The Bias Corrected CESMv1 data for current (2006-2015) and future (2091-2100) for RCP8.5 emission scenario at coarser resolution has been downscaled to 10km resolution over India using the Weather Research and Forecasting (WRF) model. The climate variables included are 2m Temperature, relative humidity, wind speed, total precipitation, mean surface shortwave flux, top-of-atmosphere outgoing longwave radiation, mean surface latent and sensible heat fluxes along with the latitude, longitude, and time information. The dataset covers the Indian National Territory region at a 369 x 369 grid. The data is available at three temporal resolutions: Daily TS, Monthly TS, and Monthly Climatology. The dataset has been structured into a total of 60 files (10 variables x 3 temporal resolutions x 2 periods packed in self-explanatory NetCDF format. The daily, monthly, and monthly climatology files contain 369x369x3650, 369x369x30, and 369x369x12 data points, respectively. The entire dataset is about 100 GB in size. The WRF version used for this project is WRF 3.8.1. . The WRF-ARW source codes and suitable tutorials are available free to users as an open-source model in the NCAR’s https://www2.mmm.ucar.edu/wrf/users/download/get_sources.html website.

The Bias Corrected CESMv1 data for mid-century (2041-2050) for RCP8.5 emission scenario at coarser resolution has been downscaled to 10km resolution over India using the Weather Research and Forecasting (WRF) model. The climate variables included are 2m Temperature (t2m), relative humidity (rh), wind speed (wspd), total precipitation (prec), mean surface shortwave flux (sw), top-of-atmosphere outgoing longwave radiation (lw), mean surface latent (lhf) and sensible (shf) heat fluxes along with the latitude, longitude, and time information. The dataset covers the Indian National Territory region at a 369 x 369 grid. The data is available at three temporal resolutions: Daily TS, Monthly TS, and Monthly Climatology. The dataset has been structured into a total of 30 files (10 variables x 3 temporal resolutions) packed in self-explanatory NetCDF format. The daily, monthly, and monthly climatology files contain 369x369x3650, 369x369x30, and 369x369x12 data points, respectively. The entire dataset is about 30 GB in size. The precipitation files in the older version contained hourly accumulated values for every day. This version contains the correct daily accumulated, monthly accumulated and monthly climatology precipitation data.

While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) and Regional Earth System Models (RESMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model (Version v3.9) for the period 2006-2010 in a resolution of 0.1 degree horizontal resolution. Conclusions about suitable physical parameterization schemes may vary within the study area. We therefore want to stimulate the development of own performance evaluation studies for climate simulations or subsequent impact studies over specific (sub-)regions in NSSA. For this reason, selected climate surface variables of the physics ensemble (i.e. the 16 experiments from 2006-2010) are provided. For more information about the setup of the experiments, please see: Laux et al., 2021: A high-resolution regional climate model physics ensemble for Northern sub-Saharan Africa. Frontiers in Earth Science (under revision).

While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) and Regional Earth System Models (RESMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model (Version v3.9) for the period 2006-2010 in a resolution of 0.1 degree horizontal resolution. Conclusions about suitable physical parameterization schemes may vary within the study area. We therefore want to stimulate the development of own performance evaluation studies for climate simulations or subsequent impact studies over specific (sub-)regions in NSSA. For this reason, selected climate surface variables of the physics ensemble (i.e. the 16 experiments from 2006-2010) are provided. For more information about the setup of the experiments, please see: Laux et al., 2021: A high-resolution regional climate model physics ensemble for Northern sub-Saharan Africa. Frontiers in Earth Science (under revision).

The data was produced employing the Advanced Research Weather Research and Forecasting model (WRF) version 4.1.2 (Skamarock et al., 2019) for the dynamical downscaling of GCM data. WRF is a fully compressible non-hydrostatic atmospheric simulation system. Two sensitivity simulations were conducted using 15-year time slices for the present day and the mid-Pliocene simulated by ECHAM5 as initial and boundary conditions (Mutz et al., 2018; Botsyun et al., 2020). Except for the atmospheric forcing data, other parameters were the same in both simulations. The model domain has a grid spacing of 30 km. In the vertical direction, 28 terrain-following eta-levels were used. The model time steps are 120 seconds with a 6 hourly data output and are aggregated to daily values in post processing. The boundary conditions were updated every 6 h. The daily re-initialization strategy from Maussion et al. (2011) and Maussion et al. (2014) were employed: each simulation starts at 12 UTC and contains 36 h, with the first 12 h as the spin-up time. This strategy kept the large-scale circulation patterns simulated by WRF closely constrained by the forcing data, while concurrently allowing WRF to develop the mesoscale atmospheric features. Physical parameterization schemes were consistent with the ones used for high-resolution dynamical downscaling in High Mountain Asia in Wang et al. (2021). The data format follows the guidelines of the [UC]² Data Standard (http://www.uc2-program.org/uc2_data_standard.pdf).

These data are made available as part of paper: S. J. Gonzalez-Roji, J. Saenz, G. Ibarra-Berastegi, J. Diaz de Argandona (2018) Moisture balance over the Iberian Peninsula according to a regional climate model, Journal of Geophysical Research 123(2):708-729. The dataset holds selected postprocessed files that allow to reproduce all the results in the paper. An analysis of the atmospheric branch of the hydrological cycle by means of a 15 km resolution numerical integration performed using Weather Research and Forecasting (WRF) nested in ERA Interim is presented. Two WRF experiments covering the period 2010–2014 were prepared. The first one (N) was configured as in standard numerical downscaling experiments. The second one (D), with the same parameterizations, included a step of 3DVAR data assimilation every 6 h. Experiment D: -windowed-D-AI: Analysis increments (T2, Q2), 2010-2014 for the D experiment -windowed-wavacurip4paper-D: Netcdf files corresponding to experiment D (using 3DVAR assimilation) and years 2010-2014 holding 3-hourly outputs from the run after selecting the window covering the Iberian Peninsula. Experiment N: -windowed-wavacurip4paper-N: Netcdf files corresponding to experiment N (no data assimilation) and years 2010-2014 holding 3-hourly outputs from the run after selecting the window covering the Iberian Peninsula

While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) and Regional Earth System Models (RESMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model (Version v3.9) for the period 2006-2010 in a resolution of 0.1 degree horizontal resolution. Conclusions about suitable physical parameterization schemes may vary within the study area. We therefore want to stimulate the development of own performance evaluation studies for climate simulations or subsequent impact studies over specific (sub-)regions in NSSA. For this reason, selected climate surface variables of the physics ensemble (i.e. the 16 experiments from 2006-2010) are provided. For more information about the setup of the experiments, please see: Laux et al., 2021: A high-resolution regional climate model physics ensemble for Northern sub-Saharan Africa. Frontiers in Earth Science (under revision).

The Bias Corrected CESMv1 data for current (2006-2015) and future (2091-2100) for RCP8.5 emission scenario at coarser resolution has been downscaled to 10km resolution over India using the Weather Research and Forecasting (WRF) model. The climate variables included are 2m Temperature, relative humidity, wind speed, total precipitation, mean surface shortwave flux, top-of-atmosphere outgoing longwave radiation, mean surface latent and sensible heat fluxes along with the latitude, longitude, and time information. The dataset covers the Indian National Territory region at a 369 x 369 grid. The data is available at three temporal resolutions: Daily TS, Monthly TS, and Monthly Climatology. The dataset has been structured into a total of 60 files (10 variables x 3 temporal resolutions x 2 periods packed in self-explanatory NetCDF format. The daily, monthly, and monthly climatology files contain 369x369x3650, 369x369x120, and 369x369x12 data points, respectively. The entire dataset is about 100 GB in size. The WRF version used for this project is WRF 3.8.1. . The WRF-ARW source codes and suitable tutorials are available free to users as an open-source model in the NCAR’s https://www2.mmm.ucar.edu/wrf/users/download/get_sources.html website.

While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) and Regional Earth System Models (RESMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model (Version v3.9) for the period 2006-2010 in a resolution of 0.1 degree horizontal resolution. Conclusions about suitable physical parameterization schemes may vary within the study area. We therefore want to stimulate the development of own performance evaluation studies for climate simulations or subsequent impact studies over specific (sub-)regions in NSSA. For this reason, selected climate surface variables of the physics ensemble (i.e. the 16 experiments from 2006-2010) are provided. For more information about the setup of the experiments, please see: Laux et al., 2021: A high-resolution regional climate model physics ensemble for Northern sub-Saharan Africa. Frontiers in Earth Science (under revision).

The Bias Corrected CESMv1 data for mid-century (2041-2050) for RCP8.5 emission scenario at coarser resolution has been downscaled to 10km resolution over India using the Weather Research and Forecasting (WRF) model. The climate variables included are 2m Temperature (t2m), relative humidity (rh), wind speed (wspd), total precipitation (prec), mean surface shortwave flux (sw), top-of-atmosphere outgoing longwave radiation (lw), mean surface latent (lhf) and sensible (shf) heat fluxes along with the latitude, longitude, and time information. The dataset covers the Indian National Territory region at a 369 x 369 grid. The data is available at three temporal resolutions: Daily TS, Monthly TS, and Monthly Climatology. The dataset has been structured into a total of 30 files (10 variables x 3 temporal resolutions) packed in self-explanatory NetCDF format. The daily, monthly, and monthly climatology files contain 369x369x3650, 369x369x120, and 369x369x12 data points, respectively. The entire dataset is about 30 GB in size. The precipitation files in the older version contained hourly accumulated values for every day. This version contains the correct daily accumulated, monthly accumulated and monthly climatology precipitation data.