Climate Scenarios for Regional applications, selected cases of Latin America Abel Centella

1ST Latin American and the Caribbean Regional Workshop Assessment for Impacts and Adaptation to Climate Change in Multiple Regions and Sectors (AIACC)

San José 27-30 June 2003

Climate Scenarios for Regional applications, selected cases of Latin America

Abel Centella

Institute of Meteorology

La Habana, Cuba

Experiences from First National Communication Experiences from First National Communication process in some countries in LA regionprocess in some countries in LA region

Countries: Cuba, El Salvador, Guatemala, Panamá, Haití, Saint Kitts & Nevis, Dominican Republic, Paraguay

National Communication Process:

• V&A is one of the issues

• Lack of time for research

• Previous experiences

• Building Capacity

The Work was oriented toThe Work was oriented to

1. Develop a climate base line for each country (grided climate data)

2. Understand the climate change issue

3. The art of climate change scenario development

4. The use of climate changes scenario results

-9 2 .5 0 -9 2 .0 0 -9 1 .5 0 -9 1 .0 0 -9 0 .5 0 -9 0 .0 0 -8 9 .5 0 -8 9 .0 0 -8 8 .5 0 -8 8 .0 01 3 .5 0

1 4 .0 0

1 4 .5 0

1 5 .0 0

1 5 .5 0

1 6 .0 0

1 6 .5 0

1 7 .0 0

1 7 .5 0

1 8 .0 0

-9 2 .5 0 -9 2 .0 0 -9 1 .5 0 -9 1 .0 0 -9 0 .5 0 -9 0 .0 0 -8 9 .5 0 -8 9 .0 0 -8 8 .5 0 -8 8 .0 01 3 .5 0

1 4 .0 0

1 4 .5 0

1 5 .0 0

1 5 .5 0

1 6 .0 0

1 6 .5 0

1 7 .0 0

1 7 .5 0

1 8 .0 0

-9 2 .5 0 -9 2 .0 0 -9 1 .5 0 -9 1 .0 0 -9 0 .5 0 -9 0 .0 0 -8 9 .5 0 -8 9 .0 0 -8 8 .5 0 -8 8 .0 01 3 .5 0

1 4 .0 0

1 4 .5 0

1 5 .0 0

1 5 .5 0

1 6 .0 0

1 6 .5 0

1 7 .0 0

1 7 .5 0

1 8 .0 0

-9 2 .5 0 -9 2 .0 0 -9 1 .5 0 -9 1 .0 0 -9 0 .5 0 -9 0 .0 0 -8 9 .5 0 -8 9 .0 0 -8 8 .5 0 -8 8 .0 01 3 .5 0

1 4 .0 0

1 4 .5 0

1 5 .0 0

1 5 .5 0

1 6 .0 0

1 6 .5 0

1 7 .0 0

1 7 .5 0

1 8 .0 0

-9 2 .5 0 -9 2 .0 0 -9 1 .5 0 -9 1 .0 0 -9 0. 5 0 -9 0. 0 0 -8 9. 5 0 -8 9 .0 0 -8 8 .5 0 -8 8 .0 01 3 .5 0

1 4 .0 0

1 4 .5 0

1 5 .0 0

1 5 .5 0

1 6 .0 0

1 6 .5 0

1 7 .0 0

1 7 .5 0

1 8 .0 0

-9 2 .5 0 -9 2 .0 0 -9 1 .5 0 -9 1 .0 0 -9 0. 5 0 -9 0. 0 0 -8 9. 5 0 -8 9 .0 0 -8 8 .5 0 -8 8 .0 01 3 .5 0

1 4 .0 0

1 4 .5 0

1 5 .0 0

1 5 .5 0

1 6 .0 0

1 6 .5 0

1 7 .0 0

1 7 .5 0

1 8 .0 0

-9 2 .5 0 -9 2 .0 0 -9 1 .5 0 -9 1 .0 0 -9 0 .5 0 -9 0 .0 0 -8 9 .5 0 -8 9 .0 0 -8 8 .5 0 -8 8 .0 01 3 .5 0

1 4 .0 0

1 4 .5 0

1 5 .0 0

1 5 .5 0

1 6 .0 0

1 6 .5 0

1 7 .0 0

1 7 .5 0

1 8 .0 0

-9 2 .5 0 -9 2 .0 0 -9 1 .5 0 -9 1 .0 0 -9 0 .5 0 -9 0 .0 0 -8 9 .5 0 -8 9 .0 0 -8 8 .5 0 -8 8 .0 01 3 .5 0

1 4 .0 0

1 4 .5 0

1 5 .0 0

1 5 .5 0

1 6 .0 0

1 6 .5 0

1 7 .0 0

1 7 .5 0

1 8 .0 0

-4 -2 0 2 4 6 8 1 0 1 2 1 4 1 6 1 8 2 0 2 2 2 4 2 6 2 8 3 0 3 2 3 4 3 6 3 8

Temperatura m edia

-92 .5 0 -92 .0 0 -91 .5 0 -91 .0 0 -90 .5 0 -90 .0 0 -89 .5 0 -89 .0 0 -88 .5 0 -88 .0 013 .5 0

14 .0 0

14 .5 0

15 .0 0

15 .5 0

16 .0 0

16 .5 0

17 .0 0

17 .5 0

18 .0 0

0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 60 0 70 0 80 0 90 0 1 00 0

-92 .5 0 -92 .0 0 -91 .5 0 -91 .0 0 -90 .5 0 -90 .0 0 -89 .5 0 -89 .0 0 -88 .5 0 -88 .0 013 .5 0

14 .0 0

14 .5 0

15 .0 0

15 .5 0

16 .0 0

16 .5 0

17 .0 0

17 .5 0

18 .0 0

-92 .5 0 -92 .0 0 -91 .5 0 -91 .0 0 -90 .5 0 -90 .0 0 -89 .5 0 -89 .0 0 -88 .5 0 -88 .0 013 .5 0

14 .0 0

14 .5 0

15 .0 0

15 .5 0

16 .0 0

16 .5 0

17 .0 0

17 .5 0

18 .0 0

-92 .5 0 -92 .0 0 -91 .5 0 -91 .0 0 -90 .5 0 -90 .0 0 -89 .5 0 -89 .0 0 -88 .5 0 -88 .0 013 .5 0

14 .0 0

14 .5 0

15 .0 0

15 .5 0

16 .0 0

16 .5 0

17 .0 0

17 .5 0

18 .0 0

-92 .5 0 -92 .0 0 -91 .5 0 -91 .0 0 -90 .5 0 -90 .0 0 -89 .5 0 -89 .0 0 -88 .5 0 -88 .0 013 .5 0

14 .0 0

14 .5 0

15 .0 0

15 .5 0

16 .0 0

16 .5 0

17 .0 0

17 .5 0

18 .0 0

-92 .5 0 -92 .0 0 -91 .5 0 -91 .0 0 -90 .5 0 -90 .0 0 -89 .5 0 -89 .0 0 -88 .5 0 -88 .0 013 .5 0

14 .0 0

14 .5 0

15 .0 0

15 .5 0

16 .0 0

16 .5 0

17 .0 0

17 .5 0

18 .0 0

-92 .5 0 -92 .0 0 -91 .5 0 -91 .0 0 -90 .5 0 -90 .0 0 -89 .5 0 -89 .0 0 -88 .5 0 -88 .0 013 .5 0

14 .0 0

14 .5 0

15 .0 0

15 .5 0

16 .0 0

16 .5 0

17 .0 0

17 .5 0

18 .0 0

-92 .5 0 -92 .0 0 -91 .5 0 -91 .0 0 -90 .5 0 -90 .0 0 -89 .5 0 -89 .0 0 -88 .5 0 -88 .0 013 .5 0

14 .0 0

14 .5 0

15 .0 0

15 .5 0

16 .0 0

16 .5 0

17 .0 0

17 .5 0

18 .0 0

P recipitación

M AY J U N

J U L AGO

TEMPERATURE

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

19

51

19

54

19

57

19

60

19

63

19

66

19

69

19

72

19

75

19

78

19

81

19

84

19

87

19

90

19

93

19

96

Ano

ma

lías

°C

CUBA

EL SALVADORGUATEMALA

PRECIPITATION

-300

-200

-100

0

100

200

300

19

41

19

44

19

47

19

50

19

53

19

56

19

59

19

62

19

65

19

68

19

71

19

74

19

77

19

80

19

83

19

86

19

89

19

92

19

95

Ano

ma

lías

(mm

)

CUBA

EL SALVADORGUATEMALA

Correlations between STA in Pacific Regions and Precipitation in El Salvador with Correlations between STA in Pacific Regions and Precipitation in El Salvador with some lags (months)some lags (months)

CLIMATE SCENARIOS WERE CREATED USING MAGICC SIMPLE CLIMATE MODEL

MAGICC/SCENGENUniversity of East Anglia

UK

Simple Climate Model

Structure Representation

CO2

CH4

N2O

Emission scenariosGlobal warming & Climate sensitivity

Global warming, emission scenarios & Climate sensitivity

HADCM2 Reino Unido

UKTR Reino Unido

UKHI Reino Unido

UKLO Reino Unido

CSIRO9/M2 Australia

BMRC Australia

CSIRO9 Australia

GISSEQ Estados Unidos

GFDLLO Estados Unidos

LLNL Estados Unidos

OSU Estados Unidos

CCCEQ Canadá

ECHAM1TR Alemania

ECHAM3TR Alemania

Selecting GCM

Criteria for selection:

• Representation of current climate

• Grid resolution

• Model vintage

• Different projections

Climate projections from different GCMs combined with different GHG scenarios and Climate Sensibilities

THE UNCERTAINTY SPACE

• Emissions

• Climate sensitivity

• GCM regional outputs Which CC scenario we can select?

MCG

Vi = (2XCO2 - 1XCO2)

VMCG = Vi / TMCG

MCS

Taño,MCS = TMAGICC

VVi,año i,año = = VVMCGMCG**TTaño,MCSaño,MCS

Combining Simple and Global Climate Models

Santer (1990)

TEMPERATURE ANNUAL VARIATION

GUATEMALA

PRECIPITATION ANNUAL VARIATION

GUATEMALA

ARIDITY INDEX

GUATEMALA

SOME LESSONS

1. Develop an uncertainty analysis approach

2. Downscaling must be incorporate (e.g High Resolution Regional Model)

3. Individual (country) experiences must be integrated in future work

Unfortunally, a regional proposal for CA & the Caribbean did not classify for the AIACC Grant