High-resolution dynamical downscaling experiment outputs data over Reunion and Mauritius islands in the South-West Indian Ocean

The present article describes a dataset encompassing model outputs generated by the Weather Research and Forecasting (WRF) regional climate model. A high-resolution (1km) downscaling simulation was performed over two tropical islands, Reunion and Mauritius, situated in the South-West Indian Ocean (SWIO), with initial and boundary conditions provided by the ERA5 reanalysis with a global resolution of 0.25 degrees x 0.25 degrees. The simulation used three nested domains sequentially configured with spatial resolutions of 9, 3, and 1km, respectively, with a downscaling ratio of 3. The physical configurations of this simulation were determined through previous modeling studies and sensitivity tests. The published simulation data currently covers aperiod of 10 years, starting from 1991 (with the possibility to be extended to 30 years). Over 60 output variables were selected for publication with open access, including those related to the intermittent energy resources (e.g., surface solar radiation and its direct/diffuse components, wind speed/direction at multiple vertical levels, and precipitation, of interest for the run-off-river hydropower), as well as the widely used climatic/meteorological variables (e.g., temperature, pressure, humidity, etc.) at a temporal resolution varying from a day up to 30 minutes. All the data are available through an open-access data server, where an intelligent algorithm is applied to simplify the download process for data users. For the first time, a long-term, high-resolution climate/meteorological dataset covering Reunion and Mauritius has been simulated and published as open-access data, yielding substantial benefits to studies on climate modeling, weather forecasting, and even those related to climate change in the SWIO region. In particular, this dataset will enable a better understanding of the temporal and spatial characteristics of intermittent climate-related energy resources, consequently facilitating their implementation towards a green and low-carbon future.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)