WRF10km with bias corrected CMIP5 CESM forcing over India

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.

Citation proposal
Anasuya Barik (Indian Institute of Technology Delhi) - Sanjeeb Kumar Sahoo (Indian Institute of Technology Delhi) - Sarita Kumari (Indian Institute of Technology Delhi) - Prof. Dr. Somnath Baidya Roy (Indian Institute of Technology Delhi). WRF10km with bias corrected CMIP5 CESM forcing over India. https://gdk.gdi-de.org/geonetwork/srv/api/records/de.dkrz.wdcc.iso3889911

Simple

Alternate title: WRF10km with bias corrected CMIP5 CESM forcing over India

Date ( Creation ): 2021-08-20

Identifier: None

Identifier: doi:10.26050/WDCC/WRF10km_wbc_C5_forc_oIndia / 10 km gridded hydrometeorological dataset developed by dynamical downscaling of the bias-corrected CMIP5 CESM RCP8.5 projections over India for current (2006-2015) and future (2091-2100) periods using WRF