Evaluation of Retrospective National Water Model Soil Moisture and Streamflow for Drought‐Monitoring Applications

Hughes, M.; Jackson, D. L.; Unruh, D.; Wang, H.; Hobbins, M.; Ogden, F. L.; Cifelli, R.; Cosgrove, B.; DeWitt, D.; Dugger, A.; Ford, T. W.; Fuchs, B.; Glaudemans, M.; Gochis, D.; Quiring, S. M.; RafieeiNasab, A.; Webb, R. S.; Xia, Y.; Xu, L.

doi:10.1029/2023jd038522

i

Evaluation of Retrospective National Water Model Soil Moisture and Streamflow for Drought‐Monitoring Applications

2024
By Hughes, M. ; Jackson, D. L. ; Unruh, D. ; ...

Details

Journal Title:

Journal of Geophysical Research: Atmospheres
Personal Author:

Hughes, M. ; Jackson, D. L. ; Unruh, D. ; Wang, H. ; Hobbins, M. ; Ogden, F. L. ; Cifelli, R. ; Cosgrove, B. ; DeWitt, D. ; Dugger, A. ; Ford, T. W. ; Fuchs, B. ; Glaudemans, M. ; Gochis, D. ; Quiring, S. M. ; RafieeiNasab, A. ; Webb, R. S. ; Xia, Y. ; Xu, L.
NOAA Program & Office:

NWS (National Weather Service) ; OAR (Oceanic and Atmospheric Research) ; CIRES (Cooperative Institute for Research in Environmental Sciences) ; CPC (Climate Prediction Center) ; EMC (Environmental Modelling Center) ; NCEP (National Centers for Environmental Prediction) ; OWP (Office of Water Prediction) ; PSL (Physical Sciences Laboratory)
Description:

The National Oceanic and Atmospheric Administration (NOAA)’s National Water Model (NWM) provides analyses and predictions of hydrologic variables relevant to drought monitoring and forecasts at fine time and space scales (hourly, 0.25–1 km). We present results exploring the potential for NWM soil moisture and streamflow analyses to inform operational drought monitoring. Both agricultural and hydrologic drought monitoring rely either explicitly or implicitly on an accurate representation of anomalous soil moisture values. Much of our analysis focuses on comparisons of soil moisture anomalies in the NWM to those from in‐situ observations. To establish benchmarks for NWM soil moisture skill, we also include other gridded data sets currently used to inform the US Drought Monitor, specifically those from the North American Land Data Assimilation System phase 2 (NLDAS‐2) land surface models. We then compare NWM streamflow low flows with ∼500 stream gauges from the United States Geological Survey (USGS) Hydro‐Climatic Data Network of undisturbed basins. The NWM soil moisture simulation’s skill parallels that from NLDAS‐2. The accuracy of drought condition identification from NWM streamflow exceeds that based on soil moisture as determined by Critical Success Index scores for extreme dry percentiles. Different meteorological forcings are used in the operational NWM cycles than those used in this retrospective analysis. This forcing disconnect, together with concerns about current‐generation land surface model soil moisture‐transport schemes, inhibit its current operational use for drought monitoring.
Source:

Journal of Geophysical Research: Atmospheres, 129(6)
DOI:

https://doi.org/10.1029/2023jd038522
ISSN:

2169-897X ; 2169-8996
Format:

pdf
Publisher:

American Geophysical Union (AGU)
Document Type:

Journal Article
Funding:

Grant no. NA17OAR4320101
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
Main Document Checksum:

urn:sha-512:60111cf012a2ead99495d853b1fdd8f4ccce67914a9d60bfed1c08eec04468fce2a90c34107b9b5304282a755d50d74d1be9a0d24725169542669afaa80e94c6
Download URL:

https://repository.library.noaa.gov/view/noaa/67766/noaa_67766_DS1.pdf
File Type:

[PDF - 3.29 MB ]

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