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Three-Dimensional Variational Data Assimilation of Ground-Based GPS ZTD and Meteorological Observations during the 14 December 2001 Storm Event over the Western Mediterranean Sea

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  • 1 National Center for Atmospheric Research, Boulder, Colorado
  • | 2 Servei de Meteorologia de Catalunya, Barcelona, Spain
  • | 3 Institut d'Estudis Espacials de Catalunya, Barcelona, Spain
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Abstract

The impact of GPS zenith total delay (ZTD) measurements on mesoscale weather forecasts is studied. GPS observations from a permanent European network are assimilated into the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) using its three-dimensional variational data assimilation (3DVAR) system. The case study focuses on a snow storm that occurred during the period of 14–15 December 2001 over the western Mediterranean Sea.

The experiments show that the most significant improvement in forecast is obtained when GPS ZTD data are assimilated together with local surface meteorological observations into the model within a cycling assimilation framework. In this case, the root-mean-square (rms) differences between forecasted and observed values are reduced by 1.7% in the wind component, 4.1% in the temperature variable, and 17.8% in the specific humidity field. This suggests the deployment of GPS receivers at surface stations to better initialize numerical weather prediction models during strong storm mesoscale events.

Corresponding author address: Dr. L. Cucurull, Cosmic Project/JCSDA, NOAA/NWS/NCEP/EMC W/NP2, 5200 Auth Road, Room 207, Suitland, MD 20746. Email: Lidia.Cucurull@noaa.gov

Abstract

The impact of GPS zenith total delay (ZTD) measurements on mesoscale weather forecasts is studied. GPS observations from a permanent European network are assimilated into the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) using its three-dimensional variational data assimilation (3DVAR) system. The case study focuses on a snow storm that occurred during the period of 14–15 December 2001 over the western Mediterranean Sea.

The experiments show that the most significant improvement in forecast is obtained when GPS ZTD data are assimilated together with local surface meteorological observations into the model within a cycling assimilation framework. In this case, the root-mean-square (rms) differences between forecasted and observed values are reduced by 1.7% in the wind component, 4.1% in the temperature variable, and 17.8% in the specific humidity field. This suggests the deployment of GPS receivers at surface stations to better initialize numerical weather prediction models during strong storm mesoscale events.

Corresponding author address: Dr. L. Cucurull, Cosmic Project/JCSDA, NOAA/NWS/NCEP/EMC W/NP2, 5200 Auth Road, Room 207, Suitland, MD 20746. Email: Lidia.Cucurull@noaa.gov

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