Paper on accounting for the location of dropwindsondes during measurements published in the Journal of Atmospheric and Oceanic Technology

Summary: Hurricane Hunter aircraft have been releasing instruments called dropwindsondes to measure pressure, temperature, moisture, and wind speed and direction in hurricanes for two decades. Data from dropwindsondes released near the storms have led to better forecasts of where they will go, but improvements to forecasts of how strong they will get have lagged. Part of the reason is because of the way the data have been sent from the aircraft to places like NOAA where they are used to start model forecasts.

Dropwindsonde data have always been sent from the aircraft in a format called TEMP DROP. Each message includes where the dropwindsonde was released on a grid with spacing of about 7 miles; it also includes when the dropwindsonde was released to the closest hour. The wind in the hurricane pushes the instrument away from the release location, and it takes many minutes for it to fall to the ocean surface; this information is not reported in the message. Current forecast models have grids as small as 1 ¼ miles and recalculate the weather every 5 seconds. Because the time and location information in the TEMP DROP messages are not accurate enough for the models inside hurricanes, dropwindsonde data in hurricanes are usually not used by forecast models.

A technique to calculate the times and locations of the observations in the TEMP DROP message is described in this paper. These calculated times and locations are compared to the true times and locations values that are saved on the aircraft.

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Important Conclusions:

  1. The location and time of each observation in the TEMP DROP message can be calculated, even though it is not transmitted in that message.
  2. The calculated observation locations are usually less than 1/3 mile from the true locations.
  3. The calculated observation times are usually less than 15 seconds from the true times.
  4. Incorporation of these corrected data into models leads to improved analyses of tropical cyclones.

Read the article at http://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-17-0023.1.