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Title

COMPARISON OF SNOW COVER RESULTING FROM MODIS SATELLITE DATA AND A NUMERICAL PREDICTION MODEL IN IRAN

Pages

 Start Page 189 | End Page 203

Abstract

 The prediction of snow cover is fundamental for runoff prediction in terms of the snow melting role. The purpose of this study was to assess the feasibility of using snow cover output of the WRF numerical prediction model in order to predict snow melting. Since there are a few snow monitoring stations in the mountainous areas of Iran, satellite data were the only widespread observation data. Accordingly, the extraction of snow cover data using MODIS sensor was addressed. Afterwards, the data was compared to the snow cover of the WRF model outputs for a case study. Finally, the results were assessed using the probability table. The studied area is located on Chalous Road, Alborz province, and the study was made for the period of January 28 to January 30, 2017 with heavy snowfall. Synoptic analysis indicated a strong pressure gradient in surface level associated with cold air in the middle layer of the atmosphere. Overlapping of satellite snow cover data with model output showed the linear correlation coefficient 0f 0. 7 at a significant level of 0. 01 in a 90 × 78 points network with 5 km resolution. The probability of detecting snow on 3 day average was 87% and the probability of false detection was about 20%. Heidke Skill Score was about 0. 7 for days with clear sky (January 29th and January 30th. ) which was the best result in January 28th. The Heidke Skill Score was reduced to 57% which may be the result of inaccurate satellite observation due to cloudiness or inaccurate forecasting. Since there is no ground station in the selected area, one cannot properly comment on this.

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