Transcript Greenhouse Gas Concentrations

IPCC AR5 WG1 Chapter 1: Introduction
Olivia Clifton
Seminar on IPCC AR5 WG1
Columbia University
01/31/2014
Goals of Chapter 1 of IPCC AR5 WG1
• Focus on the concepts & definitions applied in
the discussions of new findings
• Examine several key indicators for a changing
climate & show how current knowledge of those
indicators compares w/ projections in previous
assessments
• Introduce new human-related emissions
scenarios
• Address directions & capabilities of current
climate science
Key concepts of climate science
• Weather vs. climate
• Climate change
– A change in the state of the climate
• can be identified by changes in the mean &/or
variability of the properties about the mean
– e.g. using statistical tests
• persists for an extended period
– typically decades or longer
Main drivers of climate change
Dominant energy loss
of LWR (aka Infrared
radiation)
Radiative Forcing (RF)
• Measure of net change in energy balance in
response to an external perturbation
– External perturbation can be caused by changes in
atmosphere, ocean, biosphere and cryosphere
• New concept to AR5: Effective RF (ERF)
– Accounts for rapid response in the climate system
– Definition: change in net downward flux at TOA after
allowing atmospheric temperature, water vapor,
clouds and land albedo to adjust
• either SSTs and sea ice cover unchanged or global mean
surface temperature unchanged
Feedbacks
• Mechanisms exist in the climate system that either
amplify (+ feedback) or diminish (- feedback) effects
of a change in climate forcing (Le Treut et al., 2007)
– Critical: Timescales can be hours or decades & centuries
• Example of a + feedback: atmospheric water vapor
increase in surface temp --> increase in atmospheric H20 (a powerful
GHG) --> increase in GHG effect --> increase in surface temperature
Climate feedbacks & timescales
+/- refers to
mechanism
and how it
feeds back on
rising
temperature
and rising CO2
Large range of
timescales for
different
feedbacks!
Transient vs. Equilibrium Model
Simulations
• Equilibrium
– Allow climate model to adjust fully to a specified
change in Radiative Forcing
– Convey difference between initial and final states
of model-simulated climate
• Transient
– Apply changes in Radiative Forcing gradually over
time
– More realistic
“Climate change commitment is defined as the
future change to which the climate system is
committed by virtue of past or current forcings.”
– Components of climate system respond on a large
range of timescales
– If anthropogenic emissions immediately ceased or
climate forcings immediately became fixed, climate
system would continue to change until equilibrium
– Paleoclimate data can help us to understand slow
equilibrium processes
Natural Variability
• Observe periodic and chaotic variations on a large range of spatial and
temporal scales
– even in the absence of external forcing
• Simple distributions (e.g. unimodal or power law) sometimes represents this
variability
– However, many components of the climate system also exhibit multiple states
• glacial-interglacial cycles, ENSO
• Movement b/w states can occur due to natural variability or external forcing
• Relationship b/w variability, forcing, and response reveals complexity of
dynamics of climate system
• Hysteresis: concept of irreversibility in the climate systems
• Trends in observations during short-timescale periods (decades) can be
dominated by natural variability in Earth’s climate system (Hawkins and Sutton,
2009)
– Climate model experiments
• In most of model simulations, an “episode” does not necessarily occur as a duplicate of & with
same timing as the observed “episode”
Multiple lines of evidence
•
Careful analysis of observational records of the atmosphere, land, ocean &
cryosphere
–
•
•
•
in situ, ice core, instrumental observations, satellites
Conceptual and numerical models of Earth’s climate system
Detection & Attribution: assessing changes occurring in climate with statistical
tools to test model vs. obs.
Historical sources, natural archives, proxies for key climate variables
– Quantitative with respect to past regional-to-global climate and atmospheric
composition variability
– Reconstructions tell us about responses of climate system to external forcings
and internal variability on different timescales
AR5: new info on external forcings caused by variations in volcanic and
solar activity; reconstructed paleoclimate temps and attributions to past
variations in external forcings
How well do the projections used in the past
assessments compare with obs. to date?
Chapter &
section in AR5
that assesses
this indicator of
change
Color Key to Indicators of change: Temperature, hydrological, others
How well do the projections used in the past
assessments compare with obs. to date?
Color Key to Indicators of change: Temperature, hydrological, others
Estimated changes in the observed globally & annually avg sfc temp anomaly relative to 19611990 compared with the range of projections from previous IPCC assessments
Range
of
results
at 2035
for each
scenario
Anomalies calculated
from 1961-1990 mean
AR4: Add’l measure of natural variability; earlier projections based on models of intermediate
complexity; previous assessments have lacked some or all aerosols and natural variability
Observed globally & annually averaged CO2 concentrations in ppm since 1950 compared with
projections from previous IPCC assessments
Range
of
results
at 2035
for each
scenario
Observed globally & annually averaged CH4 concentrations in ppb since 1950 compared with
projections from previous IPCC assessments
Range
of
results
at 2035
for each
scenario
Methane stabilizes 1999-2006,
then increases again in 2007;
SRES scenarios developed in
2000 don’t capture this trend
Observed globally & annually averaged N2O concentrations in ppb since 1950 compared with
projections from previous IPCC assessments
Range
of
results
at 2035
for each
scenario
Observed trends of nitrous
oxide tend to be in lower part
of projections for previous
assessments
Extreme Events
• A definition: rare or rarer than the 10th or 90th
percentile of a probability density function estimated
from the observations; rare at a particular place and/or
time of the year
• At present, single extreme events cannot generally be
directly attributed to anthropogenic influence
– In some circumstances, the change in likelihood for the
event to occur was attributable to accounting for observed
changes in climate
– For some climate extremes, such as drought, floods and
heat waves, several factors, such as duration and intensity,
need to be combined to produce an extreme event
(Seneviatne et al., 2012)
(Gaussian)
PDFs of daily temperature (~ Gaussian)
and daily precipitation (~ skewed)
- - - previous distribution
----- changed distribution
(Skewed)
In a skewed distribution, a change in the mean of the
distribution generally affects its variability or spread.
An increase in precipitation would thus lead to an
increase in heavy precipitation extremes and vice
versa. Furthermore, climate change may alter the
frequency of precipitation and the duration of dry
spells between precipitation events.
“Extremes” Table shows change in confidence level for
extreme events based on prior IPCC assessments
Green =
extreme
event
discussed in
all 3 reports
Climate Change Indicators
• Sea Level (ocean warming & land ice melt)
– Direct observations: tide gauges (150 yrs) and satellite radar altimeters (20 yrs)
– AR4 and SREX say global climate change is likely cause of sea level rise even with regional
variability from non-uniform density change, circulation changes, & deformation of ocean
basins
– Long-term sea level rise has decadal & multi-decadal oscillation, but 20th century sea level still
> 19th century
• Ocean Acidification (ocean uptake of CO2)
– Observed decrease in ocean pH resulting from increasing CO2 has significant impact on
chemistry of sea water
– Due to the increased storage of carbon by the ocean, ocean acidification will increase in future
-> potentially serious threats to health of world’s ocean ecosystems
• Ice (amount of ice on land & ocean)
– Summer 2012 lowest Northern Hemisphere sea ice extent on record
– AR4 finds no consistent trends for Antarctica sea ice, but more recent studies indicate a small
increase
– Since AR4, improvements in techniques of measurements and understanding of the change
Estimated changes in observed global annual mean seal level
since 1950 relative to 1961-1990
Range
of
results
at 2035
for each
scenario
Earlier models had greater uncertainties in modeling the contributions due to limited observational
evidence and deficiencies in theoretical understanding of relevant processes. Also earlier
assessments don’t include unforced or natural interannual variability.
Uncertainty
• Scenario uncertainty due to uncertainty of future emissions of
GHGs and other forcing agents
• “Model uncertainty” associated with climate models
– Ambiguous term, IPCC AR5 sets definitions
• Model spread: range of behaviors observed in ensembles of climate model
• Model uncertainty: describes uncertainty about the extent to which any
particular climate model provides an accurate representation of the real
climate system; arises from approximations required in the development of
models
• Internal variability and initial condition uncertainty
– AR5: square brackets show 90% uncertainty interval
• interval likely to have 90% likelihood of covering the value that is being
estimated
• Boundary condition uncertainty for the assessment of historical and
paleoclimate simulations
Treatment of Uncertainty in IPCC AR5
A combination of different
methods, such as
observations and modeling, is
important for evaluating
confidence level.
Qualifier “likelihood”
expresses a probabilistic
estimate of the occurrence of
a single event or of an
outcome
Development of capabilities of observations
# of satellite
instruments
assimilated into
the European
Centre MediumRange Weather
Forecasts;
demonstrates
five-fold increase
in usage of
satellite data over
this time
Capabilities in Global Climate Modeling; Development of climate
models over the last 35 years
Continuing increase in horizontal and vertical
resolution; especially evident in refined ocean grids
below
Size of cylinder
represents complexity
and range of processes of
each aspect
--> Representation of Earth System processes are much
more expensive and improved, particularly for the
radiation and the aerosol cloud interactions and for the
treatment of the cryosphere
Historical and projected total anthropogenic RF (W/m2)
relative to ~ 1765 (preindustrial) between 1950 and 2100
AR5, designed
for CMIP5
Previous IPCC
Since AR4, the incorporation of ‘long-term’ paleoclimate simulations in the CMIP5 framework has allowed incorporation
of information from paleoclimate data to inform projections.
Description of Future Scenarios
Total RF (anthro+natural; W/m2) for RCPs and ECPs
Description of Future Scenarios
GHG Concentrations for RCPs and ECPs
Description of Future Scenarios
Equivalent a) CO2 concentration and b) CO2 emissions (no
land use) for RCPs and ECPS and some SRES
Description of Future Scenarios
Anthropogenic
BC emissions
Anthropogenic
NOx emissions
Anthropogenic
SOx emissions
If understanding of the climate system has increased, why
hasn’t the range of temperature projections been reduced?