An Environmental Watch System for the Andean Countries: El Observatorio Andino

An experimental Environmental Watch System, the so-called Observatorio Andino (OA), has been implemented in Venezuela, Colombia, Ecuador, Peru, Bolivia, and Chile over the past 2 yr. The OA is a collaborative and regional network that aims to monitor several environmental variables and develop accurate forecasts based on different scientific tools. Its overall goal is to improve risk assessments, set up early warning systems, support decision-making processes, and provide easily and intuitively understandable spatial maps to end users. The initiative works under the scientific and logistic coordination of the Centro de Modelado Científico (CMC) at Zulia University, Venezuela, and the Centro Internacional para la Investigación del Fenómeno “El Niño” (CIIFEN), and it is operated at a local level by the national weather services (NWSs) of the above-mentioned six Andean nations. The OA provides several freely available model outputs, including meteorological and hydrological forecasts, droughts, fire and flood indices, ecosystems dynamics, climate and health applications, and 5-day high-resolution oceanographic predictions for the eastern Pacific. This article briefly describes the current products, methodologies, and dynamical and statistical modeling outputs provided by the OA. Also, a discussion on how these sets of tools have been put together as a coordinated scientific watch and forecast system for each country and for the entire region is presented. Our experiences over the past 2 yr suggest that this initiative would significantly improve the current decision-making processes in Andean countries

The Same-Source Parallel MM5

With the March 1998 release of the Penn State University/NCAR Mesoscale Model (MM5), the official version of the model (MM5v2 Release 8) now runs on distributed memory (DM) message-passing platforms. Under an IBM-funded effort, source translation and runtime library support minimize the impact of parallelization on the original model source code with the result that the majority of code is line-for-line identical with the original version. Parallel performance and scaling are equivalent to earlier, hand-parallelized versions; the modifications have no effect when the code is compiled and run without the DM option. Supported computers include the IBM SP2, Cray T3E, and Fujitsu VPP. The approach is compatible with sharedmemory parallelism, allowing DM/SM hybrid parallelization on distributed memory clusters of SMP. Preliminary results show that scalability on distributed shared memory computers such as the SGI Origin 2000 also benefits from a distributed memory programming mode..

The Same-Source Parallel MM5

Beginning with the March 1998 release of the Penn State University/NCAR Mesoscale Model (MM5), and continuing through eight subsequent releases up to the present, the official version has run on distributed -memory (DM) parallel computers. Source translation and runtime library support minimize the impact of parallelization on the original model source code, with the result that the majority of code is line-for-line identical with the original version. Parallel performance and scaling are equivalent to earlier, hand-parallelized versions; the modifications have no effect when the code is compiled and run without the DM option. Supported computers include the IBM SP, Cray T3E, Fujitsu VPP, Compaq Alpha clusters, and clusters of PCs (so-called Beowulf clusters). The approach also is compatible with shared-memory parallel directives, allowing distributed-memory/shared-memory hybrid parallelization on distributed-memory clusters of symmetric multiprocessors