TY - JOUR AU - Ho, Khanh V AU - Süle, Gabriella AU - Kovács, Bence AU - Erdős, László TI - Strong differences in microclimate among the habitats of a forest-steppe ecosystem JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS PY - 2024 SN - 0324-6329 UR - https://m2.mtmt.hu/api/publication/34493221 ID - 34493221 LA - English DB - MTMT ER - TY - JOUR AU - Khanh, Ho Vu AU - Süle, Gabriella AU - Kovács, Bence AU - ErdĘs, László TI - Strong differences in microclimate among the habitats of a forest-steppe ecosystem. JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 128 PY - 2024 IS - 1 SP - 1 EP - 26 PG - 26 SN - 0324-6329 UR - https://m2.mtmt.hu/api/publication/34795037 ID - 34795037 LA - English DB - MTMT ER - TY - JOUR AU - Ho, Vu Khanh AU - Gabriella, Süle AU - Bence, Kovács AU - László, Erdős TI - Strong differences in microclimate among the habitats of a forest-steppe ecosystem JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 128 PY - 2024 IS - 1 SP - 1-26 SN - 0324-6329 UR - https://m2.mtmt.hu/api/publication/34794386 ID - 34794386 LA - English DB - MTMT ER - TY - JOUR AU - Stevan, Savić AU - Boško, Milovanović AU - Dragan, Milošević AU - Jelena, Dunjić AU - Milica, Pecelj AU - Milica, Lukić AU - Miloš, Ostojić AU - Renata, Fekete TI - Thermal assessments at local and micro scales during hot summer days: a case study of Belgrade (Serbia) JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 128 PY - 2024 IS - 1 SP - 121 EP - 141 PG - 21 SN - 0324-6329 DO - 10.28974/idojaras.2024.1.7 UR - https://m2.mtmt.hu/api/publication/34754127 ID - 34754127 LA - English DB - MTMT ER - TY - JOUR AU - Gombos, Béla AU - Nagy, Zoltán AU - Hajdu, András AU - Nagy, János TI - Climate change in the Debrecen area in the last 50 years and its impact on maize production JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 127 PY - 2023 IS - 4 SP - 485 EP - 504 PG - 20 SN - 0324-6329 DO - 10.28974/idojaras.2023.4.5 UR - https://m2.mtmt.hu/api/publication/34417887 ID - 34417887 AB - The average yield of maize is significantly dependent on the meteorological conditions of the growing year. Both the most favorable weather conditions and the weather anomalies that tend to cause damage depend on the given phenophase. The aim of this research is to analyze the climatic changes that are important in maize production in the Hajdúság region. For the climatological study of the area, homogenized temperature and precipitation data from the Hungarian Meteorological Service was used for the Debrecen region, which are freely available for download from the data repository of the institution. Trend analysis was performed for the last 50-year (1973–2022) and 30-year (1993–2022) periods. In total, 40 meteorological data series matching the study objective were analyzed. Linear regression calculations were performed using the SPSS 27 statistical software. For the non-parametric procedure, the MAKESENS Excel application was used, based on the Mann-Kendall (MK) test and Sen's slope estimation. This research shows that the choice of the length of the study period affects the results of trend analysis. The numerical values of the trend slope for the 30-year vs. 50-year period differ, and for some parameters there are also substantial differences (e.g., trend sign). The results of the parametric and non-parametric trend analyses differed only marginally for the temperature variables included. Also, for precipitation data that do not follow a normal distribution (e.g., monthly), there were only a few significant differences. The trend in mean annual temperature shows an increase of 0.39 and 0.52 °C in 10 years, and an increase of around 2 °C in 50 years and 1.5 °C in 30 years. There is a significant warming in both the summer and winter half-years, with the summer half-year showing a steeper upward trend in the 50-year data series and the winter half-year in the 30-year data series. There is a clear pattern of large, highly significant warming in the summer months and less significant changes in the two spring and two autumn months that were observed. A negative, non-significant trend in annual precipitation is observed. The decreases of 17 mm and 24 mm/10 years obtained for the 50- and 30-year time series are not negligible from a practical point of view. For the summer half-year, the precipitation amount is decreasing, with a slope of -27 mm/10 years for the last 30 years, but even this value is not significant due to the high variability. There is no significant change in the amount of precipitation in the winter half-year over the last decades. Significant trends cannot be detected from monthly or even semi-annual or annual precipitation data. The Mann-Kendall test showed a trend decrease only in the 30-year April data series at the p=0.1 significance level. Overall, the changes are negative for maize production. It should be highlighted that the obvious warming, combined with a slight decrease in precipitation, is leading to a deterioration in crop water availability and a reduction in crop yields. The impact of the identified adverse climatic changes can be compensated to a significant extent by the proposed agrotechnical responses. LA - English DB - MTMT ER - TY - JOUR AU - Kugler, Zsófia AU - Horváth, Viktor Győző TI - A comparison of river streamflow measurement from optical and passive microwave radiometry JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 127 PY - 2023 IS - 4 SP - 473 EP - 484 PG - 12 SN - 0324-6329 DO - 10.28974/idojaras.2023.4.4 UR - https://m2.mtmt.hu/api/publication/34417883 ID - 34417883 N1 - Export Date: 21 December 2023 Correspondence Address: Kugler, Z.; Department of Photogrammetry and Geoinformatics, Műegyetem rkp. 3, Hungary; email: kugler.zsofia@emk.bme.hu Funding Agency and Grant Number: European Union [RRF-2.3.1-21-2022-00004]; Ministry of Innovation and Technology NRDI Office within the framework of the Artificial Intelligence National Laboratory Program; European Union within the framework of the Artificial Intelligence National Laboratory [RRF-2.3.1-21-2022-00004]; National Research and Innovation Office; National Research, Development and Innovation Fund of Hungary [TKP2021-NKTA-32] Funding text: The authors would like to express their gratitude towards Dr. Kalman Kovacs, Dr. Daniel Kristof, and the Lechner Knowledge Center for providing advice and support with the acquisition of satellite images. The research was supported by the Ministry of Innovation and Technology NRDI Office within the framework of the Artificial Intelligence National Laboratory Program. The GPUs have been donated by NVIDIA.The authors would like to thank Dr. Kalman Kovacs and the Data Supply Department of the Hungarian Meteorological Service for sharing the extensive local and medical meteorological and accident databases for the purpose of the research presented in this paper. The research presented here was supported by the the European Union project RRF-2.3.1-21-2022-00004 within the framework of the Artificial Intelligence National Laboratory.Part of the work presented was supported by the National Research and Innovation Office.Project no. TKP2021-NKTA-32 has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the TKP2021-NKTA funding scheme. AB - Climate change has a crucial impact on the global energy and water cycle. The hydrological cycle can be studied both from ground and satellite measurements on a global scale. Yet a comprehensive overview is challenging to establish given the spatial and temporal limitations related to various Earth Observation satellite sensors or maintenance of in-situ gauges. Optical remote sensing of visible light can not overcome the substantial obstacle from cloud cover that vastly limits its capability in daily global monitoring. Active satellite sensors like SAR or altimetry are not capable to provide global coverage on a daily basis, therefore, they can be geographically limited. Passive microwave radiometry (PMR) can acquire both daily and global scales that enables the temporally frequent and spatially extensive observations of continental river gauge. Previous studies demonstrated the use of PMR measurements for global daily river gauge benefiting from its high sensitivity of microwave radiation to water presence. This study aims at comparing the methodology of PMR to optical river gauge measurements based on the assumption that at selected locations along the river channel, increase in streamflow is related to increase in the floodplain water surface inundation. Comparison showed a significant obstacle of cloud cover over tropical regions, where PMR has the potential to measure river streamflow. Yet over regions with less clouds both optical and PMR can be good alternative to in-situ streamflow ground measurements. LA - English DB - MTMT ER - TY - JOUR AU - Szántó, Mátyás AU - Vajta, László TI - Forecasting critical weather front transitions based on locally measured meteorological data JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 127 PY - 2023 IS - 4 SP - 459 EP - 471 PG - 13 SN - 0324-6329 DO - 10.28974/idojaras.2023.4.3 UR - https://m2.mtmt.hu/api/publication/34417880 ID - 34417880 N1 - Export Date: 21 December 2023 Correspondence Address: Szántó, M.; Department of Control Engineering and Information Technology, Műegyetem rkp. 3, Hungary; email: mszanto@iit.bme.hu Funding Agency and Grant Number: European Union [RRF-2.3.1-21-2022-00004] Funding text: The authors would like to thank Dr. Kalman Kovacs and the Data Supply Department of the Hungarian Meteorological Service for sharing the extensive local and medical meteorological and accident databases for the purpose of the research presented in this paper. The research presented here was supported by the the European Union project RRF-2.3.1-21-2022-00004 within the framework of the Artificial Intelligence National Laboratory. AB - Certain types of medical meteorological phenomenontransitions can have a significant deteriorating effect on road safety conditions. Hence, a system that is capable of warning road users of the possibility of such conversions can prove to be utterly useful. Vehicles on different levels of automation (i.e., ones equipped with driver assistance systems – DAS) can use this information to adjust their parameters and become more cautious or warn the drivers to be more careful while driving. In this paper, we prove that identifying the critical type of weather front transition (i.e., no front to unstable cold front) is possible based on locally observable meteorological information. We present our method for classifying weather front transitions to non-critical versus critical types. Our developed machine learning model was trained on a dataset covering 10 years of meteorological data in Hungary, and it shows promising results with a recall value of 86%, and an F1-score of 60%. As the developed method will form the basis of a patent, we are omitting key components and parameters of our solution from this paper. LA - English DB - MTMT ER - TY - JOUR AU - Fridvalszky, András Máté AU - Tóth, Balázs György AU - Szécsi, László TI - Evaluating dehazing techniques on artificial and satellite land surface images JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 127 PY - 2023 IS - 4 SP - 447 EP - 457 PG - 11 SN - 0324-6329 DO - 10.28974/idojaras.2023.4.2 UR - https://m2.mtmt.hu/api/publication/34417874 ID - 34417874 N1 - Export Date: 21 December 2023 Correspondence Address: Fridvalszky, A.; Department of Control Engineering and Information Technology, Műegyetem rkp. 3, Hungary; email: fridvalszky@iit.bme.hu Funding Agency and Grant Number: Ministry of Innovation and Technology NRDI Office Funding text: The authors would like to express their gratitude towards Dr. Kalman Kovacs, Dr. Daniel Kristof, and the Lechner Knowledge Center for providing advice and support with the acquisition of satellite images. The research was supported by the Ministry of Innovation and Technology NRDI Office within the framework of the Artificial Intelligence National Laboratory Program. The GPUs have been donated by NVIDIA. AB - Many image-based recognition tasks are highly susceptible to different types of natural phenomena like foggy weather, snow, or rain. The participating media will likely obscure important details necessary for these algorithms to work correctly. Still, these aspects could be recovered in certain situations with prior information about the underlying light interactions. This could be done with certain heuristics or with the nowadays popular deep-learning based methods. In this paper, we review and compare the results of two approaches to remove or scale down the effects of foggy weather. We also examine how these results can be applied to high resolution satellite images of land surfaces. LA - English DB - MTMT ER - TY - JOUR AU - Birinyi, Edina AU - Olajosné Lakatos, Boglárka AU - Belényesi, Márta AU - Kristóf, Dániel AU - Hetesi, Zsolt AU - Mrekva, László AU - Mikus, Gábor TI - Contribution of data-driven methods to risk reduction and climate change adaptation in Hungary and beyond JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 127 PY - 2023 IS - 4 SP - 421 EP - 446 PG - 26 SN - 0324-6329 DO - 10.28974/idojaras.2023.4.1 UR - https://m2.mtmt.hu/api/publication/34417849 ID - 34417849 AB - Among a series of tangible phenomena related to climate change and ecosystem degradation, the severe drought damage that occurred in 2022 urges in particular a thoughtful and long-term concept to tackle and mitigate the effects of similar events. To develop this concept, in addition to taking stock of scientific results so far, it is crucial to establish the basis for mutually supportive cooperation between the sectors concerned, including agriculture, water management, and nature conservation. As confirmed by scientific knowledge, the continuous deterioration of the landscape's water retention and evapotranspiration capacity is associated with weakening the climate regulating function and the degradation of agricultural production conditions. Accordingly, the task is not to find new resources and interventions ensuring the continuation of current landscape use; the real goal is to find the landscape use (farming methods and water use) that will ensure sustainable human livelihoods and environmental conditions. All the tools and knowledge are available for the first steps and subsequent ongoing monitoring and refinement of a precautionary and prevention-based approach to support all levels of ecosystem services. With continuous professional dialogue and implementation of established and new methods, several goals can be achieved simultaneously, such as the integration of economic trends into the approach, the revitalization of Hungarian landscape culture, and hence the preservation of the rural workforce. LA - English DB - MTMT ER - TY - JOUR AU - Aydemir, Alper AU - Karahüseyin, Fikriye Ezgi AU - Yılmaz, Yaşar Can TI - Evaluation of wind comfort with computational fluid dynamics simulations for pedestrian sidewalks around buildings JF - IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE J2 - IDŐJÁRÁS VL - 127 PY - 2023 IS - 3 SP - 401 EP - 420 PG - 20 SN - 0324-6329 DO - 10.28974/idojaras.2023.3.7 UR - https://m2.mtmt.hu/api/publication/34139550 ID - 34139550 AB - Wind power could be one of the most clean and powerful renewable resources for electrical energy production, but on the other hand, uncontrolled wind flow especially in urban places could cause undesired situations as damage to buildings, decrease in pedestrian comfort, environmental damage, or even life loss. Construction of high-rise buildings, widely spread structures within cities, and environmental changes forces, engineers to find quick, reliable, and also economically viable solutions during design stages, but wind comfort of sidewalks generally not considered enough even if they are located in crowded areas. The web-based computer aided engineering (CAE) program named Simscale which runs on the basis of sophisticated graphical interface was used as computational fluid dynamics (CFD) software to determine wind speeds under influence of buildings in the Nuh Naci Yazgan University campus. Also, field measurements carried out in campus area for a short term period were compared with long term hourly wind speed data obtained from the Turkish State Meteorological Service (MGM) station located in Kayseri to identify most optimal wind speed data for the research area. Results of analysis showed that wind speed increased in the mostly used paths of campus, which means that the layout of buildings negatively affected the wind comfort. CFD analysis softwares could be used to determine the possible consquences of wind with less economic investment in a short time, and they could be used in accordance with comfort criterias as well as safety regulations. LA - English DB - MTMT ER -