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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]

(1) The main objectives of this study are the spatial and temporal analysis of annual 24-hour extreme precipitation amounts for different return periods, and (2) the interannual variability of the frequency of month-to-month maximum rainfall using harmonic analysis. Long time series data from 110 well-scattered rain gauges are analysed using extreme values theory and harmonic analysis techniques. The results indicate that the Jenkinson solution is more appropriate than the linear Gumbel solution for the extreme value law. The maximum expected values of 180–200 mm are observed along the southern coasts of the Greek peninsula and in the islands close to the Turkish coast, as well as in the north–west parts of the country. The harmonic analysis showed that the highest percentage of variance for rainfall extremes explained by the first harmonic (PVR(1)) appears over the southern and south-eastern parts of Greece in association with the greatest values of the amplitude of this harmonic, therefore explaining more than 90% of the variation of the frequency of maximum annual 24-hour rainfall amounts. In contrast, for regions north of 38° N and especially mountainous regions, more harmonics (3–5) are necessary to describe the parameter under investigation. [ABSTRACT FROM AUTHOR]

Precipitation division and climate shift in China were analysed using daily precipitation data from 486 stations for the period 1960–2000. A modified hierarchical clustering method was used to divide China into sub-regions that have a coherent annual cycle, interannual evolutions and long-term trends. A division with 20 grouping areas can well describe the anomalous regional features seasonally, and a division with 40 grouping areas can reach a relatively stable level, theoretically for the annual and summer precipitation in mainland China. Rapid changes or interdecadal transition points of the regional precipitation series are detected by a multiple timescale t-test method. For mean annual precipitation, the interdecadal shift from a low to a high level is found to occur around 1987 in the Xinjiang region and around 1983 in Northeast China. The transition points of increasing summer rainfall in the eastern Tibetan Plateau and the lower Yangtze River are centred closely about 1979. Changes in the double-decadal precipitation are also detected for the two periods of 1961–1980 and 1981–2000. An increasing trend in annual precipitation is mainly found in the lower Yangtze River valley, the Xinjiang region, and Northeast China. Decreasing annual precipitation is mainly situated from the middle Yangtze River to the Yellow River. In summer and winter, the spatial pattern of precipitation anomalies shows two pairs of contrasting shifts with negative departures in North China and southern coastal China, while positive departures are found in the middle and lower Yangtze River valley and Northeast China. This pattern of regional precipitation shift in China is associated with southerly monsoon flow in eastern China and westerly flow in northwestern China. [ABSTRACT FROM AUTHOR]