NASA satellites provided a look at the rainfall potential in Hurricane Sally before and after it made landfall in southern Alabama. NASA’s Aqua satellite and IMERG analysis were used to analyze the storm’s flooding potential.
Sally came ashore on Wednesday, Sept. 16 around 5:45 a.m. EDT near Gulf Shores, Alabama. It was a Category 2 storm on the Saffir-Simpson Hurricane Wind scale with sustained winds near 105 mph (169 kph). As a slow-moving storm, Sally generated a lot of rainfall, left behind flooded streets and knocked out power to hundreds of thousands on the U.S. Gulf Coast.
NASA’s Infrared View of Sally
Cloud top temperatures provide information to forecasters about where the strongest storms are located within a tropical cyclone. Tropical cyclones do not always have uniform strength, and some sides are stronger than others. The stronger the storms, the higher they extend into the troposphere, and the colder the cloud top temperatures. NASA provides that data to forecasters at NOAA’s National Hurricane Center or NHC so they can incorporate it in their forecasting.
At that time, the AIRS image showed those strong storms over the Florida Panhandle, much of Alabama, Georgia and extending into western South Carolina.
On Sept. 16 at 3:11 p.m. EDT (1911 UTC) NASA’s Aqua satellite analyzed Sally using the Atmospheric Infrared Sounder or AIRS instrument. AIRS found the coldest cloud top temperatures as cold as or colder than minus 63 degrees Fahrenheit (minus 53 degrees Celsius) around the center of circulation and to the northeast and east of the center. NASA research has shown that cloud top temperatures that cold indicate strong storms that have the capability to create heavy rain. Credit: NASA JPL/Heidar ThrastarsonNASA Calculates Sally’s Rainfall.
NASA combined data from multiple satellites to estimate the rainfall from Hurricane Sally in near-real time at half-hourly intervals from September 11-16, 2020. Rainfall rates and rainfall accumulations are estimated using NASA’s Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm. IMERG combines observations from a fleet of satellites, in near-real time, to provide near-global estimates of precipitation every 30 minutes.
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