Sensitivity of Present and Future Surface Temperatures to Precipitation Characteristics
Lynn, Barry H.
Kinney, PatrickNote: Order does not necessarily reflect citation order of authors.
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CitationLynn, Barry H., Leonard Druyan, Christian Hogrefe, Jimy Dudhia, Cynthia Rosenzweig, Richard Goldberg, David Rind, Richard Healy, Joyce Rosenthal, and Patrick Kinney. 2004. Sensitivity of Present and Future Surface Temperatures to Precipitation Characteristics. Climate Research 28, no. 1: 53–65.
AbstractA model simulation study shows that different diurnal cycles of precipitation are consistent with radically different present and future climate characteristics. In projected future climate scenarios, divergence in the time of day and type of precipitation had very divergent impacts on the radiation balance and consequently on surface temperatures. The relationship between the diurnal cycle of precipitation versus the present and future climate was examined using the GISS-MM5 (Goddard Institute for Space Studies Mesoscale Model 5) regional climate modeling system with 2 alternative moist convection schemes. June-August (JJA) mean surface temperatures of the 1990s, 2050s, and 2080s were simulated over the eastern US on a double nested 108/36 km domain, with the 36 km domain centered over the eastern US. In the 1990s, one model version simulated maxima in (convective) precipitation during the early morning, while the second model simulated the hour of precipitation maxima with considerable spatial variability (in better agreement with observations). In the futuristic climate scenarios, differences in the time of day of precipitation had very important impacts on the radiation balance at the surface. One version gave more precipitation at night and fewer clouds during the day, promoting higher surface temperatures. The alternative version created more precipitation during the day, consistent with diminished absorption of solar radiation at the surface and consequently lower surface temperatures. The results demonstrate the importance of improving cumulus parameterizations in regional mesoscale and global climate models and suggest that such improvements would lead to greater confidence in model projections of climate change.
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