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Lecture #1
Overview of Climate Forcing
Factors
Climate Forcing Factors
• Changes in solar luminosity and orbital
parameters
• Greenhouse gas variability—water vapor, CO2,
Methane.
• Changes in surface properties
• Differential temporal responses to external
forcing by the atmosphere and oceans.
• Natural and human-induced changes in aerosols
and dust--volcanoes, desert dust, pollutants
Climate Forcing
• Defined as an energy imbalance imposed
on the climate system either externally or
by human activities
• Radiative forcing: a change in energy flux at the
tropopause[watts per square meter]
• A non-radiative forcing is a climate forcing that
creates an energy imbalance that does not
immediately involve radiation
• A direct forcing is a climate forcing that directly
affects the radiation budget of the earth’s climate
system
• A climate feedback is amplification or
dampening of the climate response to a specific
forcing due to changes in the atmosphere,
oceans, land, or continental glaciers
Spectrum of energy emitted by the
sun resembles blackbody at 5900K
• Peak at 0.470 micrometers
• Absorption bands
Earth’s radiation
• Peak between 10 and 15 micrometers
• Absorption bands
The Greenhouse Effect
• The major gases that absorb longwave radiation
are CO2, methane, and nitrous oxide. These are
what are referred to as greenhouse gases.
• Water vapor is actually the dominate
greenhouse gas. To obtain substantial
greenhouse warming the oceans must warm
and evaporate more water vapor in the air to
cause a positive feedback.
• Clouds are also major greenhouse warming
agents.
• Clouds also reflect solar radiation(cool)
• Globally clouds contribute to a net cooling as
reflection of solar radiation dominates LW
absorption.
• Because clouds are poorly treated in
General Circulation Models (GCMs) their
influence on climate is a major uncertainty
in climate prediction.
The solid line depicts monthly concentrations of atmospheric CO2 at Mauna Loa Observatory, Hawaii. The yearly
oscillation is explained mainly by the annual cycle of photosynthesis and respiration of plants in the northern hemisphere. The
steadily increasing concentration of atmospheric CO2 at Mauna Loa since the 1950s is caused primarily by the CO 2 inputs from
fossil fuel combustion (dashed line). Note that CO2 concentrations have continued to increase since 1979, despite relatively
constant emissions; this is because emissions have remained substantially larger than net removal, which is primarily by ocean
uptake. [From Scheraga, Joel and Irving Mintzer, 1990: Introduction. From Policy Options for Stabilizing Global Climate, D.A.
Lashof and D.A. Tirpak, Eds. U.S. Environmental Protection Agency, Office of Policy, Planning and Evaluation. Hemisphere
Publishing Corp. New York. ]
From Max Beran.
Atmospheric concentrations of carbon
dioxide, methane and nitrous oxide over
the last 10,000 years (large panels) and
since 1750 (inset panels). Measurements
are shown from ice cores (symbols with
different colours for different studies) and
atmospheric samples (red lines). The
corresponding radiative forcings are shown
on the right hand axes of the large panels.
[From IPCC, 2007]
• IPCC estimates greenhouse gases
contribute to 2.3[2.07 to 2.5] W m-2.
Summary
Changes in solar luminosity and
orbital parameters
Changes in solar luminosity
• There are observed changes in solar luminosity which
account for something like 0.12[-0.4 to 00.0] W m-2 which
is small compared to the 2.3 W m-2 estimated for
Greenhouse gases. These changes are related to
changes in sunspot activity, solar diameter, and umbral
penumbral ratio.
• Nonetheless there are hundreds of statistical studies
which suggest a correlation with temperature and other
weather parameters that is far stronger than the
measured changes in luminosity imply. Is this just
statistics fooling us or is there some unknown amplifier?
• Some studies find that these parameters correlate with
cloud cover which would provide such an amplifier. But
convincing physical arguments have not been made.
Cosmic Ray Flux Variations
• Dozens of recent papers
relate(statistically) variations on cosmic
ray fluxes to global climate
• These studies show a positive correlation
between cosmic ray fluxes and cloud
cover(ie. contributing to warming)
• The argument is that high cosmic ray
fluxes generate ions which can then serve
as cloud condensation nuclei(CCN).
• The problem is, CCN are large(greater than 0.1
micrometer), soluble particles
• Ions, are several orders of magnitude smaller in
size and are not soluble so they do not activate
cloud droplets at real cloud supersaturations. To
become CCN they must coalesce with solvable
aerosols and have sulfates condense on them
which is not all that probable
• Moreover, cloud cover is mainly controlled by
dynamics(ascent and adiabatic cooling) and not
by concentrations of CCN and certainly not total
aerosol concentrations!
(19) The variations in sun activity reflect temperature events: Dalton minimum (Dm),
Maunder minimum (Mm), Spörer minimum (Sm), Wolf minimum (Wm), Oort minimum (Om),
and Medieval Maximum (MM).
Changes in orbital parameters
• The earth undergoes natural oscillations in
orbital parameters such as the eccentricity
of the orbit, the axial tilt, and the precession
of the equinoxes. The theory of climate
change related to variations in these
parameters is called the Milankovitch
theory and it predicts the earth will be
gradually moving into an ice age in the next
5000 years.
The Milankovitch theory
Changes in surface parameters
• The net albedo of Earth is determined by percent
cover of oceans vs. land, glacial coverage, landsurface vegetation vs. deserts, etc. In addition, the
latter land-surface parameters influence surface
temperatures through changes in sensible vs. latent
heat transfer.
• Human activity alters the land-surface parameters
through deforestation, agriculture, and urbanization.
• IPCC estimates these contribute to -0.2[-0.4 to 0.0]
W m-2 forcing
Differential temporal responses to
external forcing by the atmosphere
and oceans.
• The atmosphere and the deep oceans have
grossly different responses to changes in
external forcing.
• The atmosphere can respond on time scales of
days to months with lingering affects of about 1
year
• The ocean responds on time scales of 10’s of
years to even 100 years
• This leads to a large natural variability of the
climate system and GCMs are unable to
represent or predict this variability well
Natural variations in aerosols and dust
• Volcanoes are a major contributor to upper
tropospheric and lower stratospheric aerosols.
These particles block sunlight contributing to
surface cooling and can reside from a single
volcano for several years and have even longer
influences through cooling of the oceans.
• The period of warming during the 1930’s has
been attributed to a period of low volcanic
activity.
• Predictability of volcanic activity is lacking!
Natural variations in dust
• Deserts and Sahalian zones in particular are large
sources of dust. These particles absorb solar radiation
and thereby warm the air layer they reside in and cool
the surface. Warming the air layer stabilizes the layer
reducing convection. Dust also alters cloud properties
appreciably. Human activity contributes to dust as well.
Not predicted well!
• If greenhouse warming contributes to desertification,
increases in surface wind strength, then additional dust
formation counters the warming.
• Meteor collisions with earth also contribute to dust and
have been blamed for the demise of dinosaurs. No
predictability!
Anthropogenic aerosols
• Air pollution aerosols contribute to cooling of the earth’s
surface by either reflecting solar radiation or directly
absorbing solar radiation which stabilizes the air layer
and cools the surface(called the direct aerosol effect)
• They also modify cloud properties (called indirect effect)
so that polluted clouds reflect more radiation (cooling
effect).
• They also modify the precipitation forming process(called
second indirect effect) which is treated in GCMs as
enhancing cloud albedo. But cloud resolving models
often exhibit reduced cloudy albedo when polluted.
• The indirect effect, especially through altering
precipitation is a major source of uncertainty in predicting
climate. In fact the treatment of clouds is a major source
of uncertainty.
More elaboration on aerosols in
later lectures
Natural Variability
• The climate system is known to have large
natural variability but the quantitative
assessment of that variability is difficult.
• Sources of variability include atmosphere/ocean
different response times such that they are
never really in equilibrium.
• Others are related to unknown or not quantified
forcing mechanisms.
• Quantification of natural variability is essential to
determine if human related forcing are greater
than natural variability.
• How much of observed climate change in
the 20th century is due to greenhouse
forcing as opposed to natural forcing?
• How significant, compared to past natural
fluctuations are the changes we now
observe and expect in the future?
(5), The hockey stick according to Mann, M.E., R.S. Bradley and M.K. Hughes (1999) (8) Blue,
Black: reconstructions from tree rings, corals, ice cores, etc. Red: direct measurements from
temperature stations as from 1860.
(3), The temperature curve of the hockey stick combined with the atmospheric curve of CO2
concentration. The figure suggests that the sharp temperature rise since 1860 was caused by CO2.
McIntyre and McKitrick(2003)
• They criticize the Mann et al
reconstructions for:
• Deficiencies in the data used
• Irregularities in the data
• Methodology of analysis
(6), the hockey stick and the corrected temperature curve (green line) by
McIntyre between 1400 and 1980. The green curve is not intended to
indicate the true temperature, but to show the result of a correct use of
data.
• The thing that immediately struck me was the absence of
a strong Midieval Warm Period(800-1200AD) or Little Ice
Age( 1500-1850AD) in Mann’s analysis!
• They argue these were regional not global phenomena
• But other studies have found the MWP in Europe(Lamb,
1965; Shindell et al., 2001), Greenland(Dahl-Jensen et
al,1998), Africa(deMenocal et al, 2000; Holmgren et al,
2001), North America(Campbell et al,1998; Li et al,2000;
Petersen,1994; Shabalova and Weber,1999), South
America(Irionda et al,1993; Villabala,1994) and
Asia(Hong et al, 2000; Liu et al, 1998)
Juckes et al(2007) reconstructions
• They used other proxies other than just
tree rings
• There results seem to confirm the Mann et
al analysis
Problems with reconstructions:
• Proxie data such as tree rings deminish with
time: 22 extend back to AD 1400, 12 extend to
AD 1000(7 in N Hemisphere)
• Cook et al(2004) conclude reconstructions
bases largely on tree-rings should be treated
with caution earlier than AD 1200.
• Proxies are affected by factors other than
temperature which are not fully understood(ie,
Excessive Bristlecone pine growth in 20th
century could be due to CO2 fertilization or??)
• Can we say then that 20th century warming
is unprecedented compared to previous
natural periods like the Medieval Warm
Period?
Warren Washington Argues that Natural
Variations do not Explain Observed
Climatic Change
• Climate models with
natural forcing
(including volcanic
and solar) do not
reproduce warming
• When increase in
greenhouse gases is
included, models do
reproduce warming
• Addition of increase in
aerosols (cooling)
improves agreement
There is evidence that the climate
is cooling in the 21st century
Ocean Heat Content:
• This is a better measure of climate
variability
• But records are of limited duration
Note flattening
2004-2008
Akasufo argues that recent
warming is a linear warming since
the little ice age with natural
variations
Loehl(2004)
• He fit time series data for “inferred” temperature
from Sargasso Sea SST estimates and from
stalagmites in a cave in South Africa to a simple
periodic set of models
• He fit these periodic models to 3000-year
temperature time series with minimal dating
error.
• Tree ring data were not used because of dating
uncertainties
• None of the models used 20th or 21st century
data
• The results clearly show the Medieval
warm period and the Little Ice Age
• 6 out of 7 of the fit models show a
warming trend over the 20th century similar
in timing and magnitude to the N
Hemisphere instrumental time series.
• One of the models passes right through
the 20th century data
• The results suggest that the 20th century
warming trends are a continuation of past
climatic cyclical patterns.
• Results are not precise enough to partition
20th century warming into natural vs manmade causes
• Nonetheless a major portion of the
warming could be a result of natural
causes
Conclusion
• As far as I am concerned the jury is still
out as to whether recent climate trends are
due to human activity or due to natural
variability associated with other forcing
parameters or internal variability of the
atmosphere/ocean/cryosphere.