Dr. Leanne Archer is a Researcher in the School of Geographical Sciences at the University of Bristol, specializing in hydrology and climate change impacts. Her work focuses on flood risk assessment in Small Island Developing States, extreme rainfall events, and the application of convection-permitting climate models. She collaborates with experts like Prof. Paul Bates and Dr. Jonty Rougier on interdisciplinary projects addressing tropical cyclone hazards and climate adaptation strategies. Her research interests include analyzing flood exposure in vulnerable regions, soil moisture dynamics in urban flooding, and improving global flood forecasts for humanitarian operations. Archer’s publications emphasize the implications of climate change on rainfall-driven disasters, particularly in Puerto Rico and East Africa, using high-resolution climate projections to evaluate future risks under 1.5° C and 2° C warming scenarios. Recent work explores innovations like the Surface Water Ocean Topography Mission for flood modeling and evaluates the suitability of TanDEM-X data for inundation studies in island nations. Her contributions bridge environmental science with policy, aiming to enhance disaster preparedness and resilience in climate-sensitive regions.
Ben Livneh is an Associate Professor at the University of Colorado Boulder , affiliated with both the Civil, Environmental, and Architectural Engineering Department and the Cooperative Institute for Research in Environmental Sciences (CIRES) . As Director of the Western Water Assessment , he bridges academic research with regional climate resilience initiatives. Ph.D. in Civil Engineering (Hydrology), University of Washington (2012) MESc in Civil Engineering, University of Western Ontario (2006) His research explores hydrologic responses to climate and land-cover changes , focusing on snowpack dynamics, wildfire impacts on water quality, sediment transport, and drought predictability. Key projects include simulations of montane snowpack for wolverine habitat preservation and post-fire landslide susceptibility analysis . Recent publications highlight continental-scale hydraulic geometry datasets , climate-energy nexus challenges , and global lake level reconstructions using satellite data. His work has been recognized by the AGU Hydrologic Sciences Early Career Award (2022) and NASA New Investigator Program (2018) . Scientific Awards AGU Hydrologic Sciences Early Career Award (2022) NASA New Investigator Award (2018) Symposium Scholar, DISCCRS VIII (2013) CIRES Visiting Fellowship (2012) Ben leads interdisciplinary collaborations with institutions like the University of Alaska Southeast and NOAA , addressing climate-water-energy-food nexus challenges through advanced modeling and remote sensing techniques.
Dr. Jessica A Eisma is an Assistant Professor of Water Resources in the Department of Civil Engineering at the University of Texas at Arlington. Her research focuses on urban and dryland hydrology, remote sensing, machine learning, citizen science, and climate change adaptation. She holds a PhD from Purdue University (2020) and prior degrees from Purdue and Michigan State University. Her work emphasizes community-centered solutions for flood resilience and green infrastructure planning in vulnerable areas. Education: PhD, Civil Engineering, Purdue University, 2020 MS, Civil Engineering, Purdue University, 2015 BS, Civil Engineering, Michigan State University, 2012 Research Interests: Urban hydrology and climate impacts on rainfall patterns Remote sensing applications for water resource management Machine learning in hydrological modeling Citizen science for environmental data collection Green infrastructure design for flood mitigation Recent Article Trends: Dr. Eisma’s recent work addresses urbanization effects on extreme rainfall, UAV-based thermal mapping of micro-urban heat islands, and equity-focused green infrastructure planning. Her publications often bridge technical innovation and community-driven solutions for climate resilience. Awards: 2024: Faculty/Staff Graduating Student Impact Reception (UTA) 2023: Emerging Leaders Award (Purdue CEG SAC) 2020: Magoon Award for Excellence in Teaching (Purdue College of Engineering) 2015: NSF Graduate Research Fellowship Advising & Grants: Advises 3 PhD students and multiple undergrad researchers Principal Investigator on grants totaling over $1M from NOAA, NSF, and others Focus areas: Houston flood resilience, Texas urban stormwater systems Lab & Teams: Leads the SEUSI Lab, dedicated to socio-environmental solutions in urban sustainability and infrastructure. Collaborates with national and international partners on water security and climate adaptation projects.
Sai Ravela is a Principal Research Scientist in the Department of Earth, Atmospheric and Planetary Sciences (EAPS) at the Massachusetts Institute of Technology (MIT). His research focuses on nonlinear stochastic dynamics, coherent fluid systems, uncertainty quantification, and autonomous observing technologies. He specializes in developing data-driven methodologies for natural hazard detection, climate change impacts, and environmental risk assessment. Ravela’s work integrates computational science with geophysical applications, including storm surge modeling, extreme rainfall analysis, and geothermal exploration. He pioneers techniques like neural dynamical systems and adversarial learning to improve predictive accuracy in nonstationary climate regimes. His contributions span environmental monitoring systems, autonomous aircraft resilience frameworks, and policy-informed climate vulnerability assessments. Key research areas include: Coastal flood risk in Bangladesh and Vietnam Dynamic data-driven applications systems (DDDAS) Machine learning for geosciences and environmental systems Uncertainty quantification in complex fluid dynamics He leads interdisciplinary projects at MIT’s Computational Science and Engineering (CSE) program, advancing methods for data assimilation, surrogate modeling, and real-time environmental observatories. His innovations bridge theoretical frameworks with practical solutions for climate adaptation and disaster resilience.
Sarah Kang is the Director of the Department of Climate Dynamics at the Max Planck Institute for Meteorology in Hamburg, Germany, a position she has held since August 2023. She leads the Director's Research Group (CDY) focusing on fundamental climate dynamics. Prior to this, she served as Professor in the Department of Urban and Environmental Engineering at Ulsan National Institute of Science and Technology (UNIST) in South Korea from 2011-2023, progressing through assistant, associate, and full professor ranks. Her research examines complex climate system dynamics, with emphasis on: Large-scale atmosphere and ocean circulation patterns Tropical-extratropical climate interactions Hydrological cycle responses to climate change Mechanisms of polar amplification Teleconnections between ocean basins and climate zones Analysis of her recent publications reveals dominant research themes: Ocean-atmosphere coupling mechanisms Radiative forcing and climate sensitivity Hemispheric climate asymmetries Tropical precipitation dynamics Polar warming impacts on global circulation with consistent methodology employing high-resolution climate modeling and observational verification. Major scientific recognitions include: AGU Atmospheric Sciences Ascent Award (2022) AOGS Kamide Lecture Award (2018) Editor's Citation for Excellence in Refereeing (GRL 2018) UNIST Teaching Excellence Award (2012) NCAR Advanced Studies Fellowship (2009) She maintains extensive professional engagement as: Co-chair of CLIVAR Climate Dynamics Panel Science Steering Committee member for CFMIP Associate Editor for Frontiers in Climate Editor for AGU Advances Board member of Korean Meteorological Society
Ben Seiyon Lee is an Assistant Professor in the Department of Statistics at George Mason University's College of Science. His work bridges computational statistics, climate modeling, and environmental risk assessment. Education: PhD in Statistics, Pennsylvania State University (2020) Lee specializes in computational methods for high-dimensional spatiotemporal data and uncertainty quantification in climate models. His research explores climate change impacts on extreme hydrological events, wildfire emissions, and medical decision-making. Recent publications focus on Bayesian spatiotemporal frameworks for extreme precipitation analysis, zero-inflated spatial models, and multisector uncertainty quantification. His work addresses challenges in flood risk assessment, agricultural yield projections, and healthcare compliance metrics.
Mariam Zachariah serves as a Research Fellow at the Centre for Environmental Policy within the Faculty of Natural Sciences at Imperial College London. She is a core contributor to World Weather Attribution (WWA), an international scientific collaboration conducting rapid climate change attribution analyses for extreme weather events globally. Her work bridges climate science, vulnerability assessment, and policy-relevant research. Her educational foundation includes a PhD from the Indian Institute of Technology Bombay (IITB), where she investigated climate impacts on Indian agriculture. This research focused on drought and extreme temperature effects on crop yields in major agrarian regions, recognizing agriculture's critical role in India's climate-vulnerable economy. Zachariah's research centers on near-real-time attribution of extreme events to quantify human-induced climate change influences. Her expertise spans climate modeling, statistical analysis of extreme weather, and integrating vulnerability frameworks to assess compound impacts on communities. She examines how climate change interacts with socioeconomic factors to exacerbate disasters, particularly in agricultural systems and flood-prone regions worldwide. Analysis of her recent publications reveals a dominant focus on rapid attribution of droughts, floods, and heatwaves across diverse global contexts - from the Horn of Africa to Central Europe and South America. These studies consistently demonstrate climate change as a significant amplifier of event severity, while emphasizing how pre-existing vulnerabilities determine actual impacts. Her work increasingly addresses compound hazards and the intersection of climate change with infrastructure failures and land management. As a key member of the World Weather Attribution initiative, Zachariah collaborates with climate scientists, social scientists, and vulnerability experts in a unique operational framework that delivers scientific assessments within days of extreme events. This work directly informs policymakers, media, and affected communities about climate change's role in contemporary disasters.
Hyuck Jin Park is a Full Professor in the Department of Energy Resources and Geosystems Engineering at Sejong University, South Korea, where he has been teaching and conducting research since 2003. With a Ph.D. in Engineering Geology from Purdue University, his expertise spans geotechnical engineering, landslide analysis, and geospatial technologies. Professor Park has built a distinguished career in landslide hazard assessment, combining traditional geotechnical approaches with modern machine learning techniques to improve prediction accuracy and risk management. His educational background includes: B.S. in Geology from Yonsei University (1990) M.S. in Geophysics from Yonsei University (1993) Ph.D. in Engineering Geology from Purdue University (2011) Professor Park's research focuses on the spatial and temporal probability of landslide occurrence, utilizing fuzzy logic, probabilistic analysis, GIS, Monte Carlo simulation, and machine learning for landslide hazard assessment. His work integrates physically based models with statistical approaches to better understand landslide mechanisms and improve prediction capabilities. He has made significant contributions to the development of methodologies that account for geological uncertainties in hazard assessment, with applications ranging from rock slope stability to rainfall-induced shallow landslides. His recent publications demonstrate a clear trend toward integrating explainable artificial intelligence with traditional geotechnical approaches for natural hazard assessment. Professor Park's work increasingly focuses on making machine learning models transparent and interpretable while maintaining high predictive accuracy. The research spans multiple hazard types including landslides, earthquakes, and floods, with a growing emphasis on climate change impacts and data-scarce environments. With an h-index of 28 and over 3,421 citations, Professor Park has established himself as a leading researcher in his field. His work has been published in high-impact journals including Engineering Geology, Landslides, and Catena, reflecting the significance and quality of his contributions to geotechnical engineering and natural hazard assessment. Professor Park has mentored numerous researchers through collaborative projects and has secured funding for his innovative work in landslide prediction and hazard assessment. His research has involved significant international collaboration, particularly with researchers from Malaysia, Australia, and Yemen, addressing landslide and flood risks in diverse geographical contexts. He leads research activities within the Department of Geoinformation Engineering at Sejong University and has contributed to the development of specialized tools like DEWS (Distance, Elevation, Watershed, and Slope unit) for landslide early warning systems.
Mingfang Ting is a Professor of Climate at the Columbia Climate School , affiliated with the Lamont-Doherty Earth Observatory . She co-directs the M.S. in Climate program and serves as Co-Senior Director for Education at the Columbia Climate School. Her research focuses on climate variability, extremes, Asian monsoons, Arctic sea ice, and climate change impacts on agriculture and health. Education: Ph.D. in Climate Dynamics (Princeton University, 1990), M.S. and B.S. from Peking University (1985, 1983). She has taught climate science at Columbia since 2004. Research Interests: Investigates weather/climate extremes in a warming world, Asian monsoon dynamics, Arctic sea ice variability, decadal climate modes, and hydroclimate impacts. Recent work emphasizes heatwaves, drought-flood linkages, and climate model projections. Key Projects (2020–2023): Advancing predictive understanding of North American drought Asian monsoon response to climate change Causal mechanisms of dry/humid heat extremes Arctic transport pathways and sea ice loss Scientific Contributions: Authored/co-authored over 200+ peer-reviewed articles. Her 2022 analysis of the 2021 North American heatwave and 2022 Pakistan floods exemplifies climate attribution science. Awards: AMS Distinguished Scientific Award (2021) AGU Fellow (2022) NSF CAREER Award (1995) Reuters' World’s Top Climate Scientists (2021) Leadership: Former Co-Editor-in-Chief of Journal of Climate (2020–2023). Active in climate education and global resilience initiatives through the Decarbonization Network. Labs/Teams: Leads interdisciplinary teams at LDEO focusing on climate dynamics and extreme event analysis. Collaborates internationally on monsoon systems and Arctic research.
Prof. Dr. Ralf Merz serves as Head of the Department of Catchment Hydrology at the Helmholtz Centre for Environmental Research (UFZ) and holds a Full Professorship in Catchment Hydrology at Martin-Luther University Halle-Wittenberg since 2011. His career bridges hydrological modeling, flood risk assessment, and water quality analysis across diverse climates from Central Asia to Europe. MSc in Civil Engineering (Technical University of Karlsruhe, 1997) PhD in Hydrology (Vienna University of Technology, 2002) Habilitation in Hydrology (Vienna University of Technology, 2009) Research Interests span comparative hydrology, flood generation mechanisms, climate change impacts on water resources, and nitrate dynamics in river systems. His work emphasizes process-based understanding of runoff events and regional flood modeling through innovative approaches like the PHEV distribution framework. Scientific Contributions include over 100 publications (2003-2025) on: Flood frequency analysis in changing climates Groundwater recharge in arid regions Hydrochemical response to droughts Remote sensing applications for groundwater studies Multi-response calibration of hydrological models Key projects involve MOSES observatory development, TRACER research school, and Pamir Mountains glaciological studies. Recognitions : APART research grant (Austrian Academy of Sciences, 2006) Leadership extends to directing the Catchment Hydrology department and participating in European hydrological networks like the Bode Hydrological Observatory and TERENO infrastructure. His methodological advancements include flood time-scale analysis and event runoff coefficient regionalization.
Dr. Jonathan T. Overpeck is the Samuel A. Graham Dean of the School for Environment and Sustainability (SEAS) at the University of Michigan, where he also holds the William B. Stapp Collegiate Professorship of Environmental Education. He is a Professor of both Climate and Space Sciences and Engineering, and Earth and Environmental Sciences, with a career spanning climate-vegetation interactions, abrupt climate change, monsoon dynamics, drought hydroclimate, sea level rise research, and interdisciplinary climate assessment. Overpeck has published over 230 works cited 60,000+ times, emphasizing public education, university-community partnerships for climate solutions, and environmental justice initiatives. PhD in Geological Sciences, Brown University MSc in Geological Sciences, Brown University BA in Geology (Honors), Hamilton College His research spans climate-biosphere interactions , climate variability and abrupt change , monsoon dynamics , drought and hydroclimate , sea level rise , climate law , and climate adaptation . Overpeck pioneered studies on megadrought terminology, temperature-driven drought intensification, and the aridification of North America. His work with the NOAA Paleoclimate Program and World Data Center for Paleoclimatology established foundational understanding of climate dynamics through annually-laminated sediment analysis in the Cariaco Basin. Overpeck's 2020-2024 research includes climate aridification , hydroclimate scaling mismatches , and temperature-precipitation interactions , with recent focus on Antarctic heatwaves, Mississippi River Basin changes, and corporate climate accountability. His article trends show concentration in climate attribution , hydrological extremes , paleoclimate modeling , and climate policy analysis . Scientific Honors: 2024 U.S. National Academy of Sciences 2015 American Geophysical Union Fellow 2009 AAAS Fellow 2007 Nobel Peace Prize contributor (IPCC) 2005 Guggenheim Fellowship Multiple U.S. Department of Commerce awards Overpeck has led or participated in significant climate adaptation projects , including NSF grants totaling $5.1M+ for Southwest Hydroclimatic Extremes (2017-2020), Amazon Drought Impacts (2014-2018), and Quantifying Drought Risk (2013-2018). He serves on the Colorado River Research Group (2014-present) and advises Climate Communication (2011-present). Current initiatives include Great Lakes University positioning, Michigan's climate resilience planning, and the Audacious Water podcast series examining Mississippi River Basin transformations. Overpeck actively contributes to climate policy discourse , advocating for science-informed decision-making and stakeholder collaboration across government, military, and corporate sectors.
Dr. Indrani Roy is an Honorary Associate Professor in the Department of Earth Sciences at University College London (UCL). She holds a PhD from Imperial College London and has extensive research experience at institutions including Imperial College and the University of Exeter. Previously, she served as a permanent employee at the India Meteorological Department (Government of India). She is a Fellow of the Royal Meteorological Society (FRMetS) and serves as its Trustee. Dr. Roy contributes to international scientific governance as a panel member for the UK's Natural Environmental Research Council (NERC) and the Romanian National Research Council. Her multidisciplinary research spans: Solar-atmosphere-ocean coupling mechanisms Monsoon dynamics and teleconnection patterns Climate change processes and extreme events Stratosphere-troposphere interactions Climate variability across decadal scales She actively investigates how solar cycles influence regional climates and extreme weather phenomena. Dr. Roy's publications demonstrate consistent focus on climate dynamics with recent emphasis on African and Asian monsoon systems, COVID-19 climate interactions, and improving predictive capabilities for extreme rainfall events. Her work increasingly integrates public health perspectives with climate science. Scientific Recognition: Fellow of the Royal Meteorological Society (FRMetS) Teaching & Advising: As an Associate Fellow of the Higher Education Academy (HEA), she currently teaches the Literature Project module (NSCI0004) for Natural Sciences at UCL. Her past teaching includes: Undergraduate research supervision (University of Exeter) Masters project supervision and guest lecturing (UCL) Instruction of Masters/PhD candidates (University of Oulu, Finland) Professional Engagement: Dr. Roy serves as reviewer for over 40 international journals (including Nature Geoscience and Science Reports) and grant agencies such as NSF, Royal Society, and French National Research Agency. She co-convenes sessions at major conferences (AOGS) and previously held editorial roles at Frontiers journals.
Dr Conrad Wasko is a Sydney Horizon Fellow at the University of Sydney and an honorary fellow at the University of Melbourne. He specializes in environmental hydrology and climate change impacts on extreme rainfall and flooding. His work has been cited by the IPCC and he co-leads the update to Australia’s flood estimation guidelines. Previously, he held an ARC DECRA Fellowship and a McKenzie Fellowship. He has published over 50 articles and received awards including the Batterham Medal (2023) and the MSSANZ Early Career Research Excellence Award (2019). His research focuses on quantifying climate-driven changes in rainfall patterns and flood risks, with applications to infrastructure resilience and policy. Education: PhD in Civil Engineering, UNSW Sydney (2016) Bachelor/Master’s qualifications (not explicitly stated in text) Key Roles: Member of The Net Zero Institute Editor of Journal of Hydrology X and Advances in Water Resources Hydroclimate Stream Leader, Modelling and Simulation Society of Australia and New Zealand His research emphasizes the intensification of extreme rainfall events with global warming, particularly their implications for flood risk and urban infrastructure. He uses advanced statistical models and climate data to project future flood scenarios and improve design standards. Recent work includes analyzing non-stationary rainfall patterns and improving flood frequency analysis techniques. Awards and Honors: Batterham Medal (Australian Academy of Technological Sciences and Engineering, 2023) Veski Victoria Fellow (2020) MSSANZ Early Career Research Excellence Award (2019) Lorenz G Straub Award (2016) Grants and Projects: ARC DECRA Fellowship (University of Melbourne) Contributions to national climate change adaptation frameworks Labs and Collaborations: Partnerships with the Water Research Centre (UNSW) and the Net Zero Institute Collaborations on global flood risk assessments and hydrological modeling tools
Dr Ting Sun is an Associate Professor in Climate & Meteorological Hazard Risks at University College London , Department of Risk and Disaster Reduction. He earned his BEng (2009) and PhD in Hydrology (2013) from Tsinghua University , followed by a visiting period at Princeton University (2011–2012). After postdoctoral appointments at Tsinghua and the University of Reading , he held a NERC Independent Research Fellowship at Reading (2017–2022) before joining UCL in May 2022. Education PhD in Hydrology, Tsinghua University, 2013 BEng in Hydraulic Engineering, Tsinghua University, 2009 Visiting PhD Student, Princeton University, 2011–2012 Research Interests Dr Sun’s work converges on urban climate modelling across scales —from neighbourhood blocks to global grids—focusing on the impacts of weather and climate extremes such as heat waves and extreme rainfall in cities. He is the lead developer of the Surface Urban Energy and Water balance Scheme (SUEWS) and its Python wrapper SuPy , developed in collaboration with Prof Sue Grimmond’s micromet group. He also contributes as a core member of the Urban Multi-scale Environmental Predictor (UMEP) development team. His multidisciplinary expertise integrates hydro-climate dynamics, computational modelling, machine learning, built-environment processes, and public-health linkages . Research Trends from Recent Publications Across the 15 most recent articles, a clear trajectory emerges from high-resolution urban-process modelling toward integrated socio-environmental assessments . Studies published in 2024–2025 couple atmospheric models (WRF-SUEWS) with global building-morphology datasets (GLAMOUR) to quantify how cities alter rainfall patterns, temperature sensitivity, and heat-related mortality. Earlier works progressively refined SUEWS’s physical parameterisations and Python accessibility, while recent outputs leverage deep-learning remote-sensing tools (SHAFTS) and hybrid hydrological-neural architectures to deliver actionable insights for urban planning and climate adaptation. Scientific Awards & Fellowships NERC Independent Research Fellowship , University of Reading, 2017–2022 HEA Fellowship , University College London, 2023 Professional Service & Editorial Roles Topic Editor , Geoscientific Model Development (from 2025) Editorial Board Member , Scientific Data (from 2024) Peer review and consultancy for journals, conferences, and policy bodies Supervision of taught-course projects and research degrees External examining and mentoring Labs, Teams & Collaborations Dr Sun leads and collaborates within the UCL Department of Risk and Disaster Reduction , working closely with the micromet group at the University of Reading (Prof Sue Grimmond) on SUEWS/SuPy development. He is an active member of the UMEP consortium and maintains extensive international collaborations spanning Tsinghua University, Princeton, and numerous European research centres, underpinning a vibrant, interdisciplinary research network focused on urban climate resilience.
Chaopeng Shen is a Professor in the Department of Civil and Environmental Engineering at Pennsylvania State University. His research bridges hydrology with state-of-the-art deep learning and differentiable modeling techniques, focusing on advancing our understanding of hydrologic cycles and their interactions with ecosystems, energy, and carbon cycles. He leads the Multi-scale Hydrology, Processes and Intelligence group (MHPI) and has developed the Process-based Adaptive Watershed Simulator (PAWS) for large-scale hydrologic modeling. Shen's work emphasizes physics-informed machine learning , where deep learning components are integrated with process-based equations through differentiable modeling. This approach enables training neural networks using big data while respecting physical laws, leading to improved generalizability and robustness. His group has demonstrated advantages of differentiable models in rainfall-runoff prediction, routing, ecosystem modeling, and water quality studies. Notably, his team's deepLDB project addresses landslide prediction using AI and big datasets. Recent publications highlight his contributions to global water modeling (grid-LSTM, differentiable Muskingum-Cunge routing), extreme flood forecasting (probabilistic diffusion models), and hydrologic uncertainty quantification . Shen actively engages in interdisciplinary collaborations through the PRISM Cooperative Institute, which aims to integrate multi-domain data for systemic risk assessment. His group has advised students including Dapeng Feng, Wen-Ping Tsai, Kuai Fang, Xinye Ji, and Tasnuva Mahjabin. Shen's research is supported by the National Science Foundation (NSF), Department of Energy (DoE), USGS, Google.org, and the Gates Foundation. He serves as Editor for the Journal of Geophysical Research - Machine Learning & Computation and Chief Editor for Frontiers in Water: Water & AI. His open-source software tools like PAWS and deepLDB are available through dedicated project websites.
