Abstract. Probability distributions of multivariate random variables are generally more complex compared to their univariate counterparts which is due to a possible nonlinear dependence between the random variables. One approach to this problem is the use of copulas, which have become popular over recent years, especially in fields like econometrics, finance, risk management, or insurance. Since this newly emerging field includes various practices, a controversial discussion, and vast field of literature, it is difficult to get an overview. The aim of this paper is therefore to provide an brief overview of copulas for application in meteorology and climate research. We examine the advantages and disadvantages compared to alternative approaches like e.g. mixture models, summarize the current problem of goodness-of-fit (GOF) tests for copulas, and discuss the connection with multivariate extremes. An application to station data shows the simplicity and the capabilities as well as the limitations of this approach. Observations of daily precipitation and temperature are fitted to a bivariate model and demonstrate, that copulas are valuable complement to the commonly used methods.

Lakes Holzmaar and Meerfelder Maar are located in the Westeifel Volcanic Field less than 10 km apart. Both maar lakes are well known for their annually laminated (varved) sediments covering the past 15 000 years. Here, we focus on reconstructing the history of Holocene vegetation, human impact and climate using high‐resolution pollen data. Detailed correlation between the two records using palynologically defined tie‐points provides for the first time a test of the precision of the individual varve chronologies. The high‐resolution pollen records of both Holzmaar and Meerfelder Maar show continuous natural successions of vegetation during the early and mid‐Holocene controlled by the development of soil, climate, immigration and competitive expansion of thermophilous tree species. From 6500 varve yr BP onwards, human impact became an increasingly more important factor. Given the high chronological precision of both records, regional similarities, but also local differences of anthropogenically influenced vegetation changes, can be recognized. The reconstructed July temperature between 8500 and 5000 varve yr BP is around 1 °C higher than today, most likely in response to higher summer insolation related to orbital forcing. High variability of reconstructed July and January temperatures as well as annual precipitation around 5000 varve yr BP is a prominent climatic signal. This is consistent with other records in several areas of Europe which also identify this period as climatically highly variable.

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