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National Water Model

The NWM v2.1 output is prototype guidance and should not be considered an official NWS river forecast.

To view the Experimental Water Information Interface Product Description Document click here
For more information on the National Water Model click here.
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CONUS Analysis and Assimilation:
The Standard Analysis and Assimilation configuration cycles hourly and produces a real-time analysis of the current streamflow and other surface and near-surface hydrologic states across the contiguous United States (CONUS). This configuration is internally cycling, with each subsequent CONUS Analysis starting from the previous hour’s run. The exception is the 19Z CONUS Analysis cycle which ingests initial conditions from the Extended Analysis below. The CONUS Analysis also produces restart files each hour which are used to initialize the short, medium, and long range forecast simulations. Meteorological forcing data are drawn from the MRMS Gauge-adjusted and Radar-only observed precipitation products along with short range RAP and HRRR, while stream-gauge observations are assimilated from the USGS.

Hawaii Analysis and Assimilation:
The Hawaii Analysis and Assimilation configuration cycles hourly and produces a real-time analysis of the current streamflow and other surface and near-surface hydrologic states across the Hawaii domain. This configuration is internally cycling, with each subsequent Hawaii Analysis starting from the previous hour’s run. The Hawaii Analysis also produces restart files each hour which are used to initialize the Hawaii Short Range forecast simulation. Meteorological forcing data are drawn from the NAM-NEST NWP Model, while stream-gauge observations are assimilated from the USGS.

Puerto Rico / USVI Analysis and Assimilation:
The Puerto Rico Analysis and Assimilation configuration cycles hourly and produces a real-time analysis of the current streamflow and other surface and near-surface hydrologic states across the Puerto Rico domain. This configuration is internally cycling, with each subsequent Puerto Rico Analysis starting from the previous hour’s run. The Puerto Analysis also produces restart files each hour which are used to initialize the Puerto Short Range forecast simulation. Meteorological forcing data are drawn from the NAM-NEST and HIRES WRF-ARW NWP Models, while stream-gauge observations are assimilated from the USGS.

CONUS Short Range Forecast:
Forced with meteorological data from the HRRR and RAP models, the Short Range Forecast configuration cycles hourly and produces hourly deterministic forecasts of streamflow and hydrologic states out to 18 hours. The model is initialized with a restart file from the Analysis and Assimilation configuration and does not cycle on its own states.

Hawaii Short Range Forecast:
Forced with meteorological data from the NAM-NEST model, the Hawaii Short Range Forecast configuration cycles four times per day and produces hourly deterministic forecasts of streamflow and hydrologic states out to 60 hours. The model is initialized with a restart file from the Hawaii Analysis and Assimilation configuration and does not cycle on its own states.

Puerto Rico /USVI Short Range Forecast:
Forced with meteorological data from the NAM-NEST and HIRES WRF-ARW models, the Puerto Rico Short Range Forecast configuration cycles two times per day and produces hourly deterministic forecasts of streamflow and hydrologic states out to 48 hours. The model is initialized with a restart file from the Puerto Rico Analysis and Assimilation configuration and does not cycle on its own states.

Medium Range Forecast:
The National Water Model (NWM) features a Medium Range ensemble forecast configuration. Cycling four times per day at 00Z, 06Z, 12Z and 18Z, this ensemble consists of seven members. Each of these Medium Range (MR) ensemble members starts from the same set of initial land surface conditions, but uses forcings (precipitation and temperature) from the current and six previous runs of the Global Forecast System (GFS). Using the current NWM issuance time as the starting point for all 7 inputs creates a time-lagged ensemble (Figure 1). An ensemble forecast mean is also calculated and provided. This MR ensemble approach seeks to represent the impact of meteorological forcing-based uncertainty on NWM hydrologic forecasts, and does not take into account uncertainty of land surface states or parameters. Each ensemble member represents one possible outcome and, collectively, the ensemble members aim to portray a range of possible outcomes.

medium-range-ensemble-ten-day-jpg

Figure 1. The forcing data used as input in the development of the 7-member NWM Medium Range Ensemble. The Member 1 forecast uses the most recent GFS model run and is 10 days in length, while Members 2 through 7 use successively older GFS cycles and extend to 8.5 days in length. The MR Ensemble forecast mean is 8.5 days in length, using the first 8.5 days from Member 1 and the full-length forecasts from Members 2 through 7.

Long Range Forecast:
The National Water Model (NWM) features a Long-Range ensemble forecast configuration. The Long-Range (LR) forecast cycles four times per day at 00Z, 06Z, 12Z, and 18Z, and there are 4 ensemble members in each cycle, each forced with a different Climate Forecast System (CFS) forecast member. Each ensemble member uses the CFS forcing with the same member identifier, e.g. LR ensemble member 1 uses CFS ensemble member 1. The LR forecast produces 6-hourly streamflow and daily land surface output, and, as with the other forecast configurations, is initialized with a common restart file from the Analysis and Assimilation configuration. The display options available are the 4 ensemble members and an ensemble forecast mean from the latest LR forecast cycle.

This LR ensemble approach seeks to represent the impact of meteorological forcing-based uncertainty on NWM hydrologic forecasts, and does not take into account uncertainty of land surface states or parameters. Each ensemble member represents one possible outcome and, collectively, all of the ensemble members aim to portray a range of possible outcomes.

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