Preprints
https://doi.org/10.5194/egusphere-2024-201
https://doi.org/10.5194/egusphere-2024-201
05 Feb 2024
 | 05 Feb 2024
Status: this preprint is open for discussion.

A simple snow temperature index model exposes discrepancies between reanalysis snow water equivalent products

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

Abstract. Current global reanalyses show marked discrepancies in snow mass and snow cover extent for the Northern Hemisphere. Here, benchmark snow datasets are produced by driving a simple offline snow model, the Brown Temperature Index Model (B-TIM), with temperature and precipitation from each of three reanalyses. B-TIM offline snow performs comparably to or better than online (coupled land-atmosphere) reanalysis snow when evaluated against in situ snow measurements. Sources of discrepancy in snow climatologies, which are difficult to isolate when comparing online reanalysis snow products amongst themselves, are partially elucidated by separately bias-adjusting temperature and precipitation in B-TIM. Interannual variability in snow mass and snow spatial patterns is far more self-consistent amongst offline B-TIM snow products than amongst online reanalysis snow products, and specific artifacts related to temporal inhomogeneity in snow data assimilation are revealed in the analysis. B-TIM, released here as an open-source, self-contained Python package, provides a simple benchmarking tool for future updates to more sophisticated online and offline snow datasets.

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

Status: open (until 25 Mar 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Aleksandra Elias Chereque, Paul J. Kushner, Lawrence Mudryk, Chris Derksen, and Colleen Mortimer

Data sets

Replication Data for: "A simple snow temperature index model exposes discrepancies between reanalysis snow water equivalent products" Aleksandra Elias Chereque https://doi.org/10.5683/SP3/IV6SVJ

Model code and software

Brown Temperature Index Model Aleksandra Elias Chereque https://doi.org/10.5281/zenodo.10044951

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

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Short summary
We look at three commonly used snow depth datasets that come from a complex combination of snow modeling and historical measurements. When compared with each other, these datasets have differences that arise for various reasons. We show that a simple snow model can be used to examine consistency and highlight issues with the complex datasets. This method indicates that one of the complex datasets should be excluded from further studies.