In this study, a technique developed to retrieve integrated water vapor from interferometric synthetic aperture radar (InSAR) data is described, and a three-dimensional variational assimilation experiment of the retrieved precipitable water vapor into the mesoscale weather prediction model MM5 is carried out. The InSAR measurements were available in the framework of the European Space Agency (ESA) project for the "Mitigation of electromagnetic transmission errors induced by atmospheric water vapor effects" (METAWAVE), whose goal was to analyze and possibly predict the phase delay induced by atmospheric water vapor on the spaceborne radar signal. The impact of the assimilation on the model forecast is investigated in terms of temperature, water vapor, wind, and precipitation forecast. Changes in the modeled dynamics and an impact on the precipitation forecast are found. A positive effect on the forecast of the precipitation is found for structures at the model grid scale or larger (1 km), whereas a negative effect is found on convective cells at the subgrid scale that develops within 1 h time intervals. The computation of statistical indices shows that the InSAR assimilation improves the forecast of weak to moderate precipitation ( {< } {15};text{ mm}/{ 3};text{h} ).

InSAR Water Vapor Data Assimilation into Mesoscale Model MM5: Technique and Pilot Study

Cimini D;
2015

Abstract

In this study, a technique developed to retrieve integrated water vapor from interferometric synthetic aperture radar (InSAR) data is described, and a three-dimensional variational assimilation experiment of the retrieved precipitable water vapor into the mesoscale weather prediction model MM5 is carried out. The InSAR measurements were available in the framework of the European Space Agency (ESA) project for the "Mitigation of electromagnetic transmission errors induced by atmospheric water vapor effects" (METAWAVE), whose goal was to analyze and possibly predict the phase delay induced by atmospheric water vapor on the spaceborne radar signal. The impact of the assimilation on the model forecast is investigated in terms of temperature, water vapor, wind, and precipitation forecast. Changes in the modeled dynamics and an impact on the precipitation forecast are found. A positive effect on the forecast of the precipitation is found for structures at the model grid scale or larger (1 km), whereas a negative effect is found on convective cells at the subgrid scale that develops within 1 h time intervals. The computation of statistical indices shows that the InSAR assimilation improves the forecast of weak to moderate precipitation ( {< } {15};text{ mm}/{ 3};text{h} ).
2015
Istituto di Metodologie per l'Analisi Ambientale - IMAA
Forecasting
Moisture
Radar
Radar measurement
Space applications
Water vapor
Weather forecasting Atmospheric water vapor
Electromagnetic transmission
Integrated water vapors
Interferometric synthetic aperture radars
Precipitable water vapor
Precipitation forecast
Variational assimilation
Weather pred
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/298767
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