NOAA's National Water Model: Advancing operational hydrology through continental‐scale modeling

JAWRA Journal of the American Water Resources Association · 2024 · 129 citations

• Computer Science
• Environmental science
• Meteorology

Abstract The National Weather Service (NWS) Office of Water Prediction (OWP), in conjunction with the National Center for Atmospheric Research and the NWS National Centers for Environmental Prediction (NCEP) implemented version 2.1 of the National Water Model (NWM) into operations in April of 2021. As with the initial version implemented in 2016, NWM v2.1 is an hourly cycling analysis and forecast system that provides streamflow guidance for millions of river reaches and other hydrologic information on high‐resolution grids. The NWM provides complementary hydrologic guidance at current NWS river forecast locations and significantly expands guidance coverage and water budget information in underserved locations. It produces a full range of hydrologic fields, which can be leveraged by a broad cross section of stakeholders ranging from the emergency responder and water resource communities, to transportation, energy, recreation and agriculture interests, to other water‐oriented applications in the government, academic and private sectors. Version 2.1 of the NWM represents the fifth major version upgrade and more than doubles simulation skill with respect to hourly streamflow correlation, Nash Sutcliffe Efficiency, and bias reduction, over its original inception in 2016. This paper will discuss the driving factors underpinning the creation of the NWM, provide a brief overview of the model configuration and performance, and discuss future efforts to improve NWM components and services.

Pelagic Sargassum Prediction and Marine Connectivity in the Tropical Atlantic

Gulf and Caribbean Research · 2020 · 37 citations

• Oceanography
• Environmental science
• Climatology

Since 2011, pelagic Sargassum has experienced extraordinary blooms in the Tropical Atlantic where a system of persistent but seasonally variable currents has retained and consolidated it in large masses. Although beneficial at sea, principally as a unique pelagic habitat, when Sargassum inundates the nearshore environment it can have catastrophic effects on tourism, fisheries, health, and local ecosystems. Providing advanced warning of arrival dates of large masses of Sargassum is critical for enabling preparations and planning for its removal, use, and mitigation. Predictions of arrival time and location involve satellite identification of Sargassum at sea together with ocean current data for forward model tracking. However, forecast ocean current data are generally valid for only 5—7 days. In this study, ocean currents from 2 models (HYCOM and OSCAR) are validated against satellite tracked drifters from the Global Drifter Program with vector correlation and with skill in replicating a drifter pathway. Various wind additions to the models are also tested. Although both models capture the surface current systems in the Tropical Atlantic, they are mediocre in performance along both boundaries. In contrast, a drifter based current data model with 0.5% wind addition had high skill levels. This skill—tested drifter—based model was then used to determine marine connectivity across the Tropical Atlantic and suggests a much broader spread of Sargassum in the eastern Tropical Atlantic than is presently observed by satellites, conforming to earlier hypotheses. This model forms the basis for seasonal scale Sargassum forecasting.