@misc{MTMT:34532361,
	title = {Rövid idejű, intenzív csapadékok vizsgálata mérnöki feladatok kiszolgálásához.},
	url = {https://m2.mtmt.hu/api/publication/34532361},
	author = {Lakatos, Mónika and Kovácsné Izsák, Beatrix Cecília and Bokros, K. and Szentes, Olivér},
	unique-id = {34532361},
	year = {2023},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@misc{MTMT:34532323,
	title = {Reprezentatív meteorológiai adatok biztosítása a múlt és a jelen éghajlatának megismerésére.},
	url = {https://m2.mtmt.hu/api/publication/34532323},
	author = {Kovácsné Izsák, Beatrix Cecília and Szentes, Olivér and Konkolyné Bihari, Zita and Bokros, K. and Hercsényi, L. and Lakatos, Mónika and Tótiván, B.},
	unique-id = {34532323},
	year = {2023},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@CONFERENCE{MTMT:34506169,
	title = {Interpolating intraday precipitation data with radar background information},
	url = {https://m2.mtmt.hu/api/publication/34506169},
	author = {Kovácsné Izsák, Beatrix Cecília and Kinga, Bokros and Konkolyné Bihari, Zita},
	booktitle = {EMS Annual Meeting Abstracts},
	unique-id = {34506169},
	abstract = {It is a common phenomenon that a small but significant precipitation cell or supercell passes between two measuring stations, resulting in an inadequate record of the daily precipitation amounts of up to 100 mm falling on a small area between the measurements and observations. This renders the interpolation from measurements alone insufficient to provide a complete depiction of the actual weather conditions. Therefore, to reduce the deviations from the actual weather situation, supplementary background information, for instance satellite data series, forecast information or radar measurements is used. In many cases, heavy thunderstorms with high rainfall can cause flash floods, which have a number of known negative effects in both social and agricultural areas. To achieve more accurate interpolation, it is therefore essential to use radar background information, as it yields significant social and agricultural benefits and can even be used for hazard warning. As the annual, seasonal and daily precipitation sum data series are interpolated using the MISH software at the OMSZ (Hungarian Meteorological Service) Unit of Climatology, the 10-minute, hourly, etc. precipitation sums are also interpolated using the MISH system. MISH software incorporates background information automatically and produce verification statistics. In our presentation, we will not only illustrate the theoretical and practical application of the MISH software, but also provide an overview of these statistics. The data series were interpolated by MISH for the whole area of Hungary, with and without radar background information, and statistical methods were used to illustrate the extent to which the interpolation was improved by the radar product used as background, and the strong relationship between interpolation with and without background information.},
	year = {2023},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:34238551,
	title = {Revisiting HISTALP precipitation dataset},
	url = {https://m2.mtmt.hu/api/publication/34238551},
	author = {Chimani, Barbara and Bochníček, Oliver and Brunetti, Michele and Ganekind, Manfred and Holec, Juraj and Kovácsné Izsák, Beatrix Cecília and Lakatos, Mónika and Tadić, Melita Perčec and Manara, Veronica and Maugeri, Maurizio and Šťastný, Pavel and Szentes, Olivér and Zardi, Dino},
	doi = {10.1002/joc.8270},
	journal-iso = {INT J CLIMATOL},
	journal = {INTERNATIONAL JOURNAL OF CLIMATOLOGY},
	volume = {2024/1},
	unique-id = {34238551},
	issn = {0899-8418},
	abstract = {The article presents a recent update of a comprehensive dataset of long‐term series of precipitation data from instrumental observations in the Greater Alpine Region (GAR), that is, the region of Europe including the Alpine mountain range and their nearer surroundings (4°–19° E in longitude and 43°–49° N in latitude). A comparison to different national homogenized datasets is also presented. Results show that in the national homogenized datasets more breaks have been detected due to higher station density. They also demonstrate the necessity of constant exchange with data providers. The resulting trends in all datasets are mainly weak and only a minority of them is statistically significant. In most cases the similarity of statistical index numbers are promising, with, for example, small RMSE between the presented new HISTALP homogenization and the time series of the national homogenized datasets. Nevertheless, for some stations higher differences occur and break signals are not what would be expected due to possible causes in the station history. The differences between the national and the HISTALP new homogenization—due to, for example, different methods used, different points in time when the homogenization took place, different options of data handling (combination of station data, gap filling routines, …) and different reference stations—illustrate the inherent uncertainty unavoidably associated to homogenization and point out the need of careful communication and use of the data. On the other hand, the results highlight the advantage of consistently homogenized datasets, versus the risks associated with mixing results from different homogenizations.},
	year = {2023},
	eissn = {1097-0088},
	pages = {Int J Climatol.2023;1–31.},
	orcid-numbers = {Chimani, Barbara/0000-0003-0298-4181; Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:34087290,
	title = {Homogenization and interpolation of relative humidity hourly values with MASH and MISH software},
	url = {https://m2.mtmt.hu/api/publication/34087290},
	author = {Kovácsné Izsák, Beatrix Cecília},
	doi = {10.1002/joc.8205},
	journal-iso = {INT J CLIMATOL},
	journal = {INTERNATIONAL JOURNAL OF CLIMATOLOGY},
	volume = {43},
	unique-id = {34087290},
	issn = {0899-8418},
	abstract = {To understand and study the climate, there is a need to create high‐quality climatological databases. At the Climate Department of the OMSZ (Hungarian Meteorological Service), we use MASH (Multiple Analysis of Series of Homogenization) and MISH (Meteorological Interpolation based on Surface Homogenized Data Basis) software to produce a spatially and temporally representative database. However, these systems were developed for daily and monthly data series, so some improvements were required when applying them to hourly relative humidity data. The problem relates to the issue of the daily cycle. The aim of this article is to show how the data set of hourly values of the relative humidity measurements was prepared. To construct the grid point database, a homogenized data set of 41 stations for the period 1961–2020 was used; this was then interpolated into to a regular grid with a resolution of 0.1°. At the end of the study, the hourly and daily data gridded series are compared.},
	year = {2023},
	eissn = {1097-0088},
	pages = {6285-6299},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@CONFERENCE{MTMT:33263522,
	title = {Homogenisation of relative humidity data series},
	url = {https://m2.mtmt.hu/api/publication/33263522},
	author = {Kovácsné Izsák, Beatrix Cecília and Szentes, Olivér and Lakatos, Mónika},
	booktitle = {EMS Annual Meeting Abstracts},
	unique-id = {33263522},
	year = {2022},
	pages = {Vol. 19, EMS2022-463, 2022},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@CONFERENCE{MTMT:33263497,
	title = {Modelling climate statistical parameters by MISH interpolation procedure},
	url = {https://m2.mtmt.hu/api/publication/33263497},
	author = {Kovácsné Izsák, Beatrix Cecília and Szentes, Olivér and Konkolyné Bihari, Zita},
	booktitle = {EMS Annual Meeting Abstracts},
	unique-id = {33263497},
	year = {2022},
	pages = {Vol. 19, EMS2022-422, 2022},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:33254113,
	title = {Extreme Months: Multidimensional Studies in the Carpathian Basin},
	url = {https://m2.mtmt.hu/api/publication/33254113},
	author = {Kovácsné Izsák, Beatrix Cecília and Szentimrey, Tamás and Lakatos, Mónika and Pongrácz, Rita},
	doi = {10.3390/atmos13111908},
	journal-iso = {ATMOSPHERE-BASEL},
	journal = {ATMOSPHERE},
	volume = {13},
	unique-id = {33254113},
	abstract = {In addition to the one-dimensional mathematical statistical methods used to study the climate and its possible variations, the study of several elements together is also worthwhile. Here, a combined analysis of precipitation and temperature time series was performed using the norm method based on the probability distribution of the elements. This means, schematically speaking, that each component was transformed into a standard normal distribution so that no element was dominant. The transformed components were sorted into a vector, the inverse of the correlation matrix was determined and the resulting norm was calculated. Where this norm was at the maximum, the extreme vector, in this case the extreme month, was found. In this paper, we presented the results obtained from a joint analysis of the monthly precipitation and temperature time series for the whole territory of Hungary over the period 1871–2020. To do this, multidimensional statistical tests that allowed the detection of climate change were defined. In the present analysis, we restricted ourselves to two-dimensional analyses. The results showed that none of the tests could detect two-dimensional climate change on a spatial average for the months of January, April, July and December, while all the statistical tests used indicated a clear change in the months of March and August. As for the other months, one or two, but not necessarily all tests, showed climate change in two dimensions.},
	year = {2022},
	eissn = {2073-4433},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389; Pongrácz, Rita/0000-0001-7591-7989}
}

@article{MTMT:33205211,
	title = {Trendvizsgálat: óraértékek hazai hőmérsékleti trendje},
	url = {https://m2.mtmt.hu/api/publication/33205211},
	author = {Barna, Zsófia and Kovácsné Izsák, Beatrix Cecília and Pieczka, Ildikó},
	doi = {10.56474/legkor.2022.3.1},
	journal-iso = {LÉGKÖR},
	journal = {LÉGKÖR: AZ ORSZÁGOS METEOROLÓGIAI INTÉZET SZAKMAI TÁJÉKOZTATÓJA},
	volume = {67},
	unique-id = {33205211},
	issn = {0133-3666},
	abstract = {Az éghajlat vizsgálatának jelentős szerepe van meteorológiai kutatásainkban. Ennek kapcsán cikkünkben a napi középhőmérséklet adatsorok, illetve a rendelkezésünkre álló óraértékek (0 UTC, 6 UTC, 12 UTC, 18 UTC) trendvizsgálatát mutatjuk be éves valamint évszakos szinten. Eredményeink szerint a legmagasabb trendértékek a 12 órás adatbázishoz kapcsolhatók. Ennek területi eloszlásához a 18 órás hasonlít leginkább, főként nyáron és ősszel. A legalacsonyabb értékeket pedig a 0 órás esetben kaptuk.},
	year = {2022},
	pages = {122-129},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389; Pieczka, Ildikó/0000-0001-5657-9494}
}

@article{MTMT:32922814,
	title = {Joint examination of climate time series based on a statistical definition of multidimensional extreme},
	url = {https://m2.mtmt.hu/api/publication/32922814},
	author = {Szentimrey, Tamás and Kovácsné Izsák, Beatrix Cecília},
	doi = {10.28974/idojaras.2022.2.1},
	journal-iso = {IDŐJÁRÁS},
	journal = {IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE},
	volume = {126},
	unique-id = {32922814},
	issn = {0324-6329},
	year = {2022},
	eissn = {0324-6329},
	pages = {159-184},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}