CISL Cyberinfrastructure: Empowering Earth System Science Research

John Clyne is the Acting Director of CISL’s Technology Development Division (TDD) and the manager of its Visualization and Analysis Systems Technologies (VAST) section. TDD’s research and development efforts, in support of the NCAR science mission, span the creation of open-source community software tools, modernizing and improving the scalability and performance of earth system numerical models, exploring emerging technologies, and conducting applied research to advance computational science. John’s career at NCAR began in 1987 while completing his M.S. in Computer Science at the University of Colorado, Boulder. John’s long career at NCAR is driven by his passion for applying his broad technical expertise to the betterment of life on earth.

Visualization and Analysis Systems Technologies (VAST) Website

Sheri Voelz has over 20 years of experience as a research software engineer working on Earth Science models. Throughout her career, she has focused on accelerating modeling codes, workflows, and IO. Sheri currently manages a group of software engineers within CISL focused on porting NCAR models onto GPUs, optimizing IO workflows, and exploring future architectures. In addition, she is the lead software engineer on the EarthWorks project, which is focused on running climate simulations at storm-resolving resolutions. She is also passionate about mentoring underrepresented groups in computational science and advocating for research software engineers and their important roles in scientific discovery.

Application Scalability and Performance (ASAP) Website

Doug Schuster is the acting director of CISL’s Information Systems
Division (ISD) and manager of ISD’s Data Engineering and Curation
Section. ISD develops and maintains services that enable search and
discovery of NCAR’s data assets, support data-proximate computational
research, and provide long-term preservation and access to the rich
variety of observational data sets and model outputs produced and
hosted at NCAR. Additionally, ISD offers consulting services to its
data services users and assists NCAR researchers in developing data
management plans that meet community open science expectations. Doug
earned his bachelor’s degree in civil engineering at the University of
Minnesota, Twins Cities, and an M.S. in atmospheric science at
Colorado State University in Fort Collins.

NSF NCAR Research Data Archive 

NSF NCAR Data Search 

NSF NCAR Digital Asset Services Hub 

Thomas Cram is a Software Engineer III with the Data Engineering and Curation Section in the Computational and Information Systems Laboratory (CISL) at the NSF National Center for Atmospheric Research (NSF NCAR).  He is a member of a team that manages the NSF NCAR Research Data Archive (RDA), which is a large collection of reference datasets used for geoscience research.  Since his appointment at NSF NCAR in 2010, he has developed extensive expertise in data curation, data management, data web portal development, and data informatics.  Prior to joining NSF NCAR, Thomas received his Masters degree in Atmospheric Science from Colorado State University in 2000 and has a research background in tropical meteorology, global climate modeling, and tropical satellite applications.
 

NSF NCAR Research Data Archive 

NSF NCAR Data Search 

NSF NCAR Digital Asset Services Hub 

Dr. Nihanth Cherukuru is a Project Scientist in CISL working at the intersection of data visualizations, accessibility and user experience research. As an interdisciplinary applied researcher, his work focuses on the application of emerging technologies in the design of data visualizations to effectively communicate scientific findings to domain experts, policymakers, and the general public. He leads the Visualization Services and Research group (ViSR) at the NSF National Center for Atmospheric Research (NCAR) whose mission is to empower users of geoscience data to create user-centric data visualizations through visualization support and the development of VAPOR- a 3D data visualization application for geosciences. 

Keywords: Data visualization support, Web-interactives, 3D visualizations, VAPOR, science communication, User experience research.

Visualization and Analysis Systems Technologies (VAST) Website

Orhan Eroglu works at the NSF National Center for Atmospheric Research (NSF NCAR) in Boulder, CO as a Software Engineer III, leading the Geoscience Community Analysis Toolkit (GeoCAT) team. He manages the GeoCAT team's several research and development projects in the scientific Python ecosystem, ensuring the implementations are scalable and compatible with the Pangeo ecosystem as well as the community is involved throughout the project lifecycle with the help of an open development approach. UXarray (Project Raijin), GeoCAT-comp, GeoCAT-examples and GeoCAT-viz, and GeoCAT-applications are the software products that GeoCAT actively developes and maintains.

Orhan received his Ph.D. degree in electrical and computer engineering from Mississippi State University, USA in 2019, with his dissertation on physics-based, machine learning-aided information retrieval from satellite observatory using the GNSS Reflectometry technique. He received his B.Sc. and M.Sc. degrees in computer engineering from Bogazici University in 2009 and Turkish Air Force Academy in 2013, respectively, in Istanbul, Turkey.

Visualization and Analysis Systems Technologies (VAST) Website

After a postdoc at NCEP's Climate Analysis Center, Jeffrey Anderson spent the next decade at NOAA's GFDL building atmospheric models, developing software infrastructure for climate system models, and exploring ensemble prediction. Since 2001 he has been a scientist at NCAR, leading development of the Data Assimilation Research Testbed, a community software facility for ensemble data assimilation. He has developed a number of algorithms that facilitate high-quality ensemble data assimilation for geophysical problems.

Data Assimilation Research Testbed (DART) Website

Dr. David John Gagne II is a Machine Learning Scientist II and head of the Machine Integration and Learning for Earth Systems (MILES) group at the NSF National Center for Atmospheric Research (NCAR) in Boulder, Colorado. He has led the development of machine learning systems that enhance understanding and prediction of high impact weather and critical Earth system processes. He received his Ph.D. in meteorology from the University of Oklahoma in 2016 and completed an NCAR ASP Postdoctoral Fellowship before assuming his current role. He is a NSF AI2ES AI Institute leader and a NSF LEAP Science and Technology Center member. He is a WMO Nowcasting and Mesoscale Research Working Group member, chaired the American Meteorological Society Artificial Intelligence Committee, and serves as an editor for the AI for the Earth Systems journal, and has led summer schools, short courses, and hackathons.

Machine Integration and Learning for Earth Systems (MILES) Website

Moha Gharamti is a Scientist II at the Computational and Information Systems Laboratory (CISL) at the NSF National Center for Atmospheric Research (NSF NCAR). He earned his bachelor's degree in Geological Engineering from the Middle East Technical University in Ankara, Turkey, and later obtained his PhD in Earth Sciences and Engineering from King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. Following his PhD, he completed an 18-month postdoctoral fellowship at the Nansen Environmental and Remote Sensing Center (NERSC) in Bergen, Norway. Gharamti has been an integral part of NSF NCAR for 8 years, contributing significantly to the advancement of data assimilation (DA) science.

Gharamti's expertise lies in both sequential and variational data assimilation methodologies, with a particular focus on the ensemble Kalman filter (EnKF). His research centers on developing innovative, efficient, and robust DA algorithms applicable across a wide range of Earth system models. His contributions span various geoscience applications, including atmospheric science, ocean biogeochemistry, hydrologic forecasting, and flood prediction. He is one of the lead developers of the Data Assimilation Research Testbed (DART), a widely used tool within the academic community and internationally.

Data Assimilation Research Testbed (DART) Website

Dr. Negin Sobhani is an HPC consultant at the NSF National Center for Atmospheric Research (NSF-NCAR).  Her focus is on adopting emerging computational technologies to improve the performance and usability of earth system models and data analysis workflows.  She has extensive experience in HPC, Earth System Modeling, AI/ML, big data analysis, and interactive visualization, which enables her to assist users from diverse backgrounds in leveraging these technologies to advance their scientific endeavors.

Negin earned her Ph.D. in Chemical Engineering from the University of Iowa in 2017, where she focused on developing and optimizing regional weather and air quality models.  She began her full-time journey at NCAR as an Advanced Study Program (ASP) postdoctoral researcher and then worked in the Climate and Global Dynamics (CGD) division before her current role in the Computational and Information Systems Laboratory (CISL).

Throughout her tenure at NCAR, Negin has led various tutorials and has been a strong advocate for user needs. She is actively involved in organizing short courses, tutorials, workshops, and other training events, mentoring graduate students and postdocs, and serving on multiple committees. Negin has been a strong advocate for open science and reproducibility in geosciences and has been actively engaged in convergent science efforts, promoting interdisciplinary collaboration to tackle complex challenges in weather and climate research.
 

John Dennis received a PhD in computer science in 2005. He is a Scientist in the Computer Information and Systems Laboratory at the National Center for Atmospheric Research. He co-leads a research group that focuses on improving the ability of large-scale geoscience applications to utilize current and future computing platforms. His research interests include parallel algorithm and compiler optimization, graph partitioning, and data-intensive computing.

Application Scalability and Performance (ASAP) Website

Ben attended the University of Texas at Austin, earning his BS and PhD in Aerospace Engineering, with a MS in Computational & Applied Mathematics.  He worked at NASA’s Lyndon B. Johnson Space Center for 18 years prior to joining NCAR.  His background includes constructing and using HPC systems (compute and storage), particularly for fluid dynamics simulations.