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Downscaled WorldClim2 projections for the Hawaiian Islands under four representative concentration pathways (RCPs; 2.6, 4.5, 6.0, and 8.5) for mid- (2040-2059), and late-century (2060-2079) scenarios

Metadata Updated: July 6, 2024

Global downscaled projections are now some of the most widely used climate datasets in the world, however, they are rarely examined for representativeness of local climate or the plausibility of their projected changes. Here we show steps to improve the utility of two such global datasets (CHELSA and WorldClim2) to provide credible climate scenarios for regional climate change impact studies. Our approach is based on three steps: 1) Using a standardized baseline period, comparing available global downscaled projections with regional observation-based datasets and regional downscaled datasets (if available); 2) bias correcting projections using observation-based data; and 3) creating ensembles to make use of the differential strengths of global downscaling datasets. We also explored the patterns and magnitude of change for these regional projected climate shifts to determine their plausibility as future climate scenarios using Hawaiʻi as an example region. While our ensemble projections were shown to largely reduce the deviations between model and observation-based current climate, we show projected climate shifts from these commonly used global datasets can fall well outside the range of future scenarios derived from fine-tuned regional downscaling efforts, and hence should be carefully evaluated. This data release includes a baseline (1983-2012) model as well future climate projections for mid- (2040-2059) and late-century (2060-2079) for three regionally-adapted global datasets (CHELSA, WorldClim2, and an ensemble). We considered mean annual temperature (MAT) and mean annual precipitation (MAP) as our primary variables for comparison since they are the most widely used and desired datasets for climate impact studies. These regionally-downscaled future climate projections are available for various individual Global Circulation Models (GCMs) under four representative concentration pathways (RCPs; 2.6, 4.5, 6.0, and 8.5) for each global dataset.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Identifier USGS:62ce68dfd34e82ff904ac9a4
Data Last Modified 20220810
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Harvest Object Id ee720deb-2230-47ef-903a-92ecd1379780
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -160.518,18.5948,-154.497,22.5008
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash bb33a300a4d7ad98a7cb4ab8920343e3c473708350401a5fc01e6d63550666c8
Source Schema Version 1.1
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