Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4465-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-4465-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
21 Jul 2021
Model experiment description paper |
| 21 Jul 2021
| 21 Jul 2021
Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): organization and experimental design
University of California, Los Angeles, CA 90095, USA
Tandong Yao
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Aaron A. Boone
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Ismaila Diallo
University of California, Los Angeles, CA 90095, USA
University of California, Los Angeles, CA 90095, USA
Xubin Zeng
University of Arizona, Tucson, USA
William K. M. Lau
Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, USA
Shiori Sugimoto
Japan Agency for Marine Earth Science and Technology (JAMSTEC), Yokohama, Japan
Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
Xiaoduo Pan
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Peter J. van Oevelen
International GEWEX Project Office, George Mason University, Fairfax, VA 22030, USA
Daniel Klocke
Max Planck Institute for Meteorology, 20146, Hamburg, DeutschlandTS4
Myung-Seo Koo
Korea Institute of Atmospheric Prediction Systems, Seoul, South Korea
Tomonori Sato
Hokkaido University, Sapporo, Japan
Zhaohui Lin
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Yuhei Takaya
Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan
Constantin Ardilouze
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Stefano Materia
Climate Simulation and Prediction (CSP), Fondazione Centro
Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), Bologna, Italy
Subodh K. Saha
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune,
India
Retish Senan
European Centre for Medium-range Weather Forecasts (ECMWF), Reading, UK
Tetsu Nakamura
Hokkaido University, Sapporo, Japan
Hailan Wang
National Center for Environmental Prediction (NCEP)/National Weather
Service/National Oceanic and Atmospheric Administration (NOAA), College Park, USA
Jing Yang
Beijing Normal University, Beijing, China
Hongliang Zhang
National Meteorology Center, China Meteorological Administration, Beijing, China
Mei Zhao
Bureau of Meteorology, Melbourne, Australia
Xin-Zhong Liang
Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, USA
J. David Neelin
University of California, Los Angeles, CA 90095, USA
Frederic Vitart
European Centre for Medium-range Weather Forecasts (ECMWF), Reading, UK
Xin Li
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Ping Zhao
Chinese Academy of Meteorological Sciences, China Meteorological
Administration, Beijing, China
Chunxiang Shi
National Meteorological Information Center, China Meteorological
Administration, Beijing, China
Weidong Guo
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Jianping Tang
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Nanjing University of Information Science and Technology, Nanjing 210044, China
Yun Qian
Pacific Northwest National Laboratory, Richland, WA 99352, USA
Samuel S. P. Shen
San Diego State University, San Diego, USA
Yang Zhang
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Tsinghua University, Beijing, China
Ruby Leung
Pacific Northwest National Laboratory, Richland, WA 99352, USA
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Daniele Peano
Climate Simulation and Prediction (CSP), Fondazione Centro
Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), Bologna, Italy
Beijing Normal University, Beijing, China
Yanling Zhan
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Michael A. Brunke
University of Arizona, Tucson, USA
Sin Chan Chou
National Institute for Space Research (INPE), Cachoeira Paulista, Brazil
Michael Ek
National Center for Atmospheric Research (NCAR), Boulder, USA
Tianyi Fan
Beijing Normal University, Beijing, China
Korea Institute of Atmospheric Prediction Systems, Seoul, South Korea
Hong Guan
Systems Research Group Inc at Environment Modeling Center, NCEP/NWS/NOAA, College Park, USA
Environment and Climate Change Canada, Dorval, Canada
Shunlin Liang
University of Maryland, College Park, USA
Helin Wei
National Center for Environmental Prediction (NCEP)/National Weather
Service/National Oceanic and Atmospheric Administration (NOAA), College Park, USA
Shaocheng Xie
Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
Haoran Xu
Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, USA
Weiping Li
National Climate Center, China Meteorological Administration, Beijing, China
Xueli Shi
National Climate Center, China Meteorological Administration, Beijing, China
Paulo Nobre
National Institute for Space Research (INPE), Cachoeira Paulista, Brazil
Yan Pan
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Yi Qin
Tsinghua University, Beijing, China
Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
Jeff Dozier
University of California, Santa Barbara, USA
Craig R. Ferguson
Atmospheric Sciences Research Center, University at Albany, State
University of New York, Albany, NY 12203, USA
Gianpaolo Balsamo
European Centre for Medium-range Weather Forecasts (ECMWF), Reading, UK
Qing Bao
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and
Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Jinming Feng
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Jinkyu Hong
Yonsei University, Seoul, South Korea
Songyou Hong
Korea Institute of Atmospheric Prediction Systems, Seoul, South Korea
Huilin Huang
University of California, Los Angeles, CA 90095, USA
Duoying Ji
Beijing Normal University, Beijing, China
Zhenming Ji
Sun Yat-Sen University, Guangzhou, China
Shichang Kang
Northwest Institute of Eco-environment and Resources, Chinese Academy of
Sciences, Lanzhou, China
University of Chinese Academy of Sciences, Beijing, 100101, China
Yanluan Lin
Tsinghua University, Beijing, China
Weiguang Liu
University of Connecticut, Storrs, USA
Nanjing University of Information Science and Technology, Nanjing 210044, China
Ryan Muncaster
Environment and Climate Change Canada, Dorval, Canada
Patricia de Rosnay
European Centre for Medium-range Weather Forecasts (ECMWF), Reading, UK
Hiroshi G. Takahashi
Tokyo Metropolitan University, Tokyo, Japan
Guiling Wang
University of Connecticut, Storrs, USA
Shuyu Wang
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune,
India
Weicai Wang
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Yuejian Zhu
National Center for Environmental Prediction (NCEP)/National Weather
Service/National Oceanic and Atmospheric Administration (NOAA), College Park, USA
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Dongyu Feng, Zeli Tan, Darren Engwirda, Jonathan D. Wolfe, Donghui Xu, Chang Liao, Gautam Bisht, James J. Benedict, Tian Zhou, Mithun Deb, Hong-Yi Li, and L. Ruby Leung
EGUsphere, https://doi.org/10.5194/egusphere-2024-2785, https://doi.org/10.5194/egusphere-2024-2785, 2024
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Our study explores how riverine and coastal flooding during hurricanes is influenced by the interaction of atmosphere, land, river and ocean conditions. Using an advanced Earth system model, we simulate Hurricane Irene to evaluate how meteorological and hydrological uncertainties affect flood modeling. Our findings reveal the importance of a multi-component modeling system, how hydrological conditions play critical roles in flood modeling, and greater flood risks if multiple factors are present.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian M. Grams
Nat. Hazards Earth Syst. Sci., 24, 2995–3012, https://doi.org/10.5194/nhess-24-2995-2024, https://doi.org/10.5194/nhess-24-2995-2024, 2024
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Extreme rainfall is the leading weather-related source of damages in Europe, but it is still difficult to predict on long timescales. A recent example of this was the devastating floods in the Italian region of Emiglia Romagna in May 2023. We present perspectives based on large-scale dynamical information that allows us to better understand and predict such events.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-151, https://doi.org/10.5194/gmd-2024-151, 2024
Revised manuscript under review for GMD
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This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
Bing Li, Shunlin Liang, Han Ma, Guanpeng Dong, Xiaobang Liu, Tao He, and Yufang Zhang
Earth Syst. Sci. Data, 16, 3795–3819, https://doi.org/10.5194/essd-16-3795-2024, https://doi.org/10.5194/essd-16-3795-2024, 2024
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This study describes 1 km all-weather instantaneous and daily mean land surface temperature (LST) datasets on the global scale during 2000–2020. It is the first attempt to synergistically estimate all-weather instantaneous and daily mean LST data on a long global-scale time series. The generated datasets were evaluated by the observations from in situ stations and other LST datasets, and the evaluation indicated that the dataset is sufficiently reliable.
Amali A. Amali, Clemens Schwingshackl, Akihiko Ito, Alina Barbu, Christine Delire, Daniele Peano, David M. Lawrence, David Wårlind, Eddy Robertson, Edouard L. Davin, Elena Shevliakova, Ian N. Harman, Nicolas Vuichard, Paul A. Miller, Peter J. Lawrence, Tilo Ziehn, Tomohiro Hajima, Victor Brovkin, Yanwu Zhang, Vivek K. Arora, and Julia Pongratz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2460, https://doi.org/10.5194/egusphere-2024-2460, 2024
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Our study explored the impact of anthropogenic land-use change (LUC) on climate dynamics, focusing on biogeophysical (BGP) and biogeochemical (BGC) effects using data from the CMIP6-LUMIP project. We found that LUC-induced carbon emissions contribute to a BGC warming of 0.20 °C, with BGC effects dominating globally over BGP effects, which show regional variability. Our findings highlight discrepancies in model simulations and emphasise the need for improved representations of LUC processes.
Malcolm John Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-2582, https://doi.org/10.5194/egusphere-2024-2582, 2024
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HighResMIP2 is a model intercomparison project focussing on high resolution global climate models, that is those with grid spacings of 25 km or less in atmosphere and ocean, using simulations of decades to a century or so in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present day and future projections, and to build links with other communities to provide more robust climate information.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-149, https://doi.org/10.5194/gmd-2024-149, 2024
Revised manuscript accepted for GMD
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.
Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, Margarita Choulga, Souhail Boussetta, Maria Kalweit, Joschka Bödecker, Carsten F. Dormann, Florian Pappenberger, and Gianpaolo Balsamo
EGUsphere, https://doi.org/10.5194/egusphere-2024-2081, https://doi.org/10.5194/egusphere-2024-2081, 2024
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We compared spatio-temporal forecast performances of three popular machine learning approaches that learned processes of water and energy exchange on the earth surface from a large physical model. The forecasting models were developed with reanalysis data and simulations on a European scale and transferred to the Globe. We found that all approaches deliver highly accurate predictions until long time horizons, implying their usefulness to advance land surface forecasting when data is available.
Mingjie Shi, Nate McDowell, Huilin Huang, Faria Zahura, Lingcheng Li, and Xingyuan Chen
EGUsphere, https://doi.org/10.22541/au.171053013.30286044/v2, https://doi.org/10.22541/au.171053013.30286044/v2, 2024
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Using Moderate Resolution Imaging Spectroradiometer data products, we quantitatively estimate the resistance and resilience of ecosystem functions to wildfires that occurred in the Columbia River Basin in 2015. Carbon state exhibits lower resistance and resilience than the ecosystem fluxes. The random forest feature importance analysis indicates that burn severity plays a minor role in the resilience of grassland, while it has a relatively major role in the resilience of forest and savanna.
Edward H. Bair, Dar A. Roberts, David R. Thompson, Philip G. Brodrick, Brenton A. Wilder, Niklas Bohn, Chris J. Crawford, Nimrod Carmon, Carrie M. Vuyovich, and Jeff Dozier
EGUsphere, https://doi.org/10.5194/egusphere-2024-1681, https://doi.org/10.5194/egusphere-2024-1681, 2024
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Key to the success of future satellite missions is understanding snowmelt in our warming climate, having implications for nearly 2 billion people. An obstacle is that an artifact, called the hook, is often mistaken for soot or dust. Instead it is caused by 3 amplifying effects: 1) a background reflectance that is too dark; 2) level terrain assumptions; 3) and differences in optical constants of ice. Sensor calibration and directional effects may also contribute. Solutions are presented.
Ye Liu, Yun Qian, Larry K. Berg, Zhe Feng, Jianfeng Li, Jingyi Chen, and Zhao Yang
Atmos. Chem. Phys., 24, 8165–8181, https://doi.org/10.5194/acp-24-8165-2024, https://doi.org/10.5194/acp-24-8165-2024, 2024
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Deep convection under various large-scale meteorological patterns (LSMPs) shows distinct precipitation features. In southeastern Texas, mesoscale convective systems (MCSs) contribute significantly to precipitation year-round, while isolated deep convection (IDC) is prominent in summer and fall. Self-organizing maps (SOMs) reveal convection can occur without large-scale lifting or moisture convergence. MCSs and IDC events have distinct life cycles influenced by specific LSMPs.
Tanguy Lunel, Maria Antonia Jimenez, Joan Cuxart, Daniel Martinez-Villagrasa, Aaron Boone, and Patrick Le Moigne
Atmos. Chem. Phys., 24, 7637–7666, https://doi.org/10.5194/acp-24-7637-2024, https://doi.org/10.5194/acp-24-7637-2024, 2024
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During the summer in Catalonia, a cool wind, the marinada, blows into the eastern Ebro basin in the afternoon. This study investigates its previously unclear dynamics using observations and a meteorological model. It is found to be driven by a cool marine air mass that flows over the mountains into the basin. The study shows how the sea breeze, upslope winds, larger weather patterns and irrigation play a prominent role in the formation and characteristics of the marinada.
Ye Liu, Timothy W. Juliano, Raghavendra Krishnamurthy, Brian J. Gaudet, and Jungmin Lee
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-76, https://doi.org/10.5194/wes-2024-76, 2024
Revised manuscript accepted for WES
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Our study reveals how different weather patterns influence wind conditions off the U.S. West Coast. We identified key weather patterns affecting wind speeds at potential wind farm sites using advanced machine learning. This research helps improve weather prediction models, making wind energy production more reliable and efficient.
Jinbo Xie, Qi Tang, Michael Prather, Jadwiga Richter, and Shixuan Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1927, https://doi.org/10.5194/egusphere-2024-1927, 2024
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Analysis of the interaction between the climate and ozone in the stratosphere is complicated by the in-ability climate model in simulating the Quasi-Biennial Oscillation (QBO) – an important climate mode in the stratosphere. We use a set of model simulation that realistically simulate QBO and a novel ozone diagnostic tool to separate the temperature and circulation-driven QBO impact. These are important for diagnosing model-model differences in the QBO-ozone responses for climate projections.
Yaoming Ma, Zhipeng Xie, Yingying Chen, Shaomin Liu, Tao Che, Ziwei Xu, Lunyu Shang, Xiaobo He, Xianhong Meng, Weiqiang Ma, Baiqing Xu, Huabiao Zhao, Junbo Wang, Guangjian Wu, and Xin Li
Earth Syst. Sci. Data, 16, 3017–3043, https://doi.org/10.5194/essd-16-3017-2024, https://doi.org/10.5194/essd-16-3017-2024, 2024
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Current models and satellites struggle to accurately represent the land–atmosphere (L–A) interactions over the Tibetan Plateau. We present the most extensive compilation of in situ observations to date, comprising 17 years of data on L–A interactions across 12 sites. This quality-assured benchmark dataset provides independent validation to improve models and remote sensing for the region, and it enables new investigations of fine-scale L–A processes and their mechanistic drivers.
Johannes Mülmenstädt, Edward Gryspeerdt, Sudhakar Dipu, Johannes Quaas, Andrew S. Ackerman, Ann M. Fridlind, Florian Tornow, Susanne E. Bauer, Andrew Gettelman, Yi Ming, Youtong Zheng, Po-Lun Ma, Hailong Wang, Kai Zhang, Matthew W. Christensen, Adam C. Varble, L. Ruby Leung, Xiaohong Liu, David Neubauer, Daniel G. Partridge, Philip Stier, and Toshihiko Takemura
Atmos. Chem. Phys., 24, 7331–7345, https://doi.org/10.5194/acp-24-7331-2024, https://doi.org/10.5194/acp-24-7331-2024, 2024
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Human activities release copious amounts of small particles called aerosols into the atmosphere. These particles change how much sunlight clouds reflect to space, an important human perturbation of the climate, whose magnitude is highly uncertain. We found that the latest climate models show a negative correlation but a positive causal relationship between aerosols and cloud water. This means we need to be very careful when we interpret observational studies that can only see correlation.
Guta Wakbulcho Abeshu, Hong-Yi Li, Mingjie Shi, and Ruby Leung
EGUsphere, https://doi.org/10.5194/egusphere-2024-1748, https://doi.org/10.5194/egusphere-2024-1748, 2024
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This study examined how water availability, climate dryness, and plant productivity interact at the catchment scale. Using various indices and statistical methods, it found a 0–2-month lag in these interactions. Strong correlations during peak productivity months were observed, with a notable hysteresis effect in vegetation response to changes in water availability and climate dryness. The findings help better understand catchment responses to climate variability.
Jianfeng Li, Andrew Geiss, Zhe Feng, L. Ruby Leung, Yun Qian, and Wenjun Cui
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-112, https://doi.org/10.5194/essd-2024-112, 2024
Preprint under review for ESSD
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We develop a high-resolution (4 km and hourly) observational derecho dataset over the United States east of the Rocky Mountains from 2004 to 2021 by using a mesoscale convective system dataset, bow echo detection based on a machine learning method, hourly gust speed measurements, and physically based identification criteria.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William Sacks, Ethan Coon, and Robert Hetland
EGUsphere, https://doi.org/10.5194/egusphere-2024-1555, https://doi.org/10.5194/egusphere-2024-1555, 2024
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We integrate E3SM land model (ELM) with the WRF Model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) – Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM, and ESMF caps for ELM initialization, execution, and finalization. The LILAC-ESMF framework maintains the integrity of the ELM’s source code structure and facilitates the transfer of future developments in LSMs to WRF-ELM.
Tapio Schneider, L. Ruby Leung, and Robert C. J. Wills
Atmos. Chem. Phys., 24, 7041–7062, https://doi.org/10.5194/acp-24-7041-2024, https://doi.org/10.5194/acp-24-7041-2024, 2024
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Climate models are crucial for predicting climate change in detail. This paper proposes a balanced approach to improving their accuracy by combining traditional process-based methods with modern artificial intelligence (AI) techniques while maximizing the resolution to allow for ensemble simulations. The authors propose using AI to learn from both observational and simulated data while incorporating existing physical knowledge to reduce data demands and improve climate prediction reliability.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
EGUsphere, https://doi.org/10.5194/egusphere-2024-1678, https://doi.org/10.5194/egusphere-2024-1678, 2024
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The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two end members of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented super-sites.
Jasper M. C. Denissen, Adriaan J. Teuling, Sujan Koirala, Markus Reichstein, Gianpaolo Balsamo, Martha M. Vogel, Xin Yu, and René Orth
Earth Syst. Dynam., 15, 717–734, https://doi.org/10.5194/esd-15-717-2024, https://doi.org/10.5194/esd-15-717-2024, 2024
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Heat extremes have severe implications for human health and ecosystems. Heat extremes are mostly introduced by large-scale atmospheric circulation but can be modulated by vegetation. Vegetation with access to water uses solar energy to evaporate water into the atmosphere. Under dry conditions, water may not be available, suppressing evaporation and heating the atmosphere. Using climate projections, we show that regionally less water is available for vegetation, intensifying future heat extremes.
Ziming Ke, Qi Tang, Jean-Christoophe Golaz, Xiaohong Liu, and Hailong Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1612, https://doi.org/10.5194/egusphere-2024-1612, 2024
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By treating volcanic emission interactively, model results improve simulated temperature variability, showing better correlations for 1940–1959 and 1960–1979, and reveals how volcanic activity influences cloud behavior and climate.
Ross J. Herbert, Andrew I. L. Williams, Philipp Weiss, Duncan Watson-Parris, Elisabeth Dingley, Daniel Klocke, and Philip Stier
EGUsphere, https://doi.org/10.5194/egusphere-2024-1689, https://doi.org/10.5194/egusphere-2024-1689, 2024
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Clouds exist at scales that climate models struggle to represent, limiting our knowledge of how climate change may impact clouds. Here we use a new km-scale global model representing an important step towards the necessary scale. We focus on how aerosol particles modify clouds, radiation, and precipitation. We find the magnitude and manner of responses tend to vary from region to region, highlighting the potential of global km-scale simulations and a need to represent aerosols in climate models.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-79, https://doi.org/10.5194/gmd-2024-79, 2024
Preprint under review for GMD
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Earth System Models (ESMs) struggle the uncertainties associated with parameterizing sub-grid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran-Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity and effectiveness.
Elena Bianco, Doroteaciro Iovino, Simona Masina, Stefano Materia, and Paolo Ruggieri
The Cryosphere, 18, 2357–2379, https://doi.org/10.5194/tc-18-2357-2024, https://doi.org/10.5194/tc-18-2357-2024, 2024
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Changes in ocean heat transport and surface heat fluxes in recent decades have altered the Arctic Ocean heat budget and caused warming of the upper ocean. Using two eddy-permitting ocean reanalyses, we show that this has important implications for sea ice variability. In the Arctic regional seas, upper-ocean heat content acts as an important precursor for sea ice anomalies on sub-seasonal timescales, and this link has strengthened since the 2000s.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Sophie Barthelemy, Bertrand Bonan, Miquel Tomas-Burguera, Gilles Grandjean, Séverine Bernardie, Jean-Philippe Naulin, Patrick Le Moigne, Aaron Boone, and Jean-Christophe Calvet
EGUsphere, https://doi.org/10.5194/egusphere-2024-1079, https://doi.org/10.5194/egusphere-2024-1079, 2024
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A drought index is developed that quantifies drought on an annual scale for deciduous broadleaf vegetation, making it applicable to monitoring clay shrinkage damage to buildings, agriculture or forestry. It is found that significant soil moisture drought events occurred in France in 2003, 2018, 2019, 2020 and 2022. Particularly high index values are observed throughout the country in 2022. It is also found that droughts will become more severe in the future.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Wangbin Shen, Zhaohui Lin, Zhengkun Qin, and Juan Li
Geosci. Model Dev., 17, 3447–3465, https://doi.org/10.5194/gmd-17-3447-2024, https://doi.org/10.5194/gmd-17-3447-2024, 2024
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In this study, a land surface image assimilation system capable of optimizing the spatial structure of the background field is constructed by introducing the curvelet analysis method and taking the similarity of image structure as a weak constraint. The findings demonstrate that the assimilation of surface soil moisture observation images effectively and reasonably enhances the spatial structure of soil moisture analysis field.
Lingcheng Li, Gautam Bisht, Dalei Hao, and L. Ruby Leung
Earth Syst. Sci. Data, 16, 2007–2032, https://doi.org/10.5194/essd-16-2007-2024, https://doi.org/10.5194/essd-16-2007-2024, 2024
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This study fills a gap to meet the emerging needs of kilometer-scale Earth system modeling by developing global 1 km land surface parameters for land use, vegetation, soil, and topography. Our demonstration simulations highlight the substantial impacts of these parameters on spatial variability and information loss in water and energy simulations. Using advanced explainable machine learning methods, we identified influential factors driving spatial variability and information loss.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Chaman Gul, Shichang Kang, Yuanjian Yang, Xinlei Ge, and Dong Guo
EGUsphere, https://doi.org/10.5194/egusphere-2024-1144, https://doi.org/10.5194/egusphere-2024-1144, 2024
Preprint archived
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Long-term variations in upper atmospheric temperature and water vapor in the selected domains of time and space are presented. The temperature during the past two decades showed a cooling trend and water vapor showed an increasing trend and had an inverse relation with temperature in selected domains of space and time. Seasonal temperature variations are distinct, with a summer minimum and a winter maximum. Our results can be an early warning indication for future climate change.
Weiming Ma, Hailong Wang, Gang Chen, Yun Qian, Ian Baxter, Yiling Huo, and Mark W. Seefeldt
Atmos. Chem. Phys., 24, 4451–4472, https://doi.org/10.5194/acp-24-4451-2024, https://doi.org/10.5194/acp-24-4451-2024, 2024
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Extreme warming events with surface temperature going above 0°C can occur in the high-Arctic winter. Although reanalysis data show that these events were short-lived and occurred rarely during 1980–2021, they have become more frequent, stronger, and longer lasting latterly. A dipole pattern, comprising high- and low-pressure systems, is found to be the key in driving them. These findings have implications for the recent changes in sea ice, hydrological cycle, and ecosystem over the Arctic.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Jianzhong Xu, Xinghua Zhang, Wenhui Zhao, Lixiang Zhai, Miao Zhong, Jinsen Shi, Junying Sun, Yanmei Liu, Conghui Xie, Yulong Tan, Kemei Li, Xinlei Ge, Qi Zhang, and Shichang Kang
Earth Syst. Sci. Data, 16, 1875–1900, https://doi.org/10.5194/essd-16-1875-2024, https://doi.org/10.5194/essd-16-1875-2024, 2024
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A comprehensive aerosol observation project was carried out in the Tibetan Plateau (TP) and its surroundings in recent years to investigate the properties and sources of atmospheric aerosols as well as their regional differences by performing multiple intensive field observations. The release of this dataset can provide basic and systematic data for related research in the atmospheric, cryospheric, and environmental sciences in this unique region.
Lingbo Li, Hong-Yi Li, Guta Abeshu, Jinyun Tang, L. Ruby Leung, Chang Liao, Zeli Tan, Hanqin Tian, Peter Thornton, and Xiaojuan Yang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-43, https://doi.org/10.5194/essd-2024-43, 2024
Revised manuscript under review for ESSD
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We have developed a new map that reveals how organic carbon from soil leaches into headwater streams over the contiguous United States. We use advanced artificial intelligence techniques and a massive amount of data, including observations at over 2,500 gauges and a wealth of climate and environmental information. The map is a critical step in understanding and predicting how carbon moves through our environment, hence a useful tool for tackling climate challenges.
Gaoyun Wang, Rong Fu, Yizhou Zhuang, Paul A. Dirmeyer, Joseph A. Santanello, Guiling Wang, Kun Yang, and Kaighin McColl
Atmos. Chem. Phys., 24, 3857–3868, https://doi.org/10.5194/acp-24-3857-2024, https://doi.org/10.5194/acp-24-3857-2024, 2024
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This study investigates the influence of lower-tropospheric humidity on land–atmosphere coupling (LAC) during warm seasons in the US Southern Great Plains. Using radiosonde data and a buoyancy model, we find that elevated LT humidity is crucial for generating afternoon precipitation events under dry soil conditions not accounted for by conventional LAC indices. This underscores the importance of considering LT humidity in understanding LAC over dry soil during droughts in the SGP.
Lindsay M. Sheridan, Raghavendra Krishnamurthy, William I. Gustafson Jr., Ye Liu, Brian J. Gaudet, Nicola Bodini, Rob K. Newsom, and Mikhail Pekour
Wind Energ. Sci., 9, 741–758, https://doi.org/10.5194/wes-9-741-2024, https://doi.org/10.5194/wes-9-741-2024, 2024
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In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas and provided valuable year-long analyses of offshore low-level jet (LLJ) characteristics at heights relevant to wind turbines. In addition to the LLJ climatology, this work provides validation of LLJ representation in atmospheric models that are essential for assessing the potential energy yield of offshore wind farms.
Matteo Mastropierro, Daniele Peano, and Davide Zanchettin
EGUsphere, https://doi.org/10.5194/egusphere-2024-823, https://doi.org/10.5194/egusphere-2024-823, 2024
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We address how different ESMs represent vegetation productivity, in terms of carbon fluxes, within the Amazon basin. By statistically assessing the role of climatological and model specific factors that influence vegetation, we showed that surface energy fluxes and the implementation of Phosphorous limitation resulted to be the main drivers of model uncertainties in a future scenario. Reducing these uncertainties allows to increase the reliability of tropical land carbon and climate projections
Niranjan Adhikari, Jing Gao, Aibin Zhao, Tianli Xu, Manli Chen, Xiaowei Niu, and Tandong Yao
Atmos. Chem. Phys., 24, 3279–3296, https://doi.org/10.5194/acp-24-3279-2024, https://doi.org/10.5194/acp-24-3279-2024, 2024
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Atmospheric water vapour isotopes at Kathmandu recorded significantly low δ18Ov and δDv values during cyclones Tauktae and Yaas in 2021, originating in the Arabian Sea and Bay of Bengal, respectively. Such depletion was associated with the intense moisture convergence and strong convection near the sampling site. The lower δ18Ov and higher d-excessv values during cyclone Yaas may be attributed to the occurrence of robust downdrafts during the rainfall.
Yawen Liu, Yun Qian, Philip J. Rasch, Kai Zhang, Lai-yung Ruby Leung, Yuhang Wang, Minghuai Wang, Hailong Wang, Xin Huang, and Xiu-Qun Yang
Atmos. Chem. Phys., 24, 3115–3128, https://doi.org/10.5194/acp-24-3115-2024, https://doi.org/10.5194/acp-24-3115-2024, 2024
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Fire management has long been a challenge. Here we report that spring-peak fire activity over southern Mexico and Central America (SMCA) has a distinct quasi-biennial signal by measuring multiple fire metrics. This signal is initially driven by quasi-biennial variability in precipitation and is further amplified by positive feedback of fire–precipitation interaction at short timescales. This work highlights the importance of fire–climate interactions in shaping fires on an interannual scale.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Dominik L. Schumacher, Mariam Zachariah, Friederike Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Maja Vahlberg, Roop Singh, Dorothy Heinrich, Julie Arrighi, Maarten van Aalst, Mathias Hauser, Martin Hirschi, Verena Bessenbacher, Lukas Gudmundsson, Hiroko K. Beaudoing, Matthew Rodell, Sihan Li, Wenchang Yang, Gabriel A. Vecchi, Luke J. Harrington, Flavio Lehner, Gianpaolo Balsamo, and Sonia I. Seneviratne
Earth Syst. Dynam., 15, 131–154, https://doi.org/10.5194/esd-15-131-2024, https://doi.org/10.5194/esd-15-131-2024, 2024
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The 2022 summer was accompanied by widespread soil moisture deficits, including an unprecedented drought in Europe. Combining several observation-based estimates and models, we find that such an event has become at least 5 and 20 times more likely due to human-induced climate change in western Europe and the northern extratropics, respectively. Strong regional warming fuels soil desiccation; hence, projections indicate even more potent future droughts as we progress towards a 2 °C warmer world.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Hsiang-He Lee, Qi Tang, and Michael Prather
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-203, https://doi.org/10.5194/gmd-2023-203, 2024
Revised manuscript not accepted
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The E3SM Chemistry diagnostics package (ChemDyg) is a software tool, which is designed for the global climate model (E3SM) chemistry development. ChemDyg generates several diagnostic plots and tables for model-to-model and model-to-observation comparison, including 2-dimentional contour mapping plots, diurnal and annual cycle, time-series plots, and comprehensive processing tables. This paper is to introduce the details of each diagnostics set and its required input data formats in ChemDyg.
Jari-Pekka Nousu, Matthieu Lafaysse, Giulia Mazzotti, Pertti Ala-aho, Hannu Marttila, Bertrand Cluzet, Mika Aurela, Annalea Lohila, Pasi Kolari, Aaron Boone, Mathieu Fructus, and Samuli Launiainen
The Cryosphere, 18, 231–263, https://doi.org/10.5194/tc-18-231-2024, https://doi.org/10.5194/tc-18-231-2024, 2024
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The snowpack has a major impact on the land surface energy budget. Accurate simulation of the snowpack energy budget is difficult, and studies that evaluate models against energy budget observations are rare. We compared predictions from well-known models with observations of energy budgets, snow depths and soil temperatures in Finland. Our study identified contrasting strengths and limitations for the models. These results can be used for choosing the right models depending on the use cases.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Yuling Hu, Haipeng Yu, Shichang Kang, Junhua Yang, Mukesh Rai, Xiufeng Yin, Xintong Chen, and Pengfei Chen
Atmos. Chem. Phys., 24, 85–107, https://doi.org/10.5194/acp-24-85-2024, https://doi.org/10.5194/acp-24-85-2024, 2024
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The Tibetan Plateau (TP) saw a record-breaking aerosol pollution event from April 20 to May 10, 2016. We studied the impact of aerosol–meteorology feedback on the transboundary transport flux of black carbon (BC) during this severe pollution event. It was found that the aerosol–meteorology feedback decreases the transboundary transport flux of BC from the central and western Himalayas towards the TP. This study is of great significance for the protection of the ecological environment of the TP.
Tom Kimpson, Margarita Choulga, Matthew Chantry, Gianpaolo Balsamo, Souhail Boussetta, Peter Dueben, and Tim Palmer
Hydrol. Earth Syst. Sci., 27, 4661–4685, https://doi.org/10.5194/hess-27-4661-2023, https://doi.org/10.5194/hess-27-4661-2023, 2023
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Lakes play an important role when we try to explain and predict the weather. More accurate and up-to-date description of lakes all around the world for numerical models is a continuous task. However, it is difficult to assess the impact of updated lake description within a weather prediction system. In this work, we develop a method to quickly and automatically define how, where, and when updated lake description affects weather prediction.
Daniel Falaschi, Atanu Bhattacharya, Gregoire Guillet, Lei Huang, Owen King, Kriti Mukherjee, Philipp Rastner, Tandong Yao, and Tobias Bolch
The Cryosphere, 17, 5435–5458, https://doi.org/10.5194/tc-17-5435-2023, https://doi.org/10.5194/tc-17-5435-2023, 2023
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Because glaciers are crucial freshwater sources in the lowlands surrounding High Mountain Asia, constraining short-term glacier mass changes is essential. We investigate the potential of state-of-the-art satellite elevation data to measure glacier mass changes in two selected regions. The results demonstrate the ability of our dataset to characterize glacier changes of different magnitudes, allowing for an increase in the number of inaccessible glaciers that can be readily monitored.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
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Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Taigang Zhang, Weicai Wang, and Baosheng An
The Cryosphere, 17, 5137–5154, https://doi.org/10.5194/tc-17-5137-2023, https://doi.org/10.5194/tc-17-5137-2023, 2023
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Detailed glacial lake bathymetry surveys are essential for accurate glacial lake outburst flood (GLOF) simulation and risk assessment. We creatively developed a conceptual model for glacial lake bathymetric distribution. The basic idea is that the statistical glacial lake volume–area curves conform to a power-law relationship indicating that the idealized geometric shape of the glacial lake basin should be hemispheres or cones.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, Emanuele Di Carlo, Franco Catalano, Souhail Boussetta, Gianpaolo Balsamo, and Andrea Alessandri
Earth Syst. Dynam., 14, 1239–1259, https://doi.org/10.5194/esd-14-1239-2023, https://doi.org/10.5194/esd-14-1239-2023, 2023
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Vegetation largely controls land hydrology by transporting water from the subsurface to the atmosphere through roots and is highly variable in space and time. However, current land surface models have limitations in capturing this variability at a global scale, limiting accurate modeling of land hydrology. We found that satellite-based vegetation variability considerably improved modeled land hydrology and therefore has potential to improve climate predictions of, for example, droughts.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
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We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Calvin Howes, Pablo E. Saide, Hugh Coe, Amie Dobracki, Steffen Freitag, Jim M. Haywood, Steven G. Howell, Siddhant Gupta, Janek Uin, Mary Kacarab, Chongai Kuang, L. Ruby Leung, Athanasios Nenes, Greg M. McFarquhar, James Podolske, Jens Redemann, Arthur J. Sedlacek, Kenneth L. Thornhill, Jenny P. S. Wong, Robert Wood, Huihui Wu, Yang Zhang, Jianhao Zhang, and Paquita Zuidema
Atmos. Chem. Phys., 23, 13911–13940, https://doi.org/10.5194/acp-23-13911-2023, https://doi.org/10.5194/acp-23-13911-2023, 2023
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To better understand smoke properties and its interactions with clouds, we compare the WRF-CAM5 model with observations from ORACLES, CLARIFY, and LASIC field campaigns in the southeastern Atlantic in August 2017. The model transports and mixes smoke well but does not fully capture some important processes. These include smoke chemical and physical aging over 4–12 days, smoke removal by rain, sulfate particle formation, aerosol activation into cloud droplets, and boundary layer turbulence.
Dongyu Feng, Zeli Tan, Donghui Xu, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 27, 3911–3934, https://doi.org/10.5194/hess-27-3911-2023, https://doi.org/10.5194/hess-27-3911-2023, 2023
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This study assesses the flood risks concurrently induced by river flooding and coastal storm surge along the coast of the contiguous United States using statistical and numerical models. We reveal a few hotspots of such risks, the critical spatial variabilities within a river basin and over the whole US coast, and the uncertainties of the risk assessment. We highlight the importance of weighing different risk measures to avoid underestimating or exaggerating the compound flood impacts.
Wenjun Tang, Junmei He, Jingwen Qi, and Kun Yang
Earth Syst. Sci. Data, 15, 4537–4551, https://doi.org/10.5194/essd-15-4537-2023, https://doi.org/10.5194/essd-15-4537-2023, 2023
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In this study, we have developed a dense station-based, long-term dataset of daily surface solar radiation in China with high accuracy. The dataset consists of estimates of global, direct and diffuse radiation at 2473 meteorological stations from the 1950s to 2021. Validation indicates that our station-based radiation dataset clearly outperforms the satellite-based radiation products. Our dataset will contribute to climate change research and solar energy applications in the future.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Xiufeng Yin, Dipesh Rupakheti, Guoshuai Zhang, Jiali Luo, Shichang Kang, Benjamin de Foy, Junhua Yang, Zhenming Ji, Zhiyuan Cong, Maheswar Rupakheti, Ping Li, Yuling Hu, and Qianggong Zhang
Atmos. Chem. Phys., 23, 10137–10143, https://doi.org/10.5194/acp-23-10137-2023, https://doi.org/10.5194/acp-23-10137-2023, 2023
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The monthly mean surface ozone concentrations peaked earlier in the south in April and May and later in the north in June and July over the Tibetan Plateau. The migration of monthly surface ozone peaks was coupled with the synchronous movement of tropopause folds and the westerly jet that created conditions conducive to stratospheric ozone intrusion. Stratospheric ozone intrusion significantly contributed to surface ozone across the Tibetan Plateau.
Wei Yang, Zhongyan Wang, Baosheng An, Yingying Chen, Chuanxi Zhao, Chenhui Li, Yongjie Wang, Weicai Wang, Jiule Li, Guangjian Wu, Lin Bai, Fan Zhang, and Tandong Yao
Nat. Hazards Earth Syst. Sci., 23, 3015–3029, https://doi.org/10.5194/nhess-23-3015-2023, https://doi.org/10.5194/nhess-23-3015-2023, 2023
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We present the structure and performance of the early warning system (EWS) for glacier collapse and river blockages in the southeastern Tibetan Plateau. The EWS warned of three collapse–river blockage chain events and seven small-scale events. The volume and location of the collapses and the percentage of ice content influenced the velocities of debris flows. Such a study is helpful for understanding the mechanism of glacier hazards and for establishing similar EWSs in other high-risk regions.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
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Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Xinyan Liu, Tao He, Shunlin Liang, Ruibo Li, Xiongxin Xiao, Rui Ma, and Yichuan Ma
Earth Syst. Sci. Data, 15, 3641–3671, https://doi.org/10.5194/essd-15-3641-2023, https://doi.org/10.5194/essd-15-3641-2023, 2023
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We proposed a data fusion strategy that combines the complementary features of multiple-satellite cloud fraction (CF) datasets and generated a continuous monthly 1° daytime cloud fraction product covering the entire Arctic during the sunlit months in 2000–2020. This study has positive significance for reducing the uncertainties for the assessment of surface radiation fluxes and improving the accuracy of research related to climate change and energy budgets, both regionally and globally.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023, https://doi.org/10.5194/gmd-16-4017-2023, 2023
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Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Edward H. Bair, Jeff Dozier, Karl Rittger, Timbo Stillinger, William Kleiber, and Robert E. Davis
The Cryosphere, 17, 2629–2643, https://doi.org/10.5194/tc-17-2629-2023, https://doi.org/10.5194/tc-17-2629-2023, 2023
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To test the title question, three snow cover products were used in a snow model. Contrary to previous work, higher-spatial-resolution snow cover products only improved the model accuracy marginally. Conclusions are as follows: (1) snow cover and albedo from moderate-resolution sensors continue to provide accurate forcings and (2) finer spatial and temporal resolutions are the future for Earth observations, but existing moderate-resolution sensors still offer value.
Wei Yang, Huabiao Zhao, Baiqing Xu, Jiule Li, Weicai Wang, Guangjian Wu, Zhongyan Wang, and Tandong Yao
The Cryosphere, 17, 2625–2628, https://doi.org/10.5194/tc-17-2625-2023, https://doi.org/10.5194/tc-17-2625-2023, 2023
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There is very strong scientific and public interest regarding the snow thickness on Mountain Everest. Previously reported snow depths derived by different methods and instruments ranged from 0.92 to 3.5 m. Our measurements in 2022 provide the first clear radar image of the snowpack at the top of Mount Everest. The snow thickness at Earth's summit was averaged to be 9.5 ± 1.2 m. This updated snow thickness is considerably deeper than values reported during the past 5 decades.
Jinming Feng, Meng Luo, Jun Wang, Yuan Qiu, Qizhong Wu, and Ke Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-867, https://doi.org/10.5194/egusphere-2023-867, 2023
Preprint withdrawn
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We modified the code of the Weather Research and Forecasting Model (WRF) v3.8.1 to include the forcing components more than the Greenhouse Gases and evaluate the impact of forcing configurations on the climate simulation results in China. It showed that different external forcing configurations in WRF could result in considerable impact on the annual temperature and precipitation trend, which was stronger than parameterization schemes but was weaker than spectral nudging.
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081, https://doi.org/10.5194/gmd-16-3029-2023, https://doi.org/10.5194/gmd-16-3029-2023, 2023
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We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
Yufang Zhang, Shunlin Liang, Han Ma, Tao He, Qian Wang, Bing Li, Jianglei Xu, Guodong Zhang, Xiaobang Liu, and Changhao Xiong
Earth Syst. Sci. Data, 15, 2055–2079, https://doi.org/10.5194/essd-15-2055-2023, https://doi.org/10.5194/essd-15-2055-2023, 2023
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Soil moisture observations are important for a range of earth system applications. This study generated a long-term (2000–2020) global seamless soil moisture product with both high spatial and temporal resolutions (1 km, daily) using an XGBoost model and multisource datasets. Evaluation of this product against dense in situ soil moisture datasets and microwave soil moisture products showed that this product has reliable accuracy and more complete spatial coverage.
Zhe Feng, Joseph Hardin, Hannah C. Barnes, Jianfeng Li, L. Ruby Leung, Adam Varble, and Zhixiao Zhang
Geosci. Model Dev., 16, 2753–2776, https://doi.org/10.5194/gmd-16-2753-2023, https://doi.org/10.5194/gmd-16-2753-2023, 2023
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PyFLEXTRKR is a flexible atmospheric feature tracking framework with specific capabilities to track convective clouds from a variety of observations and model simulations. The package has a collection of multi-object identification algorithms and has been optimized for large datasets. This paper describes the algorithms and demonstrates applications for tracking deep convective cells and mesoscale convective systems from observations and model simulations at a wide range of scales.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Dominikus Heinzeller, Ligia Bernardet, Grant Firl, Man Zhang, Xia Sun, and Michael Ek
Geosci. Model Dev., 16, 2235–2259, https://doi.org/10.5194/gmd-16-2235-2023, https://doi.org/10.5194/gmd-16-2235-2023, 2023
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The Common Community Physics Package is a collection of physical atmospheric parameterizations for use in Earth system models and a framework that couples the physics to a host model’s dynamical core. A primary goal for this effort is to facilitate research and development of physical parameterizations and physics–dynamics coupling methods while offering capabilities for numerical weather prediction operations, for example in the upcoming implementation of the Global Forecast System (GFS) v17.
Huiming Lin, Yindong Tong, Long Chen, Chenghao Yu, Zhaohan Chu, Qianru Zhang, Xiufeng Yin, Qianggong Zhang, Shichang Kang, Junfeng Liu, James Schauer, Benjamin de Foy, and Xuejun Wang
Atmos. Chem. Phys., 23, 3937–3953, https://doi.org/10.5194/acp-23-3937-2023, https://doi.org/10.5194/acp-23-3937-2023, 2023
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Lhasa is the largest city in the Tibetan Plateau, and its atmospheric mercury concentrations represent the highest level of pollution in this region. Unexpectedly high concentrations of atmospheric mercury species were found. Combined with the trajectory analysis, the high atmospheric mercury concentrations may have originated from external long-range transport. Local sources, especially special mercury-related sources, are important factors influencing the variability of atmospheric mercury.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Aolin Jia, Shunlin Liang, Dongdong Wang, Lei Ma, Zhihao Wang, and Shuo Xu
Earth Syst. Sci. Data, 15, 869–895, https://doi.org/10.5194/essd-15-869-2023, https://doi.org/10.5194/essd-15-869-2023, 2023
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Satellites are now producing multiple global land surface temperature (LST) products; however, they suffer from data gaps caused by cloud cover, seriously restricting the applications, and few products provide gap-free global hourly LST. We produced global hourly, 5 km, all-sky LST data from 2011 to 2021 using geostationary and polar-orbiting satellite data. Based on the assessment, it has high accuracy and can be used to estimate evapotranspiration, drought, etc.
Yi Yang, Douglas Maraun, Albert Ossó, and Jianping Tang
Nat. Hazards Earth Syst. Sci., 23, 693–709, https://doi.org/10.5194/nhess-23-693-2023, https://doi.org/10.5194/nhess-23-693-2023, 2023
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This study quantifies the spatiotemporal variation and characteristics of compound long-duration dry and hot events in China over the 1961–2014 period. The results show that over the past few decades, there has been a substantial increase in the frequency of these compound events across most parts of China, which is dominated by rising temperatures. We detect a strong increase in the spatially contiguous areas experiencing concurrent dry and hot conditions.
Dalei Hao, Gautam Bisht, Karl Rittger, Timbo Stillinger, Edward Bair, Yu Gu, and L. Ruby Leung
The Cryosphere, 17, 673–697, https://doi.org/10.5194/tc-17-673-2023, https://doi.org/10.5194/tc-17-673-2023, 2023
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We comprehensively evaluated the snow simulations in E3SM land model over the western United States in terms of spatial patterns, temporal correlations, interannual variabilities, elevation gradients, and change with forest cover of snow properties and snow phenology. Our study underscores the need for diagnosing model biases and improving the model representations of snow properties and snow phenology in mountainous areas for more credible simulation and future projection of mountain snowpack.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
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Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
He Sun, Tandong Yao, Fengge Su, Wei Yang, Guifeng Huang, and Deliang Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-16, https://doi.org/10.5194/hess-2023-16, 2023
Manuscript not accepted for further review
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Based on field research campaigns since 2017 in the Yarlung Zangbo (YZ) river basin and a well-validated model, our results reveal that large regional differences in runoff regimes and changes exist in the basin. Annual runoff shows decreasing trend in the downstream sub-basin but increasing trends in the upper and middle sub-basins, due to opposing precipitation changes. Glacier runoff plays more important role in annual total runoff in downstream basin.
Chandan Sarangi, Yun Qian, L. Ruby Leung, Yang Zhang, Yufei Zou, and Yuhang Wang
Atmos. Chem. Phys., 23, 1769–1783, https://doi.org/10.5194/acp-23-1769-2023, https://doi.org/10.5194/acp-23-1769-2023, 2023
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We show that for air quality, the densely populated eastern US may see even larger impacts of wildfires due to long-distance smoke transport and associated positive climatic impacts, partially compensating the improvements from regulations on anthropogenic emissions. This study highlights the tension between natural and anthropogenic contributions and the non-local nature of air pollution that complicate regulatory strategies for improving future regional air quality for human health.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Yangxin Chen, Duoying Ji, Qian Zhang, John C. Moore, Olivier Boucher, Andy Jones, Thibaut Lurton, Michael J. Mills, Ulrike Niemeier, Roland Séférian, and Simone Tilmes
Earth Syst. Dynam., 14, 55–79, https://doi.org/10.5194/esd-14-55-2023, https://doi.org/10.5194/esd-14-55-2023, 2023
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Solar geoengineering has been proposed as a way of counteracting the warming effects of increasing greenhouse gases by reflecting solar radiation. This work shows that solar geoengineering can slow down the northern-high-latitude permafrost degradation but cannot preserve the permafrost ecosystem as that under a climate of the same warming level without solar geoengineering.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
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Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
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Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Dario Nicolì, Alessio Bellucci, Paolo Ruggieri, Panos J. Athanasiadis, Stefano Materia, Daniele Peano, Giusy Fedele, Riccardo Hénin, and Silvio Gualdi
Geosci. Model Dev., 16, 179–197, https://doi.org/10.5194/gmd-16-179-2023, https://doi.org/10.5194/gmd-16-179-2023, 2023
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Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of the near-term climate and are useful for informing decision-makers on future climate-related risks. The predictive skill for key variables is assessed from the operational decadal prediction system compared with non-initialized historical simulations so as to quantify the added value of initialization.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
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Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Shaoyong Wang, Xiaobo He, Shichang Kang, Hui Fu, and Xiaofeng Hong
The Cryosphere, 16, 5023–5040, https://doi.org/10.5194/tc-16-5023-2022, https://doi.org/10.5194/tc-16-5023-2022, 2022
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This study used the sine-wave exponential model and long-term water stable isotopic data to estimate water mean residence time (MRT) and its influencing factors in a high-altitude permafrost catchment (5300 m a.s.l.) in the central Tibetan Plateau (TP). MRT for stream and supra-permafrost water was estimated at 100 and 255 d, respectively. Climate and vegetation factors affected the MRT of stream and supra-permafrost water mainly by changing the thickness of the permafrost active layer.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Wei Li, Jie Chen, Lu Li, Yvan J. Orsolini, Yiheng Xiang, Retish Senan, and Patricia de Rosnay
The Cryosphere, 16, 4985–5000, https://doi.org/10.5194/tc-16-4985-2022, https://doi.org/10.5194/tc-16-4985-2022, 2022
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Snow assimilation over the Tibetan Plateau (TP) may influence seasonal forecasts over this region. To investigate the impacts of snow assimilation on the seasonal forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer in 2018. The results show that snow assimilation can improve seasonal forecasts over the TP through the interaction between land and atmosphere.
Han Ma, Shunlin Liang, Changhao Xiong, Qian Wang, Aolin Jia, and Bing Li
Earth Syst. Sci. Data, 14, 5333–5347, https://doi.org/10.5194/essd-14-5333-2022, https://doi.org/10.5194/essd-14-5333-2022, 2022
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The fraction of absorbed photosynthetically active radiation (FAPAR) is one of the essential climate variables. This study generated a global land surface FAPAR product with a 250 m resolution based on a deep learning model that takes advantage of the existing FAPAR products and MODIS time series of observation information. Direct validation and intercomparison revealed that our product better meets user requirements and has a greater spatiotemporal continuity than other existing products.
Huilin Huang, Yun Qian, Ye Liu, Cenlin He, Jianyu Zheng, Zhibo Zhang, and Antonis Gkikas
Atmos. Chem. Phys., 22, 15469–15488, https://doi.org/10.5194/acp-22-15469-2022, https://doi.org/10.5194/acp-22-15469-2022, 2022
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Using a clustering method developed in the field of artificial neural networks, we identify four typical dust transport patterns across the Sierra Nevada, associated with the mesoscale and regional-scale wind circulations. Our results highlight the connection between dust transport and dominant weather patterns, which can be used to understand dust transport in a changing climate.
Simon K. Allen, Ashim Sattar, Owen King, Guoqing Zhang, Atanu Bhattacharya, Tandong Yao, and Tobias Bolch
Nat. Hazards Earth Syst. Sci., 22, 3765–3785, https://doi.org/10.5194/nhess-22-3765-2022, https://doi.org/10.5194/nhess-22-3765-2022, 2022
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This study demonstrates how the threat of a very large outburst from a future lake can be feasibly assessed alongside that from current lakes to inform disaster risk management within a transboundary basin between Tibet and Nepal. Results show that engineering measures and early warning systems would need to be coupled with effective land use zoning and programmes to strengthen local response capacities in order to effectively reduce the risk associated with current and future outburst events.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
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We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
EGUsphere, https://doi.org/10.5194/egusphere-2022-1111, https://doi.org/10.5194/egusphere-2022-1111, 2022
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A process-based plant Carbon (C)-Nitrogen (N) interface coupling framework has been developed, which mainly focuses on the plant resistance and N limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem-biogeochemical model and testing results show a general improvement in simulating plant properties with this framework.
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 5473–5491, https://doi.org/10.5194/hess-26-5473-2022, https://doi.org/10.5194/hess-26-5473-2022, 2022
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Sea level rise, storm surge and river discharge can cause coastal backwater effects in downstream sections of rivers, creating critical flood risks. This study simulates the backwater effects using a large-scale river model on a coastal-refined computational mesh. By decomposing the backwater drivers, we revealed their relative importance and long-term variations. Our analysis highlights the increasing strength of backwater effects due to sea level rise and more frequent storm surge.
Melissa Ruiz-Vásquez, Sungmin O, Alexander Brenning, Randal D. Koster, Gianpaolo Balsamo, Ulrich Weber, Gabriele Arduini, Ana Bastos, Markus Reichstein, and René Orth
Earth Syst. Dynam., 13, 1451–1471, https://doi.org/10.5194/esd-13-1451-2022, https://doi.org/10.5194/esd-13-1451-2022, 2022
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Subseasonal forecasts facilitate early warning of extreme events; however their predictability sources are not fully explored. We find that global temperature forecast errors in many regions are related to climate variables such as solar radiation and precipitation, as well as land surface variables such as soil moisture and evaporative fraction. A better representation of these variables in the forecasting and data assimilation systems can support the accuracy of temperature forecasts.
Yilin Fang, L. Ruby Leung, Charles D. Koven, Gautam Bisht, Matteo Detto, Yanyan Cheng, Nate McDowell, Helene Muller-Landau, S. Joseph Wright, and Jeffrey Q. Chambers
Geosci. Model Dev., 15, 7879–7901, https://doi.org/10.5194/gmd-15-7879-2022, https://doi.org/10.5194/gmd-15-7879-2022, 2022
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We develop a model that integrates an Earth system model with a three-dimensional hydrology model to explicitly resolve hillslope topography and water flow underneath the land surface to understand how local-scale hydrologic processes modulate vegetation along water availability gradients. Our coupled model can be used to improve the understanding of the diverse impact of local heterogeneity and water flux on nutrient availability and plant communities.
Jaime Gaona, Pere Quintana-Seguí, María José Escorihuela, Aaron Boone, and María Carmen Llasat
Nat. Hazards Earth Syst. Sci., 22, 3461–3485, https://doi.org/10.5194/nhess-22-3461-2022, https://doi.org/10.5194/nhess-22-3461-2022, 2022
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Droughts represent a particularly complex natural hazard and require explorations of their multiple causes. Part of the complexity has roots in the interaction between the continuous changes in and deviation from normal conditions of the atmosphere and the land surface. The exchange between the atmospheric and surface conditions defines feedback towards dry or wet conditions. In semi-arid environments, energy seems to exceed water in its impact over the evolution of conditions, favoring drought.
Jizu Chen, Wentao Du, Shichang Kang, Xiang Qin, Weijun Sun, Yang Li, Yushuo Liu, Lihui Luo, and Youyan Jiang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-179, https://doi.org/10.5194/tc-2022-179, 2022
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This study developed a dynamic deposition model of light absorbing particles (LAPs), which coupled with a surface energy and mass balance model. Based on the coupled model, we assessed atmospheric deposited BC effect on glacier melting, and quantified global warming and increment of emitted black carbon respective contributions to current accelerated glacier melting.
Yaozhi Jiang, Kun Yang, Hua Yang, Hui Lu, Yingying Chen, Xu Zhou, Jing Sun, Yuan Yang, and Yan Wang
Hydrol. Earth Syst. Sci., 26, 4587–4601, https://doi.org/10.5194/hess-26-4587-2022, https://doi.org/10.5194/hess-26-4587-2022, 2022
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Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Rui Ma, Jingfeng Xiao, Shunlin Liang, Han Ma, Tao He, Da Guo, Xiaobang Liu, and Haibo Lu
Geosci. Model Dev., 15, 6637–6657, https://doi.org/10.5194/gmd-15-6637-2022, https://doi.org/10.5194/gmd-15-6637-2022, 2022
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Parameter optimization can improve the accuracy of modeled carbon fluxes. Few studies conducted pixel-level parameterization because it requires a high computational cost. Our paper used high-quality spatial products to optimize parameters at the pixel level, and also used the machine learning method to improve the speed of optimization. The results showed that there was significant spatial variability of parameters and we also improved the spatial pattern of carbon fluxes.
Meng Huang, Po-Lun Ma, Nathaniel W. Chaney, Dalei Hao, Gautam Bisht, Megan D. Fowler, Vincent E. Larson, and L. Ruby Leung
Geosci. Model Dev., 15, 6371–6384, https://doi.org/10.5194/gmd-15-6371-2022, https://doi.org/10.5194/gmd-15-6371-2022, 2022
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The land surface in one grid cell may be diverse in character. This study uses an explicit way to account for that subgrid diversity in a state-of-the-art Earth system model (ESM) and explores its implications for the overlying atmosphere. We find that the shallow clouds are increased significantly with the land surface diversity. Our work highlights the importance of accurately representing the land surface and its interaction with the atmosphere in next-generation ESMs.
Yilin Fang, L. Ruby Leung, Ryan Knox, Charlie Koven, and Ben Bond-Lamberty
Geosci. Model Dev., 15, 6385–6398, https://doi.org/10.5194/gmd-15-6385-2022, https://doi.org/10.5194/gmd-15-6385-2022, 2022
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Accounting for water movement in the soil and water transport within the plant is important for plant growth in Earth system modeling. We implemented different numerical approaches for a plant hydrodynamic model and compared their impacts on the simulated aboveground biomass (AGB) at single points and globally. We found care should be taken when discretizing the number of soil layers for numerical simulations as it can significantly affect AGB if accuracy and computational costs are of concern.
Lim-Seok Chang, Donghee Kim, Hyunkee Hong, Deok-Rae Kim, Jeong-Ah Yu, Kwangyul Lee, Hanlim Lee, Daewon Kim, Jinkyu Hong, Hyun-Young Jo, and Cheol-Hee Kim
Atmos. Chem. Phys., 22, 10703–10720, https://doi.org/10.5194/acp-22-10703-2022, https://doi.org/10.5194/acp-22-10703-2022, 2022
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Our study explored the synergy of combined column and surface measurements during GMAP (GEMS Map of Air Pollution) campaign. It has several points to note for vertical distribution analysis. Particularly under prevailing local wind meteorological conditions, Pandora-based vertical structures sometimes showed negative correlations between column and surface measurements. Vertical analysis should be done carefully in some local meteorological conditions when employing either surface or columns.
Bastian Kirsch, Cathy Hohenegger, Daniel Klocke, Rainer Senke, Michael Offermann, and Felix Ament
Earth Syst. Sci. Data, 14, 3531–3548, https://doi.org/10.5194/essd-14-3531-2022, https://doi.org/10.5194/essd-14-3531-2022, 2022
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Conventional observation networks are too coarse to resolve the horizontal structure of kilometer-scale atmospheric processes. We present the FESST@HH field experiment that took place in Hamburg (Germany) during summer 2020 and featured a dense network of 103 custom-built, low-cost weather stations. The data set is capable of providing new insights into the structure of convective cold pools and the nocturnal urban heat island and variations of local temperature fluctuations.
Yijie Sui, Min Feng, Chunling Wang, and Xin Li
Earth Syst. Sci. Data, 14, 3349–3363, https://doi.org/10.5194/essd-14-3349-2022, https://doi.org/10.5194/essd-14-3349-2022, 2022
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High-latitude water bodies differ greatly in their morphological and topological characteristics related to their formation, type, and vulnerability. In this paper, we present a water body dataset for the North American high latitudes (WBD-NAHL). Nearly 6.5 million water bodies were identified, with approximately 6 million (~90 %) of them smaller than 0.1 km2.
Sol Kim, L. Ruby Leung, Bin Guan, and John C. H. Chiang
Geosci. Model Dev., 15, 5461–5480, https://doi.org/10.5194/gmd-15-5461-2022, https://doi.org/10.5194/gmd-15-5461-2022, 2022
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The Energy Exascale Earth System Model (E3SM) project is a state-of-the-science Earth system model developed by the US Department of Energy (DOE). Understanding how the water cycle behaves in this model is of particular importance to the DOE’s mission. Atmospheric rivers (ARs) – which are crucial to the global water cycle – move vast amounts of water vapor through the sky and produce rain and snow. We find that this model reliably represents atmospheric rivers around the world.
Lingcheng Li, Gautam Bisht, and L. Ruby Leung
Geosci. Model Dev., 15, 5489–5510, https://doi.org/10.5194/gmd-15-5489-2022, https://doi.org/10.5194/gmd-15-5489-2022, 2022
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Land surface heterogeneity plays a critical role in the terrestrial water, energy, and biogeochemical cycles. Our study systematically quantified the effects of four dominant heterogeneity sources on water and energy partitioning via Sobol' indices. We found that atmospheric forcing and land use land cover are the most dominant heterogeneity sources in determining spatial variability of water and energy partitioning. Our findings can help prioritize the future development of land surface models.
Kai Zhang, Wentao Zhang, Hui Wan, Philip J. Rasch, Steven J. Ghan, Richard C. Easter, Xiangjun Shi, Yong Wang, Hailong Wang, Po-Lun Ma, Shixuan Zhang, Jian Sun, Susannah M. Burrows, Manish Shrivastava, Balwinder Singh, Yun Qian, Xiaohong Liu, Jean-Christophe Golaz, Qi Tang, Xue Zheng, Shaocheng Xie, Wuyin Lin, Yan Feng, Minghuai Wang, Jin-Ho Yoon, and L. Ruby Leung
Atmos. Chem. Phys., 22, 9129–9160, https://doi.org/10.5194/acp-22-9129-2022, https://doi.org/10.5194/acp-22-9129-2022, 2022
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Here we analyze the effective aerosol forcing simulated by E3SM version 1 using both century-long free-running and short nudged simulations. The aerosol forcing in E3SMv1 is relatively large compared to other models, mainly due to the large indirect aerosol effect. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 have a strong correlation. The aerosol forcing estimates in E3SMv1 are sensitive to the parameterization changes in both liquid and ice cloud processes.
Chaman Gul, Shichang Kang, Siva Praveen Puppala, Xiaokang Wu, Cenlin He, Yangyang Xu, Inka Koch, Sher Muhammad, Rajesh Kumar, and Getachew Dubache
Atmos. Chem. Phys., 22, 8725–8737, https://doi.org/10.5194/acp-22-8725-2022, https://doi.org/10.5194/acp-22-8725-2022, 2022
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This work aims to understand concentrations, spatial variability, and potential source regions of light-absorbing impurities (black carbon aerosols, dust particles, and organic carbon) in the surface snow of central and western Himalayan glaciers and their impact on snow albedo and radiative forcing.
Peter Hitchcock, Amy Butler, Andrew Charlton-Perez, Chaim I. Garfinkel, Tim Stockdale, James Anstey, Dann Mitchell, Daniela I. V. Domeisen, Tongwen Wu, Yixiong Lu, Daniele Mastrangelo, Piero Malguzzi, Hai Lin, Ryan Muncaster, Bill Merryfield, Michael Sigmond, Baoqiang Xiang, Liwei Jia, Yu-Kyung Hyun, Jiyoung Oh, Damien Specq, Isla R. Simpson, Jadwiga H. Richter, Cory Barton, Jeff Knight, Eun-Pa Lim, and Harry Hendon
Geosci. Model Dev., 15, 5073–5092, https://doi.org/10.5194/gmd-15-5073-2022, https://doi.org/10.5194/gmd-15-5073-2022, 2022
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This paper describes an experimental protocol focused on sudden stratospheric warmings to be carried out by subseasonal forecast modeling centers. These will allow for inter-model comparisons of these major disruptions to the stratospheric polar vortex and their impacts on the near-surface flow. The protocol will lead to new insights into the contribution of the stratosphere to subseasonal forecast skill and new approaches to the dynamical attribution of extreme events.
Xinghua Zhang, Wenhui Zhao, Lixiang Zhai, Miao Zhong, Jinsen Shi, Junying Sun, Yanmei Liu, Conghui Xie, Yulong Tan, Kemei Li, Xinlei Ge, Qi Zhang, Shichang Kang, and Jianzhong Xu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-211, https://doi.org/10.5194/essd-2022-211, 2022
Manuscript not accepted for further review
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A comprehensive aerosol observation project was carried out in the Tibetan Plateau (TP) in recent years to investigate the properties and sources of atmospheric aerosols as well as their regional differences by performing multiple short-term intensive field observations. The real-time online high-time-resolution (hourly) data of aerosol properties in the different TP region are integrated in a new dataset and can provide supporting for related studies in in the TP.
Donghui Xu, Gautam Bisht, Khachik Sargsyan, Chang Liao, and L. Ruby Leung
Geosci. Model Dev., 15, 5021–5043, https://doi.org/10.5194/gmd-15-5021-2022, https://doi.org/10.5194/gmd-15-5021-2022, 2022
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The runoff outputs in Earth system model simulations involve high uncertainty, which needs to be constrained by parameter calibration. In this work, we used a surrogate-assisted Bayesian framework to efficiently calibrate the runoff-generation processes in the Energy Exascale Earth System Model v1 at a global scale. The model performance was improved compared to the default parameter after calibration, and the associated parametric uncertainty was significantly constrained.
Yun Lin, Jiwen Fan, Pengfei Li, Lai-yung Ruby Leung, Paul J. DeMott, Lexie Goldberger, Jennifer Comstock, Ying Liu, Jong-Hoon Jeong, and Jason Tomlinson
Atmos. Chem. Phys., 22, 6749–6771, https://doi.org/10.5194/acp-22-6749-2022, https://doi.org/10.5194/acp-22-6749-2022, 2022
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How sea spray aerosols may affect cloud and precipitation over the region by acting as ice-nucleating particles (INPs) is unknown. We explored the effects of INPs from marine aerosols on orographic cloud and precipitation for an atmospheric river event observed during the 2015 ACAPEX field campaign. The marine INPs enhance the formation of ice and snow, leading to less shallow warm clouds but more mixed-phase and deep clouds. This work suggests models need to consider the impacts of marine INPs.
Xue Zheng, Qing Li, Tian Zhou, Qi Tang, Luke P. Van Roekel, Jean-Christophe Golaz, Hailong Wang, and Philip Cameron-Smith
Geosci. Model Dev., 15, 3941–3967, https://doi.org/10.5194/gmd-15-3941-2022, https://doi.org/10.5194/gmd-15-3941-2022, 2022
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We document the model experiments for the future climate projection by E3SMv1.0. At the highest future emission scenario, E3SMv1.0 projects a strong surface warming with rapid changes in the atmosphere, ocean, sea ice, and land runoff. Specifically, we detect a significant polar amplification and accelerated warming linked to the unmasking of the aerosol effects. The impact of greenhouse gas forcing is examined in different climate components.
Jianglei Xu, Shunlin Liang, and Bo Jiang
Earth Syst. Sci. Data, 14, 2315–2341, https://doi.org/10.5194/essd-14-2315-2022, https://doi.org/10.5194/essd-14-2315-2022, 2022
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Land surface all-wave net radiation (Rn) is a key parameter in many land processes. Current products have drawbacks of coarse resolutions, large uncertainty, and short time spans. A deep learning method was used to obtain global surface Rn. A long-term Rn product was generated from 1981 to 2019 using AVHRR data. The product has the highest accuracy and a reasonable spatiotemporal variation compared to three other products. Our product will play an important role in long-term climate change.
Yongqin Liu, Pengcheng Fang, Bixi Guo, Mukan Ji, Pengfei Liu, Guannan Mao, Baiqing Xu, Shichang Kang, and Junzhi Liu
Earth Syst. Sci. Data, 14, 2303–2314, https://doi.org/10.5194/essd-14-2303-2022, https://doi.org/10.5194/essd-14-2303-2022, 2022
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Glaciers are an important pool of microorganisms, organic carbon, and nitrogen. This study constructed the first dataset of microbial abundance and total nitrogen in Tibetan Plateau (TP) glaciers and the first dataset of dissolved organic carbon in ice cores on the TP. These new data could provide valuable information for research on the glacier carbon and nitrogen cycle and help in assessing the potential impacts of glacier retreat due to global warming on downstream ecosystems.
Steve Delhaye, Thierry Fichefet, François Massonnet, David Docquier, Rym Msadek, Svenya Chripko, Christopher Roberts, Sarah Keeley, and Retish Senan
Weather Clim. Dynam., 3, 555–573, https://doi.org/10.5194/wcd-3-555-2022, https://doi.org/10.5194/wcd-3-555-2022, 2022
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It is unclear how the atmosphere will respond to a retreat of summer Arctic sea ice. Much attention has been paid so far to weather extremes at mid-latitude and in winter. Here we focus on the changes in extremes in surface air temperature and precipitation over the Arctic regions in summer during and following abrupt sea ice retreats. We find that Arctic sea ice loss clearly shifts the extremes in surface air temperature and precipitation over terrestrial regions surrounding the Arctic Ocean.
Yuan Qiu, Jinming Feng, Zhongwei Yan, and Jun Wang
Earth Syst. Sci. Data, 14, 2195–2208, https://doi.org/10.5194/essd-14-2195-2022, https://doi.org/10.5194/essd-14-2195-2022, 2022
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A high-resolution climate projection dataset in central Asia, named the HCPD-CA dataset, is derived from the dynamically downscaled results based on three bias-corrected global climate models and contains 4 geostatic variables and 10 meteorological elements that are widely used to drive ecological and hydrological models. This dataset can serve as a scientific basis for assessing the potential impacts of projected climate changes over central Asia on many sectors.
Edward H. Bair, Jeff Dozier, Charles Stern, Adam LeWinter, Karl Rittger, Alexandria Savagian, Timbo Stillinger, and Robert E. Davis
The Cryosphere, 16, 1765–1778, https://doi.org/10.5194/tc-16-1765-2022, https://doi.org/10.5194/tc-16-1765-2022, 2022
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Understanding how snow and ice reflect solar radiation (albedo) is important for global climate. Using high-resolution topography, darkening from surface roughness (apparent albedo) is separated from darkening by the composition of the snow (intrinsic albedo). Intrinsic albedo is usually greater than apparent albedo, especially during melt. Such high-resolution topography is often not available; thus the use of a shade component when modeling mixtures is advised.
Joe McNorton, Nicolas Bousserez, Anna Agustí-Panareda, Gianpaolo Balsamo, Luca Cantarello, Richard Engelen, Vincent Huijnen, Antje Inness, Zak Kipling, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 5961–5981, https://doi.org/10.5194/acp-22-5961-2022, https://doi.org/10.5194/acp-22-5961-2022, 2022
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Concentrations of atmospheric methane continue to grow, in recent years at an increasing rate, for unknown reasons. Using newly available satellite observations and a state-of-the-art weather prediction model we perform global estimates of emissions from hotspots at high resolution. Results show that the system can accurately report on biases in national inventories and is used to conclude that the early COVID-19 slowdown period (March–June 2020) had little impact on global methane emissions.
Wenjun Tang, Jun Qin, Kun Yang, Yaozhi Jiang, and Weihao Pan
Earth Syst. Sci. Data, 14, 2007–2019, https://doi.org/10.5194/essd-14-2007-2022, https://doi.org/10.5194/essd-14-2007-2022, 2022
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Photosynthetically active radiation (PAR) is a fundamental physiological variable for research in the ecological, agricultural, and global change fields. In this study, we produced a 35-year high-resolution global gridded PAR dataset. Compared with the well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES), our PAR product was found to be a more accurate dataset with higher resolution.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
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A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Ming Li, Husi Letu, Yiran Peng, Hiroshi Ishimoto, Yanluan Lin, Takashi Y. Nakajima, Anthony J. Baran, Zengyuan Guo, Yonghui Lei, and Jiancheng Shi
Atmos. Chem. Phys., 22, 4809–4825, https://doi.org/10.5194/acp-22-4809-2022, https://doi.org/10.5194/acp-22-4809-2022, 2022
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To build on the previous investigations of the Voronoi model in the remote sensing retrievals of ice cloud products, this paper developed an ice cloud parameterization scheme based on the single-scattering properties of the Voronoi model and evaluate it through simulations with the Community Integrated Earth System Model (CIESM). Compared with four representative ice cloud schemes, results show that the Voronoi model has good capabilities of ice cloud modeling in the climate model.
Chuanxi Zhao, Wei Yang, Matthew Westoby, Baosheng An, Guangjian Wu, Weicai Wang, Zhongyan Wang, Yongjie Wang, and Stuart Dunning
The Cryosphere, 16, 1333–1340, https://doi.org/10.5194/tc-16-1333-2022, https://doi.org/10.5194/tc-16-1333-2022, 2022
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On 22 March 2021, a ~ 50 Mm 3 ice-rock avalanche occurred from 6500 m a.s.l. in the Sedongpu basin, southeastern Tibet. It caused temporary blockage of the Yarlung Tsangpo river, a major tributary of the Brahmaputra. We utilize field investigations, high-resolution satellite imagery, seismic records, and meteorological data to analyse the evolution of the 2021 event and its impact, discuss potential drivers, and briefly reflect on implications for the sustainable development of the region.
Pinya Wang, Yang Yang, Huimin Li, Lei Chen, Ruijun Dang, Daokai Xue, Baojie Li, Jianping Tang, L. Ruby Leung, and Hong Liao
Atmos. Chem. Phys., 22, 4705–4719, https://doi.org/10.5194/acp-22-4705-2022, https://doi.org/10.5194/acp-22-4705-2022, 2022
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China is now suffering from both severe ozone (O3) pollution and heat events. We highlight that North China Plain is the hot spot of the co-occurrences of extremes in O3 and high temperatures in China. Such coupled extremes exhibit an increasing trend during 2014–2019 and will continue to increase until the middle of this century. And the coupled extremes impose more severe health impacts to human than O3 pollution occurring alone because of elevated O3 levels and temperatures.
Mukesh Rai, Shichang Kang, Junhua Yang, Maheswar Rupakheti, Dipesh Rupakheti, Lekhendra Tripathee, Yuling Hu, and Xintong Chen
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-199, https://doi.org/10.5194/acp-2022-199, 2022
Revised manuscript not accepted
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Our study revealed distinctive seasonality with the maximum and minimum aerosol concentrations during the winter and summer seasons respectively. However, interestingly summer high (AOD > 0.8) was observed over South Asia. The highest aerosols are laden over South Asia and East China within 1–2 km, however, aerosol overshooting found up to 10 km due to the deep convection process. Whereas, integrated aerosol transport for OC during spring was found to be 5 times higher than the annual mean.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Yanxing Hu, Tao Che, Liyun Dai, Yu Zhu, Lin Xiao, Jie Deng, and Xin Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-63, https://doi.org/10.5194/essd-2022-63, 2022
Preprint withdrawn
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We propose a data fusion framework based on the random forest regression algorithm to derive a comprehensive snow depth product for the Northern Hemisphere from 1980 to 2019. This new fused snow depth dataset not only provides information about snow depth and its variation over the Northern Hemisphere but also presents potential value for hydrological and water cycle studies related to seasonal snowpacks.
Sally S.-C. Wang, Yun Qian, L. Ruby Leung, and Yang Zhang
Atmos. Chem. Phys., 22, 3445–3468, https://doi.org/10.5194/acp-22-3445-2022, https://doi.org/10.5194/acp-22-3445-2022, 2022
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This study develops an interpretable machine learning (ML) model predicting monthly PM2.5 fire emission over the contiguous US at 0.25° resolution and compares the prediction skills of the ML and process-based models. The comparison facilitates attributions of model biases and better understanding of the strengths and uncertainties in the two types of models at regional scales, for informing future model development and their applications in fire emission projection.
Enrico Scoccimarro, Daniele Peano, Silvio Gualdi, Alessio Bellucci, Tomas Lovato, Pier Giuseppe Fogli, and Antonio Navarra
Geosci. Model Dev., 15, 1841–1854, https://doi.org/10.5194/gmd-15-1841-2022, https://doi.org/10.5194/gmd-15-1841-2022, 2022
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This study evaluated the ability of the CMCC-CM2 climate model participating to the last CMIP6 effort, in representing extreme events of precipitation and temperature at the daily and 6-hourly frequencies. The 1/4° resolution version of the atmospheric model provides better results than the version at 1° resolution for temperature extremes, at both time frequencies. For precipitation extremes, especially at the daily time frequency, the higher resolution does not improve model results.
Huiming Lin, Yindong Tong, Chenghao Yu, Long Chen, Xiufeng Yin, Qianggong Zhang, Shichang Kang, Lun Luo, James Schauer, Benjamin de Foy, and Xuejun Wang
Atmos. Chem. Phys., 22, 2651–2668, https://doi.org/10.5194/acp-22-2651-2022, https://doi.org/10.5194/acp-22-2651-2022, 2022
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The Tibetan Plateau is known as
The Third Poleand is generally considered to be a clean area owing to its high altitude. However, it may receive be impacted by air pollutants transported from the Indian subcontinent. Pollutants generally enter the Tibetan Plateau in several ways. Among them is the Yarlung Zangbu–Brahmaputra Grand Canyon. In this study, we identified the influence of the Indian summer monsoon on the origin, transport, and behavior of mercury in this area.
Youhua Ran, Xin Li, Guodong Cheng, Jingxin Che, Juha Aalto, Olli Karjalainen, Jan Hjort, Miska Luoto, Huijun Jin, Jaroslav Obu, Masahiro Hori, Qihao Yu, and Xiaoli Chang
Earth Syst. Sci. Data, 14, 865–884, https://doi.org/10.5194/essd-14-865-2022, https://doi.org/10.5194/essd-14-865-2022, 2022
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Datasets including ground temperature, active layer thickness, the probability of permafrost occurrence, and the zonation of hydrothermal condition with a 1 km resolution were released by integrating unprecedentedly large amounts of field data and multisource remote sensing data using multi-statistical\machine-learning models. It updates the understanding of the current thermal state and distribution for permafrost in the Northern Hemisphere.
Guta Wakbulcho Abeshu, Hong-Yi Li, Zhenduo Zhu, Zeli Tan, and L. Ruby Leung
Earth Syst. Sci. Data, 14, 929–942, https://doi.org/10.5194/essd-14-929-2022, https://doi.org/10.5194/essd-14-929-2022, 2022
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Existing riverbed sediment particle size data are sparsely available at individual sites. We develop a continuous map of median riverbed sediment particle size over the contiguous US corresponding to millions of river segments based on the existing observations and machine learning methods. This map is useful for research in large-scale river sediment using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc.
Shichang Kang, Yulan Zhang, Pengfei Chen, Junming Guo, Qianggong Zhang, Zhiyuan Cong, Susan Kaspari, Lekhendra Tripathee, Tanguang Gao, Hewen Niu, Xinyue Zhong, Xintong Chen, Zhaofu Hu, Xiaofei Li, Yang Li, Bigyan Neupane, Fangping Yan, Dipesh Rupakheti, Chaman Gul, Wei Zhang, Guangming Wu, Ling Yang, Zhaoqing Wang, and Chaoliu Li
Earth Syst. Sci. Data, 14, 683–707, https://doi.org/10.5194/essd-14-683-2022, https://doi.org/10.5194/essd-14-683-2022, 2022
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The Tibetan Plateau is important to the Earth’s climate. However, systematically observed data here are scarce. To perform more integrated and in-depth investigations of the origins and distributions of atmospheric pollutants and their impacts on cryospheric change, systematic data of black carbon and organic carbon from the atmosphere, glaciers, snow cover, precipitation, and lake sediment cores over the plateau based on the Atmospheric Pollution and Cryospheric Change program are provided.
Jooyeop Lee, Martin Claussen, Jeongwon Kim, Je-Woo Hong, In-Sun Song, and Jinkyu Hong
Clim. Past, 18, 313–326, https://doi.org/10.5194/cp-18-313-2022, https://doi.org/10.5194/cp-18-313-2022, 2022
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It is still a challenge to simulate the so–called Green Sahara (GS), which was a wet and vegetative Sahara region in the mid–Holocene, using current climate models. Our analysis shows that Holocene greening is simulated better if the amount of soil nitrogen and soil texture is properly modified for the humid and vegetative GS period. Future climate simulation needs to consider consequent changes in soil nitrogen and texture with changes in vegetation cover for proper climate simulations.
Hong-Yi Li, Zeli Tan, Hongbo Ma, Zhenduo Zhu, Guta Wakbulcho Abeshu, Senlin Zhu, Sagy Cohen, Tian Zhou, Donghui Xu, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 665–688, https://doi.org/10.5194/hess-26-665-2022, https://doi.org/10.5194/hess-26-665-2022, 2022
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We introduce a new multi-process river sediment module for Earth system models. Application and validation over the contiguous US indicate a satisfactory model performance over large river systems, including those heavily regulated by reservoirs. This new sediment module enables future modeling of the transportation and transformation of carbon and nutrients carried by the fine sediment along the river–ocean continuum to close the global carbon and nutrient cycles.
Xueyuan Gao, Shunlin Liang, Dongdong Wang, Yan Li, Bin He, and Aolin Jia
Earth Syst. Dynam., 13, 219–230, https://doi.org/10.5194/esd-13-219-2022, https://doi.org/10.5194/esd-13-219-2022, 2022
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Numerical experiments with a coupled Earth system model show that large-scale nighttime artificial lighting in tropical forests will significantly increase carbon sink, local temperature, and precipitation, and it requires less energy than direct air carbon capture for capturing 1 t of carbon, suggesting that it could be a powerful climate mitigation option. Side effects include CO2 outgassing after the termination of the nighttime lighting and impacts on local wildlife.
Wenfeng Chen, Tandong Yao, Guoqing Zhang, Fei Li, Guoxiong Zheng, Yushan Zhou, and Fenglin Xu
The Cryosphere, 16, 197–218, https://doi.org/10.5194/tc-16-197-2022, https://doi.org/10.5194/tc-16-197-2022, 2022
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A digital elevation model (DEM) is a prerequisite for estimating regional glacier thickness. Our study first compared six widely used global DEMs over the glacierized Tibetan Plateau by using ICESat-2 (Ice, Cloud and land Elevation Satellite) laser altimetry data. Our results show that NASADEM had the best accuracy. We conclude that NASADEM would be the best choice for ice-thickness estimation over the Tibetan Plateau through an intercomparison of four ice-thickness inversion models.
Ye Liu, Yun Qian, and Larry K. Berg
Wind Energ. Sci., 7, 37–51, https://doi.org/10.5194/wes-7-37-2022, https://doi.org/10.5194/wes-7-37-2022, 2022
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Uncertainties in initial conditions (ICs) decrease the accuracy of wind speed forecasts. We find that IC uncertainties can alter wind speed by modulating the weather system. IC uncertainties in local thermal gradient and large-scale circulation jointly contribute to wind speed forecast uncertainties. Wind forecast accuracy in the Columbia River Basin is confined by initial uncertainties in a few specific regions, providing useful information for more intense measurement and modeling studies.
Eduardo Moreno-Chamarro, Louis-Philippe Caron, Saskia Loosveldt Tomas, Javier Vegas-Regidor, Oliver Gutjahr, Marie-Pierre Moine, Dian Putrasahan, Christopher D. Roberts, Malcolm J. Roberts, Retish Senan, Laurent Terray, Etienne Tourigny, and Pier Luigi Vidale
Geosci. Model Dev., 15, 269–289, https://doi.org/10.5194/gmd-15-269-2022, https://doi.org/10.5194/gmd-15-269-2022, 2022
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Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in their ability to reproduce present and future climate changes. Model realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. We here show that increasing resolution of up to ~ 25 km can help reduce model biases but not remove them entirely.
Huilin Huang, Yongkang Xue, Ye Liu, Fang Li, and Gregory S. Okin
Geosci. Model Dev., 14, 7639–7657, https://doi.org/10.5194/gmd-14-7639-2021, https://doi.org/10.5194/gmd-14-7639-2021, 2021
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This study applies a fire-coupled dynamic vegetation model to quantify fire impact at monthly to annual scales. We find fire reduces grass cover by 4–8 % annually for widespread areas in south African savanna and reduces tree cover by 1 % at the periphery of tropical Congolese rainforest. The grass cover reduction peaks at the beginning of the rainy season, which quickly diminishes before the next fire season. In contrast, the reduction of tree cover is irreversible within one growing season.
Chang-Hwan Park, Aaron Berg, Michael H. Cosh, Andreas Colliander, Andreas Behrendt, Hida Manns, Jinkyu Hong, Johan Lee, Runze Zhang, and Volker Wulfmeyer
Hydrol. Earth Syst. Sci., 25, 6407–6420, https://doi.org/10.5194/hess-25-6407-2021, https://doi.org/10.5194/hess-25-6407-2021, 2021
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In this study, we proposed an inversion of the dielectric mixing model for a 50 Hz soil sensor for agricultural organic soil. This model can reflect the variability of soil organic matter (SOM) in wilting point and porosity, which play a critical role in improving the accuracy of SM estimation, using a dielectric-based soil sensor. The results of statistical analyses demonstrated a higher performance of the new model than the factory setting probe algorithm.
Xiaona Chen, Shunlin Liang, Lian He, Yaping Yang, and Cong Yin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-279, https://doi.org/10.5194/essd-2021-279, 2021
Preprint withdrawn
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The present study developed a 39 year consistent 8-day 0.05 degree gap-free SCE dataset over the NH for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite based on the NOAA AVHRR-SR CDR and several contributory datasets. Compared with published SCE datasets, GLASS SCE has several advantages in snow cover studies, including long time series, finer spatial resolution (especially for years before 2000), and complete spatial coverage.
Jinlei Chen, Shichang Kang, Wentao Du, Junming Guo, Min Xu, Yulan Zhang, Xinyue Zhong, Wei Zhang, and Jizu Chen
The Cryosphere, 15, 5473–5482, https://doi.org/10.5194/tc-15-5473-2021, https://doi.org/10.5194/tc-15-5473-2021, 2021
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Sea ice is retreating with rapid warming in the Arctic. It will continue and approach the worst predicted pathway released by the IPCC. The irreversible tipping point might show around 2060 when the oldest ice will have completely disappeared. It has a huge impact on human production. Ordinary merchant ships will be able to pass the Northeast Passage and Northwest Passage by the midcentury, and the opening time will advance to the next 10 years for icebreakers with moderate ice strengthening.
Keunmin Lee, Je-Woo Hong, Jeongwon Kim, Sungsoo Jo, and Jinkyu Hong
Atmos. Chem. Phys., 21, 17833–17853, https://doi.org/10.5194/acp-21-17833-2021, https://doi.org/10.5194/acp-21-17833-2021, 2021
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This study examine two benefits of urban forest, thermal mitigation and carbon uptake. Our analysis indicates that the urban forest reduces both the warming trend and urban heat island intensity. Urban forest is a net CO2 source despite larger photosynthetic carbon uptake because of strong contribution of ecosystem respiration, which can be attributed to the substantial amount of soil organic carbon by intensive historical soil use and warm temperature in a city.
Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, https://doi.org/10.5194/esd-12-1427-2021, 2021
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We address the question of how large an initial condition ensemble of climate model simulations should be if we are concerned with accurately projecting future changes in temperature and precipitation extremes. We find that for most cases (and both models considered), an ensemble of 20–25 members is sufficient for many extreme metrics, spatial scales and time horizons. This may leave computational resources to tackle other uncertainties in climate model simulations with our ensembles.