Analysing a 13 years MODIS land surface temperature time series in the Mekong basin

Abstract

Land surface temperature (LST) is an important parameter in the climate system, impacting vegetation development, snow cover, runoff, and human livelihoods. Knowledge of LST dynamics can furthermore be used as an indicator for climate variability and change. LST is regularly measured from satellite sensors on a broad spatial scale and with a high temporal resolution. In this research, MODIS (Moderate Resolution Imaging Spectroradiometer) sensor data are used to assess the spatial and temporal patterns of LST in the Mekong Basin (MB) including its temporal variability. The dataset contains 13 years of MODIS LST data, a unique measurement time series in terms of resolution, accuracy, and homogeneity. In the analysis a temporal granularity of 8-days was used. The MB was divided into six physiographically homogenous regions. The height and magnitude of annual LST curves differ between the regions and prove to be strongly dependent on the topography. Large intra-annual magnitudes and low temperatures (daytime/nighttime annual regional means are 14 °C/-7 °C) are found in the northern areas, mainly in the high-lying Tibetan Plateau. The more southern areas are characterized by low LST seasonality and high temperatures (daytime/nighttime annual regional means of these regions range from 25 °C to 30 °C/19 °C to 25 °C). The year-to-year variability of LST is similar in all regions (regional weekly daytime/nighttime deviations lower than 4 °C/6 °C, except for the Tibetan Plateau, where regional weekly daytime/nighttime deviations reach 6 °C/18 °C). In summer, 42 % of daytime LST could be explained by topographic height. In winter and in nighttime scenes, topography explained 89-97 % of the LST distribution. Land use and land use change further influence the LST pattern, mainly in the daytime. An example of rising LST due to deforestation is given. This study allows for an improved understanding of temperature dynamics in one of the world’s largest river basins.