Organization
University of Illinois at Urbana-Champaign
Email
Business Phone
Work
(217) 333-3080
Business Address
Department of Atmospheric Sciences
1301 W Green Street
Urbana, IL 61801
United States
First Author Publications
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Di Girolamo, L., et al. (2021), and the CAMP2Ex Science Team, Data Fusion Visualization for the NASA CAMP2Ex Field Campaign..
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Di Girolamo, L., et al. (2010), A global view of one‐dimensional solar radiative transfer through oceanic water clouds, Geophys. Res. Lett., 37, L18809, doi:10.1029/2010GL044094.
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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.
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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.
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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.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
Co-Authored Publications
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Berman, M.T., et al. (2024), The Observed Impact of the Lower Stratospheric Thermodynamic Environment on Overshooting Top Characteristics During the RELAMPAGO‐CACTI Field Campaign, J. Geophys. Res., 129, e2023JD040348, doi:10.1029/2023JD040348.
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De Vera, M.V., et al. (2024), Observations of the macrophysical properties of cumulus cloud fields over the tropical western Pacific and their connection to meteorological variables, Atmos. Chem. Phys., doi:10.5194/acp-24-5603-2024.
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Lorenzo, G.R., et al. (2024), An emerging aerosol climatology via remote sensing over Metro Manila, the Philippines, Atmos. Chem. Phys., doi:10.5194/acp-23-10579-2023.
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Stubenrauch, C., et al. (2024), Lessons Learned from the Updated GEWEX Cloud Assessment Database Claudia J. Stubenrauch1 · Stefan Kinne2 · Giulio Mandorli1 · William B. Rossow3 · David M. Winker4 · Steven A. Ackerman5 · Helene Chepfer1 · Larry Di Girolamo6 · Anne Garnier4,7 · Andrew Hei, Surv. Geophys., doi:10.1007/s10712-024-09824-0.
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Hong, Y., et al. (2023), Near-global distributions of overshooting tops derived from Terra and Aqua MODIS observations, Atmos. Meas. Tech., 16, 1391-1406, doi:10.5194/amt-16-1391-2023.
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Loveridge, J., et al. (2023), Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization, Atmos. Meas. Tech., 16, 3931-3957, doi:10.5194/amt-16-3931-2023.
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Loveridge, J., et al. (2023), Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 1: Model description and Jacobian calculation, Atmos. Meas. Tech., 16, 1803-1847, doi:10.5194/amt-16-1803-2023.
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Mitra, A., et al. (2023), Fusion of MISR Stereo Cloud Heights and Terra-MODIS Thermal Infrared Radiances to Estimate Two-Layered Cloud Properties, J. Geophys. Res..
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Roy, P., et al. (2023), A Closer Look at the Evolution of Supercooled Cloud Droplet Temperature and Lifetime in Different Environmental Conditions with Implications for Ice Nucleation in the Evaporating Regions of Clouds, J. Atmos. Sci., 80, 2481-2501, doi:10.1175/JAS-D-22-0239.1.
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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.
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Dutta, S., et al. (2021), The Reduction in Near‐Global Cloud Cover After Correcting for Biases Caused by Finite Resolution Measurements, Geophys. Res. Lett..
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Fromm, M., et al. (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.
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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.
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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.
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Alexandra, ., 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.
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Foster, M.J., et al. (2018), State of the Climate in 2017: Cloudiness, Bull. Am. Meteor. Soc., 99, S31-S33.
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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.
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Lee, B., et al. (2018), Three-Dimensional Cloud Volume Reconstruction from the Multi-angle Imaging SpectroRadiometer, doi:10.3390/rs10111858.
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Wang, Y., et al. (2018), Inference of an Optimal Ice Particle Model through Latitudinal Analysis of MISR and MODIS Data, doi:10.3390/rs10121981.
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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.
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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.
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Foster, M.J., et al. (2017), State of the Climate in 2016: Cloudiness, Bull. Am. Meteor. Soc., 98, S27-S28.
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Mueller, ., 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.
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Foster, M.J., et al. (2016), State of the Climate: Cloudiness, Bull. Am. Meteor. Soc., 97, S17-S18.
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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.
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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.
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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.
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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.
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Liang, L., et al. (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.
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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.
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Reid, J.S., 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.
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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.
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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.
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Jones, A.L., et al. (2012), Reducing the resolution bias in cloud fraction from satellite derived clear-conservative cloud masks, J. Geophys. Res., 117, D12201, doi:10.1029/2011JD017195.
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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.
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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.
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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.
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Liang, L., et al. (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.
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Snodgrass, E.R., et al. (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.
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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.
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Dey, S., et al. (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.
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Mueller, K.J., et al. (2008), Stereo observations of polar stratospheric clouds, Geophys. Res. Lett., 35, L17813, doi:10.1029/2008GL033792.
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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.
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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.
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Yang, Y., et al. (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.
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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.
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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.
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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.
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McFarquhar, G.M., 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.
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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.
