Microphysical Sensitivity of Superparameterized Precipitation Extremes in the Contiguous United States Due to Feedbacks on Large‐Scale Circulation

• Published in: Earth and space science (Hoboken, N.J.) N.J.), 2020-07, Vol.7 (7), p.n/a
• Main Authors: Charn, Alexander B., Collins, William D., Parishani, Hossein, Risser, Mark D., O'Brien, Travis A.
• Format: Article
• Language: English
• Subjects: Atmospheric circulation; Boundary conditions; Climate Prediction Center Hourly Precipitation Dataset; Community Atmosphere Model; ENVIRONMENTAL SCIENCES; Experiments; extreme precipitation; ILIAD; microphysics; Precipitation; Rain; Rainfall; superparameterization
• ISSN: 2333-5084; 2333-5084
• DOI: 10.1029/2019EA000731

Superparameterized (SP) global climate models have been shown to better simulate various features of precipitation relative to conventional models, including its diurnal cycle as well as its extremes. While various studies have focused on the effect of differing microphysics parameterizations on precipitation within limited‐area cloud‐resolving models, we examine here the effect on contiguous U.S. (CONUS) extremes in a global SP model. We vary the number of predicted moments for hydrometeor distributions, the character of the rimed ice species, and the representation of raindrop self‐collection and breakup. Using a likelihood ratio test and accounting for the effects of multiple hypothesis testing, we find that there are some regional differences, particularly during spring and summer in the Southwest and the Midwest, in both the current climate and a warmer climate with uniformly increased sea surface temperatures. These differences are most statistically significant and widespread when the number of moments is changed. To determine whether these results are due to (fast) local effects of the different microphysics or the (slower) ensuing feedback on the large‐scale atmospheric circulation, we run a series of short, 5‐day simulations initialized from reanalysis data. We find that the differences largely disappear in these runs and therefore infer that the different parameterizations impact precipitation extremes indirectly via the large‐scale circulation. Finally, we compare the present‐day results with hourly rain gauge data and find that SP underestimates extremes relative to observations regardless of which microphysics scheme is used given a fixed model configuration and resolution. Key Points The choice of superparameterized Community Atmosphere Model (SPCAM) microphysics parameterization impacts the statistics of precipitation extremes through large‐scale circulation feedbacks Changes in precipitation extremes from present day to future, warmer climates are insensitive to microphysics parameterization in SPCAM Regardless of the microphysics scheme, the precipitation extremes simulated with SPCAM underestimate those observed via rain gauges