* Hagemann, S., 2002

An improved land surface parameter dataset for global and regional climate models

MPI Report No. 336, Max Planck Institute for Meteorology, Hamburg

* Hagemann, S., M. Botzet, L. Dümenil and B. Machenhauer, 1999

Derivation of global GCM boundary conditions from 1 km land use satellite data

MPI Report No. 289, Max Planck Institute for Meteorology, Hamburg


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As the U.S. Geological Survey has recently (about 2001) made an updated version of their ecosystem dataset available, these changes were incorporated in the LSP dataset. During this implementation, several improvements were made to the LSP dataset, which is now refered to as LSP2 dataset (Hagemann, 2002). Over Africa, the background surface albedo of bare soil was corrected with METEOSAT albedo data. In addition, the seasonal variation of vegetation characteristics was considered and monthly mean fields of vegetation ratio, leaf area index and background albedo were developed and implemented. Fig. 5 and Fig. 6 show the LSP2 fields of vegetation ratio for the growing (maximum) and dormancy (minimum) season, respectively, at 0.5 degree resolution. Both figures illustrate large seasonal variations in this parameter, ranging in many places up to 50-70%. Similar large variations are found in the leaf area index. In previous simulations with the MPI climate models (ECHAM, HIRHAM, REMO) mean annual values of both of these parameters have been used all year round. The inclusion of a seasonal cycle in these models has improved the simulation of the hydrological cycle and the 2 m temperature in several places.





The new global distributions of background surface albedo and soil field capacity are shown in Fig. 1 and Fig. 2 at 0.5 degree resolution. Also at T42 resolution (~2.8 degree) there are considerable differences between the new land surface data and the old data constructed by Claussen et al. (1994) that are currently used in the MPI climate models. These differences are shown for the background surface albedo Fig. 3 and soil field capacity Fig. 4.

At a resolution of 1 km a global distribution of major ecosystem types (according to Olson, 1994) was recently made available by the U.S. Geological Survey. It was derived from International Geosphere Biosphere Programme 1 km AVHRR data. From this global distribution a global dataset of land surface parameters (LSP dataset) is constructed by allocating parameters to each ecosystem type. These parameters are: background surface albedo, surface roughness length due to vegetation, fractional vegetation cover and leaf area index for the growing and dormancy season, forest ratio, plant-available soil water holding capacity, and volumetric wilting point. This global dataset is provided for the use in global and regional climate modelling.


The coupling between atmosphere and biosphere is of particular importance over land surfaces from both the atmospheric and hydrological point of view. For an adequate modelling of processes at the land surface boundary to the atmosphere an accurate representation of the land surface is necessary. The description of the present land surface is a significant problem in global and regional climate modelling. The available datasets are particularly inaccurate in some regions of the world and up to now their spatial resolution was too coarse to fit the demands of high resolution limited area models. Remote sensing is a relatively new technique to measure present land surface characteristics with a very fine spatial resolution which offers the possibility to create new datasets of land surface parameters.


Derivation of Global GCM Boundary Conditions from 1 km Land Use Satellite Data

by Stefan Hagemann, Michael Botzet, Lydia Dümenil and Bennert Machenhauer