Climate Modeling
Univ. of Alaska-Fairbanks Summer School
July 16, 2012
Joe Barsugli
CIRES, University of Colorado,
affiliated with NOAA/ESRL/PSD
and Western Water Assessment
The Basic Narrative of Climate Change
We are changing the Carbon Cycle
Which causes an imbalance in the amount of
energy reaching the Earth
Which warms the planet
Energy Balance
Eventually feeding back on the
carbon cycle
Temperature
Because the Energy Balance and the
Water Cycle involve the winds and ocean
currents -- they are changed too,
potentially changing all aspects of
climate, including clouds.
Which amplifies the climate change,
mainly because of increased water vapor
Water vapor
Which changes the water cycle
Goals
Climate Science
•What is the basic narrative of climate change science?
Emissions Scenarios
•What is an emissions scenario?
•Which emissions scenarios are used by climate modelers?
•What are the main factors causing the Earth’s energy imbalance?
•What are the important similarities and differences among the scenarios?
Climate Models
•What is in a climate model?
•What does the hydrologic component of a climate model look like?
•What are the basic methodologies of making climate model projections?
•What are the known biases in climate model simulations?
•What will the future of climate modeling bring?
Emissions
from Fossil
Fuel +Graphics
Cement
Climate Change:
The Usual
TOTAL ~9 Gt C/yr
Fossil Fuel Emission (GtC/y)
9
8
Emissions
7
6
5
4
3
2
1
0
Atmoapheric [CO2] (ppmv)
1870 1890 1910 1930 1950 1970 1990 2010
4001850
1850 1870 1890 1910 1930 1950 1970 1990 2010
380
[CO2]
CO2 emissions  accumulation of
CO2 in atmosphere
Pre-Industrial: 270 ppm
2012: 393 ppm
360
340
320
2 ppm/year
300
280
0.81850
Warming of about 0.8C
(1.5F) since preindustrial climate
Temperature (deg C)
0.6
1870
1890
1910
1930
Temperature
1950
1970
1990
2010
0.2 C/decade
0.4
0.2
0
-0.2
-0.4
-0.6
1850
1870
1890
1910
1930
1950
Data Source: G. Marland, T.A. Boden, R.J. Andres, and J. Gregg at CDIAC; Slide from global Carbon Project ; NOAA ESRL;
1970
1990
2010
IPCC “SRES” Emissions Scenarios
•IPCC Special Report on Emissions Scenarios
http://www.ipcc.ch/ipccreports/sres/emission/index.htm
SRES scenarios…
• Were developed because previous IPCC assessments did not make a
clear distinction between uncertainty among climate model forecasts for a
given scenario and uncertainty in the emissions trajectory itself.
•“…are alternative images of how the future might unfold…”
•Differ in their assumptions regarding “demographic development, socioeconomic development, and technological change.”
•Are given memorable names like “B1”, “A1B”, and “A2”
SRES (2000) CO2 Emissions Scenarios
IPCC 5th assessment scenarios will probably include some scenarios with higher emissions.
Emissions Scenarios: Resulting CO2
Concentrations
Fossil Fuel
Emissions: Actual vs. IPCC Scenarios
0
1850
1900
1950
2000
2050
2100
10
Fossil Fuel Emission (GtC/y)
9.5
9
8.5
8
7.5
CDIAC
IEAall
A1B(Av)
A1FI(Av)
A1T(Av)
A2(Av)
B1(Av)
B2(Av)
7
6.5
6
5.5
5
1990
1995
2000
2005
Raupach et al 2007, PNAS (updated); Slide from global Carbon Project
2010
RCPs, the new SRES
scenarios
•
•
•
•
Stands for “Representative Concentration Pathways”
Derived from emissions scenarios much like SRES concentrations
were… so that Earth System Models and “classic” Atmosphere Ocean
GCMs could run comparable scenarios.
Are named by the approximate radiative forcing strength at the year
2100, in W/m^2.
Policy (mitigation) assumption are made (SRES did not make any
policy assumptions)
RCPs are the new Emissions Scenarios
RCP8.5
RCP6.0
RCP4.5
RCP2.6
Radiative Forcing: Imbalance in longwave + solar radiation caused by
changes in greenhouse gas and aerosols relative to pre-industrial
conditions.
For comparison: Doubling CO2 ~ +4 W/m^2
Average insolation at top of the atmosphere ~ 340 W/m^2
Adapted from vanVuuren et al, 2011
RCP <-> SRES
Note: different baselines used)
Imbalance in radiation (solar + longwave (infrared) caused
by changes in GHG relative to pre-industrial conditions
For reference.. Doubling CO2 ~ +4 W/m^2
vanVuuren et al, 2011
Average insolation ~ 340 W/m^2
Which affects the Earth’s Energy Balance …
Radiative Forcing at Present (year 2005)
Source: IPCC AR4 WG1 SPM
Global Mean Surface Air Temperature Projections (relative to 1980-1999)
2040 2070
Source: IPCC AR4 WG1 SPM
Bottom Line on Emissions Scenarios
•Scenarios are not forecasts, but can be useful planning tools.
•There are no probabilities associated with the occurrence of these
scenarios.
•The emissions scenarios provide standard parameters for climate
modelers to make intercomparison of their projections easier.
• Scenarios B1, A1B, and A2 have become de facto “low”, “medium”
and “high” emissions scenarios for the CMIP3/AR4 models based on
year 2100 cumulative emissions, and were chosen by climate modeling
centers to intensively study.
•CMIP5 RCP’s are in many ways comparable to the SRES scenarios.
•RCPs 4.5 6.0 and 8.5 will probably be taken as the new “low” medium”
and “high” scenarios.
•Earth System Models introduce another level of complexity and
uncertainty. Radiative forcing in an Earth System model under a RCP
emissions may differ from an AOGCM using the concentrations from the
RCP
Bottom Line on (Global Mean) Climate Projections
•
•
•
•
The global mean climate responses to the different SRES scenarios
start to diverge after about 2030. Before that, climate change is similar
in all scenarios. By 2040 the scenarios have diverged somewhat. By
2070 B1 has appreciably diverged from the others. By 2100, all three
scenarios are distinct. However the full estimate of uncertainty from all
sources still has a large degree of overlap in year 2100.
For a given climate model, the temperature and precipitation
changes in the different scenarios differ mainly in magnitude and
timing.
For a given scenario, there is significant variation in temperature and
precipitation changes among the different climate model simulations
due to differences in model formulation.
CMIP5 – more divergence among radiative forcing, esp if you consider
RCP2.6 and RCP8.5. In the latter half of the century there will be
more divergence among simulations because of carbon-cycle
feedbacks.
Choice (or not) of Emissions Scenarios
The projected climate is contingent on the choice of emissions.
Emissions scenario is not a big deal for regional climate out to midcentury.
Emissions scenario becomes a big deal by the end of the century.
Global
Regional (UK)
variability
emissions
model
emissions
model
Fraction of uncertainty due to various sources Hawkins and Sutton, 2009
Review and Questions
Climate Science
•What is the basic narrative of climate change science?
•How are we changing the carbon cycle?
Emissions Scenarios
•What is an emissions scenario?
•Which emissions scenarios are used by climate modelers?
•What are the main factors causing the Earth’s energy imbalance?
•What are the important similarities and differences among the SRES
scenarios?
Climate Models
•What is in a climate model?
•What does the hydrologic component of a climate model look like?
•What is the basic methodology of making climate model projections?
•What are the known biases in climate model simulations?
•Why is downscaling necessary?
•How do climate models differ in their projections for Western/Central US.
•What will the future of climate modeling bring?
Breakout Exercise 1: Why
use climate models to inform
local decisions on adaptation?
Break into groups, including instructors….
Your goal is to explain to a stakeholder why climate
models are used to inform the future.
Components of Climate Models
ATMOSPHERE
SEA ICE
LAND SURFACE
(Physical)
OCEAN
Atmosphere-Ocean GCM
LAND
OCEAN
Biogeochemical Model
(incl. Carbon Cycle)
DYNAMIC
VEGETATION
ATMOSPHERIC
CHEMISTRY
Earth System Model (ESM)
•AOGCM – Atmosphere/Ocean General Circulation Model
•Earth System Models
•Problems with biases being passed from one component to another
•IPCC Fifth Assessment is looking at both ESM and Atmosphere-Ocean
GCMs
Numerical Solution: Timesteps and Gridboxes
Solved at discrete time intervals:
Tt +1 - Tt -1
Dt
wind
Typical timestep: 5 min - 20 min.
Typical grid size (resolution):
Horizontal ~ 60-180 mi (100-300 km)
Vertical ~30 layers of varying depth
Model Topography: GCM vs. RCM Need for Downscaling!
feet
NCAR CCSM 3.0 T85 (1.4ox1.4o)
feet
WRF Regional Climate Model at 48km resolution
Some CMIP5 Atmosphere Model Resolutions
AOGCM:
NCAR CCSM4 (1.25 lon x 0.9 lat)
MIROC4H (0.56X0.56; T213)
MIROC5 (1.4X1.4)
HadCM3(N48) (3.75 x 2.5)
MRI CGCM3 (1.1X1.1)
CNRM CM5 (1.4 X 1.4) (TL127)
CANCM4 (2.8 X 2.8;T63)
ESM:
HadGEM-CC (1.875 x 1.25)
GFDL ESM2M (2.5 x 2.0)
MIROC-ESM-CHEM (2.8X2.8)
Compare this to CMIP3, where the median model resolution was around 3-degrees, the
highest (one) was at ~1 degree, and the next highest was NCAR CCSM3 was at 1.4
degrees. The coarsest were 4x5 degrees.
Technical note: Take model resolutions with a small grain of salt. Resolution is not
directly comparable between models with different numerical schemes.
Numerical Solution: Parameterization
• Most of the physical process are at scales smaller than the grid
spacing
– Need to represent the cumulative efect of sub-gridscale
processes on the grid in terms of gridscale parameters.
– e.g. convective precipitation = f(T, moisture, winds)
• Atmosphere
– clouds:
• precipitation & radiation
– boundary layers
• Surface fluxes, turbulent energy
• Ocean
– Mixing by eddies
– Vertical mixing in upper ocean
– Flow over sills => deep water formation
• Based on theory and observations
• Parameters “tuned” (usually globally) to get reasonable climate
Hydrologic Component of Land Surface Model
NCAR CCSM3
Biophysical Component of Land Surface Model
NCAR CCSM3
Hydrologic Component of Land Surface Model
GFDL CM2.0
Hydrology in Climate Models
If the climate models have hydrology component in their land
surface model, why do we need to run the output through
another hydrology model?
•
•
•
•
•
Each land surface model has a different formulation -- some simple,
some sophisticated.
In even the most sophisticated global model, many (most?) topographic
effects are lacking.
Sub-grid variations in land surface characteristics only partially
represented.
Small basins not accounted for in routing models.
Land surface models in climate models have not (generally) been
calibrated for specific regions.
Emissions Scenario (B1, A1B, A2; RCPs)
GHG Concentrations (IAM)
Climate Model (AOGCM)
NCAR CCSM UKMO-HadCM3
Run1 … Run 4
Earth System Model
NCAR CESM
HadGEM
Different numbers of runs for each model and scenario….
Climate Prediction vs. Projection
Climate Projections (IPCC AR4)
•estimate the forced signal due to GHG and other radiative forcing agents.
•are obtained from free-running GCM simulations that are not periodically
restarted from observed conditions.
•compare the climate “with” and “without” GHG emissions, etc..
Climate (decadal) Prediction (to be Included in IPCC AR5)
•Starts from the observed conditions (a process called data assimilation- very
difficult for the ocean!)
•Attempts to predict the actual trajectory of the decadal variations in climate
•It is an open question how much skill there is on decadal time scales.
Blue curve: free-running model
Red blurs: ensemble of
predictions for three starting
dates.
Black curve: observed
Globally averaged annual mean surface temperature anomaly (relative to 1979–2001). Smith
et al. 2007)
Modeling Methodology: Bias Correction is needed!
20th Century
Simulations
Climate Model
Projections
Bias
Correction
Observations
Bias-corrected
Projections
In many IPCC figures, a simple bias correction is (implicitly) applied:
•Temperatures are shown relative to a reference climatology for each
model.
•Precipitation is shown as a percent change from a reference
climatology for each model.
Resolution and Climate Model Evaluation
Which spatial features of the climate do we expect the 20th
century model simulations to reproduce, and which can’t they
reproduce, even in theory?
CAN’T REPRODUCE EXACTLY
SHOULD REPRODUCE
•The climate statistics at a given
observational site
•The average regional climate for
homogeneous regions.
•The average climate in mountainous
regions (snow may be badly
misrepresented due to elevation effects)
•The “large-scale” climate trends in
mountainous regions
•The different climates in Denver, South
Park, and Grand Junction
•The qualitative changes in climate for
broad regions as one crosses the Rockies.
Chaos and Climate Model Evaluation
Which temporal features of the climate do we expect the 20th
century model simulations to reproduce, and which can’t they
reproduce, even in theory?
CAN’T REPRODUCE
SHOULD REPRODUCE
•The weather on May 4th, 1953, or any
other given day.
•The climatological averages and other
statistics for the observed record.
•The 1997-8 El Nino or other specific El
Nino/La Nina Events
•The statistics of El Nino/La Nina and other
tropical disturbances such as the MaddenJulian Oscillation.
•A specific warm decade or cold decade if it
was due to internal modes of variability
•The statistics of internal decadal and multidecadal climate fluctuations. Decadal or
multi-decadal changes forced by volcanic,
solar, and GHG variations.
Precipitation and Temperature Bias
Percent precipitation error (a,b) and absolute temperature error (c,d) of the ensemble
average of 18 models in relation to the University of Delaware climate data (1979- 99).
Panels on the left show the mean error for May to October; panels on the right, November
to April. (McAfee, Russell, and Webb, 2012 )
Koppen Classification bias (as a proxy for ecosystem types)
OBS
Bias-Adjusted
Projection
Model
Model
Projection
. Köppen classification maps produced using (a) University of Delaware temperature and
precipitation (1979-99), (b) the ensemble of 18 models (1979-99), using (c) adjusted 207999 ensemble climate and (d) unadjusted 2079-99 ensemble projections. See Table 1 for
Köppen type descriptions. (McAfee, Russell and Webb, 2012)
Model Biases: Streamflow
Green R. ?
???
Colorado R.
~72 BCM/yr
(obs ~ 19)
River routing model output: NCAR CCSM4.0 20th Century Average
Only cells with > 5MAF/year are shown.
Model Biases: The Regional Picture
COLD
Source: IPCC WG1 Ch. 11, 11 Supp. And Climate Change in Colorado
WET
ENSO Spectra in CMIP3 GCMs
GFDL model ENSO
3x too strong
NCAR CCSM has
2-year ENSO
HADCM3 is close
Gray band is obs.
uncertainty.
Individual Model
Projections: Temperature
Source: IPCC WG1 11 Supp.
Individual Model
Projections: Precipitation
Source: IPCC WG1 Ch. 11 Supp.
Trends in Global Climate Modeling
Increased Complexity -- more
components of the Climate System (more
sources of uncertainty!) Chemistry is
expensive!
1990
1995
Increased Resolution; but
computational cost increases rapidly!
We won’t be able to directly resolve
cloud-scale processes (1km) on a
global scale for long climate runs for
quite a while.
2001
2007
Trends in Global Climate Modeling
• Neither of these guarantee that the model simulations will
improve! We also need better scientific understanding…
• Some personal opinions…
– ENSO/Tropical Ocean changes -- I am optimistic based on
increasing knowledge of oceanic processes .
– MJO -- I am less optimistic, based on progress so far.
– PDO and other decadal variability … problematic!
– Mean climate biases over land -- increased resolution, better land
surface models will help, but the remote influence of oceanic biases
may remain.
Why use climate models –
followup exercies
• Take the reasons we all came up with
and write a 1 paragraph statement
about why(or why not) climate models
are a useful source of information for
adapation studies. [ we will leave the
questions about downscaling for
another day!]
End
Why Use Climate Models?
To create plausible, physically based
scenarios, reflecting the current state of
scientific understanding, to inform
planning for the future.