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The entire collection of Earth and Environmental System Modeling Research Highlights can be accessed using the search below. You may also search the BER Research Highlights database by selecting Earth and Environmental System Modeling and/or Multisector Dynamics then selecting List.

Project: PCMDI – An Earth System Model Evaluation Project
Title Contact Institution Date
Predicting Slowdowns in Decadal Climate Warming Trends With Explainable Neural Networks RGMA Elizabeth A. Barnes Colorado State University
Constraining the Increased Frequency of Global Precipitation Extremes Under Warming RGMA Chad Thackeray University of California - Los Angeles
Superior Daily and Sub-Daily Precipitation Statistics for Intense and Long-Lived Storms in Global Storm-Resolving Models RGMA Hsi-Yen Ma Lawrence Livermore National Laboratory
Speeding up Detection of Climate Response to Emission Reductions RGMA Mark Zelinka Lawrence Livermore National Laboratory
Estimate Coupled Cloud Feedbacks from Inexpensive Short-Term Atmosphere-Only Simulations RGMA Stephen Klein Lawrence Livermore National Laboratory
Evaluating Climate Models’ Cloud Feedbacks Against Expert Judgment RGMA Stephen Klein Lawrence Livermore National Laboratory
Interpreting Modeled Oceans Across CMIP Eras and the Latest Observations RGMA Paul J. Durack Lawrence Livermore National Laboratory
Estimate Ensemble Size for Robust ENSO Evaluation in Climate Models RGMA Jiwoo Lee Lawrence Livermore National Laboratory
Learning to Correct Climate Projection Biases RGMA Hsi-Yen Ma Lawrence Livermore National Laboratory
Robust evaluation of ENSO in climate models: How many ensemble members are needed? RGMA David Bader Lawrence Livermore National Laboratory
On the Emergence of Human IInfluence on Surface Air Temperature Changes Over India RGMA Celine Bonfils Lawrence Livermore National Laboratory
Causes of Polar Amplification in Earth System Models RGMA Mark Zelinka Lawrence Livermore National Laboratory
Projected Changes to Hydroclimate Seasonality in the Continental United States RGMA Kate Marvel NASA Goddard Institute for Space Studies
The Convective-To-Total Precipitation Ratio and the “Drizzling” Bias in Climate Models RGMA Di Chen University of California - Los Angeles
Anthropogenic Influence on Extreme Precipitation Over Global Land Areas Seen in Multiple Observational Datasets RGMA Gavin D. Madakumbura University of California - Los Angeles
Satellites may Underestimate Warming in the Troposphere RGMA Benjamin Santer Lawrence Livermore National Laboratory
What are the Possible Causes of Wet-Season Dry Biases over Amazonia? RGMA Hsi-Yen Ma Lawrence Livermore National Laboratory
Performance Changes in Extratropical Modes of Variability Across CMIP Generations RGMA Jiwoo Lee Lawrence Livermore National Laboratory
Observational Constraints on Low Cloud Feedback Reduce Uncertainty of Climate Sensitivity RGMA Timothy A. Myers Lawrence Livermore National Laboratory
Emergent Constraints on Climate Sensitivities RGMA Chad Thackeray University of California - Los Angeles
Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways RGMA Jiwoo Lee Lawrence Livermore National Laboratory
Natural Variability Helps to Explain the Gap Between Atmospheric Warming in Satellite Observations and Climate Models RGMA Stephen Po-Chedley Lawrence Livermore National Laboratory
Climate Models Underestimate Diversity of Synoptic Conditions Associated With Extreme Precipitation Over California RGMA Jesse Norris University of California - Los Angeles
Assessing Prior Emergent Constraints on Surface Albedo Feedback in the Latest Earth System Models RGMA Chad Thackeray University of California - Los Angeles
New Insights in Climate Science in 2020 RGMA Mark Zelinka Lawrence Livermore National Laboratory
Evaluating El Niño in Climate Models With the CLIVAR 2020 ENSO Metrics Package RGMA Jiwoo Lee Lawrence Livermore National Laboratory
Evaluating the Diurnal and Semidiurnal Cycle of Precipitation in CMIP6 Models Using Satellite- and Ground-Based Observations RGMA Peter Gleckler Lawrence Livermore National Laboratory
Climate Models Simulate Extreme Precipitation With Sharply Contrasting Physical Mechanisms RGMA Jesse Norris University of California - Los Angeles
A Better Way to Gain Insights into Climate Model Moist Process Errors RGMA Hsi-Yen Ma Lawrence Livermore National Laboratory (LLNL)
Greater Committed Warming After Accounting for the Pattern Effect RGMA Mark Zelinka Lawrence Livermore National Laboratory

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