Submitted as: model experiment description paper
19 Oct 2023
Submitted as: model experiment description paper |  | 19 Oct 2023
Status: this preprint is currently under review for the journal GMD.

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

Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary Lebo, Emily Slinskey, and the UCLA Center for Climate Science Team

Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (U.S.), remains challenging due to the low resolution of global climate models (GCMs). Yet 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 predictions. Here, we present an ensemble of dynamically downscaled simulations over the western U.S. from 1980–2100 at 9-km grid spacing, driven by sixteen latest-generation GCMs. This dataset is titled the Western U.S. 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 intensified local atmospheric updrafts tied to 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 U.S. climate.

Stefan Rahimi et al.

Status: open (until 16 Dec 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2023-162', Anonymous Referee #1, 18 Nov 2023 reply
  • RC2: 'Comment on gmd-2023-162', Anonymous Referee #2, 19 Nov 2023 reply
  • CEC1: 'Comment on gmd-2023-162', Juan Antonio Añel, 19 Nov 2023 reply
    • AC1: 'Reply on CEC1', Stefan Rahimi-Esfarjani, 20 Nov 2023 reply
      • CEC2: 'Reply on AC1', Juan Antonio Añel, 21 Nov 2023 reply

Stefan Rahimi et al.

Stefan Rahimi et al.


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Short summary
Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically-based ensemble of climate data for use at local scales. Strengths and weakness of the data are frankly discussed as we overview the downscaled dataset.