Climate Change, Texas, and the Limits of Confidence. John Nielsen-Gammon Dept. of Atmospheric Sciences Texas A&M University
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1 Climate Change, Texas, and the Limits of Confidence John Nielsen-Gammon Dept. of Atmospheric Sciences Texas A&M University
2 Global Surface Temperature (3)
3 Pattern of Temperature Trend
4 Regional Temperatures, (PAGES 2013)
5 Multiple datasets & analyses (AR5 WG1 FAQ2.1)
6
7 Mass change, ice sheets (AR5 WG1 Figs 4.13d-4.14d)
8 Changes in Water and Ice (AR5 WG1 FAQ2.1)
9 Global Surface Temperature (3)
10 Global temperatures Global Surface Temperature Anomalies ( C) Base Period: HadCRUT surface GISTEMP surface NGT surface BEST surface RCP8.5 avg
11 Global temperatures Global Surface Temperature Anomalies ( C) Base Period: HadCRUT surface GISTEMP surface NGT surface BEST surface RCP8.5 avg
12 Global Energy Balance, Part 1 Sun Atmosphere Earth Each arrow = 20 W/m 2
13 Scientific Principles Energy Imbalance implies a net gain or loss of energy Typical annually averaged energy imbalances are << 1% of the energy flow
14 Global Energy Balance, Part 1 Sun Atmosphere Earth Each arrow = 20 W/m 2
15 Global Energy Balance, Part 1 Sun Atmosphere Earth Each arrow = 20 W/m 2
16 Global Energy Balance, Part 1 Sun Atmosphere Earth Each arrow = 20 W/m 2
17 Global Energy Balance, Part 1 Sun Atmosphere Earth Each arrow = 20 W/m 2
18 Global Energy Balance, Part 1 Sun Atmosphere Earth Each arrow = 20 W/m 2
19 Global Energy Balance, Part 2 Sun Atmosphere Earth Each arrow = 20 W/m 2
20 Global Energy Balance, Part 2 Sun Atmosphere Earth Each arrow = 20 W/m 2
21 Global Energy Balance, Part 2 Sun Atmosphere Earth Each arrow = 20 W/m 2
22 Global Energy Balance, Part 2 Sun Atmosphere Earth Each arrow = 20 W/m 2
23 Global Energy Balance, Part 3 Sun Atmosphere Earth To maintain heat flow into atmosphere, Earth must warm too
24 Detection and Attribution Identify trend: detection Compare with distinct patterns in space and time caused by different forcing agents Apportion role of different forcing agents: attribution
25 Evolution of Estimated Forcings (AR5 WG1 Fig. 8.18)
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31
32 Global temperatures Global Surface Temperature Anomalies ( C) Base Period: HadCRUT surface GISTEMP surface NGT surface BEST surface RCP8.5 avg
33 Texas vs Globe Global Surface Temperature Anomalies ( C) Base Period: HadCRUT surface GISTEMP surface NGT surface BEST surface RCP8.5 avg Texas
34 Texas 5-yr Avg vs Globe Global Surface Temperature Anomalies ( C) Base Period: HadCRUT surface GISTEMP surface NGT surface BEST surface RCP8.5 avg Texas 5yr
35 Extreme Weather Short definition: Weather that s newsworthy Long definition: two kinds Weather that s extremely unlikely Weather that s unhealthy or damaging (The same event often fits both definitions)
36
37
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40 Melissa Phillip, Houston Chronicle
41 Rainfall (inches) 9 Waller County-Average 1-Day Rainfall (since 1950)
42 Rainfall (inches) 9 8 Waller County-Average 1-Day Rainfall (since 1950) April 18,
43 Rainfall (inches) 9 8 Waller County-Average 1-Day Rainfall (since 1950) August 28,
44 Rainfall (inches) Waller County-Average 1-Day Rainfall (since 1950) August 28, 2017 August 29,
45 Example #1: Heat and Cold IPCC SREX
46 The Three Pillars of Sound Attribution
47 The Three Pillars of Sound Attribution A clear historical trend
48 The Three Pillars of Sound Attribution A clear historical trend Consistent model projection s
49 The Three Pillars of Sound Attribution A clear historical trend Consistent model projection s A sound physical basis
50 Example #2: Heavy Rain
51 The Faucet Climate change s thermodynamic impact: the size of the pipe + 7% per C Climate change s dynamic impact: turning the handle
52 The Faucet The size of the pipe matters most when the faucet is wide open
53 99.98th %ile (14-yr return period) Change in Frequency 0.0x to 0.11x 0.11x to 0.25x 0.25x to 0.43x 0.43x to 0.67x 0.67x to 1.0x 1.0x to 1.5x 1.5x to 2.3x 2.3x to 4x 4x to 9x
54 95% confidence interval using effective degrees of freedom estimated following D. A. Griffith & Z. Zhang (1999): Computational Simplifications Needed for Efficient Implementation of Spatial Statistical Techniques in a GIS, Geographic Information Sciences, 5:2, , DOI: /
55 1 Frequency (events per decade) Example: 20% increase % increase ~ 30% trend
56 Arid Wet
57 Alex 2010 Average Five Day Rainfall, 50,000 sq. mi. Georges 1998 NC Sep 2010 Beulah 1967 Harvey
58 Claude e 1979 Average Five Day Rainfall, 2,000 sq. mi. Beulah 1967 TX Jun 1899 LA Aug 1940 Harvey
59 Average Five Day Rainfall, 2,000 sq. mi. Claude e 1979 Beulah 1967 TX Jun 1899 LA Aug 1940 Harris County: 34 Harvey
60 Example #3: Hurricanes
61 Hurricanes: The Balance of Evidence Increase in peak intensity (1.5 pillars) Decrease in frequency (1 pillar) but spatially variable (1.5 pillars)
62 Did Harvey stall because of climate change? Lat H4 Harvey 2017 Aug TS Allison 2001Jun TS Allison 1989 Jun TS 1908#4 Jul H1 Juan 1985 Oct 2005 TS Alberto 1994 H3 1871#3 Aug H1 1904#1 Oct Coast
63
64 Resources IPCC.ch Special report on extremes (SREX) Fifth assessment report, working group 1 (AR5 WG1) National climate assessment News items AP + USA TODAY + NYTIMES ~ Network news
65 Summary The climate is changing Over the long haul, it s us Future changes are hard to pin down Some impacts are easy It ll get warmer, it ll rain harder Some impacts are hard More droughts? Fewer hurricanes?
66 Contact Information John W. Nielsen-Gammon
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