The Assessment of CMIP5 Climate Models in the Context of Complementary Relationship of Areal Evapotranspiration

The moisture in the atmosphere has a key role through evapotranspiration process among all meteorological variables governing hydrological energy and water cycle. In atmospheric dynamics, it functions to maintain the energy balance between the surface and the atmosphere, and it produce precipitation by supplying water to the atmosphere. Additionally, the evapotranspiration has an significant effects on flow-duration curve of long-term streamflow particularly below ordinary and low flows. The most climate models have an evapotranspiration module, but it is not easy to validate due to a lack of observation data. The main objective of this study is to verify the interactive relationship between potential and actual evapotranspiration through the complementary relationship of observed areal evapotranspiration in multi-purpose dam basin and then assess the simulation ability of CMIP5 climate models’ evapotranspiration modules. The 5 GCM datasets with the highest performance in Korean region that obtained from the previous research were collected and the study area is Soyanggang dam basin in Han River, the South Korea. The actual evapotranspiration data of raw GCMs are shown to be overestimated during 1974~2000 of the reference period and the quantile mapping was applied for the regional bias correction. Single GCM model indicates to improve overall quantitative performance through the regional bias correction. However, the additional bias correction was required for improving reproducibility of the complementary relationship between the actual and potential areal evapotranspiration. In order to resolve, the Bayesian multi-model ensemble averaging scheme was applied and leaded to sufficiently useful consequences in terms of absolute biases and reproducibility of complementary relationship. This technique allowed reducing the uncertainty arising from the direct use of actual evapotranspiration of GCMs and consequently expected to contribute in improving reliability of the estimation of low flow during non-flood season for inflow projection.