Climate change and uncertainty assessment over a hydroclimatic transect of Michigan

Abstract

Predictions of a warmer climate over the Great Lakes region due to global change generally agree on the magnitude of temperature changes, but precipitation projections exhibit dependence on which General Circulation Models and emission scenarios are chosen. To minimize model-and scenario-specific biases, we combined information provided by the 3rd phase of the Coupled Model Intercomparison Project database. Specifically, the results of 12 GCMs for three emission scenarios B1, A1B, and A2 were analyzed for mid-(2046-2065) and end-century (2081-2100) intervals, for six locations of a hydroclimatic transect of Michigan. As a result of Bayesian Weighted Averaging, total annual precipitation averaged over all locations and the three emission scenarios increases by 7 % (mid-)-10 % (end-century), as compared to the control period . The projected changes across seasons are non-uniform and precipitation decreases by 3 % (mid-)-5 % (end-) for the months of August and September are likely. Further, average temperature is very likely to increase by 2.02-2.85°C by the mid-century and 2.58-4.73°C by the end-century. Three types of nonadditive uncertainty sources due to climate models, anthropogenic forcings, and climate internal variability are addressed. When compared to the emission uncertainty, the relative magnitudes of the uncertainty types for climate model ensemble and internal variability are 149 and 225 % for mean monthly precipitation, and they are respectively 127 and 123 % for mean monthly temperature. A decreasing trend of the frost days and an increasing trend of the growing season length are identified. Also, a significant increase in the magnitude and frequency of heavy rainfall events is projected, with relatively more pronounced changes for heavy hourly rainfall as compared to daily events. Quantifying the inherent natural uncertainty and projecting hourly-based extremes, the study results deliver useful information for water resource stakeholders interested in impacts of climate change on hydro-morphological processes.

Projected changes in future climate over the Midwest and Great Lakes region using downscaled CMIP5 ensembles

“…Several previous studies based on downscaled GCMs climate data have shown that climate change will bring many detrimental effects on ecosystems, water resources, and socio-economic systems in the Midwest and Great Lakes region by increasing heat stress and amplifying risks of more intense extreme events such as floods and droughts (Lofgren et al, 2002;Kling et al, 2003;Hayhoe et al, 2010;Winkler et al, 2012;Pryor et al, 2014;Notaro et al, 2015;Kim et al, 2016). Specifically, these studies have several results in common by projecting increasing air and water temperature, wetter winters and drier summers, increasing magnitude of extreme precipitation, and decreasing water levels of the Great Lakes in the future.…”

Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin

“…Examples of using weather generators to bridge the spatial gap between GCMs and hydrological impacts are widespread (e.g. Wilks, 1992;Katz, 1996;Semenov and Barrow, 1997;Fowler et al, 2000Fowler et al, , 2005Elshamy et al, 2006;Hewitson and Crane, 2006;Kilsby et al, 2007;te Linde et al, 2010;Fatichi et al, 2011;Lu et al, 2015;Kim et al, 2015).…”

Soil erosion assessment—Mind the gap

“…While, a priori, this can be true for a range of other environmental settings, subsequent research should address the relative importance of all relevant sources of geomorphic internal variability. As is the case for uncertainty partition in other environmental sciences, the contributing components may result in nonadditive behavior [e.g., Kim et al ., ; Fatichi et al ., ], implying that only relative (i.e., with respect to each other) importance can be estimated. Nevertheless, such a step is necessary to decipher the role of individual factors that determine the internal variability.…”