The Relationship of Soil Moisture Parameterizations to Subsequent Seasonal and Monthly Mean Temperature in the United States

Abstract

The water content parameter and the moisture anomaly index, both derived from the Palmer Drought Severity model, were correlated against subsequent mean monthly and seasonal (three-month means) temperatures for 344 climatic divisions in the United States (1931?83). During spring and summer, Monte Carlo field significance tests demonstrate that the correlation fields produced from the soil moisture parameters are significantly larger than those derived using persistence of monthly and seasonal temperature anomalies. The areas of the United States with enhanced soil moisture parameterization?temperature correlations tend to be confined to the interior. The average reduction of the standard error of estimate (root-mean-square error) is 0.15°C for seasonal forecasts made at the end of April and May over inland, nonarid climate divisions. The reduction of the standard error is less for monthly forecasts (?0.05°C) during the April through July forecast time periods. The areas with the greatest reduction in error favor the southern portions of the United States during early spring, but in late spring and summer they are also found in the central and northern states. The empirical relationships found between soil moisture parameters and subsequent monthly and seasonal temperature suggest that soil moisture is important on a local scale, not only in a diagnostic mode, but also in a prognostic sense. Since the spring and early summer are times when the persistence of temperature anomalies is not very effective as a prediction tool, the existence of a demonstrable increase in predictability of monthly and seasonal temperatures using soil moisture indices, easily calculated on an operational basis, suggests that another objective long-range forecast aid is available for immediate use. Further increases of the correlations of soil moisture with subsequent monthly and seasonal mean temperature may come from improvements in the water balance computations which are part of the Palmer model, i.e., estimation of evapotranspiration, the treatment of runoff, the inclusion of snow cover, the inclusion of irrigation estimates, or from other models, or preferably from a network of soil moisture measurements. With respect to the Palmer water budget evapotranspiration calculations, sensitivity studies of the soil moisture parameterizations were performed using a fixed annual cycle of evapotranspiration?no year-to-year variations of the annual cycle. Statistically significant, but not drastic, degradations of the correlations of parameterized soil moisture with subsequent seasonal and monthly mean temperature were noted. The largest increase of forecast error occurred during the seasonal forecast period. This suggests that improved estimates of evapotranspiration in the water balance equation may be especially important for long (seasonal) forecasting periods during late spring and summer, but dramatic improvements in forecast skill may be difficult to achieve.