Felhők a Vezúv felett
Credit: Fotó: Mánfai György, 2016

Published

2 Jul 2025

Cloud physics research group

magyar zászló

Research group members:

István Geresdi (leader), Prof., PhD
Noémi Sarkadi, PhD
András Peterka
Máté Kurcsics

Former members:
Gabriella Schmeller, PhD
Jeevan Kumar Bodaballa, PhD
Anikó Cséplő, PhD

Understanding the physical and chemical processes in clouds is essential to reliably predict short-term (weather) and long-term (climate) changes in the atmosphere. With the help of computer models, we investigate a wide range of atmospheric processes (from the formation of water droplets of a few microns to flows of the order of km). Thanks to the developments made in recent years, among other things, we can more accurately simulate the effect of natural and artificial aerosol particles on precipitation formation, and we can also determine how atmospheric pollutants affect the chemical characteristics of water droplets.

We conduct our research in international and domestic cooperation. Our important partner for several decades is the National Center for Atmospheric Research (USA) (https://ncar.ucar.edu/). With them, in recent years we examined how and with what efficiency it is possible to artificially increase the amount of precipitation falling from the clouds in winter and summer climatic conditions. We are working with our domestic partners (National Meteorological Service, the University of Pannonia, and Eötvös University) to increase the efficiency of operational weather forecasting. In the most recently completed tender, we set ourselves the goal of more accurate forecasting of foggy weather situations.

In the past 5 years, three people in the research group obtained Ph.D. degrees.

Research topics

  • Aerosol-cloud-precipitation formation and interactions (physical and chemical processes)

BLK1_aerosol_evolution.mp4 (left) and BLK1_drop_evolution.mp4 (right)

Aerosol (left) and cloud drop (right) size distribution evolution in the case of a less hydrophobic (LH) and a near hygroscopic (NH) aerosol particle.

  • Artificial cloud seeding (effect on precipitation formation on AgI and on salt particles)
    Felhofizika_kep_pp
    Impacts of cloud seeding of the precipitation. (Source: Geresdi, István ; Xue, L.; Sarkadi, Noémi & Rasmussen, R.: Evaluation of orographic cloud seeding using a bin microphysics scheme: Three-dimensional simulation of real cases. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 59: 9 pp. 1537-1555., 19 p. (2020) (Q2))

  • Microphysical and dynamical processes in different clouds (such as in squall lines, orographically enhancing cloud formation, fog, etc.)
    Felhofizika_fog_gif
    Formation of fog in the Carpathian Basin, 2019. 10. 26.
    Felhofizika_gif_squall3d
    3D simulation of mixing ratios of hydrometeors in a case of a squall line, 2011. 05. 20.

Felhofizika_kep_t-all-stations
The long-term predicted temperature anomaly by seasons at different meteorological stations by the end of 1961-2020. The symbols above each column denote the significant levels evaluated by z-probe. The data from different surface stations are depicted by columns with different colors.

Felhofizika_budapest
The anomalies of the temperature values in the time period of 1961-2020 compared to the reference period 1961-1990 for different seasons at Budapest station. T ref means the average value corresponding to the reference period.

Tenders

  • UAE-NATURE: Using Advanced Experimental - Numerical Approaches To Untangle Rain Enhancement
  • GINOP-2.3.2-15-2016-00055
  • OTKA (116025)

Selected publications (2021/2022)

  1. Sarkadi, Noémi ; Xue, Lulin ✉; Grabowski, Wojciech W.; Lebo, Zachary J.; Morrison, Hugh; White, Bethan; Fan, Jiwen; Dudhia, Jimy & Geresdi, István: Microphysical piggybacking in the Weather Research and Forecasting Model. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 14: 8 Paper: e2021MS002890, 25 p. (2022) (Q1/D1)
  2. Schmeller, Gabriella; Nagy, Gábor; Sarkadi, Noémi ; Cséplő, Anikó; Pirkhoffer, Ervin; Geresdi, István; Balogh, Richárd; Ronczyk, Levente & Czigány, Szabolcs: Trends in extreme precipitation events (SW Hungary) based on a high-density monitoring network. HUNGARIAN GEOGRAPHICAL BULLETIN, (2009-) 71: 3 pp. 231-247., 17 p. (2022) (Q2)
  3. Cséplő, Anikó ✉; Izsák, Beatrix & Geresdi, István: Long-term trend of surface relative humidity in Hungary. THEORETICAL AND APPLIED CLIMATOLOGY, 149: 3-4 pp. 1629-1643., 15 p. (2022) (Q2)
  4. Jeevan Kumar, Bodaballa ; Geresdi, István; Ghude, Sachin D. & Salma, Imre: Numerical simulation of the microphysics and liquid chemical processes occur in fog using size resolving bin scheme. ATMOSPHERIC RESEARCH, 266 Paper: 105972, 14 p. (2022) (Q1)
  5. Geresdi, Istvan; Xue, Lulin ✉; Chen, Sisi; Wehbe, Youssef; Bruintjes, Roelof; Lee, Jared A.; Rasmussen, Roy M.; Grabowski, Wojciech W.; Sarkadi, Noémi & Tessendorf, Sarah A.: Impact of hygroscopic seeding on the initiation of precipitation formation: results of a hybrid bin microphysics parcel model. ATMOSPHERIC CHEMISTRY AND PHYSICS, 21: 21 pp. 16143-16159., 17 p. (2021) (Q1/D1)

Modeling and observing secondary ice production

Clouds and precipitation are important elements of the climate system. They affect our daily weather and, in the longer term, the climate. Understanding how ice forms in clouds is key to accurate weather forecasting and climate modeling. Ice particles play an important role in the formation of surface precipitation and also affect the propagation of radiation from the Sun and the Earth.

Ice formation in clouds occurs over a wide temperature range (0°C to -40°C) during primary and secondary ice formation. In the majority of clouds, primary ice formation (PIP) is generated by ice-forming aerosol particles (INP) through heterogeneous nucleation. Observations show that the concentration of ice crystals often exceeds the concentration of available active ice nuclei. This suggests that ice crystals can be generated by secondary processes (SIP). In contrast to PIP, the range of possible processes for SIP is not yet fully understood. Although many review articles mention the potentially important role of SIP in precipitation formation, relatively little theoretical work has been done on the subject so far. Models used for research and operational forecasting purposes either do not take this process into account or use a parameterized formula that has been shown in recent years by laboratory measurements to be based on questionable assumptions.

Példák másodlagos jégképződési folyamatokra (SIP): a) vízcseppek széttöredezése fagyás során, b) zúzmarás szilánkosodás (Hallett-Mossop hatás), c) jég-jég ütközések okozta töredezés és d) jégkristályok szublimációja miatti széttöredezés. A kék színek a jé
Figure 1. “A conceptual diagram summarizing four secondary ice production (hereafter SIP) mechanisms: a) fragmentation droplets during freezing, b) rime splintering (so-called Hallett–Mossop process), c) fragmentation of ice particles due to ice–ice collision, d) fragmentation of ice particles due to sublimation. Blue color refers to ice phase and red color to liquid phase.” (based on Kolorev et al., 2020; Figure 16).

Measuring the impact of secondary ice formation is complicated by several factors. For aircraft measurements, it is not easy to identify the processes that contribute to the growth of ice crystals, and for laboratory measurements it is impossible to reproduce the dynamic and microphysical environment of clouds. In this research, we mainly use numerical simulations to investigate the impact of SIP. The aim is to identify the dominant SIP mechanisms and estimate their effects under different environmental conditions, such as cloud type, temperature, liquid water content, primary ice formation, and different INP concentrations. In an international collaboration, laboratory experiments are planned to clarify how snow sublimation and snow-snow collisions affect secondary ice crystal formation.

In the first part of the project, we will further develop an existing microphysical scheme (University of Pecs and NCAR bin scheme), which is used for a variety of purposes, to model a wide range of processes leading to secondary ice formation. Sensitivity tests will be performed to determine which SIP may be dominant depending on the dynamic, thermodynamic, and microphysical characteristics of the cloud.

In a collaboration with Johannes Gutenberg University Mainz, we will investigate how fragmentation due to snow sublimation and snowflake-snowflake collisions affect secondary ice formation. Currently, only a qualitative description of these processes exists. Using laboratory measurements, we aim to quantify how environmental conditions affect secondary ice crystal formation. This quantification will allow the incorporation of the process into the numerical model. In addition, we intend to perform case studies by modeling clouds that have been intensively observed by aircraft measurements.

Compared to existing research, this project is a unique combination of numerical modeling and state-of-the-art laboratory observations:(i) it brings together experts in numerical modeling, data analysis and experimental physics, facilitating a broad investigation of SIP; (ii) we use a 3D model to investigate the interaction between the dynamical and microphysical properties of clouds and SIP processes;(iii) our collaboration with the University of Mainz will allow the study of a secondary ice formation process for which few results have been obtained so far; (iv) the integration of laboratory data and the application of real-world observations will ensure that our descriptions are based on real physical processes.

The complex methodology of this project is relatively rarely applied in the field of cloud science. Few research initiatives, both domestically and abroad, offer such a synergistic combination of modeling and experimental work. The aim of this research is to better understand how secondary ice formation affects precipitation processes and how it influences cloud lifetimes and optical properties.

Reference:

Kolorev, A. and Leisner, T., 2020: Review of experimental studies of secondary ice production. Atmospheric Chemistry and Physics, 20, pp. 11767–11797. https://doi.org/10.5194/acp-20-11767-2020