Rgnvaldsson, īlafur, Institute for Meteorological
Research and the University of Bergen, Norway and ēgstsson, Hlfdn, Institute
for Meteorological Research and University of Iceland and Icelandic
Meteorological Office and Jonassen, Marius, Institute for Meteorological
Research and the University of Bergen and īlafsson, Haraldur, University of
Iceland, University of Bergen and the Icelandic Meteorological Office
An on-demand weather
forecasting system, named SARWeather, has been developed. The system is
tailored to meet the demanding needs of Search And Rescue operators world-wide.
SARWeather uses the AR-WRF model, initialized and forced on the boundaries with
data from the GFS global forecasting system. One of the unique features of the
system is that it is run on the Amazon Elastic Compute Cloud (Amazon EC2). This
ensures that twenty individual forecasts can be run simultaneously for any
region in the world. Increasing the number of potential forecasts is straight
forward, and can be done at a short notice. A second unique feature of
SARWeather is that the system does not require any prior knowledge on behalf of
the user regarding atmospheric modeling and/or high performance computing.
Thirdly, output from SARWeather can be easily ingested into other decision
support software, such as ArcGIS.
Data from a UAS system
named SUMO (Small Unmanned Meteorological Observer) have been shown to improve
local weather forecasts. Ongoing research aims at combining the SUMO with
SARWeather by transmitting atmospheric observations from vertical proŽles, made
by the SUMO observer, directly from the Želd to the SARWeather system via 3G
mobile transmissions.