Assessments and Corrections of GLDAS2.0 Forcing Data in Four Large Transboundary Rivers in the Tibetan Plateau and Northeast China

GLDAS2.0 provides long-term fine resolution gridded hydrometeorological data sets, which are necessary for water-related studies, particularly in some transboundary rivers that are partially without observation. Yet, GLDAS2.0 has only been validated at limited locations, and few studies have been conducted to develop approaches to correct the GLDAS2.0 data for transboundary rivers. This work assessed the GLDAS2.0 data and developed approaches to correct their uncertainties for studies in large transboundary rivers in the Tibetan Plateau and Northeast China (NC). To achieve these goals, observational data from 1982 to 2010 and a water and energy budget-based distributed hydrological model including biosphere after calibration and validation were employed. We find that the GLDAS2.0 data (except for wind speed) can reasonably replicate observed seasonal variations. However, its specific humidity and wind speed have large uncertainty, and precipitation has large uncertainty in summer. In NC, the trends of its precipitation, air temperature, downward longwave radiation, and wind speed are consistent with the observations. In the Yarlung Tsangpo, Lancang, and Nu Rivers, the trends of all GLDAS2.0 data reproduce the observation very well, that is, wetting, warming, and dimming trends. Validations show that the corrections are effective and the corrected forcing data can be successfully used in hydrological simulation with improved performance than the raw GLDAS2.0 data, which demonstrates the usefulness of the methodology and corrected forcing data to hydrometeorological studies in transboundary rivers in China as well as in other nearby regions/countries. Plain Language Summary GLDAS2.0 provides long-term hydrometeorological data sets, which are necessary for water-related studies, particularly in some transboundary rivers that are partially without observation. This work assessed GLDAS2.0 data and developed approaches to correct their uncertainties for studies in large transboundary rivers in the Tibetan Plateau (TP) and Northeast China (NC). In NC, the trends of GLDAS2.0 precipitation, air temperature, downward longwave radiation, and wind speed are consistent with observations. In TP, the trends of all the GLDAS2.0 data reproduce observation very well. Validations show that the corrections are effective and the corrected data have improved performance than raw GLDAS2.0 data in hydrological simulation.

Automated summary

GLDAS2.0 provides important hydrometeorological data sets for water-related studies in transboundary rivers. This work assessed the data and developed approaches to correct their uncertainties in the Tibetan Plateau and Northeast China. The findings showed that the GLDAS2.0 data can reasonably simulate seasonal variations, but specific humidity, wind speed, and summer precipitation have large uncertainties. The corrected data improved the performance in hydrological simulations, demonstrating the usefulness of the methodology for transboundary river studies.