Research Focus:
Statistical Downscaling of Global Climate Models
Research Abstract:
Global climate models (GCMS) are the primary tool used by regional planners to assess future climate impact on agriculture. Downscaling is the process of generating locally relevant data from the GCMS. Outputs from 20 GCMS of the 5th phase of the Coupled Model Intercomparison Project (CMIP5) using two Representative Concentration Pathways (RCP45 and RCP85) have been downscaled for the Contiguous USA for several meteorological variables (tasmin, tasmax, rhsmin, rhsmax, pr, rsds, uas,vas) for 1950-2099 using the Multivariate Adaptive Constructed Analogs (MACA) statistical downscaling method and can be accessed through either the REACCH data portal or the Northwest Knowledge Network (see http://maca.northwestknowledge.net). The original MACA method has been refined for better performance in correcting for biases inherent in climate models. The MACA data has been utilized by both REACCH teams and other organizations over the Pacific Northwest for studying future hydrology, vegetation and agricultural crops.
Biography:
Katherine Hegewisch is a postdoctoral researcher working with Dr. John Abatzoglou in the Department of Geography at the UI. Dr. Hegewisch earned her Ph.D. in Physics from WSU in 2010. Dr. Hegewisch has been working on the statistical downscaling of global climate models (GCMS), the development of tools to visualize the downscaled data and most recently the downscaling of mid term climate forecasts. Her specialized knowledge is in the area of scientific computing and big data.
Publications and Presentations:
Lute, A., Abatzoglou, J., Hegewisch, K. 2015. Projected changes in snowfall extremes and interannual variability of snowfall in the western United States. Water Resources Research. 51(2): 960-972.
Barbero, R., Abatzoglou, J., Kolden, C., Hegewisch, K., Larkin, N. Podschwit, H. 2015. Multi-scalar influence of weather and climate on very large-fires in the Eastern United States. International Journal of Climatology. 35(8): 2180-2186.
Pierce, D., Cayan, D., Maurer, E., Abatzoglou, J., Hegewisch, K. 2015. Improved bias correction techniques for hydrological simulations of climate change. Journal of Hydrometeorology. 16(6): 2421-2442.
Pierce, D., Cayan, D., Maurer, E., Abatzoglou, J., Hegewisch, K. 2015. Improved bias correction techniques for hydrological simulations of climate change. Journal of Hydrometeorology. 16(6): 2421-2442.
Barbero, R., Abatzoglou, J., Kolden, C., Hegewisch, K. Larkin, N., Podschwit, H. 2014. Multi-scalar influence of weather and climate on very large-fires in the Eastern United States. International Journal of Climatology. Published online in Wiley Online Library.
Sheehan, T., Bachelet, D., Ferschweiler, K., Abatzoglou, J., Hegewisch K. Wildfire, Vegetation Change, and Carbon: The Effect of Differenct Projected Climate Futures on Vegetation in the Westnern United States. American Geophysical Union Fall Meeting, Dec. 9-13, 2013, San Francisco, CA.
Rupp, D., Abatzoglou, J., Hegewisch, K., Mote, P. 2013. Evaluation of CIMP5 20th century climate simulations for the Pacific Northwest USA. Journal of Geophysical Research. 118(19): 10,884-10,906.