Large Ensemble of Global Hydroclimatic Stress and Extreme Indices

d092493
 
Abstract:

This dataset provides a global collection of hydroclimatic stress and climate extreme indices derived from large ensemble simulations of two Earth system models: the Community Earth System Model Large Ensemble version 2 (LENS2) and the Energy Exascale Earth System Model version 2 (E3SMv2). The dataset includes daily vapor pressure deficit (VPD) and Keetch-Byram Drought Index (KBDI), as well as the Standardized Precipitation Evapotranspiration Index (SPEI) at 1-, 3-, and 12-month accumulation timescales. Together, these indices characterize atmospheric moisture demand, drought variability, and hydroclimatic stress relevant to ecosystem impacts, wildfire risk, and climate extremes. The indices are derived from the 100-member LENS2 ensemble and the 21-member E3SMv2 ensemble, spanning 1850-2100 and covering both the historical period (1850-2014) and the SSP3-7.0 scenario (2015-2100). Both ensembles provide global coverage at approximately 1 x 1.25 horizontal resolution in the atmosphere and land components, enabling consistent analysis of hydroclimatic extremes and internal climate variability across past and projected climates. In addition to these process-based stress metrics, the dataset also includes a suite of standard Expert Team on Climate Change Detection and Indices (ETCCDI) threshold- and duration-based extreme indices derived from temperature and precipitation.

Variables:
Atmospheric Precipitation Indices Compound Extreme Events Drought Indices Extreme Weather
Temperature Indices Water Vapor Indicators Water Vapor Indices
Data Types:
Model Simulation
Data Contributors:
UCAR/NCAR
National Center for Atmospheric Research, University Corporation for Atmospheric Research
Total Volume:
0.0 MB
Data Formats:
netCDF, Zarr
Metadata Record:
Data License:
Citation counts are compiled through information provided by publicly-accessible APIs according to the guidelines developed through the https://makedatacount.org/ project. If journals do not provide citation information to these publicly-accessible services, then this citation information will not be included in GDEX citation counts. Additionally citations that include dataset DOIs are the only types included in these counts, so legacy citations without DOIs, references found in publication acknowledgements, or references to a related publication that describes a dataset will not be included in these counts.