Richard Moore
Organization:
NASA Langley Research Center
Email:
Business Phone:
Work:
(757) 864-6043
Mobile:
(757) 759-1951
Business Address:
NASA LaRC MS 483
Hampton, VA 23681
United StatesFirst Author Publications:
- Moore, R., et al. (2021), Sizing response of the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) and Laser Aerosol Spectrometer (LAS) to changes in submicron aerosol composition and refractive index, Atmos. Meas. Tech., 14, 4517-4542, doi:10.5194/amt-14-4517-2021.
Co-Authored Publications:
- Crosbie, E., et al. (2024), Measurement report: Cloud and environmental properties associated with aggregated shallow marine cumulus and cumulus congestus, Atmos. Chem. Phys., doi:10.5194/acp-24-6123-2024.
- Decker, Z., et al. (2024), Airborne Observations Constrain Heterogeneous Nitrogen and Halogen Chemistry on Tropospheric and Stratospheric Biomass Burning Aerosol, Geophys. Res. Lett., 51, e2023GL107273, doi:10.1029/2023GL107273.
- Li, X., et al. (2024), Process Modeling of Aerosol‐Cloud Interaction in Summertime Precipitating Shallow Cumulus Over the Western North Atlantic, J. Geophys. Res., 129, e2023JD039489, doi:10.1029/2023JD039489.
- Zhang, J., et al. (2024), Stratospheric air intrusions promote global-scale new particle formation.Science, Wang, 385, 210-216, doi:10.1126/science.adn2961.
- Brunke, M. A., et al. (2023), Aircraft Observations of Turbulence in Cloudy and Cloud-Free Boundary Layers Over the Western North Atlantic Ocean From ACTIVATE and Implications for the Earth System Model Evaluation and Development, J. Geophys. Res..
- Corral, A., et al. (2023), Environmental Science: Atmospheres View Article Online PAPER View Journal Dimethylamine in cloud water: a case study over, The Author(s). Published by the Royal Society of Chemistry Environ. Sci.: Atmos, 10.1039/D2EA00117A, doi:10.1039/d2ea00117a.
- Ferrare, R., et al. (2023), Airborne HSRL-2 measurements of elevated aerosol depolarization associated with non-spherical sea salt, TYPE Original Research, doi:10.3389/frsen.2023.1143944.
- June, N. A., et al. (2023), Aerosol size distribution changes in FIREX-AQ biomass burning plumes: the impact of plume concentration on coagulation and OA condensation/evaporation, Atmos. Chem. Phys., doi:10.5194/acp-22-12803-2022.
- Li, X., et al. (2023), Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part II: Aerosol–Meteorology–Cloud Interaction, J. Atmos. Sci., 80, 1025-1045, doi:10.1175/JAS-D-21-0324.1.
- Rickly, P., et al. (2023), Emission factors and evolution of SO2 measured from biomass burning in wildfires and agricultural fires, Atmos. Chem. Phys., doi:10.5194/acp-22-15603-2022.
- Saide Peralta, et al. (2023), Understanding the Evolution of Smoke Mass Extinction Efficiency Using Field Campaign Measurements, Geophys. Res. Lett., 49, e2022GL099175, doi:10.1029/2022GL099175.
- Sorooshian, A., et al. (2023), Spatially coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: the NASA ACTIVATE dataset, Earth Syst. Sci. Data, 15, 3419-3472, doi:10.5194/essd-15-3419-2023.
- Tang, Y., et al. (2023), Evaluation of the NAQFC driven by the NOAA Global Forecast System (version 16): comparison with the WRF-CMAQ during the summer 2019 FIREX-AQ campaign, Geosci. Model. Dev., doi:10.5194/gmd-15-7977-2022.
- Travis, K. R., et al. (2023), Emission Factors for Crop Residue and Prescribed Fires in the Eastern US during FIREX-AQ, J. Geophys. Res., 128, e2023JD039309, doi:10.1029/2023JD039309.
- Warneke, C., et al. (2023), Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ), J. Geophys. Res., 128, e2022JD037758, doi:10.1029/2022JD037758.
- Bourgeois, I., et al. (2022), Comparison of airborne measurements of NO, NO2, HONO, NOy , and CO during FIREX-AQ, Atmos. Meas. Tech., 15, 4901-4930, doi:10.5194/amt-15-4901-2022.
- Corral, A., et al. (2022), Cold Air Outbreaks Promote New Particle Formation Off the U.S. East Coast, Geophys. Res. Lett..
- Dadashazar, H., et al. (2022), Analysis of MONARC and ACTIVATE Airborne Aerosol Data for Aerosol-Cloud Interaction Investigations: Efficacy of Stairstepping Flight Legs for Airborne In Situ Sampling, hosseind@arizona.edu (H.D.armin@arizona.edu (A.S., 13, 1242, doi:10.3390/atmos13081242.
- Dadashazar, H., et al. (2022), Organic enrichment in droplet residual particles relative to out of cloud over the northwestern Atlantic: analysis of airborne ACTIVATE data, Atmos. Chem. Phys., doi:10.5194/acp-22-13897-2022.
- Gryspeerdt, E., et al. (2022), The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data, Atmos. Meas. Tech., doi:10.5194/amt-2021-371.
- Kirschler, S., et al. (2022), Seasonal updraft speeds change cloud droplet number concentrations in low-level clouds over the western North Atlantic, Atmos. Chem. Phys., doi:10.5194/acp-22-8299-2022.
- Noyes, K. J., 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.
- Peterson, D., et al. (2022), Measurements from inside a Thunderstorm Driven by Wildfire: The 2019 FIREX-AQ Field Experiment, Bull. Amer. Meteor. Soc., 103, E2140-E2167, doi:10.1175/BAMS-D-21-0049.1.
- Saide Peralta, et al. (2022), Understanding the Evolution of Smoke Mass Extinction Efficiency Using Field Campaign Measurements, Geophys. Res. Lett., 49, e2022GL099175, doi:10.1029/2022GL099175.
- Sanchez, K., et al. (2022), North Atlantic Ocean SST-gradient-driven variations in aerosol and cloud evolution along Lagrangian cold-air outbreak trajectories, Atmos. Chem. Phys., 22, 2795-2815, doi:10.5194/acp-22-2795-2022.
- Schlosser, J., et al. (2022), Polarimeter + Lidar–Derived Aerosol Particle Number Concentration, Front. Remote Sens., 3, 885332, doi:10.3389/frsen.2022.885332.
- Tornow, F., et al. (2022), Dilution of Boundary Layer Cloud Condensation Nucleus Concentrations by Free Tropospheric Entrainment During Marine Cold Air Outbreaks, Geophys. Res. Lett., 49, e2022GL09844, doi:10.1029/2022GL098444.
- Decker, Z., et al. (2021), Nighttime and daytime dark oxidation chemistry in wildfire plumes: an observation and model analysis of FIREX-AQ aircraft data, Atmos. Chem. Phys., 21, 16293-16317, doi:10.5194/acp-21-16293-2021.
- Pagonis, D., et al. (2021), Airborne extractive electrospray mass spectrometry measurements of the chemical composition of organic aerosol, Atmos. Meas. Tech., 14, 1545-1559, doi:10.5194/amt-14-1545-2021.
- Sanchez, K., et al. (2021), Linking marine phytoplankton emissions, meteorological processes, and downwind particle properties with FLEXPART, Atmos. Chem. Phys., 21, 831-851, doi:10.5194/acp-21-831-2021.
- Wiggins, E. B., et al. (2021), Reconciling assumptions in bottom-up and top-down approaches for estimating aerosol emission rates from wildland fires using observations from FIREX-AQ, J. Geophys. Res., 126, e2021JD035692, doi:10.1029/2021JD035692.
- Sinclair, K., et al. (2020), Observations of Aerosol‐Cloud Interactions During the North Atlantic Aerosol and Marine Ecosystem Study, Geophys. Res. Lett., 47, 1-10, doi:10.1029/2019GL085851.
- Schuster, G., et al. (2019), A Laboratory Experiment for the Statistical Evaluation of Aerosol Retrieval (STEAR) Algorithms, Remote Sensing, 11, doi:10.3390/rs11050498.
- Sinclair, K., et al. (2019), Polarimetric retrievals of cloud droplet number concentrations T a,b,⁎ b,c b b,c, Remote Sensing of Environment, 228, 227-240, doi:10.1016/j.rse.2019.04.008.
- Alexandrov, M. D., et al. (2018), Retrievals of cloud droplet size from the research scanning polarimeter data: T Validation using in situ measurements, Remote Sensing of Environment, 210, 76-95, doi:10.1016/j.rse.2018.03.005.
- Segal-Rozenhaimer, M., et al. (2018), Bias and Sensitivity of Boundary Layer Clouds and Surface Radiative Fluxes in MERRA-2 and Airborne Observations Over the Beaufort Sea During the ARISE Campaign, J. Geophys. Res., 123, 6565-6580, doi:10.1029/2018JD028349.
- Smith, W., et al. (2017), Arctic Radiation-Icebridge Sea And Ice Experiment: The Arctic Radiant Energy System during the Critical Seasonal Ice Transition, Bull. Am. Meteorol. Soc., 1399-1426, doi:10.1175/BAMS-D-14-00277.1.
- Zamora, L., 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.
- Beyersdorf, A., et al. (2016), The impacts of aerosol loading, composition, and water uptake on aerosol extinction variability in the Baltimore–Washington, D.C. region, Atmos. Chem. Phys., 16, 1003-1015, doi:10.5194/acp-16-1003-2016.
- Corr, C. A., et al. (2016), Observational evidence for the convective transport of dust over the Central United States, J. Geophys. Res., 121, doi:10.1002/2015JD023789.
- Shinozuka, Y., et al. (2015), The relationship between cloud condensation nuclei (CCN) concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellite-based CCN estimates, Atmos. Chem. Phys., 15, 7585-7604, doi:10.5194/acp-15-7585-2015.
- Crumeyrolle, S., et al. (2014), Factors that influence surface PM2.5 values inferred from satellite observations: perspective gained for the US Baltimore–Washington metropolitan area during DISCOVER-AQ, Atmos. Chem. Phys., 14, 2139-2153, doi:10.5194/acp-14-2139-2014.
- Brock, C., et al. (2011), Characteristics, sources, and transport of aerosols measured in spring 2008 during the aerosol, radiation, and cloud processes affecting Arctic Climate (ARCPAC) Project, Atmos. Chem. Phys., 11, 2423-2453, doi:10.5194/acp-11-2423-2011.