DOI: 10.48364/isimip.886955
title: ISIMIP2a atmospheric climate input data

description: The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for advanced estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate impacts across sectors.<br>ISIMIP2a is the first simulation round of the second phase of ISIMIP, focusing on historical simulations of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.<br>These datasets contain the historical (atmospheric) climate data to be used in ISIMIP2a simulations. All datasets provide the variables near-surface air temperature (tas), precipitation (pr), near-surface relative humidity (rhs), surface downwelling longwave radiation (rlds), surface downwelling shortwave radiation (rsds), surface pressure (ps), and near-surface wind speed (wind). In addition, some datasets also provide daily minimum and maximum near-surface air temperature (tasmin and tasmax, respectively).<br>Included are 6 datasets: GSWP3, PGMFD, WATCH, WATCH-WFDEI, GSWP3-EWEMBI, and GSWP3-W5E5. They all have global coverage at daily temporal and 0.5° spatial resolution. Temporal coverage differs between datasets.
description: All 6 datasets are observational in nature, i.e., based on reanalyses and other observational data sources. GSWP3 v0.5b covers 1901-2010, was generated in phase 3 of the Global Soil Wetness Project (GSWP3; Dirmeyer et al., 2006) and is a dynamically downscaled and bias-adjusted version of the 20th Century Reanalysis v2 (Compo et al., 2011; Kim, 2017).<br>The Princeton Global Meteorological Forcing Dataset (PGMFD) v2.1 covers 1901-2012 and is an interpolated and bias-adjusted version of the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP-NCAR) reanalysis (Kalnay et al. 1996; Kistler et al. 2001), with data for years prior to 1948 generated based on resampled NCEP-NCAR data (Sheffield et al., 2006).<br>The WATCH Forcing Dataset (also known als WFD) covers 1901-2001 and was generated in the WATer and Global Change (WATCH) project. It is an interpolated and bias-adjusted version of ERA-40, the 40-year reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF; Uppala et al., 2005), with data for years prior to 1958 generated based on resampled ERA-40 data (Weedon et al., 2011).<br>WATCH-WFDEI covers 1901-2016 and is a combination of WATCH for 1901-1978 with WFDEI for 1979-2016, where WFDEI is an interpolated and bias-adjusted version of the ERA-Interim reanalysis (Dee et al., 2011; Weedon et al., 2014). Since the two input datasets were not homogenized prior to their combination, the WATCH-WFDEI data are potentially discontinuous at the 1978/1979 transition, and results must be interpreted with caution (Müller Schmied et al., 2016).<br>GSWP3-EWEMBI covers 1901-2016 and is a combination of GSWP3 v0.5b for 1901-1978 with EWEMBI v1.1 for 1979-2016, where EWEMBI is another interpolated and bias-adjusted version of the ERA-Interim reanalysis (Lange, 2018; Lange, 2019a). In order to reduce discontinuities at the 1978/1979 transition, prior to their combination, GSWP3 data were homogenized with EWEMBI data using the bias-adjustment method ISIMIP3BASD v2.4.1 (Lange, 2019b; Lange, 2020).<br>GSWP3-W5E5 covers 1901-2016 and is a combination of GSWP3 v0.5b for 1901-1978 with W5E5 v1.0 for 1979-2016, where W5E5 is an interpolated and bias-adjusted version of the ERA5 reanalysis (Hersbach et al., 2020; Lange, 2019c; Cucchi et al., 2020). Also in this case, prior to their combination, GSWP3 data were homogenized with W5E5 data using ISIMIP3BASD v2.4.1.