UAE Research Program for Rain Enhancement Science Collaborators


Center for Western Weather and Water Extremes



Dr. Luca Delle Monache

University of California San Diego

Deputy Director of the Center for Western Weather and Water Extremes

Role

Dr. Luca Delle Monache is the project PI. He will manage the project and lead the development, testing, and deployment of the new machine learning (ML) framework. Will interact with sponsor to assure that the generated products support the sponsor’s mission and will co-author reports and scientific publications.

Bio

Dr. Luca Delle Monache is the Deputy Director of the Center for Western Weather and Water Extremes (CW3E), Scripps Institute of Oceanography, University of California San Diego. He is responsible to develop new science and application directions to support CW3E’s Vision and Mission. Specifically, Dr. Delle Monache oversees the development of the Center’s modeling, data assimilation, postprocessing, and artificial intelligence capabilities, with the goal of maintaining state-of-the-art models and tools while actively exploring innovative algorithms and approaches. In close coordination with the Center Director and the management team, he develops new scientific and programmatic strategies to maintain and further expand CW3E leadership on understanding, observing, and predicting extreme events in Western North America and other regions across the world.

He earned a Laurea (~M.S.) in Mathematics from the University of Rome, Italy (1997), an M.S. in Meteorology from the San Jose State University, U.S. (2002), and a Ph.D. in Atmospheric Sciences from the University of British Columbia, Canada (2005). His interests include the design of ensemble methods, probabilistic prediction and uncertainty quantification, numerical weather prediction, data assimilation, inverse modeling, postprocessing methods including artificial intelligence algorithms, renewable energy, air quality and transport and dispersion modeling. Among his main scientific accomplishments, there is the development during his Ph.D. of the first ensemble for air quality prediction, and later in his career the design of the analog ensemble which has been applied successfully in several of the fields, and is based on a new paradigm for ensemble design. Dr. Delle Monache has been the principal investigator of several multi-institution multi-million projects funded by the National Science Foundation, the National Oceanic and Atmospheric Administration, the National Aeronautics and Space Administration, the Department of Energy, the Department of Defense, and the private sector. Before joining CW3E, he was a postdoc and then a staff scientist at the Lawrence Livermore National Laboratory, Livermore, California (2006-2009), and a project scientist and then the Science Deputy Director of the National Security Applications Program at the National Center for Atmospheric Research, Boulder, Colorado (2009-2018).

Dr. Duncan Axisa

University of California San Diego

Program Manager at the Center for Western Weather and Water Extremes

Role

Dr. Axisa is the project Co-PI. He will co-lead the design of AI framework and ensure that the method’s perspective is based on the physical processes of precipitation. Dr. Axisa will coordinate the research on identifying key variables important to cloud seedability and ensure that appropriate cloud features are extracted during data processing. He will co-lead the validation and deployment of AI-RAO. Dr. Axisa will coauthor reports and scientific publications. He will be involved with project management, team coordination and liaise with sponsor.

Bio

Dr. Duncan Axisa is a Program Manager at the Center for Western Weather and Water Extremes (CW3E) at the Scripps Institution of Oceanography (SIO) University of California San Diego (UCSD). He supports senior management in leadership and direction of the Center’s growing research and applications capabilities, by assisting in developing and executing program research goals. Duncan provides critical support to the Forecast Informed Reservoir Operations (FIRO) program: a key activity that develops new science, technology, and numerical modeling tools to aid future reservoir operations for flood control, water supply, and ecosystems.

Dr. Axisa has extensive experience leading scientific programs, multi-institutional collaborative efforts to design major experiments and research centered on aerosol-cloud-precipitation interactions and weather modification. After spending a decade at the National Center for Atmospheric Research’s Research Applications Laboratory (RAL) Hydrometeorological Applications Program and several years in a scientific instrumentation company, Duncan has served the science community in highly collaborative, entrepreneurial, and externally funded research and technology transfer roles. As a scientist, Dr. Axisa’s experience focuses on measurements of aerosol, cloud, and precipitation properties, and in evaluating the performance of numerical models.

Among his main scientific accomplishments are measurements of the impacts of pollution aerosols on clouds in the Sierra Nevada, characterization of aerosol-cloud interactions in pre-monsoon and monsoon clouds in South Asia, microphysical interactions of dust with pollution and clouds in Saudi Arabia, observations and modeling of convection-associated dust outbreaks over the Arabian Peninsula, measurements of newly formed particles in the mid-latitude upper troposphere, and source identification of ice nucleating particles. He has participated in over 30 field campaigns including NASA- and NSF-funded studies of aerosol impacts on clouds and precipitation. He has published breakthrough research in hygroscopic seeding and documented unambiguously the cloud seeding effect in convective clouds. His recent publications include “A large source of cloud condensation nuclei from new particle formation in the tropics” in Nature (2019) and “A biogenic secondary organic aerosol source of cirrus ice nucleating particles” in Nature Communications (2020). Dr. Axisa received the Weather Modification Association (WMA) Field Meteorologist Distinguished Service Award and the prestigious Weather Modification Association (WMA) Thunderbird Award “for fundamental contributions to the art and science of weather modification”. He has served as a Member of the American Meteorological Society (AMS) Committee on Planned and Inadvertent Weather Modification during 2005 –2012 and again from 2018 – present.

Dr. Axisa holds a BEd from University of Malta, BS in Meteorology and MS in Atmospheric Science from Texas A&M University, and a PhD in Engineering from University of Denver.

Dr. Zhenhai Zhang

University of California San Diego

Staff Researcher at the Center for Western Weather and Water Extremes

Role

Dr. Zhang will work on the generation of seedable cloud features. He will use detailed research aircraft measurements for a few case studies of seedable clouds, including both hygroscopic (warm cloud) and glaciogenic (cold cloud) seeding. Then he will match those cloud cases with selected Numerical Weather Prediction (NWP), satellite, and radar datasets and extract physical properties from those datasets to describe seeding targets. The final goal of his work is to establish the criteria for “good” and “bad” seeding targets with a combination of those datasets.

Bio

In 2017, Dr. Zhang joined the Center for Western Weather and Water Extremes (CW3E) at Scripps Institution of Oceanography, the University of California San Diego. As a staff researcher, Dr. Zhang’s research mainly focuses on the relationship between atmospheric rivers and extratropical cyclones, as well as their impacts on extreme weather. Both storms are of vital importance to the local weather and regional climate during cool seasons over the U.S. West Coast and their interactions are critical to the extreme weather events. His work quantified the relationship between these two major winter storms. Dr. Zhang’s research also includes subseasonal-to-seasonal predictability of atmospheric rivers, precipitation, and temperature. He has been contributing to the development of the CW3E Subseasonal AR Outlook with forecasts from four state-of-the-art dynamic model centers.

Before joining CW3E, Dr. Zhang earned his Ph.D. in Atmospheric Science at the State University of New York at Stony Brook in 2016. During the Ph.D. program, he evaluated the historical performance and future predictions of extratropical cyclones under climate change using the simulations of global climate models from the IPCC Coupled Model Intercomparison Project Phase 5. He also developed a high-resolution downscaling method with Weather Research & Forecasting Model (WRF) to dynamically downscaled the simulation of climate models to better understand the future changes of the physical and dynamical process of extratropical cyclones under climate change.

Dr. Vesta Afzali Gorooh

University of California San Diego

Postdoc at the Center for Western Weather and Water Extremes

Role

Dr. Afzali Gorooh will work closely with PI Luca Delle Monache, managing the project. She will interact with sponsors to ensure that the generated products support the sponsor’s mission and will co-author reports and scientific publications. Also, she will be involved with developing cloud-patch feature extraction for cloud seedability, quantitative precipitation estimation (QPE) products at high spatiotemporal resolution, and generating short-term precipitation forecasts.

Bio

Dr. Afzali Gorooh is a Postdoctoral Scholar-Employee at the Center for Western Weather and Water Extremes (CW3E) at Scripps Institution of Oceanography, the University of California San Diego, where she joined in January 2023. She focuses on satellite remote sensing for the development of quantitative precipitation estimation and generating short-term precipitation forecasts at high spatiotemporal resolution using machine learning techniques. This research aligns with her Ph.D. work, which she completed in Civil and Environmental Engineering in December 2022 at the Civil and Environmental Engineering Ph.D. program at UC Irvine, under the supervision of Prof. Soroosh Sorooshian in the Center for Hydrometeorology and Remote Sensing.

During her Ph.D., Vesta was named a Future Investigator by NASA Earth and Space Science and Technology to develop deep neural networks for cloud type classification and surface precipitation estimation using new generation of geostationary satellites. She worked as an intern at NASA Ames in 2018 and at Cooperative Institute for Satellite Earth System Studies (CISESS) /Earth System Science Interdisciplinary Center (ESSIC) in 2022 while completing her graduate degree. To date, she has produced over a dozen scientific articles, which have been disseminated in peer-reviewed scientific and technical journals.

At CW3E, she will continue her work through widespread collaboration, peer-reviewed journal publications, and international conference presentations.

Dr. Vaghef Ghazvinian

University of California San Diego

Postdoc at the Center for Western Weather and Water Extremes

Role

Dr. Ghazvinian will develop the proposed AI framework and algorithms. He will lead the technical work and ensure that the proposed method is based on suitable and advanced Deep Learning algorithms capable of processing diverse and comprehensive datasets to extract key features for cloud seedability. He will co-lead the validation and deployment of AI-RAO. He will lead and co-author methodology and scientific sections based on relevant published peer reviewed journals.

Bio

Dr. Vaghef Ghazvinian is a postdoctoral scholar at CW3E, Scripps institution of oceanography, UCSD. He focuses on development of machine learning prediction tools for extreme weather and water events under supervision of Dr. Luca Delle Monache. His research outcome will support CW3E’s objectives in improving precipitation and flash flood decision support systems and forecast informed reservoir operations. His research interests include hydrometeorological forecast postprocessing, probabilistic forecasting and mathematical methods for forecast verification.

Before joining CW3E, he received his PhD in Civil Engineering-Water Resources from the University of Texas at Arlington under the supervision of Dr. Yu Zhang. Through his PhD, he has specialized in earth and hydrometeorological data processing and computer programming, large scale, highly detailed and computationally efficient weather/water forecast computations, advanced statistical modeling with machine learning and deep learning for weather/water forecasting. He has focused primarily on developing statistical postprocessing models to improve medium-range precipitation/flood forecasts from state-of-the-art operational/research-based schemes. His proposed methods adequately address practical limitations in current mechanisms and improve their robustness and efficacy, in particular forecasts accuracy for heavy-to-extreme, high impact events. He is among a few researchers in the field that has successfully improved the performance of probabilistic quantitative precipitation forecasting using end-to-end, computationally efficient deep learning frameworks. These frameworks allow for simultaneous generations of reliable and highly skillful postprocessed precipitation forecasts over multiple forecast horizons and seasons in a unified manner.

He intends to continue his work through widespread international collaboration and model-development efforts, peer-reviewed journal publications, conference presentations and invited talks.


Colorado State University


Dr. V Chandrasekar

Colorado State University

Professor of Electrical and Computer Engineering

University Distinguished Professor

Role

Dr. Chandra will be the lead radar scientist and nowcasting subject matter expert for this project. He will provide advice and supervise activities related to radar data processing, quality control, and algorithm development and interface to other non-weather radar areas of the project. He also will provide expertise on blending between nowcasting and forecasting domains linking AI and NWP techniques and technologies.

Bio

Dr. Chandrasekar (Chandra) has made pioneering contributions in the area of polarimetric radar observations of the atmosphere. Dr Chandra has extensive experience in Radar System Design, Radar Network Development, DSP Design as well as RF Communication Systems. He has contributed significantly to the areas weather radar and applications to Atmospheric Sciences. He also conducts research on related topics including Image Processing, Neural Network Applications and Large Scale System Simulation. He has organized and participated in six large multi-agency, national level experiments involving many radars, aircraft and ground instrumentation. He is an avid experimentalist conducting special experiments to collect in-situ observations to verify the new techniques and technologies. Dr Chandra is co-author of two textbooks, Polarimetric and Doppler Weather Radar (by Cambridge University Press) and Probability and Random Processes (by McGraw Hill). He has been a PI or Co-PI on several national level programs such as the Advanced Communication Technology Satellite (ACTS) program at CSU, DARPA NGI program, the current NASA TRMM mission and the future NASA GPM mission. He is currently a CO-PI of the CSU-CHILL radar facility and plays an important role in maintaining it as one of the most advanced meteorological radar systems in the world available for research, and continues to work actively with the CSU-CHILL radar supporting its research and education mission. He is a Co-PI and the Deputy director of the NSF Engineering Research Center, CASA (Center for Collaborative Adaptive Sensing of the Atmosphere), where he serves as the Research Director and provides leadership for the sensing research thrust. He has also been the Director of the prestigious and long-standing Research Experience for Undergraduate Program at Colorado State University. He was elected Fellow of IEEE, The American Meteorological Society and CIRA in recognition of his contributions to “Quantitative Remote Sensing”. He is a member of the National Academy of Sciences panel on “Future Radar Systems beyond NEXRAD” as well as the panel to assess “NEXRAD Flash Flood Forecasting Capabilities at Sulphur Mountain, California”. He has served as a visiting professor at the National research Council of Italy, as well as Distinguished Visiting Scientist at the NASA Goddard Space Flight Center. He has won numerous awards including, the NASA Technical innovation Award, 2002, Cermack Outstanding Advisor Award, 2001, Abell Outstanding Researcher Award, 2001, Distinguished Minority Service Award, 1999, Deans Council Award for Excellence in Teaching and Research, 1996, Halliburton Foundation Young Faculty Research Excellence Award, 1993, Vaisala Distinguished fellow and Abell Outstanding Research and Graduate Program Award, 2004.

Dr. Chandrasekar Radhakrishnan

Colorado State University

Research Scientist, Radar Laboratory

Role

Dr. C. Radhakrishnan will pre-process and quality control the weather radar data.

Bio

Dr. Radhakrishnan is currently a research scientist in the Radar Laboratory at Colorado State University. He got his bachelor’s and master’s degree from Anna University, India, during 2006 and 2009. He completed his Ph.D. in Mechanical Engineering at the Indian Institute of Technology, Madras (2013). After Ph.D. he joined IBM India Research Laboratory (IRL) and worked on operational weather and air quality forecasting. He worked in the prestigious Green Horizon project aimed at providing clean air and to increase the use of renewable energy for Beijing, China. He developed Ensemble Kalman Filter (EnKF) based assimilation system to assimilate MODIS satellite aerosol optical depth (AOD) and surface fine particulate matter (PM) 2.5 observations simultaneously into the Community Multiscale Air Quality Model (CMAQ) model to improve the air quality forecast. The project received an outstanding accomplishment award, and he won Manager’s choice award-2015 for his contribution. Subsequently, he worked towards developing an operational air quality forecast system based on NWP models and AI algorithms for Delhi Megacity. The project received the Regional General Manager Excellence Award, and he won Manager’s choice award-2016. He also led the team and developed a low-cost AI based tool for renewable energy forecast to support solar/wind farms. His current research focus is on AI techniques as applied to weather radar and satellite remote sensing applications.

Dr. Duncan Axisa

Colorado State University

Research Assistant, Radar Laboratory

Role

Specialist in machine learning techniques, including applications to Nowcasting and QPE and general radar processing. Kim will develop deep learning based nowcast model from weather radar images.

Bio

EunYeol Kim is currently a PhD scholar and a research assistant in the Radar Laboratory at Colorado State University. He got his Undergraduate degree from Sungkyunkwan University and Masters at Colorado State University. His research focus is on AI techniques as applied to weather radar applications.


Khalifa University


Dr. Ernesto Damiani

Khalifa University

Professor, Department of Electrical Engineering and Computer Science

Senior Director, Robotics & Intelligent Systems Institute

Director Of the Center for Cyber Physical Systems

Role

Dr. Ernesto Damiani will be leading the team from Khalifa University, who is responsible for Task 1 “Datasets Gathering and Quality Control” with a focus on satellite data, and Task 3 “Development of Real-time Prototype System for Analysis and Nowcasting”. He will work closely and coordinate the execution of the project with PI Luca Delle Monache and the rest of the team.

Bio

Dr. Ernesto Damiani is the Senior Director of Robotics and Intelligent Systems Institute at Khalifa University. He is also a Professor in the Electrical and Computer Engineering department and Director of the Khalifa University Center for Cyber Physical Systems (C2PS). Dr. Damiani is the Chair of the Information Security Program and a Research Professor in EBTIC. He is on extended leave from the Department of Computer Science, Università degli Studi di Milano, Italy, where he leads the SESAR research lab. He is also the President of the Italian Consortium of Computer Science Universities (CINI). Dr. Damiani’s research interests include secure service-oriented architectures, privacy-preserving Big Data analytics and Cyber-Physical Systems security. Dr. Damiani holds and has held visiting positions at a number of international institutions, including George Mason University in Virginia, US; Tokyo Denki University, Japan; LaTrobe University in Melbourne, Australia; and the Institut National des Sciences Appliquées (INSA) at Lyon, France. He is a Fellow of the Japanese Society for the Progress of Science.

He has been Principal Investigator in a number of large-scale research projects funded by the European Commission in the context of the Seventh Framework Program and Horizon 2020, the Italian Ministry of Research, and by private companies such as British Telecom, Cisco Systems, SAP, Telecom Italia, Siemens Networks (now Nokia Siemens) and many others. Dr. Damiani serves in the editorial board of several international journals; among others, he is the EIC of the IEEE Transactions on Service Computing, the International Journal on Big Data, and of the International Journal of Knowledge and Learning. Dr. Damiani serves as Associate Editor of the IEEE Trans. on Fuzzy Systems, of the IEEE Trans. on Services and of Multimedia Technology and Application (MTAP). He has served as Area Editor of the Journal of Systems Architecture. He is the Editor in Chief of the Intl. Journal of Knowledge and Learning. Ernesto guest edited special issues in many top research journals, including Soft Computing, ACM TOIT, FGCS, Computer in Human Behavior and many others. Dr. Damiani has been involved as General and Program Chair in the organization of many conferences and events worldwide, including several Dagstuhl schools. He is/has served as PC member in most major conferences in his area. He serves as the General Chair of IEEE Services conference series, the flagship event of IEEE TCS (including IEEE ICWS, SCC, SMDS), with more than 1000 submissions this year. Dr. Damiani is an ACM Distinguished Scientist (2008), and a Senior Member of the IEEE. He was awarded with the IFIP Outstanding Service Award (2011), the ACM SIGAPP Outstanding Service Award (2000). He received the IEEE IES Chester-Sall Award in 2007, and the IEEE ICWS/Service Society Stephen S. Yau Award in 2016. In 2017 Dr. Damiani received a doctorate honoris causa from INSA-Lyon for his contributions to research and teaching on Big Data. In 2021 he received the IEEE TCHS Research and Innovation Award. Dr. Damiani’s work has more than 20,100 citations on Google Scholar and more than 8,100 citations on Scopus, with an h-index of 37. With 588 publications listed on DBLP, he is considered among the most prolific European computer scientists.

Dr. Hussam Al Hamadi

Khalifa University

Research Scientist

Role

Dr. Al Hamadi will contribute to the data collection tasks, to build the historical data sets used to train machine learning methods.

Bio

Dr. Hussam Al Hamadi studied computer engineering at Ajman University where he graduated in 2005. He spent the period between 2005 and 2010 working as a computer consultant and tutor in several governmental and private institutions to eventually joined the Khalifa University as a teaching assistant in 2010. He holds several international certificates in networking, business, and tutoring, like MCSA, MCSE, CCNA, CBP, and CTP. In 2017, he received his Ph.D. degree in computer engineering from Khalifa University, where he is currently a research scientist in their Center for Cyber-Physical Systems (C2PS). His research interests focus on applied security protocols for several systems as software agents, SCADA, e-health systems and autonomous vehicles.

Bayan Banimfreg

Khalifa University, Center for Cyber Physical Systems

Postdoctoral Fellow

Role

In my position, I am primarily involved in collecting data to build datasets that play a critical role in training machine learning models. A key aspect of my responsibility is to preprocess and clean the collected data, ensuring that it is of high quality and reliability. In addition, I focus on leveraging data visualization techniques to enhance cloud seeding efforts. Overall, my work is essential in the process of gathering and maintaining high-quality datasets, and leveraging them for predictive modeling purposes.

Bio

Dr. Bayan Banimfreg holds a Bachelor of Science in Electrical Engineering from Yarmouk University in Jordan, which was completed in 2010. Later, Dr. Banimfreg completed a Master of Science in Electrical Engineering from the University of Texas at San Antonio in 2014, followed by an MBA from Webster University in 2016. Recently, Dr. Banimfreg completed a Ph.D. in Engineering System Management with a focus on big data analytics from the American University of Sharjah in 2022. Overall, Dr. Banimfreg's research interests lie in the areas of big data analytics, machine learning, and AI. Dr. Banimfreg is passionate about using these technologies to develop innovative solutions to complex problems.