Publication Citation
Jin, M., J. M. Shepherd, and M. D. King (2005), Urban aerosols and their variations with clouds and rainfall: A case study for New York and Houston, J. Geophys. Res., 110, D10S20, doi:10.1029/2004JD005081.
Joiner, J., et al. (2018), Global relationships among traditional reflectance vegetation indices (NDVI T and NDII), evapotranspiration (ET), and soil moisture variability on weekly timescales, Remote Sensing of Environment, 219, 339-352, doi:10.1016/j.rse.2018.10.020.
Joiner, J., et al. (2018), Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data, doi:10.3390/rs10091346.
Juárez, M. D., A. B. Davis, and E. J. Fetzer (2011), Scale-by-scale analysis of probability distributions for global MODIS-AQUA cloud properties: how the large scale signature of turbulence may impact statistical analyses of clouds, Atmos. Chem. Phys., 11, 2893-2901, doi:10.5194/acp-11-2893-2011.
Kahn, R. (2020), A global perspective on wildfires. EOS, American Geophysical Union, EOS - American Geophysical Union, 101, 1-5, doi:10.1029/2020EO138260.
Kahn, R. (2020), A global perspective on wildfires. EOS, American Geophysical Union, EOS - American Geophysical Union, 101, 1-5, doi:10.1029/2020EO138260.
Kahn, R., et al. (2005), MISR Calibration and Implications for Low-Light-Level Aerosol Retrieval over Dark Water, J. Atmos. Sci., 62, 1032-1052.
Kahn, R., et al. (2007), Satellite-derived aerosol optical depth over dark water from MISR and MODIS: Comparisons with AERONET and implications for climatological studies, J. Geophys. Res., 112, D18205, doi:10.1029/2006JD008175.
Kahn, R., et al. (2007), Aerosol source plume physical characteristics from space-based multiangle imaging, J. Geophys. Res., 112, D11205, doi:10.1029/2006JD007647.
Kahn, R., et al. (2009), MISR Aerosol Product Attributes and Statistical Comparisons With MODIS, IEEE Trans. Geosci. Remote Sens., 47, 4095-4114, doi:10.1109/TGRS.2009.2023115.
Kalashnikova, O. V., and R. Kahn (2008), Mineral dust plume evolution over the Atlantic from MISR and MODIS aerosol retrievals, J. Geophys. Res., 113, D24204, doi:10.1029/2008JD010083.
Kato, S., and A. Marshak (2009), Solar zenith and viewing geometry-dependent errors in satellite retrieved cloud optical thickness: Marine stratocumulus case, J. Geophys. Res., 114, D01202, doi:10.1029/2008JD010579.
King, M. D., et al. (2003), Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS, IEEE Trans. Geosci. Remote Sens., 41, 442-458, doi:10.1109/TGRS.2002.808226.
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.
Levy, R., et al. (2009), A Critical Look at Deriving Monthly Aerosol Optical Depth From Satellite Data, IEEE Trans. Geosci. Remote Sens., 47, 2942-2956, doi:10.1109/TGRS.2009.2013842.
Li, J., et al. (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., et al. (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., et al. (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, Y., et al. (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.
Liu, Y., et al. (2007), Using aerosol optical thickness to predict ground-level PM2.5 concentrations in the St. Louis area: A comparison between MISR and MODIS, Remote Sensing of Environment, 107, 33-44, doi:10.1016/j.rse.2006.05.022.

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