Dr. Zhenguang Huang is an assistant research scientist in the department of Climate and Space Sciences and Engineering. His research focus is on 3-D global five- and six-moment multi-fluid simulations, and 3-D global multi-ion MHD simulations of the space plasma. He is also one of the main developers of the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme (BATSRUS) and the Space Weather Modeling Framework (SWMF).
Dr. Lulu Zhao is an assistant research scientist in the Climate and Space Sciences and Engineering. Her research focus is the modelling of the acceleration and transport of energetic particles using M-FLAMPA (multiple-field-line-advection-model with particle acceleration). The M-FLAMPA model extract magnetic field lines from the magnetohydrodynamics (MHD) simulations of the background solar wind solution through SWMF (space weather frame work). Along those magnetic field lines, the particle transport and acceleration are modelled by solving the particle transport equations.
Modeling space physics and predicting space weather with a combination of first-principles models, machine learning and data assimilation.
Gabor Toth, Climate and Space Sciences and Engineering
Shasha Zou is an Associate Professor of Climate and Space Science and Engineering. Her general research interest is about studying the dynamic interaction between the Sun’s extended atmosphere, i.e., solar wind, and the near-Earth space environment. In particular, she is interested in the physical processes of formation and evolution of ionospheric structures and their impact on technology, such as global navigation and communication satellite system (GNSS), during space weather disturbances using multi-instrument observations and numerical models. Numerical models often used include magnetohydrodynamic (MHD) model of the global magnetosphere, and physics-based global ionosphere and thermosphere model.
Ricky Rood is a Professor of Climate and Space Sciences and Engineering. His current research and teaching focus is on climate change and its repercussions in society. His research history includes numerical modeling of trace constituents and atmospheric dynamics. He was director of NASA’s Center for Computational Science at Goddard Space Flight Center. He is currently consulting with NOAA on the Next Generation Global Prediction System.
Professor Rood is an active member of the climate science community, working on strategic approaches to the climate-change problem solving. He writes blogs for Wunderground.com and Climatepolicy.org and he is a main contributor of The Climate Workspace project, glisaclimate.org, a site that supports an online community of people working to address climate change questions and problems.
Allison Steiner is a Professor of Climate and Space Sciences and Engineering. Her research focus is on the relationship between the atmosphere and the terrestrial biosphere to help understand the bigger question: how will the Earth respond to climate change? Her research integrates gas and particulate matter, including anthropogenic aerosols and natural aerosols such as pollen, into high-resolution models. She and her research group then compare these results with observations to develop a comprehensive understanding of regional scale climate and atmospheric chemistry.
His research makes use of rich information contained in the spectrally resolve observations (chiefly from space) to probe the climate system and gauge the performance of climate models. Topics of his ongoing projects include formulation and design of climate monitoring system based on accurate in-flight calibration system, spectrally resolved radiation budget and radiative feedbacks, detecting spectral signals of climate changes, and model evaluations using spectral data set. In the course of such studies, huge amount of data sets from observations or climate model simulations are fed into radiative transfer model to general spectral radiances at thousands of channels for each grid on the globe and for each time interval. To accurately and efficiently carry out such calculation is only possible with massive high performance computing and, as of today, such task is still computationally challenging.
Most of his research and teaching involves parallel computing of some form: design of scalable algorithms and data structures; applications to numerous scientific problems such as a large multidisciplinary team modeling space weather or a small interdisciplinary group doing imputation on datasets of social preferences; and performance analysis, both experimental and analytical. These projects have used a variety of computer architectures, ranging from tens to hundreds of thousands of cores. He also works on algorithms for abstract fine-grain parallel computer models motivated by concerns such as time/number-of-processors/peak-power tradeoffs and the constraints imposed by the fact that computation is done in 2- or 3-dimensional space. Further, he develops serial algorithms for optimizing adaptive sampling problems such as adaptive clinical trials, algorithms for isotonic regression, and various other computer science problems.