Peng Xian
Organization:
Naval Research Laboratory
Email:
Business Address:
7 Grace Hopper Ave. Stop 2
Monterey, CA 93940
United StatesFirst Author Publications:
- 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.
- 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.
- 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.
Co-Authored Publications:
- Khan, A. L., P. Xian, and J. Schwarz (2023), Black carbon concentrations and modeled smoke deposition fluxes to the bare-ice dark zone of the Greenland Ice Sheet, The Cryosphere, 17, 2909-2918, doi:10.5194/tc-17-2909-2023.
- Lu, Z., et al. (2023), First Mapping of Monthly and Diurnal Climatology of Saharan Dust Layer Height Over the Atlantic Ocean From EPIC/DSCOVR in Deep Space, Geophys. Res. Lett., 50, e2022GL102552, doi:10.1029/2022GL102552.
- 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., 23, 7161-7175, doi:10.5194/acp-23-7161-2023.
- 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.
- 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.
- 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.
- 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.
- 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.
- Park, H. J., et al. (2020), Predicting Vertical Concentration Profiles in the Marine Atmospheric Boundary Layer With a Markov Chain Random Walk Model, J. Geophys. Res., 125, e2020JD032731, doi:10.1029/2020JD032731.
- Mardi, A. H., et al. (2018), Biomass Burning Plumes in the Vicinity of the California Coast: Airborne Characterization of Physicochemical Properties, Heating Rates, and Spatiotemporal Features, J. Geophys. Res., 123, 13,560-13,582, doi:10.1029/2018JD029134.
- 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.