@article{MTMT:34789229,
	title = {Inter-Comparison of Precipitation Simulation and Future Projections Over China From an Ensemble of Multi-GCM Driven RCM Simulations},
	url = {https://m2.mtmt.hu/api/publication/34789229},
	author = {Tong, Y. and Gao, X. and Xu, Y. and Cui, X. and Giorgi, F.},
	doi = {10.1029/2023JD040166},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34789229},
	issn = {2169-897X},
	year = {2024},
	eissn = {2169-8996}
}

@article{MTMT:34773804,
	title = {Deterministic Forecasting and Probabilistic Post‐Processing of Short‐Term Wind Speed Using Statistical Methods},
	url = {https://m2.mtmt.hu/api/publication/34773804},
	author = {Sun, Lei and Lan, Yufeng and Sun, Xian and Liang, Xiuji and Wang, Jing and Su, Yekang and He, Yunping and Xia, Dong},
	doi = {10.1029/2023JD040134},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34773804},
	issn = {2169-897X},
	abstract = {There is a great need for an accurate short‐term wind speed forecast, and statistical forecasts have gained increased popularity for their computational efficiency and satisfactory skill. However, there has been no systematic research to fully explore the capabilities of statistical approaches and evaluate the applicability of probabilistic information from statistical ensemble. This study first compares the skills of different statistical methods, based on linear regression, machine learning (ML), and deep learning (DL), using three strategies (i.e., direct, recursive, and multi‐output) against the three operational numerical models and their bias‐corrections, for short‐term wind speed forecast over Pearl River Estuary during 2018–2021. Inter‐comparison between statistical forecasts reveals the dominant superiority of direct strategy. On this basis, Random Forest (RF) and Support Vector Machines (SVM) perform best compared to other statistical forecasts and bias correction of numerical forecasts throughout 48 hr lead time, while the performance of methods with simplified (linear) or more complex (DL) model structures degrades significantly. Moreover, the top 10 forecasts are utilized to account for forecast uncertainties but present a substantial under‐dispersed prediction. Two traditional methods and three modern methods are implemented to perform probabilistic post‐processing. Modern methods based on ML or DL present worse skills, while traditional methods, particularly for ensemble model output statistics, show added value in discriminating binary events due to limited enhancements in calibration. Overall, RF and SVM using direct strategy are highly recommended for short‐term wind speed forecasts, and efforts are ongoing to address the issues of strong wind prediction and ensemble calibration.},
	year = {2024},
	eissn = {2169-8996},
	orcid-numbers = {Sun, Lei/0000-0003-0328-2042; Xia, Dong/0000-0001-6958-2385}
}

@article{MTMT:34734172,
	title = {Effects of Pollen on Hydrometeors and Precipitation in a Convective System},
	url = {https://m2.mtmt.hu/api/publication/34734172},
	author = {Zhang, Yingxiao and Subba, Tamanna and Matthews, Brianna H. and Pettersen, Claire and Brooks, Sarah D. and Steiner, Allison L.},
	doi = {10.1029/2023JD039891},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34734172},
	issn = {2169-897X},
	abstract = {Anemophilous (wind‐driven) pollen is one type of primary biological aerosol particle, which can rupture under high humidity conditions and form smaller sub‐pollen particles (SPPs). Both pollen and SPPs can reach the upper troposphere under convective conditions, acting as cloud condensation nuclei (CCN) and ice nucleating particles (INPs), thus influencing cloud formation and precipitation. However, the impacts of these biological aerosols on cold cloud formation and local climate remain unclear as there are large uncertainties on their emission flux and ice nucleating abilities. Here, we incorporate pollen emission and rupture processes in the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) simulations and update the Morrison microphysics scheme within WRF‐Chem using aerosol‐aware INP parameterizations to account for pollen in addition to other anthropogenic and biogenic aerosol. INP parameterizations for pollen and SPP are derived from laboratory experiments. When including pollen rupture rates as observed in a series of chamber studies, SPP concentrations increase, leading to an increase of cloud ice and water by up to 50% and potentially extending the duration of the convective system. Among all simulated hydrometeors, graupel and raindrops exhibit the largest enhancements from the inclusion of SPPs, with intensifying precipitation at the backside of the convective system and a greater spatial extent. Sensitivity simulations indicate that SPPs have a greater effect on cloud microphysical processes than whole pollen grains, and further observational evidence is needed to constrain these processes.},
	year = {2024},
	eissn = {2169-8996},
	pages = {1-24},
	orcid-numbers = {Zhang, Yingxiao/0000-0003-4127-0974; Subba, Tamanna/0000-0002-0319-9751; Pettersen, Claire/0000-0002-8685-6242; Brooks, Sarah D./0000-0001-8185-9332; Steiner, Allison L./0000-0002-3823-1512}
}

@article{MTMT:34770135,
	title = {Modeling Natural Tritium in Precipitation and its Dependence on Decadal Solar Activity Variations Using the Atmospheric General Circulation Model MIROC5‐Iso},
	url = {https://m2.mtmt.hu/api/publication/34770135},
	author = {Cauquoin, A. and Fourré, É. and Landais, A. and Okazaki, A. and Yoshimura, K.},
	doi = {10.1029/2023JD039745},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34770135},
	issn = {2169-897X},
	abstract = {Modeling tritium content in water presents a meaningful way to evaluate the representation of the water cycle in climate models as it traces fluxes within and between the reservoirs involved in the water cycle (stratosphere, troposphere, and ocean). In this study, we present the implementation of natural tritium in water in the atmospheric general circulation model (AGCM) MIROC5‐iso and its simulation for the period 1979–2018. Owing to recently published tritium production calculations, we were able to investigate, for the first time, the influence of natural tritium production related to the 11‐yr solar cycle on tritium in precipitation. MIROC5‐iso correctly simulates continental, latitudinal, and altitude effects on tritium in precipitation. The seasonal tritium content peaks, linked to stratosphere‐troposphere exchanges, are accurately simulated in terms of timing, even though MIROC5‐iso underestimates the amplitude of the changes. Decadal tritium concentration variations in precipitation owing to the 11‐yr solar cycle are well simulated in MIROC5‐iso, in agreement with the observations at Vostok in Antarctica for example, Finally, our simulations revealed that the internal climate variability plays an important role in tritium in polar precipitation. Owing to its influence on the south polar vortex, the Southern Annular Mode enhances the effect of the production component on tritium in East Antarctic precipitation. In Greenland, we found an east‐west contrast in the detection of the 11‐yr solar cycle in tritium in precipitation owing to the influence of the North Atlantic Oscillation on humidity conditions.},
	year = {2024},
	eissn = {2169-8996},
	orcid-numbers = {Cauquoin, A./0000-0002-4620-4696; Fourré, É./0000-0002-2554-9660; Okazaki, A./0000-0002-4598-0589; Yoshimura, K./0000-0002-5761-1561}
}

@article{MTMT:34751434,
	title = {Comment on “Comparison of the Efficiencies of the Prognostic Generalized Complementary Functions on Evaporation Estimation” by Wang, L., et al., Published in Journal of Geophysical Research: Atmospheres},
	url = {https://m2.mtmt.hu/api/publication/34751434},
	author = {Szilágyi, József},
	doi = {10.1029/2023JD040070},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34751434},
	issn = {2169-897X},
	abstract = {Surprising significant underperformance of the polynomial complementary relationship (PCR) of evaporation (Szilagyi et al., 2017, https://doi.org/10.1002/2016jd025611) by Wang et al. (2023, https://doi.org/10.1029/2023jd038683) is caused by the (a) station-by-station application of a grid-based estimation procedure of the Priestley-Taylor parameter (α) value, and (b) choice of the wind function. Application of the Rome wind function in the Penman equation together with either a well-chosen single (constant) α or α as a function of the wet-environment air temperature, should result in much improved evaporation estimates by the PCR in line with previous studies. © 2024. American Geophysical Union. All Rights Reserved.},
	year = {2024},
	eissn = {2169-8996},
	orcid-numbers = {Szilágyi, József/0000-0003-4449-0470}
}

@article{MTMT:34674217,
	title = {New Method for Determining Azimuths of ELF Signals Associated With the Global Thunderstorm Activity and the Hunga Tonga Volcano Eruption},
	url = {https://m2.mtmt.hu/api/publication/34674217},
	author = {Kubisz, J. and Golkowski, M. and Mlynarczyk, J. and Ostrowski, M. and Michalec, A.},
	doi = {10.1029/2023JD040318},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34674217},
	issn = {2169-897X},
	keywords = {SCHUMANN RESONANCES; ELF electromagnetic waves; ELF impulses; ELF wave azimuth of arrival},
	year = {2024},
	eissn = {2169-8996}
}

@article{MTMT:34673491,
	title = {Limited Evidence for a Microbial Signal in Ground-Level Smoke Plumes},
	url = {https://m2.mtmt.hu/api/publication/34673491},
	author = {Gering, Sarah M. and Sullivan, Amy P. and Kreidenweis, Sonia M. and Mcmurray, Jill A. and Fierer, Noah},
	doi = {10.1029/2023JD039416},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34673491},
	issn = {2169-897X},
	keywords = {smoke; Microbes; wildfire; pyroaerobiology},
	year = {2024},
	eissn = {2169-8996}
}

@article{MTMT:34653145,
	title = {Physical Properties, Chemical Components, and Transport Mechanisms of Atmospheric Aerosols Over a Remote Area on the South Slope of the Tibetan Plateau},
	url = {https://m2.mtmt.hu/api/publication/34653145},
	author = {Yu, Zeren and Tian, Pengfei and Kang, Chenliang and Song, Xin and Huang, Jianping and Guo, Yumin and Shi, Jinsen and Tang, Chenguang and Zhang, Haotian and Zhang, Zhida and Cao, Xianjie and Liang, Jiening and Zhang, Lei},
	doi = {10.1029/2023JD040193},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34653145},
	issn = {2169-897X},
	keywords = {PHYSICOCHEMICAL PROPERTIES; ATMOSPHERIC AEROSOLS; in situ observations; Himalayas-South Asia regional mountain-valley winds; local mountain-valley winds},
	year = {2024},
	eissn = {2169-8996}
}

@article{MTMT:34626634,
	title = {Development of Interpretable Probability Ellipse in Tropical Cyclone Track Forecasts Using Multiple Operational Ensemble Prediction Systems},
	url = {https://m2.mtmt.hu/api/publication/34626634},
	author = {Yoo, Seungwoo and Ho, Chang-Hoi},
	doi = {10.1029/2023JD039295},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34626634},
	issn = {2169-897X},
	keywords = {ensemble prediction; Forecast uncertainty; Tropical cyclone; track forecast; probability ellipse},
	year = {2024},
	eissn = {2169-8996}
}

@article{MTMT:34672809,
	title = {One-Minute Resolution GOES-R Observations of Lamb and Gravity Waves Triggered by the Hunga Tonga-Hunga Ha'apai Eruptions on 15 January 2022},
	url = {https://m2.mtmt.hu/api/publication/34672809},
	author = {Horvath, Akos and Vadas, Sharon L. and Stephan, Claudia C. and Buehler, Stefan A.},
	doi = {10.1029/2023JD039329},
	journal-iso = {J GEOPHYS RES ATMOS},
	journal = {JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES},
	volume = {129},
	unique-id = {34672809},
	issn = {2169-897X},
	keywords = {gravity waves; GOES-R; Lamb waves; Tonga eruption; mesoscale imagery},
	year = {2024},
	eissn = {2169-8996}
}