Analysis and Modeling of Climate Change

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Analysis and Modeling of Climate Change
Training Course on Facing the Challenges of
Climate Change Issues, Impacts and adaptation
Strategies for Bangladesh with focus on Water and
Waste Management Organized by International
Training Network (ITN) Centre, BUET

• A.K.M. Saiful Islam

Associate Professor, IWFM Coordinator, Climate
Change Study Cell
Bangladesh University of Engineer and Technology
(BUET)
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Presentation Outline

• Overview of the Climate System
• Modeling of Climate Change
• General Circulation Model (GCM)
• IPCC SRES Scenarios
• Regional Climate Model (RCM)
• Climatic Modeling at BUET

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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.

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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.

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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.
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Heart of Climate Model
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Complexity of GCM
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Hardware Behind the Climate Model

• Geophysical Fluid Dynamics Laboratory

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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.

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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.

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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.

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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.

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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.

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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

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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
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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

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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

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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

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Arctic Sea Ice Prediction using community climate
system model
Arctic Sea Ice in 2040
Arctic Sea Ice in 2000
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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.

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Prediction of Temperature increase
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Prediction of Sea level rise
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Regional details of Climate Change
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Regional Climate modeling

• An RCM is a tool to add small-scale detailed
  information of future climate change to the
  large-scale projections of a GCM. RCMs are full
  climate models and as such are physically based
  and represent most or all of the processes,
  interactions and feedbacks between the climate
  system components that are represented in GCMs.
• They take coarse resolution information from a
  GCM and then develop temporally and spatially
  fine-scale information consistent with this using
  their higher resolution representation of the
  climate system.
• The typical resolution of an RCM is about 50 km
  in the horizontal and GCMs are typically 500300
  km

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RCM can simulate cyclones and hurricanes
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Regional Climate change modeling in Bangladesh

• PRECIS regional climate modeling is now running
  in Climate change study cell at IWFM,BUET.
• Uses LBC data from GCM (e.g. HadCM3).
• LBC data available for baseline, A2, B2, A1B
  scenarios up to 2100.
• Predictions for every hour. Needs more than 100
  GB free space.

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Domain used in PRECIS experiment
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Topography of Experiment Domain
Simulation Domain 88 x 88 Resolution 0.44
degree
Zoom over Bangladesh
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Predicted Change of Mean Temperature (0C) using
A1B
Baseline 2000
2050
2090
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Predicting Maximum Temperature using A2 Scenarios
Output of PRECIS model using SRES A2 scenario
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Predicting Minimum Temperature using A2 Scenarios
Output of PRECIS model using SRES A2 scenario
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Change of Mean Rainfall (mm/d) using A1B Scenarios
Baseline 2000
2050
2090
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Predicting Rainfall using A2 Scenarios
Output of PRECIS model using SRES A2 scenario
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Change of mean climatic variables of Bangladesh
using A1B Scenarios
Temperate (0C)
Rainfall (mm/d)
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Monthly Average Rainfall (mm/d)
Month 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090
January 2.61 0.34 0.03 0.03 0.42 0.99 1.24 0.21 0.12 1.66 1.02
February 0.61 0.55 1.38 1.01 1.24 1.88 0.45 1.10 0.53 1.61 0.76
March 2.42 1.02 4.82 3.04 1.87 3.07 0.99 3.62 2.84 1.27 3.59
April 5.84 1.38 11.46 5.99 2.82 7.84 11.41 6.60 8.39 8.74 3.66
May 10.03 5.59 10.36 6.42 11.92 18.16 33.47 16.53 29.47 11.29 11.96
June 17.06 7.90 14.79 13.59 10.84 21.48 12.87 12.93 7.24 10.04 11.70
July 7.20 9.07 7.97 8.13 7.32 11.26 5.62 10.26 10.31 6.33 9.98
August 7.39 5.46 5.11 3.92 9.79 6.67 7.46 13.60 10.65 9.13 9.59
September 4.49 6.71 5.47 7.83 7.51 8.82 10.29 10.80 10.52 8.18 7.48
October 5.68 1.48 4.16 2.76 6.16 3.11 1.89 3.94 2.55 8.84 7.58
November 0.14 0.16 0.41 0.91 0.03 0.73 0.08 1.91 0.27 1.23 0.51
December 0.14 0.06 0.10 0.26 0.06 0.18 1.09 0.04 0.13 0.32 0.03
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Monthly Average Temperature (0C)
Month 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090
January 14.74 15.08 14.63 15.94 15.66 17.66 19.52 16.49 17.68 21.55 20.88
February 14.27 21.18 20.18 22.36 20.61 20.65 23.14 25.37 24.50 23.00 23.32
March 24.25 26.34 25.68 25.66 28.82 26.70 29.23 29.04 29.71 28.53 28.84
April 27.95 32.36 29.10 31.28 34.07 31.96 31.29 32.64 32.81 31.53 34.52
May 29.51 32.11 32.16 33.17 31.97 32.37 29.31 32.00 32.59 33.88 35.62
June 29.18 31.42 30.66 31.44 30.82 31.56 31.94 31.18 37.24 34.80 35.07
July 28.59 28.23 28.88 28.99 29.35 30.28 30.58 30.45 31.03 31.76 30.44
August 28.19 28.24 29.06 29.65 28.62 30.34 30.26 29.31 30.12 29.93 30.09
September 28.02 27.29 28.65 28.11 28.58 30.72 29.07 29.79 30.72 29.01 29.87
October 25.24 25.21 27.10 27.29 26.14 28.48 28.22 29.25 29.72 27.82 29.09
November 19.44 20.20 21.03 20.52 21.06 23.21 22.64 22.04 23.76 25.52 26.30
December 14.48 17.37 17.86 18.53 16.24 18.85 19.99 18.26 19.36 20.90 20.80
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Trends of Temperature of Bangladesh (1947-2007)
Max. Temp. 0.63 0C/100 year
Min. Temp. 1.37 0C/100 year
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Spatial Distribution of Trends of Temperature
(1947-2007)
Maximum Temperature Maximum increase 0.0581 at
Shitakunda Minimum increase -0.026 at Rangpur
Minimum Temperature Maximum increase 0.0404 at
Bogra Minimum increase -0.023 at Tangail
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Conclusions

• Analysis of the historic data (1948-2007) shows
  that daily maximum and minimum temperature has
  been increased with a rate of 0.63 0C and 1.37
  0C per 100 years respectively.
• PRECIS simulation for Bangladesh using A1B
  climate change scenarios showed that mean
  temperature will be increased at a constant rate
  40C per 100 year from the base line year 2000.
• On the other hand, mean rainfall will be
  increased by 4mm/d in 2050 and then decreased by
  2.5mm/d in 2100 from base line year 2000.

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Recommendations

• In future, Climate change predictions will be
  generated in more finer spatial scale(25km).
• PRECIS model will be simulated with other
  Boundary condition data such as ECHAM5 using A1B
  scenarios.
• Results will be compared with other regional
  climate models such as RegCM3 etc.

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Climate Change Study Cell, BUET
http//teacher.buet.ac.bd/diriwfm/climate/
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Thank you