Hurricanes

1
Climate Change
2
The Only Constant in Nature is Change
3
Outline

• Focus on station data
• Make a case global data bases have major issues
• Work with the US climate stations which are more
  stable though not without own issues
• Correlate US temperatures with carbon dioxide,
  solar and oceanic cycles
• Show how solar and ocean cycles correlate better
  than carbon dioxide with the changes

4
NASA GISS
NASA GISS
5
Issues with the Global Station Data

• Station dropout (6000 to 2000, most significant
  since 1990).
• Large increases in missing monthly data after
  1990
• Little or no urban adjustment
• Also issues with siting of instruments
• All produce a warm bias!!!

6
Station Dropout and Global Temps
A discontinuity in both at the same time
6000 5000 4000 3000 2000
Most were rural stations
7
Number of Missing Months
For the 110 Russian weather stations reporting
weather data continuously from 1971 to 2001, the
total number of missing monthly observations each
year (McKitrick and Michaels)
8
SVERDLOVSK, RUSSIA
9
John Goetz
10
Station Dropout and Missing Data

• Since many of the stations that dropped out were
  the smaller stations, the bias in the remaining
  stations is towards larger metro area stations
  where there is more warmth
• Infilling of data is very difficult. Some of the
  methods used can introduce a warm bias

11
Urban Heat Island Effect

• More and more of the world is urbanized
  (population increased from 1.5 B to 6 B in
  1900s). Cities grow around airports where we
  measure temperatures
• Peer review research suggests adjustment is
  necessary
• Oke (1973) and Hoyt (2002) have shown towns with
  much smaller populations can have warming (town
  of 1000 up to 2C or 3F) especially in winter
• Zhou et al (2005) have shown global data bases
  (for China) not properly adjusted for
  urbanization. Block (2004) showed the same
  problem exists in central Europe.
• Hinkel et al (2003) showed even the village of
  Barrow, Alaska with a population of 4600 has
  shown a warming of 2.2C (3.4F) in winter over
  surrounding rural areas
• Insufficient adjustments introduces a warm bias
  in data

12
Siting Issues

• Pielke and Davey have found a majority of
  stations including climate stations in eastern
  Colorado did not meet WMO requirements for proper
  siting
• Anthony Watts (surfacestations.org) started a
  volunteer effort to document siting issues with
  all stations in US. He and his team is now
  through almost half the stations. The majority of
  stations are poorly or very poorly sited.
• Most of these siting issues introduce a warm
  bias.

13
Contamination of the Data Bases

• Numerous peer-reviewed papers ignored by the IPCC
  and the media have estimated that these problems
  with the observing networks may account for
  30-50 of the warming since 1880 (Pielke and
  Matsui, Lin, et al., Kalney and Cai, de laat and
  Maurellis, Pielke and Davey, Michaels and
  Balling, Michaels and McKitrick)

14
NCDC USHCN Data

• National Climate Data Center maintains a database
  of 1221 stations across the contiguous 48 United
  States. Adjustments have been made to account for
  changes over time in the time of observations,
  missing data, type of instrumentation, changes in
  station siting, and urban warming (Karl, 1988).
• Version 2 (2006) eliminated the Karl urban
  adjustment replacing it with a change point
  detection algorithm

15
USHCN V2 DATA
16
(No Transcript)
17
Factors
18
R2 0.44
19
R -0.14 R2 0.02
20
R2 HadCRUT3v and CO2 0.02 R2 UAH MSU LT and
CO2 0.01

21
Cyclical Factors
22
11 YEAR SOLAR SUNSPOT CYCLE

1950 1960 1970 1980
1990 2000
23
11 year solar cycles vary in their strength on a
longer term on cycles of 22, 53, 88, 106, 213,
429, etc. years
Active cycle periods
1700 1800 1900 2000
Quieter cycle periods
Gleissberg Cycle
24
The Solar Connection

• DIRECT EFFECTS
• Changes due to changes in solar brightness or
  irradiance
• INDIRECT EFFECTS
• UV warming through ozone chemistry high up in low
  and mid latitudes
• Geomagnetic activity /solar wind effects that
  warm higher latitudes and reduce low clouds
  through the reduction of cosmic rays
• Scafetta and West (2007) have suggested total
  solar irradiance or TSI was a good proxy for the
  total solar effect (direct plus indirect) and
  that it could account for 50 or more of the
  warming since 1900

25
R2 0.57
26
Ultraviolet Radiation and Ozone

• Though solar irradiance varies only 0.1 over the
  11 year cycle, radiation at longer UV wavelengths
  are known to increase by 6 to 8 percent with
  still larger changes (factor of two or more) at
  extremely short UV and X-ray wavelengths (Baldwin
  and Dunkerton, JAS 2004).
• Labitzke has shown statistically significant
  differences of temperatures in the lower
  stratosphere into the middle troposphere with the
  11 year solar cycle (warmest at max)
• Shindell et al NASA GISS (1999) showed results
  from a global climate model including ozone and
  UV found UV induced stratospheric ozone changes
  and generated heat that penetrates into the
  troposphere, in effect confirming Labitzkes
  findings

27
High flux implying high UV
28
Pattern fit the findings of Labitzke and
Shindells models
29
Maunder Minimum
Climate scientist Drew Shindell at NASA GISS ran
a model which included ultraviolet and
stratospheric ozone. During the Maunder Minimum,
the Sun emitted less UV, and so less ozone
formed.
30
Cosmic Rays and Low Clouds

• Also an active sun leads to less cosmic rays and
  a reduction in the amount of low level (water
  droplet) cloudiness. Low clouds have a cooling
  effect by reflecting energy back to space.
• This was first proposed by Svensmark (1997),
  confirmed by others like Bago and Butler
  (Astronomy and Geophysics 2000), and Yu and
  Tinsley (AGU 2002).
• Recently Svensmark was able to replicate water
  cloud droplet nucleation in a laboratory with
  cosmic rays (Royal Society Proceedings A 2006)
• Shaviv (2005) estimated that the combination of
  cosmic ray cloud effects and brightness related
  increases in irradiance since 1900 could account
  for 77 of the changes in global temperatures and
  he found the correlation extended back 500
  million years!

31
An inverse relationship
Bago and Butler
32
Cyclical Factors - Oceans

• Multi-decadal cycles in the ocean temperature
  patterns in both Pacific and Atlantic
• Pacific Decadal Oscillation
• Atlantic Multidecadal Oscillation
• IPCC AR4 admits these are natural and driven by
  the long term changes in the thermohaline
  circulation (Atlantic) and in the corresponding
  large ocean circulations in the Pacific
• They admit to regional effects but not global
  impact

33
(No Transcript)
34
PDO - COLD MODE PDO WARM MODE
Mostly El Ninos
Mostly La Ninas
Wolter
35
(No Transcript)
36
Thermal Inertia

• The thermal capacity of water is much higher than
  that of air (not only is it considerably denser,
  but it has about four times the specific heat).
• It is not unreasonable to suppose that, because
  of the huge discrepancy in volumetric thermal
  capacities, the influence of water on air is very
  much greater and more immediate than air on
  water.
• A change in atmospheric temperatures might take
  decades to affect the oceans, but the flip of an
  anomaly in the water has an almost immediate
  effect on the air.

37
(No Transcript)
38
McLean 2008
McLean 2008
39
Cooling events then recent warming from
variations in volcanic activity
( a measure of level of sulfate aerosols)
40
Years with more than ½ STD departures
stratospheric aerosols
More than 1/2 STD Above
More than ½ STD Below
January to December Annual Temperature Anomalies
Data NASA GISS, CDC
Last 8-10 years
41
NOAA CDC
Mean ocean temperature anomalies in the Atlantic
from 0 to 70N
42
Atlantic Multidecadal Oscillation
Correlates with general warmth, statistically
significant in places
43
PDO, AMO and Global Warming

• If PDO relates to more EL Ninos which lead to
  global warming and if AMO relates to general
  global warmth, the sum of the two may be useful
  in identifying warm periods (and when negative
  cold periods)

44
11 Year Mean PDOAMO
Late 1800s to mid 1920s
Late 1950s to late 1970s
1980 to current
Late 1920s to mid 1950s
45
Late 1950s to late 1970s
Late 1800s to mid 1920s
1980 to current
Late 1920s to late 1950s
46
R2 0.85
47
TEMP 52.87 0.37PDO 0.52AMO
TEMP 52.87 0.37PDO 0.52AMO
Divergence
48
With USHCN Version 2
49
(No Transcript)
50
Summary

• Temperatures have warmed especially since 1979
  but less than the global data bases suggest due
  to contamination. Temperature changes are
  cyclical
• The sun and oceans play a much more important
  role in cyclical climate change
• Changes in these factors (PDO turned negative,
  AMO diminishing and solar showing signs of a long
  term minimum) point towards a downturn in
  temperatures ahead

51
(Cliverd et al., 2007)
52
(No Transcript)
53
Future View of Global Warming Scare

• I think the future will view the response of
  contemporary science to global warming as
  simply another version of the fable of The
  Emperors New Clothes (Lindzen 2005)

IPCC SPM
.