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Global climate models The last shows a trend much lower than the observed but also positive. This can be explained because some studies suggest that that there were additional forcings like solar and volcanic aerosols variability. The observed temperature anomaly along the century was also plotted. As can be seen, in general, there is a reasonable adjustment between the model and the observations with regard to long term trends, but the model does represent in an adequate manner the interannual variability. This is because of the intrinsically unpredictable character of the natural variability of the climatic system and according to this, no matter how perfect the models could be, the interannual variability in the long term will never be able to be well simulated. Meanwhile it is to be noticed that the trend of increase represented by the model follows the observed trend. Some further results of climate change simulation can be seen in the Chapter 12 and 13. Model intercomparison studies, such as those discussed above, provide valuable information on the differences between GCM projections and the reasons for these differences. However, the range of differences between GCM results is unlikely to be indicative of the full range of uncertainties about future climate. Three main sources of uncertainty can be identified: 1. Uncertainties in future greenhouse gas and aerosol emissions. The IS92 and provisional SRES emissions scenarios described in Chapter 12 exemplify these uncertainties, with each scenario implying different levels of atmospheric composition and hence of radiative forcing. 2. Uncertainties in global climate sensitivity, due to differences in the way physical processes and feedbacks are simulated in different models. This means that some GCMs simulate greater mean global warming per unit of radiative forcing than others. 3. Uncertainties in regional climate changes, which are apparent from the differences in regional estimates of climate change by different GCMs for the same, mean global warming. While the results of GCM experiments probably capture a large part of the uncertainty ranges in 2 and 3, they certainly cannot describe the range of uncertainty due to emissions described in 1. Due to constraints of time and resources, only a limited number of GCM experiments can be conducted. In addition, many experiments have been specifically designed to be directly comparable with other models, to aid model development, and their assumed forcing is very similar. Most early GCM experiments were for a hypothetical 2 x CO2 equilibrium case. The AOGCM outputs in the DDC are for transient forcing approximating to a 1% increase in equivalent CO2 per year (close to the IS92a emissions scenario). One set of runs for an IS92d emissions scenario (approximately a 0.5%/year increase) is also included from the HadCM2 model. Some alternative emissions scenarios have also been used in experiments with the GFDL model assuming 0.25, 0.5, 1, 2, and 4%/year increases (Kattenberg et al. 1996), but these are not included in the DDC. 147
Although changes in weather and climate extremes are important to society in general, it is only recently that evidence for changes we have observed until now has been able to be compared to similar changes that we see in model simulations for future climate (see Chapter 12). Despite of the global models have improved over time, they still have limitations that affect the simulation of extreme events because of the insufficient spatial resolution and of simulation errors, and because parameterizations that must represent processes that cannot yet be included explicitly in the models, particularly dealing with clouds and precipitation, are not adequate to represent this extreme events (Meehl et al. 2000). There is no general agreement yet among models concerning future changes in mid-latitude storms (intensity, frequency and variability), though there are now a number of studies that have looked at such possible changes and some show fewer weak but greater numbers of deeper mid-latitude lows, meaning a reduced total number of cyclones, which agree with some observational studies (e.g., Pezza and Ambrizzi 2003 and references therein). Due to the limitations of spatial resolution in current AOGCMs, climate models do not provide any direct information at present regarding lightening, hail, and tornadoes. These limitations are particularly important over the La Plata basin, once that a large percentage of its precipitation comes from MCCs and mid-latitude front systems. If the models are not able to include such systems, they will certainly have problems to correctly simulate the rainfall amount over the region. References Global climate models Gates, W. L., J. S. Boyle, C. Convey, G. G. Dease, C. M. Doutriaux, R. S. Drach, M. Fiorino, P. J. Gleckler, J. J. Hnilo, S. M. Marlais, T. J. Phillips, G. L. Potter, B. D. Santer, K. R. Sperber, K. E. Taylor and D. N. Williams 1999: An overview of the results of the atmospheric model intercomparison project (AMIP I). Bull. Amer. Meteor. Soc., 80, 29-55. Hack, J. J. 1993: Climate Sytem simulation: basic numerical and computational concepts. In Climate System Modeling, K.E. Trenberth editor, Cambridge University Press, 283-318. Intergovernmental Panel on Climate Change 2001: Climate Change 2001: The Scientific Basis. Cambridge University Press, 881pp. Kattenberg, A., F. Giorgi, H. Hrassl, G. A. Meehl, J. F. B. Mitchell, R. J. Stouffer, T. Tokioka, A. J. Weaver and T. M. L. Wigley 1996: In: Climate Change 1995: The Science of Climate Change. Contribution of Working Group I to the Second Assessment Report of the Intergovernmental Panel on Climate Change [Houghton, J.T., L.G. Meira Filho, B.A. Callander, N. Harris, A.Kattenberg, and K. Maskell (Eds). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 572pp. Kiehl, J. T. 1993: Atmospheric general circulation modeling. In Climate System Modeling, K.E. Trenberth editor, Cambridge University Press, 319-369. 148
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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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a) b) c) Mean Temperature Real evap
Page 97 and 98: The positive trends of the mean tem
Page 99 and 100: d) e) f) Mean Temperature Real evap
Page 101 and 102: a) b) c) Mean Temperature Real evap
Page 103 and 104: 7.5. Discussion and final comments
Page 105 and 106: ABSTRACT The water, as resource, is
Page 107 and 108: puts in risk large number of person
Page 109 and 110: The main services and problems of w
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: Global climate models Table 11.2. M
Page 151 and 152: Socio-economic variables and also s
Page 153 and 154: Applicability in impact assessments
Page 155 and 156: of the global climate system to the
Page 157 and 158: Climate scenarios B2: Assumes a wor
Page 159 and 160: Climate scenarios The reliability o
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
Page 171 and 172: La Plata basin are also considerabl
Page 173 and 174: 10 N EQ 10 S 20 S 30 S 40 S 50 S 10
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
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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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