Ralph Kahn

Organization

University of Colorado, Boulder

NASA Goddard Space Flight Center

Email

Contact person by email

Website

PUMAS -- Practical Uses of Math And Science

First Author Publications

Kahn, R.A. (2024), Editorial, Spa. Res. Today 216, COSPAR Session on Sp, 9933.
Kahn, R.A., et al. (2024), Evolving Particles in the 2022 Hunga Tonga—Hunga Ha'apai Volcano Eruption Plume, J. Geophys. Res., 129, e2023JD039963, doi:10.1029/2023JD039963.
Kahn, R.A. (2023), Reducing Aerosol Climate-Forcing Uncertainty: A Three-Way Street To reduce persistent aerosol-climate-forcing uncertainty, new in situ aerosol and cloud measurement programs are needed, plus much better integration of satellite and suborbital measurements, Eos, 104, doi:10.1029/2023EO235016.
Kahn, R.A. (2023), Editorial, Spa. Res. Today, 216, 5-6.
Kahn, R.A., et al. (2023), Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within-The-Atmosphere Observations: A Three-Way Street, Rev. Geophys., 61, e2022RG000796, doi:10.1029/2022RG000796.
Kahn, R.A. (2023), Editorial, Frontiers Earth Sci., 11, 1212045, doi:10.3389/feart.2023.1212045.
Kahn, R.A., and . Samset (2022), Remote sensing measurements of aerosol properties, K. Carslaw, Ed., Elsevier, ISBN, 9780128197660, Chapter 10 in.
Kahn, R.A., et al. (2022), Ralph A. Kahn, Yang Liu, and David J. Diner Contents, H. Akimoto, H. Tanimoto (eds.Handbook of Air Quality and Climate Change, 1, doi:10.1007/978-981-15-2527-8_62-1.
Kahn, R.A. (2020), A global perspective on wildfires. EOS, American Geophysical Union, EOS - American Geophysical Union, 101, 1-5, doi:10.1029/2020EO138260.
Kahn, R.A. (2020), A global perspective on wildfires. EOS, American Geophysical Union, EOS - American Geophysical Union, 101, 1-5, doi:10.1029/2020EO138260.
Kahn, R.A., et al. (2017), SAM-CAAM: A Concept for Acquiring Systematic Aircraft Measurements to Characterize Aerosol Air Masses, Bull. Am. Meteoro. Soc., 2215-2228, doi:10.1175/BAMS-D-16-0003.1.
Kahn, R.A., et al. (2016), The Sensitivity of SeaWiFS Ocean Color Retrievals to Aerosol Amount and Type, J. Atmos. Oceanic Technol., 33, 1185-1209, doi:10.1175/JTECH-D-15-0121.1.
Kahn, R.A., and B. Gaitley (2015), An analysis of global aerosol type as retrieved by MISR, J. Geophys. Res., 120, 4248-4281, doi:10.1002/2015JD023322.
Kahn, R.A. (2015), Satellites and Satellite Remote Sensing, Encyclopedia of Atmospheric Sciences, 2nd edition, G. R. North, J. Pyle and F. Zhang, eds., 5, 51-66, doi:10.1016/B978-0-12-382225-3.00347-9.
Kahn, R.A., and . Limbacher (2012), Eyjafjallajökull volcano plume particle-type characterization from space-based multi-angle imaging, Atmos. Chem. Phys., 12, 9459-9477, doi:10.5194/acp-12-9459-2012.
Kahn, R.A. (2011), Reducing the Uncertainties in Direct Aerosol Radiative Forcing, Surv. Geophys., doi:10.1007/s10712-011-9153-z.
Kahn, R.A., et al. (2011), Response to ‘‘Toward unified satellite climatology of aerosol properties. 3. MODIS versus MISR versus AERONET’’, J. Quant. Spectrosc. Radiat. Transfer, 112, 901-909, doi:10.1016/j.jqsrt.2010.11.001.
Kahn, R.A., et al. (2010), Multiangle Imaging SpectroRadiometer global aerosol product assessment by comparison with the Aerosol Robotic Network, J. Geophys. Res., 115, D23209, doi:10.1029/2010JD014601.
Kahn, R.A., et al. (2009), Desert dust aerosol air mass mapping in the western Sahara, using particle properties derived from space-based multi-angle imaging, Tellus, 61B, 239-251, doi:10.1111/j.1600-0889.2008.00398.x.
Kahn, R.A., 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.
Kahn, R.A., et al. (2008), Wildfire smoke injection heights: Two perspectives from space, Geophys. Res. Lett., 35, L04809, doi:10.1029/2007GL032165.
Kahn, R.A., 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.A., et al. (2007), Aerosol source plume physical characteristics from space-based multiangle imaging, J. Geophys. Res., 112, D11205, doi:10.1029/2006JD007647.
Kahn, R.A., et al. (2005), MISR Calibration and Implications for Low-Light-Level Aerosol Retrieval over Dark Water, J. Atmos. Sci., 62, 1032-1052.
Kahn, R.A., et al. (2005), Multiangle Imaging Spectroradiometer (MISR) global aerosol optical depth validation based on 2 years of coincident Aerosol Robotic Network (AERONET) observations, J. Geophys. Res., 110, D10S04, doi:10.1029/2004JD004706.
Kahn, R.A., et al. (2004), Understanding Aerosols: Aerosol Data Sources and Their Roles within PARAGON, Bull. Am. Meteorol. Soc., 1511, doi:10.1175/BAMS-85-10-1511.
Kahn, R.A., et al. (2004), Environmental snapshots from ACE-Asia, J. Geophys. Res., 109, D19S14, doi:10.1029/2003JD004339.
Kahn, R.A., et al. (2001), Sensitivity of multiangle imaging to natural mixtures of aerosols over ocean, J. Geophys. Res., 106, 18219-18238, doi:10.1029/2000JD900497.
Kahn, R.A., et al. (2001), Aerosol properties derived from aircraft multiangle imaging over Monterey Bay, J. Geophys. Res., 106, 11977-11995, doi:10.1029/2000JD900740.
Kahn, R.A., et al. (1998), Sensitivity of multiangle imaging to aerosol optical depth and to pure-particle size distribution and composition over ocean, J. Geophys. Res., 103, 32195-32213, doi:10.1029/98JD01752.
Kahn, R.A., et al. (1997), Sensitivity of Multi-angle remote sensing observations to aerosol sphericity, J. Geophys. Res., 102, 16861-16870, doi:10.1029/96JD01934.

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

Co-Authored Publications

Carroll, B.J., et al. (2024), Measuring Coupled Fire–Atmosphere Dynamics The California Fire Dynamics Experiment (CalFiDE), Bull. Am. Meteorol. Soc., doi:10.1175/BAMS-D-23-0012.1.
Limbacher, ., et al. (2024), MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm, Atmos. Meas. Tech., 17, 471-498, doi:10.5194/amt-17-471-2024.
Noyes, ., and R.A. Kahn (2024), Satellite Multi-Angle Observations of Wildfire Smoke Plumes During the CalFiDE Field Campaign: Aerosol Plume Heights, Particle Property Evolution, and Aging Timescales, J. Geophys. Res..
deSouza, P., et al. (2023), This article can be cited before page numbers have been issued, to do this please use: P. N. deSouza, K., View Article Online, doi:10.1039/D2EA00142J.
Hammer, ., et al. (2023), Assessment of the impact of discontinuity in satellite instruments and retrievals on global PM2.5 estimates, Remote Sensing of Environment, 294, 113624, doi:10.1016/j.rse.2023.113624.
Marshak, A., et al. (2023), Aerosol Properties in Cloudy Environments from Remote Sensing Observations, Bull. Am. Meteorol. Soc., 102, E2177-E2197, doi:10.1175/BAMS-D-20-0225.1.
Mytilinaios, M., et al. (2023), Comparison of dust optical depth from multi-sensor products and the MONARCH dust reanalysis over Northern Africa, the Middle East and Europe, Atmos. Chem. Phys., 23, 5487-5516, doi:10.5194/acp-23-5487-2023.
Nelson, R.R., et al. (2023), Expanding the coverage of Multi-angle Imaging SpectroRadiometer (MISR) aerosol retrievals over shallow, turbid, and eutrophic waters, Atmos. Meas. Tech., 16, 4947-4960, doi:10.5194/amt-16-4947-2023.
Yue, J., et al. (2023), La Soufriere Volcanic Eruptions Launched Gravity Waves Into Space, Geophys. Res. Lett., 49, doi:10.1029/2022GL097952.
Adebiyi, A.A., et al. (2022), A review of coarse mineral dust in the Earth system, Aeolian Resrch., 60, 100849, doi:10.1016/j.aeolia.2022.100849.
Bian, Q., et al. (2022), Constraining Aerosol Phase Function Using Dual-View Geostationary Satellites, J. Geophys. Res..
Bian, Q., et al. (2022), Constraining Aerosol Phase Function Using Dual-View Geostationary Satellites, J. Geophys. Res..
Christensen, M.W., et al. (2022), Opportunistic experiments to constrain aerosol effective radiative forcing, Atmos. Chem. Phys., doi:10.5194/acp-22-641-2022.
Christensen, M.W., et al. (2022), Opportunistic experiments to constrain aerosol effective radiative forcing, Atmos. Chem. Phys., doi:10.5194/acp-22-641-2022.
Fromm, M., et al. (2022), Quantifying the Source Term and Uniqueness of the August 12, 2017 Pacific Northwest PyroCb Event, J. Geophys. Res..
Li, J.1.✉., et al. (2022), in the climate system REVIEwS, Nature, doi:10.1038/scattering.
Li, Y., et al. (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.
Limbacher, ., et al. (2022), The new MISR research aerosol retrieval algorithm: a multi-angle, multi-spectral, bounded-variable least squares retrieval of aerosol particle properties over both land and water, Atmos. Meas. Tech., 15, 6865-6887, doi:10.5194/amt-15-6865-2022.
Martin, M., et al. (2022), A Global Analysis of Wildfire Smoke Injection Heights Derived from Space-Based Multi-Angle Imaging, doi:10.3390/rs10101609.
McNeill, J., et al. (2022), OPEN Large global variations in measured airborne metal concentrations driven by anthropogenic sources, Nature, doi:10.1038/s41598-020-78789-y.
Noyes, ., et al. (2022), Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging, doi:10.3390/rs12050769.
Noyes, ., et al. (2022), Wildfire Smoke Particle Properties and Evolution, From Space-Based Multi-Angle Imaging II: The Williams Flats Fire during the FIREX-AQ Campaign, doi:10.3390/rs12223823.
Noyes, ., et al. (2022), Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution, and Controlling Factors, Using Satellite Observations. Atm. Chem. Phys., 22, 10267-10290, doi:10.5194/acp-22-10267-2022.
van Donkelaar, ., et al. (2022), Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty, Environ. Sci. Technol., doi:10.1021/acs.est.1c05309.
Yue, J., et al. (2022), La Soufriere Volcanic Eruptions Launched Gravity Waves Into Space, Geophys. Res. Lett..
Zamora, L.M., et al. (2022), Comparisons between the distributions of dust and combustion aerosols in MERRA-2, FLEXPART, and CALIPSO and implications for deposition freezing over wintertime Siberia, Atmos. Chem. Phys., doi:10.5194/acp-22-12269-2022.
Chen, T., et al. (2021), Potential impact of aerosols on convective clouds revealed by Himawari-8 observations over different terrain types in eastern China, Atmos. Chem. Phys., 21, 6199-6220, doi:10.5194/acp-21-6199-2021.
deSouza, ., et al. (2021), Spatial variation of fine particulate matter levels in Nairobi before and during the COVID-19 curfew: Implications for environmental justice, Environ. Res. Comm., 3, 071003, doi:10.1088/2515-7620/ac1214.
Flower, ., and R.A. Kahn (2021), Invited Research Article Twenty years of NASA-EOS multi-sensor satellite observations at Kīlauea volcano (2000–2019), Journal of Volcanology and Geothermal Research, 415, 107247, doi:10.1016/j.jvolgeores.2021.107247.
Fromm, M., et al. (2021), Quantifying the Source Term and Uniqueness of the August 12, 2017 Pacific Northwest PyroCb Event, J. Geophys. Res..
Hammer, M.S., et al. (2021), The Authors, some Effects of COVID-19 lockdowns on fine particulate rights reserved; exclusive licensee matter concentrations American Association for the Advancement of Science. No claim to, Hammer et al., Sci. Adv., 7, eabg7670.
McNeill, J., et al. (2021), OPEN Large global variations in measured airborne metal concentrations driven by anthropogenic sources, Nature, doi:10.1038/s41598-020-78789-y.
deSouza, ., et al. (2020), Air Quality Monitoring Case Study Using Mobile Low-cost Sensors mounted on Trash-trucks, Sustainable Cities and Society, 60, 102239, doi:10.1016/j.scs.2020.102239.
deSouza, ., et al. (2020), Combining low-cost, surface-based aerosol monitors with size-resolved satellite data for air quality applications, Atmos. Meas. Tech., 13, 5319-5334, doi:10.5194/amt-13-5319-2020.
Flower, ., and R.A. Kahn (2020), Interpreting the volcanological processes of Kamchatka, based on multi- T sensor satellite observations, Remote Sensing of Environment, 237, 111585, doi:10.1016/j.rse.2019.111585.
Flower, ., and R.A. Kahn (2020), The Evolution of Icelandic Volcano Emissions, as Observed From Space in the Era of NASA's Earth Observing System (EOS), J. Geophys. Res., 125, e2019JD031625, doi:10.1029/2019JD031625.
Garay, M.J., et al. (2020), Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product, Atmos. Meas. Tech., 13, 593-628, doi:10.5194/amt-13-593-2020.
Hammer, M.S., et al. (2020), Improved Global Estimates of Fine Particulate Matter Concentrations and Trends Derived from Updated Satellite Retrievals, Modeling Advances, and Additional Ground-Based Monitors, Environ. Sci. Tech., 54, 7879-7890, doi:10.1021/acs.est.0c01764.
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.
Lyapustin, A., et al. (2020), MAIAC Thermal Technique for Smoke Injection Height From MODIS, IEEE Geosci. Remote Sens. Lett., 17, 730-734, doi:10.1109/LGRS.2019.2936332.
Noyes, ., et al. (2020), Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging, doi:10.3390/rs12050769.
Sogacheva, L., et al. (2020), Merging regional and global aerosol optical depth records from major available satellite products, Atmos. Chem. Phys., 20, 2031-2056, doi:10.5194/acp-20-2031-2020.
Su, T., et al. (2020), A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions, Remt. Sens. Env., 237, 111519, doi:10.1016/j.rse.2019.111519.
Zamora, L.M., and R.A. Kahn (2020), Saharan dust aerosols change deep convective cloud prevalence, possibly by inhibiting marine new particle formation, J. Climate, 33, 9467-9477, doi:10.1175/JCLI-D-20-0083.1.
Gonzalez-Alonso, L., et al. (2019), Biomass-burning smoke heights over the Amazon observed from space, Atmos. Chem. Phys., 19, 1685-1702, doi:10.5194/acp-19-1685-2019.
Kim, D., et al. (2019), Asian and Trans‐Pacific Dust: A Multimodel and Multiremote Sensing Observation Analysis, J. Geophys. Res..
Limbacher, ., and R.A. Kahn (2019), Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters, Atmos. Meas. Tech., 12, 675-689, doi:10.5194/amt-12-675-2019.
Yu, H., et al. (2019), Estimates of African Dust Deposition Along the Trans‐ Atlantic Transit Using the Decadelong Record of Aerosol Measurements from CALIOP, MODIS, MISR, and IASI, J. Geophys. Res., 124, 7975-7996, doi:10.1029/2019JD030574.
Flower, ., and R.A. Kahn (2018), Karymsky volcano eruptive plume properties based on MISR multi-angle imagery and the volcanological implications, Atmos. Chem. Phys., 18, 3903-3918, doi:10.5194/acp-18-3903-2018.
Friberg, M.D., et al. (2018), Constraining chemical transport PM2.5 modeling outputs using surface monitor measurements and satellite retrievals: application over the San Joaquin Valley, Atmos. Chem. Phys., 18, 12891-12913, doi:10.5194/acp-18-12891-2018.
Samset, ., et al. (2018), Aerosol absorption: Progress toward global and regional constraints, Current Climate Change Repts., doi:10.1007/s40641-018-0091-4.
Vernon, C.J., et al. (2018), The impact of MISR-derived injection height initialization on wildfire and volcanic plume dispersion in the HYSPLIT model, Atmos. Meas. Tech., 11, 6289-6307, doi:10.5194/amt-11-6289-2018.
Zamora, L.M., et al. (2018), A satellite-based estimate of combustion aerosol cloud microphysical effects over the Arctic Ocean, Atmos. Chem. Phys., 18, 14949-14964, doi:10.5194/acp-18-14949-2018.
Flower, ., and R.A. Kahn (2017), Distinguishing Remobilized Ash From Erupted Volcanic Plumes Using Space-Borne Multiangle Imaging, Geophys. Res. Lett..
Flower, ., and R.A. Kahn (2017), Assessing the altitude and dispersion of volcanic plumes using MISR multi-angle imaging from space: Sixteen years of volcanic activity in the Kamchatka Peninsula, Russia, Journal of Volcanology and Geothermal Research, 337, 1-15, doi:10.1016/j.jvolgeores.2017.03.010.
Friberg, M.D., et al. (2017), Daily ambient air pollution metrics for five cities: Evaluation of datafusion-based estimates and uncertainties, Atmos. Environ., 158, 36-50, doi:10.1016/j.atmosenv.2017.03.022.
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.
Limbacher, ., 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.
Petrenko, M., et al. (2017), Refined Use of Satellite Aerosol Optical Depth Snapshots to Constrain Biomass Burning Emissions in the GOCART Model, J. Geophys. Res., 122, doi:10.1002/2017JD026693.
Zamora, L.M., et al. (2017), Aerosol indirect effects on the nighttime Arctic Ocean surface from thin, predominantly liquid clouds, Atmos. Chem. Phys., 17, 7311-7332, doi:10.5194/acp-17-7311-2017.
Lee, H., et al. (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.
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.
Seinfeld, J.H., et al. (2016), COLLOQUIUM INTRODUCTION Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system, Proc. Natl. Acad. Sci., 113, doi:10.1073/pnas.1514043113.
van Donkelaar, ., et al. (2016), Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors, Environ. Sci. Technol., 50, 3762-3772, doi:10.1021/acs.est.5b05833.
Li, S., et al. (2015), Improving satellite-retrieved aerosol microphysical properties using GOCART data, Atmos. Meas. Tech., 8, 1157-1171, doi:10.5194/amt-8-1157-2015.
Limbacher, ., 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.
Solomos, S., et al. (2015), Smoke dispersion modeling over complex terrain using high resolution meteorological data and satellite observations - The Fire Hub platform, Atmos. Environ., 119, 348-361, doi:10.1016/j.atmosenv.2015.08.066.
Taylor, M., et al. (2015), Global aerosol mixtures and their multiyear and seasonal characteristics, Atmos. Environ., 116, 112-129, doi:10.1016/j.atmosenv.2015.06.029.
Chin, M., et al. (2014), Multi-decadal aerosol variations from 1980 to 2009: a perspective from observations and a global model, Atmos. Chem. Phys., 14, 3657-3690, doi:10.5194/acp-14-3657-2014.
Colarco, P.R., et al. (2014), Impact of satellite viewing-swath width on global and regional aerosol optical thickness statistics and trends, Atmos. Meas. Tech., 7, 2313-2335, doi:10.5194/amt-7-2313-2014.
Duncan, B., et al. (2014), Satellite data of atmospheric pollution for U.S. air quality applications: Examples of applications, summary of data end-user resources, answers to FAQs, and common mistakes to avoid, Atmos. Environ., 94, 647-662, doi:10.1016/j.atmosenv.2014.05.061.
Kim, D., et al. (2014), Sources, sinks, and transatlantic transport of North Africandust aerosol: A multimodel analysis and comparison with remote sensing data, J. Geophys. Res., 119, 6259-6277, doi:10.1002/2013JD021099.
Kim, D., et al. (2014), Sources, sinks, and transatlantic transport of North African dust aerosol: A multimodel analysis and comparison with remote sensing data, J. Geophys. Res., 119, 6259-6277, doi:10.1002/2013JD021099.
Rosenfeld, D., et al. (2014), Global observations of aerosol-cloud-precipitationclimate interactions, Rev. Geophys., 52, 750-808, doi:10.1002/2013RG000441.
Schwartz, S., et al. (2014), Earth’s climate sensitivity: Apparent Inconsistencies in recent analyses., Earth’s Future, 2, doi:10.1002/2014EF000273.
Guo, Y., et al. (2013), Tropical Atlantic dust and smoke aerosol variations related to the Madden-Julian Oscillation in MODIS and MISR observations, J. Geophys. Res., 118, 1-17, doi:10.1002/jgrd.50409.
Mallet, M., et al. (2013), Absorption properties of Mediterranean aerosols obtained from multi-year ground-based remote sensing observations, Atmos. Chem. Phys., 13, 9195-9210, doi:10.5194/acp-13-9195-2013.
Nelson, D., et al. (2013), Stereoscopic Height and Wind Retrievals for Aerosol Plumes with the MISR INteractive eXplorer (MINX), Remote Sens., 5, 4593-4628, doi:10.3390/rs5094593.
Patadia, F., et al. (2013), Aerosol airmass type mapping over the Urban Mexico City region from space-based multi-angle imaging, Atmos. Chem. Phys., 13, 9525-9541, doi:10.5194/acp-13-9525-2013.
Rashki, A., et al. (2013), Dryness of ephemeral lakes and consequences for dust activity: The case of the Hamoun drainage basin, southeastern Iran, Science of the Total Environment, 463–464, 552-564, doi:10.1016/j.scitotenv.2013.06.045.
Yu, H., et al. (2013), Satellite perspective of aerosol intercontinental transport: from qualitative tracking to quantitative characterization, Atmos. Res., 124, 73-100, doi:10.1016/j.atmosres.2012.12.013.
Carboni, E., et al. (2012), Intercomparison of desert dust optical depth from satellite measurements, Atmos. Meas. Tech., 5, 1973-2002, doi:10.5194/amt-5-1973-2012.
Ichoku, C., et al. (2012), Satellite contributions to the quantitative characterization of biomass burning for climate modeling, Atmos. Res., 111, 1-28, doi:10.1016/j.atmosres.2012.03.007.
Kaskaoutis, D., et al. (2012), Editorial: Desert Dust Properties, Modelling, and Monitoring, Advances in Meteorology, 2012, 483632, doi:10.1155/2012/483632.
Val Martin, ., et al. (2012), Space-based observational constraints for 1-D fire smoke plume-rise models, J. Geophys. Res., 117, D22204, doi:10.1029/2012JD018370.
Petrenko, M., et al. (2012), The use of satellite-measured aerosol optical depth to constrain biomass burning emissions source strength in the global model GOCART, J. Geophys. Res., 117, D18212, doi:10.1029/2012JD017870.
Scollo, S., et al. (2012), MISR observations of Etna volcanic plumes, J. Geophys. Res., 117, D06210, doi:10.1029/2011JD016625.
Lyapustin, A., et al. (2011), Reduction of aerosol absorption in Beijing since 2007 from MODIS and AERONET, Geophys. Res. Lett., 38, L10803, doi:10.1029/2011GL047306.
Sessions, W.R., et al. (2011), An investigation of methods for injecting emissions from boreal wildfires using WRF-Chem during ARCTAS, Atmos. Chem. Phys., 11, 5719-5744, doi:10.5194/acp-11-5719-2011.
Tian, B., et al. (2011), Modulation of Atlantic aerosols by the Madden‐Julian Oscillation, J. Geophys. Res., 116, D15108, doi:10.1029/2010JD015201.
Chatterjee, A., et al. (2010), A geostatistical data fusion technique for merging remote sensing and ground‐based observations of aerosol optical thickness, J. Geophys. Res., 115, D20207, doi:10.1029/2009JD013765.
Levy, R.C., et al. (2010), Global evaluation of the Collection 5 MODIS dark-target aerosol products over land, Atmos. Chem. Phys., 10, 10399-10420, doi:10.5194/acp-10-10399-2010.
Lyapustin, A., et al. (2010), Analysis of snow bidirectional reflectance from ARCTAS Spring-2008 Campaign, Atmos. Chem. Phys., 10, 4359-4375, doi:10.5194/acp-10-4359-2010.
Val Martin, ., et al. (2010), Smoke injection heights from fires in North America: analysis of 5 years of satellite observations, Atmos. Chem. Phys., 10, 1491-1510, doi:10.5194/acp-10-1491-2010.
Mims, S.R., et al. (2010), MISR Stereo Heights of Grassland Fire Smoke Plumes in Australia, IEEE Trans. Geosci. Remote Sens., 48, 25-35, doi:10.1109/TGRS.2009.2027114.
Pierce, J.R., et al. (2010), Detecting thin cirrus in Multiangle Imaging Spectroradiometer aerosol retrievals, J. Geophys. Res., 115, D08201, doi:10.1029/2009JD013019.
Schwartz, S., et al. (2010), Why Hasn’t Earth Warmed as Much as Expected?, J. Climate, 23, 2453-2464, doi:10.1175/2009JCLI3461.1.
van Donkelaar, ., et al. (2010), Global Estimates of Ambient Fine Particulate Matter Concentrations from Satellite-Based Aerosol Optical Depth: Development and Application, Research, 118, 847-855, doi:).
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Levy, R.C., 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.
Liu, ., et al. (2009), Analysis of the impact of the forest fires in August 2007 on air quality of Athens using multi-sensor aerosol remote sensing data, meteorology and surface observations, Atmos. Environ., 43, 3310-3318, doi:10.1016/j.atmosenv.2009.04.010.
Myhre, ., et al. (2009), Modelled radiative forcing of the direct aerosol effect with multi-observation evaluation, Atmos. Chem. Phys., 9, 1365-1392, doi:10.5194/acp-9-1365-2009.
Chen, W., et al. (2008), Sensitivity of multiangle imaging to the optical and microphysical properties of biomass burning aerosols, J. Geophys. Res., 113, D10203, doi:10.1029/2007JD009414.
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Kalashnikova, O.V., and R.A. Kahn (2008), Mineral dust plume evolution over the Atlantic from MISR and MODIS aerosol retrievals, J. Geophys. Res., 113, D24204, doi:10.1029/2008JD010083.
Lallart, P., et al. (2008), POLDER2/ADEOSII, MISR, and MODIS/Terra reflectance comparisons, J. Geophys. Res., 113, D14S02, doi:10.1029/2007JD009656.
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