Using the 2003 post-demonstration evaluations, technical performance results, and the
lessons learned from meetings with Iowa DOT and support personnel, a list of system
development activities was compiled that was considered important for the success of the
winter 2004 field demonstration. The list below includes enhancements for 2004 to the
RCTM the RWFS, the mesoscale model ensemble and the client display application.
RCTM module modifications focused on the preparation of better road treatment
recommendations. The RWFS updates were centered on improved handling of the
quantitative precipitation forecast data, increasing the temporal resolution of the output,
and better quality control and use of observations in the preparation of weather forecasts.
The mesoscale model ensemble configuration was changed to use a better selection of
models with a higher temporal resolution in an attempt to improve the detection of weak
weather events. And finally, several refinements were made to the display application
based on Iowa DOT feedback.
9.1
Road Condition and Treatment Module (RCTM)
The following enhancements were made to the road condition and treatment module
including the road temperature model (SNTHERM-RT) and coded rules of practice:
1) Road Temperature Model Initialization: Revised the road temperature model
(SNTHERM-RT) so that it could be initialized using road temperature surface and
subsurface observations for routes with RWIS stations that had both surface and
subsurface data. For evaluation purposes, this method was applied to two RWIS
stations (Ames RWIS, and I-235 RWIS).
2) Plowing Rules: Fixed a software bug that was introduced in the middle of the
winter 2003 demonstration that did not allow `plow only' treatments to be
recommended.
3) System Reset: Added ability for the users to reset the road conditions (road snow
depth = 0 and chemical concentration = 0) for each route or a group of routes.
4) Blowing Snow Potential: In the absence of a more sophisticated solution, created
a `blowing snow' alert when blowing snow conditions were likely. The blowing
snow potential algorithm is based on precipitation type, snowfall rate, air
temperature, wind speed, number of diurnal cycles, and occurrence of other
precipitation types since the last snowfall.
5) Rules Of Practice: Refined the coded rules of practice using Iowa weather and
treatment case data. Several significant improvements were made to the code for
2004. Logic was added within the MDSS system to recognize the overall storm
situation. During the winter of 2003, the treatment module essentially determined
the next treatment recommendation based on the weather that was forecasted from
the current trigger to the time it would take to traverse a given route. This
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