An integrated multi-scale Soil moisture and temperature observatory on the Tibetan Plateau

Scarce in situ data in the western and central Tibetan Plateau (TP) hinders scientific research on physical process representation in climate models. Satellite remote sensing and climate models are effective data sources in complex topography and harsh environments; however, they have not been effectively validated or improved for the lack of multi-scale observations matching their pixel or grid scales. Therefore, it is necessary to develop an integrated multi-scale observatory. Since 2014, a satellite pixel oriented TP Integrated Multi-Scale moisture and temperature Observatory (TP-IMSO) was established and has been in operation for ten years to obtain a long-term multi-scale soil temperature and moisture dataset which integrates site point and spatial surface observation designs. The TP-IMSO is composed of two automatic wireless transmission networks over the Naqu and A’li areas, and atmospheric and soil temperature and humidity vertical profile observations in the “soil – atmosphere” interface layer. We also develop a dual frequency remote data transmission system based on Beidou satellite and 4G and a dual power supply system that is resistant to low temperature and low pressure in high-altitude regions. A cube dataset of soil temperature and humidity was obtained through spatial interpolation in both horizontal and vertical directions within the soil. It is found that the elements of the TP-IMSO networks have a highly variable character. The soil moisture in the top layer (0-3cm) is more variable than that in other layers, and the largest standard deviation of all the five layers occurs in July. Using observation data to validate multiple soil moisture remote sensing products, the root mean squared error (RMSE) of remote sensing products ranges from 0.038 to 0.177 cm³·cm^-3, and for ERA-interim and National Centers for Environmental Prediction (NCEP) reanalysis data, the RMSE ranges from 0.038 to 0.081 cm³﹒cm^-3.