Terrestrial Hydrology Research Group

Princeton University

Bias-Corrected and Downscaled Future Climate Global Meterological Forcing Data: 1948-2099

Overview

A global 150-yr (1948-2099) dataset of meteorological forcings for driving land surface models and other land modeling schemes. It is derived by bias correcting and downscaling WCRP CMIP3 climate model data for the 20th century and 21st century future climate projections. The dataset is bias-corrected and downscaled using the newly developed equidistant quantile matching method (Li et al., 2010) which better represents changes in the full distribution (not just the mean change). In addition to precipitation and temperature, radiation, humidity, pressure and windspeed are also downscaled. The downsclaing is based on the observational based global forcing dataset of Sheffield et al. (2006) also available from this website. The data are available at 1.0-degree spatial resolution and 3-hourly temporal resolution.

The data are currently available for one climate model (NCAR-PCM1) for the 20th century historical forcing (20C3M; 1948-2000) and one future climate scenario (SRES A2; 2001-2099). Data for other climate models and scenarios may be added in the future.

This work was supported by NSF Project 0629471 "Collaborative research: Understanding change in the climate and hydrology of the Arctic land region: Synthesizing the results of the ARCSS Fresh Water Initiative Projects"

Data Access

The dataset is freely available but we ask that you leave a few details about yourself and how you intend to use the dataset. Also, please cite the references below if you use the data. As of 28 April 2011, the data are available at 3-hourly at 1.0-degree resolution, globally. The dataset may be updated periodically through improvements to the methodology and from additional models/scenarios, and these updates are listed below.

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Updates

Apr 28 2011
Intitial version of the dataset for NCAR-PCM1 climate model and SRESA2 future climate scenario

Abstract

Li, H., J. Shefffield, and E. F. Wood, 2010: Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching, J. Geophys. Res., 115, D10101, DOI:10.1029/2009JD012882.

Sheffield, J., G. Goteti, and E. F. Wood, 2006: Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling, J. Climate, 19 (13), 3088-3111


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