Pattern Scaling for Developing Change Scenarios in Water Supply Studies

Friday, 19 December 2014
Aavudai Anandhi, Kansas State University, Agronomy, Manhattan, KS, United States, Doanald Pierson, Water Quality Modeling Group, New York City Department of Environmental Protection, Kingston, NY, United States and Allan Frie, CUNY Hunter College, Geography, New York, NY, United States
Change factor methodology (CFM), or delta change factor methodology, is a type of pattern scaling. Although a variety of methods are available to develop scenarios, CFMs are widely used for their ease and speed of application and their capability to directly scale local data according to changes suggested by the global climate model (GCM) scenarios. Change factors (CFs) can be calculated and used in a number of ways to estimate future climate scenarios, but no clear guidelines are available in the literature to decide which methodologies are most suitable for different applications. This study compares and contrasts several categories of CFM (additive versus multiplicative and single versus multiple) for a number of climate variables. The study employs several theoretical examples as well as an applied study from the New York City water supply. Results show that in cases where the frequency distribution of the GCM baseline climate is close to the frequency distribution of the observed climate, or when the frequency distribution of the GCM future climate is close to the frequency distribution of the GCM baseline climate, additive and multiplicative single CFMs provide comparable results. Two options to guide the choice of CFM are suggested: the first is a detailed methodological analysis for choosing the most appropriate CFM, and the second is a default method for circumstances in which a detailed methodological analysis is too cumbersome.