2007 Articles

Regional Climate Model–Simulated Timing and Character of Seasonal Rains in South America

Rauscher, Sara A.; Seth, Anji; Liebmann, Brant; Quan, Jian-Hua; Camargo, Suzana J.

The potential of an experimental nested prediction system to improve the simulation of subseasonal rainfall statistics including daily precipitation intensity, rainy season onset and withdrawal, and the frequency and duration of dry spells is evaluated by examining a four-member ensemble of regional climate model simulations performed for the period 1982–2002 over South America. The study employs the International Centre for Theoretical Physics (ICTP) regional climate model, version 3 (RegCM3), driven with the NCEP–NCAR reanalysis and the European Centre–Hamburg GCM, version 4.5. Statistics were examined for five regions: the northern Amazon, southern Amazon, the monsoon region, Northeast Brazil, and southeastern South America. RegCM3 and the GCM are able to replicate the distribution of daily rainfall intensity in most regions. The analysis of the rainy season timing shows the observed onset occurring first over the monsoon region and then spreading northward into the southern Amazon, in contrast to some previous studies. Correlations between the onset and withdrawal date and SSTs reveal a strong relationship between the withdrawal date in the monsoon region and SSTs in the equatorial Pacific, with above-average SSTs associated with late withdrawal. Over Northeast Brazil, the regional model errors are smaller than those shown by the GCM, and the strong interannual variability in the timing of the rainy season is better simulated by RegCM3. However, the regional model displays an early bias in onset and withdrawal over the southern Amazon and the monsoon regions. Both RegCM3 and the GCM tend to underestimate (overestimate) the frequency of shorter (longer) dry spells, although the differences in dry spell frequency during warm and cold ENSO events are well simulated. The results presented here show that there is potential for added value from the regional model in simulating subseasonal statistics; however, improvements in the physical parameterizations are needed for this tropical region.