Description:
There is a major need for accurate and timely observations and predictions of the altitude in the atmosphere of the rain-snow transition boundary (“snow level”) in the mountainous regions of the United States spanning the time period from September to May. Winter storms frequently impact major interstates and highways, including Interstate 80 through the Sierra Nevada and Tetons, Interstates 70 and I-79 through the Appalachians, and Interstate 90 through the Cascades and Bitterroots. As the snow levels change during a winter storm, so do the number of miles of highway that are impacted by snow and more miles of highway that need to be plowed and/or closed.
Adverse weather in various mountainous and remote regions is one of the major causes for delay on the roadway system which can add significant costs to shipping resulting in overall negative impacts to the economy. In regards to public safety, observation systems that monitor rain-snow level evolution in the atmosphere are very sparse throughout the western and eastern mountain ranges. High spatial and temporal resolution observations and predictions with sufficient temporal and geographic coverage to match the scale of winter storms and traffic flows will help with travel planning with the public and commerce. These high resolution observations and predictions would need to be readily available with low latency and adequate accuracy to NOAA and the public and using relatively low-cost instrumentation to permit deployment of a wide network of sensors in hazard-prone regions. These sensors that would provide the observations and follow-on predictions could provide improved weather conditions data oriented towards forecasters, public, and freight industry and could lead to development of a hazard avoidance system for the public.
The sensor data could also provide a critical dataset for academia to help improve snow level forecasting, which is a major challenge for forecasters. This would ultimately benefit decision makers in private industry, public safety, and freight movement planning.
Improved snow level forecasts could help mitigate costs of shipping by allowing implementation of shipping models to account for adverse weather by shipping products earlier, later, or stopping in route. Having an improved handle on snow levels would avoid loss of revenue due to unexpected closures and hazardous driving conditions for trucks.
Snow level forecasts also directly affect flood forecasts and warnings and associated rivers and streams would provide an additional benefit to the public, industry, and emergency management community when planning for large scale flood events. This information would benefit planning for agriculture and avoid problems with survival of farm animals during spring months.
