A collaborative stochastic weather generator for climate impacts assessment in the Lower Santa Cruz River Basin, Arizona

Stochastic weather generators provide opportunities to simulate weather conditional on a multitude of variables and form a robust approach to climate projections in impacts assessments studies. Though weather generators have been prominent in the literature and have demonstrated varied applications including climate impacts assessments, they don't appear to be a dominant approach that is regularly used in climate impacts assessments. Why? A likely reason is the disconnect between weather generators as a tool and stakeholder understanding as users of the information being developed from the weather generators. This presentation will focus on the collaborative process to develop a weather generator to meet the specific needs of stakeholders in a climate impacts study on the Lower Santa Cruz River Basin in Arizona.

The weather generator is designed to understand changes in seasonal properties including: (1) spell characteristics of the pre-monsoon dry season; (2) length of the monsoon season; (3) precipitation amounts during the monsoon season; (4) precipitation amounts over the winter wet period; and (5) annual temperature variability. These hydroclimate metrics of interest were developed in collaboration with the study stakeholders and the weather generator was developed to address impacts based on these metrics under two future climate scenarios. Mathematically, the developed weather generator uses a non-parametric resampling algorithm based on Markov state transition for precipitation in a three-state system characteristic of southeastern Arizona and consisting of, (i) pre-monsoon dry, (ii) monsoon, and (iii) winter wet seasons. Temperature distribution was modeled parametrically and includes temperature seasonality modulation coupled with precipitation occurrence. The resulting weather generator uses a broad approach and is a standalone tool that can be adopted in other applications of climate change impacts using stakeholder defined hydroclimate metrics.