uri,href,identifier,attrs.Abstract,"attrs.Accession Number","attrs.Alternate Journal",attrs.Author,"attrs.Author Address",attrs.DOI,attrs.ISSN,attrs.Journal,attrs.Keywords,attrs.Language,attrs.Notes,attrs.Pages,attrs.Title,attrs.Volume,attrs.Year,attrs.\.reference_type,attrs._chapter,attrs._record_number,attrs._uuid,attrs.reftype,child_publication
/reference/b00a1349-fb5f-4e2d-b1bc-cfceb0863de2,https://data.globalchange.gov/reference/b00a1349-fb5f-4e2d-b1bc-cfceb0863de2,b00a1349-fb5f-4e2d-b1bc-cfceb0863de2,"Heat is an environmental and occupational hazard. The prevention of deaths in the community caused by extreme high temperatures (heat waves) is now an issue of public health concern. The risk of heat-related mortality increases with natural aging, but persons with particular social and/or physical vulnerability are also at risk. lmportant differences in vulnerability exist between populations, depending on climate, culture, infrastructure (housing), and other factors. Public health measures include health promotion and heat wave warning systems, but the effectiveness of acute measures in response to heat waves has not yet been formally evaluated. Climate change will increase the frequency and the intensity of heat waves, and a range of measures, including improvements to housing, management of chronic diseases, and institutional care of the elderly and the vulnerable, will need to be developed to reduce health impacts.",ISI:000255349400007,"Annu Rev Publ Health","Kovats, R. S.
Hajat, S.","Kovats, RS; London Sch Hyg & Trop Med, PEHRU, London WC1E 7HT, England; London Sch Hyg & Trop Med, PEHRU, London WC1E 7HT, England; London Sch Hyg & Trop Med, PEHRU, London WC1E 7HT, England",10.1146/annurev.publhealth.29.020907.090843,0163-7525,"Annual Review of Public Health","heat waves; early warning; mortality; august 2003; air-pollution; hospital admissions; united-states; excess mortality; elderly-people; french cities; risk-factors; hot weather; series data",English,"293QI; Times Cited:67; Cited References Count:100; Annual Review of Public Health",41-55,"Heat stress and public health: A critical review",29,2008,0,"[""Ch. 9: Human Health FINAL"",""Ch. 17: Southeast and Caribbean FINAL""]",831,b00a1349-fb5f-4e2d-b1bc-cfceb0863de2,"Journal Article",/article/10.1146/annurev.publhealth.29.020907.090843
/reference/dac369a3-921e-426f-b4a2-5798dfb9c515,https://data.globalchange.gov/reference/dac369a3-921e-426f-b4a2-5798dfb9c515,dac369a3-921e-426f-b4a2-5798dfb9c515,,,,"Palecki, M.A.
Changnon, S.A.
Kunkel, K.E.",,10.1175/1520-0477(2001)082<1353:TNAIOT>2.3.CO;2,,"Bulletin of the American Meteorological Society",,,,1353-1368,"The nature and impacts of the July 1999 heat wave in the midwestern United States: Learning from the lessons of 1995",82,2001,0,"[""Ch. 18: Midwest FINAL""]",2405,dac369a3-921e-426f-b4a2-5798dfb9c515,"Journal Article",/article/10.1175/1520-0477(2001)082%3C1353:TNAIOT%3E2.3.CO;2
/reference/dd5b893d-4462-4bb3-9205-67b532919566,https://data.globalchange.gov/reference/dd5b893d-4462-4bb3-9205-67b532919566,dd5b893d-4462-4bb3-9205-67b532919566,,,,,,10.7930/J0Z31WJ2,,,,,,,"Climate Change Impacts in the United States: The Third National Climate Assessment",,2014,9,"[""Ch. 0: About this Report FINAL""]",4692,dd5b893d-4462-4bb3-9205-67b532919566,"Edited Book",/report/nca3
/reference/e3139f21-797c-4d60-8099-6efe715f64bc,https://data.globalchange.gov/reference/e3139f21-797c-4d60-8099-6efe715f64bc,e3139f21-797c-4d60-8099-6efe715f64bc,,,,"Wisconsin Climate and Health Program,",,,,,,,,2,"Understanding the link between climate and health",,2015,10,,26622,e3139f21-797c-4d60-8099-6efe715f64bc,Report,/report/understanding-link-between-climate-health
/reference/e518fff1-caa5-4ed1-8fdc-b512da7cbe3b,https://data.globalchange.gov/reference/e518fff1-caa5-4ed1-8fdc-b512da7cbe3b,e518fff1-caa5-4ed1-8fdc-b512da7cbe3b,"The disease burden due to heat-stress illness (HSI), which can result in significant morbidity and mortality, is expected to increase as the climate continues to warm. In the United States (U.S.) much of what is known about HSI epidemiology is from analyses of urban heat waves. There is limited research addressing whether HSI hospitalization risk varies between urban and rural areas, nor is much known about additional diagnoses of patients hospitalized for HSI.",,,"Jagai, Jyotsna S.; Grossman, Elena; Navon, Livia; Sambanis, Apostolis; Dorevitch, Samuel",,10.1186/s12940-017-0245-1,1476-069X,"Environmental Health",,,,38,"Hospitalizations for heat-stress illness varies between rural and urban areas: An analysis of Illinois data, 1987–2014",16,2017,,,21209,e518fff1-caa5-4ed1-8fdc-b512da7cbe3b,"Journal Article",/article/10.1186/s12940-017-0245-1
/reference/e8089a19-413e-4bc5-8c4a-7610399e268c,https://data.globalchange.gov/reference/e8089a19-413e-4bc5-8c4a-7610399e268c,e8089a19-413e-4bc5-8c4a-7610399e268c,,,,"Easterling, D.R.; J.R. Arnold; T. Knutson; K.E. Kunkel; A.N. LeGrande; L.R. Leung; R.S. Vose; D.E. Waliser; M.F. Wehner",,10.7930/J0H993CC,,,,,,207-230,"Precipitation Change in the United States",,2017,7,,21565,e8089a19-413e-4bc5-8c4a-7610399e268c,"Book Section",/report/climate-science-special-report/chapter/precipitation-change
/reference/ee7f8311-bd00-4353-87a9-61ffb7813bf0,https://data.globalchange.gov/reference/ee7f8311-bd00-4353-87a9-61ffb7813bf0,ee7f8311-bd00-4353-87a9-61ffb7813bf0,"Downscaled climate data are available at fine spatial scales making them desirable to local climate change practitioners. However, without a description of their uncertainty, practitioners cannot know if they provide quality information. We pose that part of the foundation for the description of uncertainty is an assessment of the ability of the underlying climate model to represent the meteorological or weather-scale processes. Here, we demonstrate an assessment of precipitation processes for the Great Lakes region using the Bias Corrected and Spatially Downscaled (BCSD) Coupled Model Intercomparison Project phase 3 (CMIP3) projections. A major weakness of the underlying models is their inability to simulate the effects of the Great Lakes, which is an important issue for most global climate models. There is also uncertainty among the models in the timing of transition between dominant precipitation processes going from the warm to cool season and vice versa. In addition, warm-season convective precipitation processes very greatly among the models. From the assessment, we discuss how process-based uncertainties in the models are inherited by the downscaled projections and how bias correction increases uncertainty in cases where precipitation processes are not well represented. Implications of these findings are presented for three regional examples: lake-effect snow, the spring seasonal transition, and summertime lake-effect precipitation.",,,"Briley, Laura J.; Ashley, Walker S.; Rood, Richard B.; Krmenec, Andrew",,10.1007/s00704-015-1652-2,1434-4483,"Theoretical and Applied Climatology",,,,643-654,"The role of meteorological processes in the description of uncertainty for climate change decision-making",127,2017,,,21113,ee7f8311-bd00-4353-87a9-61ffb7813bf0,"Journal Article",/article/10.1007/s00704-015-1652-2
/reference/f1e633d5-070a-4a7d-935b-a2281a0c9cb6,https://data.globalchange.gov/reference/f1e633d5-070a-4a7d-935b-a2281a0c9cb6,f1e633d5-070a-4a7d-935b-a2281a0c9cb6,,,,USGCRP,,10.7930/J0R49NQX,,,,,,,"The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment",,2016,9,,19368,f1e633d5-070a-4a7d-935b-a2281a0c9cb6,Book,/report/usgcrp-climate-human-health-assessment-2016
/reference/fe83e7d3-3f29-4aef-81ae-28abd70dda2e,https://data.globalchange.gov/reference/fe83e7d3-3f29-4aef-81ae-28abd70dda2e,fe83e7d3-3f29-4aef-81ae-28abd70dda2e,,,,"Vavrus, Stephen J.; Notaro, Michael; Lorenz, David J.",,10.1016/j.wace.2015.10.005,2212-0947,"Weather and Climate Extremes","Climate Model; Uncertainty; CMIP; Downscaled; Extremes",,,10-28,"Interpreting climate model projections of extreme weather events",10,2015,,,21149,fe83e7d3-3f29-4aef-81ae-28abd70dda2e,"Journal Article",/article/10.1016/j.wace.2015.10.005