Joint IMAGe CGD - Probabilistic Estimation and Validation of Regional Precipitation Changes Using Statistical Downscaling Method

04/18/2012 - 12:00pm
Mesa Laboratory - Damon Room

LIANG NING, The Pennsylvania State University

A statistical downscaling method based on self-organizing maps (SOMs) is used to produce high-resolution, downscaled precipitation estimates over the state of Pennsylvania in the mid-Atlantic region of the U.S. using the National Center for Environmental Prediction (NCEP) and nine General Circulation Models (GCMs) synoptic circulation data.  Over the historical period, the downscaling method provides a faithful reproduction of the observed probability distributions and temporal characteristics of precipitation on both daily and monthly time scales. The downscaled precipitation fields show significant improvements over the raw GCM precipitation fields with regard to observed average monthly precipitation amounts, average monthly numbers of rainy days, and standard deviations of monthly precipitation amounts.

When applied to the future period 2046-2065, downscaling predicts increases in annual and winter precipitation, and decrease in summer precipitation when ensemble averaged across the nine GCMs.  In order to examine the sensitivity of precipitation change to the water vapor increase brought by global warming, two downscaling approaches are used: one includes the specific humidity in the downscaling algorithm and the other does not.  The downscaled precipitation increases employing specific humidity are larger than those without it.  Application of downscaling reduces the inter-GCM variation, suggesting that some of spread among models in the raw projected precipitation may result from differences in precipitation parameterization schemes rather than fundamentally different climate responses. Projected changes in the North Atlantic Oscillation (NAO) are found to be significantly related to changes in winter precipitation in the downscaled results but not for the raw GCM results, suggesting that the downscaling more effectively captures the influence of climate dynamics on projected changes in winter precipitation.

Mesa Laboratory – Damon Room 

Wednesday, April 18, 2012