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10.2. Regional effects of biomass burning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .129 10.3. Land use change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .131 10.3.1. Deforestation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .131 10.3.2. Urban effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .135 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .136 CHAPTER XI GLOBAL CLIMATE MODELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .140 11.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .141 11.2. Atmospheric General Circulation models (AGCMs) . . . . . . . . . . . . . . . . . . .142 11.3. AGCMs uncertainties and their use for Climate Change studies . . . . . . . . . .145 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .148 CHAPTER XII CLIMATE SCENARIOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .150 12.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151 12.2. Criteria for the selection of climatic scenarios . . . . . . . . . . . . . . . . . . . . . . . .151 12.3. Techniques for developing climatic scenarios . . . . . . . . . . . . . . . . . . . . . . . . .152 12.3.1. Synthetic Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152 12.3.2. Analogous Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152 a. Temporal analogous scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .153 b. Spatial analogous scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .153 12.3.3. Scenarios from global climate models outputs . . . . . . . . . . . . . . . . . . . . . . . .153 12.4. Development of other scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .154 12.4.1. Social Economic Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .154 12.4.2. Sea level raise scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .157 12.5 Validation of the GCM for the current period . . . . . . . . . . . . . . . . . . . . . . . . .157 12.6 Climate change scenarios from GCM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .158 12.6.1. Baseline scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .159 12.6.2. Global scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .159 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .165 CHAPTER XIII REGIONAL CLIMATIC SCENARIOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . .166 13.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167 13.2. Regional Climatic Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167 13.2.1. Direct use of GCM outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167 13.2.2. Interpolation of GCM outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167 13.2.3. Statistical downscaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .168 13.2.4. High resolution experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .168
13.3. Regional validation of GCM for South America . . . . . . . . . . . . . . . . . . . . .169 13.4. Regional Scenarios for the La Plata basin . . . . . . . . . . . . . . . . . . . . . . . . . . . .171 13.4.1. Hadley Centre GCM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .171 13.4.2. Regional features in other Climate Change experiments . . . . . . . . . . . . . . . .174 a. Pre-industrial period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .176 b. 1% increase in CO2 up to doubling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .176 c. Climate of the twentieth century . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .177 13.4.3. Hadley Centre and ECHAM GCM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .179 13.5. Future plans of CPTEC/INPE in Climate Change modeling . . . . . . . . . . . . .179 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .181 CHAPTER XIV LOW-FREQUENCY VARIABILITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .183 14.1. Background on low frequency variability . . . . . . . . . . . . . . . . . . . . . . . . . . . .184 14.2. Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .185 14.3. Precipitation Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .186 14.4. SST composites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .190 14.5. SLP composites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .192 14.6. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .195 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .197 CHAPTER XV STATISTICAL ANALYSIS OF EXTREME EVENTS IN A NON-STATIONARY CONTEXT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .199 15.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .200 15.2. Parametric and non-parametric methods for detecting trend in hydrological variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .201 15.3. Example: Testing for trend in annual maximum one-hour rainfall at Porto Alegre, Brazil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .202 15.4. Example: POT procedure applied to fitting daily rainfalls at Ceres, Argentina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .204 15.5. Records with missing values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .209 15.6. Spatial trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .211 15.7. Methods based on L-moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .212 15.8. The concept of return period in the presence of time-trends . . . . . . . . . . . . .213 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .215 Curricula of the autors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .216
Page 1 and 2: CLIMATE CHANGE IN THE LA PLATA BASI
Page 3 and 4: INDEX FOREWORD . . . . . . . . . .
Page 5: 7.3. Methodology . . . . . . . . .
Page 9 and 10: 1.1. Dropping the hypothesis of sta
Page 11 and 12: Introduction as they pour water ove
Page 13 and 14: A better understanding of the obser
Page 15 and 16: References Introduction Barros, V.
Page 17 and 18: ABSTRACT The hydrologic cycle of th
Page 19 and 20: La Plata basin climatology Within t
Page 21 and 22: in this last description, although
Page 23 and 24: warm season (October-April), in the
Page 25 and 26: La Plata basin climatology b. Upper
Page 27 and 28: La Plata basin climatology 2.3.3. R
Page 29 and 30: La Plata basin climatology Fig. 2.8
Page 31 and 32: 2.3.7. West and South borders La Pl
Page 33 and 34: References La Plata basin climatolo
Page 35 and 36: La Plata basin climatology Robertso
Page 37 and 38: 3.1. Introduction Interannual low f
Page 39 and 40: Interannual low frequency variabili
Page 41 and 42: 1989). This signal varies along eac
Page 43 and 44: Interannual low frequency variabili
Page 45 and 46: The main physiographic and hydrolog
Page 47 and 48: SUB-BASIN COUNTRY Argentina Bolivia
Page 49 and 50: the most important stretches of the
Page 51 and 52: Physiography and Hydrology The Para
Page 53 and 54: Physiography and Hydrology The Pant
Page 55 and 56: Physiography and Hydrology forcings
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Physiography and Hydrology It is no
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Physiography and Hydrology tion of
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Physiography and Hydrology INTERNAV
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5.1. Introduction Precipitation and
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From 1956 to 1991, in most of the A
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-15 -20 -25 -30 -35 -40 -15 -20 -25
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Regional precipitation trends 5.3.2
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Regional precipitation trends and L
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trast, other regions suffer floodin
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ABSTRACT The main hydrological tren
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Following are the observed changes:
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In the case of the Paraná River th
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Hydrological trends In order to com
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Hydrological trends In table 6.1 it
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Hydrological trends On the other ha
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the central area of the high basin
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7.1. Introduction Several authors,
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Real evaporation trends a) PET > Pi
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a) b) c) Mean Temperature Real evap
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The positive trends of the mean tem
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d) e) f) Mean Temperature Real evap
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7.5. Discussion and final comments
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ABSTRACT The water, as resource, is
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puts in risk large number of person
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The main services and problems of w
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There are similar problems in diffe
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8.3.3. Energy a. Hydroelectric depe
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(chapters 12 and 13), because of th
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The main services and problems of w
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9.1. Introduction The emissions of
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9.4. Greenhouse effect The atmosphe
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Temperature anomalies (°C) 0.8 0.6
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Global climatic change at a global
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In view of the unavoidability of th
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Background on other regional aspect
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Considering the non-linear interact
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SST anomalies also have influence o
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ABSTRACT The purpose of this chapte
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Global climate models Mid-1970’s
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Global climate models Table 11.1. B
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Global climate models Table 11.2. M
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Although changes in weather and cli
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Socio-economic variables and also s
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Applicability in impact assessments
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of the global climate system to the
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Climate scenarios B2: Assumes a wor
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Climate scenarios The reliability o
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Climate scenarios From Table 12.2 i
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Climate scenarios Fig. 12.5. The mu
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Climate scenarios this would be rel
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Results of global circulation model
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13.2.3. Statistical downscaling The
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La Plata basin are also considerabl
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10 N EQ 10 S 20 S 30 S 40 S 50 S 10
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Regional climatic scenarios Fig. 13
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a. Pre-industrial experiment: Initi
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Regional climatic scenarios Kalnay,
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Low-frequency variability 14.1. Bac
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egime occurred during the periods o
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Fig. 14.2. As Fig. 14.1, except for
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14.4. SST composites Low-frequency
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Low-frequency variability during th
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Fig. 14.10. As Fig. 14.9, except fo
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Low-frequency variability In genera
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Low-frequency variability Mantua, N
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15.1. Introduction Statistical anal
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Statistical analysis of extreme eve
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CURRÍCULA OF THE AUTHORS Vicente B
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Curricula of the autors Rubén Mari
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Proyect: SGP II 057: “Trends in t
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