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The North Atlantic Oscillation (NAO) is a large-scale climate teleconnection that coincides with worldwide changes in weather. Its impacts have been documented at large scales, particularly in Europe, but not as much at regional scales. Furthermore, despite documented impacts on ecological dynamics in Europe, the NAO’s influence on North American biota has been somewhat overlooked. This paper examines long-term temperature and precipitation trends in the southern Appalachian Mountain region—a region well known for its biotic diversity, particularly in salamander species—and examines the connections between these trends and NAO cycles. To connect the NAO phase shifts with southern Appalachian ecology, trends in stream salamander abundance are also examined as a function of the NAO index. The results reported here indicate no substantial long-term warming or precipitation trends in the southern Appalachians and suggest a strong relationship between cool season (November–April) temperature and precipitation and the NAO. More importantly, trends in stream salamander abundance are best explained by variation in the NAO as salamanders are most plentiful during the warmer, wetter phases. [ABSTRACT FROM AUTHOR]

The idea of using large-scale information to predict local climate variability is widely exploited in climate change impact studies as an alternative to computationally expensive high-resolution models. This approach implies the hypothesis that the statistical relationship between large-scale climate states and local variables defined for the present-day climate remains valid in the altered climate. In this paper, the concept of weather regimes is used to deduce a relationship between large-scale circulation and European winter temperature. The change in temperature with increased greenhouse gases is, however, not homogeneous among the individual regimes. As a result, the impact of the weather regimes on local temperature changes varies in the future, limiting its usefulness for refining temperature changes to the small scale. [ABSTRACT FROM AUTHOR]

This paper analyzes the changes in the precipitation climatologies of Europe for the periods 1960–90 and 2070–2100 using a heterogeneous set of regional climate models (RCMs). The authors used the Climatic Research Unit (CRU) database to define a precipitation climatology for current climate conditions (1960–90), then compare the estimates with the RCMs’ simulations for the same period using spectral analysis. After the authors evaluated the performance of the models compared with validation data for current climate, they calculated the future climate spectra (2070–2100). Changes in the future climate have been evaluated in terms of differences in the phase and amplitude of the annual cycle with respect to present conditions. The results show that models provide consistent results and that under the A2 scenario (increased greenhouse gases conditions) precipitation climatologies in Europe are expected to suffer noticeable changes, the most important being a strengthening of the annual cycle in most of the Atlantic coastal areas of the continent. While total amounts of rainfall might undergo little change, the consequences of changes in the seasonal distribution of precipitation will strongly affect both ecosystems and human activities. Differences were also found in the probability distribution function (pdf) of precipitation, indicating an overall increase in the frequency of precipitation-related hazards in Europe. [ABSTRACT FROM AUTHOR]

Three algorithm intercomparison experiments have recently been conducted as part of the Global Precipitation Climatology Project with the goal of (a) assessing the skill of current satellite rainfall algorithms, (b) understanding the differences between them, and (c) moving toward improved algorithms. The results of these experiments are summarized and intercompared in this paper. It was found that the skill of satellite rainfall algorithms depends on the regime being analyzed, with algorithms producing very good results in the tropical western Pacific and over Japan and its surrounding waters during summer, but relatively poor rainfall estimates over western Europe during late winter. Monthly rainfall was estimated most accurately by algorithms using geostationary infrared data, but algorithms using polar data [Advanced Very High Resolution Radiometer and Special Sensor Microwave/Imager (SSM/I)] were also able to produce good monthly rainfall estimates when data from two satellites were available. In most eases, SSM/I algorithms showed significantly greater skill than IR-based algorithms in estimating instantaneous rain rates. [ABSTRACT FROM AUTHOR]