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12.4.2. Sea level rise scenarios Climate scenarios One of the projected impacts in the context of global warming is the sea level rise. Both the thermal expansion of the sea water as well as the melting of the ice sheets and glaciers contribute to this phenomenon. In addition, local conditions such as descents in coastal lands, tectonic movements, changes in the oceanic circulation, tides and storms must also be considered in the elaboration of scenarios of future sea level change. Figure 12.3 shows different scenarios of sea level change that show between 0.25-0.45 m for the period 1900-2100 (IPCC 2001). If adding the uncertainties between the models this range increases to 0.20-0.70 m, and if all uncertainties are considered to 0.10-0.90 m. Fig. 12.3. Scenarios of sea level rise for the period 1990-2100. [IPCC, 2001] 12.5. Validation of GCMs outputs for the current period GCMs have been increasing their complexity to represent in an increasingly adequate manner the physical processes involved in the climate system. Even though they are not still capable of representing the totality of processes and have certain difficulties, like the interaction between radiation and aerosols, their capacity to represent current climate has been progressing and therefore the reliability of their future projections is growing. 157
Climate scenarios The reliability of future climate scenarios obtained from GCMs is based on their ability to represent current climate and its variability. Gates et al. (1999) presents results of some simulations on current climate made in the context of the Atmospheric Model Intercomparison Project (AMIP). The largest errors correspond to cloud cover and temperature at 200 hPa, while the lowest ones are in the surface temperature. The outputs related to the global hydrological processes within the AMIP project were analyzed by Lau et al. (1996) from the analysis of 29 GCMs. Although it is observed a great variability among the different models, when considering an ensemble of them, the result is very close to the observations showing an overestimation in the tropical precipitation and an underestimation in the extra-tropics. Results of GCMs developed by a group of institutes with high scientific and computer capability are available through the web page of the Data Distribution Centre (DDC) of the IPCC (www.dkrz.de/ipcc/ddc/html/SRES/SRES_all.html). Table 12.1 shows a list of models and the institutions that developed them. Their validation for the climate of Southeastern South America is presented in Chapter 13. Table 12.1. GCM with information available through the DDC. Model Institution Current period Future period HADCM3 Hadley Centre for Climate Prediction and Research (Reino Unido) 12.6. Climate change scenarios from GCMs In the previous section, the difficulties of the GCMs to represent current climate were mentioned. This imposes limitations on the reliability of the scenarios of future climate. Likewise, it is necessary to validate the GCMs outputs at a regional level before using them in the preparation of scenarios. A way to elaborate climate change scenarios based on GCMs despite of errors that they show in the representation of current climate consists of preparing scenarios of differences between what is foreseen by GCMs for the future and its representation for the current baseline climate. This way, it is obtained a spatial distribution of the change in climate variables based exclusively on one GCM results. 158 1950-1999 2000-2100 Australia's Commonwealth Scientific CSIRO-mk2 and Industrial Research Organization 1961-1999 2000-2100 (Australia) ECHAM4/ Max Planck Institute OPYC3 für Meteorologie (Alemania) GFDL-R30 NCAR-PCM CCCma Geophysical Fluid Dynamics Laboratory (Estados Unidos) National Centre for Atmospheric Research (Estados Unidos) Canadian Center for Climate Modeling and Analysis (Canadá) 1990-1999 2000-2100 1961-1999 2000-2100 1981-1999 2000-2100 1950-1999 2000-2100
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CLIMATE CHANGE IN THE LA PLATA BASI
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INDEX FOREWORD . . . . . . . . . .
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7.3. Methodology . . . . . . . . .
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13.3. Regional validation of GCM fo
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1.1. Dropping the hypothesis of sta
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Introduction as they pour water ove
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A better understanding of the obser
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References Introduction Barros, V.
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ABSTRACT The hydrologic cycle of th
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La Plata basin climatology Within t
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in this last description, although
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warm season (October-April), in the
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La Plata basin climatology b. Upper
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La Plata basin climatology 2.3.3. R
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La Plata basin climatology Fig. 2.8
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2.3.7. West and South borders La Pl
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References La Plata basin climatolo
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La Plata basin climatology Robertso
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3.1. Introduction Interannual low f
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Interannual low frequency variabili
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1989). This signal varies along eac
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Interannual low frequency variabili
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The main physiographic and hydrolog
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SUB-BASIN COUNTRY Argentina Bolivia
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the most important stretches of the
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Physiography and Hydrology The Para
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Physiography and Hydrology The Pant
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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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Page 111 and 112: There are similar problems in diffe
Page 113 and 114: 8.3.3. Energy a. Hydroelectric depe
Page 115 and 116: (chapters 12 and 13), because of th
Page 117 and 118: The main services and problems of w
Page 119 and 120: 9.1. Introduction The emissions of
Page 121 and 122: 9.4. Greenhouse effect The atmosphe
Page 123 and 124: Temperature anomalies (°C) 0.8 0.6
Page 125 and 126: Global climatic change at a global
Page 127 and 128: In view of the unavoidability of th
Page 129 and 130: Background on other regional aspect
Page 135 and 136: Considering the non-linear interact
Page 137 and 138: SST anomalies also have influence o
Page 141 and 142: ABSTRACT The purpose of this chapte
Page 143 and 144: Global climate models Mid-1970’s
Page 145 and 146: Global climate models Table 11.1. B
Page 147 and 148: Global climate models Table 11.2. M
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Page 151 and 152: Socio-economic variables and also s
Page 153 and 154: Applicability in impact assessments
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Page 157: Climate scenarios B2: Assumes a wor
Page 161 and 162: Climate scenarios From Table 12.2 i
Page 163 and 164: Climate scenarios Fig. 12.5. The mu
Page 165 and 166: Climate scenarios this would be rel
Page 167 and 168: Results of global circulation model
Page 169 and 170: 13.2.3. Statistical downscaling The
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Page 175 and 176: Regional climatic scenarios Fig. 13
Page 177 and 178: a. Pre-industrial experiment: Initi
Page 183 and 184: Regional climatic scenarios Kalnay,
Page 185 and 186: Low-frequency variability 14.1. Bac
Page 187 and 188: egime occurred during the periods o
Page 189 and 190: Fig. 14.2. As Fig. 14.1, except for
Page 191 and 192: 14.4. SST composites Low-frequency
Page 193 and 194: Low-frequency variability during th
Page 195 and 196: Fig. 14.10. As Fig. 14.9, except fo
Page 197 and 198: Low-frequency variability In genera
Page 199 and 200: Low-frequency variability Mantua, N
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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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