TY - BOOK AU - Kovácsné Izsák, Beatrix Cecília AU - Szentes, Olivér AU - Konkolyné Bihari, Zita AU - Bokros, K. AU - Hercsényi, L. AU - Lakatos, Mónika AU - Tótiván, B. TI - Reprezentatív meteorológiai adatok biztosítása a múlt és a jelen éghajlatának megismerésére. PY - 2023 UR - https://m2.mtmt.hu/api/publication/34532323 ID - 34532323 LA - Hungarian DB - MTMT ER - TY - CONF AU - Kovácsné Izsák, Beatrix Cecília AU - Kinga, Bokros AU - Konkolyné Bihari, Zita TI - Interpolating intraday precipitation data with radar background information T2 - EMS Annual Meeting Abstracts PY - 2023 UR - https://m2.mtmt.hu/api/publication/34506169 ID - 34506169 AB - 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. LA - English DB - MTMT ER - TY - JOUR AU - Jakuschné Kocsis, Tímea AU - Magyar-Horváth, Kinga AU - Konkolyné Bihari, Zita AU - Kovácsné Székely, Ilona TI - Analysis of the correlation between the incidence of food-borne diseases and climate change in Hungary JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 127 PY - 2023 IS - 2 SP - 217 EP - 231 PG - 15 SN - 0324-6329 DO - 10.28974/idojaras.2023.2.4 UR - https://m2.mtmt.hu/api/publication/34002421 ID - 34002421 AB - 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. LA - English DB - MTMT ER - TY - CONF AU - Kovácsné Izsák, Beatrix Cecília AU - Szentes, Olivér AU - Konkolyné Bihari, Zita TI - Modelling climate statistical parameters by MISH interpolation procedure T2 - EMS Annual Meeting Abstracts PY - 2022 SP - Vol. 19, EMS2022-422, 2022 UR - https://m2.mtmt.hu/api/publication/33263497 ID - 33263497 LA - English DB - MTMT ER - TY - BOOK AU - Lakatos, Mónika AU - Konkolyné Bihari, Zita AU - Kovácsné Izsák, Beatrix Cecília AU - Marton, Annamária AU - Szentes, Olivér TI - MEGFIGYELT ÉGHAJLATI VÁLTOZÁSOK MAGYARORSZÁGON PY - 2021 UR - https://m2.mtmt.hu/api/publication/32758501 ID - 32758501 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Lakatos, Mónika AU - Konkolyné Bihari, Zita AU - Kovácsné Izsák, Beatrix Cecília AU - Marton, Annamária AU - Szentes, Olivér TI - MEGFIGYELT ÉGHAJLATI VÁLTOZÁSOK MAGYARORSZÁGON JF - LÉGKÖR: AZ ORSZÁGOS METEOROLÓGIAI INTÉZET SZAKMAI TÁJÉKOZTATÓJA J2 - LÉGKÖR VL - 66 PY - 2021 IS - 3 SP - 5 EP - 11 PG - 7 SN - 0133-3666 UR - https://m2.mtmt.hu/api/publication/32744041 ID - 32744041 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Kovácsné Izsák, Beatrix Cecília AU - Konkolyné Bihari, Zita AU - Szentes, Olivér TI - ÉGHAJLATVÁLTOZÁS: HOMOGENIZÁLT VAGY NYERS ADATSOROKAT VIZSGÁLJAK? JF - LÉGKÖR: AZ ORSZÁGOS METEOROLÓGIAI INTÉZET SZAKMAI TÁJÉKOZTATÓJA J2 - LÉGKÖR VL - 66 PY - 2021 IS - 3 SP - 12 EP - 15 PG - 4 SN - 0133-3666 UR - https://m2.mtmt.hu/api/publication/32744032 ID - 32744032 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Lakatos, Mónika AU - Konkolyné Bihari, Zita AU - Kovácsné Izsák, Beatrix Cecília AU - Szentes, Olivér TI - Globális és hazai éghajlati trendek, szélsőségek változása: 2020-as helyzetkép JF - SCIENTIA ET SECURITAS J2 - SCI SEC VL - 2 PY - 2021 IS - 2 SP - 164 EP - 171 PG - 8 SN - 2732-2688 DO - 10.1556/112.2021.00037 UR - https://m2.mtmt.hu/api/publication/32367531 ID - 32367531 AB - 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. LA - Hungarian DB - MTMT ER - TY - CHAP AU - Lakatos, Mónika AU - Szentimrey, Tamás AU - Kovácsné Izsák, Beatrix Cecília AU - Szentes, Olivér AU - Hoffmann, Lilla AU - Bíróné Kircsi, Andrea AU - Konkolyné Bihari, Zita ED - Lakatos, Mónika ED - Hoffmann, Lilla ED - Bíróné Kircsi, Andrea ED - Szentimrey, Tamás TI - COMPARATIVE STUDY OF CARPATCLIM, E-OBS AND ERA5 DATASET T2 - 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) PB - World Meteorological Organization (WMO) CY - Geneva T3 - WCDMP- No. 86 PY - 2021 SP - 84 EP - 101 PG - 18 UR - https://m2.mtmt.hu/api/publication/31919767 ID - 31919767 AB - 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. LA - English DB - MTMT ER - TY - CHAP AU - Kovácsné Izsák, Beatrix Cecília AU - Szentimrey, Tamás AU - Lakatos, Mónika AU - Konkolyné Bihari, Zita AU - Bíróné Kircsi, Andrea ED - Lakatos, Mónika ED - Hoffmann, Lilla ED - Bíróné Kircsi, Andrea ED - Szentimrey, Tamás TI - TRANSFORMATION OF CARPATCLIM DATASETS TO GRID-BOX AVERAGE DATASETS T2 - 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) PB - World Meteorological Organization (WMO) CY - Geneva T3 - WCDMP- No. 86 PY - 2021 SP - 69 EP - 83 PG - 15 UR - https://m2.mtmt.hu/api/publication/31919763 ID - 31919763 AB - 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. LA - English DB - MTMT ER -