Preprints
https://doi.org/10.5194/egusphere-2023-3014
https://doi.org/10.5194/egusphere-2023-3014
22 Jan 2024
 | 22 Jan 2024

Benchmarking of SWE products based on outcomes of the SnowPEx+ Intercomparison Project

Lawrence Mudryk, Colleen Mortimer, Chris Derksen, Aleksandra Elias Chereque, and Paul Kushner

Abstract. We assess and rank 23 gridded snow water equivalent (SWE) products by implementing a novel evaluation strategy using a new suite of reference data from two cross-validated sources and a series of product inter-comparisons. The new reference data combines in situ measurements from both snow courses and airborne gamma measurements. Compared to previous evaluations of gridded products, we have substantially increased the spatial coverage and sample size across North America, and we are able to evaluate product performance across both mountain and non-mountain regions. The evaluation strategy we use ranks overall relative product performance while still accounting for individual differences in ability to represent SWE climatology, variability, and trends. Assessing these gridded products fills an important gap in the literature since individual gridded products are frequently chosen without prior justification as the basis for evaluating land surface and climate model outputs, along with other climate applications. The top performing products across the range of tests performed are ERA5-Land followed by the Crocus snow model. Our evaluation indicates that accurate representation of hemispheric SWE varies tremendously across the range of products. While most products are able to represent SWE reasonably well across Northern Hemisphere non-mountainous regions, the ability to accurately represent SWE in mountain regions and to accurately represent historical trends are much more variable. Finally, we demonstrate that for the ensemble of products evaluated here, attempts to assimilate surface snow observations and/or satellite measurements lead to a deleterious influence on regional snow mass trends, which is an important consideration for how such gridded products are produced and applied in the future.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Lawrence Mudryk, Colleen Mortimer, Chris Derksen, Aleksandra Elias Chereque, and Paul Kushner

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-3014', Anonymous Referee #1, 17 Mar 2024
    • AC3: 'Reply on RC1', Lawrence Mudryk, 20 Jun 2024
  • RC2: 'Comment on egusphere-2023-3014', Anonymous Referee #2, 14 Apr 2024
    • AC1: 'Reply on RC2', Lawrence Mudryk, 20 Jun 2024
    • AC2: 'Reply on RC2', Lawrence Mudryk, 20 Jun 2024
Lawrence Mudryk, Colleen Mortimer, Chris Derksen, Aleksandra Elias Chereque, and Paul Kushner
Lawrence Mudryk, Colleen Mortimer, Chris Derksen, Aleksandra Elias Chereque, and Paul Kushner

Viewed

Total article views: 631 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
442 161 28 631 60 16 15
  • HTML: 442
  • PDF: 161
  • XML: 28
  • Total: 631
  • Supplement: 60
  • BibTeX: 16
  • EndNote: 15
Views and downloads (calculated since 22 Jan 2024)
Cumulative views and downloads (calculated since 22 Jan 2024)

Viewed (geographical distribution)

Total article views: 641 (including HTML, PDF, and XML) Thereof 641 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 05 Oct 2024
Download
Short summary
We evaluate and rank 23 products that estimate historical snow amounts. The evaluation uses new a set of ground measurements with improved spatial coverage enabling evaluation across both mountain and non-mountain regions. Performance measures vary tremendously across the products: while most perform reasonably in non-mountain regions, accurate representation of snow amounts in mountain regions and of historical trends is much more variable.