Distributions of Tropical Precipitation Cluster Power and Their Changes Under Global Warming. Part I: observational baseline and comparison to a high-resolution atmospheric model

Kevin M. Quinn and J. David Neelin

J. Climate, 30, 8033-8044, doi:0.1175/JCLI-D-16-0683.1. Group page.

Abstract. The total amount of precipitation integrated across a precipitation feature (contiguous precipitating grid cells exceeding a minimum rain rate) is a useful measure of the aggregate size of the disturbance, expressed as the rate of water mass lost or latent heat released, i.e. the power of the disturbance. The probability distribution of cluster power is examined over the Tropics using Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite-retrieved rain rates and global climate model output. Observed distributions are scale-free from the smallest clusters up to a cutoff scale at high cluster power, after which the probability drops rapidly. After establishing an observational baseline, precipitation from the High Resolution Atmospheric Model (HIRAM) at two horizontal grid spacings (roughly 0.5 and 0.25°) are compared. When low rain rates are excluded by choosing a minimum rain rate threshold in defining clusters, the model accurately reproduces observed cluster power statistics at both resolutions. Middle and end-of-century cluster power distributions are investigated in HIRAM in simulations with prescribed sea surface temperatures and greenhouse gas concentrations from a "business as usual" global warming scenario. The probability of high cluster power events increases strongly by end-of-century, exceeding a factor of 10 for the highest power events for which statistics can be computed. Clausius-Clapeyron scaling accounts for only a fraction of the increased probability of high cluster power events.

Citation:
Quinn, K. M., and J. D. Neelin, 2017: Distributions of Tropical Precipitation Cluster Power and Their Changes Under Global Warming. Part I: observational baseline and comparison to a high-resolution atmospheric model. J. Climate, 30, 8033-8044, doi:0.1175/JCLI-D-16-0683.1.

Acknowledgments. This project was supported in part by the National Science Foundation (NSF Grant AGS-1540518) and National Oceanic and Atmospheric Administration (NOAA Grants NA14OAR4310274 and NA15OAR4310097). Portions of this material have been presented at the 96th Annual Meeting of the American Meteorological Society in 2016. We thank the National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) for producing their observational precipitation data sets, available at http://disc.sci.gsfc.nasa.gov/datacollection/TRMM_3B42_daily_V7.html. Additionally, we would like to acknowledge the NOAA/Geophysical Fluid Dynamics Laboratory (GFDL) for producing their model output, available at http://nomads.gfdl.noaa.gov:8080/DataPortal/cmip5.jsp. We thank N. Berg, K. Hales-Garcia, M. Schwartz, and D. Walton for assistance in procedure development and J. Meyerson for graphics support.

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