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Consistency Assessment and Uncertainty Analysis of Spatial-Temporal Characteristics of Evaporation Data in the Greater Mekong Subregion
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DOI：10.1175/JHM-D-24-0014.1.png)
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Abstract
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To optimize the use of evaporation products in hydrometeorological applications across the Greater Mekong Subregion (GMS), it is essential to evaluate the spatiotemporal consistency of datasets and quantify their uncertainty. This study employs the comparison map profile (CMP) and three-cornered hat (TCH) methods to evaluate four widely riod 1980-2013. The CMP method evaluates the spatiotemporal consistency, while the TCH method estimates the relative uncertainty of the dataset across different land-cover types. The results show that the annual average evaporation across these datasets ranges from 809.47 to 920.66 mm yr21, with spatial similarity exceeding 0.76; ERA5-Land exhibits slightly lower consistency in the southern GMS. However, these datasets show limited consistency in evaporation variability. FLUXCOM has the lowest variability and lacks a significant trend, and the other datasets reveal consistent upward trends. Across the entire GMS, ERA5-Land has the highest relative uncertainty, while GLEAM consistently maintains the lowest. Regionally, uncertainty is highest in grasslands within the northern GMS (N-GMS), while in the middle GMS (M-GMS) and southern GMS (S-GMS), it primarily stems from rainfed cropland. Among datasets, ERA5-Land has the highest uncertainty in N-GMS, FLUXCOM has the highest uncertainty in M-GMS, and GLDAS has the highest uncertainty in S-GMS. By integrating the CMP and TCH results, this study explores potential causes of dataset spatial inconsistencies and the uncertainty across different land-cover types in the GMS. These findings offer valuable insights for selecting and applying evaporation datasets in future hydrometeorological research and applications in GMS.
Keywords:
Evaporation
Evapotranspiration
Uncertainty
Variational analysis
Trends
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