ORACLES

Larry Di Girolamo

Organization:

University of Illinois at Urbana-Champaign

Email:

Contact person by email

Business Phone:

Work: (217) 333-3080

Business Address:

Department of Atmospheric Sciences

1301 W Green Street

Urbana, IL 61801

United States

Website:

http://www.atmos.illinois.edu/index.html

First Author Publications:

Di Girolamo, L., et al. (2021), and the CAMP2Ex Science Team, Data Fusion Visualization for the NASA CAMP2Ex Field Campaign..
Di Girolamo, L., L. Liang, and S. Platnick (2010), A global view of one‐dimensional solar radiative transfer through oceanic water clouds, Geophys. Res. Lett., 37, L18809, doi:10.1029/2010GL044094.
Di Girolamo, L. (2009), Satellite-Observed Location of Stratocumulus Cloud-Top Heights in the Presence of Strong Inversions Harshvardhan, Guangyu Zhao, Larry Di Girolamo, and Robert N. Green, IEEE Trans. Geosci. Remote Sens., 47, 1421-1428, doi:10.1109/TGRS.2008.2005406.
Di Girolamo, L. (2007), The spatial and temporal variability of aerosol optical depths in the Mojave Desert of southern California, Remote Sensing of Environment, 107, 54-64, doi:10.1016/j.rse.2006.06.024.
Di Girolamo, L., et al. (2004), Analysis of Multi-angle Imaging SpectroRadiometer (MISR) aerosol optical depths over greater India during winter 2001–– 2004, Geophys. Res. Lett., 31, L23115, doi:10.1029/2004GL021273.

Co-Authored Publications:

Fu, D., et al. (2022), An evaluation of the liquid cloud droplet effective radius derived from MODIS, airborne remote sensing, and in situ measurements from CAMP2 Ex, Atmos. Chem. Phys., doi:10.5194/acp-22-8259-2022.
Dutta, S., et al. (2021), The Reduction in Near‐Global Cloud Cover After Correcting for Biases Caused by Finite Resolution Measurements, Geophys. Res. Lett..
Mitra, A., et al. (2021), Assessment and Error Analysis of Terra-MODIS and MISR Cloud-Top Heights Through Comparison With ISSCATS Lidar, J. Geophys. Res., 126, e2020JD034281, doi:10.1029/2020JD034281.
Foster, M. J., et al. (2020), State of the Climate in 2019: Cloudiness [in “State of the Climate in 2019”], Bull. Am. Meteor. Soc., 101, S51-S53, doi:10.1175/BAMS-D-20-0104.1.
Hong, Y., and L. Di Girolamo (2020), Cloud phase characteristics over Southeast Asia from A-Train satellite observations Yulan Hong and Larry Di Girolamo Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, Atmos. Chem. Phys., 20, 8267-8291, doi:10.5194/acp-20-8267-2020.
Verstraete, M. M., et al. (2020), Replacing missing values in the standard Multi-angle Imaging SpectroRadiometer (MISR) radiometric camera-by-camera cloud mask (RCCM) data product, Earth Syst. Sci. Data, 12, 611-628, doi:10.5194/essd-12-611-2020.
Zhao, G., et al. (2020), SOFTWARE ARTICLE PYTAF: A Python Tool for Spatially Resampling Earth Observation Data, Earth Science Informatics, doi:10.1007/s12145-020-00461-w.
Chowdhury, S., et al. (2019), Tracking ambient PM2.5 build-up in Delhi national capital region during the dry T season over 15 years using a high-resolution (1 km) satellite aerosol dataset, Atmos. Environ., 204, 142-150, doi:10.1016/j.atmosenv.2019.02.029.
Chowdhury, S., et al. (2019), Indian annual ambient air quality standard is achievable by completely mitigating emissions from household sources, Proc. Natl. Acad. Sci., doi:10.
Foster, M. J., et al. (2019), State of the Climate in 2018: Cloudiness, Bull. Am. Meteor. Soc., 100, S34-S35, doi:10.1175/2019BAMSStateoftheClimate.1.
Fromm, M., D. Peterson, and L. Di Girolamo (2019), The Primary Convective Pathway for Observed Wildfire Emissions in the Upper Troposphere and Lower Stratosphere: A Targeted Reinterpretation, J. Geophys. Res., 124, 13,254-13,272, doi:10.1029/2019JD031006.
Fu, D., et al. (2019), Regional Biases in MODIS Marine Liquid Water Cloud Drop Effective Radius Deduced Through Fusion With MISR, J. Geophys. Res., 124, 13,182-13,196, doi:10.1029/2019JD031063.
Wang, Y., et al. (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, J. Geophys. Res., 124, doi:10.1029/2019JD030457.
Alexandra, L. J., and L. Di Girolamo (2018), Design and Verification of a New Monochromatic Thermal Emission Component for the I3RC Community Monte Carlo Model, J. Atmos. Sci., 75, 885-906, doi:10.1175/JAS-D-17-0251.1.
Foster, M. J., et al. (2018), State of the Climate in 2017: Cloudiness, Bull. Am. Meteor. Soc., 99, S31-S33.
Jovanovic, D. J. D. V., et al. (2018), Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA, Terms of Use, 12, 042603, doi:10.1117/1.JRS.12.042603.
Lee, B., et al. (2018), Three-Dimensional Cloud Volume Reconstruction from the Multi-angle Imaging SpectroRadiometer, doi:10.3390/rs10111858.
Wang, Y., et al. (2018), Inference of an Optimal Ice Particle Model through Latitudinal Analysis of MISR and MODIS Data, doi:10.3390/rs10121981.
Werner, F., et al. (2018), Improving cloud optical property retrievals for partly cloudy pixels using coincident higher-resolution single band measurements: A feasibility study using ASTER observations, J. Geophys. Res., 123, doi:10.1029/2018JD028902.
Zhan, Y., et al. (2018), Instantaneous top-of-atmosphere albedo comparison between CERES and MISR over the Arctic, Remote Sens., 10, 1882, doi:10.3390/rs10121882.
Foster, M. J., et al. (2017), State of the Climate in 2016: Cloudiness, Bull. Am. Meteor. Soc., 98, S27-S28.
Mueller, K. J., et al. (2017), Assessment of MISR Cloud Motion Vectors (CMVs) Relative to GOES and MODIS Atmospheric Motion Vectors (AMVs), J. Appl. Meteor. Climat., 56, 555-572, doi:10.1175/JAMC-D-16-0112.1.
Foster, M. J., et al. (2016), State of the Climate: Cloudiness, Bull. Am. Meteor. Soc., 97, S17-S18.
Werner, F., et al. (2016), Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS, Atmos. Meas. Tech., 9, 5869-5894, doi:10.5194/amt-9-5869-2016.
Zhang, Z., et al. (2016), A framework based on 2-D Taylor expansion for quantifying the impacts of subpixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method, J. Geophys. Res., 121, 7007-7025, doi:10.1002/2016JD024837.
Zhao, G., et al. (2016), Regional Changes in Earth’s Color and Texture as Observed From Space Over a 15-Year Period, IEEE Trans. Geosci. Remote Sens., 54, 4240-4249, doi:10.1109/TGRS.2016.2538723.
Cho, H., et al. (2015), Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans, J. Geophys. Res., 120, doi:10.1002/2015JD023161.
Liang, L., L. Di Girolamo, and W. Sun (2015), Bias in MODIS cloud drop effective radius for oceanic water clouds as deduced from optical thickness variability across scattering angles, J. Geophys. Res., 120, 7661-7681, doi:10.1002/2015JD023256.
Liang, L., and L. Di Girolamo (2013), A global analysis on the view-angle dependence of plane-parallel oceanic liquid water cloud optical thickness using data synergy from MISR and MODIS, J. Geophys. Res., 118, 1-18, doi:10.1029/2012JD018201.
Reid, J., et al. (2013), Observing and understanding the Southeast Asian aerosol system by remote sensing: An initial review and analysis for the Seven Southeast Asian Studies (7SEAS) program, Atmos. Res., 122, 403-468, doi:10.1016/j.atmosres.2012.06.005.
Stubenrauch, C. J., et al. (2013), Assessment Of Global Cloud Datasets From Satellites: Project and Database Initiated by the GEWEX Radiation Panel, Bull. Am. Meteorol. Soc., 1031-1049, doi:10.1175/BAMS-D-12-00117.1.
Dey, S., et al. (2012), Variability of outdoor fine particulate (PM2.5) concentration in the Indian Subcontinent: A remote sensing approach, Remote Sensing of Environment, 127, 153-161, doi:10.1016/j.rse.2012.08.021.
Jones, A. L., L. Di Girolamo, and G. Zhao (2012), Reducing the resolution bias in cloud fraction from satellite derived clear-conservative cloud masks, J. Geophys. Res., 117, D12201, doi:10.1029/2011JD017195.
Dey, S., and L. Di Girolamo (2011), A decade of change in aerosol properties over the Indian subcontinent, Geophys. Res. Lett., 38, L14811, doi:10.1029/2011GL048153.
Dey, S., et al. (2011), Satellite‐observed relationships between aerosol and trade‐wind cumulus cloud properties over the Indian Ocean, Geophys. Res. Lett., 38, L01804, doi:10.1029/2010GL045588.
Dey, S., and L. Di Girolamo (2010), A climatology of aerosol optical and microphysical properties over the Indian subcontinent from 9 years (2000–2008) of Multiangle Imaging Spectroradiometer (MISR) data, J. Geophys. Res., 115, D15204, doi:10.1029/2009JD013395.
Liang, L., L. Di Girolamo, and S. Platnick (2009), View-angle consistency in reflectance, optical thickness and spherical albedo of marine water-clouds over the northeastern Pacific through MISR-MODIS fusion, Geophys. Res. Lett., 36, L09811, doi:10.1029/2008GL037124.
Snodgrass, E. R., L. Di Girolamo, and R. M. Rauber (2009), Precipitation Characteristics of Trade Wind Clouds during RICO Derived from Radar, Satellite, and Aircraft Measurements, J. Appl. Meteor. Climat., 48, 464-483, doi:10.1175/2008JAMC1946.1.
Zhao, G., et al. (2009), Examination of direct cumulus contamination on MISR-retrieved aerosol optical depth and angstrom coefficient over ocean, Geophys. Res. Lett., 36, L13811, doi:10.1029/2009GL038549.
Dey, S., L. Di Girolamo, and G. Zhao (2008), Scale effect on statistics of the macrophysical properties of trade wind cumuli over the tropical western Atlantic during RICO, J. Geophys. Res., 113, D24214, doi:10.1029/2008JD010295.
Mueller, K. J., et al. (2008), Stereo observations of polar stratospheric clouds, Geophys. Res. Lett., 35, L17813, doi:10.1029/2008GL033792.
Yang, Y., and L. Di Girolamo (2008), Impacts of 3-D radiative effects on satellite cloud detection and their consequences on cloud fraction and aerosol optical depth retrievals, J. Geophys. Res., 113, D04213, doi:10.1029/2007JD009095.
Genkova, I., et al. (2007), Cloud top height comparisons from ASTER, MISR, and MODIS for trade wind cumuli, Remote Sensing of Environment, 107, 211-222, doi:10.1016/j.rse.2006.07.021.
Yang, Y., L. Di Girolamo, and D. Mazzoni (2007), Selection of the automated thresholding algorithm for the Multi-angle Imaging SpectroRadiometer Radiometric Camera-by-Camera Cloud Mask over land, Remote Sensing of Environment, 107, 159-171, doi:10.1016/j.rse.2006.05.020.
Zhao, G., and L. Di Girolamo (2007), Statistics on the macrophysical properties of trade wind cumuli over the tropical western Atlantic, J. Geophys. Res., 112, D10204, doi:10.1029/2006JD007371.
Brewer, J., and L. Di Girolamo (2006), Limitations of fractal dimension estimation algorithms with implications for cloud studies☆, Atmos. Res., 82, 433-454, doi:10.1016/j.atmosres.2005.12.012.
Zhao, G., and L. Di Girolamo (2006), Cloud fraction errors for trade wind cumuli from EOS-Terra instruments, Geophys. Res. Lett., 33, L20802, doi:10.1029/2006GL027088.
McFarquhar, G., et al. (2004), Trade wind cumuli statistics in clean and polluted air over the Indian Ocean from in situ and remote sensing measurements, Geophys. Res. Lett., 31, L21105, doi:10.1029/2004GL020412.
Zhao, G., and L. Di Girolamo (2004), A Cloud Fraction versus View Angle Technique for Automatic In-Scene Evaluation of the MISR Cloud Mask, J. Appl. Meteor., 43, 860-869.

Note: Only publications that have been uploaded to the ESD Publications database are listed here.

NASA - National Aeronautics and Space Administration

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ORACLES

Larry Di Girolamo