@article{MTMT:34472868,
	title = {Seamlessly combined historical and projected daily meteorological datasets for impact studies in Central Europe: The FORESEE v4.0 and the FORESEE-HUN v1.0},
	url = {https://m2.mtmt.hu/api/publication/34472868},
	author = {Kern, Anikó and Dobor, Laura and Hollós, Roland and Marjanović, Hrvoje and Torma, Csaba and Kis, Anna and Fodor, Nándor and Barcza, Zoltán},
	doi = {10.1016/j.cliser.2023.100443},
	journal-iso = {CLIM SERV},
	journal = {CLIMATE SERVICES},
	volume = {33},
	unique-id = {34472868},
	issn = {2405-8807},
	year = {2024},
	eissn = {2405-8807},
	orcid-numbers = {Kern, Anikó/0000-0002-3504-1668; Torma, Csaba/0000-0002-4240-0788; Kis, Anna/0000-0002-3227-1230; Barcza, Zoltán/0000-0002-1278-0636}
}

@{MTMT:34397478,
	title = {A mezőgazdaság jövője az AGROMO modellrendszer eredményei alapján},
	url = {https://m2.mtmt.hu/api/publication/34397478},
	author = {Fodor, Nándor and Barcza, Zoltán and Hollós, Roland and Bónis, Péter and Sugár, Eszter and Árendás, Tamás},
	booktitle = {Növény és környezet: a debreceni tartamkísérletek 40 éve},
	unique-id = {34397478},
	year = {2023},
	pages = {17-18}
}

@article{MTMT:34231901,
	title = {Sensitivity of simulated soil water content, evapotranspiration, gross primary production and biomass to climate change factors in Euro-Mediterranean grasslands},
	url = {https://m2.mtmt.hu/api/publication/34231901},
	author = {Bellocchi, G. and Barcza, Zoltán and Hollós, Roland and Acutis, M. and Vidnyánszky-Bottyán, Emese and Doro, L. and Hidy, Dóra and Lelleiné Kovács, Eszter and Ma, S. and Minet, J. and Pacskó, Vivien and Perego, A. and Ruget, F. and Seddaiu, G. and Wu, L. and Sándor, Renáta},
	doi = {10.1016/j.agrformet.2023.109778},
	journal-iso = {AGR FOREST METEOROL},
	journal = {AGRICULTURAL AND FOREST METEOROLOGY},
	volume = {343},
	unique-id = {34231901},
	issn = {0168-1923},
	year = {2023},
	eissn = {1873-2240},
	orcid-numbers = {Barcza, Zoltán/0000-0002-1278-0636; Acutis, M./0000-0002-1576-8261; Doro, L./0000-0003-1404-2255; Ma, S./0000-0002-3357-4647; Pacskó, Vivien/0000-0003-4673-6833; Wu, L./0000-0003-0221-9009}
}

@article{MTMT:34087599,
	title = {Fedlabx: a practical and privacy-preserving framework for federated learning},
	url = {https://m2.mtmt.hu/api/publication/34087599},
	author = {Yan, Yuping and Albujeer, Mohammed B. M. Kamel and Zoltay, Marcell and Gál, Marcell and Hollós, Roland and Jin, Yaochu and Ligeti, Péter and Tényi, Ákos},
	doi = {10.1007/s40747-023-01184-3},
	journal-iso = {COMPLEX INTELL SYST},
	journal = {COMPLEX & INTELLIGENT SYSTEMS},
	volume = {10},
	unique-id = {34087599},
	issn = {2199-4536},
	abstract = {Federated learning (FL) draws attention in academia and industry due to its privacy-preserving capability in training machine learning models. However, there are still some critical security attacks and vulnerabilities, including gradients leakage and interference attacks. Meanwhile, communication is another bottleneck in basic FL schemes since large-scale FL parameter transmission leads to inefficient communication, latency, and slower learning processes. To overcome these shortcomings, different communication efficiency strategies and privacy-preserving cryptographic techniques have been proposed. However, a single method can only partially resist privacy attacks. This paper presents a practical, privacy-preserving scheme combining cryptographic techniques and communication networking solutions. We implement Kafka for message distribution, the Diffie–Hellman scheme for secure server aggregation, and gradient differential privacy for interference attack prevention. The proposed approach maintains training efficiency while being able to addressing gradients leakage problems and interference attacks. Meanwhile, the implementation of Kafka and Zookeeper provides asynchronous communication and anonymous authenticated computation with role-based access controls. Finally, we prove the privacy-preserving properties of the proposed solution via security analysis and empirically demonstrate its efficiency and practicality.},
	year = {2023},
	eissn = {2198-6053},
	pages = {677-690},
	orcid-numbers = {Jin, Yaochu/0000-0003-1100-0631; Ligeti, Péter/0000-0002-3998-0515}
}

@article{MTMT:33989177,
	title = {Quantifying uncertainties related to observational datasets used as reference for regional climate model evaluation over complex topography — a case study for the wettest year 2010 in the Carpathian region},
	url = {https://m2.mtmt.hu/api/publication/33989177},
	author = {Kalmár, Tímea and Kristóf, Erzsébet and Hollós, Roland and Pieczka, Ildikó and Pongrácz, Rita},
	doi = {10.1007/s00704-023-04491-4},
	journal-iso = {THEORET APPL CLIMAT},
	journal = {THEORETICAL AND APPLIED CLIMATOLOGY},
	volume = {153},
	unique-id = {33989177},
	issn = {0177-798X},
	abstract = {Gridded observational datasets are often used for the evaluation of regional climate model (RCM) simulations. However, the uncertainty of observations affects the evaluation. This work introduces a novel method to quantify the uncertainties in the observational datasets and how these uncertainties affect the evaluation of RCM simulations. Besides precipitation and temperature, our method uses geographic variables (e.g. elevation, variability of elevation, effect of station), which are considered as uncertainty sources. To assess these uncertainties, a complex analysis based on various statistical tools, e.g. correlation analysis and permutation test, was carried out. Furthermore, we used a special metric, the reduction of error ( RE ) to identify where the RCM shows improvement compared to the lateral boundary conditions (LBCs). We focused on the Carpathian region, because of its unique orographic and climatic conditions. The method is applied to two observational datasets (CarpatClim and E-OBS) and to RegCM simulations for 2010, the wettest year in this region since 1901.},
	year = {2023},
	eissn = {1434-4483},
	pages = {807-828},
	orcid-numbers = {Kalmár, Tímea/0000-0003-0405-4404; Kristóf, Erzsébet/0000-0001-9892-9552; Pieczka, Ildikó/0000-0001-5657-9494; Pongrácz, Rita/0000-0001-7591-7989}
}

@article{MTMT:33331257,
	title = {A kukorica jövőbeli sorsa},
	url = {https://m2.mtmt.hu/api/publication/33331257},
	author = {Fodor, Nándor and Árendás, Tamás and Bónis, Péter and Sugár, Eszter and Hollós, Roland},
	journal-iso = {AGROFÓRUM EXTRA},
	journal = {AGROFÓRUM EXTRA},
	volume = {33},
	unique-id = {33331257},
	issn = {1788-7380},
	year = {2022},
	pages = {32-38}
}

@article{MTMT:33239320,
	title = {Critical Climate Periods Explain a Large Fraction of the Observed Variability in Vegetation State},
	url = {https://m2.mtmt.hu/api/publication/33239320},
	author = {Kern, Anikó and Barcza, Zoltán and Hollós, Roland and Birinyi, Edina and Marjanović, Hrvoje},
	doi = {10.3390/rs14215621},
	journal-iso = {REMOTE SENS-BASEL},
	journal = {REMOTE SENSING},
	volume = {14},
	unique-id = {33239320},
	abstract = {Previous studies have suggested that a major part of the observed variability in vegetation state might be associated with variability in climatic drivers during relatively short periods within the year. Identification of such critical climate periods, when a particular climate variable most likely has a pronounced influence on the vegetation state of a particular ecosystem, becomes increasingly important in the light of climate change. In this study, we present a method to identify critical climate periods for eight different semi-natural ecosystem categories in Hungary, in Central Europe. The analysis was based on the moving-window correlation between MODIS NDVI/LAI and six climate variables with different time lags during the period 2000–2020. Distinct differences between the important climate variables, critical period lengths, and direction (positive or negative correlations) have been found for different ecosystem categories. Multiple linear models for NDVI and LAI were constructed to quantify the multivariate influence of the environmental conditions on the vegetation state during the late summer. For grasslands, the best models for NDVI explained 65–87% variance, while for broad-leaved forests, the highest explained variance for LAI was up to 50%. The proposed method can be easily implemented in other geographical locations and can provide essential insight into the functioning of different ecosystem types.},
	year = {2022},
	eissn = {2072-4292},
	orcid-numbers = {Kern, Anikó/0000-0002-3504-1668; Barcza, Zoltán/0000-0002-1278-0636; Marjanović, Hrvoje/0000-0001-5701-7581}
}

@article{MTMT:33157280,
	title = {Conditional interval reduction method: A possible new direction for the optimization of process based models},
	url = {https://m2.mtmt.hu/api/publication/33157280},
	author = {Hollós, Roland and Fodor, Nándor and Merganičová, K. and Hidy, D. and Árendás, Tamás and Grünwald, T. and Barcza, Zoltán},
	doi = {10.1016/j.envsoft.2022.105556},
	journal-iso = {ENVIRON MODELL SOFTW},
	journal = {ENVIRONMENTAL MODELLING & SOFTWARE},
	volume = {158},
	unique-id = {33157280},
	issn = {1364-8152},
	year = {2022},
	eissn = {1873-6726},
	orcid-numbers = {Fodor, Nándor/0000-0002-6460-1767; Barcza, Zoltán/0000-0002-1278-0636}
}

@CONFERENCE{MTMT:33107531,
	title = {Climate data for 1951–2100 for scientific, societal and policy purposes in Central Europe: the FORESEE database},
	url = {https://m2.mtmt.hu/api/publication/33107531},
	author = {Kern, Anikó and Dobor, Laura and Hollós, Roland and Marjanović, H. and Torma, Csaba and Kis, Anna and Fodor, N. and Barcza, Zoltán},
	booktitle = {Book of abstracts: Natural resources, green technology and sustainable development},
	unique-id = {33107531},
	year = {2022},
	pages = {32},
	orcid-numbers = {Kern, Anikó/0000-0002-3504-1668; Dobor, Laura/0000-0001-6712-9827; Torma, Csaba/0000-0002-4240-0788; Kis, Anna/0000-0002-3227-1230; Barcza, Zoltán/0000-0002-1278-0636}
}

@article{MTMT:32784533,
	title = {Real-world wintertime CO, N2O and CO2 emissions of a Central European village},
	url = {https://m2.mtmt.hu/api/publication/32784533},
	author = {Haszpra, László and Barcza, Zoltán and Pappné Ferenczi, Zita and Kern, Anikó and Hollós, Roland and Kljun, N},
	doi = {10.5194/amt-15-5019-2022},
	journal-iso = {ATMOS MEAS TECH},
	journal = {ATMOSPHERIC MEASUREMENT TECHNIQUES},
	volume = {15},
	unique-id = {32784533},
	issn = {1867-1381},
	abstract = {Abstract. Although small rural settlements are only minor individual sources of greenhouse gases and air pollution, their high overalloccurrence can significantly contribute to the total emissions of a regionor country. Emissions from a rural lifestyle may be remarkably differentthan those of urban and industrialized regions, but nevertheless they havehardly been studied so far. Here, flux measurements at a tall-tower eddycovariance monitoring site and the footprint model FFP are used to determine the real-world wintertime CO, N2O, and CO2 emissions of a small village in western Hungary. The recorded emission densities, dominantly resulting from residential heating, are 3.5,0.043, and 72 µg m−2 s−1 for CO, N2O, and CO2, respectively. While the measured CO and CO2emissions are comparable to those calculated using the assumed energyconsumption and applying the according emission factors, the nitrous oxideemissions exceed the expected value by a magnitude. This may indicate thatthe nitrous oxide emissions are significantly underestimated in the emissioninventories, and modifications in the methodology of emission calculationsare necessary. Using a three-dimensional forward transport model, we furthershow that, in contrast to the flux measurements, the concentrationmeasurements at the regional background monitoring site are onlyinsignificantly influenced by the emissions of the nearby village.},
	year = {2022},
	eissn = {1867-8548},
	pages = {5019-5031},
	orcid-numbers = {Haszpra, László/0000-0002-7747-6475; Barcza, Zoltán/0000-0002-1278-0636; Kern, Anikó/0000-0002-3504-1668}
}