The Climate Prediction Center issues each month a set of operational monthly and seasonal predictions for the United States. Obviously we are concerned about using all the information we could have, so as to maximize whatever little skill there is. Acting on long-held believes by Namias and other practioners with regards to the state of the soil and summer climate prediction, the CPC and its forerunner CAC, in the early 1990's, embarked on a program to quantify the impact of anomalous soil moisture conditions on subsequent monthly and seasonal atmospheric conditions. In the ancient past this had been done only qualitatively as part of the subjective input to the monthly/seasonal forecast, or, at best, via linear correlations between antecedent precipitation and next month's temperature, thus only hinting at a role for the lower boundary, primarily in summer. In order to be quantitative we had to produce a multi-decade integration of a soil moisture model - after all ‘climate' work requires long data sets. (See a companion paper in LDAS session). The first such model, a ‘leaky' hydrologist's bucket, was described in Huang et al(1996). This information has been used since that time. The resulting calculated soil moisture is, indeed, a much better local predictor than antecedent precipitation for subsequent temperature. We will review the forecast tools that use soil moisture as an initial state, with emphasis on non-local versus local impacts. The non-local aspects, such as enhanced precipitation downstream of a positive soil moisture anomaly, are our main hope for improved meaningful forecasts. We will also discuss skill of such tools vis-a-vis other available tools. Secular changes in soil moisture appear to become more important also need to be discussed.