NOAA's National Water Model: Advancing operational hydrology through continental‐scale modeling
B. Cosgrove, David Gochis, T. Flowers, A. L. Dugger, Fred L. Ogden, Tom Graziano, Ed Clark, Ryan Cabell, Nick Casiday, Zhengtao Cui, Kelley Eicher, Greg Fall, Xia Feng, Katelyn FitzGerald, Nels Frazier, Camaron M. George, R.B. Gibbs, Liliana Hernandez Gonzalez, Donald R. Johnson, Ryan M. Jones, L. R. Karsten, Henok Kefelegn, David Kitzmiller, Haksu Lee, Yuqiong Liu, Hassan Mashriqui, David B. Mattern, Alyssa McCluskey, J. L. McCreight, Rachel McDaniel, Alemayehu Midekisa, Andy Newman, Linlin Pan, Cham Q. Pham, A. Rafieeinasab, Roy Rasmussen, Laura Read, Mehdi Rezaeianzadeh, F. Salas, Dina Sang, K. M. Sampson, Tim Schneider, Qi Shi, Gautam Sood, Andy Wood, Wanru Wu, David Yates, Wei Yu, Yongxin Zhang
Abstract
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.