Reliable Future Climatic Projections for Sustainable Hydro-Meteorological Assessments in the Western Lake Erie Basin

Abstract

Modeling efforts to simulate hydrologic processes under different climate conditions rely on accurate input data. Among other inaccuracies, errors in climate projections can lead to incorrect decisions. This study aimed to develop a reliable climate (precipitation and temperature) database for the Western Lake Erie Basin for the 21st century. Two statistically downscaled bias-corrected sources of climate projections (GDO: Global Downscaled Climate and Hydrology Projections and MACA: Multivariate Adaptive Constructed Analogs) were tested for their effectiveness in simulating historic climate (1966–2005) using ground-based station data from the National Climatic Data Center. MACA was found to have less bias than GDO and was better at simulating selected climate indices; thus, its climate projections were subsequently tested with different bias correction methods including the power transformation method, variance scaling of temperature, and Stochastic Weather Generators. The power transformation method outperformed the other methods and was used in bias corrections for 2006 to 2099. From the analysis, mean daily precipitation values were expected to remain more or less the same under both RCP (Representative Concentration Pathway) 4.5 and RCP 8.5 scenarios, ranging between 2.4 mm and 3.2 mm, while standard deviations were expected to increase, pointing to a rescaling of the distribution. Maximum one-day precipitation was expected to increase and could vary between 120 and 650 mm across the basin, while the number of wet days could potentially increase under the effects of RCP 4.5 and RCP 8.5. Both mean maximum and mean minimum daily air temperatures were expected to increase by up to 5.0 °C across the basin, while absolute maximum and minimum values could increase by more than 10 °C. The number of days in which precipitation could potentially fall as snow was expected to decrease, as was the annual number of days for optimal corn growth, although an earlier start to the growing season could be expected. Results from this study were very useful in creating a reliable climate database for the entire Western Lake Erie Basin (WLEB), which can be used for hydrologic, water resources, and other applications in the basin. The resulting climate database is published and accessible through the Purdue University Research Repository (Mehan et al., 2019), which is an open-access repository.