Projected Precipitation Changes within the Great Lakes Region: A Multi-scale Analysis of Precipitation Intensity and Seasonality

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Wednesday, 7 January 2015
Samantha Basile, University of Michigan, Ann Arbor, MI; and A. Steiner, D. Brown, and A. Bryan

The Great Lakes region supports a diverse network of agriculture, transportation and tourism centered on some of the largest freshwater bodies of water in the world. Precipitation affects these sectors as concerns about precipitation timing and intensity can affect the agricultural growing season, runoff, and subsequent water quality. As part of work with the Great Lakes Integrated Sciences and Assessments Center (GLISA) and a NOAA Coastal and Ocean Climate Applications (COCA) project (Enhancing Manager and Stakeholder Awareness of and Responses to Changing Climatic Conditions and their impacts on Lake Erie) we are engaging with community stakeholders to communicate and interpret precipitation data that may influence decisions concerning bottom water hypoxia, harmful algal blooms (HABs), and water resources within the Great Lakes region. Here, we examine precipitation projections for mid-century (2041 to 2065) within the Great Lakes basin (GLB) and two sub-regions using three climate model ensembles of varying resolutions to constrain and compare associated precipitation uncertainties. These include: 1. atmosphere-ocean models from the CMIP5 global simulations with the RCP 8.5 scenario (12 members, resolution ranging from ~1 to ~3 degrees), 2. dynamically downscaled regional climate models from NARCCAP with the SRES A2 scenario (4 members at ~0.5 degree resolution (50 km)), and 3. high resolution (~0.25 degree resolution (25 km)) regional climate model simulations with the RCP 8.5 scenario (RegCM (hereafter RCM3(HiRes)), 2 members). For the entire GLB, all three ensembles captured the intensity of historical events well, but with a bias in the high intensity precipitation events as compared to observed intensity, with fewer overprediction events by the NARCCAP and RCM3(HiRes) ensembles. Daily probability density functions from three model ensembles reveal consistent increases in high precipitation event probabilities for all seasons, even after accounting for wet model biases during the observation period (1980 to 1999). Comparing all three ensembles to the historical period for the GLB, both CMIP5 and NARCCAP ensembles capture the annual seasonal cycle with a wet bias in the winter and spring, while the RCM3(HiRes) ensemble shows a dry bias for all seasons except winter. For the Lake Michigan and Western Lake Erie basin sub-regions, the spring and winter biases remain present across ensembles, however the RCM3(HiRes) summer dry bias is reduced. Overall, the three climate model ensembles show consensus for an increase in precipitation intensity as well as increased seasonal spring and winter precipitation across the GLB.