DEPARTAMENTO DE METEOROLOGIA UNIVERSIDADE FEDERAL DE ALAGOAS
[email protected] REGIONAL MEETING ON CLIPS AND
AGROMETEOROLOGICAL APPLICATIONS FOR THE MERCOSUR COUNTRIES LUIZ
CARLOS B. MOLION LONG-TERM CLIMATE PREDICTION AS A MARKETING
STRATEGY CAMPINAS, SO PAULO, BRAZIL - JULY 13 TO 16 2005 Slide 2
CLIMATE MONITORING AND PREDICTION: A KEY FACTOR TO INCREASING
PRODUCTION WITH REDUCED COST GLOBALIZATION REQUIRES MARKETING
STRATEGIES WORLDS POPULATION IS INCREASING AND MEETING THE FOOD
DEMAND IS A CHALLENGE Slide 3 EXAMPLE 1 : SOYBEAN Slide 4 Slide 5
TOP SOYBEAN PRODUCING COUNTRIES Slide 6 EXAMPLE 2: SUGAR Slide 7
TOP SUGAR PRODUCING COUNTRIES (x 1.000.000 MTONS) EUROPEAN
COMMUNITY............20 EUROPEAN COMMUNITY............20
NDIA..............................................16
NDIA..............................................16
CHINA............................................ 11
CHINA............................................ 11
USA................................................ 8
USA................................................ 8
THAILAND..................................... 7
THAILAND..................................... 7 EASTERN
EUROPE...................... 7 EASTERN EUROPE......................
7 AUSTRALIA................................... 5
AUSTRALIA................................... 5
BRASIL......................................... 28
BRASIL......................................... 28 Slide 8 Slide 9
CLIMATE ANOMALIES MONITORING Slide 10 MONTHLY RAINFALL ANOMALIES -
2003 SOURCE:CAMS XIE, CPTEC/INPE Slide 11 PREDICTING CLIMATE
VARIABILITY OR CLIMATE EXTREMES IS A CHALLENGE BECAUSE OF ITS
STRONG IMPACT ON SOCIETY ! Slide 12 METHODS FOR CLIMATE PREDICTION
SHORT-RANGE:SEASONAL TO INTERANNUAL SUCCESSFUL EXAMPLE: EL NIO
1997-98 SUCCESSFUL EXAMPLE: EL NIO 1997-98 SYSTEMATIC APPROACH: USE
AGCM/ARCM SYSTEMATIC APPROACH: USE AGCM/ARCM SINGLE MODEL:
LIMITATIONS DUE TO TEMPORAL AND SPATIAL SCALES BEING TOO LARGE
E.G., EASTERN COAST OF NEB SINGLE MODEL: LIMITATIONS DUE TO
TEMPORAL AND SPATIAL SCALES BEING TOO LARGE E.G., EASTERN COAST OF
NEB Slide 13 FORECAST OF THE EXPERIMENTAL CLIMATE PREDICTION CENTER
(ECPC), SAN DIEGO, CA, USA Slide 14 J. ROADS Slide 15 Slide 16
METHODS FOR CLIMATE PREDICTION SHORT-RANGE:SEASONAL TO INTERANNUAL
SUCCESSFUL EXAMPLE: EL NIO 1997-98 SUCCESSFUL EXAMPLE: EL NIO
1997-98 SYSTEMATIC APPROACH: USE AGCM/ARCM SYSTEMATIC APPROACH: USE
AGCM/ARCM SINGLE MODEL: LIMITATIONS DUE TO TEMPORAL AND SPATIAL
SCALES BEING TOO LARGE E.G., EASTERN COAST OF NEB SINGLE MODEL:
LIMITATIONS DUE TO TEMPORAL AND SPATIAL SCALES BEING TOO LARGE
E.G., EASTERN COAST OF NEB POOLED MULTI - MODEL ENSEMBLES: IRI
GENERATES PROBABILITIES DISTRIBUTION FORECASTS IMPROVED FORECASTS !
POOLED MULTI - MODEL ENSEMBLES: IRI GENERATES PROBABILITIES
DISTRIBUTION FORECASTS IMPROVED FORECASTS ! Slide 17 FORECAST OF
THE INTERNATIONAL RESEARCH INSTITUTE FOR CLIMATE PREDICTION (IRI),
NEW YORK, USA Slide 18 85% T. BARNSTON Slide 19 METHODS FOR CLIMATE
PREDICTION SHORT-RANGE:SEASONAL TO INTERANNUAL SUCCESSFUL EXAMPLE:
EL NIO 1997-98 SUCCESSFUL EXAMPLE: EL NIO 1997-98 SYSTEMATIC
APPROACH: USE AGCM/ARCM SYSTEMATIC APPROACH: USE AGCM/ARCM SINGLE
MODEL: LIMITATIONS DUE TO TEMPORAL AND SPATIAL SCALES BEING TOO
LARGE E.G., EASTERN COAST OF NEB SINGLE MODEL: LIMITATIONS DUE TO
TEMPORAL AND SPATIAL SCALES BEING TOO LARGE E.G., EASTERN COAST OF
NEB POOLED MULTI - MODEL ENSEMBLES: IRI GENERATES PROBABILITIES
DISTRIBUTION FORECASTS IMPROVED FORECASTS ! POOLED MULTI - MODEL
ENSEMBLES: IRI GENERATES PROBABILITIES DISTRIBUTION FORECASTS
IMPROVED FORECASTS ! SIGNS OF NATURE:FARMERS ALMANACK ALLIGATOR,
DUCK, JOO-DE-BARRO (OVENBIRD) SIGNS OF NATURE:FARMERS ALMANACK
ALLIGATOR, DUCK, JOO-DE-BARRO (OVENBIRD) Slide 20
LONG-RANGE:DECADAL TO INTERDECADAL PURE STATISTICAL / STOCHASTIC DO
NOT TAKE IN ACCOUNT CLIMATE DYNAMICS. RELY ON STATIONARY SIGNAL
(CYCLES). PURE STATISTICAL / STOCHASTIC DO NOT TAKE IN ACCOUNT
CLIMATE DYNAMICS. RELY ON STATIONARY SIGNAL (CYCLES). USE OF
SIMILARITY BETWEEN CLIMATE STATES OR REGIMES COMBINED WITH
STATISTICAL / STOCHASTIC AND DIAGNOSTICS STUDIES. EXAMPLE : PDO USE
OF SIMILARITY BETWEEN CLIMATE STATES OR REGIMES COMBINED WITH
STATISTICAL / STOCHASTIC AND DIAGNOSTICS STUDIES. EXAMPLE : PDO
METHODS FOR CLIMATE PREDICTION Slide 21 PACIFIC DECADAL OSCILLATION
Slide 22 WARM PHASECOLD PHASE DATA SOURCE: NOAA CIRES / CDC Slide
23 SST PDO: WARM PHASE MINUS COLD PHASE >1.0C < - 0.4C Slide
24 1947-1976 1977-1998 1925-1946 WARMWARM COLD PACIFIC DECADAL
OSCILLATION Slide 25 WORLD CLIMATE Slide 26 GLOBAL MEAN TEMPERATURE
ANOMALIES AND PDO PHASES
---------------------------------------------------------------------
------------------------------------------
--------------------------------- WARM --------------------------
COLD -------------------------- WARM COINCIDENCE.....???? LITTLE
ICE AGE SOURCE: CRU / EAU /UK Slide 27 1947-1976 1977-1998
1925-1946 WARMWARM COLDCOLD PACIFIC DECADAL OSCILLATION Slide 28
---------------------------------------------------------------------
-------------------------- - 0,14C 1947-1976 COLD GLOBAL MEAN
TEMPERATURE ANOMALIES AND PDO PHASES Slide 29 1976 1998 COLD
WARMYEARS STANDARD DEVIATIONS MULTIVARIATE ENSO INDEX (MEI) Slide
30 1976 (MEI) MULTIVARIATE ENSO INDEX STANDARD DEVIATIONS YEARS
Slide 31 SOUTH AMERICA CLIMATE IMPACTS Slide 32 SLP 1948/76 1948/98
SLP 1977/98 1948/98 + - + COLD PHASE WARM PHASE + - (hPa) +- -
Slide 33 SLP 1977/98 1948/76 >-0.5 > +1.0 Slide 34 SLP JJA
1977/98 1948/76 SLP JFM 1977/98 1948/76 SUMMERWINTER Slide 35 RAIN
1948/76 1948/98 RAIN 1977/98 1948/76 - + + - COLD PHASE WARM PHASE
Slide 36 RAINFALL 1977/98 1948/76 (mm/day) > 4 < - 1 Slide 37
SURF. TEMP 1948/76 1948/98 SURF. TEMP 1977/98 1948/98 + + - - COLD
PHASE WARM PHASE +- Slide 38 SURF AIR TEMP 1977/98 1948/76 > 1C
~ 1.0 Slide 39 TSM 1977/98 48/98 TSM 1946/76 48/98 + + -- WARM
PHASE COLD PHASE - + Slide 40 CONCLUDING REMARKS THE VULNERABILITY
OF SOCIETY INCREASES WITH POPULATION GROWTH AND THE ABILITY TO MEET
SUSTAINABLE FOOD SUPPLY BECOMES QUESTIONABLE THE VULNERABILITY OF
SOCIETY INCREASES WITH POPULATION GROWTH AND THE ABILITY TO MEET
SUSTAINABLE FOOD SUPPLY BECOMES QUESTIONABLE FORECAST DELIVERY TO
USER HAVE TO BE IMPROVED. FORECAST DELIVERY TO USER HAVE TO BE
IMPROVED. FORECAST HAVE TO MEET USERS NEEDS. FORECAST HAVE TO MEET
USERS NEEDS. USERS HAVE TO LEARN ABOUT RISK OF FORECAST FAILING AND
ITS CONSEQUENCES. USERS HAVE TO LEARN ABOUT RISK OF FORECAST
FAILING AND ITS CONSEQUENCES. CLIMATE PREDICTION IS A KEY FACTOR
FOR ACHIEVING SUSTAINABILITY ! HOWEVER...... CLIMATE PREDICTION IS
A KEY FACTOR FOR ACHIEVING SUSTAINABILITY ! HOWEVER...... USE OF
ARCMs FOR DOWNSCALING CALL FOR BETTER SURFACE MET NETWORK. USE OF
ARCMs FOR DOWNSCALING CALL FOR BETTER SURFACE MET NETWORK. Slide 41
SUGGEST TO PERFORM DIAGNOSTIC STUDIES ON THE INFLUENCE OF PDO ON
LOCAL AND REGIONAL CLIMATE AND THEIR RESULTS TO BE USED IN
COMBINATION WITH FORECASTS. EXAMPLES: ONSET OF RAINY SEASON,
FREQUNCY OF SEVERE FROST OR DROUGHTS. SUGGEST TO PERFORM DIAGNOSTIC
STUDIES ON THE INFLUENCE OF PDO ON LOCAL AND REGIONAL CLIMATE AND
THEIR RESULTS TO BE USED IN COMBINATION WITH FORECASTS. EXAMPLES:
ONSET OF RAINY SEASON, FREQUNCY OF SEVERE FROST OR DROUGHTS. ARE
DECISION MAKERS PREPARED TO USE FORECASTS AS ISSUED? ARE DECISION
MAKERS PREPARED TO USE FORECASTS AS ISSUED? DO FARMERS BENEFIT FROM
FORECAST INFORMATION? DO FARMERS BENEFIT FROM FORECAST INFORMATION?
METHODS OF ESTIMATING IMPACTS OF CLIMATE VARIABILITY ADN CLIMATE
FORECASTS ON SOCIETY ARE NEEDED METHODS OF ESTIMATING IMPACTS OF
CLIMATE VARIABILITY ADN CLIMATE FORECASTS ON SOCIETY ARE NEEDED
CONCLUDING REMARKS Slide 42 THE END
