Climate Change and Climate Change and Extreme Events: Lies, Extreme Events: Lies,
Damned Lies, and StatisticsDamned Lies, and Statistics
By
David R. LegatesUniversity of Delaware
AndDelaware State Climatologist
““Figures often beguile Figures often beguile me, particularly when I me, particularly when I have the arranging of have the arranging of them myself; in which them myself; in which
case the remark case the remark attributed to Disraeli attributed to Disraeli
would often apply with would often apply with justice and force: justice and force:
‘‘There are three kinds There are three kinds of lies: lies, damned of lies: lies, damned lies, and statistics’.”lies, and statistics’.”
Mark TwainMark TwainChapters from my AutobiographyChapters from my Autobiography
North American ReviewNorth American Review, No. DCXVIII, No. DCXVIII
Lies, Damned Lies, StatisticsLies, Damned Lies, Statistics
…and Weather Observers!…and Weather Observers!
DISCLAIMER
The Delaware State Climatologist The Delaware State Climatologist does does NOT represent either the represent either the
Executive, Legislative, or Judicial Executive, Legislative, or Judicial branches of government and does branches of government and does not speak for the Governor or any not speak for the Governor or any
other State agency or official.other State agency or official.
““Recent media coverage of events associated of events associated with the subject of climate change has with the subject of climate change has
generated some confusion as to the role of generated some confusion as to the role of the State Climatologist.”the State Climatologist.”
Governor Minner – February 13, 2007Governor Minner – February 13, 2007
Heavy Rainfalls CalledSign of Climate Changein New Report
Severe WeatherPredicted as Norm
““Delaware…has seen a 37% Delaware…has seen a 37% increase in storms dumping increase in storms dumping 2-inches or more of rainfall 2-inches or more of rainfall
over a 24-hour period.”over a 24-hour period.”
Environment America and USPIRGEnvironment America and USPIRG““When it Rains, It Pours: Global Warming and When it Rains, It Pours: Global Warming and the Rising Frequency of Extreme Precipitation the Rising Frequency of Extreme Precipitation
in the United States”in the United States”
Page 36
}≈37%
Days with Precipitation >2.0 InchesPorter Reservoir, Wilmington DE
Days with Precipitation >2.0 InchesPorter Reservoir, Wilmington DE
Days with Precipitation >2.0 InchesNew Castle County AP, Wilmington DE
Days with Precipitation >2.0 InchesUniversity Farm, Newark DE
Days with Precipitation >2.0 InchesPorter Reservoir, Wilmington DE
http://www.surfacestations.org
MMTS
http://www.surfacestations.org
Days with Precipitation >2.0 InchesPorter Reservoir, Wilmington DE
Page 36
Dr. Willie Dr. Willie SoonSoon
HarvardHarvardUniversityUniversity
Number of 3” Rainfalls per Year in Madison WI
ASOSERA
Number of 3” Rainfalls per Decade in Madison WI
ASOSERA
Number of 3” Rainfalls per Decade in Madison WI
“Pre-ASOS”
Number of 3” Rainfalls per Decade in Madison WI
“Pre-ASOS”
Number of 2” Rainfalls per Year in Stoughton WI
Number of 3” Rainfalls per Year in Stoughton WI
0
1
2
3
4
5
6
7
8
1932-1941 1942-1951 1952-1961 1969-1978 1998-2008
Number of 3” Rainfalls per Decade in Stoughton WI
*
*Actually, an 11-year ‘decade’
What is Wrong What is Wrong with the with the
Statistics?Statistics?
Number of 2” Rainfalls per Year in Stoughton WI
FREQUENCY COUNTS!
Regarding the Dependent Variable:• It is composed of discrete events that are
frequency counts and non-negative integers.• Infrequently occurring events tend to cluster
around 0 and/or 1 and exhibit low frequencies at higher values.
• It is highly positively skewed and truncated at 0 – Thus the Mean > Median
• Error term is NOT iid ~ N(0,)• OLS regression is inappropriate for these
data!
Two Alternatives to OLS Regression:• Poisson Regression
– Assumes a Poisson distribution, where values are non-negative integers, and is highly positively skewed.
– Assumes Equidispersion (i.e., mean is equal to the variance)
• Negative Binomial Regression– Assumes a Poisson-like distribution; values are non-
negative integers and is positively skewed– No assumption of Equidispersion; appropriate for over-
dispersed data (i.e., variance is greater than the mean)
Advantages of Poisson or Negative Binomial Regression:
• Although OLS, Poisson and negative binomial regressions yield similar results, the non-normality of the errors leads to large standard errors and an arbitrary increase in the level of significance of the coefficients in OLS.
• Assumptions can be more easily met with Poisson or Negative Binomial regression than with OLS.
• OLS regression could lead to a Type I error (rejection of null hypothesis when true) and erroneously conclude that the variable is changing over time when, in fact, it is not.
Page 36
Climate Change and Climate Change and Extreme Events: Lies, Extreme Events: Lies,
Damned Lies, and StatisticsDamned Lies, and Statistics
By
David R. LegatesUniversity of Delaware
AndDelaware State Climatologist
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