weather prediction models. Improvements in characterizing the land surface
and modeling the atmospheric boundary layer are required.
Prediction of solar radiation on cloudy and partly cloudy days remains a
challenge and more research is required to optimize methods than may
improve insolation prediction.
Display
System Status: The operational versions of the MDSS needs to show the users
when critical parts or inputs to the system are unavailable and the forecasts
may be impaired.
Operational MDSS systems should incorporate radar data into the display to
support tactical snow fighting operations.
General
Tactical Support: The DOTs require guidance once a storm has begun. A
tactical DSS solution will need to include radar products (precipitation type,
rate, liquid equivalent, etc.), snow gauge data and advanced nowcasting
algorithms.
Real-time Precipitation Observations: Developing a capability that provides
precipitation rate information in real-time would help tactical decision making
and will provide verification data to help tune predictions systems. A new
sensor or the application of an existing technology reapplied to this problem
could be very beneficial. If proven, the real time precipitation rate sensor
could become an enhancement to automatic weather stations.
Weak Events: Weak snow events turn out to be more important than strong
events for two reasons: (1) they occur more frequently and (2) they usually
catch the operators by surprise. Unfortunately, forecasting these events 12
hours in advance is as challenging as trying to determine where/when small
thunderstorms will develop. The hot start modeling approach, which takes
advantage of radar data appears to help.
Start/Stop Time: The end-users may want to see a dynamic range of likely
start and stop times. For example, snow will start between 6AM and 9AM and
end between 4PM and 5PM. This will give them some feel for the confidence
we have in the forecast. The range could be based on the spread of the
individual forecast modules.
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