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Scales of perception: public awareness of regional and neighborhood climates

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Abstract

Understanding public perceptions of climate is critical for developing an effective strategy to mitigate the effects of human activity on the natural environment and reduce human vulnerability to the impacts of climate change. While recent climate assessments document change among various physical systems (e.g., increased temperature, sea level rise, shrinking glaciers), environmental perceptions are relatively under-researched despite the fact that there is growing skepticism and disconnect between climate science and public opinion. This study utilizes a socio-ecological research framework to investigate how public perceptions compared with environmental conditions in one urban center. Specifically, air temperature during an extreme heat event was examined as one characteristic of environmental conditions by relating simulations from the Weather Research and Forecast (WRF) atmospheric model with self-reported perceptions of regional and neighborhood temperatures from a social survey of Phoenix, AZ (USA) metropolitan area residents. Results indicate that: 1) human exposure to high temperatures varies substantially throughout metropolitan Phoenix; 2) public perceptions of temperature are more strongly correlated with proximate environmental conditions than with distal conditions; and 3) perceptions of temperature are related to social characteristics and situational variables. The social constructionist paradigm explains public perceptions at the regional scale, while experience governs attitude formation at the neighborhood scale.

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Notes

  1. Gallup’s findings on America’s increasing skepticism about climate change were challenged by a Stanford poll that asked slightly different questions and found a solid majority of the public (75%) believes that the earth has been heating up over the last 100 years and human behavior is responsible (Krosnick, Op Ed in the New York Times, June 9, 2010). Editor in Chief of the Gallup Poll, Frank Newport, replied that a variety of other national polls “show demonstrable drops in Americans’ acknowledgement of and concern about global warming” (Newport, Letter to the Editor in the New York Times, June 17, 2010) Surveys conducted by the Yale Project on Climate Communication showed a shift over time toward less concern and more disbelief among the American public that climate change is happening. The percentage of the public who were alarmed or concerned in the 2008 survey was 51%, which slipped to 39% in 2010. Those who were doubtful or dismissive increased from 19% in 2008 to 31% in 2010 (Leiserowitz et al. 2010).

  2. The average size of the Census Block Groups sampled in this study was 0.45 square miles (or 1.2 square kilometers); the average population count was 2,085 people per CBG.

References

  • Aitken SC, Cutter SL, Foote KE, Sell JL (1989) Environmental perception and behavioral geography. In: Gaile GL, Wilmott CJ (eds) Geography in America. Merrill, Colombus, pp 218–238

    Google Scholar 

  • Alley RB, Marotzke J, Nordhaus WD, Overpeck JT, Peteet DM, Pielke RA Jr, Pierrehumbert RT, Rhines PB, Stocker TF, Talley LD, Wallace JM (2003) Abrupt climate change. Science 299:2005–2010

    Article  Google Scholar 

  • Anderson JR, Hardy EE, Roach JT, RE Witmer (1976) A land use and land cover classification system for use with remote sensor data. Geological Survey Professional Paper 964, U.S. Government Printing Office, 28pp

  • Arnfield AJ (2003) Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. Int J Climatol 23:1–26

    Article  Google Scholar 

  • Beck U (1992) Risk society: toward a new modernity. Sage, London

    Google Scholar 

  • Bord RJ, Fisher A, O’Connor RE (1998) Public perceptions of global warming: United States and international perspectives. Clim Res 11:75–84

    Article  Google Scholar 

  • Borden K, Cutter S (2008) Spatial patterns of natural hazards mortality in the United States. Int J Health Geogr 7:64

    Article  Google Scholar 

  • Bostrom A, Morgan MG, Fischhoff B, Read D (1994) What do people know about global climate change? Part 1: mental models. Risk Anal 14:959–970

    Article  Google Scholar 

  • Bowman T (2008) Summary report: A meeting to assess public attitudes about climate change. Sponsored by NOAA, NASA, and the George Mason University Center for Climate Change Communications. NOAA, Silversprings, MD

  • Brazel A, Selover N, Vose R, Heisler G (2000) The tale of two climates—Baltimore and Phoenix urban LTER sites. Climate Research 15:123–135

    Article  Google Scholar 

  • Brazel A, Gober P, Lee S-J, Grossman-Clarke S, Zehnder JA, Hedquist B, Comparri E (2007) Determinants of changes in the regional urban heat island in metropolitan Phoenix (Arizona, USA) between 1990 and 2004. Clim Res 33:171–182

    Article  Google Scholar 

  • Brody SD, Peck BM, Highfield WE (2004) Examining localized patterns of air quality perception in Texas: a spatial and statistical analysis. Risk Anal 24:1561–1574

    Article  Google Scholar 

  • Brody SD, Zahran S, Vedlitz A, Grover H (2008) Examining the relationship between physical vulnerability and public perceptions of global climate change in the United States. Environ Behav 40:72–95

    Article  Google Scholar 

  • Brown M (2000) Urban parameterizations for mesoscale meteorological models. In: Boybeyi Z (ed) Mesoscale atmospheric dispersion. WIT press, Ashurst Southampton England, pp 193–255

  • Burt JE, Barber GM (1996) Elementary statistics for geographers. The Guilford Press, New York

    Google Scholar 

  • Carey M (2010) In the shadow of melting glaciers: climate change and andean society. Oxford University Press, New York, NY

  • Census Bureau (2010) American community survey. Available at: www.census.gov

  • (CDC) Centers for Disease Control (2000) Heat-related illnesses, deaths, and risk factors—Cincinnati and Dayton, Ohio, 1999 and United States, 1979–1997. Morb Mortal Wkly Rep 49:470–473

    Google Scholar 

  • (CDC) Centers for Disease Control and Prevention (2005) Heat-related mortality—Arizona, 1993–2002 and United States, 1979–2002. Morb Mortal Wkly Rep 54:628–630

    Google Scholar 

  • Chen F, Janjic Z, Mitchell K (1997) Impact of the atmospheric surface-layer parameterizations in the new land-surface scheme of the NCEP mesoscale Eta model. Bound-Layer Meteor 85:391–421

    Article  Google Scholar 

  • Chen F, Kusaka H, Bornstein R, Ching J, Grimmond CSB, Grossman-Clarke S, Loridan T, Manning KW, Martilli A, Miao S, Sailor D, Salamanca FP, Taha H, Tewari M, Wang X, Wyszogrodzki AA, Zhang C (2011) The integrated WRF/urban modeling system: development, evaluation, & applications to urban environmental problems. Int J Climatol 31:273–288

    Article  Google Scholar 

  • Corral-Verdugo V, Bechtel RB, Frijo-Sing B (2003) Environmental beliefs and water conservation: an empirical study. J Environ Psychol 23:247–257

    Article  Google Scholar 

  • Dai A, Trenberth KE (2004) The diurnal cycle and its depiction in the community climate system model. J Clim 17:930–951

    Article  Google Scholar 

  • Diffenbaugh N, Pal J, Trapp R, Giorgi F (2005) Fine-scale processes regulate the response of extreme events to global climate change. Proc Natl Acad Sci USA 102:15774–15778

    Article  Google Scholar 

  • Dispensa JM, Brulle RJ (2003) Media’s social construction of environmental issues: focus on Global Warming—a comparative study. Int J Sociol Soc Pol 23:74–105

    Article  Google Scholar 

  • Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107

    Article  Google Scholar 

  • Dunlap RE (1998) Lay perceptions of global risk. Int Sociol 13:473–498

    Article  Google Scholar 

  • Dunlap RE, Catton WR Jr (1979) Environmental sociology. Annu Rev Sociol 5:243–273

    Article  Google Scholar 

  • Dunlap RE, McCright AM (2008) A widening gap: republican and democratic views on climate change. Environment 50:26–35

    Google Scholar 

  • Dunlap RE, Scarce R (1991) The polls-poll trends: environment problems and protection. Public Opin Q 55:651–672

    Article  Google Scholar 

  • Eberhart-Phillips JE, Saunders TM, Robinson AL, Hatch DL, Parrish RG (1994) Profile of mortality from the 1989 Loma Prieta earthquake using coroner and medical examiner reports. Disasters 18:160–170

    Article  Google Scholar 

  • Ellis J, Galvin KA (1994) Climate patterns and land-use practices in the dry zones of Africa. Bioscience 44:340–349

    Article  Google Scholar 

  • Fernandez-Ballesteros R (ed) (2003) Environmental attitudes and values. Encyclopedia of psychological assessment, volume 1. Sage, Thousand Oaks, pp 364–369

    Google Scholar 

  • Fischhoff B (1985) Managing risk perceptions. Issues Sci Technol 2:83–96

    Google Scholar 

  • Fotheringham AS, Brunsdon C, Charlton M (2000) Quantitative geography: perspectives on spatial data analysis. Sage, London

    Google Scholar 

  • Galloway McLean K, Ramos-Castillo A, Gross T, Johnston S, Vierros M, Noa R (2009) Report of the Indigenous Peoples’ Global Summit on Climate Change: 20–24 April 2009. Anchorage, Alaska. United Nations University – Traditional Knowledge Initiative, Darwin, Australia

  • Garcia-Mira R, Real JE, Romay J (2005) Temporal and spatial dimensions in the perception of environmental problems: an investigation of the concept of environmental hyperopia. Int J Psychol 40:5–10

    Article  Google Scholar 

  • Geller H (2003) Energy revolution: policies for a sustainable future. Island Press, Washington

    Google Scholar 

  • Gimblett HR (2001) Integrating geographic information systems and agent-based modeling techniques for simulating social and ecological processes. Oxford University Press, Oxford

    Google Scholar 

  • Goudie A (2000) The human impact: on the natural environment. MIT Press, Massachusetts

    Google Scholar 

  • Gregory RS, Leiserowitz A, Failing L (2006) Climate change impacts, vulnerabilities, and adaptation in Northwest Alaska. Available at SSRN: http://ssrn.com/abstract=1589799

  • Grimm NB, Redman CL (2004) Approaches to the study of urban ecosystems: the case of Central Arizona—Phoenix. Urban Ecosyst 7:199–213

    Article  Google Scholar 

  • Grossman-Clarke S, Zehnder JA, Stefanov WL, Liu Y, Zoldak MA (2005) Urban modifications in a mesoscale meteorological model and the effects on near surface variables in an arid metropolitan region. J Appl Meteorol 44:1281–1297

    Article  Google Scholar 

  • Grossman-Clarke S, Stefanov WL, Zehnder JA (2010a) Urban weather, climate and air quality modeling: increasing resolution and accuracy using improved urban morphology. In: Yang X (ed) Urban remote sensing. Wiley-Blackwell. http://mailer.fsu.edu/~xyang/wiley.htm. In press

  • Grossman-Clarke S, Zehnder JA, Loridan T, Grimmond SCB (2010b) Contribution of land use changes to near surface air temperatures during recent summer extreme heat events in the phoenix metropolitan area. J Appl Meteorol Climatol 49:1649–1664

    Article  Google Scholar 

  • Hamilton LC (2008) Who cares about Polar regions? Results from a survey of US public opinion. Arctic Antarct Alpine Res 40:671–678

    Article  Google Scholar 

  • Hardisty DJ, Johnson EJ, Weber EU (2010) A dirty word or a dirty world? attribute framing, political affiliation, and query theory. Psychol Sci 21:86–92

    Article  Google Scholar 

  • Harlan SL, Brazel AJ, Prashad L, Stefanov WL, Larsen L (2006) Neighborhood microclimates and vulnerability to heat stress. Soc Sci Med 63:2847–2863

    Article  Google Scholar 

  • Harlan SL, Budruk M, Gustafson A, Larson K, Ruddell D, Smith VK, Yabiku ST, Wutich A (2007) Phoenix Area Social Survey 2006 Highlights: Community and Environment in a Desert Metropolis. Central Arizona—Phoenix Long-Term Ecological Research Project, Contribution No. 4. Global Institute of Sustainability, Arizona State University

  • Harlan SL, Brazel A, Jenerette GD, Jones NS, Larsen L, Prashad L, Stefanov WL (2008) In the shade of affluence: the inequitable distribution of the urban heat island. Res Soc Probl Publ Pol 15:173–202

    Article  Google Scholar 

  • Hedquist BC, Brazel AJ (2004) Urban heat island (UHI) measures for the S.E. metropolitan area of the CAP LTER: transects versus fixed stations. Presented at the 6th Annual CAP LTER Poster Symposium, Tempe, AZ

  • Hong SY, Dudhia J, Chen SH (2004) A revised approach to ice-microphysical processes for the bulk parameterization of cloud and precipitation. Mon Weather Rev 132:103–120

    Article  Google Scholar 

  • Hope D, Gries C, Zhu W, Fagan WF, Redman CL, Grimm NB, Nelson AL, Martin C, Kinzig A (2003) Socioeconomics drive urban plant diversity. Proc Natl Acad Sci India 100:8788–8792

    Article  Google Scholar 

  • (IPCC) Intergovernmental Panel on Climate Change (2001) Climate Change 2001: Impacts, adaptation, and vulnerability. Report of Working Group II. United Nations Environment Program

  • (IPCC) Intergovernmental Panel on Climate Change (2007) Climate Change 2007: Synthesis Report. Available at: http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr.pdf, Accessed 12/20/08

  • Janjic ZI (2002) Nonsingular Implementation of the Mellor–Yamada Level 2.5 Scheme in the NCEP Meso model. NCEP Office Note, No. 437, pp 61

  • Jenerette GD, Harlan SL, Brazel AJ, Jones N, Larsen L, Stefanov WL (2007) Regional relationships between vegetation, surface temperature, and human settlement in a rapidly urbanizing ecosystem. Landsc Ecol 22:353–365

    Article  Google Scholar 

  • Johnson DP, Wilson JS, Luber GC (2009) Socioeconomic indicators of heat-related health risk supplemented with remotely sensed data. Int J Health Geogr 8:57

    Article  Google Scholar 

  • Jones JM (2010) Conservatives doubts about global warming grow. Available at http://www.gallup.com/poll/126563/Conservatives-Doubts-Global-Warming-Grow.aspx, Accessed May 28, 2010, (March 11)

  • Kain JS (2004) The Kain–Fritsch Convective Parameterization: An Update. J Appl Meteorol 43:170–181

    Article  Google Scholar 

  • Kalkstein LS, Davis RE (1989) Weather and human mortality: an evaluation of demographic and inter-regional responses in the United States. Ann Assoc Am Geogr 79:44–64

    Article  Google Scholar 

  • Kalkstein LS, Green JS (1997) An evaluation of climate/mortality relationships in large U.S. cities and the possible impacts of a climate change. Environ Health Perspect 105:84–93

    Article  Google Scholar 

  • Karl TR, Trenberth KE (2003) Modern global climate change. Science 302:1719–1723

    Article  Google Scholar 

  • Karl TR, Jones PD, Knight RW, Kukla G, Plummer N, Razuvayev V, Gallo KP, Lindseay J, Charlson RJ, Peterson TC (1993) A new perspective on recent global warming: asymmetric trends of daily maximum and minimum temperature. Am Meteorol Soc 74:1007–1023

    Article  Google Scholar 

  • Keeter S, Kennedy C, Dimock M, Best J, Craighill P (2006) Gauging the impact of growing nonresponse on estimates from a national RDD survey. Public Opin Q 70:759–779

    Article  Google Scholar 

  • Kellstedt PM, Zahran S, Vedlitz A (2008) Personal efficacy, the information environment, and attitudes toward global warming and climate change in the United States. Risk Anal 28:113–126

    Article  Google Scholar 

  • Kempton W, Boster JS, Hartley JA (1995) Environmental values in american culture. MIT Press, Cambridge

    Google Scholar 

  • Klinenberg E (2002) Heat wave: a social autopsy of disaster in Chicago. University of Chicago Press, Chicago

    Google Scholar 

  • Kowalok ME (1993) Common threads: research lessons from acid rain, ozone depletion, and global warming. Environ 35:12–20

    Article  Google Scholar 

  • Krosnick JA, Holbrook AL, Lowe L, Visser P (2006) The origins and consequences of democratic citizens’policy agendas: a study of popular concern about global warming. Climatic Change 77:7–43

    Article  Google Scholar 

  • Kurz T (2002) The psychology of environmentally sustainable behavior: fitting together pieces of the puzzle. Ana Soc Iss Pub Pol 2:257–278

    Article  Google Scholar 

  • Kusaka H, Kimura F (2004) Thermal effects of urban canyon structure on the nocturnal heat island: numerical experiment using a mesoscale model coupled with an urban canopy model. J Appl Meteorol 43:1899–1910

    Article  Google Scholar 

  • Leiserowitz AA (2005) American risk perceptions: is climate change dangerous? Risk Anal 25:1433–1442

    Article  Google Scholar 

  • Leiserowitz AA (2006) Climate change risk perception and policy preferences: the role of affect, imagery, and values. Climatic Change 77:45–72

    Article  Google Scholar 

  • Leiserowitz AA, Maibach E, Roser-Renout C (2010) Global warming’s six Americas, January 2010. Yale University and George Mason University, Yale Project on Climate Change, New Haven, CT. Available at http://environment.yale.edu/uploads/SixAmericasJan2010.pdf

  • List JA (2004) Young, selfish and male: field evidence of social preferences. Econ J 492:121–149

    Article  Google Scholar 

  • Lorenzoni I, Pidgeon NE, O’Connor RE (2005) Dangerous climate change: the role for risk research. Risk Anal 25:1387–1398

    Article  Google Scholar 

  • Lowry W (1967) The climate of cities. Sci Am 217:15–23

    Article  Google Scholar 

  • Mainieri T, Barnett EG, Valdero TR, Unipan JB, Oskamp S (1997) Green buying: the influence of environmental concern on consumer behavior. J Soc Psychol 137:189–204

    Article  Google Scholar 

  • (MCDPH) Maricopa County Department of Public Health, Division of Disease Control, Office of Epidemiology and Data Services (2008) Heat caused and heat related death occurrences in Maricopa County. (August 12). Phoenix, AZ

  • Martilli M (2007) Current research and future challenges in urban mesoscale modeling. Int J Climatol 27:1909–1918

    Article  Google Scholar 

  • Martin CA (2001) Landscape water use in Phoenix, Arizona. Desert Plants 17:26–31

    Google Scholar 

  • Martin CA, Peterson KA, Stabler LB (2003) Residential landscaping in Phoenix, Arizona, U.S.: practices and preferences relative to covenants, codes, and restrictions. J Arboric 29:9–17

    Google Scholar 

  • Marx SM, Weber EU, Orlove BS, Leiserowitz A, Krantz DH, Roncoli C, Phillips J (2007) Communication and mental processes: experiential and analytic processing of uncertain climate information. Global Environ Change 17:47–58

    Article  Google Scholar 

  • Masson V (2006) Urban surface modeling and the meso-scale impact of cities. Theor Appl Climatol 84:35

    Article  Google Scholar 

  • McCormick S (2008) Hot or Not?: recognizing and preparing for climate-induced illness. Paper presented at the annual meeting of the American Sociological Association Annual Meeting, Sheraton Boston and the Boston Marriott Copley Place, Boston, MA. Available at: http://www.allacademic.com/meta/p242555_index.html

  • McMichael AJ, Woodruff RE, Hales S (2006) Climate change and human health: present and future risks. Lancet 367:859–869

    Article  Google Scholar 

  • Meehl GA, Tebaldi C (2004) More intense, more frequent, and longer lasting heat waves in the 21st century. Science 305:994–997

    Article  Google Scholar 

  • Mirchandani H, McDonald G, Hood I, Fonseca C (1996) Heat-related deaths in Philadelphia—1993. Am J Forensic Med Pathol 17:106–108

    Article  Google Scholar 

  • Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102:16663–16682

    Article  Google Scholar 

  • Moran PA (1950) Notes on continuous stochastic phenomena. Biometrika 37:17–23

    Google Scholar 

  • Neter J, Wasserman W (1974) Applied linear statistical models. Richard D. Irwin, Inc.

  • Newport F (2010) (March 11) Americans’ global warming concerns continue to drop. Available at: http://www.gallup.com/poll/126560/Americans-Global-Warming-Concerns-Continue-Drop.aspx, Accessed May 28, 2010

  • (NOAA) National Oceanic and Atmospheric Administration (2006) US Natural Hazard Statistics. Available at http://www.nws.noaa.gov/om/hazstats.shtml#, Accessed December 21, 2008

  • Norgaard KM (2011) Living in denial: climate change, emotions, and every day life. MIT Press, Cambridge

    Google Scholar 

  • O’Connor RE, Bord RJ, Fisher A (1999) Risk perceptions, general environmental beliefs, and willingness to address climate change. Risk Anal 19:461–471

    Google Scholar 

  • Ogbu JU (1993) Differences in cultural frames of reference. Int J Behav Dev 16:483–506

    Google Scholar 

  • Oke T (1978) Boundary layer climates. Wiley, New York

    Book  Google Scholar 

  • Oke TR (1982) The energetic basis of the urban heat island. Q J Roy Meteorol Soc 108:1–24

    Google Scholar 

  • Oke TR (1997) Part 4: the changing climatic environments: urban climates and global environmental change. In: Thompson RD, Perry A (eds) Applied climatology principals and practice. Routledge, London, pp 273–287

    Google Scholar 

  • O’Neill MS, Ebi K (2009) Temperature extremes and health: impacts of climate variability and change in the United States. J Occup Environ Med 51:13–25

    Article  Google Scholar 

  • Read D, Bostrom A, Morgan MG, Fischhoff B, Smuts T (1994) What do people know about global climate change? Part 2: survey studies of educated laypeople. Risk Anal 14:971–982

    Article  Google Scholar 

  • Reith J, Jorgensen HS, Pedersen PM, Nakayama H, Raaschou HO, Jeppensen LL, Olsen TS (1996) Body temperature in acute stroke: relation to stroke severity, infant size, mortality, and outcome. Lancet 347:422–425

    Article  Google Scholar 

  • Ruddell DM, Harlan SL, Grossman-Clarke S, Buyanteyev A (2010) Risk and exposure to extreme heat in microclimates of Phoenix, AZ. In: Showalter P, Lu Y (eds) Geospatial contributions to urban hazard and disaster analysis. Springer, New York, pp 179–202

    Google Scholar 

  • Sailor DJ, Lu L (2004) A top-down methodology for developing diurnal and seasonal anthropogenic heating profiles for urban areas. Atmos Environ 38:2737–2748

    Article  Google Scholar 

  • Seager R, Tang M, Held I, Kushnir Y, Lu J, Vecchi G, Huang H, Harnik N, Leetmaa A, Lau N, Li C, Velez J, Naik N (2006) Model projections of an imminent transition to a more arid climate in southwestern North America. Science 316:1181–1184

    Article  Google Scholar 

  • Semenza JC, Rubin CH, Falter KH, Selanikio JD, Flanders WD, How HL, Wilhelm JL (1996) Heat-related deaths during the July 1995 heat wave in Chicago. Am J Prev Med 16:269–277

    Article  Google Scholar 

  • Sheridan SC, Kalkstein LS (2004) Progress in heat watch-warning system technology. Bull Am Meteorol Soc 85:1931–1941

    Article  Google Scholar 

  • Sherif M (1936) The psychology of social norms. Harper, Oxford

    Google Scholar 

  • Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Wang W, Powers JG (2005) A description of the advanced research WRF version 2. NCAR Technical Note-468+STR, pp. 88

  • Slovic P, Peters E (2006) Risk perception and affect. Curr Dir Psychol Sci 15:322–325

    Article  Google Scholar 

  • Souch C, Grimmond S (2006) Applied climatology: urban climate. Progr Phys Geogr 30:270–279

    Article  Google Scholar 

  • Stedman RC (2004) Risk and climate change: perceptions of key policy actors in Canada. Risk Anal 24:1395–1406

    Article  Google Scholar 

  • Stefanov WL, Ramsey MS, Christensen PR (2001) Monitoring urban land cover change: an expert system approach to land cover classification of semiarid to arid urban centers. Rem Sens Environ 77:173–185

    Article  Google Scholar 

  • Taha H (1997) Urban climates and heat islands: albedo, evapotranspiration, and anthropogenic heat. Energ Build 25:99–103

    Article  Google Scholar 

  • Tuan Y-F (1990) Topophilia: a study of environmental perception, attitudes, and values. Colombia University Press, New York, NY

  • Ungar S (1992) The rise and (relative) decline of global warming as a social problem. Socio Q 33:483–501

    Article  Google Scholar 

  • Uzzell DL (2000) The psycho-spatial dimension of global environmental problems. J Environ Psychol 20:307–318

    Article  Google Scholar 

  • Vandentorren S, Suzan F, Medina S, Pascal M, Maulpoix A, Cohen J-C (2004) Mortality in 13 French cities during the August 2003 heat wave. Am J Public Health 94:1518–1520

    Article  Google Scholar 

  • Voogt JA (2002) Urban Heat Island. In: Douglas I (ed) Encyclopedia of global environmental change. Wiley & Sons, Chichester, pp 660–666

    Google Scholar 

  • Weber EU (2006) Experience-based and description-based perceptions of long-term risk: Why global warming does not scare us (yet). Climatic Change 77:103–120

    Article  Google Scholar 

  • Wilhelmi OV, Purvis KL, Harriss RC (2004) Designing a geospatial information infrastructure for mitigation of heat wave hazards in urban areas. Nat Hazards Rev 5:147–158

    Article  Google Scholar 

  • Ye L, Zaval L, Johnson E (2011) Local warming: daily temperature change influences belief in global warming. Psychol Sci 22:454–459

    Google Scholar 

  • Zahran S, Brody S, Grover H, Vedlitz A (2006) Climate change vulnerability and policy support. Soc Nat Resour 19:771–789

    Article  Google Scholar 

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Acknowledgements

This study is based upon research supported by the National Science Foundation (NSF) under grant Nos. DEB-0423704 Central Arizona - Phoenix Long-Term Ecological Research (CAP LTER), SES-0345945 Decision Center for a Desert City (DCDC), and GEO-0816168 Urban Vulnerability to Climate Change. Any opinions, findings, and conclusions or recommendation expressed in this study are those of the authors and do not necessarily reflect the views of the NSF.

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Authors and Affiliations

  1. Spatial Sciences Institute, University of Southern California, 3616 Trousdale Parkway, Suite B55, Los Angeles, CA, USA

    Darren Ruddell

  2. Arizona State University, Phoenix metropolitan area, AZ, USA

    Sharon L. Harlan, Susanne Grossman-Clarke & Gerardo Chowell

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  1. Darren Ruddell
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Corresponding author

Correspondence to Darren Ruddell.

Appendix 1: A technical note on the WRF simulations

Appendix 1: A technical note on the WRF simulations

This study employed WRF version 3.0.1.1 to simulate spatial and temporal distribution of T 2m in the Phoenix metropolitan area during the extreme heat event 15–19 July 2005. The WRF run was started at 00 UTC (1700 LST) allowing 24 overlapping hours for model spin up for 72 h simulation periods. 2-way nested WRF model runs with four domains and resolutions of 27, 9, 3 and 1 km, respectively were performed. In the simulations, 41 vertical levels were used with the first five vertical levels of ~25, 35, 45, 60 and 80 m AGL. The innermost domain included the Phoenix metropolitan area, surrounding desert and agricultural land.

WRF initial and boundary conditions were provided by NCEP ETA analysis data that are available with a 40 km resolution at a 3-h time-step. Planetary boundary layer processes were included via the Mellor-Yamada-Janjic scheme (Janjic 2002), microphysics through the WRF Single-Moment 3-class simple ice scheme (Hong et al. 2004), convection for the domains with 27 km and 9 km resolutions by the Kain-Fritsch scheme (Kain 2004) and the long and short wave radiation processes were included through the Rapid Radiative Transfer Model (Mlawer et al. 1997) and Dudhia scheme (Dudhia 1989), respectively. The Noah UCM and the Noah Land surface model (Noah LSM; Chen et al. 1997) were applied to the fraction of a model grid cell with built and natural surfaces, respectively.

An anthropogenic heat flux, Q F , derived by the Sailor and Lu (2004) method was added to the sensible heat flux in WRF. Hourly Q F values are based on the monthly energy consumption and average vehicle kilometers traveled per person. The average energy and fuel consumption data are spatially and temporally allocated based on the spatial distribution of the working and residential population densities (Grossman-Clarke et al. 2005). For this particular urban area, which is mostly suburban and not very densely settled, Q F values are small in comparison to the other heat fluxes. Maximum values for the built-up urban, xeric, and mesic residential areas are ~30, 35 and 20 W m−2 and occurred during the evening rush hour (LST 1700). Values during other day time hours are between 5 and 25 Wm−2.

The standard procedure for obtaining initial soil moisture for WRF is by interpolating the NCEP ETA model soil moisture values to the WRF spatial resolution. The initial soil moisture data reflect conditions in the native desert surrounding Phoenix but not the soil moisture content as influenced by specific local irrigation practices. Therefore the standard WRF cannot account for effects of irrigation on latent heat fluxes and subsequently air temperatures.

Irrigation occurs in the region year round to sustain agricultural productivity and non-native plant species that are predominantly used in urban landscaping. Most plants cannot survive extended periods of water stress, particularly during the hot summer months. Flood irrigation of agricultural fields is the preferred irrigation practice. For example, approximately 10–15 cm of water are applied to agricultural fields on a weekly basis via flooding during the summer months. This provides soil moisture conditions at field capacity to a depth of about 90 cm. Therefore, to account for flood irrigation in the WRF simulations, the initial soil moisture content of all soil levels was set to the reference soil moisture which corresponds to field capacity (USGS LULC category 3). The Noah LSM soil model has four layers with thicknesses of 0.05, 0.25, 0.70 and 1.50 m. The predominant soil categories in the region are “sandy loam” and “loam” with field capacities of 0.383 and 0.329 m3 m−3 and wilting points of 0.047 and 0.066 m3 m−3. In the course of the simulations the soil moisture content for the sandy loam dropped to 0.35, 0.36, 0.32 m3 m−3 for soil layer one to three and stayed at field capacity for layer four. Plants did not experience significant water stress. In comparison the climatological soil moisture content as obtained from the NCEP ETA model initial data are 0.10, 0.11, 0.12 and 0.14 m3 m−3.

Drip irrigation (the placement of drippers close to the plants’ stems to allow water to drip over an extended period of time into the soil) is the preferred irrigation practice for urban vegetation in Phoenix (Martin 2001; Martin et al. 2003). This irrigation technique ensures that there is sufficient water available in the root zone of plants to fulfill the transpiration demand, but very little water is “lost” by soil evaporation because the soil surfaces in between plants are usually dry. In WRF, the root depth of the urban and agricultural vegetation extends to 1 m (layer 3). To account for the drip irrigation practice and to avoid high evaporation rates from bare soil surfaces that are usually dry in urban landscaping in Phoenix, the initial soil moisture content was increased for the 3 sub-surface layers for the urban land use categories but not for the top soil layer. This ensured that vegetation in the model did not experience water stress and was able to transpire according to the atmospheric demand. The initial soil water content of the top soil layer was left at the value provided by the NCEP ETA model.

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Ruddell, D., Harlan, S.L., Grossman-Clarke, S. et al. Scales of perception: public awareness of regional and neighborhood climates. Climatic Change 111, 581–607 (2012). https://doi.org/10.1007/s10584-011-0165-y

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  • DOI: https://doi.org/10.1007/s10584-011-0165-y

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