Paul G. Witsaman NWS Southern Region Headquarters Fort Worth, TX
ABSTRACT
Lack of access to real-time/near real-time upper air observations has been a problem in improving weather forecasts at wildland fires. Adapting the Forecast Systems Laboratory’s (FSL) aircraft data information concept to the incident scale provides a viable solution to this problem. FSL uses the term ACARS/AMDAR in reference to upper air weather data they collect from commercial aircraft. This data includes pressure, temperature, humidity, wind speed, wind direction provided by sensors installed on commercial aircraft. FSL then ingests this data into numerical weather prediction models.
At large fires, the Incident Command Team (ICT) deploys aviation assets to assist in controlling the fire. One or more of the fixed wing or rotary wing aircraft being used would be equipped with the ACARS/AMDAR type equipment. The data collected from these sensors would be relayed to the on-site NWS Incident Meteorologist (IMET). Access to this important asynoptic data would provide mission critical and vital weather information to the IMET assisting the Fire Behavior Analyst (FBAN), and the entire ICT.
This observed data could be used immediately to track winds and temperatures aloft. Accurate winds aloft remains a critical, but hard to assess, fire weather parameter. Strong winds aloft that reach the surface can cause an extremely dangerous fire control situation. Another important benefit provided would be real-time verification of transport winds and mixing height forecasts. The data could also be used to run rapid local models from the IMET’s All-hazards Meteorological Response System (AMRS).
The impact of an unforecast critical fire weather element continues to be an important concern for the IMET, the FBAN, and the ICT. In the effort to mitigate that risk, this paper will detail a proof of concept test to ingest asypnotic upper air weather data into the wildland fire weather forecast process.
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