July 1, 2022
Deriving a Long-Term Pan Evaporation Reanalysis Dataset for Two Chinese Pan Types
Wang, Kaiwen; Liu, Xiaomang; Li, Yuqi; Yang, Xiaohua; Bai, Peng; Liu, Changming; Chen, Fei. (2019). Deriving a Long-Term Pan Evaporation Reanalysis Dataset for Two Chinese Pan Types. Journal Of Hydrology, 579.
Abstract
A long-term continuous and consistent pan evaporation (E-pan) reanalysis dataset will augment the analysis of E-pan distributions when the observation network is discontinuous or inconsistent, and assist in the evaluation of the outputs of General Circulation Models (GCMs) and Land Surface Models (LSMs). From the 1950s to early 2000s, China had a continuous observation of the D20 pan, but this was replaced by the 601B pan across China around 2002, and thus the E-pan observation network became discontinuous and inconsistent. This study developed a long-term monthly, 0.05 degrees, continuous and consistent reanalysis dataset for both D20 and 6018 pans covering mainland China throughout 1960-2014, based on meteorological data homogenization and interpolation and E-pan assimilation. The PenPan-V3 model used inE(pan) assimilation was successfully validated by observations at 767 and 591 stations for D20 and 601B pans, respectively. Comprehensively considering the physical influence of elevation, radiation, wind speed, humidity, and air temperature, the average annual and seasonal gridded E-pan reanalyses show significant spatial dependent on proximity to the ocean and latitude, consistent with previous studies. The reanalysis dataset can be used to analyze E-pan distributions across China, including the areas without observations, and to estimate the representativeness of E-pan to atmospheric evaporative demand. The dataset has been released in two cloud servers in China and the United States, and it will continue to be maintained and updated.
Keywords
General Circulation Model; Evaporation (meteorology); Atmospheric Temperature; Wind Speed; China; Long-term Continuous And Consistent Dataset; Pan Evaporation Reanalysis Dataset; Representativeness To Atmospheric Evaporative Demand; Maximal T-test; Reference Evapotranspiration; Climate Data; Energy-balance; Reference Crop; Trends; Water; Model; Demand; General Circulation Models; Air Temperature; Data Collection; Evaporation; Evaporative Demand; Humidity; Latitude; Meteorological Data; United States
