Download State of Climate Change and Water Modeling in Bangladesh

Training Program on Water Security and Climate Change
State of Climate Change and
Water Modeling in Bangladesh
A.K.M. Saiful Islam
Associate Professor, IWFM
Coordinator, Climate Change Study Cell
Bangladesh University of Engineer and Technology (BUET)
Presentation Outline
• Overview of the Trend of temperature of
Bangladesh and Climate System
• Modeling of Climate Change
• General Circulation Model (GCM)
• IPCC SRES Scenarios
• Climate Change Scenarios
• Regional Climate Model (RCM)
• Climatic Modeling at BUET
• Storm Surge and Salinity modeling due to SLR
Location of BMD Stations
Temperature
Stations (30)
Rainfall
Stations (30)
Trends of Temperature of
Bangladesh (1947-2007)
Max. Temp. = 0.63 0C/100 year
Min. Temp. = 1.37 0C/100 year
2008
2005
2002
1999
1996
1993
1990
1987
1984
1981
1978
1975
2008
2005
2002
1999
1996
1993
1990
1987
1984
1981
1978
1975
1972
1969
1966
20
1963
29.4
1960
20.2
1957
20.4
29.6
1954
20.6
1951
30
29.8
1966
20.8
1963
21
30.2
1960
21.2
30.4
1957
30.6
1954
21.4
1951
30.8
1948
21.6
1948
y = 0.0137x - 6.0268
21.8
31
1972
y = 0.0063x + 17.855
31.2
Trends of Minimum Temperature
22
1969
Trends of Maximum Temperature
31.4
Trends of Discharge
Brahmaputra at Bahadurabad
Ganges at Hardinge Bridge
120000
90000
Average flood discharge (Jul-Sep)
Annual maximum discharge
Average flood discharge (Jul-Sep)
Annual maximum discharge
75000
Discharge (m3 /s)
Discharge (m3 /s)
100000
80000
60000
40000
60000
45000
30000
20000
15000
0
0
1954
1964
1974
1984
Year
1994
2004
1934 1944 1954 1964 1974 1984 1994 2004
Year
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
Climate Models
• Climate models are computer-based simulations that use
mathematical formulas to re-create the chemical and
physical processes that drive Earth’s 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.
General Circulation Model (GCM)
• General Circulation Models (GCMs) are a class of computerdriven 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 atmosphereocean GCMs (AOGCMs, e.g. HadCM3, EdGCM, GFDL CM2.X,
ARPEGE-Climate) combine the two models.
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.
Heart of Climate Model
Conservation of momentum
Conservation of mass
Conservation of energy
Complexity of GCM
Hardware Behind the Climate Model
• Geophysical Fluid Dynamics Laboratory
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.
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.
GCM output described in the 2007 IPCC Fourth
Assessment Report (SRES scenarios), multilayer mean
Models
Variables
BCC:CM1
BCCR:BCM2
CCCMA:CGCM3_1-T47
CCCMA:CGCM3_1-T63
CNRM:CM3
CONS:ECHO-G
CSIRO:MK3
GFDL:CM2
GFDL:CM2_1
INM:CM3
IPSL:CM4
LASG:FGOALS-G1_0
MPIM:ECHAM5
MRI:CGCM2_3_2
NASA:GISS-AOM
NASA:GISS-EH
NASA:GISS-ER
NCAR:CCSM3
NCAR:PCM
NIES:MIROC3_2-HI
NIES:MIROC3_2-MED
UKMO:HADCM3
UKMO:HADGEM1
 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
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.
Prediction of Temperature increase
Observed Ice melting
http://www.worldwithoutwinter.com/melting%20ice%20caps.jpg
• Images gathered from the Defense
Meteorological Satellite Program of NASA show
the minimum Arctic sea ice concentration 1979
(left) and 2003 (right).
1979
2003
Predicted Arctic sea Ice
Arctic Sea Ice in
2000
Arctic Sea Ice in
2040
Results from community climate system models
Prediction of Sea level rise
Regional details of Climate Change
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 500~300 km
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.
Domain used in PRECIS experiment
Topography of Experiment Domain
Simulation Domain = 88 x 88
Resolution = 0.44 degree
Zoom over Bangladesh
Yearly Average Temperature
Yearly Average Temperature Map
Station
PRECIS
Yearly Average Precipitation of Bangladesh
Yearly Average Precipitation Map
Station
PRECIS
Predicted Change of Mean
Temperature (0C) using A1B
Baseline = 2000
2050
2090
Change of Mean Rainfall (mm/d) using
A1B Scenarios
Baseline = 2000
2050
2090
Predicting Maximum Temperature
using A2 Scenarios
[Output of PRECIS model using SRES A2 scenario]
Change of Mean Rainfall (mm/d)
using A1B Scenarios
Baseline = 2000
2050
2090
Change of mean climatic variables of
Bangladesh using A1B Scenarios
Temperate (0C)
Rainfall (mm/d)
High-resolution Regional Climate Change Information for
Bangladesh to inform Impacts assessments, Vulnerability
indicators and Adaptation policies
Experiment ID
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Description of the Simulation
ERA40:Reanalysis
ERA-Interim: Reanalysis
NCEP_R2:Reanalysis
HadAM3P:Baseline#1
HadAM3P:Baseline#2
HadAM3P:Baseline#3
HadAM3P:SRES_A2#1
HadAM3P:SRES_A2#2
HadAM3P:SRES_A2#3
HadAM3P:SRES_B2
HadCM3Q0:SRES_A1B
ECHAM4:Baseline
ECHAM4:SRES_A2
ECHAM4:SRES_B2
ECHAM5:SRES_A1B
Time Frame
1957-2001
1989-2009
1979-2004
1960-1990
1960-1990
1960-1990
2070-2100
2070-2100
2070-2100
2070-2100
1949-2099
1960-1990
2069-2100
2069-2100
1950-2100
Length( years)
40
20
25
30
30
30
30
30
30
30
150
30
30
30
150
Storm Surge Model during SIDR
Advanced Circulation (ADCIRC) model to predict storm surge
Hassan Mashriqui, an assistant extension professor of
coastal engineering of Louisiana State University (LSU)
Has simulated storm surge model during SIDR
Source: http://www.oar.noaa.gov/spotlite/2007/spot_cyclone.html
2D Hydrodynamic Modeling for Salt water Intrusion
IWM studied “Impact of Sea level Rise on Coastal Rivers of Bangladesh”
Five ppt line for different sea level rise in dry season
What will happen to Artic Polar Bears ?
Antarctic Penguins are watching…
The Sundarbans ..Mangrove forest?
Thank you