The model initialization with high-resolution SAR wind data provided by the Sentinel-1 mission and its impact on the meteorological model WRF-ARW simulations is discussed. The activity is performed within the Horizon 2020 CEASELESS project, focusing on one of the target areas, the northern Adriatic Sea (northern-central Mediterranean). The Sentinel-1 SAR wind is ingested into LAPS, a numerical system developed at NOAA, specifically designed for data analysis and nowcasting issues, since it has the advantage of being faster and less computational demanding than advanced data assimilation methods. Here, LAPS analyses are used to perform a smarter initialization of the WRF-ARW model simulations than using simply global model fields. The impact of the Sentinel-1 SAR wind on the model simulations is evaluated for twenty cases, ranging through several atmospheric conditions occurring in different seasons of the years 2014–2018. For each case study, a reference WRF-ARW simulation is forced with GFS analysis and forecasts used as initial and boundary conditions, respectively. Additional model runs are initialized with the LAPS analyses, which include the information of Sentinel-1 SAR wind, METAR data and the SEVIRI/MSG (Eumetsat) brightness temperature. A statistical evaluation of the WRF-ARW simulations is performed versus an independent set of surface records, provided by the Friuli Venezia Giulia regional station network (northeastern Italy), and METAR data. The comparison is performed for 10 m wind, 2 m air and dew point temperature. The results show a positive, albeit modest, impact on the WRF model simulations initialized with the LAPS analyses. The initialization with the Sentinel-1 SAR wind show benefits for all surface variables. Finally, a Mediterranean tropical-like cyclone (Medicane), occurred in the Ionian Sea in November 2017, is considered in order to show how the use of Sentinel wind data can contribute to a better analysis and simulation of severe weather episodes in the Mediterranean. The improvement in the simulation of the pressure minimum location is remarkable.

Initialization of WRF Model Simulations With Sentinel-1 Wind Speed for Severe Weather Events

Antonio Ricchi;
2021

Abstract

The model initialization with high-resolution SAR wind data provided by the Sentinel-1 mission and its impact on the meteorological model WRF-ARW simulations is discussed. The activity is performed within the Horizon 2020 CEASELESS project, focusing on one of the target areas, the northern Adriatic Sea (northern-central Mediterranean). The Sentinel-1 SAR wind is ingested into LAPS, a numerical system developed at NOAA, specifically designed for data analysis and nowcasting issues, since it has the advantage of being faster and less computational demanding than advanced data assimilation methods. Here, LAPS analyses are used to perform a smarter initialization of the WRF-ARW model simulations than using simply global model fields. The impact of the Sentinel-1 SAR wind on the model simulations is evaluated for twenty cases, ranging through several atmospheric conditions occurring in different seasons of the years 2014–2018. For each case study, a reference WRF-ARW simulation is forced with GFS analysis and forecasts used as initial and boundary conditions, respectively. Additional model runs are initialized with the LAPS analyses, which include the information of Sentinel-1 SAR wind, METAR data and the SEVIRI/MSG (Eumetsat) brightness temperature. A statistical evaluation of the WRF-ARW simulations is performed versus an independent set of surface records, provided by the Friuli Venezia Giulia regional station network (northeastern Italy), and METAR data. The comparison is performed for 10 m wind, 2 m air and dew point temperature. The results show a positive, albeit modest, impact on the WRF model simulations initialized with the LAPS analyses. The initialization with the Sentinel-1 SAR wind show benefits for all surface variables. Finally, a Mediterranean tropical-like cyclone (Medicane), occurred in the Ionian Sea in November 2017, is considered in order to show how the use of Sentinel wind data can contribute to a better analysis and simulation of severe weather episodes in the Mediterranean. The improvement in the simulation of the pressure minimum location is remarkable.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11697/159153
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