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Slides for GGR 314, Global Warming Chapter 7: Heat and Water Stress, Terrestrial Species Extinctions Course taught by Danny Harvey Department of Geography University of Toronto
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Exhibit 7-1: Regions currently with water stress
Source: IPCC AR4 WG2, Chapter 3, Fig. 3.2
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Source: Barnett et al. (2005, Nature, Vol. 438, 303-309)
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Exhibit 7-2: Ratio of annual snowfall to annual runoff
Exhibit 7-2: Ratio of annual snowfall to annual runoff. The red line outlines the areas where runoff is predominantly from snowmelt and there is not adequate storage to buffer seasonal variations. Source: Barnett et al. (2005, Nature, Vol. 438, )
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Exhibit 7-3: Retreat of the Gangotri glacier in the Himalayas
Source: IPCC AR4 WG4, Chapter 10, Fig. 10.6
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Exhibit 7-4: Recent retreat of some Himalayan glaciers
Source: IPCC AR4 WG2, Chapter 10
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Exhibit 7-5: Projected change in annual river runoff, 2050 compared to the 1961-1990 average
Source: Arnell et al (2011, Glob. Env. Change, Vol. 21, )
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Exhibit 7-6: Numbers of people in different regions in 2050 experiencing an increase (top) or decrease (bottom) in water stress (<1000 m3/P/yr) based on climate projections by the same 4 AOGCMs featured in Exhibit 7-5. Source: Arnell et al (2011, Glob. Env. Change, Vol. 21, )
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Exhibit 7-7: Projected changes in annual river runoff; links to water and sustainable development
Source: IPCC AR4 WG2, Chapter 3, Fig. 3.8
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Recall: Exhibit 4-5: Projected global mean temperature change for a business-as-usual scenario compared to variations during the previous millennium and observed changes during the past 150 years, neglecting likely positive climate-carbon cycle feedbacks. Source: Harvey (2010, Energy and The New Reality, Vol 1, Earthscan, Fig. 1.5)
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Exhibit 7-8: Distribution of maximum wetbulb temperature (Tw) that occurred at any time during the decade The warmest Tw to have occurred anywhere is about 30oC. Source: Sherwood and Huber (2010, Proc. Nat. Acad. Sci., Vol. 107, )
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Exhibit 7-9: Maximum annual Tw as simulated by an AGCM-ML ocean model after the global mean temperature has warmed by 10oC relative to Source: Sherwood and Huber (2010, Proc. Nat. Acad. Sci., Vol. 107, )
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Exhibit 7-10: Histograms showing the frequencies of different surface air temperatures for all time steps and grid points (black), maximum surface air temperatures at all grid points (blue), and maximum Tw values (red) as observed during the decade (left) and as simulated after a global mean warming of 10oC (right). The red dashed curve in the right chart is the Tw distribution shown in the left chart for the decade. The vertical dashed line is the absolute maximum Tw value (35oC) that humans can survive. Source: Sherwood and Huber (2010, Proc. Nat. Acad. Sci., Vol. 107, )
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Exhibit 7-11: Maximum mammal body size was a factor of 1000 smaller than today 70 million years ago, when temperatures were 5-7oC warmer. Cooling over the past 50 million years (inferred from the data in the lower panel) made it easier to dissipate heat as the mass of the largest mammals increased during the past 70 million years and the surface:volume ratio decreased. Mammals about 20 times less massive than the largest found today survived the PETM 55 million years ago Age (millions of years) Source: Smith et al (2010, Science, Vol. 330, )
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Exhibit 7-12: Frequency distribution of departures of individual summers from the average summer temperature, for the time period (observed) and as projected for (frequencies in each case are adjusted to represent 100 summers) Source: Battisti and Naylor (2009, Science, Vol. 323, )
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Exhibit 7-13: Frequency of summers in that are warmer than the warmest summer on record ( ) Source: Battisti and Naylor (2009, Science, Vol. 323, )
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Exhibit 7-14: Frequency of summers in that are warmer than the warmest summer on record ( ) Source: Battisti and Naylor (2009, Science, Vol. 323, )
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Exhibit 7-15: Average change (oC) in summer temperature in Europe, as simulated by 6 different high-resolution regional climate models driven by 3 different AOGCMs, for compared to Source: Fischer and Schar (2010, Nature Geoscience, Vol. 3, )
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Exhibit 7-16: Ratio of number of heat waves per year in (left) and (right) to the number in (a heat wave is defined as a spell of at least 6 consecutive days where the maximum temperature exceeds the local 90th percentile for the period). Source: Fischer and Schar (2010, Nature Geoscience, Vol. 3, )
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Exhibit 7-17: Increase in the temperature of heat waves during (left) and (right) compared to heat waves during Source: Fischer and Schar (2010, Nature Geoscience, Vol. 3, )
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Exhibit 7-18: Average daily maximum temperature during JJA for the period (top) and numbers of days per year with maximum temperature > 35oC and minimum night-time temperature > 25oC Source: Lelieveld et al. (2012, Climatic Change, in press)
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Exhibit 7-19a: Probability distribution of hourly temperature for the period and as projected for (orange), (red) and (magenta) Source: Lelieveld et al. (2012, Climatic Change, in press)
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Exhibit 7-19b: Probability distribution of hourly temperature for the period and as projected for (orange), (red) and (magenta) Source: Lelieveld et al. (2012, Climatic Change, in press)
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August 2006 following a July heat wave
Exhibit 7-20a: Heliotropium convolvulaceum on a Mojave Desert Sand-dune June 2006 August 2006 following a July heat wave Photos by R. Sage, University of Toronto
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Exhibit 7-20b: Opuntia cacti in the Mojave Desert
August 2006 following a July heat wave. The injury patterns are unusual and indicate severe stress Photos by R. Sage, University of Toronto
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Exhibit 7-20c: Cacti injured by heat stress
Healthy cacti Exhibit 7-20c: Cacti injured by heat stress Photos by R. Sage, University of Toronto
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Eriognomum ovalifolium. White Mountains, California.
Exhibit 7-21a: Tundra vegetation near lower elevation limit showing evidence of dieback in the cushion plant Eriognomum ovalifolium. White Mountains, California. Photo by R. Sage, University of Toronto
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Exhibit 7-21b: Healthy tundra. White Mountains, California.
Photo by R. Sage, University of Toronto
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Exhibit 7-22: Impact of projected global warming (top) and increasing GDP per capita (bottom) on the incidence of malaria. Net result: malaria decreases everywhere Source: Beguin et al (2011, Glob. Env. Change, Vol. 21, )
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Exhibit 7-23: Increase in the incidence of malaria (red) if GDP per person decreases by 50% (with an unchanged % of GDP devoted to health and sanitation) Source: Beguin et al (2011, Glob. Env. Change, Vol. 21, )
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