Articles | Volume 14, issue 11
https://doi.org/10.5194/essd-14-4949-2022
https://doi.org/10.5194/essd-14-4949-2022
Data description paper
 | 
11 Nov 2022
Data description paper |  | 11 Nov 2022

Downscaled hyper-resolution (400 m) gridded datasets of daily precipitation and temperature (2008–2019) for the East–Taylor subbasin (western United States)

Utkarsh Mital, Dipankar Dwivedi, James B. Brown, and Carl I. Steefel

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Latest update: 04 Mar 2024
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Short summary
We present a new dataset that estimates small-scale variations in precipitation and temperature in mountainous terrain. The dataset is generated using a new machine learning framework that extracts relationships between climate and topography from existing coarse-scale datasets. The generated dataset is shown to capture small-scale variations more reliably than existing datasets and constitutes a valuable resource to model the water cycle in the mountains of Colorado, western United States.
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