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

Miguel Rico-Ramirezمشاهده پروفایل

دانشیار

• Radar Hydrology
• Hydroinformatics
• Flood Forecasting
• +۳ مورد دیگر

Dr. Miguel Rico-Ramirez serves as Associate Professor of Radar Hydrology and Hydroinformatics at the University of Bristol's School of Civil, Aerospace and Design Engineering. His research integrates advanced radar technology with hydrological modeling to address critical water resource challenges including flood forecasting, drought management, and precipitation measurement across diverse global contexts from South Korea to Mexico City. Education: Bachelor of Engineering (Eng.) Master of Engineering (M.Eng.) Ph.D. in Engineering, University of Bristol His research program focuses on radar-based precipitation estimation, hydroinformatics, and flood prediction systems. He pioneers deep learning applications for rainfall nowcasting and develops innovative methods for uncertainty quantification in hydrological modeling. Current work emphasizes cosmic-ray neutron sensor validation, satellite-based flood mapping, and seasonal forecast applications for reservoir operations, with strong emphasis on translating research into operational water management solutions. Recent publications (2023-2025) reveal three dominant research thrusts: (1) deep learning frameworks for spatiotemporal rainfall prediction, (2) global validation of precipitation and soil moisture datasets using novel sensor networks, and (3) operational implementation of seasonal forecasts for drought mitigation in South Korea. His work consistently bridges radar meteorology with practical hydrological applications across urban and data-scarce environments. Scientific Awards: No specific awards documented in source materials Dr. Rico-Ramirez supervises postgraduate researchers in radar hydrology and hydroinformatics, with projects spanning flood early warning systems, precipitation nowcasting, and climate adaptation strategies. His research receives funding for international collaborations focused on water security challenges, particularly in drought-prone regions and data-scarce basins like the Nile Delta. Current grants support development of integrated forecasting systems combining global datasets with machine learning for extreme event management. He leads the Radar Hydrology research group within Bristol's Water and Environmental Engineering division, collaborating closely with Professor Dawei Han on hydroinformatics and Dr. Rafael Rosolem on water-climate interactions. The team maintains active partnerships with meteorological agencies and water authorities globally, particularly in flood forecasting system implementation across South Korea and Mexico.

David J. Stensrudمشاهده پروفایل

استاد

• Mesoscale meteorology
• Numerical weather prediction
• Synoptic meteorology
• +۵ مورد دیگر

David J. Stensrud is a Professor of Meteorology and Atmospheric Science at Pennsylvania State University, where he has been a faculty member in the Department of Meteorology and Atmospheric Science within the College of Earth and Mineral Sciences. His research focuses on advancing our understanding of severe weather phenomena and improving numerical weather prediction capabilities. Dr. Stensrud received his academic training at Penn State, earning his M.S. in Meteorology in 1985 and his Ph.D. in Meteorology in 1992. His educational background has provided the foundation for his extensive research career focused on atmospheric dynamics and prediction. Dr. Stensrud's research spans several critical areas in atmospheric science, with particular emphasis on mesoscale meteorology , numerical weather prediction , and synoptic meteorology . He is internationally recognized for his work on ensemble forecasting , where he explores how groups of numerical weather prediction models can provide probabilistic forecasts of severe weather events. His research on convective-scale data assimilation aims to improve how observations from radar and satellites are incorporated into high-resolution weather models. Additional research interests include the physical processes behind severe weather phenomena like derechos and heavy rainfall events, the predictability of convective-scale phenomena, and the dynamics of the North American monsoon system. He has made significant contributions to understanding how urban environments influence thunderstorms and how convective systems interact with their larger-scale environment. Analysis of Dr. Stensrud's recent publications reveals a consistent focus on improving severe weather prediction through advanced data assimilation techniques. His work primarily centers on integrating radar and satellite observations into convection-allowing models to enhance forecasting capabilities for thunderstorms and other severe weather phenomena. A notable trend in his research is the increasing sophistication of ensemble approaches to address uncertainties in both initial conditions and model physics. His publications demonstrate a progression from fundamental studies of mesoscale phenomena to increasingly operational applications with potential for real-world forecasting improvements. Dr. Stensrud has served in several important professional capacities that highlight his standing in the meteorological community: Chair, Storm-scale Radar Data Assimilation Workshop, Norman, Oklahoma, October 2011 Member, NOAA/NWS Functional Weather Radar Requirements Integrated Working Team, 2012-2013 Guest Editor, Advances in Meteorology, Special Issue on "Storm-scale data assimilation and NWP", 2013 Commissioner, Scientific and Technological Activities Commission, American Meteorological Society, 2016-2017 Dr. Stensrud has authored more than 150 peer-reviewed publications and a textbook entitled "Parameterization Schemes: Keys to Understanding Numerical Weather Models." He has been actively involved in mentoring graduate students, though specific names of advisees are not provided in the available information. In collaboration with colleagues at Penn State, he helped create a 20-station environmental monitoring network across Pennsylvania with plans to expand to 50+ stations. His research has been supported by various grants that have enabled field campaigns such as the Mesoscale Predictability Experiment (MPEX) in 2013, where his team intercepted severe thunderstorms to collect critical observational data. Dr. Stensrud is involved with several research teams and facilities at Penn State, including work with the Joel N. Myers Weather Center and the Bob and Charlotte Landis Broadcast Room. His research group focuses on analyzing data from dual-polarization radar systems and developing improved techniques for assimilating these observations into convection-allowing models. He collaborates extensively with other researchers at Penn State and beyond, particularly in studies involving the interactions between urban environments and thunderstorms, and the upscale effects of deep convection on larger-scale weather patterns.

Edriss S. Titiمشاهده پروفایل

استاد

• Nonlinear Partial Differential Equations
• Applied Mathematics
• Numerical Analysis
• +۵ مورد دیگر

Edriss S. Titi is a University Distinguished Professor and Arthur Owen Professor of Mathematics at Texas A&M University within the College of Arts & Sciences. His research focuses on nonlinear partial differential equations, applied mathematics, and geophysical fluid dynamics. He leads studies on fluid mechanics, atmospheric and oceanic dynamics, data assimilation, and control theory. His work often addresses mathematical rigor in modeling complex systems like climate dynamics and turbulent flows. Research Interests: Nonlinear PDEs and their applications Fluid dynamics and turbulence Data assimilation algorithms Climate and ocean modeling Infinite-dimensional dynamical systems Recent publications emphasize Navier-Stokes equations , primitive equations , and data assimilation in chaotic systems . His methodologies bridge theoretical analysis and computational modeling, with applications to weather prediction and geophysical flows. Collaborations include the Institute for Applied Mathematics and Computational Science (IAMCS) at Texas A&M. Notable contributions include rigorous analysis of global well-posedness for oceanic models and development of CDAnet, a physics-informed deep learning framework for fluid flow downscaling.

Tamas Monaمشاهده پروفایل

پژوهشگر

• Epidemiology
• Plant Pathology
• Meteorology
• +۵ مورد دیگر

Dr. Tamas Mona is a Postdoctoral Research Associate in the Department of Plant Sciences at the University of Cambridge , affiliated with the Epidemiology and Modelling Group . His work focuses on environmental suitability models for large-scale epidemiological forecasting, particularly in wheat rust outbreaks across Africa, the Middle East, and Asia. Collaborations include the UK Met Office, CIMMYT, and institutions in Ethiopia, Kenya, Bangladesh, and Nepal. PhD in Environmental Sciences (2019), Eötvös Loránd University MSc in Meteorology (2013), Eötvös Loránd University BSc in Physics with Meteorology (2011), Eötvös Loránd University Research interests integrate meteorological applications with epidemiological models to predict crop disease outbreaks. Key projects involve tracking transmission pathways for stem rust pathogens and analyzing how irrigation creates green bridges for intercontinental pathogen spread. Publications emphasize environmental science and computational epidemiology . Current collaborations span Sub-Saharan Africa (EIAR, ATI, KARLO) and South Asia (BWMRI, NARC) through initiatives like the Global Food Security IRC . Modeling frameworks developed by Mona contribute to policy advisory systems for emerging pest threats, aligning with DEFRA and UK government strategies.

• Scientific Computing
• Numerical Analysis
• Applied Mathematics
• +۵ مورد دیگر

Eirik Valseth is an Associate Professor of Scientific Computing at the Norwegian University of Life Sciences (NMBU), Department of Data Science. He holds concurrent roles as a research associate at the Oden Institute, University of Texas at Austin, and an affiliated researcher at Simula Research Laboratory (Department of Numerical Analysis and Scientific Computing). His expertise lies in advanced finite element methods for PDEs with applications in flood modeling and hydropower systems. Current Affiliation: NMBU (Norwegian University of Life Sciences) Secondary Affiliations: Oden Institute (UT Austin), Simula Research Laboratory Research interests span numerical methods for challenging PDE systems, including: Stabilized finite element formulations Hurricane storm surge and riverine flood modeling Hydropower infrastructure analysis Computational mechanics and applied mathematics His recent publications (2024–2025) emphasize flood risk assessment (compound flooding, dam breaks, dredging impacts), advanced numerical methods (isogeometric analysis, stochastic finite elements, graph-grammar algorithms), and environmental applications (pollution transport, pathogen distribution, mosquito population dynamics after hurricanes). Key trends include cross-disciplinary integration of physics-aware machine learning and robust hydrodynamic simulation tools. Valseth's work extends to software development (e.g., WAVEx for spectral wave models, SWEMniCS for coastal circulation) and large-scale modeling frameworks like the ADCIRC unstructured mesh model for US coasts. Collaborative projects involve institutions such as University of Texas at Austin, Simula, and NOAA.

Callum Atkinsonمشاهده پروفایل

مدرس ارشد

• Turbulent flows
• Heat transfer
• Aerodynamics
• +۵ مورد دیگر

Dr. Callum Atkinson is a Senior Lecturer in Mechanical & Aerospace Engineering at Monash University, specializing in turbulent flow dynamics and experimental fluid mechanics. His research focuses on understanding and controlling turbulent shear flows in pipes, boundary layers, jets, and rocket engines, combining high-fidelity numerical simulations with advanced optical diagnostics like holographic PIV and tomographic techniques. He has developed novel methodologies for 3D velocity and density measurements, contributing to drag reduction studies, heat transfer analysis, and flow control in aerospace and mechanical systems. His work addresses UN Sustainable Development Goals related to energy efficiency and sustainable transport. Current roles include leading collaborative projects on adverse pressure gradient boundary layers and flow mixing, and he actively participates in peer review for journals like Journal of Fluid Mechanics and Physics of Fluids . He supervises PhD students in topics such as hybrid rocket engine optimization and turbulence modeling, leveraging Monash's engineering research infrastructure. Notable contributions include one of the world's largest adverse pressure gradient simulations and pioneering volumetric flow visualization techniques. His experimental toolkit includes laser diagnostics, tomographic PIV, and background-oriented schlieren systems. Recent work has explored superhydrophobic surface drag reduction, thermal jet behavior, and the dynamics of high-speed jet flows. He maintains a strong focus on bridging experimental and computational fluid dynamics to advance fundamental understanding and industrial applications.

Greg Hueyمشاهده پروفایل

استاد

• Atmospheric Chemistry
• Aerosols
• Clouds
• +۴ مورد دیگر

Dr. Greg Huey is a Professor in the School of Earth & Atmospheric Sciences at the Georgia Institute of Technology, where he leads research in atmospheric chemistry with expertise in trace gas measurement and aerosol processes. His work bridges laboratory studies, aircraft campaigns, and global modeling to address air quality and climate challenges. His educational background includes a Ph.D. in Physical Chemistry from the University of Wisconsin-Madison (1992) and a B.S. in Chemistry from the University of Virginia (1986). Dr. Huey's research centers on chemical kinetics of ionic and neutral species, heterogeneous chemistry , and aircraft-based sampling of condensable gases. He specializes in chemical ionization mass spectrometry for trace gas analysis, with applications to wildfire smoke, urban pollution, and stratospheric-tropospheric exchange. Key themes include aerosol formation mechanisms, ozone production pathways, and halogen chemistry impacts on oxidation capacity. Analysis of his 2021-2025 publications reveals dominant research threads in Asian pollution transport , wildfire smoke chemistry , and urban ozone formation . His work frequently integrates NASA field campaigns (KORUS-AQ, FIREX-AQ, ATom) with satellite validation and modeling to quantify pollution impacts across scales. His scientific recognition includes: Outstanding Teaching Award, Georgia Tech (2007) Dr. Huey directs major field campaigns and instrumentation development for atmospheric trace gas measurements. His research is supported by NASA and NSF grants focused on aircraft-based studies of wildfire emissions, monsoon-driven transport, and urban air quality. He actively mentors students through Georgia Tech's atmospheric science programs and a multi-institution REU site. He contributes to international efforts like the Asian Monsoon Chemical and Climate Impact Project (ACCLIP), developing advanced chemical ionization mass spectrometers for deployment on NASA aircraft to study global atmospheric composition.

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.

Prathap Ramamurthyمشاهده پروفایل

دانشیار

• Climate Change
• Energy Sustainability
• Environmental Fluid Dynamics
• +۵ مورد دیگر

Prathap Ramamurthy is an Associate Professor in the Department of Mechanical Engineering at City College of New York (CCNY) . He holds affiliations with the CUNY-CREST Institute, Earth System Science and Environmental Engineering, and NOAA-CESSRST. His research focuses on urban climate dynamics, environmental fluid dynamics, and climate sustainability. Key research areas include: Urban boundary layer dynamics and heat mitigation strategies Coastal urban meteorology and convective precipitation Air quality modeling and remote sensing applications Climate change impacts on urban environments His work combines field campaigns (e.g., CoURAGE experiment), numerical modeling, and AI-driven approaches to address challenges in urban resilience and energy systems. Major projects include studies on misting infrastructure, heat pumps in winter climates, and hurricane impacts on Puerto Rico's climate. Recent articles emphasize data-driven solutions for extreme weather adaptation and urban-rural atmospheric interactions. He collaborates with interdisciplinary teams to advance climate science and community-focused environmental monitoring initiatives.

Zhihong Liمشاهده پروفایل

پژوهشگر ارشد

• Data Assimilation
• Convective-Scale Nowcasting
• Numerical Weather Prediction (NWP)
• +۴ مورد دیگر

Dr. Zhihong Li is a Senior Research Scientist at the Met Office, affiliated with the Department of Meteorology at the University of Reading. His work focuses on advancing data assimilation methods for high-resolution (1.5 km) numerical weather prediction (NWP) systems, particularly for nowcasting applications (0–6 hour forecasts). He specializes in 3D-Var and 4D-Var techniques and their integration into the Met Office's Unified Model to improve initial conditions and assimilate novel observations like radar Doppler winds and reflectivities. Previously, Zhihong spent a decade at the University of Wales Bangor researching coastal and shelf seas numerical modeling before joining the Met Office in 1999. Since 2003, he has contributed to the JCMM Data Assimilation group, aiding the development of operational high-resolution forecasting systems. His current projects emphasize verifying rainfall, fog, and cloud forecasts using rapid hourly data assimilation cycles. Zhihong's expertise bridges ocean-atmosphere interactions, coastal modeling, and cutting-edge NWP methodologies. Despite his senior role, no specific scientific awards are explicitly stated in the provided text. His research team, MetOffice@Reading Obs R&D Surface Team, collaborates closely with academic and operational meteorological communities to enhance short-range forecast accuracy.

• 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

Zhaoxia Puمشاهده پروفایل

استاد

• Numerical Weather Prediction
• Data Assimilation
• Machine Learning
• +۵ مورد دیگر

Dr. Zhaoxia Pu is a Professor in the Department of Atmospheric Sciences at the University of Utah and an Adjunct Professor at the School of Computing . Recognized as a Fellow of both the American Meteorological Society and the Royal Meteorological Society, she serves on the NOAA Science Advisory Board and has led 38 federally funded projects from agencies including NOAA, NASA, NSF, DOE, and ONR. Specializes in numerical weather prediction , data assimilation , and AI/machine learning for high-impact weather systems Developed advanced methods integrating satellite/radar data (GOES-R, CYGNSS, TROPICS) with Earth system models (UFS, E3SM, WRF) Recipient of the 2024 Excellence in Research Award and 2023 Provost's Banner Project recognition Research Trends : Her recent publications focus on: Machine learning approaches for precipitation retrieval using GOES-R data Cold fog microphysics and visibility parameterization in complex terrain Tropical cyclone dynamics through radar and lidar data assimilation Boundary layer turbulence in landfalling storms Drought mechanisms linked to synoptic-scale circulation New particle formation in mountainous regions Scientific Leadership : Lead scientist for CFACT NSF field campaign (2021–2025) Editorial board member of leading journals Active reviewer for NSF, DOE, NOAA, and NASA Teaching & Mentorship : Teaches Numerical Weather Prediction , Atmospheric Dynamics , and Introduction to Atmospheric Sciences courses. Has supervised 28 graduate students to completion.

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.