DEPARTAMENTO DE METEOROLOGIA UNIVERSIDADE FEDERAL DE ALAGOAS REGIONAL MEETING ON CLIPS AND AGROMETEOROLOGICAL APPLICATIONS FOR THE MERCOSUR COUNTRIES LUIZ CARLOS B. MOLION LONG-TERM CLIMATE PREDICTION AS A MARKETING STRATEGY CAMPINAS, SÃO PAULO, BRAZIL - JULY 13 TO

CLIMATE MONITORING AND PREDICTION: A KEY FACTOR TO INCREASING PRODUCTION WITH REDUCED COST GLOBALIZATION REQUIRES MARKETING STRATEGIES WORLD’S POPULATION IS INCREASING AND MEETING THE FOOD DEMAND IS A CHALLENGE

EXAMPLE 1 : SOYBEAN

TOP SOYBEAN PRODUCING COUNTRIES   

EXAMPLE 2: SUGAR

TOP SUGAR PRODUCING COUNTRIES (x MTONS) EUROPEAN COMMUNITY EUROPEAN COMMUNITY ÍNDIA ÍNDIA CHINA CHINA USA USA THAILAND THAILAND EASTERN EUROPE EASTERN EUROPE AUSTRALIA AUSTRALIA BRASIL BRASIL

CLIMATE ANOMALIES MONITORING

MONTHLY RAINFALL ANOMALIES SOURCE:CAMS XIE, CPTEC/INPE

PREDICTING CLIMATE VARIABILITY OR CLIMATE EXTREMES IS A CHALLENGE BECAUSE OF ITS STRONG IMPACT ON SOCIETY !

METHODS FOR CLIMATE PREDICTION SHORT-RANGE:SEASONAL TO INTERANNUAL SUCCESSFUL EXAMPLE: EL NIÑO SUCCESSFUL EXAMPLE: EL NIÑO 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

FORECAST OF THE EXPERIMENTAL CLIMATE PREDICTION CENTER (ECPC), SAN DIEGO, CA, USA

J. ROADS

METHODS FOR CLIMATE PREDICTION SHORT-RANGE:SEASONAL TO INTERANNUAL SUCCESSFUL EXAMPLE: EL NIÑO SUCCESSFUL EXAMPLE: EL NIÑO 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 !

FORECAST OF THE INTERNATIONAL RESEARCH INSTITUTE FOR CLIMATE PREDICTION (IRI), NEW YORK, USA

   85%  T. BARNSTON

METHODS FOR CLIMATE PREDICTION SHORT-RANGE:SEASONAL TO INTERANNUAL SUCCESSFUL EXAMPLE: EL NIÑO SUCCESSFUL EXAMPLE: EL NIÑO 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, JOÃO-DE-BARRO (“OVENBIRD”) “SIGNS” OF NATURE:FARMERS ALMANACK ALLIGATOR, DUCK, JOÃO-DE-BARRO (“OVENBIRD”)

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

PACIFIC DECADAL OSCILLATION

  WARM PHASECOLD PHASE   DATA SOURCE: NOAA CIRES / CDC

SST PDO: WARM PHASE MINUS COLD PHASE >1.0°C  < - 0.4°C

      WARMWARM COLD PACIFIC DECADAL OSCILLATION

WORLD CLIMATE

GLOBAL MEAN TEMPERATURE ANOMALIES AND PDO PHASES WARM COLD WARM COINCIDENCE.....???? LITTLE ICE AGE SOURCE: CRU / EAU /UK

       WARMWARM COLDCOLD PACIFIC DECADAL OSCILLATION

,14°C   COLD GLOBAL MEAN TEMPERATURE ANOMALIES AND PDO PHASES

1976   1998 COLD WARMYEARS STANDARD DEVIATIONS MULTIVARIATE ENSO INDEX (MEI)

1976 (MEI) MULTIVARIATE ENSO INDEX STANDARD DEVIATIONS YEARS

SOUTH AMERICA CLIMATE IMPACTS

SLP 1948/76 – 1948/98 SLP 1977/98 – 1948/ COLD PHASE WARM PHASE + - (hPa) +- -

SLP 1977/98 – 1948/76 >-0.5 > +1.0

SLP JJA 1977/98 – 1948/76 SLP JFM 1977/98 – 1948/76 SUMMERWINTER

RAIN 1948/76 – 1948/98 RAIN 1977/98 – 1948/ COLD PHASE WARM PHASE

RAINFALL 1977/98 – 1948/76 (mm/day) > 4 < - 1

SURF. TEMP 1948/76 – 1948/98 SURF. TEMP 1977/98 – 1948/ COLD PHASE WARM PHASE +-

SURF AIR TEMP 1977/98 – 1948/76 > 1°C ~ 1.0

TSM 1977/98 – 48/98 TSM 1946/76 – 48/ WARM PHASE COLD PHASE - +

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.

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

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