Assimilation of MODIS snow cover fraction for improving snow variables estimation in west China

Chunlin Huang

doi:10.1117/12.974512

19 October 2012 Assimilation of MODIS snow cover fraction for improving snow variables estimation in west China

Chunlin Huang

Proceedings Volume 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV; 853111 (2012) https://doi.org/10.1117/12.974512
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

Accurate estimation of snow properties is important for effective water resources management especially in mountainous areas. In this work, we develop a snow data assimilation scheme based on ensemble Kalman filter (EnKF), which can assimilate remotely sensed snow observations into the Common Land Model (CoLM) to produce spatially continuous and temporally consistent snow variables. The snow cover fraction (SCF) product (MOD10C1) from the moderate resolution imaging spectroradiometer (MODIS) aboard the NASA Terra satellite was used to update CoLM snow properties. The assimilation experiment is conducted during 2003-2004, in Xingjiang province, west China. The preliminary results are very promising and show that distributions of snow variables (such as SCF, snow depth, and SWE) are more reasonable and reliable after assimilating MODIS SCF data. The results also indicate that EnKF is an effective and operationally feasible solution for improve snow properties prediction.

Citation Download Citation

Chunlin Huang "Assimilation of MODIS snow cover fraction for improving snow variables estimation in west China", Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 853111 (19 October 2012); https://doi.org/10.1117/12.974512

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