Development of the GCOM-C global ETsub(index) estimation algorithm
2016
Tasumi, M. (University of Miyazaki, Miyazaki (Japan). Faculty of Agriculture, Department of Forest and Environmental Sciences) | Kimura, R. | Allen, R.G. | Moriyama, M. | Trezza, R.
Freshwater resources management has become a primary global issue. Improved management of agricultural water is important because agriculture is the dominant user of fresh water. Estimation of evapotranspiration (ET) using satellite imagery is regarded as an effective tool for improving agricultural water management. This paper presents the progress made in the development of a global Evapotranspiration-Index (ETsub(index)) estimation algorithm that is applicable to Global Change Observation Mission-Climate (GCOM-C) satellite observation. The algorithm computes an ET-related indicator that is termed the ETsub(index). The primary input data are thermal observation data from the satellite and near-surface wind speed data from a global climate model. The ETsub(index) is equivalent to the crop coefficient, which has been applied widely for agricultural and irrigation water management around the globe. As a result, the ETsub(index) maps have congruency with traditional agricultural water management methodologies, although the application targets of the ETsub(index) are not limited to irrigation or agriculture. The algorithm estimates the ETsub(index) by analyzing the relative position of actual surface temperature between two extreme surface conditions (wet and dry conditions). Estimation of the wet and dry surface temperatures is a key component of the algorithm. The developed model represents the wet and dry surface temperatures with less than 1degC bias and less than 6degC random error in Shenmu, China. The simple structure of the algorithm is designed to process global data with limited computational load. The final product is a 16-day, cloud-free global ETsub(index) map having spatial resolution equal to that of GCOM-C thermal observation. Daily actual ET is estimated from the global ETsub(index) map using local or global weather datasets that include cloudy and rainy days.
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