Using MODIS Land Surface Temperature in Operational Snow Model

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Tuesday, 4 February 2014
Hall C3 (The Georgia World Congress Center )
Eylon Shamir, Hydrologic Research Center, San Diego, CA; and K. P. Georgakakos

Reliable flash flood warnings and alerts for regions that experience seasonal development of snow pack requires estimates of the snow line and of soil water deficit below the snow line. In operational regional flash flood guidance systems that assist forecasters with the production of such warnings, the snow line and the soil moisture below it are estimated from a soil moisture accounting model that is implemented in conjunction with a snow accumulation and ablation model. These models are forced by real time observations of precipitation and air surface temperature. In many regions worldwide the availability of in-situ air surface temperature data is rather sparse especially in high mountain areas where snow is prevalent. In this study we assessed the usability of land surface temperature (LST) from MODIS that is available from Aqua and Terra four times daily at 1km resolution (MOD11A1 &MYD11A1) as a surrogate for air surface temperature forcing for the snow model. The study was conducted in the mountainous terrain of Southeastern Turkey, an area with relatively dense observational in-situ network that is maintained by the Turkish State Meteorological Service. We found that the simulated snow accumulation and ablation characteristics forced by approximating the surface air temperature from the MODIS LST product is comparable to simulations that are based on surface air temperature derived from the dense observed network. The uncertainty associated with the simulation of snow using the LST is also assessed for various terrain and land cover characteristics. The MODIS LST product demonstrates operational quality that can improve snow modeling in mid latitude regions that lack sufficient meteorological observations.

Research Funded by NASA Disasters Program