Homogenization of a combined hourly air temperature dataset over Romania

Daily and sub‐daily homogenization of climate variables have been intensively investigated in the last decades, but to the best of our knowledge, this is the first study on homogenization of hourly temperature in Romania. This paper describes the creation of a homogenized hourly air temperature data set at a country scale by combining data from four independent meteorological networks. The air temperature measurements for the period 2009 and 2017 were obtained from the following networks: Romanian National Meteorological Administration (ANM), National Network for Monitoring Air Quality (RNMCA), Regional Basic Synoptic Network (RBSN), and Meteorological Terminal Aviation Routine Weather Report network (METAR). The climatological limits, persistence, temporal variation (step test), and spatial consistency were the quality control tests used to isolate the errors due to malfunctioning of the temperature sensors, data coding or transmission. The Climatol homogenization method was successfully applied for identifying and correcting any suspicious values. The missing data were filled by considering the similarities between each station and the reference series. Comparing the output with the original data, it is apparent that the removal of the break points, correction and homogenization resulted in a new data set with statistical properties very similar to the raw data, but more reliable for climate research due to the increased homogeneity. Eventually, the procedure can be implemented in operational use for collecting more data from other networks.This work was supported by a grant of Ministry of Research and Innovation, Romania, CNCS—UEFISCDI, project number PN‐III‐P1‐1.1‐PD‐2016‐1579, within PNCDI III

Joint examination of climate time series based on a statistical definition of multidimensional extreme

The joint examination of the climate time series may be efficient methodology for the characterization of extreme weather and climate events. In general, the main difficulties are connected with the different probability distribution of the variables and the handling of the stochastic connection between them. The first problem can be solved by the standardization procedures, i.e., to transform the variables into standard normal ones. For example, there are the Standardized Precipitation Index (SPI) series for the precipitation sums assuming gamma distribution, or the standardization of temperature series assuming normal distribution. In case of more variables, the problem of stochastic connection can be solved on the basis of the vector norm of the transformed variables defined by their covariance matrix. We will present the developed mathematical methodology and some examples for its meteorological applications

Konfliktuskezelési módok tükröződése a Közös Rorschach Vizsgálatban = Conflict handling as reflected by the Consensus Rorschach method

A kutatás keretében komplex tesztbattériát alkalmaztunk, amely a kommunikációs viselkedést személyiség- megküzdési, kötődési, valamint párkapcsolatműködési jegyekkel együttesen mérte. Vizsgálati mintánkba 300 sine morbo pár, valamint 70 munkacsoport került. A kommunikációs viselkedés szoros kapcsolatban állt a személyiségjegyekkel, ezt az összefüggést befolyásolta a kapcsolati elégedettség is. A párdinamikai viszonyokat meghatározta a két partner kötődése, mind tudatos, mind pedig tudattelőttes személyiségrétegek tekintetében. A párkapcsolati elégedettséget és a megküzdési képességet számottevően befolyásolták a spirituális orientáció hatásai. A munkahelyi kommunikációt szintén alakitotta a személyiség, ennél azonban lényegesebb hatással volt a munkahelyen betöltött szerep. Megkezdődött a Közös Rorschach Vizsgálat terápiás alkalmazása. | Complex test battery was administered to 300 couples, that included measures of interpersonal communication (Consensus Rorschach), measures of attachment, coping, as well as family functioning and family satisfaction. Communicative behavior was closely related to personality characteristics, however effects were moderated by family satisfaction. Couple dynamics were also influenced by attachment style, as if both partners were unsecurely attached, interpersonal communication was characterized by intense rivalry, hostility and tension. Relationship satisfaction and coping both were influenced by spiritual orientation, with most significant when both partners were strongly committed to spiritual practice. Interpersonal communication at work was influenced by personality and role requirements both, with emphasis on the latter. Consensus Rorschach has been applied with great efficancy as a diagnostic method in family therapy setting

Többdimenziós éghajlati idősorok extrémumainak vizsgálata

Az éghajlatváltozás tanulmányozásához elengedhetetlen a szélsőségek vizsgálata. A szélsőségek vizsgálata történhet egyrészt úgy, hogy az extrém éghajlati események idősorát vizsgáljuk, másrészt úgy, hogy az éghajlati idősorok extrémumait vizsgáljuk. Ez utóbbi esetben, ha egyetlen elemet vizsgálunk, a szélsőség az adott idősor maximuma vagy minimuma. Jelen tanulmányban az éghajlati idősorok szélsőértékeit határozzuk meg úgy, hogy több meteorológiai elemet együttesen vizsgálunk és így határozzuk meg az extrémumokat. Rögtön felmerül a kérdés, hogy többdimenziós idősornál van-e értelme szélsőértékről beszélni, és ha igen, milyen módon határozható meg. Ehhez kapcsolódóan bemutatjuk az ún. norma módszert, definiáljuk a vektorváltozó extrémumát, és példákon keresztül mutatjuk be a módszer alkalmazását csapadék- és hőmérséklet-idősorok együttes vizsgálatával. Tanulmányunkhoz a magyarországi napi átlaghőmérsékleti és csapadék idősorokat használtuk fel az 1901‒2019 időszakra. Az alábbiakban bemutatjuk az együttes vizsgálat során kapott legfontosabb eredményeket, és összevetjük az egydimenziós esetben kapott szélsőségekkel. Amennyiben ezzel a módszerrel visszakapjuk az eredeti egydimenziós idősorok szélsőségeit, úgy az éghajlat-változás vizsgálatához nem ad többletet a bemutatni kívánt módszer. Elöljáróban összegezhetjük, hogy elemzéseink azt jelzik, hogy vannak olyan évek, amelyek csak a csapadék vagy csak az átlaghőmérséklet szempontjából nem számítanak extrémnek, de együtt vizsgálva a két elemet mégis kimondhatjuk, hogy szélsőséges évek voltak. Ezek alapján tehát a többdimenziós éghajlati idősorok extrémumainak vizsgálata kiegészíti, és ezáltal hatékonyabbá teszi az éghajlatváltozás vizsgálatát ahhoz képest, mintha csak az egydimenziós idősorokat vizsgálnánk

Creation of a representative climatological database for Hungary from 1870 to 2020

Climate studies, particularly those that are related to climate change, require long, high-quality controlled data sets, which are representative both spatially and temporally. Changing the conditions of measurements, for example relocating the station, or changing the frequency and timing of measurements, or changing the instruments used can cause breaks in the time series. To avoid these problems, data errors and inhomogeneities are eliminated and the data gaps are filled by using the MASH (Multiple Analysis of Series for Homogenization, Szentimrey, 1999, 2008) homogenization procedure. The Hungarian meteorological observation network was upgraded significantly in the last decades. Homogenization of the data series raises the question of how to homogenize long and short data series together within the same process. It is possible to solve this with the MASH method due it has solid mathematical foundations, which make it suitable for such purposes. The solution includes the synchronization of the common parts’ inhomogeneities within three (or more) different MASH processing of the three (or more) datasets with different lengths depending on the time periods and elements. After the homogenization process, the station data series were interpolated to a 0.1 degree regular grid covering the whole area of Hungary. The MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey and Bihari, 2007) program system was used for this purpose. The MISH procedure was developed specifically for the interpolation of various meteorological elements. In the case of mean temperature, we also renewed the MISH modeling, as compared to previous years, the number of homogenized stations doubled due to the new work, so it was expedient to model the climate statistical parameters with this extended station system. Time series of daily mean temperature and precipitation sum for the period 1870–2020 for Hungary were used in this study. As a result, the longest ever homogenized, gridded daily data sets became available for Hungary. The method described here can also be applied to produce representative datasets for other meteorological elements

Uncertainty in gridded precipitation products: Influence of station density, interpolation method and grid resolution

This work analyses three uncertainty sources affecting the observation-basedgridded data sets: station density, interpolation methodology and spatial resolution.For this purpose, we consider precipitation in two countries, Poland and Spain,three resolutions (0.11, 0.22 and 0.44 ), three interpolation methods, both areal-and point-representative implementations, and three different densities of theunderlying station network (high/medium/low density). As a result, for each resolu-tion and interpolation approach, nine different grids have been obtained for eachcountry and inter-compared using a variance decomposition methodology.Results indicate larger differences among the data sets for Spain than for Poland,mainly due to the larger spatial variability and complex orography of the formerregion. The variance decomposition points out to station density as the most influ-ential factor, independent of the season, the areal- or point-representative imple-mentation and the country considered, and slightly increasing with the spatialresolution. In contrast, the decomposition is stable when extreme precipitation indi-ces are considered, in particular for the 50-year return value.Finally, the uncertainty due to station sub-sampling inside a particular grid boxdecreases with the number of stations used in the averaging/interpolation. In thecase of spatially homogeneous grid boxes, the interpolation approach obtains simi-lar results for all the parameters, excepting the wet day frequency, independently ofthe number of stations. When there is a more significant internal variability in thegrid box, the interpolation is more sensitive to the number of stations, pointing outto a minimum stations?density for the target resolution (six to seven stations).VALUE has been funded as EU COST Action ES1102. Participation of S.H. and J.M.G. was partially supported by theproject MULTI-SDM (CGL2015-66583-R, MINECO/FEDER). P.M.M.S. and R.M.C. wish to acknowledge the projects SOLAR (PTDC/GEOMET/7078/2014) and FCTUID/GEO/50019/ 2013 - Instituto Dom Luiz, both financedby the Fundação para a Ciência e Tecnologia. We acknowl-edge the E-OBS data set from the EU-FP6 project ENSEM-BLES (http://ensembles-eu.metoffice.com) and the dataproviders in the ECA&D project (http://www.ecad.eu)