28 Apr 2023
 | 28 Apr 2023
Status: this preprint is open for discussion.

Spatiotemporal snow water storage uncertainty in the midlatitude American Cordillera

Yiwen Fang, Yufei Liu, Dongyue Li, Haorui Sun, and Steven A. Margulis

Abstract. This work quantifies the uncertainty of accumulation-season peak snow water storage in the portions of the midlatitude American Cordillera where snow is a dominant driver of hydrology. This is accomplished through intercomparison of commonly used global and regional products over the Western U.S. (WUS) and Andes domains, which have similar hydrometeorology but are disparate with respect to the amount of available in situ information. The recently developed WUS Snow Reanalysis (WUS-SR) and Andes Snow Reanalysis (Andes-SR) datasets, which have been extensively verified against in situ measurements, are used as baseline reference datasets in the intercomparison. Relative to WUS-SR climatological peak SWE storage (269 km3), high- and moderate-resolution products (i.e. those with resolutions less than ~10 km) are in much better agreement (284 ± 14 km3; overestimated by 6 %) compared to low-resolution products (127 km3 ± 54 km3; underestimated by 53 %). In comparison to the Andes-SR peak snow storage (29 km3), all other products show large uncertainty and bias (19 km3 ± 16 km3; underestimated by 34 %). Examination of spatial patterns related to orographic effects, showed that only the high- to moderate-resolution SNODAS and UA products show comparable estimates of windward-leeward SWE patterns over a subdomain (Sierra Nevada) of the WUS. Coarser products distribute too much snow on the leeward side in both the Sierra Nevada and Andes, missing orographic-rainshadow patterns that have important hydrological implications. The uncertainty of peak seasonal snow storage is primarily explained by precipitation uncertainty in both the WUS (R2 = 0.55) and Andes (R2 = 0.84). Despite using similar forcing inputs, snow storage diverges significantly within the ERA5 (i.e. ERA5 vs. ERA5-Land) products and the GLDAS (modeled with Noah, VIC, and Catchment model) products due to resolution-induced elevation differences and/or differing model process representation related to rain–snow partitioning and accumulation-season snowmelt generation. The availability and use of in situ precipitation and snow measurements (i.e., in WUS) in some products adds value by reducing snow storage uncertainty, however where such data are limited, i.e. in the Andes, significant biases and uncertainty exist.

Yiwen Fang et al.

Status: open (until 23 Jun 2023)

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Yiwen Fang et al.


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Short summary
Using newly developed snow reanalysis datasets as references, snow water storage is at high uncertainty among commonly used global products in the Andes, and low-resolution products in the western U.S, where snow is the key element of water resources. In addition to precipitation, elevation differences, and model mechanism variances drive snow uncertainty. This work provides insights for research applying these products and generating future products in areas with limited in situ data.