@CONFERENCE{MTMT:35273917,
	title = {Evaluation of climate change impacts for tourism in Hungary based on tourism climate metrics},
	url = {https://m2.mtmt.hu/api/publication/35273917},
	author = {Kovács, Attila},
	booktitle = {EMS Annual Meeting Abstracts},
	doi = {10.5194/ems2024-95},
	unique-id = {35273917},
	year = {2024},
	pages = {EMS Annual Meeting Abstracts Vol. 21, EMS2024-95},
	orcid-numbers = {Kovács, Attila/0000-0002-4766-8898}
}

@misc{MTMT:35273300,
	title = {Assessment of observed and expected climate exposure of tourism sector in Hungary},
	url = {https://m2.mtmt.hu/api/publication/35273300},
	author = {Kovács, Attila},
	unique-id = {35273300},
	abstract = {Climate change may adversely influence tourist destinations, affecting travel behavior (motivation and destination selection) and thus tourism demand. The evaluation of the present and expected future exposure of tourist areas to climate change is extremely important. Destinations with favorable climate conditions can gain competitive advantage compared to other areas. Climate exposure-based assessment in a country or in specific tourist destinations can contribute to develop and implement targeted adaptation strategies to climate change. In the research, I analyze the observed and future climate conditions for the area of Hungary, Central Europe, using different tourism climate indices. One applied measure is a modified form of the Tourism Climate Index (mTCI, Kovács et al. 2016). For the quantification of the present conditions (i.e. period 1971–2000), I use the grid point based observational database CarpatClim-HU at 10 km horizontal resolution. The future data are derived from two regional climate models (ALADIN and REMO) driven by different global climate models. Future anthropogenic activity is described by RCP4.5 and RCP8.5 scenarios. With the use of multi-model and multi-scenario ensemble the uncertainties in climate model predictions could be better described. The climate conditions are determined for multiple future periods: 2041– 2070 and 2071–2100. The results are displayed on a monthly basis and on a Hungarian district spatial scale. In the present period, based on mTCI, the most favorable conditions occur in the shoulder months (April, May, September and October), while there is a slight deterioration in summer. Future tendencies indicate that climate change will have impact on the tourism sector in Hungary. The summer months (especially July and August) may bring less favorable conditions with one mTCI category in most parts of the country. Certain scenarios also show a slight drop in May and September in some districts. However, most shoulder months (March, April, October and November) are expected to be more pleasant for tourism in the future. In addition to the mTCI index, I intend to use the Holiday Climate Index (HCI:Urban, Scott et al. 2016) and compare the results with mTCI.
		
		Project no. 142335 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the PD_22 funding scheme.},
	year = {2024},
	orcid-numbers = {Kovács, Attila/0000-0002-4766-8898}
}

@mastersthesis{MTMT:35091472,
	title = {A városi zöldinfrastruktúra szerepe a fenntartható csapadékvíz-gazdálkodásban [The role of the green infrastructure in the sustainable urban water management]},
	url = {https://m2.mtmt.hu/api/publication/35091472},
	author = {Csete, Ákos Kristóf},
	doi = {10.14232/phd.11820},
	publisher = {University of Szeged},
	unique-id = {35091472},
	year = {2024},
	orcid-numbers = {Csete, Ákos Kristóf/0000-0002-5350-7070}
}

@article{MTMT:34790894,
	title = {Evaluating the Impact of Heat Mitigation Strategies Using Added Urban Green Spaces during a Heatwave in a Medium-Sized City},
	url = {https://m2.mtmt.hu/api/publication/34790894},
	author = {Skarbit, Nóra and Unger, János and Gál, Tamás Mátyás},
	doi = {10.3390/su16083296},
	journal-iso = {SUSTAINABILITY-BASEL},
	journal = {SUSTAINABILITY},
	volume = {16},
	unique-id = {34790894},
	year = {2024},
	eissn = {2071-1050},
	orcid-numbers = {Skarbit, Nóra/0000-0002-6894-4310; Unger, János/0000-0002-0637-0091; Gál, Tamás Mátyás/0000-0002-1761-3239}
}

@article{MTMT:34568395,
	title = {Modelling the building-related photovoltaic power production potential in the light of the EU's Solar Rooftop Initiative},
	url = {https://m2.mtmt.hu/api/publication/34568395},
	author = {Molnár, Gergely and Cabeza, Luisa F. and Chatterjee, Souran and Ürge-Vorsatz, Diana},
	doi = {10.1016/j.apenergy.2024.122708},
	journal-iso = {APPL ENERG},
	journal = {APPLIED ENERGY},
	volume = {360},
	unique-id = {34568395},
	issn = {0306-2619},
	year = {2024},
	eissn = {1872-9118}
}

@article{MTMT:34561168,
	title = {Modeling urban air temperature using satellite-derived surface temperature, meteorological data, and local climate zone pattern—a case study in Szeged, Hungary},
	url = {https://m2.mtmt.hu/api/publication/34561168},
	author = {Guo, Yuchen and Unger, János and Khabibolla , Almaskhan and Tian, Guohang and He, Ruizhen and Li, Huawei and Gál, Tamás Mátyás},
	doi = {10.1007/s00704-024-04852-7},
	journal-iso = {THEORET APPL CLIMAT},
	journal = {THEORETICAL AND APPLIED CLIMATOLOGY},
	volume = {155},
	unique-id = {34561168},
	issn = {0177-798X},
	abstract = {Urban air temperature is a crucial variable for many urban issues. However, the availability of urban air temperature is often limited due to the deficiency of meteorological stations, especially in urban areas with heterogeneous land cover. Many studies have developed different methods to estimate urban air temperature. However, meteorological variables and local climate zone (LCZ) have been less used in this topic. Our study developed a new method to estimate urban air temperature in canopy layer during clear sky days by integrating land surface temperature (LST) from MODIS, meteorological variables based on reanalysis data, and LCZ data in Szeged, Hungary. Random forest algorithms were used for developing the estimation model. We focused on four seasons and distinguished between daytime and nighttime situations. The cross-validation results showed that our method can effectively estimate urban air temperature, with average daytime and nighttime root mean square error (RMSE) of 0.5 ℃ ( R 2  = 0.99) and 0.9 ℃ ( R 2  = 0.95), respectively. The results based on a test dataset from 2018 to 2019 indicated that the optimal model selected by cross-validation had the best performance in summer, with time-synchronous RMSE of 2.1 ℃ ( R 2  = 0.6, daytime) and 2.2 ℃ ( R 2  = 0.86, nighttime) and seasonal mean RMSE of 1.5 ℃ ( R 2  = 0.34, daytime) and 1.2 ℃ ( R 2  = 0.74, nighttime). In addition, we found that LCZ was more important at night, while meteorological data contributed more to the model during the daytime, which revealed the temporal mechanisms of the effect of these two variables on air temperature estimation. Our study provides a novel and reliable method and tool to explore the urban thermal environment for urban researchers.},
	year = {2024},
	eissn = {1434-4483},
	pages = {3841-3859},
	orcid-numbers = {Unger, János/0000-0002-0637-0091; Gál, Tamás Mátyás/0000-0002-1761-3239}
}

@inbook{MTMT:34524930,
	title = {Hőhullámos és normál nyári időszakok hőkomfort viszonyainak regionális és városi léptékű összehasonlítása},
	url = {https://m2.mtmt.hu/api/publication/34524930},
	author = {Unger, János and Skarbit, Nóra and Gál, Tamás Mátyás},
	booktitle = {Tanulmánykötet Prof. Dr. Mika János születésének 70. évfordulója alkalmából},
	unique-id = {34524930},
	year = {2023},
	pages = {355-368},
	orcid-numbers = {Unger, János/0000-0002-0637-0091; Skarbit, Nóra/0000-0002-6894-4310; Gál, Tamás Mátyás/0000-0002-1761-3239}
}

@mastersthesis{MTMT:34197922,
	title = {A lokális klímazónák városklimatológiai alkalmazása},
	url = {https://m2.mtmt.hu/api/publication/34197922},
	author = {Gál, Tamás Mátyás},
	publisher = {Universití of Szeged},
	unique-id = {34197922},
	year = {2023},
	orcid-numbers = {Gál, Tamás Mátyás/0000-0002-1761-3239}
}

@{MTMT:34163103,
	title = {Potential risks related to heat load, energy demand and water balance based on EURO-CORDEX climate projections in the broader Carpathian region},
	url = {https://m2.mtmt.hu/api/publication/34163103},
	author = {Skarbit, Nóra and Unger, János and Gál, Tamás Mátyás},
	booktitle = {Natural Hazards and Climate Change - conference and workshop for identifying and tackling challenges together},
	unique-id = {34163103},
	year = {2023},
	pages = {45-45},
	orcid-numbers = {Skarbit, Nóra/0000-0002-6894-4310; Unger, János/0000-0002-0637-0091; Gál, Tamás Mátyás/0000-0002-1761-3239}
}

@article{MTMT:33883696,
	title = {Finding the Green Grass in the Haystack? Integrated National Assessment of Ecosystem Services and Condition in Hungary, in Support of Conservation and Planning},
	url = {https://m2.mtmt.hu/api/publication/33883696},
	author = {Tanács, Eszter and Vári, Ágnes and Bede-Fazekas, Ákos and Báldi, András and Csákvári, Edina and Endrédi, Anett and Fabók, Veronika and Kisné Fodor, Lívia and Kiss, Márton and Koncz, Péter and Kovács-Hostyánszki, Anikó and Mészáros, János and Pásztor, László and Rezneki, Rita and Standovár, Tibor and Zsembery, Zita and Török, Katalin},
	doi = {10.3390/su15118489},
	journal-iso = {SUSTAINABILITY-BASEL},
	journal = {SUSTAINABILITY},
	volume = {15},
	unique-id = {33883696},
	abstract = {Human well-being needs healthy ecosystems, providing multiple ecosystem services. Therefore, the assessment of ecosystems on large scales is a priority action. In Hungary, this work (MAES-HU) took place between 2016 and 2022. Twelve ecosystem services (ES) were mapped and assessed along with several ecosystem condition (EC) indicators. Their integrated spatial analysis aimed to identify patterns of ES multifunctionality, reveal relationships between EC and ES and delineate ES bundles. The results show outstanding multifunctionality of natural ecosystem types compared with the more artificial types, emphasizing the importance of natural areas in order to fulfil human needs. Native forests provide the most varied range of services, which underlines the importance of forest management to consider multiple services. There is a positive correlation between condition and multifunctionality in forests; areas in better condition (in terms of species composition and structure) provide more services at an outstanding level. ES bundles mainly reflect the major ecosystem types, topography and forest condition. Our analysis represents an example of synthesizing national MAES results with a combination of methods. Finding ES hotspots on a national scale and connecting them with an assessment of EC may help in finding optimal strategies to balance conservation targets and competing land uses.},
	year = {2023},
	eissn = {2071-1050},
	orcid-numbers = {Tanács, Eszter/0000-0003-1953-9340; Vári, Ágnes/0000-0001-5285-847X; Bede-Fazekas, Ákos/0000-0002-2905-338X; Báldi, András/0000-0001-6063-3721; Kiss, Márton/0000-0002-5621-7976; Mészáros, János/0000-0003-2604-3052; Pásztor, László/0000-0002-1605-4412; Standovár, Tibor/0000-0002-4686-3456}
}