METR112-Climate Modeling - PowerPoint PPT Presentation

1 / 42
About This Presentation
Title:

METR112-Climate Modeling

Description:

Basic concepts of climate system Numerical method and parameterization in the model Evaluation and sensitivity study of the model METR112-Climate Modeling – PowerPoint PPT presentation

Number of Views:182
Avg rating:3.0/5.0
Slides: 43
Provided by: metSjsuE
Category:

less

Transcript and Presenter's Notes

Title: METR112-Climate Modeling


1
METR112-Climate Modeling
  • Basic concepts of climate system
  • Numerical method and parameterization in the
    model
  • Evaluation and sensitivity study of the model

2
Question from last week Sun Spot are
relatively dark areas on the surface of the Sun
where intense magnetic activity inhibits
convection and so cools the surface. The number
of sunspots correlates with the intensity of
solar radiation
Foukal et al. (1977) realised that higher values
of radiation are associated with more sunspots

because the areas surrounding sunspots are
brighter, the overall effect is that more
sunspots means a brighter sun
3
How can you know the future climate and climate
change?
4
Climate system
http//www.usgcrp.gov/usgcrp/Library/nationalasses
sment/overviewtools.htm
5
Atmosphere composition
Even though with small percentage, trace gases
such as CO2 and water vapor act as very important
gas composition in the atmosphere
6
Atmosphere vertical structure
Troposphere where most weather processes take
place
Note the height of tropopause is not the same
everywhere. The tropopause is lower in high
latitude than in tropics
7
Atmosphere energy budget
(Kiehl and trenberth 1997)
8
Atmosphere general circulation
  • Hadley cell
  • Trade wind
  • Westerlies
  • ITCZ
  • Subtropical high
  • Strom track region
  • Polar Hadley cell

9
Ocean critical roles in climate system
Physical properties and role in climate
  • The biggest water resource on earth
  • Low albedo ? excellent absorber of solar
    radiation
  • One of the primary heat sources for atmosphere
  • High heat capacity ? reduces the magnitude of
    seasonal cycle of atmosphere
  • Important polarward energy transport
  • Large reservoir for chemical elements for
    atmosphere

10
Ocean salinity distribution closely relates to
precipitation evaporation
From Pickard and Emery Descriptive Physical
Oceanography An Introduction
11
Ocean annual cycle of mixed layer
In winter, SST is low, wind waves are large),
mixed layer is deep In summer, (SST high? water
stable), mixed layer is shallow.
March is nearly isothermal in upper 100 meters.
March-August, SST increases, (absorption of
solar radiation). Mixed layer? 30
m. August-March, net loss of heat, seasonal
thermocline eroding due to mixing.
12
Ocean surface currents the gyres
http//www.windows.ucar.edu/tour/link/earth/Water
/images/Surface_currents_jpg_image.html
  • Wind drived
  • Coriolis force and location of land affect
    current pattern
  • Clockwise in NH, anticlockwise in SH

The water of the ocean surface moves in a regular
pattern called surface ocean currents. The
currents are named. In this map, warm currents
are shown I n red and cold currents are shown in
blue.
13
Role of ocean surface currents
Surface ocean currents carry heat from place to
place in the Earth system. This affects regional
climates. The Sun warms water at the equator
more than it does at the high latitude polar
regions. The heat travels in surface currents to
higher latitudes. A current that brings warmth
into a high latitude region will make that
regions climate less chilly.
14
Thermocline The thermocline (sometimes
metalimnion) is a thin but distinct layer in a
large body of fluid (e.g. such as an ocean or
lake), in which temperature changes more rapidly
with depth than it does in the layers above or
below. In the ocean, the thermocline may be
thought of as an invisible blanket which
separates the upper mixed layer from the calm
deep water below.
Graph showing a tropical ocean thermocline (depth
vs. temperature). Note the rapid change between
400 and 800 meters.
15
Ocean thermocline
  • When water is sufficiently cooled, at polar
    latitudes, by cold atmospheric air, it gets
    denser and sinks
  • The vertical sinking motion causes horizontal
    water motion as surface waters replace the
    sinking water.
  • The large-scale flow pattern that results from
    the sinking of water in the Nordic and Greenland
    Seas and around Antarctica is called the oceanic
    conveyor belt

16
Land where most human impact are applied
  • Lower boundary of 30 of earth surface lower heat
    capacity than ocean
  • Higher variability in interaction with atmosphere
    than ocean surface
  • Moisture exchange
  • Albedo
  • Topography forced momentum change
  • Human impact directly change the land surface
  • Release of CO2 and other GHGs
  • Release of Aerosol
  • Change the Land surface cover
  • UHI effect

17
The greenhouse gases act as insulation
18
Land aerosols
Aerosol the small particles in the atmosphere
which varying in size, chemical composition,
temporal and spatial distribution and life
time Source volcano eruptions, wind lifting of
dust, biomass burning, vegetation New result and
great uncertainty of the effect of aerosol on
climate Small aerosol reflect back the solar
radiation Large aerosol can block longwave
radiation
19
Land Landuse changes
  • Land-cover changes alter
  • surface albedo and emissivity
  • water uptake by roots
  • leaf area index
  • canopy interception capacity
  • stomatal resistance
  • roughness length
  • .
  • These changes affect
  • partitioning of surface energy fluxes
  • boundary layer structure
  • cloud and precipitation formation
  • .

Urbanization is an example of landuse change
20
General climate model an approach for the
future climate
  • Atmospheric GCM is first used in 1950s to predict
    short-time future weather
  • GCM develops and performs continuously improving
    since then with helps from updating computational
    resources and better understanding of
    atmospheric dynamics
  • Atmospheric and Oceanic Coupled GCMs (e.g., CCSM,
    HadCM, GISS, CCCS, CFS) are major ways to predict
    and project future climate
  • A list of GCM and climate modeling programs
  • http//stommel.tamu.edu/baum/climate_modeling.htm
    l

21
Regional climate model
  • The first generation of regional climate model is
    developed by Dickinson et.al (1989) and Giorgi
    et. al (1990) due to the coarse resolution of GCM
    not able to resolve local process
  • Second generation of RCM (RegCM2) is developed in
    NCAR (Giorgi et al. 1993) based on MM5 and
    improved boundary layer parameterizations
  • Third generation of RCM (RegCM3) (Pal et al.
    2007) is developed with various improvements in
    dynamics and physical parameterizations

22
The past, present and future of climate models
During the last 25 years, different components
are added to the climate model to better
represent our climate system
http//www.usgcrp.gov/usgcrp/images/ocp2003/ocpfy2
003-fig3-4.htm
23
Definition
Climate Model NASA Earth Observatory Glossary
http//earthobservatory.nasa.gov/Library/glossary
.php3?modealphasegbsegendd A quantitative
way of representing the interactions of the
atmosphere, oceans, land surface, and ice.
Models can range from relatively simple to
quite comprehensive. Also see General
Circulation Model. General Circulation Model
(GCM) A global, three-dimensional computer model
of the climate system which can be used to
simulate human-induced climate change. GCMs are
highly complex and they represent the effects of
such factors as reflective and absorptive
properties of atmospheric water vapor,
greenhouse gas concentrations, clouds, annual and
daily solar heating, ocean temperatures and ice
boundaries. The most recent GCMs include global
representations of the atmosphere, oceans, and
land surface.
24
Differences between Regional Climate Model (RCM)
and Global Climate Model (GCM)
RCM GCM
  • Coverage for selected region, for
    the globe
  • Model resolution finer resolution, coarse
    resolution
  • 1 km-10km 60-250km, or larger
  • 3. Model components are different

25
Climate Model
  • Equations believed to represent the physical,
    chemical, and biological
  • processes governing the climate system for the
    scale of interest

It can answer What If questions for example,
what would the climate be if CO2 is
doubled? what would the climate be if
Greenland ice is all melt? what..if
Amazon forest is gone? whatif SF bay
area population is doubled?
26
Numerical method finite difference method
27
Example CCSM (Community Climate System Model)
Community Climate System Model is a fully coupled
climate model of spectral coordinate in the
horizontal and 26 layers in the vertical
direction. It contains of AGCM(CAM), OGCM(POP),
land surface model(CLM) and sea ice model(CSIM).
Each model component exchanges information with
the others through a flux coupler (cpl)
CLM
CAM
cpl
POP
CISM
atmosphere
CAM an improved version of CCM using hybrid
coordinates and a Eulerian dynamical core which
is separated from the parameterization
package CLM an successor from NCAR LSM by
changing the biogeophysical, carbon cycle and
vegetation dynamics parameterizations in the
LSM POP almost identical to LANLs POP1.4.3,
only minor changes are made to facilitate the
original version server as ocean model component
of CCSM2.0.1 CSIM consists an elastic-viscous-pla
stic dynamics scheme, and ice thickness
distribution, energy-conserving thermodynamics, a
slab ocean mixed layer model, and the ability to
run using prescribed ice concentrations
land
ocean
ice
28
Hybrid Vertical coordinate
Picture taken from http//www.ccsm.ucar.edu/models
/atm-cam/
29
Model physics in CAM
Radiation
(Moist) precipitation
Longwave
Shortwave
Deep
Shallow
Stratiform condensation
Hack
Zhang-McFarlane
Zhang et al
(1994)
(1995)
(2003)
Cloud fraction
Collins (2001)
Surface Exchange
Turbulence
Atm-Lnd
Atm-Ice
Free atmosphere
Atm-Ocn
ABL
ABL depth ( Vogelezang and holtslag 1996)
(Monin-Obkhov similarity theory)
30
CLM combination of BATS, LSM Common Land Model
  • 10 soil layers, up to five snow layers
  • Prognostic variables are canopy temperature,
    intercepted water by canopy, soil or snow
    temperature, water and ice mass in the soil or
    snow layer and snow layer thickness
  • Mosaic land-cover
  • Same surface data with LSM2, and similar
    parameterizations with Common Land Model

31
Mosaic sub-grid land-cover treatment
Needleleaf
Glacier
Vegetation
Grass
Crop
Wet-land
Lake
Bare ground
32
Water balance in CLM
  • Surface evaporation
  • TOPMODEL-like runoff scheme
  • Canopy water budget
  • Soil water budget
  • Snow water budget

33
Canopy water budget
Precipitation arriving at canopy top
Evaporation from canopy
Direct drainage
Canopy drip
34
Radiation balance in CLM
Canopy temperature Rn,c Hc LvEc 0
Tc
Newton-Raphson method
F(x)F(x)(xn-xn-1)0
Soil and snow temperature
Tsoil, Tsnow
Crank-Nicholson method
35
model evaluation-Model uncertainty
  • Verify the predictions and statistics of
    predictions
  • Compatibility with observations
  • Various simulations to assure the agreement with
    basic theoretical understanding
  • Model Inter-comparison studies
  • Compare different models

36
Multimodel ensembles show systematic
discrepancies when comapared with observed mean
temperature
Contours are observed mean surface
temperature, color shading show discre- pancy
calculated from multimodel ensembles.
Typical model error (RMS error in multi-model
ensem- ble) surface temperature
field. Calculated from IPCC AR4 participating
models.
Source Fig. 8.2 of IPCC AR4 chapter 8
37
Multimodel ensemble show significant errors in
standard deviations of surface temperatures
Contours are observed surface temperature
variability,color shading show that of
discre- pancy calculated from multimodel
ensembles from observations.
Source Fig. 8.3 of IPCC AR4 chapter 8
38
Short and longwave radiation budgets show
dominant RMS errors in tropical and subtropical
regions based on 12 month climatology
Curves show RMS errors in short wave (left panel)
and long wave (right panel) radiation
Source Fig. 8.4 of IPCC AR4 chapter 8
39
Simulated precipitation show systematic biases
Observed annual mean precipitation in cm
Multimodel ensemble of annual mean precipitation
in cm
Source Fig. 8.5 of IPCC AR4 chapter 8
40
Zonal mean wind stress on ocean surface is
reasona- bly captured by multi-model ensemble
mean quantity
Source Fig. 8.7 of IPCC AR4 chapter 8
41
Zonal mean SST show marginal errors using
multi-model ensemble mean quantity
Source Fig. 8.8 of IPCC AR4 chapter 8
42
Different climate projection scenarios suggest
unprece- dented increasing trend in global mean
temperatures
Source Fig. 10.4 of IPCC AR4 chapter 10
Write a Comment
User Comments (0)
About PowerShow.com