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How Well Do Operational Numerical Weather Prediction Configurations Represent Hydrology?
European Ctr Medium Range Weather Forecasts, Reading, Berks, England;Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England;Univ Reading, Dept Meteorol, Reading, Berks, England;Ctr Nat Hazards & Disaster Sci, Uppsala, Sweden.ORCID iD: 0000-0002-1472-868x
Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England.
European Ctr Medium Range Weather Forecasts, Reading, Berks, England.
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2019 (English)In: Journal of Hydrometeorology, ISSN 1525-755X, E-ISSN 1525-7541, Vol. 20, no 8, p. 1533-1552Article in journal (Refereed) Published
Abstract [en]

Land surface models (LSMs) have traditionally been designed to focus on providing lower-boundary conditions to the atmosphere with less focus on hydrological processes. State-of-the-art application of LSMs includes a land data assimilation system (LDAS), which incorporates available land surface observations to provide an improved realism of surface conditions. While improved representations of the surface variables (such as soil moisture and snow depth) make LDAS an essential component of any numerical weather prediction (NWP) system, the related increments remove or add water, potentially having a negative impact on the simulated hydrological cycle by opening the water budget. This paper focuses on evaluating how well global NWP configurations are able to support hydrological applications, in addition to the traditional weather forecasting. River discharge simulations from two climatological reanalyses are compared: one "online" set, which includes land-atmosphere coupling and LDAS with an open water budget, and an "offline" set with a closed water budget and no LDAS. It was found that while the online version of the model largely improves temperature and snow depth conditions, it causes poorer representation of peak river flow, particularly in snowmelt-dominated areas in the high latitudes. Without addressing such issues there will never be confidence in using LSMs for hydrological forecasting applications across the globe. This type of analysis should be used to diagnose where improvements need to be made; considering the whole Earth system in the data assimilation and coupling developments is critical for moving toward the goal of holistic Earth system approaches.

Place, publisher, year, edition, pages
AMER METEOROLOGICAL SOC , 2019. Vol. 20, no 8, p. 1533-1552
Keywords [en]
Water budget, balance, Numerical weather prediction, forecasting, Data assimilation, Land surface model
National Category
Meteorology and Atmospheric Sciences Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:uu:diva-391286DOI: 10.1175/JHM-D-18-0086.1ISI: 000477628000001OAI: oai:DiVA.org:uu-391286DiVA, id: diva2:1344917
Available from: 2019-08-22 Created: 2019-08-22 Last updated: 2019-08-22Bibliographically approved

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