An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)

S. Rahimi; L. Huang; J. Norris; A. Hall; N. Goldenson; W. Krantz; B. Bass; C. Thackeray; H. Lin; D. Chen; E. Dennis; E. Collins; Z. J. Lebo; E. Slinskey; S. Graves; S. Biyani; B. Wang; S. Cropper

doi:10.5194/gmd-17-2265-2024

Geoscientific Model Development (Mar 2024)

An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)

S. Rahimi,
L. Huang,
J. Norris,
A. Hall,
N. Goldenson,
W. Krantz,
B. Bass,
C. Thackeray,
H. Lin,
D. Chen,
E. Dennis,
E. Collins,
Z. J. Lebo,
E. Slinskey,
S. Graves,
S. Biyani,
B. Wang,
S. Cropper

Affiliations

S. Rahimi: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
L. Huang: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
J. Norris: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
A. Hall: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
N. Goldenson: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
W. Krantz: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
B. Bass: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
C. Thackeray: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
H. Lin: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
D. Chen: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
E. Dennis: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
E. Collins: Department of Atmospheric Science, University of Wyoming, Laramie, WY 82071, USA
Z. J. Lebo: School of Meteorology, University of Oklahoma, Norman, OK 73019, USA
E. Slinskey: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
S. Graves: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
S. Biyani: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
B. Wang: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA
S. Cropper: Center for Climate Science, University of California, Los Angeles, Los Angeles, CA 90095, USA

DOI: https://doi.org/10.5194/gmd-17-2265-2024
Journal volume & issue: Vol. 17
pp. 2265 – 2286

Abstract

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Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Published in Geoscientific Model Development

ISSN: 1991-959X (Print); 1991-9603 (Online)
Publisher: Copernicus Publications
Country of publisher: Germany
LCC subjects: Science: Geology
Website: https://www.geoscientific-model-development.net/

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