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The Mediterranean has been identified as one of the most responsive regions to climate change. It has been conjectured that one of the effects of a warmer climate could be to make the Mediterranean Sea prone to the formation of hurricanes. Already in the present climate regime, however, a few of the numerous low pressure systems that form in the area develop a dynamical evolution similar to the one of tropical cyclones. Even if their spatial extent is generally smaller and the life cycle shorter compared to tropical cyclones, such storms produce severe damage on the highly populated coastal areas surrounding the Mediterranean Sea. This study, based on the analysis of individual realistically simulated storms in homogeneous long-term and high-resolution data from multiple climate change scenarios, shows that the projected effect of climate change on Mediterranean tropical-like cyclones is decreased frequency and a tendency toward a moderate increase of intensity.

An important challenge in current climate modeling is to realistically describe small-scale weather statistics, such as topographic precipitation and coastal wind patterns, or regional phenomena like polar lows. Global climate models simulate atmospheric processes with increasingly higher resolutions, but still regional climate models have a lot of advantages. They consume less computation time because of their limited simulation area and thereby allow for higher resolution both in time and space as well as for longer integration times. Regional climate models can be used for dynamical down-scaling purposes because their output data can be processed to produce higher resolved atmospheric fields, allowing the representation of small-scale processes and a more detailed description of physiographic details (such as mountain ranges, coastal zones, and details of soil properties). However, does higher resolution add value when compared to global model results? Most studies implicitly assume that dynamical downscaling leads to output fields that are superior to the driving global data, but little work has been carried out to substantiate these expectations. Here a series of articles is reviewed that evaluate the benefit of dynamical downscaling by explicitly comparing results of global and regional climate model data to the observations. These studies show that the regional climate model generally performs better for the medium spatial scales, but not always for the larger spatial scales. Regional models can add value, but only for certain variables and locations—particularly those influenced by regional specifics, such as coasts, or mesoscale dynamics, such as polar lows. Therefore, the decision of whether a regional climate model simulation is required depends crucially on the scientific question being addressed.

Changes in precipitation characteristics directly affect society through their impacts on drought and floods, hydro-dams, and urban drainage systems. Global warming increases the water holding capacity of the atmosphere and thus the risk of heavy precipitation. Here, daily precipitation records from over 700 Chinese stations from1956 to 2005 are analyzed. The results show a significant shift from light to heavy precipitation over eastern China. An optimal fingerprinting analysis of simulations from 11 climate models driven by different combinations of historical anthropogenic (greenhouse gases, aerosols, land use, and ozone) and natural (volcanic and solar) forcings indicates that anthropogenic forcing on climate, including increases in greenhouse gases (GHGs), has had a detectable contribution to the observed shift toward heavy precipitation. Some evidence is found that anthropogenic aerosols (AAs) partially offset the effect of the GHG forcing, resulting in a weaker shift toward heavy precipitation in simulations that include the AA forcing than in simulations with only the GHG forcing. In addition to the thermodynamic mechanism, strengthened water vapor transport from the adjacent oceans and by midlatitude westerlies, resulting mainly from GHG-induced warming, also favors heavy precipitation over eastern China. Further GHG-induced warming is predicted to lead to an increasing shift toward heavy precipitation, leading to increased urban flooding and posing a significant challenge for mega-cities in China in the coming decades. Future reductions in AA emissions resulting from air pollution controls could exacerbate this tendency toward heavier precipitation.

This comprehensive book describes the powerful tools of mathematical statistics which find wide application in climatological research. Suitable for graduate courses on statistics for climatic, atmospheric and oceanic science, this book will also be valuable as a reference source for researchers in climatology, meteorology, atmospheric science, and oceanography.

This paper discusses the state of European research in historical climatology. This field of science and an overview of its development are described in detail. Special attention is given to the documentary evidence used for data sources, including its drawbacks and advantages. Further, methods and significant results of historical-climatological research, mainly achieved since 1990, are presented. The main focus concentrates on data, methods, definitions of the \"Medieval Warm Period\" and the \"Little Ice Age,\" synoptic interpretation of past climates, climatic anomalies and natural disasters, and the vulnerability of economies and societies to climate as well as images and social representations of past weather and climate. The potential of historical climatology for climate modelling research is discussed briefly. Research perspectives in historical climatology are formulated with reference to data, methods, interdisciplinarity and impacts. [PUBLICATION ABSTRACT]

Medicanes, strong mesoscale cyclones with tropical-like features, develop occasionally over the Mediterranean Sea. Due to the scarcity of observations over sea and the coarse resolution of the long-term reanalysis datasets, it is difficult to study systematically the multidecadal statistics of sub-synoptic medicanes. Our goal is to assess the long-term variability and trends of medicanes, obtaining a long-term climatology through dynamical downscaling of the NCEP/NCAR reanalysis data. In this paper, we examine the robustness of this method and investigate the value added for the study of medicanes. To do so, we performed several climate mode simulations with a high resolution regional atmospheric model (CCLM) for a number of test cases described in the literature. We find that the medicanes are formed in the simulations, with deeper pressures and stronger winds than in the driving global NCEP reanalysis. The tracks are adequately reproduced. We conclude that our methodology is suitable for constructing multi-decadal statistics and scenarios of current and possible future medicane activities.

This study explores the possibility of reconstructing the weather of Southeast Asia for the last decades using an atmospheric regional climate model, the Climate version of the Lokal-Modell (CLM). For this purpose global National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses data were dynamically downscaled to 50 km and in a double-nesting approach to 18-km grid distance. To prevent the regional model from deviating significantly from the reanalyses with respect to large-scale circulation and large-scale weather phenomena, a spectral nudging technique was used. The performance of this technique in dealing with Southeast Asian typhoons is now examined by considering an ensemble of one simulated typhoon case. This analysis is new insofar as it deals with simulations done in the climate mode (so that any skill of reproducing the typhoon is not related to details of initial conditions), is done in ensemble mode (the same development is described by several simulations), and is done with a spectral nudging constraint (so that the observed large-scale state is enforced in the model domain). This case indicates that tropical storms that are coarsely described by the reanalyses are correctly identified and tracked; considerably deeper core pressure and higher wind speeds are simulated compared to the driving reanalyses. When the regional atmospheric model is run without spectral nudging, significant intraensemble variability occurs; also additional, nonobserved typhoons form. Thus, the insufficiency of lateral boundary conditions alone for determining the details of the dynamic developments in the interior becomes very clear. The same lateral boundary conditions are consistent with different developments in the interior. Several sensitivity experiments were performed concerning varied grid distances, different initial starting dates of the simulations, and changed spectral nudging parameters.

Empirical reconstructions of the Northern Hemisphere (NH) temperature in the past millennium based on multiproxy records depict small-amplitude variations followed by a clear warming trend in the past two centuries. We use a coupled atmosphere-ocean model simulation of the past 1000 years as a surrogate climate to test the skill of these methods, particularly at multidecadal and centennial time scales. Idealized proxy records are represented by simulated grid-point temperature, degraded with statistical noise. The centennial variability of the NH temperature is underestimated by the regression-based methods applied here, suggesting that past variations may have been at least a factor of 2 larger than indicated by empirical reconstructions.

For ages, the topic of climate – in the sense of “usual weather” – has in the western tradition attracted attention as a possible explanatory factor for differences in societies and in human behavior. Climate, and its purported impact on society, is an integrated element in western thinking and perception. In this essay, the history of ideas about the climatic impact on humans and society and the emergence of the ideology of climatic determinism are sketched from the viewpoint of a natural scientist. This ideology favored the perception of westerners being superior to the people in the rest of the world, giving legitimacy to colonialism. In modern times, when natural sciences instituted self-critical processes (repeatability, falsification) and norms (such as the Mertonian norms named CUDOS), the traditional host for climate issues, namely, geography, lost its grip, and physics took over. This “scientification” of climate science led to a more systematic, critical and rigorous approach of building and testing hypotheses and concepts. This gain in methodical rigor, however, went along with the loss of understanding that climate is hardly a key explanatory factor for societal differences and developments. Consequently, large segments of the field tacitly and unknowingly began reviving the abandoned concept of climatic determinism. Climate science finds itself in a “post-normal” condition, which leads to a frequent dominance of political utility over methodical rigor.

When subjecting ocean models to atmospheric forcing, the models exhibits two types of variability—a response to the external forcing (hereafter referred to as signal) and inherently generated (internal, intrinsic, unprovoked, chaotic) variations (hereafter referred to as noise). Based on an ensemble of simulations with an identical atmospherically forced oceanic model that differ only in the initial conditions at different times, the signal-to-noise ratio of the atmospherically forced oceanic model is determined. In the large scales, the variability of the model output is mainly induced by the external forcing and the proportion of the internal variability is small, so the signal-to-noise ratio is large. For smaller scales, the influence of the external forcing weakens and the influence of the internal variability strengthens, so the signal-to-noise ratio becomes less and less. Thus, the external forcing is dominant for large scales, while most of the variability is internally generated for small scales.