جست‌وجوی استاد و پژوهشگر

Tapio Schneiderمشاهده پروفایل

استاد

• Atmospheric Dynamics
• Climate Modeling
• Geophysical Turbulence
• +۴ مورد دیگر

Tapio Schneider is the Theodore Y. Wu Professor of Environmental Science and Engineering at the California Institute of Technology. His research focuses on atmospheric dynamics across Earth and other planets, climate modeling innovations, and geophysical turbulence analysis. He contributes to the Climate Modeling Alliance (CliMA) and develops advanced computational tools for climate prediction. Albert-Ludwigs-Universität Freiburg (Vordiplom, 1993) Princeton University (M.Sc. 1997, Ph.D. 2001) University of Washington, Seattle (Visiting Graduate Student, 1994-1995) His research spans climate dynamics , atmospheric turbulence , and AI-enhanced climate modeling , addressing challenges in cloud dynamics, extreme weather patterns, and planetary climate systems. Current work emphasizes hybrid machine learning-physical models and computational acceleration for high-resolution simulations. Recent publications highlight trends in AI integration for climate science, with applications in hydrology , cloud microphysics , ocean circulation , snowpack modeling , and climate tipping points . His team develops open-source tools like ClimateMachine for GPU-accelerated simulations. Scientific Recognition: Fellow, American Geophysical Union (2022) Rosenstiel Award (2019) World Economic Forum Young Scientist (2012) David and Lucile Packard Fellow (2005-2010) Alfred P. Sloan Research Fellow (2004-2006) Tapio leads climate dynamics research at Caltech, directs the Linde Center for Global Environmental Science (2011-2012), and serves as Editor for the Journal of Advances in Modeling Earth Systems . His group collaborates with NASA Jet Propulsion Laboratory (2016-2024) and Google Research (2022-present).

Sebastian Schemmمشاهده پروفایل

دانشیار

• Atmospheric Sciences
• Extratropical Cyclone Dynamics
• Jet Stream Physics
• +۷ مورد دیگر

Sebastian Schemm is a Heisenberg Fellow at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge, a position regarded as equivalent to a non-permanent Associate Professor. He leads research within the Atmosphere-Ocean Dynamics group and previously held an ERC Starting Grant-funded Assistant Professorship (without tenure track) at ETH Zurich. Education and Career Path PhD (2013) and MSc (2010), ETH Zurich, Switzerland Postdoctoral researcher, University of Bergen, Norway (2014–2017) Postdoctoral researcher, Laboratoire de Météorologie Dynamique, ENS Paris (2017–2018) Assistant Professor (ERC Starting Grant), ETH Zurich (2020–2024) Heisenberg Fellow, DAMTP, University of Cambridge (2025–present) Research Focus Schemm’s work centres on atmospheric and climate dynamics, spanning turbulence to planetary scales. Core themes include the physics of extratropical cyclone life cycles, jet-stream and storm-track dynamics, Rossby waves and teleconnection patterns, high-resolution atmospheric modelling, and the integration of machine-learning techniques for parameter estimation, data assimilation, and kilometre-scale global simulations. He also contributes to large-scale initiatives such as ECMWF’s WeatherGenerator. Scientific Awards and Editorial Service DFG Heisenberg Fellowship (2025) ERC Starting Grant (2020–2024) European Meteorological Society Young Researcher Medal (2019) Co-Editor, Weather and Climate Dynamics (EGU) Co-Editor, Quarterly Journal of the Royal Meteorological Society PhD Supervision & Funding He currently supervises PhD students at both Cambridge and ETH Zurich, with funding streams including the Cambridge CREATES Doctoral Training Partnership and Swiss/EU grants. Ongoing students explore reinforcement-learning parameterisations, jet-stream–storm-track relationships, mid-latitude eddy energetics, machine-learning ensemble forecasting, and Bayesian parameter estimation in LES. Active Projects EU Horizon project WeatherGenerator (led by ECMWF) PASC HiRAD-Gen : High-Resolution Atmospheric Downscaling Using Generative Models

Annette Rudolphمشاهده پروفایل

استادیار

• Artificial Intelligence and Applications in Environmental and Geosciences
• Clouds and Climate
• Theoretical Meteorology
• +۳ مورد دیگر

Jun.-Prof. Dr. Annette Rudolph is an Assistant Professor leading the AI and (Climate-Induced) Land Use Change research group at TU Berlin's Institute of Landscape Architecture and Environmental Planning. She holds a Diplom in Mathematics (TU Berlin, 2011) and a PhD in Meteorology (FU Berlin, 2018), with a habilitation thesis on geophysical fluid dynamics and data-driven methods (2023). Her research integrates AI, climate science, and geophysical fluid dynamics. Academic Roles: Head of FG KI und Landnutzungswandel (since 2023), Postdoc in SFB 1114 (2014–2022) Research interests focus on AI applications in environmental sciences, clouds-climate interactions, and fluid dynamics. Her work bridges theoretical meteorology with data science, including machine learning for precipitation modeling and climate analysis. Publications emphasize AI-driven climate modeling, geostatistical methods, and atmospheric dynamics. Notable contributions include a 2024 paper on deep learning for precipitation nowcasting and a 2023 study on CAPE-precipitation relationships using machine learning. She developed e-learning resources on geodata analysis using Python and R, and led DAAD-funded research in Oslo (2022). Current projects involve AI-driven land-use change analysis and climate impact modeling.

Tom Beuclerمشاهده پروفایل

استادیار

• Geo-Environmental Data Science
• Climate Informatics
• Atmospheric Physics
• +۵ مورد دیگر

Tom Beucler is a Conditional Pre-Tenure Assistant Professor in Geo-Environmental Data Science at the University of Lausanne’s Institute for Earth Surface Dynamics (IDYST). He holds a Master’s degree in Science and Mechanics from École Polytechnique (2014) and a PhD in Atmospheric Science from MIT (2019). Postdoctoral research at Columbia University and UC Irvine focused on machine learning applications in climate science under Professors Pierre Gentine and Michael Pritchard. Research Interests: Climate informatics, atmospheric physics, fluid dynamics, tropical meteorology, and integrating machine learning into climate models for extreme weather prediction and hydrological cycle modeling. Collaborations: Works with environmental scientists and computer engineers to improve climate models using neural networks and causal discovery methods. Initiatives: Organizes weekly brainstorming sessions to promote machine learning adoption in environmental sciences. Publications span climate-invariant machine learning, data-driven parameterizations, and hybrid AI-climate modeling frameworks like ClimSim. His work emphasizes causal consistency and generalizability across climate conditions.

Kristen L. Rasmussenمشاهده پروفایل

دانشیار

• Convective Storms
• Cloud-Climate Interactions
• Mesoscale Meteorology
• +۶ مورد دیگر

Kristen L. Rasmussen is an Associate Professor in the Department of Atmospheric Science at Colorado State University (CSU), affiliated with the Walter Scott, Jr. College of Engineering. She holds a Ph.D. (2014) and M.S. (2011) in Atmospheric Sciences from the University of Washington, and dual B.S. (Meteorology and Mathematics) and B.A. (Music) from the University of Miami (2007). Before joining CSU in 2016, she was an Advanced Study Program Postdoctoral Fellow at NCAR (2015–2016). Her research focuses on convective storms, cloud-climate interactions, mesoscale meteorology, and hydrometeorology. Key interests include analyzing extreme rainfall, tropical convective systems, and the impacts of climate change on storm dynamics. She leads the Rasmussen Group, which investigates topics like the NASA INCUS satellite mission, subtropical storms in South America, and climate modeling. Received awards such as the 2015 AMS Mesoscale Processes Conference Very Early Career Award and the 2011 NASA Earth System Science Graduate Fellowship. Active in field campaigns like RELAMPAGO in Argentina and PRECIP in Taiwan/Japan. Teaches courses on synoptic and mesoscale meteorology, hydrometeorology, and mountain meteorology. Her group includes researchers and students studying topics ranging from convective storm environments to stratospheric aerosol injection impacts. Ongoing projects include the INCUS mission and climate projections for extreme precipitation in the U.S. Midwest.

Ferrante Neriمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Optimization
• +۵ مورد دیگر

Professor Ferrante Neri is a faculty member at the University of Surrey, holding the positions of Professor of Machine Learning and Artificial Intelligence and Associate Dean (International) for the Faculty of Engineering and Physical Sciences (FEPS). He is affiliated with the Nature Inspired Computing and Engineering Research Group, Surrey Institute for People-Centred AI (PAI), and the Computer Science Research Centre within the School of Computer Science and Electronic Engineering. His research focuses on optimization, explainable AI, and machine learning, with contributions to memetic computing and differential evolution. Since 2010, he has chaired the IEEE Task Force on Memetic Computing. He advises PhD students in topics like dynamic multi-objective optimization and AI-driven applications. His teaching expertise includes mathematical foundations for computer science. He has supervised students such as Aisha E S E Saeid and Pengjin Wu. Notable research areas include evolutionary algorithms, neural architecture search, and applications in robotics and environmental monitoring. Labs and teams include the Nature Inspired Computing group, which explores AI-driven solutions for complex problems. His work bridges theoretical advancements and practical applications in fields like autonomous systems and deep learning.

Nathaniel Chaneyمشاهده پروفایل

استادیار

• Hydrology
• Earth System Science
• Soil Science
• +۱۲ مورد دیگر

Nathaniel Chaney is an Assistant Professor in the Department of Civil and Environmental Engineering at Duke University’s Pratt School of Engineering. He leads the Chaney Lab, a research group focused on computational hydrology and Earth system modeling. His work centers on understanding and representing land surface heterogeneity in hydrological and climate models using big data, machine learning, and high-performance computing. Ph.D. in Hydrology, Princeton University, 2015 B.A. in Atmospheric Sciences and Applied Mathematics, U.C. Berkeley Postdoctoral Research Associate, Princeton University and NOAA Geophysical Fluid Dynamics Laboratory His research interests include hydrology, Earth system science, soil science, ecology, geomorphology, numerical modeling, high performance computing, machine learning, and environmental data assimilation. He develops and applies models like HydroBlocks and POLARIS to improve the representation of land heterogeneity in Earth system models. His work bridges field-scale and macro-scale hydrology, addressing challenges in land-atmosphere interactions, drought monitoring, and climate prediction. The most recent publications highlight advancements in modeling land heterogeneity, improving soil moisture estimates, characterizing land surface temperature patterns, and enhancing Earth system models through better representation of catchment-scale processes. Key themes include spatial heterogeneity, land-atmosphere coupling, and the integration of remote sensing data with high-resolution modeling. He is actively mentoring several Ph.D. students, including Laura Torres Rojas, Tyler Waterman, Emma Xu, Jiaxuan Cai, Luiz Bacelar, Daniel Guyumus, and undergraduate Sarah Bailey. His lab fosters interdisciplinary research in hydrology, climate science, and data science. Nathaniel Chaney teaches courses such as CEE 584: Physical Hydrology, CEE 506: Environmental Spatial Data Analysis, and various independent study and advanced topics courses in civil and environmental engineering. He is currently recruiting motivated Ph.D. and postdoctoral researchers interested in his research themes.

• Atmospheric convection
• Severe weather
• Mesoscale processes
• +۵ مورد دیگر

Adam Houston is a Professor in the Department of Earth and Atmospheric Sciences at the University of Nebraska-Lincoln, where he has served since 2006 after joining as an assistant professor. His research centers on severe local storms and cloud/mesoscale atmospheric phenomena. Education: Ph.D. in Atmospheric Sciences, University of Illinois at Urbana-Champaign (2004) B.S. in Meteorology, Texas A&M University Dr. Houston's expertise spans atmospheric convection , severe weather , mesoscale processes , and climate diagnostics . He leads the Severe Storms Research Group (SSRG), investigating deep convective initiation, supercell dynamics, and airmass boundary influences using numerical modeling and observational techniques including UAS and Doppler radar. Analysis of recent publications (2023-2025) reveals dominant themes in deep convection initiation mechanisms , supercell thunderstorm dynamics , and UAS-based atmospheric profiling . His work increasingly addresses urban impacts on convection and data assimilation for severe storm forecasting through major field campaigns. Research Infrastructure: Severe Storms Research Group (SSRG) Principal investigator in TORUS, LAPSE-RATE, and SCALES field campaigns NSF-funded collaborative projects including AGS-FIRP Track 1 initiatives

Daniel T. Dawson IIمشاهده پروفایل

دانشیار

• Severe convective storms
• Tornado dynamics
• Cloud and precipitation microphysics
• +۴ مورد دیگر

Dr. Daniel T. Dawson II is an Associate Professor of Atmospheric Science at Purdue University's Department of Earth, Atmospheric, and Planetary Sciences (EAPS). He leads the STorMLab (Storm and Tornado Modeling Laboratory), focusing on severe convective storm dynamics, tornado physics, and improving numerical prediction of severe weather. He holds a Ph.D. from the University of Oklahoma (2009) and B.S. from Purdue University (2002). His research integrates observational data from field campaigns like VORTEX2 and VORTEX-SE with advanced numerical modeling, particularly using EnKF radar data assimilation techniques. Education: Ph.D., University of Oklahoma, School of Meteorology (2009) M.S., University of Oklahoma, School of Meteorology (2004) B.S., Purdue University, Earth and Atmospheric Sciences (2002) His research interests include storm-scale microphysics, radar observations, and the role of surface drag in tornadogenesis. He collaborates with the Weather Radar Research Laboratory led by his spouse, Dr. Robin Tanamachi, and co-teaches the EAPS 59100 Severe Storms Field Work course, emphasizing hands-on storm chasing and forecasting. Dawson has extensive experience with the National Severe Storms Laboratory (NSSL), the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS), and the National Center for Atmospheric Research (NCAR). His work addresses challenges in Warn-on-Forecast systems and has contributed to understanding the geographic controls of severe storm environments. He leads Purdue's mobile disdrometer operations in field campaigns like PERiLS and VORTEX-SE, emphasizing real-time data collection for improving storm prediction models. Labs/Teams: STorMLab (Purdue), Weather Radar Research Laboratory (collaboration), and the Purdue TriPIPS and XTRRA radar initiatives.

Stephen Saleebyمشاهده پروفایل

پژوهشگر

• Atmospheric Science
• Cloud Microphysics
• Aerosol-Cloud Interactions
• +۳ مورد دیگر

Stephen Saleeby is a Senior Research Associate at Colorado State University, working in the field of atmospheric science since July 2000. His research focuses on cloud microphysics, aerosol-cloud interactions, and numerical modeling using the RAMS mesoscale model. Education: B.S. in Physics (1997), M.S. in Atmospheric Science (2000) Affiliation: Colorado State University Research Interests: Cloud microphysics, aerosol effects on precipitation, numerical modeling His recent publications analyze aerosol impacts on deep convection, ice nucleation processes, and convective storm initiation mechanisms. He has contributed to model development (e.g., tobac v1.5) and validation studies using satellite and radar observations. Field experience includes the ISPA-2 and ISPA-3 projects at Storm Peak Lab, where he conducted aerosol and snowfall measurements. He also coaches the Kinard Middle School Science Olympiad Meteorology Team.

Adele Lichtenberger Igelمشاهده پروفایل

استاد

• Cloud Physics
• Aerosol-Cloud Interactions
• Atmospheric Modeling
• +۵ مورد دیگر

Adele Lichtenberger Igel is a Professor in the Department of Land, Air, and Water Resources at the University of California, Davis. She leads the Cloud Physics Group, focusing on cloud processes, aerosol-cloud interactions, and microphysics parameterization in atmospheric models. Her research integrates modeling, observations, and theory to understand cloud properties, precipitation formation, and climate feedbacks. Affiliations: Cloud Physics Group, UC Davis; Atmospheric Science Graduate Group. Teaching: Courses include ATM5 (Global Climate Change), ATM128 (Radiation and Satellite Meteorology), and ATM244 (Cloud and Precipitation Physics). Research interests span aerosol effects on cloud dynamics, bulk microphysics scheme development, Arctic mixed-phase clouds, and convective systems. Notable contributions include advancing unified liquid water category bulk schemes and investigating ice habit impacts on precipitation. Her work addresses model uncertainties through comparisons of bin and bulk schemes, and she leads field projects analyzing fog, marine aerosols, and orographic snowfall. Recent publications highlight aerosol-cloud interactions in stratocumulus systems, Arctic cloud sustenance via free-tropospheric aerosols, and limitations of traditional microphysics categorizations. Awards include runner-up recognition for opinion work on convective invigoration and student mentorship accolades. Key collaborations involve DOE ASR-funded projects on convective invigoration and Arctic cloud processes. Her group actively trains graduate students (e.g., Nathan Pope, Lucas Sterzinger) and undergraduates (e.g., Abbey Williams) in cloud physics and computational modeling, with outputs including over 50 peer-reviewed articles and modeling tools like the AMP scheme.

Sonia Lasher-Trappمشاهده پروفایل

استاد

• Climate Science
• Meteorology
• Cloud Physics
• +۵ مورد دیگر

Sonia Lasher-Trapp is a Professor in the Department of Atmospheric Sciences at the University of Illinois at Urbana-Champaign. She previously held faculty positions at Purdue University from 2003 to 2014. Her research focuses on cloud and precipitation processes, numerical modeling, and the impacts of climate change on severe weather events. She leads a research group investigating entrainment effects in thunderstorms, hail dynamics, and microphysical parameterization. Education: Ph.D. in Meteorology, The University of Oklahoma, 1998 M.S. in Meteorology, The University of Oklahoma, 1993 B.S. in Meteorology (summa cum laude), Saint Louis University, 1990 Research Interests: Climate change impacts on precipitation, thunderstorm dynamics, cloud microphysics, aerosol-cloud interactions, and numerical weather modeling. Recent work emphasizes the role of entrainment, ice nucleation, and CCN/INP variability in storm systems. Recent Research Trends: Publications from 2020–2025 highlight investigations into hailfall changes under future climates, supercell entrainment mechanisms, and pseudo-global-warming climate attribution studies. Collaborations focus on Southern Ocean cloud processes and interdisciplinary field campaigns. Awards: American Meteorological Society Fellow (2023), Edward N. Lorenz Teaching Excellence Award (2021) Teaching: Teaches graduate courses in precipitation physics, microphysical parameterization, aerosol-cloud-climate interactions, and undergraduate courses in atmospheric thermodynamics and cloud physics. Labs/Teams: Leverages the Blue Waters supercomputer for high-resolution climate modeling projects. Collaborates with international teams on initiatives like CAPRICORN, MARCUS, and SOCRATES to study Southern Ocean cloud systems.

Marco Giorgettaمشاهده پروفایل

پژوهشگر

• Climate Dynamics
• Atmospheric Waves
• Global Climate Modeling
• +۴ مورد دیگر

Marco Giorgetta is a Researcher and Group Leader at the Max Planck Institute for Meteorology in Hamburg, Germany. He leads the Wave Driven Circulations group within the Climate Physics department. His work focuses on understanding atmospheric dynamics, particularly the Quasi-Biennial Oscillation (QBO), wave-mean flow interactions, and global climate modeling. He has been a core contributor to the development of the ICON atmospheric model and has coordinated major projects like QUBICC and COMBINE. Education: PhD in Natural Sciences (1996), Universität Hamburg Diploma in Physics (1991), ETH Zürich Research Interests: Marco’s research integrates advanced modeling techniques with observational data to study climate variability and atmospheric processes. Key areas include the QBO, gravity waves, tropical dynamics, and the impact of climate change on stratospheric processes. His work emphasizes high-resolution simulations and machine learning applications in climate modeling. Key Projects: Coordinator of ROMIC-2 QUBICC (2020–2023) and FP7 COMBINE (2009–2013) ICON model development lead from 2004–2020 Executive board member of the International Max Planck Research School on Earth System Modelling (2001–2014) Labs/Teams: He leads the Wave Driven Circulations group, collaborating on projects like the Barbados Cloud Observatory and Destination Earth initiatives. His work contributes to the broader ICON Earth System Model framework.

Anita Rappمشاهده پروفایل

دانشیار

• Remote Sensing
• Climate Change
• Satellite Meteorology
• +۴ مورد دیگر

Dr. Anita Rapp is an Associate Professor and Graduate Committee Chair in the Department of Atmospheric Science at Texas A&M University. Her research focuses on remote sensing, climate change, and atmospheric processes including satellite meteorology, global hydrologic cycles, and cloud-radiation interactions. She leads initiatives like the DCOTSS project and TRACER field campaign, studying aerosol-convection interactions and stratospheric hydration. Education: Ph.D. (2008), M.S. (2004) in Atmospheric Science from Colorado State University; B.S. (2000) in Meteorology from Texas A&M University. Research interests emphasize tropical convective systems, ITCZ dynamics, and the role of aerosols in modulating cloud properties and lightning activity. Her work integrates observational datasets from satellites (e.g., CloudSat, TRMM) and ground-based instruments with high-resolution modeling frameworks. Recent publications highlight advancements in aerosol vertical profiling techniques, environmental controls on overshooting convection, and the climatic implications of midtropospheric dry layers. Awards include NASA fellowships and recognition from the NASA Contractors Steering Council. Advising opportunities exist for graduate students and postdocs through TRACER and DCOTSS. She collaborates on field campaigns to advance understanding of cross-tropopause transport and aerosol-cloud interactions. Her lab contributes to developing observational datasets for boundary layer and storm-scale processes.

Andreas Preinمشاهده پروفایل

استاد

• High-resolution weather and climate modeling
• Extreme weather events
• Convection-permitting climate models
• +۳ مورد دیگر

Andreas Prein is Full Professor at ETH Zurich's Department of Environmental Systems Science and leads the High-Resolution Weather and Climate Modeling group. He specializes in modeling weather and climate dynamics, focusing on extreme events across scales, with particular emphasis on regional and local-scale extremes in a warming climate. His research bridges fundamental process understanding with practical applications, actively collaborating with stakeholders and contributing to international programs like the World Climate Research Programme (WCRP). Research Focus High-resolution weather and climate modeling Physical processes driving extreme events Regional/local-scale climate extremes Convection-permitting climate models Mesoscale convective systems Publications Trend His 2025 publications demonstrate a strong focus on extreme precipitation, mesoscale convective systems, and high-resolution modeling applications across global regions including the US, China, South America, and Spain. The work emphasizes both methodological advances (machine learning, downscaling techniques) and practical applications (flood attribution, risk assessment). Scientific Recognition Clarivate Highly Cited Researcher Over 100 peer-reviewed publications Deputy Director, Center for Climate and Weather Extremes (NCAR) WCRP and GEWEX panel member Professional Activities Active in international scientific panels and frequently advises government agencies on climate extremes. His group at ETH Zurich focuses on dynamically modeling weather and climate systems to understand changes in extreme events.