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Webinar: Using Pressure Change to Stochastically Disaggregate Hourly Precipitation Series from Temperature Projections of Climate Change in The Northeast of The US

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Tuesday, 04 February 2020, 12:00

Tuesday, February 4, 2020. 12:00PM. Webinar: Using Pressure Change to Stochastically Disaggregate Hourly Precipitation Series from Temperature Projections of Climate Change in The Northeast of The US. Ziwen Yu, University of Florida. Sponsored by Consortium for Climate Risk in the Urban Northeast. More information here

 

Stochastic precipitation generators (SPGs) can be used to produce synthetic precipitation series for numerous applications including irrigation system, reservoir, and drainage infrastructure planning and design. Typically, the stochastic processes built into these generators assume a stationary climate. To incorporate non-stationarity in the generation process, this study presents an hourly precipitation generation algorithm conditioned on average monthly temperature (AMT) projected by Global Climate Models (GCMs). The physical basis for precipitation formation is considered explicitly in the design of the algorithm using Pressure Change Events (PCE), the characteristics of which depict the relationship between hourly climate characteristics and AMT. The algorithm consists of a multi-variable Markov Chain and moving window conditioned on time, temperature, and pressure change. The synthetic results, when compared with historical observations in the northeast US, suggest that future precipitation in this region will have greater scatter with more frequent mild events and fewer but intensified extremes especially in warm seasons. Summers are predicted to have less precipitation while winters will be wetter. These predictions generally agree with current research on climate change projections in the northeast US.

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