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The present paper uses characteristics of the marine interstitial ciliate community in the White Sea intertidal sandflat during the period of 1991-2011, in order to study its long-term dynamics, investigating in particular whether it exhibits scaling behaviour into its fluctuations, which is a characteristic feature of the climate system. To this aim, a recently proposed version of the detrended fluctuation analysis is herewith employed which has been successfully applied to a wide range of simulated and physiologic time series in recent years. In case that the fluctuations of the ciliate community present self-similarity processes, an ideal field test for the currently proposed biological models will be established, allowing to evaluate their reliability. Indeed, we show for the first time that different ciliate species exhibit long-range power-law persistent correlations. This means that ciliate fluctuations in different intervals are positively correlated, obeying a power-law behaviour. Although the origin of power-law temporal evolution of ciliates should be further investigated, this finding is probably associated with the self-organized criticality of ciliates. It should be noted that the long-range correlations obtained do not imply the presence of specific cycles but rather the existence of dynamic links between long-term and short-term temporal evolution. The scaling behaviour found in marine interstitial ciliate community should be taken into account in the investigation of their response to the present or future climate change. [ABSTRACT FROM AUTHOR]

Meteorological and oceanographic data from ships of opportunity are the largest contributor to the world’s ocean surface database and thus are extensively used to estimate the change in climatic properties over the world’s oceans during the previous 150 years. The importance of these data for climate change studies underscores the need to fully understand the error associated with averages of these data. The sampling error problem is especially acute for ship data due to the fact that ships are moving platforms and, thus, report observations from constantly varying locations with time. This paper develops a theoretical framework for assessing the averaged sampling error associated with monthly, 1°×1° latitude-longitude box averaged ship data. It should be noted that the time-space distribution of ships within the averaging domain strongly affects the sampling error. This is shown in our derivation. The framework developed here can be used to improve upon existing methods for estimating the sampling error associated with three-dimensional box averages of meteorological and oceanographic data obtained from ship records. The framework is complimentary to existing methods of assessing biases and random error due to instrumentation, recording, etc. It is demonstrated mathematically that the uncertainty due to incomplete sampling is primarily a trade off between of the number of observations and their relative locations within the box as well as the inherent time-space correlation structure of the variable of interest. This work differs from other studies in that the three-dimensional interdependence of data is taken into account in deriving an expression for the sampling error. [ABSTRACT FROM AUTHOR]

Significant changes in the climatic system have been observed, which may be attributed to human-enhanced greenhouse effect. Even stronger changes are projected for the future, impacting in an increasing way on human activity sectors. The present contribution, prepared in the framework of the MICE (Modelling the Impact of Climate Extremes) Project of the European Union, reviews how climate change may impact on winter tourism in the Alpine region, intense precipitation and flood potential in central Europe, forest damage in Scandinavia and beach holidays in the Mediterranean coast. Impacts are likely to be serious and largely adverse. Due to a lack of adequate information and lack of broadly accepted and reliable mathematical models describing the impact of changes in climate extremes on these activity sectors, it has been found useful to use expert judgement based impact assessment. Accordingly, regional mini-workshops were organized serving as platforms for communication between scientists and stakeholders, vehicles for dissemination of the state-of-the-art of the scientific understanding and for learning stakeholders’ view on extreme events, their impacts and the preparedness system. Stakeholders had the opportunity to react to the scientific results and to reflect on their perception of the likely impacts of projected changes in extremes on relevant activity sectors and the potential to adapt and avert adverse consequences. The results reported in this paper present the stakeholders’ suggestions for essential information on different extreme event impacts and their needs from science. [ABSTRACT FROM AUTHOR]