Organization
University of North Dakota
First Author Publications
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Zhang, J., et al. (2023), Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals, Atmos. Meas. Tech., 16, 2531-2546, doi:10.5194/amt-16-2531-2023.
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Zhang, J., et al. (2021), Development of an Ozone Monitoring Instrument (OMI) aerosol index (AI) data assimilation scheme for aerosol modeling over bright surfaces – a step toward direct radiance assimilation in the UV spectrum, Geosci. Model. Dev., 14, 27-42, doi:10.5194/gmd-14-27-2021.
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Zhang, J., et al. (2019), Characterization and application of artificial light sources for nighttime aerosol optical depth retrievals using the VIIRS Day/Night Band, Atmos. Meas. Tech., doi:10.5194/amt-2018-424.
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Zhang, J., et al. (2017), Has China been exporting less particulate air pollution over the past decade?, Geophys. Res. Lett., 44, 2941-2948, doi:10.1002/2017GL072617.
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Zhang, J., et al. (2016), An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature, Atmos. Chem. Phys., 16, 6475-6494, doi:10.5194/acp-16-6475-2016.
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Zhang, J., et al. (2014), Evaluating the impact of multisensor data assimilation on a global aerosol particle transport model, J. Geophys. Res., 119, 4674-4689, doi:10.1002/2013JD020975.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
Co-Authored Publications
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Midzak, N., et al. (2024), An investigation of non-spherical smoke particles using CATS lidar, J. Geophys. Res., 128, e2023JD038805., doi:10.1029/2023JD038805.
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Sorenson, B.T., et al. (2024), Thermal infrared observations of a western United States biomass burning aerosol plume, Atmos. Chem. Phys., doi:10.5194/acp-24-1231-2024.
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Xian, P., et al. (2024), Intercomparison of aerosol optical depths from four reanalyses and their multi-reanalysis consensus, Atmos. Chem. Phys., doi:10.5194/acp-24-6385-2024.
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Gumber, A., et al. (2023), Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity, Atmos. Meas. Tech., 16, 2547-2573, doi:10.5194/amt-16-2547-2023.
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Marquis, ., et al. (2023), Estimating the Impact of Assimilating Cirrus Cloud–Contaminated Hyperspectral Infrared Radiances for Numerical Weather Prediction, J. Atmos. Oceanic Technol., 40, 327-340, doi:10.1175/JTECH-D-21-0165.1.
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Sorenson, B.T., et al. (2023), Ozone Monitoring Instrument (OMI) UV aerosol index data analysis over the Arctic region for future data assimilation and climate forcing applications, Atmos. Chem. Phys., doi:10.5194/acp-23-7161-2023.
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Xian, P., et al. (2023), Arctic spring and summertime aerosol optical depth baseline from long-term observations and model reanalyses – Part 2: Statistics of extreme AOD events, and implications for the impact of regional biomass burning processes, Atmos. Chem. Phys., doi:10.5194/acp-22-9949-2022.
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Xian, P., et al. (2023), Arctic spring and summertime aerosol optical depth baseline from long-term observations and model reanalyses – Part 1: Climatology and trend, Atmos. Chem. Phys., doi:10.5194/acp-22-9915-2022.
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Yorks, J.E., et al. (2023), Meyer, J. L. Carr, M. J. Garay, K. E. Christian; A. Bennedetti, A. M. Ring, A. Crawford, M. J. Pavolonis, V. Aquila, J. Kim, S. Kondragunta, A SmallSat Concept to Resolve Diurnal and Vertical Variations of Aerosols and Clouds, Bull. Am. Meteorol. Soc., doi:10.1175/BAMS-D-21-0179.1.
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Kyba, C.C.M., et al. (2022), Multiple Angle Observations Would Benefit Visible Band Remote Sensing Using Night Lights, J. Geophys. Res., 274, 118979, doi:10.1016/j.atmosenv.2022.118979.
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Midzak, N., et al. (2022), Constrained Retrievals of Aerosol Optical Properties Using Combined Lidar and Imager Measurements During the FIREX-AQ Campaign, Front. Remote Sens., 3, 818605, doi:10.3389/frsen.2022.818605.
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Reid, J.S., et al. (2022), A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode, Evaluation of the Fine and Coarse Mode. Remote Sens., 14, 2978, doi:10.3390/rs14132978.
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Reid, J.S., et al. (2022), EXTREME BIOMASS BURNING SMOKE, Community Challenges And Prospects In The Operational Forecasting Of, doi:10.1109/IGARSS47720.2021.9555160.
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Toth, T., et al. (2022), Retrieving particulate matter concentrations over the contiguous United States using CALIOP observations, Atmos. Environ., 274, 118979, doi:10.1016/j.atmosenv.2022.118979.
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Carson-Marquis, B.N., et al. (2021), Improving WRF-Chem Meteorological Analyses and Forecasts over Aerosol-Polluted Regions by Incorporating NAAPS Aerosol Analyses, J. Appl. Meteor. Climat., 60, 839-855, doi:10.1175/JAMC-D-20-0174.1.
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Marquis, J.W., et al. (2021), Conceptualizing the Impact of Dust-Contaminated Infrared Radiances on Data Assimilation for Numerical Weather Prediction, J. Atmos. Oceanic Technol., 38, 209-221, doi:10.1175/JTECH-D-19-0125.1.
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Wang, Z., et al. (2021), Quantifying uncertainties in nighttime light retrievals from Suomi-NPP and NOAA-20 VIIRS Day/Night Band data, Remote Sensing of Environment, 263, 112557, doi:10.1016/j.rse.2021.112557.
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Bazrkar, M.H., et al. (2020), Hydroclimatic aggregate drought index (HADI): a new approach for identification and categorization of drought in cold climate regions, Stochastic Environmental Research and Risk Assessment, 34, 1847-1870, doi:10.1007/s00477-020-01870-5.
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Midzak, N., et al. (2020), A Classification of Ice Crystal Habits Using Combined Lidar and Scanning Polarimeter Observations during the SEAC4RS Campaign, J. Atmos. Oceanic Technol., 37, 2185-2196, doi:10.1175/JTECH-D-20-0037.1.
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Solbrig, J.E., et al. (2020), Assessing the stability of surface lights for use in retrievals of nocturnal atmospheric parameters, Atmos. Meas. Tech., 13, 165-190, doi:10.5194/amt-13-165-2020.
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Starr, J., et al. (2020), Albedo Impacts of Changing Agricultural Practices in the United States through Space-Borne Analysis, Albedo Impacts of Changing Agricultural Practices in the United States through Space-Borne Analysis, doi:10.3390/rs12182887.
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Lee, L., et al. (2019), Investigation of CATS aerosol products and application toward global diurnal variation of aerosols, Atmos. Chem. Phys., 19, 12687-12707, doi:10.5194/acp-19-12687-2019.
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Lee, L., et al. (2019), Investigation of CATS aerosol products and application toward global diurnal variation of aerosols, Atmos. Chem. Phys., 19, 12687-12707, doi:10.5194/acp-19-12687-2019.
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Shi, Y.R., et al. (2019), Characterizing the 2015 Indonesia fire event using modified MODIS aerosol retrievals, Atmos. Chem. Phys., 19, 259-274, doi:10.5194/acp-19-259-2019.
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Toth, T., et al. (2019), A bulk-mass-modeling-based method for retrieving particulate matter pollution using CALIOP observations, Atmos. Meas. Tech., 12, 1739-1754, doi:10.5194/amt-12-1739-2019.
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Kaku, K.C., et al. (2018), Assessing the Challenges of Surface-Level Aerosol Mass Estimates From Remote Sensing During the SEAC4RS and SEARCH Campaigns: Baseline Surface Observations and Remote Sensing in the Southeastern United States, J. Geophys. Res., 123, 7530-7562, doi:10.1029/2017JD028074.
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Peng, X., et al. (2018), Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP), Q. J. R. Meteorol. Soc., 30, 8, doi:10.1002/qj.3497.
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Toth, T., et al. (2018), Minimum aerosol layer detection sensitivities and their subsequent impacts on aerosol optical thickness retrievals in CALIPSO level 2 data products, Atmos. Meas. Tech., 11, 499-514, doi:10.5194/amt-11-499-2018.
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Alfaro-Contreras, R., et al. (2017), A Study of the Longer Term Variation of Aerosol Optical Thickness and Direct 2 Shortwave Aerosol Radiative Effect Trends Using MODIS and CERES 3 4, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2017-365.
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Marquis, J.W., et al. (2017), Estimating Infrared Radiometric Satellite Sea Surface Temperature Retrieval Cold Biases in the Tropics due to Unscreened Optically Thin Cirrus Clouds, J. Atmos. Oceanic Technol., 34, 355-373, doi:10.1175/JTECH-D-15-0226.1.
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Reid, J.S., et al. (2017), Ground-based High Spectral Resolution Lidar observation of aerosol vertical distribution in the summertime Southeast United States, J. Geophys. Res., 122, doi:10.1002/2016JD025798.
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Rubin, J., et al. (2017), Assimilation of AERONET and MODIS AOT observations using variational and ensemble data assimilation methods and its impact on aerosol forecasting skill, J. Geophys. Res., 122, 4967-4992, doi:10.1002/2016JD026067.
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Kaku, K.C., et al. (2016), Investigation of the relative fine and coarse mode aerosol loadings and properties in the Southern Arabian Gulf region, Atmos. Res., 169, 171-182, doi:10.1016/j.atmosres.2015.09.029.
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Toth, T., et al. (2016), Temporal variability of aerosol optical thickness vertical distribution observed from CALIOP, J. Geophys. Res., 121, 9117-9139, doi:10.1002/2015JD024668.
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Christensen, M., et al. (2015), A theoretical study of the effect of subsurface oceanic bubbles on the enhanced aerosol optical depth band over the southern oceans as detected from MODIS and MISR, Atmos. Meas. Tech., 8, 2149-2160, doi:10.5194/amt-8-2149-2015.
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McHardy, T.M., et al. (2015), An improved method for retrieving nighttime aerosol optical thickness from the VIIRS Day/Night Band, Atmos. Meas. Tech., 8, 4773-4783, doi:10.5194/amt-8-4773-2015.
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Toth, T.D., et al. (2014), Impact of data quality and surface-to-column representativeness on the PM2.5/satellite AOD relationship for the contiguous United States, Atmos. Chem. Phys., 14, 6049-6062, doi:10.5194/acp-14-6049-2014.
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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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Campbell, J.R., et al. (2010), CALIOP Aerosol Subset Processing for Global Aerosol Transport Model Data Assimilation, Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, 3, 203-214, doi:10.1109/JSTARS.2010.2044868.
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Reid, J.S., et al. (2009), Global Monitoring and Forecasting of Biomass-Burning Smoke: Description of and Lessons From the Fire Locating and Modeling of Burning Emissions (FLAMBE) Program, Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, 2, 144-162, doi:10.1109/JSTARS.2009.2027443.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.