Stephen Po-Chedley | 18-ERD-054
Project Overview
The rate and geographic pattern of atmospheric warming are key indicators of historical climate change and play a role in modulating future changes in Earth's climate. The past and future evolution of atmospheric temperature is simulated using global climate models, while observational estimates of past warming are derived from satellite microwave measurements. Individual climate models simulate widely varying rates of past and future atmospheric warming, and most model simulations exhibit greater temperature change in the troposphere (the lowest 10 kilometers of the atmosphere) than satellite observations between 1979 and 2020.
This project examined intermodel differences in the pattern of atmospheric warming and how these differences influence climate feedbacks that can amplify or damp the rate of global surface warming. A key result is that climate model representation of the current climate can influence climate feedbacks and simulation of future climate changes. Another focus of this project was to analyze how models respond to different input datasets, such as volcanic aerosols or sea surface temperature (in atmosphere-only simulations). We find that different prescribed inputs can affect simulated changes in atmospheric temperature, even though "input uncertainty" is often unconsidered in model-observational comparisons. A final focus of this research project was to consider the influence of natural internal climate variability on satellite-era changes in climate. Although Earth is warming substantially due to anthropogenic emissions of greenhouse gases, the observed warming rate can be modulated by natural variations in Earth's climate. We find that natural climate variability has slowed the rate of tropical tropospheric warming, which explains model-satellite differences in the rate of tropospheric warming.
Mission Impact
This research contributed to the climate program by improving capabilities needed to analyze a large quantity of climate model simulation output and to compare model data with observations. More broadly, the research findings help advance our understanding of recent and future changes in climate, which advances the Department of Energy's mission to address energy and environmental challenges. Since climate and energy are interrelated, improvements in our ability to understand past changes and simulate future climate changes enhances our ability to make confident energy policy decisions.
Publications, Presentations, and Patents
Christy, J. R., et al. 2018. "Global Climate: Tropospheric Temperature [in ‘State of the Climate in 2017']." Bulletin of the American Meteorological Society 99, 8: S16-18. doi:10.1175/2018BAMSStateoftheClimate.1. LLNL-JRNL-746708
——— 2019 "Global Climate: Tropospheric Temperature [in ‘State of the Climate in 2018']." Bulletin of the American Meteorological Society 100, 9: S17-19. doi:10.1175/2019BAMSStateoftheClimate.1. LLNL-JRNL-772017
——— 2020. "Global Climate: Tropospheric Temperature [in ‘State of the Climate in 2019']." Bulletin of the American Meteorological Society 101, no. 8 (2020): S30-32. doi:10.1175/2020BAMSStateoftheClimate.1. LLNL-JRNL-811903
Feldl, N., et al. 2020. "Sea ice and atmospheric circulation shape the high-latitude lapse rate feedback." npj Climate and Atmospheric Science 3, 1: 1-9. doi:10.1038/s41612-020-00146-7. LLNL-JRNL-783239
Po-Chedley, S., et al. 2018a. "Sources of Intermodel Spread in the Lapse Rate and Water Vapor Feedbacks." Journal of Climate 31, 8. doi:10.1175/JCLI-D-17-0674.1. LLNL-JRNL-739332
——— 2018b. "On the Intermodel Spread of the Lapse Rate and Water Vapor Feedbacks." Oregon State University, Corvallis, OR, September 2018. LLNL-PRES-758891
——— 2018c. "Climate Constraint Reflects Forced Signal." Nature 563, 7729: E6-9. doi: 10.1038/s41586-018-0640-y. LLNL-JRNL-748281
——— 2019a. "The Influence of Climatology on Model Feedbacks." NASA Langley Seminar, Langley, VA, March 2019. LLNL-PRES-758949
——— 2019b. "Climatological Controls on the Response of Tropical Clouds and Relative Humidity to Greenhouse Gas Forcing." Naval Postgraduate School Department of Meteorology Colloquium, Monterey, CA, March 2019. LLNL-PRES-769519
——— 2019c. "Climatology Explains Intermodel Spread in Tropical Upper Tropospheric Cloud and Relative Humidity Response to Greenhouse Warming." Geophysical Research Letters 46, 22: 13399-409. doi:10.1029/2019GL084786. LLNL-JRNL-783140
——— 2019d. " Climatological controls on the response of tropical clouds and relative humidity to greenhouse gas forcing." CFMIP, Mykonos, Greece, October 2019. LLNL-PRES-793026
Rieger, L. A., et al. 2020. "Quantifying CanESM5 and EAMv1 Sensitivities to Mt. Pinatubo Volcanic Forcing for the CMIP6 Historical Experiment." Geoscientific Model Development 13, 10: 4831-43. doi:10.5194/gmd-13-4831-2020. LLNL-JRNL-800287
Santer, B. D., et al. 2019. "Celebrating the Anniversary of Three Key Events in Climate Change Science." Nature Climate Change 9, 3: 180-82. doi:10.1038/s41558-019-0424-x. LLNL-JRNL-758507
Siler, N., et al. 2019. "Natural Variability Has Slowed the Decline in Western U.S. Snowpack Since the 1980s." Geophysical Research Letters 46, 1: 346-55. doi:10.1029/2018GL081080. LLNL-JRNL-758571
Zelinka, M. D., et al. 2020. "Causes of Higher Climate Sensitivity in CMIP6 Models." Geophysical Research Letters 47, 1: 1-12. doi:10.1029/2019GL085782. LLNL-JRNL-791582
