An assessment of the Strengths and Limitations of the National Water Model Snow Representation against In-Situ Measurements, Remote Sensing Products, and Assimilated Data
Abstract
Considerable research is currently directed towards hydrological processes that provide insights into predicting hydrologic responses at the continental scale. Confronted with the desire and need to enhance water resources forecasts and mapping, National Oceanic and Atmospheric Administration (NOAA) implemented the National Water Model (NWM), which provides hourly forecasts of streamflow and spatial estimates of hydrologic states over the U.S. This project uses the NWM reanalysis products to investigate the NWM snow representation, as snow is a key component of the hydrological cycle in mountainous regions. In this study, we evaluated the performance of the NWM reanalysis products in terms of their accuracy in Snow Water Equivalent (SWE) and Snow-Covered Area (SCA) estimation. We evaluated these variables across snow process stages. In our analysis, we used a combination of observations from in-situ measurements, assimilated products, and satellite imagery to evaluate how well the NWM snow parameterization represents effects of factors significantly affecting SWE, such as snow-covered area, elevation, slope and aspect, forest cover, and topographic shading in target regions within the Western U.S. Results indicate that there were differences between the NWM SWE/SCA estimates and SWE/SCA recorded at in-situ measurements or captured by satellites. We used evaluation of these differences to address challenges of the current snow parameterization within the NWM, and identify characteristics relevant to model inputs and causes of discrepancies. Our results reveal that differences between modeled and observed snow were attributed to both shortcomings in the current representation of snowmelt processes within the Noah-MP as implemented in the NWM, as well as precipitation errors. Examining the causes of these differences highlights characteristics on which to focus future model developments to overcome some of the limitations in the snow parameterization.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMH121...03G
- Keywords:
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- 1805 Computational hydrology;
- HYDROLOGY;
- 1816 Estimation and forecasting;
- HYDROLOGY;
- 1839 Hydrologic scaling;
- HYDROLOGY;
- 1847 Modeling;
- HYDROLOGY