@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:34002421,
	title = {Analysis of the correlation between the incidence of food-borne diseases and climate change in Hungary},
	url = {https://m2.mtmt.hu/api/publication/34002421},
	author = {Jakuschné Kocsis, Tímea and Magyar-Horváth, Kinga and Konkolyné Bihari, Zita and Kovácsné Székely, Ilona},
	doi = {10.28974/idojaras.2023.2.4},
	journal-iso = {IDŐJÁRÁS},
	journal = {IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE},
	volume = {127},
	unique-id = {34002421},
	issn = {0324-6329},
	abstract = {It is increasingly accepted globally, that many food-borne diseases are associated with climate change. The goal of the present research is to investigate whether changes in the annual number of the registered food-borne diseases in Hungary can be correlated to any climate parameter, as it is reasonable to suppose that it can be linked to climate change. Ten climate parameters and indices were examined as potential influencing factors. A multiple linear regression model was employed, using the backward elimination method to find the climate factors that have a significant effect on the annual number of food-borne diseases. It was found that the annual mean temperature was the only significant predictor of the annual number of registered food-borne diseases, and that 22.0% of the total variance in the annual number of food-borne diseases can be explained by the annual mean temperature. It should be noted that this relationship is negative, given that they are derived from time series with opposite trends. This phenomenon may be explained by the process of evolution and adaptation of the infecting fauna.},
	year = {2023},
	eissn = {0324-6329},
	pages = {217-231},
	orcid-numbers = {Jakuschné Kocsis, Tímea/0000-0003-3430-5569}
}

@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}
}

@misc{MTMT:32758501,
	title = {MEGFIGYELT ÉGHAJLATI VÁLTOZÁSOK MAGYARORSZÁGON},
	url = {https://m2.mtmt.hu/api/publication/32758501},
	author = {Lakatos, Mónika and Konkolyné Bihari, Zita and Kovácsné Izsák, Beatrix Cecília and Marton, Annamária and Szentes, Olivér},
	unique-id = {32758501},
	year = {2021},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:32744041,
	title = {MEGFIGYELT ÉGHAJLATI VÁLTOZÁSOK MAGYARORSZÁGON},
	url = {https://m2.mtmt.hu/api/publication/32744041},
	author = {Lakatos, Mónika and Konkolyné Bihari, Zita and Kovácsné Izsák, Beatrix Cecília and Marton, Annamária and Szentes, Olivér},
	journal-iso = {LÉGKÖR},
	journal = {LÉGKÖR: AZ ORSZÁGOS METEOROLÓGIAI INTÉZET SZAKMAI TÁJÉKOZTATÓJA},
	volume = {66},
	unique-id = {32744041},
	issn = {0133-3666},
	year = {2021},
	pages = {5-11},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:32744032,
	title = {ÉGHAJLATVÁLTOZÁS: HOMOGENIZÁLT VAGY NYERS ADATSOROKAT VIZSGÁLJAK?},
	url = {https://m2.mtmt.hu/api/publication/32744032},
	author = {Kovácsné Izsák, Beatrix Cecília and Konkolyné Bihari, Zita and Szentes, Olivér},
	journal-iso = {LÉGKÖR},
	journal = {LÉGKÖR: AZ ORSZÁGOS METEOROLÓGIAI INTÉZET SZAKMAI TÁJÉKOZTATÓJA},
	volume = {66},
	unique-id = {32744032},
	issn = {0133-3666},
	year = {2021},
	pages = {12-15},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:32367531,
	title = {Globális és hazai éghajlati trendek, szélsőségek változása: 2020-as helyzetkép},
	url = {https://m2.mtmt.hu/api/publication/32367531},
	author = {Lakatos, Mónika and Konkolyné Bihari, Zita and Kovácsné Izsák, Beatrix Cecília and Szentes, Olivér},
	doi = {10.1556/112.2021.00037},
	journal-iso = {SCI SEC},
	journal = {SCIENTIA ET SECURITAS},
	volume = {2},
	unique-id = {32367531},
	abstract = {A WMO 2021 elején kiadott állapotértékelője szerint a COVID–19 miatti korlátozások ellenére az üvegházhatású gázok légköri koncentrációja tovább emelkedett. A tengerszint emelkedés a közelmúltban gyorsult, rekordmagas volt a jégvesztés Grönlandon, az Antarktisz olvadása is gyorsulni látszik. Szélsőséges időjárás pusztított, élelmiszer-ellátási gondok léptek fel, és 2020-ban a COVID–19 hatásával együtt nőtt a biztonsági kockázat több régióban is. Az éghajlatváltozás felerősíti a meglévő kockázatokat, és újabb kockázatok is fellépnek majd a természeti és az ember által alkotott rendszerekben. Az éghajlatváltozás hatása a hazai mérési sorokban is megjelenik. Az Országos Meteorológiai Szolgálat (OMSZ)  homogenizált, ellenőrzött mérései szerint 1901 óta 1,2 °C-ot nőtt az évi középhőmérséklet. Két normál időszakot vizsgálva egyértelmű a magasabb hőmérsékletek felé tolódás, a csapadék éven belüli eloszlása megváltozott, az őszi másodmaximum eltűnőben van. Nőtt az aszályhajlam, gyakoribbá váltak a hőhullámok, intenzívebb a csapadékhullás, emiatt az éghajlatvédelemi intézkedések mellett a jól megalapozott alkalmazkodás is indokolt. A biztonsági kockáza-tok csökkenthetők az OMSZ és Országos Katasztrófavédelmi Főigazgatóság közötti együttműködés által.},
	keywords = {globális éghajlatváltozás; magyarországi éghajlati tendenciák; éghajlati normálok; éghajlati szélsőségek változása; éghajlatváltozás okozta biztonsági kockázatok},
	year = {2021},
	eissn = {2732-2688},
	pages = {164-171}
}

@inbook{MTMT:31919767,
	title = {COMPARATIVE STUDY OF CARPATCLIM, E-OBS AND ERA5 DATASET},
	url = {https://m2.mtmt.hu/api/publication/31919767},
	author = {Lakatos, Mónika and Szentimrey, Tamás and Kovácsné Izsák, Beatrix Cecília and Szentes, Olivér and Hoffmann, Lilla and Bíróné Kircsi, Andrea and Konkolyné Bihari, Zita},
	booktitle = {TENTH SEMINAR FOR HOMOGENIZATION AND QUALITY CONTROL IN CLIMATOLOGICAL DATABASES AND FIFTH CONFERENCE ON SPATIAL INTERPOLATION TECHNIQUES IN CLIMATOLOGY AND METEOROLOGY (Budapest, Hungary, 12-14 October 2020, Online)},
	unique-id = {31919767},
	abstract = {Recently the pan-European observational dataset E-OBS has been considered as a reference for several European climate  analyses.  Moreover,  the  usage  of  the  newly  available  global  reanalysisERA5  is  increasing  for  climate change studies. CARPATCLIM is a regional climate dataset for the Carpathian region, which is situated in central-eastern Europe. The E-OBS and ERA5 dataset were tested against CARPATLIM and against other regional datasets inthe framework of the COPERNICUS C3S_311a_Lot4 project. The common time period of E-OBS, ERA5 and CARPATCLIM is the period of 1979-2010. Different measures, evaluation statistics were computed for comparison of the gridded Tx, Tn and precipitation fields for this period. Analysis of Variance (ANOVA) method was applied for instance, which is an adequate statistical method to explore the statistical structure of different datasets. ANOVA can  be  used  effectively  for  the  characterization  of  the  spatiotemporal  statistical  properties  of  CARPATCLIM,  E-OBS  and  ERA5.  In  addition,  different  evaluation  scores,  yearly  cycle,  absolute  and monthly  extremes, quantiles, wet  days  frequency,  several  climate  indices  for  temperature  were  computed  and  reported  in  the  COPERNICUS C3S_311a_Lot4  project.  Trend  analysis  (exponential  trend  model  for  precipitation  and  linear  trend  model  for temperature) and homogeneity test for the gridded data were applied too. The differences between the datasets come from the station density behind the grids and also the methods used for homogenization and gridding determine the results. The main outcomes of this comparative study are presented on graphs and maps in this paper.},
	year = {2021},
	pages = {84-101},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@inbook{MTMT:31919763,
	title = {TRANSFORMATION OF CARPATCLIM DATASETS TO GRID-BOX AVERAGE DATASETS},
	url = {https://m2.mtmt.hu/api/publication/31919763},
	author = {Kovácsné Izsák, Beatrix Cecília and Szentimrey, Tamás and Lakatos, Mónika and Konkolyné Bihari, Zita and Bíróné Kircsi, Andrea},
	booktitle = {TENTH SEMINAR FOR HOMOGENIZATION AND QUALITY CONTROL IN CLIMATOLOGICAL DATABASES AND FIFTH CONFERENCE ON SPATIAL INTERPOLATION TECHNIQUES IN CLIMATOLOGY AND METEOROLOGY (Budapest, Hungary, 12-14 October 2020, Online)},
	unique-id = {31919763},
	abstract = {The CarpatClim datasets were developed for grid points, i.e. the meteorological variables were interpolated to grid points, while the E-OBS datasets were constructed as grid-box averages.For comparability we have transformed the CarpatClim datasets for grid-box averages. For this purpose, beside the gridded values with 0.1 x 0.1-degree resolution we used also certain modelled climate statistical parameters. These statistical parameters were modelled during the construction of CarpatClim datasets and they were also outputs of our  MISH  (Meteorological  Interpolation  based  on  Surface  Homogenized  Data  Basis; Szentimrey  and  Bihari) procedure applied for gridding. There is a MISH specialty that the necessary statistical parameters -like spatial trend and correlation structure -are modelled for a very dense half minutes grid and saved. We developed a mathematical procedure  and  applied  it  for  the  gridded  series  using  these  saved  parameters.  Now  we  have  two  versions  of CarpatClim  gridded  datasets  for  temperature  (Tx,  Tn)  and  precipitation,  namely  grid-point  and  grid-box  average datasets. Comparison of CarpatClim grid-point and CarpatClim grid-box datasets are presented too.},
	year = {2021},
	pages = {69-83},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}