This is a pilot research project to evaluate the natural variability of monthly precipitation and use these estimates to 1) evaluate General Circulation Model (GCM) simulations of present-day precipitation variability and 2) determine whether and where GCM-forecasts of terrestrial precipitation changes under doubled Carbon Dioxide scenarios will be first detected. This assessment will be obtained by compiling a pilot data base of monthly precipitation totals from terrestrial stations and removing "gage-induced" biases (including the effect of the wind, wetting on the interior walls of the gage, and evaporation form the gage) by an empirically-based method. As surface air temperature, wind speed, and humidity are required to facilitate the gage corrections, the database also will contain observations of these climatological variables. Missing observations of both air temperature and wind speed will be interpolated both spatially and temporally. Digital filtering procedures then will be used to obtain areally-averaged estimates of precipitation that are compatible with the GCM resolutions. The natural variability in monthly precipitation will be computed and used to calculate signal-to-noise and compared with a number of general circulation models. These results then will be used to determine where (if anywhere) Carbon Dioxide-induced changes in precipitation will be detectable and consequently, important.
