Abstract
The monthly mean precipitation-air temperature (MMP-MMAT) relation over the United States has been examined by analyzing the observed MMP and MMAT during the period of 1931–87. The authors’ main purpose is to examine the possibility of using MMP as a second predictor in addition to the MMAT itself in predicting the next month's MMAT and to shed light on the physical relationship between MMP and MMAT. Both station and climate division data are used.
It was found that the lagged MMP-MMAT correlation with MMP leading by a month is generally negative, with the strongest negative correlation in summer and in the interior United States continent. Over large areas of the interior United States in summer, predictions of MMAT based on either antecedent MMP alone or on a combination of antecedent MMP and MMAT are better than a Prediction scheme based on MMAT alone. On the whole, even in the interior United States though, including MMP as a second predictor does not improve the skill of MMAT forecasts on either dependent or independent data dramatically because the first predictor (temperature persistence) has accounted for most of the MMP's predictive variance. For a verification performed separately for antecedent wet and dry months, much larger skill was found following wet than dry Julys for both one- and two-predictor schemes. Upon further analysis, we attribute this to the differences in the climate between the dependent (1931–60) and independent (1961–87) periods (the second being considerably colder in August) rather than to a true wetness dependence in the predictability.
We found some evidence for the role of soil moisture in explaining negative MMP-MMAT and positive MMAT-MMAT lagged correlations both from observed data and from output of multiyear runs with the National Meteorological Center model. This suggests that we should use some direct measure of soil moisture to improve MMAT forecasts instead of using the MMP as a proxy.
