Regional climate models are important research tools available to scientists around the world, including in economically developing nations (EDNs). The Earth Systems Physics (ESP) group of the Abdus Salam International Centre for Theoretical Physics (ICTP) maintains and distributes a state-of-the-science regional climate model called the ICTP Regional Climate Model version 3 (RegCM3), which is currently being used by a large research community for a diverse range of climate-related studies. The RegCM3 is the central, but not only, tool of the ICTP-maintained Regional Climate Research Network (RegCNET) aimed at creating south–south and north–south scientific interactions on the topic of climate and associated impacts research and modeling. In this paper, RegCNET, RegCM3, and illustrative results from RegCM3 benchmark simulations applied over south Asia, Africa, and South America are presented. It is shown that RegCM3 performs reasonably well over these regions and is therefore useful for climate studies in EDNs.

Como a América do Sul se estende por diferentes latitudes e possui formas de relevo variadas, proporciona a atuação e o desenvolvimento de diferentes sistemas atmosféricos, os quais contribuem para a não homogeneidade climática da região. Portanto o objetivo deste estudo é apresentar uma revisão dos sistemas atmosféricos que atuam nos diferentes setores do continente sul-americano e que contribuem para a precipitação.

This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of Sao Paulo, Brazil, over the period 1933–2005, based on the peaks‐over‐threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually, a GPD model is fitted to a sample of POT values selected with a constant threshold. However, in this work we use time‐dependent thresholds, composed of relatively largepquantiles (for examplepof 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several values ofp. Four different GPD models (GPD‐1, GPD‐2, GPD‐3, and GDP‐4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time‐varying covariates were incorporated into scale parameter of GPD‐2, GPD‐3, and GPD‐4, describing annual cycle in GPD‐2, linear trend in GPD‐3, and both annual cycle and linear trend in GPD‐4. The GPD‐1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models we used rescaled Akaike Information Criterion (AIC) with second‐order bias correction. This criterion isolates GPD‐3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non‐parametric Mann–Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds, withp‐value being virtually zero. Therefore, there is strong evidence that high quantiles of daily rainfall in the city of Sao Paulo have been increasing in magnitude and frequency over time. For example, 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright © 2008 Royal Meteorological Society