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

Viewed

Total article views: 2,416 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,754 581 81 2,416 139 57 61
  • HTML: 1,754
  • PDF: 581
  • XML: 81
  • Total: 2,416
  • Supplement: 139
  • BibTeX: 57
  • EndNote: 61
Views and downloads (calculated since 28 Mar 2022)
Cumulative views and downloads (calculated since 28 Mar 2022)

Viewed (geographical distribution)

Total article views: 2,416 (including HTML, PDF, and XML) Thereof 2,320 with geography defined and 96 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 11 Oct 2024
Download
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.
Altmetrics
Final-revised paper
Preprint