Showing papers by "Zbigniew W. Kundzewicz published in 2012"

Changes in impacts of climate extremes: Human systems and ecosystems

Abstract: In this chapter, two different types of impacts on human and ecological systems are examined: (i) impacts of extreme weather and climate events; and (ii) extreme impacts triggered by less-than-extreme weather or climate events (in combination with non-climatic factors, such as high exposure and/or vulnerability). Where data are available, impacts are examined from sectoral and regional perspectives.

Changes in Flood Risk in Europe

Abstract: This interdisciplinary book, authored by an international team, offers: • A comprehensive overview of flood risk in Europe, past and present, and future • National/regional chapters covering Central Europe, Western Europe, Southern Europe and Northern Europe, the Alpine region and the Iberian Peninsula. • A focus on detection and attribution of change with respect to climate change and its impacts, water resources and flood risk, the re-insurer’s view point, and future projections of flood risk • Rectification of common-place judgements, e.g.: “climate is warming so floods should become more frequent and intense”; observations do not always confirm this expectation

Historical Floods in Europe in the Past Millennium

Abstract: The paper focuses on floods in Europe derived from documentary evidence during the past millennium. The beginnings of early-instrumental and systematic-instrumental hydrological observations in Europe are discussed. Basic sources of documentary evidence related to floods and the problems that may be encountered in the use of historical source materials are described. An overview of documentary-based flood research in the form of long-term frequency and severity series, as well as a summary of the most disastrous floods in the Mediterranean, Western, Central and Northern Europe, is presented. The role and value of floods described in the documentary record to better understanding current flood risks in Europe are discussed.

Climate change regional review: Poland

Abstract: Poland is a country where a climate change warming signal can be detected in temperature, but observed changes in other variables, and especially in precipitation, are complex. Temperature projections indicate further warming, but models do not agree as to seasonal distribution of changes in precipitation. This article reviews evidence for climate change and its impacts in Poland, in the context of observations and projections. It also reviews various aspects of climate change mitigation policy in the country whose energy supply is more coal-dominated than any other country. This is one reason why climate change mitigation efforts are modest and climate policy largely passive. The dramatic decline of industrial production involving a rapid decline in CO2 emissions during 1989–1992 was the crucial element of the Poland's position in the negotiations of international agreements. The European Union (EU) accession in 2004 tied Poland to EU climate policy. This cautious approach is largely in harmony with public attitudes. Poles are aware of climate change, but it is not considered as a priority issue and public opinion is divided about the issues of mitigation. Adaptation to climate change impacts in Poland is driven by the fact that observed impacts are not very large and there is no persuasive attribution of these impacts to greenhouse gas emissions. Reactive adaptation to climate change is preferred over anticipatory adaptation. There are several ‘special care’ areas in Poland in terms of adaptation: the mountains; the coastal zone of the Baltic Sea; and the river valleys. WIREs Clim Change 2012 doi: 10.1002/wcc.175 This article is categorized under: Trans-Disciplinary Perspectives > National Reviews

Modeling global temperature changes with genetic programming

Abstract: We use genetic programming (GP), a variant of evolutionary computation, to build interpretable models of global mean temperature as a function of natural and anthropogenic forcings. In contrast to the conventional approach, which engages models that are physically-based but very data-demanding and computation-intense, the proposed method is a data-driven randomized search algorithm capable of inducing a model from moderate amount of training data at reasonable computational cost. GP maintains a population of models and recombines them iteratively to improve their performance meant as an ability to explain the training data. Each model is a multiple input-single output arithmetic expression built of a predefined set of elementary components. Inputs include external climate forcings, such as solar activity, volcanic eruptions, composition of the atmosphere (greenhouse gas concentration and aerosols), and indices of internal variability (oscillations in the Ocean-Atmosphere system), while the output is the large-scale temperature. We used the data from the period 1900-1999 for training and the period 2000-2009 for testing, and employed two quality measures: mean absolute error and correlation coefficient. The experiment showed that the models evolved by GP are capable to predict, based exclusively on non-temperature data, the global temperature more accurately than a reference approach known in the literature.