ERA-Interim/Land is a global reanalysis of land-surface parameters from 1979-2010 at 80 km spatial resolution. It was produced with a recent version of the HTESSEL land-surface model using atmospheric forcing from ERA-Interim, with precipitation adjustments based on GPCP v2.1.
The evolution of the global land surface state (moisture content and/or temperature) of the different components, soil, vegetation, snow, is of great interest to understand climate-change impact in recent years and the numerical weather prediction system at ECMWF provides the most accurate meteorological forcing to drive the land surface numerical schemes. ERA-Interim/Land, a global land-surface dataset covering recent decades, is the result of a single 32 year simulation with the latest ECMWF land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on Global Precipitation Climate Project. ERA-Interim/Land preserves closure of the water balance and includes a number of parameterisations improvements in the land surface scheme with respect to the original ERA-Interim dataset, which makes it suitable for climate studies involving land water resources. The quality of ERA-Interim/Land, that includes a number of parameterisations improvements introduced in recent years in the operational NWP model, was assessed in comparison to site measurements, satellite-based products and other reanalyses, and it is supporting the study of climate trends. ERA-Interim/Land provides a global integrated and coherent water resources estimate that is used also for the initialization of numerical weather prediction and climate models. Enhanced versions are foreseen within the ERA-Clim projects.
For a description of this data set, see Balsamo et al. (2011)
Balsamo, G., Albergel, C., Beljaars, A., Boussetta, S., Brun, E., Cloke, H., Dee, D., Dutra, E., Muñoz-Sabater, J., Pappenberger, F., de Rosnay, P., Stockdale, T., and Vitart, F.: ERA-Interim/Land: a global land surface reanalysis data set, Hydrol. Earth Syst. Sci., 19, 389-407, doi:10.5194/hess-19-389-2015. 2015. http://www.hydrol-earth-syst-sci.net/19/389/2015/hess-19-389-2015.html
C. Albergel, W. Dorigo, R. H. Reichle, G. Balsamo, P. de Rosnay, J. Muñoz-Sabater, L. Isaksen, R. de Jeu and W. Wagner: Skill and Global Trend Analysis of Soil Moisture from Reanalyses and Microwave Remote Sensing. J. Hydrometeor, 14, 1259–1277, doi:10.1175/JHM-D-12-0161.1, 2013.