Search

Climate change impacts are already happening through the world, and it is now clear that there is the need for an adaptive response from global institutions down to the local level. Reducing vulnerability to cope with climate variability might be more challenging in tropical countries than in North America or Europe. The ten papers of this special issue were presented during the Adaptclim conference that was held by the Sinergia Project, the CLARIS LPB project, and the GeoData Institute in Asunción, Paraguay, in 2010. All papers, except one regarding the Brahmaputra Basin in South Asia, present studies from South America. These studies are first contextualized geographically and then are related one to another by a simplified vulnerability concept linking climate stress to sensitivity and adaptive capacity of natural and human systems. One half of the papers focus on actual or future climate change and the present-day causes of the vulnerability of natural and agrosystems. Droughts are and will be the main source of stress for agriculture in South America. Increasing fragmentation of forest of the center of this continent is aggravating their vulnerability to dry spells. Another half of the studies of this special issue deal with the adaptive capacity human populations to system perturbations produced or enhanced by climate change. The studies point out inclusion of traditional knowledge and involvement of local actors in their own vulnerability assessment to increase adaptive capacity. These elements of climate justice, giving voice to those less responsible for carbon emissions but bearing their most severe consequences, allow the particular needs of a community to be considered and can direct adaptation policy toward preserving or rebuilding their specific capabilities under threat from climate change. The special issue also made clear that a basin analysis of the climate change problem could provide information, results, and methods more readily of use for the local population and decision makers. [ABSTRACT FROM AUTHOR]

The goal of the CLARIS project was to build an integrated European–South American network dedicated to promote common research strategies to observe and predict climate changes and their consequent socio-economic impacts taking into account the climate and societal peculiarities of South America. Reaching that goal placed the present network as a privileged advisor to contribute to the design of adaptation strategies in a region strongly affected by and dependent on climate variability (e.g. agriculture, health, hydro-electricity). Building the CLARIS network required fulfilling the following three objectives: (1) The first objective of CLARIS was to set up and favour the technical transfer and expertise in earth system and regional climate modelling between Europe and South America together with the providing of a list of climate data (observed and simulated) required for model validations; (2) The second objective of CLARIS was to facilitate the exchange of observed and simulated climate data between the climate research groups and to create a South American high-quality climate database for studies in extreme events and long-term climate trends; (3) Finally, the third objective of CLARIS was to strengthen the communication between climate researchers and stakeholders, and to demonstrate the feasibility of using climate information in the decision-making process. [ABSTRACT FROM AUTHOR]

The present manuscript analyzes monthly equatorial Pacific indices by using a specific neural algorithm, the so-called “Self-Organizing Maps” (SOMs). The main result is a change found in the nature of the transitions between cold to warm and warm to cold extreme events from 1950 to present, around the late 1970s. SOM is an unsupervised clustering technique which allows one to reduce high-dimensional data space (in this case, three indices over 636 months) in terms of a smaller set of three-dimensional reference vectors (100) characterizing pertinent situations. These reference vectors, which are displayed on a two-dimension map, are closely related by a topological relationship leading us to discriminate La Niña conditions from the opposite El Niño conditions. In a second step, a Hierarchical Agglomerative Clustering (HAC) method is used to further group the reference vectors into a small number of clusters (12) whose spatial and temporal characteristics can be analyzed and interpreted in terms of physical parameters. Schematically, these 12 clusters can be divided into two “warm” clusters, six “neutral” or “transition” clusters and four “cold” clusters. In each particular group (warm, neutral, cold), the clusters mainly differ from each other by the amplitude of the anomalies, their spatial patterns and their temporal variability. Some clusters are found to be strongly linked to the boreal spring period, while others have barely any records during that season. Other clusters are associated with records mainly observed either prior to or after 1980. This suggests that the method is able to identify changes in the variability of the tropical Pacific basin observed on decadal time scales (1976 climate shift in our case). Each monthly record can be summarized by the cluster to which it belongs. The temporal evolution of this value during extreme ENSO events shows similar patterns (persistence in specific clusters and transition between groups of clusters) associated with comparable El Niño or La Niña events. The methodology described in the present study (SOM plus HAC) is suggested to be useful both for seasonal ENSO predictability and for the detection of decadal changes in ENSO behavior. [ABSTRACT FROM AUTHOR]

Projections for South America of future climate change conditions in mean state and seasonal cycle for temperature during the twenty-first century are discussed. Our analysis includes one simulation of seven Atmospheric-Ocean Global Circulation Models, which participated in the Intergovernmental Panel on Climate Change Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three Special Report on Emissions Scenarios (SRES) A2, A1B, and B1. We developed a statistical method based on neural networks and Bayesian statistics to evaluate the models’ skills in simulating late twentieth century temperature over continental areas. Some criteria [model weight indices (MWIs)] are computed allowing comparing over such large regions how each model captures the temperature large scale structures and contributes to the multi-model combination. As the study demonstrates, the use of neural networks, optimized by Bayesian statistics, leads to two major results. First, the MWIs can be interpreted as optimal weights for a linear combination of the climate models. Second, the comparison between the neural network projection of twenty-first century conditions and a linear combination of such conditions allows the identification of the regions, which will most probably change, according to model biases and model ensemble variance. Model simulations in the southern tip of South America and along the Chilean and Peruvian coasts or in the northern coasts of South America (Venezuela, Guiana) are particularly poor. Overall, our results present an upper bound of potential temperature warming for each scenario. Spatially, in SRES A2, our major findings are that Tropical South America could warm up by about 4°C, while southern South America (SSA) would also undergo a near 2–3°C average warming. Interestingly, this annual mean temperature trend is modulated by the seasonal cycle in a contrasted way according to the regions. In SSA, the amplitude of the seasonal cycle tends to increase, while in northern South America, the amplitude of the seasonal cycle would be reduced leading to much milder winters. We show that all the scenarios have similar patterns and only differ in amplitude. SRES A1B differ from SRES A2 mainly for the late twenty-first century, reaching more or less an 80–90% amplitude compared to SRES A2. SRES B1, however, diverges from the other scenarios as soon as 2025. For the late twenty-first century, SRES B1 displays amplitudes, which are about half those of SRES A2. [ABSTRACT FROM AUTHOR]

In this study, the mechanisms leading to the El Niño peak and demise are explored through a coupled general circulation model ensemble approach evaluated against observations. The results here suggest that the timing of the peak and demise for intense El Niño events is highly predictable as the evolution of the coupled system is strongly driven by a southward shift of the intense equatorial Pacific westerly anomalies during boreal winter. In fact, this systematic late-year shift drives an intense eastern Pacific thermocline shallowing, constraining a rapid El Niño demise in the following months. This wind shift results from a southward displacement in winter of the central Pacific warmest SSTs in response to the seasonal evolution of solar insolation. In contrast, the intensity of this seasonal feedback mechanism and its impact on the coupled system are significantly weaker in moderate El Niño events, resulting in a less pronounced thermocline shallowing. This shallowing transfers the coupled system into an unstable state in spring but is not sufficient to systematically constrain the equatorial Pacific evolution toward a rapid El Niño termination. However, for some moderate events, the occurrence of intense easterly wind anomalies in the eastern Pacific during that period initiate a rapid surge of cold SSTs leading to La Niña conditions. In other cases, weaker trade winds combined with a slightly deeper thermocline allow the coupled system to maintain a broad warm phase evolving through the entire spring and summer and a delayed El Niño demise, an evolution that is similar to the prolonged 1986/87 El Niño event. La Niña events also show a similar tendency to peak in boreal winter, with characteristics and mechanisms mainly symmetric to those described for moderate El Niño cases. [ABSTRACT FROM AUTHOR]

A numerical simulation is used to investigate the mixed layer heat balance of the tropical Pacific Ocean including the equatorial cold tongue and the region of vortices associated with tropical instability waves (TIWs). The study is motivated by a need to quantify the effects that TIWs have on the climatological heat budget of the cold tongue mixed layer; there has been some discrepancy between observations indicating very large equatorward heat transport by TIWs and models that disagree on the full three-dimensional budget. Validation of the model reveals that the TIW-induced circulation patterns are realistic but may have amplitudes about 15% weaker than those in the observations. The SST budget within tropical instabilities is first examined in a frame of reference moving with the associated tropical instability vortices (TIVs). Zonal advection of temperature anomalies and meridional advection of temperature by current anomalies dominate horizontal advection. These effects strongly heat the cold cusps and slightly cool the downwelling areas located at the leading edge of the vortices. Cooling by vertical mixing is structured at the vortex scale and almost compensates for horizontal advective heating in the cold cusps. In contrast to some previous studies, TIW-induced vertical advection is found to be negligible in the SST budget. Cooling by this term is only significant below the mixed layer. The effect of TIWs on the climatological heat budget is then investigated for the region bounded by 2°S–6°N, 160°–90°W, where instabilities are most active. TIW-induced horizontal advection leads to a warming of 0.84°C month-1, which is of the same order as the 0.77°C month-1 warming effect of atmospheric fluxes, while the mean currents and vertical mixing cool the upper ocean by -0.59°C month-1 and -1.06°C month-1, respectively. The cooling effect of TIW-induced vertical advection is also negligible in the long-term surface layer heat budget and only becomes significant below the mixed layer. The results above, and in particular the absence of cancellation between horizontal and vertical TIW-induced eddy advection, are robust in three other sensitivity experiments involving different mixing parameterizations and increased vertical resolution. [ABSTRACT FROM AUTHOR]

The Paraná-Plata basin is the second largest hydrological basin in South America and is of great importance for the countries of the region (Argentina, Bolivia, Brazil, Paraguay and Uruguay). The present study focuses on the long-term trends in basin-scale precipitation with special emphasis on the role of distribution changes in extreme large-scale precipitation events and on the characteristics and evolution of ENSO teleconnections over the last 50 years. First, we defined a Paraná-Plata basin total precipitation index (PTPI) as the precipitations spatially averaged over the hydrological basin. On interannual time scales, such an index is mainly representative of anomalous monsoon precipitations in the northern part of the basin and large convective precipitation anomalies in the center of the basin (Paraguay-southern Brazil-Uruguay-northern Argentina) typical of the canonical ENSO teleconnection pattern. Our major findings clearly highlight a positive trend in yearly averaged PTPI mainly from the late 1960s to the early 1980s with a strong dependence from month-to-month. The largest precipitation increase is observed from November to May in southern Brazil and Argentina. A close examination of PTPI distributions during the two halves of the period 1950-2001 shows that the changes in the mean state from 1950-1975 to 1976-2001 result from significant changes in each calendar month mean state and in the tails of the PTPI anomaly distributions in May with lesser and weaker large-scale dry events and stronger large-scale wet events. Further studies will be needed to assess whether the observed trend in large-scale extreme precipitation conditions can be related to natural climate variability or anthropogenic activities and whether it is associated to changes in local/regional extreme events. The stronger wet conditions in different months seem to be associated to changes in ENSO characteristics (amplitude, propagation, spatial structure, ...) since the 1982-1983 El Niño. Indeed, spatial ENSO teleconnections (stronger in November and April-May) have greatly evolved from 1950-1975 to 1976-2001. Moreover, we demonstrate that there is a strong modulation and displacement of the teleconnection patterns from one event to another, impeding the definition of robust statistical relationship between ENSO and precipitation in the Paraná-Plata basin (except maybe over a very limited area near the common border between Paraguay, Argentina and Brazil). Finally, the non-antisymmetrical patterns of precipitation between El Niño and La Niña conditions and the non-linear relationship between precipitation and either Niño3.4 or Niño1+2 sea surface temperature indices show that linear statistical forecast systems are actually of very limited use for impact predictions on society on a local or regional scale. [ABSTRACT FROM AUTHOR]