The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners.
As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.
i
The Role of Forcing and Parameterization in Improving Snow Simulation in the Upper Colorado River Basin Using the National Water Model
-
2024
-
-
Source: Water Resources Research, 60(8)
Details:
-
Journal Title:Water Resources Research
-
Personal Author:
-
NOAA Program & Office:
-
Description:This study assesses snow water equivalent (SWE) simulation uncertainty in the National Water Model (NWM) due to forcing and model parameterization, using data from 46 Snow Telemetry (SNOTEL) sites in the Upper Colorado River Basin (UCRB). We evaluated the newly developed Analysis of Record for Calibration (AORC) forcing data for SWE simulation and examined the impact of bias correction applied to AORC precipitation and temperature. Additionally, we investigated the sensitivity of SWE simulations to choices of physical parameterization schemes through 72 ensemble experiments. Results showed that NWM driven by AORC forcings captured the overall temporal variation of SWE but underestimated its amount. Adjusting AORC precipitation with SNOTEL observations reduced SWE root‐mean‐square error (RMSE) by 66%, adjusting temperature trimmed it by 10%, and adjusting both decreased it by 69%. Among the physical processes, the snow/soil temperature time scheme (STC) demonstrated the highest sensitivity, followed by the surface exchange coefficient for heat (SFC), snow surface albedo (ALB), and rainfall and snowfall partitioning (SNF), while the lower boundary of soil temperature (TBOT) proved to be insensitive. Further optimization of the parameterization combination resulted in a 12% SWE RMSE reduction. When combined with the bias‐corrected AORC precipitation and temperature, this optimization led to a remarkable 78% SWE RMSE reduction. Despite these enhancements, a persistent slow and late spring ablation suggests model deficiencies in snow ablation physics. The study emphasizes the critical need to enhance the accuracy of forcing data in mountainous regions and address model parameterization uncertainty through optimization efforts.
-
Source:Water Resources Research, 60(8)
-
DOI:
-
ISSN:0043-1397;1944-7973;
-
Format:
-
Publisher:
-
Document Type:
-
Funding:
-
License:
-
Rights Information:CC BY
-
Compliance:Submitted
-
Main Document Checksum:
-
Download URL:
-
File Type: