied to the directional polarized camera (DPC) and Polarized and Directionality of the Earth’s Reflectance (POLDER) measurements for evaluation, and the resulting retrieval accuracy of the POLDER-based measurements (RMSEPOLDER = 205.176 hPa, RMSEDPC = 171.141 hPa, R2POLDER = 0.636, R2DPC = 0.663, respectively) were higher than that of the MODIS and POLDER Rayleigh pressure measurements. The synergistic algorithm also showed good performance with the application of DPC data. This algorithm is expected to provide data support for atmosphere-related fields as an atmospheric remote sensing algorithm within the Cloud Application for Remote Sensing, Atmospheric Radiation, and Updating Energy (CARE) platform.
Climate–Vegetation Coverage Interactions in the Hengduan Mountains Area, Southeastern Tibetan Plateau, and Their Downstream Effects
Congxi FANG, Jinlei CHEN, Chaojun OUYANG, Lu WANG, Changfeng SUN, Quan ZHANG, Jun WEN
2024, 41(4): 701-716. doi: 10.1007/s00376-023-3077-7
Abstract:
Little is known about the mechanism of climate–vegetation coverage coupled changes in the Tibetan Plateau (TP) region, which is the most climatically sensitive and ecologically fragile region with the highest terrain in the world. This study, using multisource datasets (including satellite data and meteorological observations and reanalysis data) revealed the mutual feedback mechanisms between changes in climate (temperature and precipitation) and vegetation coverage in recent decades in the Hengduan Mountains Area (HMA) of the southeastern TP and their influences on climate in the downstream region, the Sichuan Basin (SCB). There is mutual facilitation between rising air temperature and increasing vegetation coverage in the HMA, which is most significant during winter, and then during spring, but insignificant during summer and autumn. Rising temperature significantly enhances local vegetation coverage, and vegetation greening in turn heats the atmosphere via enhancing net heat flux from the surface to the atmosphere. The atmospheric heating anomaly over the HMA thickens the atmospheric column and increases upper air pressure. The high pressure anomaly disperses downstream via the westerly flow, expands across the SCB, and eventually increases the SCB temperature. This effect lasts from winter to the following spring, which may cause the maximum increasing trend of the SCB temperature and vegetation coverage in spring. These results are helpful for estimating future trends in climate and eco-environmental variations in the HMA and SCB under warming scenarios, as well as seasonal forecasting based on the connection between the HMA eco-environment and SCB climate.
Impact of Initial Soil Conditions on Soil Hydrothermal and Surface Energy Fluxes in the Permafrost Region of the Tibetan Plateau
Siqiong LUO, Zihang CHEN, Jingyuan WANG, Tonghua WU, Yao XIAO, Yongping QIAO
2024, 41(4): 717-736. doi: 10.1007/s00376-023-3100-z
Abstract:
Accurate initial soil conditions play a crucial role in simulating soil hydrothermal and surface energy fluxes in land surface process modeling. This study emphasized the influence of the initial soil temperature (ST) and soil moisture (SM) conditions on a land surface energy and water simulation in the permafrost region in the Tibetan Plateau (TP) using the Community Land Model version 5.0 (CLM5.0). The results indicate that the default initial schemes for ST and SM in CLM5.0 were simplistic, and inaccurately represented the soil characteristics of permafrost in the TP which led to underestimating ST during the freezing period while overestimating ST and underestimating SLW during the thawing period at the XDT site. Applying the long-term spin-up method to obtain initial soil conditions has only led to limited improvement in simulating soil hydrothermal and surface energy fluxes. The modified initial soil schemes proposed in this study comprehensively incorporate the characteristics of permafrost, which coexists with soil liquid water (SLW), and soil ice (SI) when the ST is below freezing temperature, effectively enhancing the accuracy of the simulated soil hydrothermal and surface energy fluxes. Consequently, the modified initial soil schemes greatly improved upon the results achieved through the long-term spin-up method. Three modified initial soil schemes experiments resulted in a 64%, 88%, and 77% reduction in the average mean bias error (MBE) of ST, and a 13%, 21%, and 19% reduction in the average root-mean-square error (RMSE) of SLW compared to the default simulation results. Also, the average MBE of net radiation was reduced by 7%, 22%, and 21%.
Persistent Variations in the East Asian Trough from March to April and the Possible Mechanism
Shui YU, Jianqi SUN
2024, 41(4): 737-753. doi: 10.1007/s00376-023-3024-7
Abstract:
The East Asian trough (EAT) profoundly influences the East Asian spring climate. In this study, the relationship of the EATs among the three spring months is investigated. Correlation analysis shows that the variation in March EAT is closely related to that of April EAT. Extended empirical orthogonal function (EEOF) analysis also confirms the co-variation of the March and April EATs. The positive/negative EEOF1 features the persistent strengthened/weakened EAT from March to April. Further investigation indicates that the variations in EEOF1 are related to a dipole sea surface temperature (SST) pattern over the North Atlantic and the SST anomaly over the tropical Indian Ocean. The dipole SST pattern over the North Atlantic, with one center east of Newfoundland Island and another east of Bermuda, could trigger a Rossby wave train to influence the EAT in March−April. The SST anomaly over the tropical Indian Ocean can change the Walker circulation and influence the atmospheric circulation over the tropical western Pacific, subsequently impacting the southern part of the EAT in March−April. Besides the SST factors, the Northeast Asian snow cover could change the regional thermal conditions and lead to persistent EAT anomalies from March to April. These three impact factors are generally independent of each other, jointly explaining large variations in the EAT EEOF1. Moreover, the signals of the three factors could be traced back to February, consequently providing a potential prediction source for the EAT variation in March and April.
Data Description Article
Shallow Convection Dataset Simulated by Three Different Large Eddy Models
Yaxin ZHAO, Xiaocong WANG, Yimin LIU, Guoxiong WU, Yanjie LIU
2024, 41(4): 754-766. doi: 10.1007/s00376-023-3106-6
Abstract:
Shallow convection plays an important role in transporting heat and moisture from the near-surface to higher altitudes, yet its parameterization in numerical models remains a great challenge, partly due to the lack of high-resolution observations. This study describes a large eddy simulation (LES) dataset for four shallow convection cases that differ primarily in inversion strength, which can be used as a surrogate for real data. To reduce the uncertainty in LES modeling, three different large eddy models were used, including SAM (System for Atmospheric Modeling), WRF (Weather Research and Forecasting model), and UCLA-LES. Results show that the different models generally exhibit similar behavior for each shallow convection case, despite some differences in the details of the convective structure. In addition to grid-averaged fields, conditionally sampled variables, such as in-cloud moisture and vertical velocity, are also provided, which are indispensable for calculation of the entrainment/detrainment rate. Considering the essentiality of the entraining/detraining process in the parameterization of cumulus convection, the dataset presented in this study is potentially useful for validation and improvement of the parameterization of shallow convection.