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In the Project for Intercomparison of Land-Surface Parameterization Schemes phase 2a experiment, meteorological data for the year 1987 from Cabauw, the Netherlands, were used as inputs to 23 land-surface flux schemes designed for use in climate and weather models. Schemes were evaluated by comparing their outputs with long-term measurements of surface sensible heat fluxes into the atmosphere and the ground, and of upward longwave radiation and total net radiative fluxes, and also comparing them with latent heat fluxes derived from a surface energy balance. Tuning of schemes by use of the observed flux data was not permitted. On an annual basis, the predicted surface radiative temperature exhibits a range of 2 K across schemes, consistent with the range of about 10 W m Ϫ2 in predicted surface net radiation. Most modeled values of monthly net radiation differ from the observations by less than the estimated maximum monthly observational error (Ϯ10 W m Ϫ2). However, modeled radiative surface temperature appears to have a systematic positive bias in most schemes; this might be explained by an error in assumed emissivity and by models' neglect of canopy thermal heterogeneity. Annual means of sensible and latent heat fluxes, into which net radiation is partitioned, have ranges across schemes of

Since its launch in March 2002, the Gravity Recovery and Climate Experiment (GRACE) mission has been measuring the global time variations of the Earth's gravity field with a current resolution of ∼500 km. Especially over the continents, these measurements represent the integrated land water mass, including surface waters (lakes, wetlands and rivers), soil moisture, groundwater, and snow cover. In this study, we use the GRACE land water solutions computed by Ramillien et al. (2005a) through an iterative inversion of monthly geoids from April 2002 to May 2004 to estimate time series of basin‐scale regional evapotranspiration rate and associated uncertainties. Evapotranspiration is determined by integrating and solving the water mass balance equation, which relates land water storage (from GRACE), precipitation data (from the Global Precipitation Climatology Centre), runoff (from a global land surface model), and evapotranspiration (the unknown). We further examine the sensibility of the computation when using different model runoff. Evapotranspiration results are compared to outputs of four different global land surface models. The overall satisfactory agreement between GRACE‐derived and model‐based evapotranspiration prove the ability of GRACE to provide realistic estimates of this parameter.

[1] 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°Â 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.Citation: Ngo-Duc, T., J. Polcher, and K. Laval (2005), A 53-year forcing data set for land surface models,