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With high temporal resolution and accurate age control, tree-ring width is a good proxy for recording past climate variations from interannual to centennial time scales. The complex network method, widely used in analyses of modern meteorological observations, is an effective method to demonstrate synchronizations within climate events, thus revealing potential climate teleconnections. In this study, we tested to use the complex network in analyzing extremes recorded in time serials of tree-ring width in East Asia during the past 600 years. Our study indicates that this method is a valuable approach to reveal synchronizations in climate-sensitive tree-ring width records, though the ability of this method is dependent on the quality of the tree-ring data. Furthermore, our study shows stronger synchronizations in extremes of tree-ring width records during the CE 1850–1950 period in the Modern Warm Period than the CE 1450–1650 period in the Little Ice Age. A remarkable shift in synchronization types within the south part and the inland East Asia sites appears during the year CE 1850–1950. These changes in synchronizations suggest potential reorganizations in climate teleconnections, which is worthy being addressed in further studies with detrending and statistical significance testing methods involved.

Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.

The present paper examines variability of characteristics of snow cover (snow cover depth, number of days with snow cover and dates of beginning and end of snow cover) in Poland. The study makes use of a set of 43 long time series of observation records from the stations in Poland, from 1952 to 2013. To describe temporal changes in snow cover characteristics, the intervals of 1952–1990 and of 1991–2013 are compared and trends in analysed data are sought (e.g., using the Mann–Kendall test). Observed behaviour of time series of snow-related variables is complex and not easy to interpret, for instance because of the location of the research area in the zone of transitional moderate climate, where strong variability of climate events is one of the main attributes. A statistical link between the North Atlantic Oscillation (NAO) index and the snow cover depth, as well as the number of snow cover days is found.

To evaluate the climate events of the Eocene, a section of the Khangiran Formation, dated Early–Middle Eocene based on Planktonic foraminifera (P6-P11 zones) was selected in the Kopeh-Dagh Basin of Northeastern Iran and sampled systematically for palynological studies. Statistical notions such as Detrended Correspondence Analyses and Canonical Correspondence Analyses were practiced on the data gathered. Results were plotted and drawn as statistical diagrams for abundance of climate proxy genera and environmental parameters. These suggests a shift from a warm, high-nutrient, low-oxygen environment of inner neritic setting to a relatively colder, less nutrient and high-oxygen outer neritic environment from the Early to the Middle Eocene.

Targeted observation is an observation strategy by which the concerned phenomenon is observed. In geoscience, targeted observation is mainly related to the forecasts of weather events or predictions of climate events. This paper will first review the history of targeted observation, and then introduce the main methods used in targeted observation. The discussion on the theoretical basis of targeted observation includes its advantages and limitations. After presenting the current situation of domestic and international targeted observations in atmospheric and oceanic sciences, the methods used for targeted observation, and their effect evaluation and testing are mainly discussed here. Finally, the author presents his suggestion about the prospect of further development in the field, and how to extend the method of targeted observation to deal with numerical model errors.

This paper examines traditional ecological knowledge of weather and climate in Samoa, a Polynesian community in the South Pacific. The research found Samoans have their own unique seasonal calendar. The Samoan seasonal calendar is predominantly based on the observations of local environmental changes, which are in turn influenced by weather and climate. Monitoring changes in plants and animal behaviour, for example, are key indicators used by the Samoans to forecast changes in weather and climate. In addition, their communal and family social activities like hunting, fishing and feasting are driven by the seasonal calendar. The Samoans knowledge of cloud formation, conditions conducive to the formation and onset of severe weather systems and seasonal changes in climate, helped them anticipate, plan and adapt to extreme weather and climate events. The ability and knowledge of the Samoans to forecast the onset of extreme weather and climate events, relying predominantly on local environmental changes are vital tools that should be incorporated in the formulation of human induced climate change adaptation strategies.

There is general agreement that changes in the frequency or intensity of extreme weather and climate events are likely to have profound impacts on society and the environment (Karl et al., 1997). A Workshop on Indices and Indicators for Climate Extremes was held in Asheville, North Carolina, 3–6 June 1997, to encourage the development of data sets, and analysis techniques, to determine whether such extreme events are becoming more extreme or variable. Over 100 participants, from 23 countries, including representatives from 15 insurance and re-insurance countries (which have a clear interest in extreme weather and climate), examined the following questions: What needs to be done to improve data sets and analyses for extreme weather monitoring? Can we establish priorities for specific data set development and improvement? Can we establish indices and indicators of extreme weather and climate? What are the impediments to improving the monitoring of climate extremes?

The detailed14c dating, palynological, carbon isotope and magnetic susceptibility analyses of a paleo-swamp record obtained near Beijing show that the succession of climate events in Beljing area is broadly consistent with the climatic behavior in the North Atlantic region during the period from 13 000 to 10 000 a B. P., but with evident local characteristics. A relatively warm and wet episode (11 400-10 950 a B.P.) was intercalated between two dry-cold episodes (11 600-11 400 and 10 950-10 450 a B. P.).