High-Resolution Dynamic Downscaling of CMIP5 Model Data to Assess the Effects of Climate Change on Renewable Energy Distribution in New York State: Project Overview and Preliminary Results

Renewable energy (onshore and offshore wind, utility-scale and distributed solar generation, and hydropower) is supplying a rapidly increasing share of electricity to New York State’s (NYS) power grid. However, little is known about the potential effects of climate change on the spatial and temporal distribution of renewables in NYS. With support from the NYS Energy Research and Development Authority, a public-private research partnership is conducting a comprehensive study of climate change and its potential effects on the state’s renewable energy resources, and how this will inform NYS’s Energy Plan and Reforming the Energy Vision programs.

We use the Weather Research and Forecasting WRF model (version 3.9.1) system to dynamically downscale climate projections from three models in the CMIP5 ensemble for two different climate change scenarios, RCP 4.5 and RCP 8.5, and for a near-future (2017 - 2036) and mid-future (2037 - 2056) climate. These future scenarios will be compared to historical climate (1998-2017) simulations forced by both the 20^thcentury runs of the CMIP5 models and a simulation forced by the ERA-Interim reanalysis. WRF is run at 6 km resolution, to capture terrain and land-lake and land-sea contrasts, translating the larger scale impacts of climate change on weather patterns and providing insight into how future climate change may influence NYS’s weather regimes. Changes in mesoscale features (such as sea and lake breezes) may have strong impacts on wind and solar energy generation in the next 40 years, as many of NYS’s existing and planned installations are sited based upon the current climate (i.e., the last 20 years) of these weather regimes.

We focus on how hub height wind speed, cloud fraction and distribution, surface irradiance, precipitation and stream flow, may change under the two RCP scenarios and directly calculate the resulting impact on wind, solar and hydropower generation, using empirically validated power curves. Here, we present an overview of preliminary project results including state-wide quantitative future estimates of power production and uncertainty constraints, and qualitative information as to the potential temporal and spatial redistribution of wind, solar, and hydropower resources developed from the downscaling exercises.