WFM 6311: Climate Change Risk Management

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WFM 6311 Climate Change Risk Management
Lecture-4 Module- 3 Regional Climate Change
Modeling

• Akm Saiful Islam

Institute of Water and Flood Management
(IWFM) Bangladesh University of Engineering and
Technology (BUET)
December, 2009
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Module-3

• Prediction of climate change
• Global and regional climate change predictions
• Dynamic and static downscaling for impact study.
• Uncertainty of predictions

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Regional Climate Change Modeling
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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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PRECIS

• PRECIS, developed by Hadley Center's, UK, is a
  regional climate modeling system.
• A regional climate model (RCM) is a dynamic
  downscaling tool that adds fine scale (high
  resolution) information to the large-scale
  projections of a global general circulation model
  (GCM).
• This makes for a more accurate representation of
  many surface features, such as complex mountain
  topographies and coastlines. RCMs are full
  climate models, and as such are physically based.

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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
Rainfall (mm/d)
Temperate (0C)
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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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Summary

• 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.