Evaluating the benefit and cost of assimilating satellite sea surface temperature into the NOAA Chesapeake Bay Operational Forecast System using 4DVAR and LETKF

Hoffman, Matthew, J. (Matthew Joseph), 1982-; Zhang, Bin; Lanerolle, Lyon W. J. (Lyon Werner John); Brown, Christopher, W.

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Evaluating the benefit and cost of assimilating satellite sea surface temperature into the NOAA Chesapeake Bay Operational Forecast System using 4DVAR and LETKF

2020
By Hoffman, Matthew, J. (Matthew Joseph), 1982- ; Zhang, Bin ; Lanerolle, Lyon W. J. (Lyon Werner John) ; ...
Series: NOAA technical report NOS CS ; 39

[PDF-1.57 MB]

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Personal Author:

Hoffman, Matthew, J. (Matthew Joseph), 1982- ; Zhang, Bin ; Lanerolle, Lyon W. J. (Lyon Werner John) ; Brown, Christopher, W.

Hoffman, Matthew, J. (Matthew Joseph), 1982- ; Zhang, Bin ; Lanerolle, Lyon W. J. (Lyon Werner John) ; Brown, Christopher, W. Less -
Corporate Authors:

United States. Office of Coast Survey
NOAA Program & Office:

NOS (National Ocean Service) ; OCS (Office of Coast Survey)

NOS (National Ocean Service) ; OCS (Office of Coast Survey) Less -
Description:

The National Oceanic and Atmospheric Administration (NOAA) presently does not assimilate observations into the coastal ocean Operational Forecast System (OFS). We conducted a preliminary assessment of the skill and computational cost/effort of two popular data assimilation techniques – Four-Dimensional Variational (4DVAR) and the Local Ensemble Transform Kalman Filter (LETKF) – in assimilating satellite-derived, sea-surface temperature (SST) into the NOAA’s Chesapeake Bay Operational Forecast System (CBOFS) with the intention of improving nowcasts and forecasts. Sea-surface temperatures from NOAA’s Visible Infrared Imager Radiometer Suite (VIIRS) onboard the Suomi National Polar Orbiting Partnership (SNPP) are used to correct the temperature field in CBOFS and the results are compared to independent temperature observations from buoys and vertical CTD profiles. Both 4DVAR and LETKF provide improvement in temperature nowcasts and forecasts over the free running model, reducing their errors by 1°C or more, with improvements not only in the surface but throughout the water column. The results of this study demonstrate that data assimilation of satellite retrievals of SST can increase skill in model predictions in estuarine waters and provide information that will aid NOAA in deciding which technique, if any, to implement in order to assimilate SST into their operational hydrodynamic model of the Chesapeake Bay.
Keywords:

[+]

Data Processing Estuarine Hydrodynamics Evaluation Mathematical Models Micrometeorology Nowcasting (Meteorology) Satellite Meteorology Temperature Measurements Weather Forecasting
Series:

NOAA technical report NOS CS ; 39
Document Type:

Technical Report
Place as Subject:

Chesapeake Bay (Md. and Va.) ; United States

Chesapeake Bay (Md. and Va.) ; United States Less -
Rights Information:

Public Domain
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Submitted
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urn:sha256:cc07c5a24e8cdcc22ac137980b5f395cca31c25f388852438c4bce2c440b311a
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https://repository.library.noaa.gov/view/noaa/23106/noaa_23106_DS1.pdf
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Evaluating the benefit and cost of assimilating satellite sea surface temperature into the NOAA Chesapeake Bay Operational Forecast System using 4DVAR and LETKF

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