title: Evaluating the Appropriateness of Downscaled Climate Information for Projecting Risks of Salmonella.
abstract: Foodborne diseases have large economic and societal impacts worldwide. To evaluate how the risks of foodborne diseases might change in response to climate change, credible and usable climate information tailored to the specific application question is needed. Global Climate Model (GCM) data generally need to, both, be downscaled to the scales of the application to be usable, and represent, well, the key characteristics that inflict health impacts. This study presents an evaluation of temperature-based heat indices for the Washington D.C. area derived from statistically downscaled GCM simulations for 1971-2000--a necessary step in establishing the credibility of these data. The indices approximate high weekly mean temperatures linked previously to occurrences of Salmonella infections. Due to bias-correction, included in the Asynchronous Regional Regression Model (ARRM) and the Bias Correction Constructed Analogs (BCCA) downscaling methods, the observed 30-year means of the heat indices were reproduced reasonably well. In April and May, however, some of the statistically downscaled data misrepresent the increase in the number of hot days towards the summer months. This study demonstrates the dependence of the outcomes to the selection of downscaled climate data and the potential for misinterpretation of future estimates of Salmonella infections.
authors.affiliation: National Climate Predictions and Projections platform (NCPP), NCAR RAL CSAP, 3450 Mitchell Lane, Boulder, CO 80301, USA. galia.guentchev@gmail.com.
authors.forename: Galina S
authors.initials: GS
authors.lastname: Guentchev
authors.affiliation: Department Atmospheric, Oceanic and Space Sciences, University of Michigan, 525 Space Research Building, Ann Arbor, MI 48109-2143, USA. rbrood@umich.edu.
authors.forename: Richard B
authors.initials: RB
authors.lastname: Rood
authors.affiliation: National Climate Predictions and Projections platform (NCPP), NCAR RAL CSAP, 3450 Mitchell Lane, Boulder, CO 80301, USA. ammann@ucar.edu.
authors.forename: Caspar M
authors.initials: CM
authors.lastname: Ammann
authors.affiliation: CIRES-NOAA/University of Colorado, 325 Broadway, Boulder, CO 80305-3328, USA. joseph.j.barsugli@noaa.gov.
authors.forename: Joseph J
authors.initials: JJ
authors.lastname: Barsugli
authors.affiliation: Department of Global Health, School of Public Health, University of Washington, 1959 NE Pacific Street, Health Sciences Building, Seattle, WA 98195, USA. krisebi@uw.edu.
authors.forename: Kristie
authors.initials: K
authors.lastname: Ebi
authors.affiliation: Department of Biostatistics, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA. berrocal@umich.edu.
authors.forename: Veronica
authors.initials: V
authors.lastname: Berrocal
authors.affiliation: Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA. marieo@umich.edu.
authors.forename: Marie S
authors.initials: MS
authors.lastname: O'Neill
authors.affiliation: Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA. gronlund@umich.edu.
authors.forename: Carina J
authors.initials: CJ
authors.lastname: Gronlund
authors.affiliation: NCAR JNT RAL, 3450 Mitchell Lane, Boulder, CO 80301, USA. jvigh@ucar.edu.
authors.forename: Jonathan L
authors.initials: JL
authors.lastname: Vigh
authors.affiliation: CIRES-NOAA/University of Colorado, 325 Broadway, Boulder, CO 80305-3328, USA. ben.koziol@noaa.gov.
authors.forename: Ben
authors.initials: B
authors.lastname: Koziol
authors.affiliation: NESII-NOAA/ESRL, 325 Broadway, Boulder, CO 80305-3328, USA. luca.cinquini@jpl.nasa.gov.
authors.forename: Luca
authors.initials: L
authors.lastname: Cinquini
mesh_terms: D002980:Climate; D057231:Climate Change; D004784:Environmental Monitoring; D006358:Hot Temperature; D006801:Humans; D008962:Models, Theoretical; D012307:Risk Factors; D012475:Salmonella / Q000302:isolation & purification*; D012480:Salmonella Infections / Q000453:epidemiology*; D012621:Seasons; D014861:Washington / Q000453:epidemiology
keywords: ARRM and BCCA statistical downscaling methods; Salmonella infections; Washington D.C.; evaluation; foodborne disease; temperature-based heat indices