Climate Projection Data for 21st century for the Western Lake Erie Basin (Indiana, Ohio, and Michigan)

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By Sushant Mehan1, Margaret Gitau1

Purdue University

Climate data from ground-based climate stations obtained from National Climate Data Center and bias corrected climate values from different climate models for different emission scenarios for the entire Western Lake Erie Basin.

Version 1.0 - published on 01 Jan 2019 doi:10.4231/R7GX48SF - cite this Archived on 12 Aug 2018

Licensed under CC0 1.0 Universal



Lake Erie is the shallowest of the five great lakes in the United States. Water from Lake Erie supports living, recreation, and navigation for people living in surrounding regions and adds a lot to the U.S. Economy. With change in climatic conditions, there is a danger that the thick layer of algae proliferating on the surface of Lake Erie will continue to grow, if the cause of the problem is not controlled under the changing climate. Since climate regulates all the hydrologic processes, specifically movement of nutrients which cause algae to bloom, reliable future climate information is needed at finer resolution to study the impact of changing climate on water resources in Lake Erie.

Climate data for sixteen different climate stations in Western Lake Erie Basin (WLEB) was generated as a part of the dissertation by Sushant Mehan, Ph.D. Candidate in the Purdue University Department of Agricultural and Biological Engineering, under the guidance of Dr. Margaret W. Gitau. All related datasets for this dissertation may be accessed here:

The reliable climate future projections were developed for precipitation and temperature (maximum and minimum) from nine different climate models for sixteen-point stations using historic climate data from 1966-2015 obtained from National Climate Data Center (NCDC). The projections are corrected for their bias from 2006-2099.

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This dataset was prepared after testing specific bias correction techniques, including power transformation of precipitation, variance scaling of temperature, and stochastic weather generators, including CLIGEN and LARS-WG. This is the best corrected data achieved using the different methods tested in Mehan et al., (2018). The users can evaluate other methods of bias correction. Everyone is allowed to copy, modify, distribute, and perform the work using the dataset. The authors make no warranties and are not liable for any errors arising out of or in connection to access or use of the dataset and associated materials.

Mehan, S., Gitau, M. W., and Flanagan, D. C.: Development of reliable future climatic projections to assess hydro-meteorological implications in the Western Lake Erie Basin, Hydrol. Earth Syst. Sci. Discuss.,, in review, 2018.

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