Publications for Terra- MISR
| Publication Citation |
|---|
| Kokhanovsky, A.A., A.B. Davis, B. Cairns, O. Dubovik, O.P. Hasekamp, I. Sano, S. Mukai, V.V. Rozanov, P. Litvinov, T. Lapyonok, I.S. Kolomiets, Y.A. Oberemok, S. Savenkov, W. Martin, A. Wasilewski, A. Di Noia, F.A. Sap, J. Rietjens, F. Xu, V. Natraj, M. Duan, T. Cheng, and R. Munro (2015), Space-based remote sensing of atmospheric aerosols: The multi-angle spectro-polarimetric frontier, Earth-Science Reviews, 85-116, doi:10.1016/j.earscirev.2015.01.012. |
| Lallart, P., R. Kahn, and D. Tanré (2008), POLDER2/ADEOSII, MISR, and MODIS/Terra reflectance comparisons, J. Geophys. Res., 113, D14S02, doi:10.1029/2007JD009656. |
| Lee, B., L. Di Girolamo, G. Zhao, and Y. Zhan (2018), Three-Dimensional Cloud Volume Reconstruction from the Multi-angle Imaging SpectroRadiometer, doi:10.3390/rs10111858. |
| Lee, H., O.V. Kalashnikova, K. Suzuki, A. Braverman, M.J. Garay, and R.A. Kahn (2016), Climatology of the aerosol optical depth by components from the Multi-angle Imaging SpectroRadiometer (MISR) and chemistry transport models, Atmos. Chem. Phys., 16, 6627-6640, doi:10.5194/acp-16-6627-2016. |
| Levis, A., A.B. Davis, and Y.Y. Schechner (2017), Multiple-Scattering Microphysics Tomography, IEEE Conference on Computer Vision and Pattern Recognition (CVPR17), 5797-5806. |
| Li, J., B.E. Carlson, and A.A. Lacis (2014), Application of spectral analysis techniques in the intercomparison of aerosol data. Part II: Using maximum covariance analysis to effectively compare spatiotemporal variability of satellite and AERONET measured aerosol optical depth, J. Geophys. Res., 119, 153-166, doi:10.1002/2013JD020537. |
| Li, J., B.E. Carlson, and A.A. Lacis (2014), Application of spectral analysis techniques in the intercomparison of aerosol data: Part III. Using combined PCA to compare spatiotemporal variability of MODIS, MISR, and OMI aerosol optical depth, J. Geophys. Res., 119, 4017-4042, doi:10.1002/2013JD020538. |
| Li, J., B.E. Carlson, and A.A. Lacis (2014), Application of spectral analysis techniques to the intercomparison of aerosol data - Part 4: Synthesized analysis of multisensor satellite and ground-based AOD measurements using combined maximum covariance analysis, Atmos. Meas. Tech., 7, 2531-2549, doi:10.5194/amt-7-2531-2014. |
| Li, J., B.E. Carlson, and A.A. Lacis (2015), How well do satellite AOD observations represent the spatial and temporal variability of PM2.5 concentration for the United States?, Atmos. Environ., 102, 260-273, doi:10.1016/j.atmosenv.2014.12.010. |
| Li, J., X. Li, B.E. Carlson, R.A. Kahn, A.A. Lacis, O. Dubovik, and T. Nakajima (2016), Reducing multisensor satellite monthly mean aerosol optical depth uncertainty: 1. Objective assessment of current AERONET locations, J. Geophys. Res., 121, doi:10.1002/2016JD025469. |
| Li, J., X. Li, B.E. Carlson, R.A. Kahn, A.A. Lacis, O. Dubovik, and T. Nakajima (2017), Reducing multisensor monthly mean aerosol optical depth uncertainty: 2. Optimal locations for potential ground observation deployments, J. Geophys. Res., 122, doi:10.1002/2016JD026308. |
| Li, J., R.A. Kahn, J. Wei, B.E. Carlson, A.A. Lacis, Z. Li, X. Li, O. Dubovik, and T. Nakajima (2020), Synergy of Satellite‐ and Ground‐Based Aerosol Optical Depth Measurements Using an Ensemble Kalman Filter Approach, J. Geophys. Res., 125, 1-17, doi:10.1029/2019JD031884. |
| Li, S., R. Khan, M. Chin, M.J. Garay, and Y. Liu (2015), Improving satellite-retrieved aerosol microphysical properties using GOCART data, Atmos. Meas. Tech., 8, 1157-1171, doi:10.5194/amt-8-1157-2015. |
| Li, Y., D.Q. Tong, F. Ngan, M.D. Cohen, A.F. Stein, S. Kondragunta, X. Zhang, C. Ichoku, E.J. Hyer, and R.A. Kahn (2020), Ensemble PM2.5 Forecasting During the 2018 Camp Fire Event Using the HYSPLIT Transport and Dispersion Model, J. Geophys. Res., 125, e2020JD032768, doi:10.1029/2020JD032768. |
| Li, Y., D. Tong, S. Ma, S.R. Freitas, R. Ahmadov, M. Sofiev, X. Zhang, S. Kondragunta, R.A. Kahn, Y. Tang, B. Baker, P. Campbell, R. Saylor, I. Stajner, and G. Grell (2022), Impacts of estimated plume rise on PM2.5 exceedance prediction during extreme wildfire events: A comparison of three schemes (Briggs, Freitas, and Sofiev), Atmos. Chem. Phys., 23, 3083-3101, doi:10.5194/acp-23-3083-2023. |
| 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. |
| Limbacher, J.A., and R.A. Khan (2014), MISR research-aerosol-algorithm refinements for dark water retrievals, Atmos. Meas. Tech., 7, 3989-4007, doi:10.5194/amt-7-3989-2014. |
| Limbacher, J.A., and R.A. Khan (2015), MISR empirical stray light corrections in high-contrast scenes, Atmos. Meas. Tech., 8, 2927-2943, doi:10.5194/amt-8-2927-2015. |
| Limbacher, J.A., and R.A. Kahn (2015), MISR empirical stray light corrections in high-contrast scenes, Atmos. Meas. Tech., 8, 1-17, doi:10.5194/amt-8-1-2015. |
| Limbacher, J.A., and R.A. Kahn (2017), Updated MISR dark water research aerosol retrieval algorithm – Part 1: Coupled 1.1 km ocean surface chlorophyll a retrievals with empirical calibration corrections, Atmos. Meas. Tech., 10, 1539-1555, doi:10.5194/amt-10-1539-2017. |