The Multi-angle Imaging SpectroRadiometer (MISR) mission is our group’s longest lasting project, starting when Prof. Di Girolamo arrived at Illinois in 1998. He actually began on the MISR mission in 1989 as a graduate student at McGill University. Back then, the MISR mission was in its pre-formulation phase – a time when MISR was competing to be one of the instruments for NASA’s new Earth Observing System flagship satellite called EOS-AM1 (which is now named Terra). Prof. Di Girolamo was at the Terra launch on December 19, 1999, and took this video:
MISR collects radiance measurements of the same scene from nine separate push-broom cameras in four solar spectral channels. Its mission is to exploit the information content in the angular anisotropy of scattered sunlight for studying aerosol, cloud and surface properties. You can learn more about MISR at the official MISR website hosted at JPL.
Our group is responsible for various components of the cloud detection, the cloud classification, and the cloud fraction by altitude algorithms. The MISR cloud products are generated, archived and distributed by the Atmospheric Science Data Center at the NASA Langley Research Center. Data access and full product description can be found here:
Our group led MISR’s contribution to and helped in the overall assessment of the Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment – the first internationally coordinated effort to compare publicly available, global cloud products retrieved from satellites. Here, we used MISR’s Cloud Fraction by Altitude (CFbA) product, but degraded to the required resolution of the assessment. You can learn more about the GEWEX Cloud assessment and access the database of cloud products by instrument here:
Our full report can be downloaded here: GEWEX_CA_2012.pdf.
As an example, the figure below shows the annual average (2001 -2017) total cloud fraction from the MISR CFbA product:
Our group also contributes to the annual AMS BAMS State of the Climate issues. The figure below from the 2019 issue shows annual average cloud cover and cloud cover anomalies from various satellite cloud products, including MISR. MISR indicates no trend in the annual average total cloud cover, with year-to-year variations having a standard deviation of only 0.27%
As you can see from our group’s publication record, we make great use of MISR cloud, aerosol, and radiation data for a wide range of studies. For example, the image below is from the first climatological study of aerosol optical depth from satellite over India that we published back in 2004 (Di Girolamo et al. 2004). Since then, we extended the climatological properties to include aerosol particle properties, how these properties have changed over the MISR record, and how they may be impacting human health. More needs to be done to address the impact of these aerosols on human health, so we helped paved the way for our next mission: the Multi-angle Imager for Aerosols (MAIA).
This project has received longterm support form the MISR mission project at the Jet Propulsion Laboratory under contract from NASA. Many of the publications listed below also include support from other grants from NASA or NSF and are listed in the acknowledgment section of the publications.
Peer-reviewed publications having MISR content
Fu, D., L. Di Girolamo, R.M. Rauber, G.M. McFarquhar, S.N. Nesbitt, J. Loveridge, Y. Hong, B. van Diedenhoven, B. Cairns, M.D. Alexandrov, P. Lawson, S. Woods, S. Tanelli, O.O. Sy, S. Schmidt, C.A. Hostetler, and A.J. Scarino, 2022: An evaluation of liquid cloud droplet effective radius derived from MODIS, airborne remote sensing and in situ measurements from CAMP2Ex, Atmos. Chem. Phys., 22, 8259-8285, 2022; https://doi.org/10.5194/acp-22-8259-2022
Foster, M.J., L. Di Girolamo, C. Phillips, M. Stengel, S. Sun-Mack, and G. Zhao, 2021: State of the Climate in 2020: Cloudiness [in “State of the Climate in 2020”], Bull. Am. Meteor. Soc., 102 (8), S61-S63, doi:10.1175/2021BAMSStateoftheClimate.1
Mitra, A., L. Di Girolamo, Y. Hong, Y. Zhan, and K.J. Mueller, 2021: Assessment and error analysis of Terra-MODIS and MISR cloud-top heights through comparison with ISS-CATS lidar. J. Geophys. Res. Atmos., 126, e2020JD034281. https://doi.org/10.1029/2020JD034281.
Dutta, S., L. Di Girolamo, S. Dey, Y. Zhan, C.M. Moroney, and G. Zhao, 2020: The reduction in near-global cloud cover after correcting for biases caused by finite resolution measurement. Geophys. Res. Lett, 47, e2020GL090313. https://doi.org/10.1029/2020GL090313.
Foster, M.J., L. Di Girolamo, R.A. Frey, A.K. Heidinger, S. Sun-Mack, C. Phillips, W.P. Menzel, M. Stengel, and G. Zhao, 2020: State of the Climate in 2019: Cloudiness [in “State of the Climate in 2019”], Bull. Am. Meteor. Soc., 101 (8), S51-S53, https://doi.org/10.1175/BAMS-D-20-0104.1
Zhao, G., M. Yang, Y. Gao, Y. Zhan, H.-K. Lee, and L. Di Girolamo, 2020: PYTAF: a python tool for spatially resampling Earth observation data. Earth Sci. Informatics, https://doi.org/10.1007/s12145-020-00461-w.
Verstraete, M., L.A. Hunt, H. De Lemos, and L. Di Girolamo, 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, https://doi.org/10.5194/essd-12-611-2020.
Fu, D., L. Di Girolamo, L. Liang, and G. Zhao, 2019: Regional Biases in Moderate Resolution Imaging Spectroradiometer (MODIS) marine liquid water cloud drop effective radius deduced through fusion with Multi-angle Imaging SpectroRadiometer (MISR). J. Geophys. Res. Atmos., 124, https://doi.org/10.1029/2019JD031063.
Wang, Y., P. Yang, S. Hioki, M.D. King, B.A. Baum, L. Di Girolamo, D. 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. J. Geophys. Res. Atmos., 124, https://doi.org/10.1029/2019JD030457.
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. Atmos., 124. https://doi.ord/10.1029/2019JD031006.
Foster, M.J., L. Di Girolamo, R.A. Frey, A.K. Heidinger, S. Sun-Mack, C. Phillips, W.P. Menzel, M. Stengel, and G. Zhao, 2019: State of the Climate in 2018: Cloudiness, Bull. Am. Meteor. Soc., 100 (9), S34-S35, doi:10.1175/2019BAMSStateoftheClimate.1.
Chowdhury, S., S. Dey, S. Guttikunda, A. Pillarisetti, K.R. Smith, and L. Di Girolamo, 2019: Indian air quality standard is achievable by completely mitigating emissions from household sources alone. Proceed. Nat. Acad. Sci., doi:10.1073/pnas.1900888116.
Chowdhury, S., S. Dey, L. Di Girolamo, K.R. Smith, A. Pillarisetti, and A. Lypapustin, 2019: Tracking ambient PM2.5 build-up in Delhi NCT during the dry season over 16 years using a high-resolution (1 km) satellite aerosol dataset. Atmos. Environ. 204, 142-150, doi:10.1016/j.atmosenv.2019.02.029.
Wang, Y., S. Hioki, P. Yang, M.D King, L. Di Girolamo, D. Fu, and B.A. Baum, 2018: Inference of an optimal ice particle model through latitudinal analysis of MISR and MODIS data. Remote Sens. 10(12), 1981, doi:10.3390/rs10121981.
Zhan, Y., L. Di Girolamo, R. Davies, and C. Moroney, 2018: Instantaneous top-of-atmosphere albedo comparison between CERES and MISR over the Arctic. Remote Sens. 10(12), 1882, doi:10.3390/rs10121882.
Lee, B., L. Di Girolamo, G. Zhao, and Y. Zhan, 2018: Three-dimensional cloud volume reconstruction from the Multi-angle Imaging SpectroRadiometer. Remote Sens. 10(11), 1858, doi:10.3390/rs10111858.
Diner, D.J., et al., 2018: Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA. J. Appl. Remote Sens. 12(4), 042603, doi: 10.1117/1.JRS.12.042603.
Foster, M.J., S.A. Ackerman, K. Bedka, L. Di Girolamo, R.A. Frey, A.K. Heidinger, S. Sun-Mack, C. Phillips, W.P. Menzel, M. Stengel, and G. Zhao, 2018: State of the Climate in 2017: Cloudiness, Bull. Am. Meteor. Soc., 99(8), S31-S33.
Foster, M.J., S.A. Ackerman, K. Bedka, L. Di Girolamo, R.A. Frey, A.K. Heidinger, S. Sun-Mack, C. Phillips, W.P. Menzel, P. Minnis, and G. Zhao, 2017: State of the Climate in 2016: Cloudiness, Bull. Am. Meteor. Soc., 98(8), S27-S28.
Mueller, K.J., D.L. Wu, A. Horvath, V.M. Jovanovic, J.-P. Mueller, L. Di Girolamo, M.J. Garay,D.J. Diner, C.M. Moroney, and S. Wanzong, 2017: Assessment of MISR Cloud Motion Vectors (CMVs) relative to GOES and MODIS Atmospheric Motion Vectors (AMVs). J. Appl. Meteor. Climatol., 56(3), 555-572, doi: 101175/JAMC-D-16-0112.1.
Foster, M.J., S.A. Ackerman, K. Bedka, R.A. Frey, L. Di Girolamo, A.K. Heidinger, S. Sun-Mack, B.C. Maddux, W.P. Menzel, P. Minnis, M. Stengel, and G. Zhao, 2016: State of the Climate: Cloudiness, Bull. Am. Meteor. Soc., 97(8), S17-S18.
Zhao, G., L. Di Girolamo, D.J. Diner, C.J. Bruegge, K. Mueller, and D.L. Wu, 2016: Regional changes in Earth’s color and texture as observed from space over a 15-year period. IEEE Trans. Geosci. Remote Sens.,54(7), 4240-4249, doi:10.1109/TGRS.2016.2538723.
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 angle. J. Geophys. Res. Atmos., 120, doi:10.1002/2015JD023256.
Stubenrauch, C.J., W.B. Rossow, S. Kinne, S. Ackerman, G. Cesana, H. Chepfer, L. Di Girolamo, B. Getzewich, A. Guignard, A. Heidinger, B. Maddux, P. Menzel, P. Minnis, C. Pearl, S. Platnick, C. Poulsen, J. Riedi, S. Sun-Mack, A. Walther, D. Winker, S. Zeng, and G. Zhao, 2013: Assessment of global cloud datasets from satellites: Project and Database initiated by the GEWEX Radiation Panel. Bull. Am. Meteor. Soc., 94, 1031 – 1049.
Liang, L., and L. Di Girolamo, 2013: A global analysis on the view-angle dependence of plane-parallel oceanic water cloud optical thickness using data synergy from MISR and MODIS. J. Geophys. Res. Atmos., 118, doi:10.1029/2012JD018201.
Reid, J.S., E.J. Hyer, R. Johnson, B.N. Holben, J. Zhang, J.R. Campbell, S.A. Christopher, L. Di Girolamo, L. Giglio, R.E. Holz, C. Kearney, J. Miettinen, E.A. Reid, F.J. Turk, J. Wang, P. Xian, R.J. Yokelson, G. Zhao, R. Balasubramanian, B.N. Chew, S. Janai, N. Lagrosas, P. Lestari, N.-H.Lin, M. Mahmud, B. Norris, A.X. Nguyen, N.T.K.Oahn, M. Oo, S. Salinas, and S.C. Liew, 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
Dey, S., L. Di Girolamo, A. van Donkelaar, S.N. Trapathi, T. Gupta, and M. Mohan, 2012: Variability of outdoor fine particulate (PM2.5) concentration in the Indian subcontinent: a remote sensing approach. Remote Sens. Environ., 127, 153-161.
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., L. Di Girolamo, G. Zhao, A.L. Jones, and G.M. McFarquhar, 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.
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.
Dey, S., and L. Di Girolamo, 2010: A climatology of aerosol optical and microphysical properties over the Indian Subcontinent from nine years (2000-2008) of Multiangle Imaging SpectroRadiometer (MISR) data. J. Geophys. Res., 115, D15204,doi:10.1029/2009JD013395.
Zhao, G., L. Di Girolamo, S. Dey, A.L. Jones, and M. Bull, 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.
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.
Harshvardhan, G. Zhao, L. Di Girolamo, and R.N. Green, 2009: Satellite-observed location of stratocumulus cloud-top heights in the presence of strong inversions. IEEE Trans. Geosci. Remote Sens., 47, 1421-1428.
Snodgrass, E.R., L. Di Girolamo, and R.M. Rauber, 2009: Precipitation characteristics of trade winds clouds during RICO derived from radar, satellite, and aircraft measurements. J. Appl. Meteor. Climatol.,48, 464-483.
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., L. Di Girolamo, M. Fromm, and S. Palm, 2008: Stereo observations of polar stratospheric clouds. Geophys. Res. Lett.,35, L17813, doi:10.1029/2008GL033792.
Rauber, R.M., B. Stevens, H.T. Ochs, C. Knight, B.A. Albrecht, A.M. Blyth, C.W. Fairall, J.B. Jensen, S. G. Lasher-Trapp, O. L. Mayol-Bracero, G. Vali, J. R. Anderson, B. A. Baker, A. R. Bandy, E. Burnet, J.-L. Brenguier, W. A. Brewer, P. R. A. Brown, P. Chuang, W. R. Cotton, L. Di Girolamo, B. Geerts, H. Gerber, S. Göke, L. Gomes, B. G. Heikes, J. G. Hudson, P. Kollias, R. P. Lawson, S. K. Krueger, D. H. Lenschow, L. Nuijens, D. W. O’Sullivan, R. A. Rilling, D. C. Rogers, A. P. Siebesma, E. Snodgrass, J. L. Stith, D. C. Thornton, S. Tucker, C. H. Twohy, and P. Zuidema, 2007: Rain In shallow Cumulus over the Ocean – The RICO campaign. Bull. Amer. Meteor. Soc., 88, 1912–1937.
Genkova, I., G. Seiz, G. Zhao, P. Zuidema, and L. Di Girolamo, 2007: Trade wind cumulus cloud top height comparisons from ASTER, MISR, and MODIS. Remote Sens. Environ.,107, 211-222.
Yang, Y., L. Di Girolamo, and D. Mazzoni, 2007: Selection of the automated thresholding algorithm for the Multi-angle Imaging SpectroRadiometer Camera-by-camera Cloud Mask over land. Remote Sens. Environ.,107, 159-171.
Frank, T.D., L. Di Girolamo, and S. Geegan, 2007: The spatial and temporal variability of aerosol optical depth in the Mojave Desert of southern California. Remote Sens. Environ.,107, 54-64.
Diner, D.J., L. Di Girolamo, and A. Nolin, 2007: Preface to the MISR Special Issue. Remote Sens. Environ.107, 1.
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
Di Girolamo, L., T. Bond, D. Bramer, D.J. Diner, F. Fettinger, R.A. Khan, J. Martonchick, M.V. Ramama, V. Ramanathan, and P. Rasch, 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.
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.
Di Girolamo, L., and M.J. Wilson, 2003: A first look at band-differenced angular signatures for cloud detection from MISR. IEEE Trans. Geosci. Remote Sens.41, 1730-1734.
Braverman, A. and L. Di Girolamo, 2002: MISR global data products: a new approach. IEEE Trans. Geosci. Remote Sens. 40, 1626-1636.
Rauber, R. and L. Di Girolamo, 2002: Imaging in meteorology. The Encyclopedia of Imaging Science and Technology, 757-773 J.P. Hornak, Ed., Wiley.
Di Girolamo, L., and R. Davies, 1995: The image navigation cloud mask for the Multi-angle Imaging SpectroRadiometer (MISR). J. Atmos. Oceanic Tech.,12, 1215–1228.
Di Girolamo, L., and R. Davies, 1994: A band-differenced angular signature technique for cirrus cloud detection. IEEE Trans. Geosci. Remote Sens.,32, 890–896.