@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}
}

@book{MTMT:31919757,
	title = {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)},
	url = {https://m2.mtmt.hu/api/publication/31919757},
	editor = {Lakatos, Mónika and Hoffmann, Lilla and Bíróné Kircsi, Andrea and Szentimrey, Tamás},
	publisher = {WMO},
	unique-id = {31919757},
	abstract = {The Hungarian Meteorological Service organized the jubilee 10th Seminar for Homogenization and Quality Control and the 5th Conference on Spatial Interpolation Techniques in Climatology and Meteorology virtually between 12 and 14 October 2020. Sandor Szalai the head of the Climate and Agrometeorological Department of OMSZ  initiated the Seminar  Series in  1996  with the support of the  WMO  and under the umbrella of the EUMETNET/ECSN (European Meteorological Network/ European Climate Support Network). Another key person is Tamás Szentimrey from the beginnings who have prepared the scientific programs of the Seminars and have lectured about the theoretical background of homogenization and interpolation on the meetings. The basic questions at the starts were the spreading of homogenization methods and the overall use of homogenized time series in climate change studies. The general view has been changed since then. Homogenization became a necessary element of data management procedures. The WMO CCl set up a team to support quality control and homogenization activities at NMHSs. The  main  task  of  the  Task  Team  on  Homogenization  (TT  HOM)  was  to  provide  guidance  to Members   on   methodologies,   standards   and   software   required   for   quality   control   and homogenization of long term climate time-series. WMO Guidelines on Homogenisation (WMO-No. 1245) were published in 2020 and are accessible in English, French and Spanish languages through  WMO’s  electronic  library  (https://public.wmo.int/en/resources/library).   Certainly, Seminars took a major part of the initiation and completion of this guidance, as these occasions created great opportunity for information exchange amongst the homogenization community. The Homogenization Seminars have been organized together with the Interpolation Conferences since  2004.  The  reason  for  joining  them  was  the  strong  connection  between  topics,  as  the homogenization   and   quality   control   procedures   apply   spatial   statistics   and   interpolation techniques for  the  spatial  comparison  of  the  data  as  well.  Besides  these  the  reconstruction  of meteorological fields and construction of gridded databases require applying spatial interpolation methods. In addition, the spatial interpolation procedures (e.g. gridding) need homogeneous data series with high quality. Homogenization  of  climate  data  series  and  spatial  interpolation  of  climate  data  play  an  ever-growing role in the meteorology and climatology. The usage of high quality data as an important issue appeared on the European and global level officially. We  hope,  that  the  Seminar  series  filled  a  major  part  in  dissemination  and  development  of homogenization methods not only in Europe, but worldwide.},
	keywords = {Homogenization},
	year = {2021}
}

@CONFERENCE{MTMT:31635680,
	title = {Comparative study of CARPATCLIM, E-OBS and ERA5 dataset.},
	url = {https://m2.mtmt.hu/api/publication/31635680},
	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 = {Abstract book. 10th Seminar for Homogenization and Quality Control and 5th Conference on Spatial Interpolation Techniques in Climatology and Meteorology},
	unique-id = {31635680},
	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 reanalysis ERA5 is increasing for climate change studies. CARPATCLIM is a regional climate dataset for the Carpathian region in central-eastern Europe. Among others the E-OBS and ERA5 dataset were tested against CARPATLIM and against other regional datasets in the framework of the COPERNICUS C3S_311a_Lot4 project.
		CARPATCLIM dataset encompassing gridded daily observations for the Carpathian region. It is available on a 0.1°(~10 km×10 km) grid and includes homogenized, gridded daily time series of various meteorological parameters from 1961 to 2010. The method and software used in CARPATCLIM project (www.carpatclim-eu.org.) for data quality control, homogenization, data completion was the MASH (Szentimrey). Interpolation of the homogenized time series was carried out by applying the MISH (Szentimrey and Bihari) procedure. The temperature and precipitation grids are available on the CARPATCLIM webpage and also via Copernicus: https://surfobs.climate.copernicus.eu/dataaccess/access_carpatclim.php.
		The common time period of E-OBS, ERA5 and CARPATCLIM is 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. 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 work.},
	keywords = {climate change; Dataset; CARPATCLIM; ERA5},
	year = {2020},
	pages = {32-33},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:31363605,
	title = {Return values of 60-minute extreme rainfall for Hungary},
	url = {https://m2.mtmt.hu/api/publication/31363605},
	author = {Lakatos, Mónika and Kovácsné Izsák, Beatrix Cecília and Szentes, Olivér and Hoffmann, Lilla and Bíróné Kircsi, Andrea and Konkolyné Bihari, Zita},
	doi = {10.28974/idojaras.2020.2.1},
	journal-iso = {IDŐJÁRÁS},
	journal = {IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE},
	volume = {124},
	unique-id = {31363605},
	issn = {0324-6329},
	year = {2020},
	eissn = {0324-6329},
	pages = {143-156},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:31192997,
	title = {Computation of daily Penman–Monteith reference evapotranspiration in the Carpathian Region and comparison with Thornthwaite estimates},
	url = {https://m2.mtmt.hu/api/publication/31192997},
	author = {Lakatos, Mónika and Weidinger, Tamás and Hoffmann, Lilla and Konkolyné Bihari, Zita and Horváth, Ákos},
	doi = {10.5194/asr-16-251-2020},
	journal-iso = {ADV SCI RES},
	journal = {ADVANCES IN SCIENCE AND RESEARCH},
	volume = {16},
	unique-id = {31192997},
	issn = {1992-0628},
	year = {2020},
	eissn = {1992-0636},
	pages = {251-259},
	orcid-numbers = {Weidinger, Tamás/0000-0001-7500-6579}
}

@{MTMT:30912010,
	title = {A GLOBÁLSUGÁRZÁS ADATOK INTERPOLÁCIÓJA MŰHOLDAS ADATOK FELHASZNÁLÁSÁVAL},
	url = {https://m2.mtmt.hu/api/publication/30912010},
	isbn = {9789639931183},
	author = {Hoffmann, Lilla and Kovácsné Izsák, Beatrix Cecília and Bíróné Kircsi, Andrea and Szentimrey, Tamás and Konkolyné Bihari, Zita},
	booktitle = {Értékteremtés meteorológiai információkkal. 45. Meteorológiai Tudományos Napok, az előadások összefoglalói},
	unique-id = {30912010},
	abstract = {Meteorológiai, éghajlati vizsgálatokhoz nemcsakaz szükséges, hogy az adatsorok minőségeidőben egyenletes  és  jó  legyen,  hanem  az  is,  hogy  azokra  a  helyekre  is  képesek  legyünkmegbízható  adatokat származtatni, ahol nemvégeztek meteorológiai megfigyeléseket. Az interpoláció során természetesen arratörekszünk, hogy az eredmény a lehető legnagyobb mértékben megközelítse a valódiállapotot. OMSZ-ban készült  egy  olyan  matematikai  statisztikaialapokon  nyugvó  interpolációs  rendszer,  a  MISH,amely kifejezetten meteorológiai változók interpolálására lett kifejlesztve.A MISH segítségévelnemcsak sokévi átlagokat  bemutató  éghajlatitérképeket  készíthetünk,  hanem  akár  egy  napravonatkozó  adatokat  is előállíthatunk.  A  MISHtovábbi  sajátossága, hogy  az  interpoláció  soránúgynevezett  háttér-információk alkalmazására isképes, azaz olyan –az interpolálandó elemmelösszefüggő –adatokat is felhasználhatunk,melyek  valamilyen  sűrű  rácshálózaton  állnakrendelkezésünkre.  Mivel  a  globálsugárzás  adatsorok viszonylag  rövidek,  ráadásul  a  tengerszintfeletti  magassággal  csak  csekély  mértékben  korrelálnak, feladatunknak tűztük ki, hogy műholdas adatokat használva javítsunk a benchmark eredményeinken.},
	year = {2019},
	pages = {12-13},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@{MTMT:30912007,
	title = {HOMOGENIZÁLT ADATSOR VAGY MÉRÉSEK?},
	url = {https://m2.mtmt.hu/api/publication/30912007},
	author = {Kovácsné Izsák, Beatrix Cecília and Szentimrey, Tamás and Hoffmann, Lilla and Bíróné Kircsi, Andrea and Lakatos, Mónika and Szentes, Olivér and Konkolyné Bihari, Zita},
	booktitle = {Értékteremtés meteorológiai információkkal. 45. Meteorológiai Tudományos Napok, az előadások összefoglalói},
	unique-id = {30912007},
	abstract = {Meteorológiai  idősorok  trendvizsgálata  hangsúlyos  szerepet  kapott  az  elmúlt  években.  Korábban  is  születtek tanulmányok a témában, de a közölt eredmények esetenként ellentétesek, mint amit napjainkban publikálunk. Egyre több támadás  éri  a  klimatológusokat,  hogy  összevissza  beszélnek,  hiszen  az  1970-es  évek  végéig  azzal  riogattak,  hogy megfagyunk,  most  meg  a  globális  felmelegedéssel  ijesztgetnek.  Fontos  azonban  észrevenni,  hogy  a  homogenizálás módszertana,  pont  az  elmúlt  30  évben  fejlődött  ki,  azóta  tudjuk  az  éghajlatváltozást  pontosabban  detektálni. Homogenizálással  a változó  mérési  körülmények,  például  állomás  áthelyezés,  a  mérési  idő  megváltozása  vagy a műszercsere okozta inhomogenitást, indokolatlan törést el tudjuk távolítani az adatsorokból.Poszterünkön megmutatjuk az elmúlt 118 év éves és évszakos átlaghőmérséklet trendjeit homogenizált és nyers adatsorokon is. Elemezzük, hogy az inhomogén adatsorok miért vitték el a statisztikákat teljesen más irányba, mint a homogenizált  adatsorok  esetében.  F-próbával  ellenőrizzük  a  lineáris  modellre  vonatkozó  feltevés  helyességét,  azaz elfogadható-e  az  a  nullhipotézis,  hogy  a  trendfüggvény  az  idő  lineáris  függvénye  a  vizsgált  adatsorok  esetén.  A poszterünkön  bemutatott  adatsorok  esetén  az  esetleges  adathibák  és  inhomogenitásokkiszűrését,  korrekcióját,  és  az adathiányok pótlását a MASH homogenizációs eljárás alkalmazásával végezzük. Az így kapott értékeket sűrű, szabályos rácshálózatra interpoláljuk, így az egész országra kiterjedően képet kaphatunk a trendértékek térbeli megjelenítéséhez. Ehhez az OMSZ Éghajlati Osztályán kifejlesztett, kifejezetten meteorológiai elemek interpolációjára  alkalmas MISH programrendszert használtuk.},
	year = {2019},
	pages = {37-38},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@CONFERENCE{MTMT:30910315,
	title = {Comparison of different drought indices based on modeled crop yield for Hungary},
	url = {https://m2.mtmt.hu/api/publication/30910315},
	author = {Hoffmann, Lilla and Kovácsné Izsák, Beatrix Cecília and Konkolyné Bihari, Zita and Bíróné Kircsi, Andrea and Zubor-Nemes, Anna and Molnár, András},
	booktitle = {EMS Annual Meeting Abstracts},
	unique-id = {30910315},
	abstract = {Climate  change  may  have  various  impacts  on  agriculture  and  environment  Carpathian/Pannonian  basin.  In the last decades extreme weather events has been intensifying in the region. Hungary is situated in the center ofthe Pannonian basin. Heavy rainfalls and lack of precipitation leading to severe drought, both occurred in ourregion recently. As a result of the climate change the agriculture and water intense sectors suffers more frequentlyfrom drought. Severe drought events cause significant impacts on crop yield and thus on the economy as well.The damage of drought due to lack of precipitation can be quantified by using various drought indices. Manydrought indices are applied in agrometeorology, however, the overall verification of these indices does not exist,although it would be crucial. The main aim of this work is to determine the drought index or indices amongst thewidely used indicators that characterize the effect of a drought event on the crop yield the best.Modeled yield of maize and wheat are investigated in this work. We analyze the widely used drought indices (e.g.Standardized Precipitation Index, SPI and Palmer Drought Severity Index, PDSI) to identify the effect of drought on the crop yield. The difference of modeled crop yield with and without water stress data is correlated to somedrought indices in this paper. The time period of the modeled crop yield is 2002-2017. The 4M crop simulationmodel were applied for these purposes. The M4 model is a deterministic model, which simulates the water andnutrient balance of the soil, the soil-plant interactions and plant growth. The 4M model is a further developmentof the Ceres (Crop Environment Resource Synthesis) model. The model simulations were performed by experts at the Research Institute of Agriculture. The results will be displayed in tables and on maps.Our motivation for this study is that one of the flagship questions were identified in PannEx (the Pannonian BasinExperiment)  Regional  Hydroclimate  Project  (RHP)  of  the  Global Energy and Water cycle exchanges project (GEWEX) Hydroclimatology Panel (GHP) is the „Adaptation of agronomical activities to weather and climateextremes”. Possibly this study will increase the knowledge on drought and will support the adaptation capacity in the face of climate change in the Pannonian Basin.},
	year = {2019},
	orcid-numbers = {Kovácsné Izsák, Beatrix Cecília/0000-0003-1323-5389}
}

@article{MTMT:30782861,
	title = {2018 volt a legmelegebb év 1901 óta Magyarországon},
	url = {https://m2.mtmt.hu/api/publication/30782861},
	author = {Lakatos, Mónika and Bíróné Kircsi, Andrea and Hoffmann, Lilla},
	journal-iso = {ERDÉSZETI LAPOK},
	journal = {ERDÉSZETI LAPOK},
	volume = {154},
	unique-id = {30782861},
	issn = {1215-0398},
	year = {2019},
	pages = {50}
}

@article{MTMT:30655977,
	title = {Korábban kezdődő vegetációs időszak – Előny vagy hátrány?},
	url = {https://m2.mtmt.hu/api/publication/30655977},
	author = {Hoffmann, Lilla and Lakatos, Mónika},
	journal-iso = {AGROFÓRUM-NÖVÉNYTERMESZTŐK NÖVÉNYVÉDŐK},
	journal = {AGROFÓRUM - A NÖVÉNYTERMESZTŐK ÉS NÖVÉNYVÉDŐK HAVILAPJA},
	volume = {30},
	unique-id = {30655977},
	issn = {1788-5884},
	year = {2019},
	pages = {14-16}
}