Recent research in land-atmosphere interactions indicates that the selection of a SVATS for GCMs is not straightforward. There are many available options, which often generate very different results. It is not clear if a single scheme is appropriate for all the land types that need to be simulated in a GCM, and which scheme is the best for the different situations. The PILPS, which is currently under progress, is expected to shed light on this issue.
Spatial variability of land surface affects the dynamics of the atmosphere at different scales. In particular, mesoscale fluxes associated with mesoscale circulations that develop above landscape discontinuities can have a very significant impact on subgrid-scale fluxes, clouds, and precipitation. While this impact has been demonstrated during the recent year, the task of developing appropriate parameterizations for GCMs mostly remains. Yet it is interesting to note that given a macroscale atmospheric background environment, a characteristic length scale of the land-surface heterogeneity, and the distribution of surface heat fluxes, it was possible to develop a primary parameterization. Because a statistical approach is adopted to develop such a parameterization, it might be possible to obtain the higher statistical moments of the product of this parameterization (e.g., mesoscale fluxes, clouds, and precipitation). For instance, the distribution of precipitation as characterized by its mean, its standard deviation, and maybe its skewness and kurtosis, is likely to be helpfull to define the landscape patchiness.
Based on this assumption, one can infer that an important challenge for hydrologists would be to develop a scheme that would be able to provide the characteristic length scale of the land-surface patchiness and the distribution of surface heat fluxes. Since in order to obtain the distribution of surface heat fluxes, this patchiness must reflect the time variation of the spatial variability of the important land characteristics, an appropriate hydrologic scheme would probably require high-resolution data sets of topography (which has been shown to affect the redistribution of water in the ground, the surface roughness, the radiation balance, and the turbulent heat fluxes in the PBL), soil texture, and vegetation type. Clearly, the organization of such data sets at the global scale represents by itself a big challenge.
Finally, it is also important to emphasize that hydrologists, atmospheric scientists, and ecologists involved in the development of parameterizations of land-atmosphere interactions for GCMs are faced with the challenge of collecting appropriate observational data sets, which could be used for the development and the evaluation of these parameterizations. While field experiments at the microscale, which often involve complex technology and management expertise, are realizable, it is not realistic to assume that the tremendous amount of equipment and human resources needed to carry out a high-resolution field experiment at the macroscale will be available in the foreseeable future. Therefore, the development of new parameterizations will need to rely heavily on numerical and other theoretical analyses, which should provide guidance for the planning of more focused field experiments, dedicated to observe only selected important parameterized processes.
Acknowledgments This report was partly funded by the U. S. Department of Energy under Grant DE-FG02-92ER61453, and by the National Oceanic and Atmospheric Administration under Grant NA36GP0257. The views expressed herein are those of the author and do not necessarily reflect the views of these agencies.