Date:
Thu, 26/11/202012:00-13:00
תאריך:
ה', 26/11/2020 - 12:00 עד 13:00
ראה גם: סמינר החוג לאא'א
מיקום:
zoom
Precipitable water vapor variability derived from GPS tropospheric pathdelays over the Eastern Mediterranean areaShlomi ZiskinAriel UniversityGlobal Navigation Station System (GNSS) meteorology is a remote sensing techniquethat utilizes signals that are transmitted from GPS satellites to ground based receiversin order to estimate the integrated water vapor or Precipitable Water Vapor (PWV)above the GPS ground station. I will briefly outline the methodology behind thistechnique, its strengths and limitations. Using this technique, I was able to assemblePWV long time series (5 to 20 years) ,with a 5 min sample rate, from 21 GNSS stationsin the Eastern Mediterranean area (Israel). I will discuss the PWV diurnal climatologywith a focus on summer months. I will also show the PWV annual and inter-annualvariations over Israel, where the latter will be compared to ERA5 reanalysis. Finally, Iwill show an application for flood prediction using machine learning methods.
מרצה:
Shlomi Ziskin
(All events)
ה', 26/11/2020 - 12:00 עד 13:00
ראה גם: סמינר החוג לאא'א
מיקום:
zoom
Precipitable water vapor variability derived from GPS tropospheric pathdelays over the Eastern Mediterranean areaShlomi ZiskinAriel UniversityGlobal Navigation Station System (GNSS) meteorology is a remote sensing techniquethat utilizes signals that are transmitted from GPS satellites to ground based receiversin order to estimate the integrated water vapor or Precipitable Water Vapor (PWV)above the GPS ground station. I will briefly outline the methodology behind thistechnique, its strengths and limitations. Using this technique, I was able to assemblePWV long time series (5 to 20 years) ,with a 5 min sample rate, from 21 GNSS stationsin the Eastern Mediterranean area (Israel). I will discuss the PWV diurnal climatologywith a focus on summer months. I will also show the PWV annual and inter-annualvariations over Israel, where the latter will be compared to ERA5 reanalysis. Finally, Iwill show an application for flood prediction using machine learning methods.
מרצה:
Shlomi Ziskin
(All events)