Global and SE U.S. Assessment of Precipitation: Comparison of Model Simulations with Reanalysis-based Observations Eduardo Ponce Mojica Polytechnic University.

Global and SE U.S. Assessment of Precipitation: Comparison of Model Simulations with Reanalysis-based Observations

Eduardo Ponce MojicaPolytechnic University of Puerto Rico

Dr. Auroop R. GangulyComputational Sciences and Engineering Division

August 2009

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Overview

• Introduction– Climate change– Precipitation

• Objectives

• Resources– Climate models– Climate observations

• Methodology

• Conclusions

• Future work

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Background

• Climate changes have been a BIG concern for the past decades– Global warming– Climate extremes– Anthropogenic effects

• Processes and materials derived from human activities

• Atmospheric concentration of greenhouse gases

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Introduction

• Climate changes may cause or worsen precipitation events– Floods– Droughts– Precipitation extremes

• Long-duration

• Short-duration

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Introduction

• Precipitation is difficult to predict– Too many parameters to take into account

• Ocean circulation

• Land surface

• Sea ice

• Concentration of atmospheric gases

• Electromagnetic radiation

– Complex meteorological physics• Mass and energy transfer

• Radiant exchange

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Introduction

• Precipitation events may be studied for a specific region, or across the whole Earth

Southeast United States Earth

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Objectives

• Compare two climate models with observations

• Use statistical analyses to describe models

• Obtain uncertainties from climate model and observations

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What is …?

• Climate

• Precipitation

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What is climate?

• Phenomena occurring in the atmosphere in a long period of time– Ranges from months to thousand or million of years

• Composed of numerous meteorological elements– Temperature– Atmospheric pressure– Wind– Rainfall– Evapotranspiration

• Affected by latitude and longitude

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What is precipitation?

• Products due to condensation of atmospheric water vapour deposited on Earth's surface– Rain– Ice pellets– Snow– Hail

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Resources

• Climate models simulations

• Climate observations data

• MATLAB– Statistical analysis– Graph global and regional data

• Microsoft Excel– Construction of data plots– Construction of data tables

CCSM3CCSM3HadCM3HadCM3NCEP1NCEP1

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Climate models

• Community Climate System Model, version 3 (CCSM3)

– United States– United States Department of Energy (DOE) Earth

System Grid (ESG)

• Hadley Centre Coupled Model, version 3 (HadCM3)

– United Kingdom– Intergovernmental Panel on Climate Change (IPCC)

Project for Climate Model Diagnosis and Intercomparison (PCMDI)

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Climate observations

• National Centers for Environmental Prediction, reanalysis 1 (NCEP1)– United States– National Oceanic and Atmospheric Administration

(NOAA)

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Methodology

• Interpolate climate models data– Different latitudes and longitudes precision– CCSM3 with NCEP1– HadCM3 with NCEP1

Interpolated model

94 x 192

CCSM3/HadCM3

128 x 256

NCEP1

94 X 192

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Methodology

• Case study regions– Global– Southeast United States

• Latitudes: 24° N – 41° N• Longitudes: 95° W - 74° W

• Time range (1948 – 1999)

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Methodology

• Apply statistical methods– Mean– Standard deviation– Skewness– Median– Bias = observations - models

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Climate graphs

Global mean – NCEP1 and CCSM3

-150 -100 -50 0 50 100 150

-80

-60

-40

-20

0

20

40

60

80

Longitude

Latit

ude

NCEP1 Average Precipitation Rate in mm/s from 1948 to 1999

0

1

2x 10

-4

-150 -100 -50 0 50 100 150

-80

-60

-40

-20

0

20

40

60

80

Longitude

Latit

ude

CCSM3 Average Precipitation Rate in mm/s from 1948 to 1999

0

1

2x 10

-4

NCEP1 average precipitation rate in mm/s from 1948 to 1999

CCSM3 average precipitation rate in mm/s from 1948 to 1999

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Climate graphs

Global mean – NCEP1 and HadCM3

-150 -100 -50 0 50 100 150

-80

-60

-40

-20

0

20

40

60

80

Longitude

Latit

ude

NCEP1 Average Precipitation Rate in mm/s from 1948 to 1999

0

1

2x 10

-4

-150 -100 -50 0 50 100 150

-80

-60

-40

-20

0

20

40

60

80

Longitude

Latit

ude

HadCM3 Average Precipitation Rate in mm/s from 1948 to 1999

0

1

2x 10

-4

NCEP1 average precipitation rate in mm/s from 1948 to 1999

HadCM3 average precipitation rate in mm/s from 1948 to 1999

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Climate graphs

SE U.S. mean – NCEP1 and CCSM3

-95 -90 -85 -80 -7524

26

28

30

32

34

36

38

40

Longitude

Latit

ude

NCEP1 Southeastern U.S. Average Precipitation Rate in mm/s from 1948 to 1999

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1x 10

-4

-95 -90 -85 -80 -7524

26

28

30

32

34

36

38

40

Longitude

Latit

ude

CCSM3 Southeastern U.S. Average Precipitation Rate in mm/s from 1948 to 1999

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1x 10

-4

NCEP1 Southeastern U.S. average precipitation rate in mm/s

from 1948 to 1999

CCSM3 Southeastern U.S. average precipitation rate in mm/s

from 1948 to 1999

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Climate graphs

SE U.S. mean – NCEP1 and HadCM3

-95 -90 -85 -80 -7524

26

28

30

32

34

36

38

40

Longitude

Latit

ude

NCEP1 Southeastern U.S. Average Precipitation Rate in mm/s from 1948 to 1999

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1x 10

-4

-95 -90 -85 -80 -7524

26

28

30

32

34

36

38

40

Longitude

Latit

ude

HadCM3 Southeastern U.S. Average Precipitation Rate in mm/s from 1948 to 1999

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1x 10

-4

NCEP1 Southeastern U.S. average precipitation rate in mm/s

from 1948 to 1999

HadCM3 Southeastern U.S. average precipitation rate in mm/s

from 1948 to 1999

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Climate graphs

CCSM3 and HadCM3 SE U.S. bias graphs

-95 -90 -85 -80 -7524

26

28

30

32

34

36

38

40

Longitude

Latit

ude

Southeastern U.S. Average of Biased Precipitation Rate in mm/s between the CCSM3 and the NCEP1 from 1948 to 1999

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2x 10

-5

Southeastern U.S. average of biased precipitation rate in mm/s between the

CCSM3 and the NCEP1 from 1948 to 1999

-95 -90 -85 -80 -7524

26

28

30

32

34

36

38

40

Longitude

Latit

ude

Southeastern U.S. Average of Biased Precipitation Rate in mm/s between the CCSM3 and the NCEP1 from 1948 to 1999

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2x 10

-5

Southeastern U.S. average of biased precipitation rate in mm/s between the HadCM3 and the NCEP1 from 1948 to

1999

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Plots

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Plots

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Plots

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Results

• Global scope– CCSM3 more accurate

• Southeast United States– HadCM3 more accurate

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Research conclusions

• Global scope– CCSM3 over predicts precipitation rate– HadCM3 over predicts precipitation rate– CCSM3 more accurate model

• Southeast U.S.– CCSM3 under predicts precipitation rate– HadCM3 under predicts precipitation rate– HadCM3 more accurate model

• Study small regions with climate models– Reduces uncertainties– Outputs statistics more accurately

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Future research

• Test accuracy of CCSM3 and HadCM3 in other regions

• Propose safety measures for high precipitation areas

• Simulate precipitation rates from 2000 to 2100

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Bibliography

• Auroop R. Ganguly, Shih-Chieh Kao, Karsten Steinhaeuser, Esther S. Parish, Marcia L. Branstetter, David J. Erickson III, and Nagendra Singh. Uncertainties in the Assessments of Climate Change Impacts on Regional Hydrology and Water Resources. (2009: In Review).

• Intergovernmental Panel on Climate Change (IPCC). Fourth Assessment Report: 2007.

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Acknowledgments

Special thanks go to…

•The Research Alliance in Math and Science program, sponsored by the Office of Advanced Scientific Computing Research, U.S. Department of Energy

•Dr. Auroop R. Ganguly for the opportunity to work on this project.

•Shih-Chieh Kao, Karsten Steinhaeuser, the GIST Group, and Rashida E. Askia for their continued support

•Debbie McCoy, who made provisions for this research experience along with exceptional professional support

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QUESTIONS