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As part of the COST Action HOME a dataset has been generated that will serve as a benchmark for homogenisation algorithms. Members of the Action and third parties have been invited and are still welcome to homogenise this dataset. The results of this exercise was analysed to obtain recommendations for a standard homogenisation procedure and are described in Venema et al. (Climate of the Past, 2012). Chapter two discusses the generation of this benchmark dataset, the climate variables considered, which types of data are in the benchmark dataset, how they have been produced, the ways to introduce artificial inhomogeneities, and the additional specifications such as length, missing data and trends. This chapter is an updated version of a report (Venema et al., 2009), which was available to the participants. A draft for the properties of the benchmark was developed at a Working Group meeting and was approved by the Management Committee of the Cost Action. The homogenized data that was returned by the participant is described in Chapter 3. In total 25 contributions have been returned before the deadline at which the truth was revealed. Multiple late contributions, submitted after the deadline, are also described. The descriptions of the contributions were written by the respective participants.

Calculating climatological normals is one of the most important tasks for national meteorological services. Since estimating statistical characteristics of climate variable from incomplete and nonhomogenous data can result in biased and altered estimation, it is necessary to fill in the gaps and test series for homogeneity. Various methods and techniques can be used when dealing with a problem of inhomogeneity and one of such tools is R package Climatol. In this work monthly temperature data from 38 meteorological stations in Croatia from period 1981-2010 are used. Stations are divided into three main climatic regions and homogenization process is performed for each one separately. Obtained breaks where then compared to the ones derived using ACMANT software for homogenization. Changes in statistical characteristics of temperature field such as mean temperature and decadal trend are observed at annual and seasonal scale. Significance of change in mean is tested using Student’s t- test, while for significance in trend Mann- Kendall’s test is used.

Calculating climatological normals is one of the most important tasks for national meteorological services. Due to requirements regarding homogeneity and completeness of data record, “data cleaning” is necessary since missing or inhomogeneous data can significantly alter the estimated statistical properties of the whole series. Lately, various techniques and methods are used for dealing with problem of inhomogeneity. One of such tools for homogenization and interpolation is package Climatol developed in the framework of the R (r-project.org). Data used in this study are mean monthly temperature data series from 38 meteorological stations in Croatia divided into three different climate regions (continental, mountain and coastal). Missing data problem can be diminished or overcome if they are replaced with some statistically justified estimates. Therefore, gaps were filled here by random selection from corresponding distribution determined from observed data records so multiannual average remains the same. Later, Climatol was applied to the original data and new homogenized dataset is obtained. In order to validate selected method, obtained break-points are compared to the ones determined using ACMANT software. Homogenization process using Climatol results in increase in correlation coefficient amongst stations in certain region and decrease in its variability, i.e. smoothness of the regions is increased. Also, principal component analysis gave increase in fraction of variance explained by first component for every region and all area. Finally, changes in statistical char- acteristics of temperature field, such as annual and seasonal mean and decadal trend, are determined. Significance of change in mean is tested using Student’s test, while for trend Mann-Kendall’s test is used. Significant changes in mean are observed only at one station, while trend analysis showed to be more sensitive to inhomogeneities. Not only change in trend rate has occurred but also few stations experienced change in trend significance at annual and seasonal scale.

Various types of studies require a sufficiently long series of data processed identically over the entire area. For climate analysis, it is necessary that analysed time series are homogeneous, which means that their variations are caused only by variations in weather and climate. Unfortunately, most of the climatological series are inhomogeneous and contain outliers that may significantly affect the analysis results. The 137 stations with precipitation measurement belonging to the meteorological station network governed by the Meteorological and Hydrological Service of Croatia were selected for the present analysis. Most of the data series cover a period from the late 1940s or early 1950s through the year 2010. For quality control and homogenization, an approach based on the software ProClimDB/Anclim was applied. In this study, we describe the results from the quality control and homogenization process for monthly precipitation sums as well as the spatial relationship of precipitation in the Croatian region. The precipitation network in Croatia is fairly homogeneous as only 23% of the 137 analysed stations are found to be inhomogeneous.

The “Little meteorologist” workshop has been taking place at the Science Festival in Zagreb since 2007 where the audience includes the general public. Since 2009 the project has been introduced as an extracurricular school activity in some primary schools where the main audience is children and teachers. Instruction sheets for several experiments were prepared for the workshop which formed the basis of the booklet. The booklet is intended to be an interesting and entertaining introduction to some basic meteorological terms and phenomena for pupils. Children can use this booklet independently in their free time but at the same time it can be a valuable source of ideas for teachers who want to enrich their teaching with some practical contents. Publication of the booklet is planned for the spring 2011. Here, the methods used in the workshop as well as the evaluation results of the workshops that were held in schools will be shown. Furthermore, the content of the booklet will be presented.

Precipitation is important for vegetation, wildlife, and people, as it replenishes the ground and surface water. Accordingly, precipitation chemistry is an important environmental issue due to many concerns, such as acid deposition, eutrophication, ecosystem health, biogeochemical cycling, and global climate change. Analyses of raw precipitation data series could lead to false conclusions. To exclude influence of e.g. meteorological sight relocations, changes in environment or changes of instruments on analyses results the data series should be homogenised. Here, two data sets of the annual volume-weighted concentrations of the major ions in precipitation are compared. First data set is calculated from raw precipitation data and the second one from homogenised data. Furthermore, the comparison of trends for these two data sets will be presented.

Little meteorological workshop (LMW) is a project the main goal of which is promotion and popularization of meteorology in Croatia. The project has been taking place at the Science Festival in Zagreb since 2007 where the audience includes the general public. Since 2009 the project has been introduced as an extracurricular school activity in some primary schools where the main audience are children and teachers. Here, the methods used in the LMWs will be presented. Furthermore, the evaluation results of the LMWs that were held in schools will be shown.

This paper outlines the first meteorological measurements taken from a snow pit in the Gorski kotar region, which is located in the mountainous western part of Croatia. The aim of the research was to determine the main meteorological characteristics of the location in the summer and in the winter period. Temperature and relative humidity were measured inside and in the vicinity of the snow pit. The samples from different depths of snow accumulated at the bottom of the pit as well as the samples of snow in vicinity of the pit were collected for chemical analysis. Changes in temperature and relative humidity in the vicinity of the snow pit showed typical seasonal variations. The values inside the pit during the summer period were constant. During the winter period, it was noticed that the values inside the pit followed the changes of the values in the vicinity of the pit. The pH measurements of the snow samples showed no indication of an increased acidity of snowmelt at the monitoring location. Further research in some other snow pits should be conducted in order to test the general relevance of the obtained results.

This paper outlines the first meteorological measurements taken from a snow pit in the Gorski kotar region, which is located in the mountainous western part of Croatia. The aim of the research was to determine the main meteorological characteristics of the location. The research rested on the assumption that meteorological conditions in snow pits could be indicators of regional climate change. Temperature and relative humidity were measured inside and in the vicinity of the snow pit. Two samples from different depths of snow accumulated at the bottom of the pit were collected for analysis. Changes in temperature and relative humidity in the vicinity of the snow pit showed typical seasonal variations. The values inside the pit were constant. The pH measurements of the snow samples showed no indication of an increased acidity of snowmelt at the monitoring location. Further research in some other snow pits should be conducted in order to test the general relevance of the obtained results.

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Instrumental meteorological measurements from periods prior to the start of national weather services are designated “early instrumental data.” They have played an important role in climate research as they allow daily to decadal variability and changes of temperature, pressure, and precipitation, including extremes, to be addressed. Early instrumental data can also help place twenty-first century climatic changes into a historical context such as defining preindustrial climate and its variability. Until recently, the focus was on long, high-quality series, while the large number of shorter series (which together also cover long periods) received little to no attention. The shift in climate and climate impact research from mean climate characteristics toward weather variability and extremes, as well as the success of historical reanalyses that make use of short series, generates a need for locating and exploring further early instrumental measurements. However, information on early instrumental series has never been electronically compiled on a global scale. Here we attempt a worldwide compilation of metadata on early instrumental meteorological records prior to 1850 (1890 for Africa and the Arctic). Our global inventory comprises information on several thousand records, about half of which have not yet been digitized (not even as monthly means), and only approximately 20% of which have made it to global repositories. The inventory will help to prioritize data rescue efforts and can be used to analyze the potential feasibility of historical weather data products. The inventory will be maintained as a living document and is a first, critical, step toward the systematic rescue and reevaluation of these highly valuable early records. Additions to the inventory are welcome.