A 53‐year forcing data set for land surface models

As most variables describing the state of the surface are not directly observable, we have to use land surface models in order to reconstruct an estimate of their evolution. These large‐scale land surface models often require high‐quality forcing data with a subdiurnal sampling. Building these data sets is a major challenge but an essential step for estimating the land surface water budget, which is a crucial part of climate change prediction. To study the interannual variability of surface conditions over the last half century, we have built a 53‐year forcing data set, named NCC. NCC has a 6‐hourly time step from 1948 to 2000 and a spatial resolution of 1° × 1°. It is based on the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis project and a number of independent in situ observations. In this study we show the adjustments which need to be applied to the reanalysis and how they impact the simulated continental water balance. The model outputs are validated with the observed discharges of the world's 10 largest rivers to estimate the combined errors of the forcing data and the land surface model. The seasonal and interannual variations of these discharges are used for this validation. Five numerical experiments have been carried out. They used the forcing data sets obtained after each step of data adjustment and the forcing of the Global Soil Wetness Project 2 as inputs for the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model. The quality of forcing data is improved after each adjustment. The precipitation correction gives the most important improvement in the simulated river discharges, while the temperature correction has a significant effect only at high latitudes. The radiation correction also improves the forcing quality, especially in term of discharge amplitude. The NCC forcing data set can be used to study the water budget over many areas and catchment basins that have not been yet analyzed in this study. With its period of 53 years, NCC can also be used to evaluate the trends of terrestrial water storage in particular regions.