87th AMS Annual Meeting

Tuesday, 16 January 2007: 4:15 PM
On the use of satellite cloud top pressure data in the estimation of snowfall occurrence and precipitation rates
216AB (Henry B. Gonzalez Convention Center)
Mark Askelson, Univ. of North Dakota, Grand Forks, ND
Road maintenance personnel are responsible for keeping roads safe for travel and thus plow and chemically treat roads upon which wintertime precipitation has fallen. In order to manage this activity, real-time information regarding where and how much precipitation has fallen is required. Our ability to determine these, however, is limited. Surface observation data are limited owing to lacking spatial and temporal densities and because few surface observation sites provide real-time information regarding wintertime precipitation accumulation. While Environmental Sensor Systems (ESSs) have great potential to help in this regard since they are located next to roadways where estimates of precipitation occurrence and accumulation are needed, they generally do not provide information regarding wintertime precipitation accumulation. Radar data, on the other hand, provide much improved spatial and temporal coverage. These data, though, are limited because low-elevation radar beams commonly overshoot winter precipitation systems at moderate to distant ranges and because radar-based precipitation estimates typically have greater errors than do surface-observation-based estimates. Satellite data are limited by their temporal resolution and by the fact that they have not commonly been applied to relatively weak wintertime systems.

In response to these limitations of both surface and radar data, satellite data are being tested as a means for improving estimations of both snowfall occurrence and accumulation. On the contrary to other approaches that utilize satellite data for similar purposes, this approach utilizes GOES cloud top pressure data in order to provide estimates with sufficient temporal resolution for real-time applications. Inasmuch, cloud top pressure data serve as a proxy for precipitation rate, which is the desired variable. Consequently, other data, specifically radar (and possibly surface observation) data, are used to correlate cloud-top pressure data with precipitation rates.

The design, development, and validation of this snowfall occurrence and accumulation estimation tool will be discussed, with focus placed on specific cases of both success and failure and on the quantification of snowfall occurrence and accumulation estimation accuracy using standard measures (e.g., probability of detection, bias, etc.). In addition, expected success and failure situations and the utilization of this tool in road maintenance applications will be considered.

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