The importance of the soc sci's has been much exaggerated. The soc sci'ts are particularly bad at prediction, & so at helping us to forestall the SP crises that occur more & more often. The rate of soc change has gone up very sharply for a number of reasons, so surprises are more frequent. This rate should ae reduced, at least in rich countries, which face far more unknown situations. Poor countries, on the other hand, mainly face situations known from those slightly more advanced. What poor countries mostly need, therefore, is better information, of old kind, not new kinds of information. Crisis-anticipating information will mostly be valueless, since no one knows how to winnow it. It also requires many low-level informers, & the identity of these people is a major problem of pol'al power. So is the identity of the processor & publisher of their data. Substantial improvements in information & its use might abolish democracy. HA.
This research examines the feasibility of using observations of land surface temperatures (in principle available from satellite observations) to initialize soil moisture (which is not available on a continental scale). This problem is important because it is known that wrong soil moisture initial conditions can negatively affect the skill of numerical weather prediction models. Since this problem requires the availability of a good soil model, considerable effort was devoted to the improvement of several aspects of the NCEP Noah landsurface model and its numerical properties (reliability, efficiency, updates and differentiability). When tested against the experimental station data at Champaign, IL collected by Dr. Tilden Meyers of NOAA/ARL, where the surface fluxes, precipitation, and surface temperature were available, the Noah model forced with observed downward radiative surface fluxes and near-surface meteorology, including precipitation, was able to reproduce the observations quite well. A method for data assimilation was developed and tested, in a manner similar to 4-dimensional variational assimilation (4D-Var) in the sense of applying the temporal behavior of the observed variable but with a single spatial dimension (land
We consider an extension of signaling games to the case of prediction, where one agent (‘sender’) perceives the current state of the world and sends a signal. The second agent (‘receiver’) perceives this signal, and makes a prediction about the next state of the world (which evolves according to stochastic but not entirely random ‘laws’). We suggest that such games may be the basis of a model for the evolution of successful theorizing about the world.