MSGID: 1:317/3 640ab269   
   PID: hpt/lnx 1.9.0-cur 2019-01-08   
   TID: hpt/lnx 1.9.0-cur 2019-01-08   
    Underused satellite, radar data may improve thunderstorm forecasts   
      
      
     Date:   
         March 9, 2023   
     Source:   
         Penn State   
     Summary:   
         Tens of thousands of thunderstorms may rumble around the world   
         each day, but accurately predicting the time and location where   
         they will form remains a grand challenge of computer weather   
         modeling. A new technique combining underused satellite and radar   
         data in weather models may improve these predictions, according   
         to a team of scientists.   
      
      
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   FULL STORY   
   ==========================================================================   
   Tens of thousands of thunderstorms may rumble around the world each day,   
   but accurately predicting the time and location where they will form   
   remains a grand challenge of computer weather modeling. A new technique   
   combining underused satellite and radar data in weather models may improve   
   these predictions, according to a Penn State-led team of scientists.   
      
      
   ==========================================================================   
   "Thunderstorms are so ubiquitous it's hard to count how many you get in   
   Pennsylvania, or the United States or globally every day," said Keenan   
   Eure, doctoral student in the Department of Meteorology and Atmospheric   
   Science at Penn State. "A lot of our challenges, even today, are figuring   
   out how to correctly predict the time and location of the initiation of   
   thunderstorms."  The scientists found that by combining data from the   
   geostationary weather satellite GOES-16 and ground-based Doppler radar   
   they could capture a more accurate picture of initial conditions in the   
   boundary layer, the lowest part of the atmosphere, where storms form.   
      
   "There's value in improving thunderstorm predictions from both Doppler   
   radar observations and satellite observations that are currently underused   
   and we showed that not only can they be used to improve predictions but   
   putting them together has lots of benefits," said Eure, lead author on   
   the study. "The sum is greater than the individual parts."  The technique   
   showed promise in improving forecasts of convection initiation, the   
   conditions that spawn storms, several hours before the thunderstorms   
   occurred in a case study from May 2018 in the Texas panhandle. The   
   scientists reported their findings in the journal Monthly Weather Review.   
      
   "Keenan focused on using satellite observations to better define the   
   environment in which the storms would later form, and on using radar   
   observations to improve the low-level wind fields that eventually   
   helped to create the storms," said David Stensrud, professor of   
   meteorology at Penn State and Eure's advisor and co-author on the   
   study. "This observation combination had not been studied previously and   
   ended up adding significant value to the model forecasts on this day."   
   The scientists used data assimilation, a statistical method that can paint   
   the most accurate possible picture of current weather conditions in the   
   weather model, important because even small changes in the atmosphere   
   can lead to large discrepancies in forecasts over time.   
      
   Understanding conditions in the boundary layer is particularly important   
   because it strongly influences the ingredients for convection --   
   near-surface moisture, lift and instability -- a process that causes   
   warm air near the Earth's surface to rise and form clouds.   
      
   "We obviously can't model every molecule in the atmosphere, but we want to   
   get as close as possible," Eure said. We really believe this work adds a   
   lot of valuable information that models currently don't have and that we   
   can help the depiction of the lowest part of the atmosphere."  The team   
   assimilated satellite and radar data separately and simultaneously and   
   found the best results came from combining infrared brightness temperature   
   observations from the satellite and radial wind velocity and boundary   
   height observations from the radar.   
      
   The work uses all-sky satellite data assimilation, developed by   
   Penn State's Center for Advanced Data Assimilation and Predictability   
   Techniques, that assimilates satellite data from all weather conditions,   
   including cloudy and clear skies. Forecasting previously relied on   
   clear-sky observations, due to challenges in diagnosing the complex   
   physical processes within clouds, the scientists said.   
      
   "While more cases need to be explored, these observations are currently   
   available and could be used to improve thunderstorm prediction over the   
   coming decade as NOAA continues to advance its Warn-on-Forecast paradigm   
   in which computer model predictions help to make severe weather warnings   
   more accurate and timely," Stensrud said.   
      
   Other Penn State researchers on the project were Matthew Kumjian and   
   Steven Greybush, associate professors, Yunji Zhang, assistant professor   
   and Paul Mykolajtchuk, former graduate student, in the Department of   
   Meteorology and Atmospheric Science.   
      
   This research builds on work by the late Fuqing Zhang, distinguished   
   professor of meteorology and atmospheric science.   
      
   NASA and the National Oceanic and Atmospheric Administration supported   
   this research.   
      
       * RELATED_TOPICS   
             o Space_&_Time   
                   # Satellites # Sun # Solar_Flare # NASA   
             o Earth_&_Climate   
                   # Weather # Severe_Weather # Storms # Atmosphere   
       * RELATED_TERMS   
             o Meteorology o Numerical_weather_prediction o   
             Weather_forecasting o Weather o Earth_science   
             o Severe_weather_terminology_(United_States) o   
             National_Hurricane_Center o Global_Positioning_System   
      
   ==========================================================================   
   Story Source: Materials provided by Penn_State. Original written by   
   Matthew Carroll. Note: Content may be edited for style and length.   
      
      
   ==========================================================================   
   Journal Reference:   
      1. Keenan C. Eure, Paul D. Mykolajtchuk, Yunji Zhang, David   
      J. Stensrud,   
         Fuqing Zhang, Steven J. Greybush, Matthew R. Kumjian. Simultaneous   
         Assimilation of Planetary Boundary Layer Observations from Radar   
         and All- Sky Satellite Observations to Improve Forecasts of   
         Convection Initiation.   
      
         Monthly Weather Review, 2023; DOI: 10.1175/MWR-D-22-0188.1   
   ==========================================================================   
      
   Link to news story:   
   https://www.sciencedaily.com/releases/2023/03/230309125034.htm   
      
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