Catálogo de publicaciones - libros

The aim of climate research is to increase our knowledge about the nature of climate and the causes of climate variability and change. Increasing our understanding of the physical processes on various spatial and temporal scales will ultimately reduce uncertainty and improve our capabilities to predict climate on monthly to seasonal timescales and allow us to separate the anthropogenic and natural causes of long term climate change.

A detailed analysis is undertaken of the Atlantic-European climate using data from 500-year-long proxy-based climate reconstructions, a long climate simulation with perpetual 1990 forcing, as well as two global and one regional climate change scenarios. The observed and simulated interannual variability and teleconnectivity are compared and interpreted in order to improve the understanding of natural climate variability on interannual to decadal time scales for the late Holocene. The focus is set on the Atlantic-European and Alpine regions during the winter and summer seasons, using temperature, precipitation, and 500 hPa geopotential height fields. The climate reconstruction shows pronounced interdecadal variations that appear to “lock” the atmospheric circulation in quasi-steady long-term patterns over multi-decadal periods controlling at least part of the temperature and precipitation variability. Different circulation patterns are persistent over several decades for the period 1500 to 1900. The 500-year-long simulation with perpetual 1990 forcing shows some substantial differences, with a more unsteady teleconnectivity behaviour. Two global scenario simulations indicate a transition towards more stable teleconnectivity for the next 100 years. Time series of reconstructed and simulated temperature and precipitation over the Alpine region show comparatively small changes in interannual variability within the time frame considered, with the exception of the summer season, where a substantial increase in interannual variability is simulated by regional climate models.

The tasks of providing multi-decadal climate projections and seasonal plus subseasonal climate predictions are of significant societal interest and pose major scientific challenges. An outline is presented of the challenges posed by, and the approaches adopted to, tracing the possible evolution of the climate system on these various time-scales. First an overview is provided of the nature of the climate system’s natural internal variations and the uncertainty arising from the complexity and non-linearity of the system. Thereafter consideration is given sequentially to the range of extant approaches adopted to study and derive multi-decadal climate projections, seasonal predictions, and significant sub-seasonal weather phenomena. For each of these three time-scales novel results are presented that indicate the nature (and limitations) of the models used to forecast the evolution, and illustrate the techniques adopted to reduce or cope with the forecast uncertainty. In particular, the contributions (i) appear to exemplify that in simple climate models uncertainties in radiative forcing outweigh uncertainties associated with ocean models, (ii) examine forecast skills for a state-of-the-art seasonal prediction system, and (iii) suggest that long-lived weather phenomena can help shape intra-seasonal climate variability. Finally, it is argued, that co-consideration of all these scales can enhance our understanding of the challenges associated with uncertainties in climate prediction.

Changes of the summer evapotranspiration regime under increased levels of atmospheric greenhouse gases are discussed for three Alpine river basins on the basis of a new set of simulations carried out with a high-resolution hydrological model. The climate change signal was inferred from the output of two simulations with a state-of-the-art global climate model (GCM), a reference run valid for 1961–1990 and a time-slice simulation valid for 2071–2100 under forcing from the A2 IPCC emission scenario. In this particular GCM experiment and with respect to the Alpine region summer temperature was found to increase by 3 to 4°C, whereas precipitation was found to decrease by 10 to 20%. Global radiation and water vapor pressure deficit were found to increase by about 5% and 2 hPa, respectively. On this background, an overall increase of potential evapotranspiration of about 20% relative to the baseline was predicted by the hydrological model, with important variations between but also within individual basins. The results of the hydrological simulations also revealed a reduction in the evapotranspiration efficiency that depends on altitude. Accordingly, actual evapotranspiration was found to increase at high altitudes and to the south of the Alps, but to decrease in low elevation areas of the northern forelands and in the inner-Alpine domain. Such a differentiation does not appear in the GCM scenario, which predicts an overall increase in evapotranspiration over the Alps. This underlines the importance of detailed simulations for the quantitative assessment of the regional impact of climate change on the hydrological cycle.

There is growing evidence that, as a result of global climate change, some of the most severe weather events could become more frequent in Europe over the next 50 to 100 years. The paper aims to (i) describe observed trends and scenarios for summer heat waves, windstorms and heavy precipitation, based on results from simulations with global circulation models, regional climate models, and other downscaling procedures, and (ii) discuss potential impacts on agricultural systems and forests in Switzerland. Trends and scenarios project more frequent heavy precipitation during winter corresponding, for example, to a three-fold increase in the exceedance of today’s 15-year extreme values by the end of the 21st century. This increases the risk of large-scale flooding and loss of topsoil due to erosion. In contrast, constraints in agricultural practice due to waterlogged soils may become less in a warmer climate. In summer, the most remarkable trend is a decrease in the frequency of wet days, and shorter return times of heat waves and droughts. This increases the risk of losses of crop yield and forage quality. In forests, the more frequent occurrence of dry years may accelerate the replacement of sensitive tree species and reduce carbon stocks, and the projected slight increase in the frequency of extreme storms by the end of the century could increase the risk of windthrow. Some possible measures to maintain goods and services of agricultural and forest ecosystems are mentioned, but it is suggested that more frequent extremes may have more severe consequences than progressive changes in means. In order to effectively decrease the risk for social and economic impacts, long-term adaptive strategies in agriculture and silviculture, investments for prevention, and new insurance concepts seem necessary.

In this paper, we study optimal economic growth programs coupled with climate change dynamics. The study is based on models derived from MERGE, a well established integrated assessment model (IAM). We discuss first the introduction in MERGE of a set of “tolerable window” constraints which limit both the temperature change and the rate of temperature change. These constraints, obtained from ensemble simulations performed with the Bern 2.5-D climate model, allow us to identity a domain intended to preserve the Atlantic thermohaline circulation. Next, we report on experiments where a two-way coupling is realized between the economic module of MERGE and an intermediate complexity “3-D-” climate model (C-GOLDSTEIN) which computes the changes in climate and mean temperature. The coupling is achieved through the implementation of an advanced “oracle based optimization technique” which permits the integration of information coming from the climate model during the search for the optimal economic growth path. Both cost-effectiveness and cost-benefit analysis modes are explored with this combined “meta-model” which we refer to as GOLDMERGE. Some perspectives on future implementations of these approaches in the context of “collaborative” or “community” integrated assessment modules are derived from the comparison of the different approaches.

In this two-part paper we evaluate the effect of “endogenizing” technological learning and strategic behavior of agents in economic models used to assess climate change policies. In the first part we show the potential impact of R&D policies or demonstration and deployment (D&D) programs in the context of stringent stabilization scenarios. In the second part we show how game-theoretic methods can be implemented in climate change economic models to take into account three types of strategic interactions: (i) the market power of the countries benefiting from very low abatement costs on international markets for CO_2 emissions, (ii) the strategic behavior of governments in the domestic allocation of CO_2 emissions quotas, and (iii) the non-cooperative behavior of countries and regions in the burden sharing of CO_2 concentration stabilization. The two topics of endogenous learning and game-theoretic approach to economic modeling are two manifestations of the need to take into account the strategic behavior of agents in the evaluation of climate change policies. In the first case an R&D policy or a demonstration and deployment (D&D) program are put in place in order to attain a cost reduction through the learning effect; in the second case the agents (countries) reply optimally to the actions decided by the other agents by exploiting their strategic advantages. Simulations based on integrated assessment models illustrate the approaches. These studies have been conducted under the Swiss NCCR-Climate program.

This paper explores the reasons why economic instruments of climate change are reluctantly applied and stresses the need for interdisciplinary research linking economic theory and empirical testing to deliberative political procedures. It is divided in three parts. The first one recalls the main issues in implementing Cost-Benefit Analysis such as information problems, uncertainties, discounting the future and irreversibilities. The second part shows how these issues can be treated in integrated assessment and techno-economic models and presents a case study, which shows that The chosen scenario tends to stabilize atmospheric CO_2 concentration at around 550 ppm in the long run. Exclusion of possibility to trade CO_2 emission permits under a cap regime would increase the cost of emission abatement for OECD countries. Combining different flexibility instruments might lead to significant gains in the overall cost of climate policy. The third part presents results of a survey conducted among the main economic and environmental associations in Switzerland. The survey reveals conflicting views on economic instruments. It shows how the social acceptability of these instruments can be improved in taking explicitly into account these opposing views of special interest groups. Therefore, policy scenarios should be selected in combining techno-economic models with empirical studies about their political and normative context.