A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses

Abstract

We present an analysis of the seasonal, subseasonal, and diurnal variability of rainfall from COAPS LandAtmosphere Regional Reanalysis for the Southeast at 10-km resolution (CLARReS10). Most of our assessment focuses on the representation of summertime subseasonal and diurnal variability. Summer precipitation in the Southeast United States is a particularly challenging modeling problem because of the variety of regional-scale phenomena, such as sea breeze, thunderstorms and squall lines, which are not adequately resolved in coarse atmospheric reanalyses but contribute significantly to the hydrological budget over the region. We find that the dynamically downscaled reanalyses are in good agreement with station and gridded observations in terms of both the relative seasonal distribution and the diurnal structure of precipitation, although total precipitation amounts tend to be systematically overestimated. The diurnal cycle of summer precipitation in the downscaled reanalyses is in very good agreement with station observations and a clear improvement both over their ''parent'' reanalyses and over newer-generation reanalyses. The seasonal cycle of precipitation is particularly well simulated in the Florida; this we attribute to the ability of the regional model to provide a more accurate representation of the spatial and temporal structure of finer-scale phenomena such as fronts and sea breezes. Over the northern portion of the domain summer precipitation in the downscaled reanalyses remains, as in the ''parent'' reanalyses, overestimated. Given the degree of success that dynamical downscaling of reanalyses demonstrates in the simulation of the characteristics of regional precipitation, its favorable comparison to conventional newer-generation reanalyses and its cost-effectiveness, we conclude that for the Southeast United states such downscaling is a viable proxy for high-resolution conventional reanalysis.

Implications of Climate Change on Florida's Water Resources

“…They have included both statistical downscaling (Maurer et al 2007) and dynamical downscaling (Mearns et al 2012;Stefanova et al 2012) of temperature, precipitation and other climatic variables. Obeysekera et al (2011) document the evaluation of 112 finer-resolution (1/8 degree), statistically-downscaled ensemble datasets based on 15 climate models of the CMIP3 scenarios B1, A1B, and A2 for the period 1950(Maurer et al 2007).…”

Applying Downscaled Global Climate Model Data to a Hydrodynamic Surface-Water and Groundwater Model

“…The global ERA-40, CCSM, and GFDL data have been dynamically downscaled using the Scripps-Florida State University/Florida Climate Center version of the Regional Spectral Model (RSM; [25] [27] [28]. Data are downscaled for a historical period that ends in 2001 for the ERA-40 and 1999 for the CCSM and GFDL, and a future period that begins in 2038 for CCSM and GFDL.…”

“…Rainfall is a major portion of the water budget, and potential changes in rainfall rates and spatial/temporal patterns can have important implications. This paper describes an application of downscaled GCM precipitation data [25] [26], for historical and future conditions to develop hydrologic simulations with the BISCAYNE/TIME model. The downscaled precipitation for historical conditions (1996-2001) from the ERA-40 is used, and the resulting BISCAYNE/TIME simulation is compared with the field-data-driven BISCAYNE/TIME simulation.…”

Seasonal prediction skill of winter temperature over North India

“…There has been a growing interest in the dynamical or statistical downscaling of the Global Circulation Model (GCM) seasonal and climate forecasts in producing regional-scale predictions (Shukla et al 2009;Stefanova et al 2012a). For such an approach in producing useful regional forecasts, the GCMs driving the regional predictions must have a reasonable fidelity to simulate the large-scale variability.…”