Arlindo da Silva

Organization

Asticou Earth Systems, LLC

Website

https://www.asticou-earth.com/who-we-are

Co-Authored Publications

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.
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.
Zhou, M., et al. (2023), Enhancement of Nighttime Fire Detection and Combustion Efficiency Characterization Using Suomi-NPP and NOAA-20 VIIRS Instruments, IEEE Trans. Geosci. Remote Sens., 61, 4402420, doi:10.1109/TGRS.2023.3261664.
LeBlanc, S.E., et al. (2022), Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties, Atmos. Chem. Phys., doi:10.5194/acp-22-11275-2022.
Doherty, S.J., et al. (2021), Modeled and observed properties related to the direct aerosol radiative effect of biomass burning aerosol over the Southeast Atlantic, Atmos. Chem. Phys., doi:10.5194/acp-2021-333 (submitted).
Pistone, K., et al. (2021), Exploring the elevated water vapor signal associated with the free-tropospheric biomass burning plume over the southeast Atlantic Ocean, Atmos. Chem. Phys., doi:10.5194/acp-2020-1322 (submitted).
Pistone, K., et al. (2021), Exploring the elevated water vapor signal associated with the free tropospheric biomass burning plume over the southeast Atlantic Ocean, Atmos. Chem. Phys., 21, 9643-9668, doi:10.5194/acp-21-9643-2021.
Xu, F., et al. (2021), A Combined Lidar-Polarimeter Inversion Approach for Aerosol Remote Sensing Over Ocean, Front. Remote Sens., 2, 1-24, doi:10.3389/frsen.2021.620871.
Carter, T.S., et al. (2020), How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America, Atmos. Chem. Phys., 20, 2073-2097, doi:10.5194/acp-20-2073-2020.
Shinozuka, Y., et al. (2020), Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016, Atmos. Chem. Phys., 20, 11491-11526, doi:10.5194/acp-20-11491-2020.
Wang, J., et al. (2020), Detecting nighttime fire combustion phase by hybrid application of visible T and infrared radiation from Suomi NPP VIIRS, Remote Sensing of Environment, 237, 111466, doi:10.1016/j.rse.2019.111466.
Bian, H., et al. (2019), Observationally constrained analysis of sea salt aerosol in the marine atmosphere, Atmos. Chem. Phys., 19, 10773-10785, doi:10.5194/acp-19-10773-2019.
Pérez-Ramírez, D., et al. (2019), Retrievals of aerosol single scattering albedo by multiwavelength lidar T measurements: Evaluations with NASA Langley HSRL-2 during discover-AQ field campaigns ⁎, Remote Sensing of Environment, 222, 144-164, doi:10.1016/j.rse.2018.12.022.
shinozuka, et al. (2019), Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016, Atmos. Chem. Phys. Discuss., doi:https://doi.org/10.5194/acp-2019-678 (submitted).
Liu, F., et al. (2018), A new global anthropogenic SO2 emission inventory for the last decade: a mosaic of satellite-derived and bottom-up emissions, Atmos. Chem. Phys., 18, 16571-16586, doi:10.5194/acp-18-16571-2018.
Veselovskii, I., et al. (2018), Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie–Raman lidar observations, Atmos. Meas. Tech., 11, 949-969, doi:10.5194/amt-11-949-2018.
Buchard, V., et al. (2017), The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part II: Evaluation and Case Studies, J. Climate, 30, 6851-6872, doi:10.1175/JCLI-D-16-0613.1.
Hughes, E.J., et al. (2016), Using CATS near-real-time lidar observations to monitor and constrain volcanic sulfur dioxide (SO2) forecasts, Geophys. Res. Lett., 43, 11,089-11,097, doi:10.1002/2016GL070119.
Yu, P., et al. (2016), Surface dimming by the 2013 Rim Fire simulated by a sectional aerosol model, J. Geophys. Res., 121, 7079-7087, doi:10.1002/2015JD024702.
Buchard, V., et al. (2015), Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis, Atmos. Chem. Phys., 15, 5743-5760, doi:10.5194/acp-15-5743-2015.
Saide, P.E., et al. (2015), Revealing important nocturnal and day-to-day variations in fire smoke emissions through a multiplatform inversion, Geophys. Res. Lett., 42, 3609-3618, doi:10.1002/2015GL063737.
Matsui, T., et al. (2014), Current And Future Perspectives Of Aerosol Research At Nasa Goddard Space Flight Center, Bull. Am. Meteorol. Soc., 1-5, doi:10.1175/BAMS-D-13-00153.1.
Reale, O., et al. (2014), Impact of assimilated and interactive aerosol on tropical cyclogenesis, Geophys. Res. Lett., 41, 3282-3288, doi:10.1002/2014GL059918.
Zhang, F., et al. (2014), Sensitivity of mesoscale modeling of smoke direct radiative effect to the emission inventory: A case study in northern sub-Saharan African region, Environmental Research Letter, 9, 075002, doi:10.1088/1748-9326/9/7/075002.
Bian, H., et al. (2013), Source attributions of pollution to the Western Arctic during the NASA ARCTAS field campaign, Atmos. Chem. Phys., 13, 4707-4721, doi:10.5194/acp-13-4707-2013.
Randles, C.A., et al. (2013), Direct and semi-direct aerosol effects in the NASA GEOS-5 AGCM: aerosol-climate interactions due to prognostic versus prescribed aerosols, J. Geophys. Res., 118, 149-169, doi:10.1029/2012JD018388.
Choi, S., et al. (2012), Analysis of satellite-derived Arctic tropospheric BrO columns in conjunction with aircraft measurements during ARCTAS and ARCPAC, Atmos. Chem. Phys., 12, 1255-1285, doi:10.5194/acp-12-1255-2012.
Liang, Q., et al. (2011), Reactive nitrogen, ozone and ozone production in the Arctic troposphere and the impact of stratosphere-troposphere exchange, Atmos. Chem. Phys., 11, 13181-13199, doi:10.5194/acp-11-13181-2011.
Witte, J.C., et al. (2011), NASA A-Train and Terra observations of the 2010 Russian wildfires, Atmos. Chem. Phys., 11, 9287-9301, doi:10.5194/acp-11-9287-2011.
Colarco, P., et al. (2010), Online simulations of global aerosol distributions in the NASA GEOS‐4 model and comparisons to satellite and ground‐based aerosol optical depth, J. Geophys. Res., 115, D14207, doi:10.1029/2009JD012820.
Salawitch, R.J., et al. (2010), A new interpretation of total column BrO during Arctic spring, Geophys. Res. Lett., 37, L21805, doi:10.1029/2010GL043798.
Wong, S., et al. (2008), Long-term variability in Saharan dust transport and its link to North Atlantic sea surface temperature, Geophys. Res. Lett., 35, L07812, doi:10.1029/2007GL032297.
Joiner, J., et al. (2007), Effects of data selection and error specification on the assimilation of AIRS data, Q. J. R. Meteorol. Soc., 133, 181-196, doi:10.1002/qj.8.
Weaver, C., et al. (2007), Direct Insertion of MODIS Radiances in a Global Aerosol Transport Model, J. Atmos. Sci., 64, 808-826, doi:10.1175/JAS3838.1.

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

National Aeronautics and Space Administration

National Aeronautics and
Space Administration