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WFM 6311: Climate Change Risk Management

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WFM 6311: Climate Change Risk Management Lecture-3: Module- 3 Climate Change Modeling -GCM Akm Saiful Islam Institute of Water and Flood Management (IWFM) – PowerPoint PPT presentation

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Title: WFM 6311: Climate Change Risk Management


1
WFM 6311 Climate Change Risk Management
Lecture-3 Module- 3 Climate Change Modeling -gtGCM
  • Akm Saiful Islam

Institute of Water and Flood Management
(IWFM) Bangladesh University of Engineering and
Technology (BUET)
December, 2012
2
Module-3
  • Prediction of climate change
  • Global and regional climate change predictions
  • Dynamic and static downscaling for impact study.
  • Uncertainty of predictions

3
Climate Change Modeling
4
Climate Models
  • Climate models are computer-based simulations
    that use mathematical formulas to re-create the
    chemical and physical processes that drive
    Earths climate. To run a model, scientists
    divide the planet into a 3-dimensional grid,
    apply the basic equations, and evaluate the
    results.
  • Atmospheric models calculate winds, heat
    transfer, radiation, relative humidity, and
    surface hydrology within each grid and evaluate
    interactions with neighboring points. Climate
    models use quantitative methods to simulate the
    interactions of the atmosphere, oceans, land
    surface, and ice.

5
General Circulation Model (GCM)
  • General Circulation Models (GCMs) are a class of
    computer-driven models for weather forecasting,
    understanding climate and projecting climate
    change, where they are commonly called Global
    Climate Models.
  • Three dimensional GCM's discretise the equations
    for fluid motion and energy transfer and
    integrate these forward in time. They also
    contain parameterizations for processes - such as
    convection - that occur on scales too small to be
    resolved directly.
  • Atmospheric GCMs (AGCMs) model the atmosphere and
    impose sea surface temperatures. Coupled
    atmosphere-ocean GCMs (AOGCMs, e.g. HadCM3,
    EdGCM, GFDL CM2.X, ARPEGE-Climate) combine the
    two models.

6
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7
GCM typical horizontal resolution of between 250
and 600 km, 10 to 20 vertical layers in the
atmosphere and sometimes as many as 30 layers in
the oceans.
8
Heart of Climate Model
Conservation of momentum
Conservation of mass
Conservation of energy
9
Complexity of GCM
10
Hardware Behind the Climate Model
  • Geophysical Fluid Dynamics Laboratory

11
Special Report on Emissions Scenarios (SRES)
  • The Special Report on Emissions Scenarios (SRES)
    was a report prepared by the Intergovernmental
    Panel on Climate Change (IPCC) for the Third
    Assessment Report (TAR) in 2001, on future
    emission scenarios to be used for driving global
    circulation models to develop climate change
    scenarios.
  • It was used to replace the IS92 scenarios used
    for the IPCC Second Assessment Report of 1995.
    The SRES Scenarios were also used for the Fourth
    Assessment Report (AR4) in 2007.

12
http//www.grida.no/publications/other/ipcc_sr/?sr
c/climate/ipcc/emission/
13
SERS Emission Scenarios
  • A1 - a future world of very rapid economic
    growth, global population that peaks in
    mid-century and declines thereafter, and the
    rapid introduction of new and more efficient
    technologies. Three sub groups fossil intensive
    (A1FI), non-fossil energy sources (A1T), or a
    balance across all sources (A1B).
  • A2 - A very heterogeneous world. The underlying
    theme is that of strengthening regional cultural
    identities, with an emphasis on family values and
    local traditions, high population growth, and
    less concern for rapid economic development.
  • B1 - a convergent world with the same global
    population, that peaks in mid-century and
    declines thereafter, as in the A1 storyline.
  • B2 - a world in which the emphasis is on local
    solutions to economic, social and environmental
    sustainability.

14
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15
A1
  • The A1 scenarios are of a more integrated world.
    The A1 family of scenarios is characterized by
  • Rapid economic growth.
  • A global population that reaches 9 billion in
    2050 and then gradually declines.
  • The quick spread of new and efficient
    technologies.
  • A convergent world - income and way of life
    converge between regions. Extensive social and
    cultural interactions worldwide.
  • There are subsets to the A1 family based on their
    technological emphasis
  • A1FI - An emphasis on fossil-fuels.
  • A1B - A balanced emphasis on all energy sources.
  • A1T - Emphasis on non-fossil energy sources.

16
A2
  • The A2 scenarios are of a more divided world. The
    A2 family of scenarios is characterized by
  • A world of independently operating, self-reliant
    nations.
  • Continuously increasing population.
  • Regionally oriented economic development.
  • Slower and more fragmented technological changes
    and improvements to per capita income.

17
B1
  • The B1 scenarios are of a world more integrated,
    and more ecologically friendly. The B1 scenarios
    are characterized by
  • Rapid economic growth as in A1, but with rapid
    changes towards a service and information
    economy.
  • Population rising to 9 billion in 2050 and then
    declining as in A1.
  • Reductions in material intensity and the
    introduction of clean and resource efficient
    technologies.
  • An emphasis on global solutions to economic,
    social and environmental stability.

18
B2
  • The B2 scenarios are of a world more divided, but
    more ecologically friendly. The B2 scenarios are
    characterized by
  • Continuously increasing population, but at a
    slower rate than in A2.
  • Emphasis on local rather than global solutions to
    economic, social and environmental stability.
  • Intermediate levels of economic development.
  • Less rapid and more fragmented technological
    change than in A1 and B1

19
SRES A1B Scenarios
  • Special Report on Emissions Scenarios  (SRES) A1B
    scenario assumes a balanced mix of technologies
    and supply sources, with technology improvements
    and resource assumptions such that no single
    source of energy is overly dominant.
  • The implications of these alternative development
    paths for future GHG emissions are challenging
    the emissions vary from the carbon-intensive to
    decarbonization paths by at least as much as the
    variation of all the other driving forces across
    the other SRES scenarios.

20
GCM output described in the 2007 IPCC Fourth
Assessment Report (SRES scenarios), multilayer
mean
Models Scenarios Variables
BCCCM1BCCRBCM2CCCMACGCM3_1-T47CCCMACGCM3_1-T63CNRMCM3CONSECHO-GCSIROMK3GFDLCM2GFDLCM2_1INMCM3IPSLCM4LASGFGOALS-G1_0MPIMECHAM5MRICGCM2_3_2NASAGISS-AOMNASAGISS-EHNASAGISS-ERNCARCCSM3NCARPCMNIESMIROC3_2-HINIESMIROC3_2-MEDUKMOHADCM3UKMOHADGEM1 1PTO2X1PTO4X20C3MCOMMITPICTLSRA1BSRA2SRB1 specific humidity precipitation flux air pressure at sea level net upward shortwave flux in air air temperature air temperature daily max air temperature daily min eastward wind northward wind
21
List of GCM Page 1
  • BCC-CM1
  • AgencyBeijing Climate Center, National Climate
    Center, China Meteorological Administration,
    No.46, S.Road, Zhongguancun Str., Beijing 100081,
    China
  • BCCR
  • Bjerknes Centre for Climate Research (BCCR),
    Univ. of Bergen, Norway
  • CGCM3
  • Canadian Centre for Climate Modelling and
    Analysis (CCCma)
  • CNRM-CM3
  • Centre National de Recherches Meteorologiques,
    Meteo France, France

22
List of GCM Page 2
  • CONS-ECHO-G
  • Meteorological Institute of the University of
    Bonn (Germany), Institute of KMA (Korea), and
    Model and Data Group.
  • CSIRO, Australia
  • INMCM3.0
  • Institute of Numerical Mathematics, Russian
    Academy of Science, Russia.
  • GFDL
  • Geophysical Fluid Dynamics Laboratory, NOAA
  • NASA-GISS-AOM
  • NASA Goddard Institute for Space Studies
    (NASA/GISS), USA

23
List of GCM Page 3
  • MRI-CGCM2_3_2
  • Meteorological Research Institute, Japan
    Meteorological Agency, Japan
  • NCAR-PCM
  • National Center for Atmospheric Research (NCAR),
    NSF (a primary sponsor), DOE (a primary sponsor),
    NASA, and NOAA
  • Model NIES-MIROC3_2-MED
  • CCSR/NIES/FRCGC, Japan
  • UKMO-HADCM3
  • Hadley Centre for Climate Prediction and
    Research, Met Office, United Kingdom

24
Arctic Sea Ice Prediction using community climate
system model
Arctic Sea Ice in 2040
Arctic Sea Ice in 2000
25
Thank about what will happen to Artic Polar Bears
who lives in Artic
26
Antarctic Penguins
27
Prediction of Global Warming
  • Figure shows the distribution of warming during
    the late 21st century predicted by the HadCM3
    climate model. The average warming predicted by
    this model is 3.0 C.

28
Prediction of Temperature increase
29
Prediction of Sea level rise
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