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° × 0.25°. 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 a period 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.

Understanding the space-time variability of Surface Solar Radiation (SSR) is mandatory for the prediction and, eventually, the skillful forecasting of photovoltaic energy production. This paper addresses the modulation of local-scale SSR over Reunion, a tropical island in the South-West Indian Ocean, by the leading modes of climate variability influencing both regional-scale and local-scale atmospheric convection and its associated cloud cover. Analyses focus on synoptic (tropical cyclones [TCs], synoptic convective regimes, including Tropical-Temperate Troughs [TTTs]) and intraseasonal (Madden-Julian Oscillation [MJO]) timescales. The SSR intra-daily variability is first assessed by a diurnal classification of SARAH-E satellite SSR data, and it is then related to the climate conditions mentioned above. SSR anomalies are found larger (smaller) on the windward (leeward) side of Reunion and in the summer (winter) season. The island-scale "cloudy" conditions can typically last 1 or 2 days. Nearby TCs can strongly reduce SSR by up to 50% on average, depending on their distances from Reunion, their sizes, and particularly, their longitudinal positions, which is observed for the first time. Nearby TCs are asso-ciated with significant negative SSR anomaly when located west of Reunion but with less significant or even positive anomaly when located east of the island. Synoptic convective regimes (the intraseasonal MJO) have a relatively weaker impact on SSR, with a value up to 13% (5%) of the mean value. Potential interactions between these SSR modulators are also investigated to understand better and eventually predict the mechanisms likely to modulate SSR (and thus photovoltaic electricity production) at sub-seasonal timescales.

The world needs energy for its social and economic development. In the growing population and industrialization, there is an increasing demand for energy worldwide. The fossil fuel resources are still major resources for fulfilling this energy demand though they are responsible for the increased GHG emissions. Renewable energy is an alternative and greener approach towards meeting increasing energy demand. The wind energy is one of the most prominent resources of greener and renewable energy. The islands of Mauritius and Reunion in the southwest Indian Ocean are blessed with wind resources. The wind energy can be used to meet the demand of energy requirement of these two islands by increasing the number of wind turbines. However, energy generation with wind turbines is sensitive to the variability in the surface wind due to climate variability. The surface wind data available is sparse due to limited ground-based observation. The data quality is also affected by instrumental errors, and data is available only for past and present. Regional Climate Models (RCMs) are the main source of climate information for the present and the future. However, simulations from RCMs deal with biases from various sources and therefore need to bias-corrected. Here we use a transfer function based on the method proposed by Li et al. (2010) for the bias-correction of surface wind over Reunion and Mauritius islands. For this purpose, RegCM4.7 RCM from CORDEX AFR22 domain has been chosen for the time period of 1981-2004. The data is interpolated at 9 km resolution and bias-corrected with respect to surface wind data obtained from ERA5 land reanalysis data. The bias-corrected results are validated with the ERA5 land reanalysis data set.