Disaggregation Modeling Process for Climatic Time Series

Abstract

To assess the potential effects of climatic changes on water resources, it is important to incorporate predictions of future climatic trends into hydrologic planning models. Disaggregation models can be used to produce a time series at one resolution from a parent series at a different scale. In this study, a disaggregation approach is used to generate a time series simulating surface air temperature and precipitation. An annual series is generated using a 70-year record from Sacramento, California, and each year is disaggregated into 24 seasonal values. The output series from this modeling process are compared with the historical record. It is found that the statistical and correlation characteristics of the historical series are well maintained. The synthetic and historical series are applied to a reservoir-sizing model, and optimal reservoir sizes are found to be statistically similar. The results indicate the potential usefulness of this technique for generating synthetic temperature and precipitation to use in hydrologic planning based on future climate scenarios.