[ACG53-03] An analysis of land surface temperature during summer clear-sky days focusing on the diurnal change characteristics using Himawari-8 data
キーワード：ひまわり８号、地表面温度
Land surface temperature (LST) is a physical quantity related to the surface heat/water budgets, and plays an important role in various fields, such as the land-atmosphere interactions, vegetation dynamics, and urban climate. A new generation of Japanese geostationary satellite, Himawari-8, can estimate the LST with high frequency (10 min) and a moderate spatial resolution (2–3 km) by improving observation functions.
However, the retrieval of LST from Himawari-8 data is basically limited to clear-sky conditions. In East and Southeast Asia, clouds are frequently generated due to the wet and hot environments, so that there are many outliers and missing values due to the clouds. Therefore, it is difficult to capture the temporal change characteristics of LST.
In order to fill the gaps due to a brief cloud cover, we attempt to use a diurnal temperature cycle (DTC) model, and show the limitations of the DTC model for various missing/outlier cases. Moreover, we investigate the thermodynamic implication of diurnal change characteristics represented by the DTC model in coastal/inland areas or various land cover types such as urban, cropland and forest areas.
However, the retrieval of LST from Himawari-8 data is basically limited to clear-sky conditions. In East and Southeast Asia, clouds are frequently generated due to the wet and hot environments, so that there are many outliers and missing values due to the clouds. Therefore, it is difficult to capture the temporal change characteristics of LST.
In order to fill the gaps due to a brief cloud cover, we attempt to use a diurnal temperature cycle (DTC) model, and show the limitations of the DTC model for various missing/outlier cases. Moreover, we investigate the thermodynamic implication of diurnal change characteristics represented by the DTC model in coastal/inland areas or various land cover types such as urban, cropland and forest areas.