Making Connections for the Future
I keep hearing that life has slowed down since the pandemic started 10-plus months ago. But whoever is saying that has not seen the work produced by the EESM scientists working on research funded by Regional & Global Model Analysis (RGMA). Read the full column.
– Renu Joseph, Program Manager
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FEATURED SCIENCE FOCUS AREA
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WACCEM Pushes Groundbreaking Research on Modeling the Water Cycle and Extreme Events
Planet Earth harbors 1.5 trillion cubic kilometers of water, which is cycled continuously between ocean, atmosphere, and land. The water cycle makes all of life possible, but unraveling its mysterious ways and understanding its past and future changes is challenging. The Water Cycle and Climate Extremes Modeling (WACCEM) Scientific Focus Area studies the roles of large-scale circulation and convection in the water cycle and the implications for variability and multidecadal changes of extreme events. Read more.
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RESEARCH HIGHLIGHTS
The following represent a small portion of RGMA research highlights published over the past few months. For a complete list of RGMA highlights, see our research highlights page. And if you're an RGMA-funded scientist, be sure to submit your research highlights here.
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Scientists at Lawrence Berkeley National Laboratory used a statistical machine learning technique to create a high-performance-computing tool for quantifying uncertainty in the detection of atmospheric rivers.
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Berkeley Lab scientists developed a method to identify which processes in regional climate models are responsible for errors in the simulation of peak snow accumulation in mountainous regions.
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Scientists investigated the predictive skill of different machine learning methods applied to estimating organic carbon content in soils and compared their results with the commonly used regression kriging approach.
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New research demonstrates that process-based models (PBMs) are valuable for problems that machine learning (ML) cannot solve alone. The authors encourage more PBM-ML synergies in the future.
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Research indicates that processes and mechanisms in the Atlantic and Pacific tropics are connected by interactive decadal timescale processes that, if initialized in models, may be predictive 1-2 years.
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Scientists have re-evaluated how much global warming is in store for the future if atmospheric greenhouse gas concentrations remain fixed at present-day levels—a quantity known as committed warming.
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The 2020 RGMA PI Meeting Brings a Community Together
While the COVID-19 pandemic changed the RGMA PI Meeting to a virtual format, there was no shortage of scientific discourse. Over the course of three and a half days in October 2020, there were more than 150 scientific presentations. Read more.
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Precipitation Processes Workshop Takes on Challenges
In late November, the NOAA-DOE Precipitation Processes and Predictability Workshop focused on advancing the understanding of precipitation processes and predictability and improvement of modeling and prediction at a broad range of scales. Read more.
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RGMA Research Featured at AGU and AMS Meetings
Organizers of the American Geophysical Union (AGU) Fall Meeting and the American Meteorological Society (AMS) Annual Meeting found creative solutions to replicate the camaraderie of in-person meetings. And at both virtual conferences, RGMA was well represented. Read more.
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Four RGMA-Connected Scientists Receive Honors
Two RGMA scientists were honored at the December 2020 AGU Fall Meeting. Two others were honored during the January 2021 AMS Annual Meeting. Read more.
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DOE Launches COMPASS
 The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales (COMPASS) Great Lakes Modeling (GLM) pilot study will focus on enhancing predictive understanding of freshwater coastal systems, especially how they respond to climate warming, land-use and land-cover, and other perturbations at watershed to regional scales, with a focus on the broader Great Lakes Region. More information will soon be published on the EESM website.
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EVENTS & MEETINGS
Do you have a meeting or event to share? Let us know, and we’ll help spread the word. Visit the EESM website for more meetings of interest.
Workshop on Improvement and Calibration of Clouds in Models: A workshop on the improvement and calibration of clouds in models is scheduled from April 12 to 16. Initially planned to be held in Toulouse, France, the conference will be virtual unless the pandemic improves to allow for some small local gatherings. Abstracts are being accepted until February 28.
European Geosciences Union (EGU) 2021: From April 19 to 30, 2021, the European Geosciences Union (EGU) will host vEGU21: Gather Online, a virtual meeting that will be held in place of the General Assembly in Vienna, Austria. In addition to almost 700 scientific sessions, the meeting will include the 2020 and 2021 award ceremonies and lectures, mentoring, and networking events. Register by March 31 to get early registration rates.
Asia Oceania Geosciences Society (AOGS) Annual Meeting: AOGS plans to be virtual for its 18th annual meeting, which will be held from August 1 to 6. Submit abstracts now until February 23.
International Conference on Clouds and Precipitation 2020: This conference is postponed until 2021. The abstract submission system will reopen later this year, so abstracts from the 2020 conference can be revised, or new abstracts can be submitted. Abstract submissions are due on February 9.
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PUBLICATIONS
Below are RGMA-related publications from the past quarter. For a complete list of journal articles and other recent publications, see our publications list. If you are an RGMA-funded scientist, be sure to submit your publications here.
Hu, H, L Leung, and Z Feng. 2020. "Understanding the Distinct Impacts of MCS and Non-MCS Rainfall on the Surface Water Balance in the Central United States Using a Numerical Water-Tagging Technique." Journal of Hydrometeorology 21(10): 2343-2357. https://doi.org/10.1175/jhm-d-20-0081.1.
Letson, F, T Shepherd, R Barthelmie, and SC Pryor. 2020. "WRF Modeling of Deep Convection and Hail for Wind Power Applications." Journal of Applied Meteorology and Climatology 59(10): 1717-1733. https://doi.org/10.1175/jamc-d-20-0033.1.
Risser, M, and M Wehner. 2020. "The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models." Advances in Statistical Climatology, Meteorology and Oceanography 6(2): 115-139. https://doi.org/10.5194/ascmo-6-115-2020.
McClenny, E, P Ullrich, and R Grotjahn. 2020. "Sensitivity of Atmospheric River Vapor Transport and Precipitation to Uniform Sea‐Surface Temperature Increases." Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2020jd033421.
Pryor, S, R Barthelmie, M Bukovsky, L Leung, and K Sakaguchi. 2020. "Climate Change Impacts on Wind Power Generation." Nature Reviews Earth & Environment. https://doi.org/10.1038/s43017-020-0101-7.
Szinai, J, R Deshmukh, D Kammen, and A Jones. 2020. "Evaluating Cross-Sectoral Impacts of Climate Change and Adaptions on the Energy-Water Nexus." Environmental Research Letters. https://doi.org/10.1088/1748-9326/abc378.
Beckage, B, K Lacasse, JM Winter, LJ Gross, N Fefferman, FM Hoffman, SS Metcalf, et al. 2020. "The Earth Has Humans, So Why Don’t Our Climate Models?" Climatic Change. https://doi.org/10.1007/s10584-020-02897-x.
Mishra, U, S Gautam, WJ Riley, and FM Hoffman. 2020. "Ensemble Machine Learning Approach Improves Predicted Spatial Variation of Surface Soil Organic Carbon Stocks in Data-Limited Northern Circumpolar Region." Frontiers in Big Data 3: 40. https://doi.org/10.3389/fdata.2020.528441.
Lora, J, C Shields, and J Rutz. 2020. "Consensus and Disagreement in Atmospheric River Detection: ARTMIP Global Catalogues." Geophysical Research Letters 47(20). https://doi.org/10.1029/2020gl089302.
Bailey, D, M Holland, A DuVivier, E Hunke, and A Turner. 2020. "Impact of a New Sea Ice Thermodynamic Formulation in the CESM2 Sea Ice Component." Journal of Advances in Modeling Earth Systems 12(11). https://doi.org/10.1029/2020ms002154.
Ma, H, AC Siongco, SA Klein, S Xie, AR Karspeck, K Raeder, JL Anderson, et al. 2020. "On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature." Journal of Climate. https://doi.org/10.1175/jcli-d-20-0338.1.
Fan, J, Y Zhang, Z Li, J Hu, and D Rosenfeld. 2020. "Urbanization-induced land and aerosol impacts on sea-breeze circulation and convective precipitation." Atmospheric Chemistry and Physics 20(22): 14163-14182. https://doi.org/10.5194/acp-20-14163-2020.
Voigt, A, N Albern, P Ceppi, K Grise, Y Li, and B Medeiros. 2020. "Clouds, Radiation, and Atmospheric Circulation in the Present‐Day Climate and Under Climate Change." WIREs Climate Change. https://doi.org/10.1002/wcc.694.
Tsai, W, K Fang, X Ji, K Lawson, and C Shen. 2020. "Revealing Causal Controls of Storage-Streamflow Relationships With a Data-Centric Bayesian Framework Combining Machine Learning and Process-Based Modeling." Frontiers in Water 2. https://doi.org/10.3389/frwa.2020.583000.
Pallotta, G, and B Santer. 2020. "Multi-Frequency Analysis of Simulated versus Observed Variability in Tropospheric Temperature." Journal of Climate 33(23): 10383-10402. https://doi.org/10.1175/jcli-d-20-0023.1.
Konduri, VS, J Kumar, WW Hargrove, FM Hoffman, and AR Ganguly. 2020. "Mapping crops within the growing season across the United States." Remote Sensing of Environment 251: 112048. https://doi.org/10.1016/j.rse.2020.112048.
Pryor, S, F Letson, and R Barthelmie. 2020. "Variability in Wind Energy Generation Across the Contiguous United States." Journal of Applied Meteorology and Climatology 59(12): 2021-2039. https://doi.org/10.1175/jamc-d-20-0162.1.
O'Brien, T, M Risser, B Loring, A Elbashandy, H Krishnan, J Johnson, C Patricola, et al. 2020. "Detection of atmospheric rivers with inline uncertainty quantification: TECA-BARD v1.0.1." Geoscientific Model Development 13(12): 6131-6148. https://doi.org/10.5194/gmd-13-6131-2020.
Meehl, G, A Hu, F Castruccio, M England, S Bates, G Danabasoglu, S McGregor, J Arblaster, S Xie, and N Rosenbloom. 2020. "Atlantic and Pacific Tropics Connected by Mutually Interactive Decadal-Timescale Processes." Nature Geoscience. https://doi.org/10.1038/s41561-020-00669-x.
Dagon, K, B Sanderson, R Fisher, and D Lawrence. 2020. "A Machine Learning Approach to Emulation and Biophysical Parameter Estimation with the Community Land Model, Version 5." Advances in Statistical Climatology, Meteorology and Oceanography 6(2): 223-244. https://doi.org/10.5194/ascmo-6-223-2020.
Najibi, N, A Mazor, N Devineni, C Mossel, and JF Booth. 2020. "Understanding the Spatial Organization of Simultaneous Heavy Precipitation Events Over the Conterminous United States." Journal of Geophysical Research: Atmospheres 125. https://doi.org/10.1029/2020JD033036.
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