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Larry Di Girolamo

University of Illinois at Urbana-Champaign

Atmospheric Sciences


Guangyu Zhao, Muqun Yang, Yizhao Gao, Yizhe Zhan, H. Joe Lee, and Larry Di Girolamo (2020): PYTAF: A Python Tool for Spatially Resampling Earth Observation Data, Earth Science Informatics (in press), Springer Nature Switzerland AG


Yi Wang, Ping Yang, Souichiro Hioki, Michael D. King, Bryan A. Baum, Larry Di Girolamo, and Dongwei Fu (2019): Ice Cloud Optical Thickness, Effective Radius, And Ice Water Path Inferred From Fused MISR and MODIS Measurements Based on a Pixel-Level Optimal Ice Particle Roughness Model, Journal of Geophysical Research: Atmospheres, John Wiley and Sons, Inc, Vol 124, Num 22, pp12126-12140
Dongwei Fu, Larry Di Girolamo, Lusheng Liang, and Guangyu Zhao (2019): Regional Biases in MODIS Marine Liquid Water Cloud Drop Effective Radius Deduced Through Fusion With MISR, Journal of Geophysical Research: Atmospheres, American Geophysical Union, Vol 124, Num 23, pp13182-13196


Yizhe Zhan, Larry Di Girolamo, Roger Davies, and Catherine Moroney (2018): Instantaneous Top-of-Atmosphere Albedo Comparison between CERES and MISR over the Arctic, Remote Sensing, Multidisciplinary Digital Publishing Institute, Vol 10, Num 12, pp1882
Yi Wang, Souichiro Hioki, Ping Yang, Michael D. King, Larry Di Girolamo, Dongwei Fu, and Bryan A. Baum (2018): Inference of an optimal ice particle model through latitudinal analysis of MISR and MODIS data, Remote Sensing, Multidisciplinary Digital Publishing Institute, Vol 10, Num 12, pp1981
Alexandra L. Jones and Larry Di Girolamo (2018): Design and Verification of a New Monochromatic Thermal Emission Component for the I3RC Community Monte Carlo Model, Journal of the Atmospheric Sciences, American Meteorological Society, Vol 75, Num 3, pp885-906


Alexandra L. Jones (2017): Alexandraljones/Imc-Emission: Code Base Plus Select Benchmark Results, Zenodo, Zenodo (website)


Guangyu Zhao, Larry Di Girolamo, David J. Diner, Carol J. Bruegge, Kevin J. Mueller, and Dong L. Wu (2016): Regional Changes in Earth's Color and Texture as Observed from Space Over a 15-Year Period, IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, Vol 54, Num 7, pp4240-4249
Alexandra L. Jones (2016): Development of an Accurate 3D Monte Carlo Broadband Atmospheric Radiative Transfer Model, University of Illinois at Urbana-Champaign, Illinois Digital Environment for Access to Learning and Scholarship, Vol Doctoral dissertation


Lusheng Liang, Larry Di Girolamo, and Wenbo Sun (2015): Bias in MODIS Cloud Drop Effective Radius for Oceanic Water Clouds as Deduced from Optical Thickness Variability Across Scattering Angles, Journal of Geophysical Research: Atmospheres, Wiley-Blackwell, Vol 120, Num 15, pp7661--7681


Larry Di Girolamo, Matias Carrasco Kind, Gregory Daues, Yulan Hong, Ralph Kahn, Lusheng Liang, Donald Petravick, John Towns, Kent Yang, Ping Yang, Yizhe Zhan, Guangyu Zhao (2019): Petascale Processing of Satellite Earth Observations, 2019 Blue Waters Annual Report, pp80-81


Larry Di Girolamo (2018): THE TERRA DATA FUSION PROJECT, Blue Waters annual-book summary slide
Larry Di Girolamo, John Towns, Shaowen Wang, Guangyu Zhao, Kent Yang, Yan Liu (2018): The Terra Data Fusion Project, 2018 Blue Waters Annual Report, pp86-87


Larry Di Girolamo (2017): The Terra Data Fusion Project, Blue Waters annual-book summary slide
Larry Di Girolamo (2017): The Terra Data Fusion Project, 2017 Blue Waters Annual Report, pp68-69


Larry Di Girolamo (2015): Global Observations of Cloud Microphysics through Terra Data Fusion, 2015 Blue Waters Annual Report, pp40-41

Yi Wang: Seasonal Bias of Retrieved Ice Cloud Optical Properties Based on MISR and MODIS Measurements

American Geophysical Union (AGU) Fall 2017 Meeting; New Orleans, Louisiana, U.S.A., Dec 13, 2017

Dongwei Fu: The Observed Behavior of the Bias in MODIS-retrieved Cloud Droplet Effective Radius through MISR-MODIS Data Fusion

American Geophysical Union (AGU) Fall 2017 Meeting; New Orleans, Louisiana, U.S.A., Dec 12, 2017

Larry Di Girolamo: The Terra Data Fusion Project: An Update

American Geophysical Union (AGU) Fall 2017 Meeting; New Orleans, Louisiana, U.S.A., Dec 11, 2017

Alexandra L. Jones: Development of a Highly Accurate 3D Radiative Transfer Model

University of Illinois Atmospheric Sciences Colloquia Series, Apr 1, 2015

Alexandra Jones and L. Di Girolamo: A New Spectrally Integrating 3D Monte Carlo Radiative Transfer Model

American Meteorological Society 14th Conference on Atmospheric Radiation; Boston, Massachusetts, U.S.A., Jul 10, 2014

Blue Waters Supercomputer Processes New Data for NASA’s Terra Satellite

Dec 15, 2017

Researchers are using the Blue Waters supercomputer at NCSA to process new data from NASA’s Terra Satellite. Approximately the size of a small school bus, the Terra satellite explores the connections between Earth’s atmosphere, land, snow and ice, ocean, and energy balance to understand Earth’s climate and climate change and to map the impact of human activity and natural disasters on communities and ecosystems.


14 Illinois researchers selected for NCSA Fellowships

May 11, 2015

Fourteen faculty members at the University of Illinois at Urbana-Champaign have been selected to receive one-year fellowships that will enable their research teams to pursue collaborative projects with the National Center for Supercomputing Applications. NCSA's fellowship program aims to catalyze and develop long-term collaborations between the center and campus researchers, particularly in the center's six thematic areas of research: Bioinformatics and Health Sciences, Computing and Data Sciences, Culture and Society, Earth and Environment, Materials and Manufacturing, and Physics and Astronomy.


3 Ways Big Data, Supercomputing Change Weather Forecasting

Jun 9, 2014

So while we're not able to control the weather, better forecasting will allow us to make more informed plans that can limit financial losses, provide new business opportunities, reduce government spending, and even save lives. Unfortunately, improving our ability to predict the weather is challenging, both scientifically and computationally. Supercomputing has played a major role in enabling predictive models since the 1950s and remains at the cornerstone of today's weather and climate modeling. Constantly improving computational capabilities have allowed scientists and forecasters to produce results faster than ever while also investigating increasingly complex phenomena and producing specialized forecast products. From model performance to system and data management, weather prediction presents unique high-performance computing challenges.


12 Illinois faculty awarded prestigious Blue Waters Professorships

Feb 4, 2014

Twelve University of Illinois faculty members from a range of fields have been selected as Blue Waters Professors, an honor that comes with substantial computing and data resources on the Blue Waters supercomputer at the university’s National Center for Supercomputing Applications (NCSA).


22 Illinois projects receive time on Blue Waters

Jun 11, 2013

The University of Illinois at Urbana-Champaign has awarded access to the Blue Waters supercomputer—which is capable of performing quadrillions of calculations every second and of working with quadrillions of bytes of data—to 22 campus research teams from a wide range of disciplines. The computing and data capabilities of Blue Waters, which is operated by the National Center for Supercomputing Applications (NCSA), will assist researchers in their work on understanding DNA, developing biofuels, simulating climate, and more.