Wednesday, 19 October 2011: 5:15 PM
Grand Zoso Ballroom Center (Hotel Zoso)
Timothy J. Brown, DRI, Reno, Nevada; and J. D. Horel, G. McCurdy, and M. G. Fearon
The Remote Automated Weather Station (RAWS) network currently totals approximately 2,100 weather-monitoring stations distributed throughout the United States. As of March 2011, 1,732 stations are defined as permanent RAWS with information suitable for a network analysis. The network is interagency in that ownership includes federal and state organizations. Given the investment in the RAWS program and the extensive usage of RAWS data, it is clear that RAWS is of critical importance to many aspects of fire business (the characterization of fire occurrence in an area, described in terms of total number of fires and acres per year; and number of fires by time, size, cause, fire-day, large fire-day, and multiple fire-day). As stated in the National Wildfire Coordinating Group Fire Environment Working Team (now the Fire Environment Committee (FENC)) October 2007 RAWS/ROMAN Study Report, The purpose of the RAWS network is to support point and gridded applications of fire weather for fire program analysis, fire danger rating, fire behavior prediction fire weather forecasting, and smoke management.
This study addresses an appropriate RAWS network. Because of the many different potential applications for RAWS data, the common denominator is to examine RAWS and non-RAWS observations as they affect gridded depictions (or analyses) of fire weather conditions. Two separate analyses were performed. The first was an analysis of the influence of RAWS and selected non-RAWS (National Weather Service (NWS) Automated Surface Observing System (ASOS)) observations on gridded analyses. The second was a quantitative analysis to assess the uniqueness of each RAWS station in terms of a RAWS Uniqueness Index (RUI) developed for this report for this purpose. Finally, the potential for incorporation of data from other networks around the country for fire business is discussed.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner