cug-xyx/tch_method

Three‐Cornered Hat (TCH) Method/Bayesian Three‐Cornered Hat (BTCH) Method

Authors

Tongren Xu ([email protected])
Xinlei He ([email protected])

Brief introduction

The three‐cornered hat (TCH) method is used to assess the relative uncertainty of gridded datasets without any a priori knowledge.
The Bayesian‐based three‐cornered hat (BTCH) method is used to integrate gridded datasets without any a priori knowledge.
TCH_calculation_v1.m is the main program of the TCH method.
BTCH_calculation_v1.m is the main program of the BTCH method.
(You need to prepare at least three types of gridded datasets to run the program, and each type of datasets needs to have complete consistency)

Related references

Xu, T., Guo, Z., Xia, Y., et al. 2019. Evaluation of twelve evapotranspiration products from machine learning, remote sensing and land surface models over conterminous United States. Journal of Hydrology 578, 124105. https://doi.org/10.1016/j.jhydrol.2019.124105
He, X., Xu, T., Xia, Y., et al. 2020. A Bayesian Three-Cornered Hat (BTCH) Method: Improving the Terrestrial Evapotranspiration Estimation. Remote Sensing 12, 878. https://doi.org/10.3390/rs12050878