Sciences and Exploration Directorate

Arlindo M da Silva

(RESEARCH AST, METEOROLOGICAL STUDIES)

 arlindo.m.dasilva@nasa.gov

 301.614.6174

Org Code: 610.1

NASA/GSFC
 Mail Code: 610.1
 Greenbelt, MD 20771

Employer: NASA

Brief Bio

Dr. Arlindo da Silva is a Research Meteorologist at the Global Modeling and Assimilation Office (GMAO, formerly DAO), NASA/Goddard Space Flight Center, where he has worked since 1994. Prior to joining the GMAO, Dr. da Silva held a faculty position at the University of Wisconsin-Milwaukee from 1990-1993, and was a Visiting Scientist at Princeton University/Geophysical Fluid Dynamics Laboratory from 1989-1990.

Originally trained as a physicist and atmospheric dynamicist, Dr. da Silva’s research has spanned a number of related topics in the last decades: dynamics of stationary and transient atmospheric waves, numerical modeling of Lake Michigan, estimation of fluxes of heat, momentum, and fresh water fluxes over the global oceans, climate diagnostics, including aerosol forcing of climate, hydrological cycle of the subtropics and Amazon basin and data assimilation. Since joining GSFC Dr. da Silva’s research has focused on techniques for 4-dimensional data assimilation, including physical-space analysis systems, error covariance modeling, forecast bias estimation and correction, quality control of observations, land-surface, precipitation, aerosol and constituent data assimilation. Dr. da Silva was the lead developer for the Physical-space Statistical Analysis System (PSAS), GEOS-4 atmospheric data assimilation system, the Quick Fire Emission Dataset (QFED), and the Goddard Aerosol Assimilation System within GEOS. Dr. da Silva was the data assimilation PI for the original Earth System Modeling Framework (ESMF) project and currently serves in the ESMF executive board. From 2014  to 2018 Dr. da Silva served as the Science Study Lead for the Aerosol-Cloud-Ecosystems (ACE) Decadal Survey Pre-formulation Study.  Currently, Dr. da Silva is the GSFC Science co-lead for the Aerosols and Clouds-Convection-Precipitation Decadal Survey Pre-formulation Study. 

Dr. da Silva has been active in the open source software community being the founder and main developer of the OpenGrADS Project (http://opengrads.org).

Research Interests

Global Aerosol Modeling and Data Assimilation

Earth Science: Aerosols

Development of global aerosol models and advanced data assimilation techniques for assimilating satellite measurements in such models. Application of these systems for air-quality forecasting, historical reanalyses, and observing system simulations in support of future NASA space missions. Curen activities include advancing the representation of aerosols in the GEOS-5 earth system model, application of Ensemble Kalman Filter (EnKF) algorithms for the assimilation of aerosol observations, and use of machine learning algorithms for aerosol retrievals.

Cloud Data Assimilation

Earth Science: Clouds

Development of advanced algorithms for assimilation of spaceborne cloud observations in global earth system models. Recent activities focus on the application of Bayesian inference for estimating the sub-grid p.d.f. of water vapor and cloud condensate from high resolution satellite data.

Biomass Burning Emissions

Earth Science: Fire

Estimation of biomass burning emissions for driving global earth system models. Recent activities have focused on top-down algorithms based on fire radiative power and data assimilation techniques leading to the development of the Quick Fire Emission Dataset (QFED).

Observing System Simulation Experiments (OSSE) for Clouds and Atmospheric Composition

Earth Science: Theory & Modeling

A model-base Observing System Simulation Experiment (OSSE) is a framework for numerical experimentation in which observables are simulated from fields generated by an earth system model, including a parameterized description of the observational error characteristics. Such simulations are performed in support of an experimental goal. Current focus is on the application of a rigorous OSSE methodology for cloud, aerosol and trace gases measurements to existing and future NASA observing missions.

Software Frameworks for Earth System Modeling and Data Assimilation

Earth Science: Theory & Modeling

Development of high-performance, flexible software infrastructure for building and coupling weather, climate, data assimilation and related Earth science applications. Specific activities include advancing the Earth System Modeling Framework (ESMF) through development of integrated development environments, and refiniment of usability layers such as MAPL and NUOPC for enhanced interoperability.

Education

PhD in Meteorology, 1989, Massachusetts Institute of Technology, under the supervision of R. Lindzen. Thesis: The role of temporal changes of the zonal wind on the excitation of large scale transients.

MS in Physics, 1984,  Catholic University of Rio de Janeiro (PUC/RJ), Brazil. Thesis: Evolution of quantum systems periodic in time.

BS in Physics, 1982, Catholic University of Rio de Janeiro (PUC/RJ), Brazil

Positions/Employment

AST, Research Meteorologist

NASA Goddard Space Flight Center - Greenbelt, Maryland

September 1994 - Present

Research meteorologist at the Global Modeling and Assimilation Office (GMAO, formerly the Data Assimilation Office - DAO). Since joining GSFC Dr. da Silva’s research has focused on techniques for 4-dimensional data assimilation, including physical-space analysis systems, error covariance modeling, forecast bias estimation and correction, quality control of observations, land-surface, precipitation, aerosol and constituent data assimilation. Dr. da Silva was the lead developer for the Physical-space Statistical Analysis System (PSAS), GEOS-4 atmospheric data assimilation system, and the Goddard Aerosol Assimilation System (GAAS) within GEOS-5. Dr. da Silva was the data assimilation PI for the original Earth System Modeling Framework (ESMF) proposal and currently serves in the ESMF executive board. Since 2014 Dr. da Silva is the Science Study Lead for the Aerosol-Cloud-Ecosystems (ACE) Decadal Survey Mission.

Visiting Scientist

University Space Research Association (USRA) - at NASA/GSFC in Greenbelt, Maryland.

February 1994 - September 1994

Development of atmospheric data assimilation algorithms.

Assistant Professor

University of Wisconsin-Milwaukee - Milwaukee, Wisconsin

September 1990 - 1993

Taught graduate and undergraduate courses in atmospheric and oceanic sciences. Research activities focused on the estimation of historical surface marine fluxes of heat, moment and fresh water over the global oceans, numerical modeling of Lake Michigan and tropical dynamics.

Visiting Scientist

Princeton University - at the Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey.

April 1989 - September 1990

Research acitivities include numerical modeling of stationary waves, climate diagnostics and estimation of surface marine fluxes.

Professional Societies

American Meteorological Society

Former President of the Milwaukee Chapter of the American Meteorological Society (1993).

1985 - Present

American Geophysical Union

1995 - Present

American Association for the Advancement of Science

2000 - Present

Professional Service

• Member, Earth System Modeling Framework (ESMF) Executive Board (2003-present)
• Member, NUOPC Common Modeling Architecture Working Group (2012-2018)
• CALIPSO Science Team
• Co-Chair, GEO-CAPE Global OSSE Working Group (2013-2017)
• AMS Committee on Air-sea Interactions (1998)
• JSC/SCOR Working Group on Air -sea fluxes (1997-1999)
 

Teaching Experience

Graduate/undergraduate courses taught at the University of Wisconsin-Milwaukee:

  1. Survey of Meteorology (undergraduate)
  2. Earth, Air, Wind and Fire (undergraduate)
  3. Weather: Principles and Forecasting (undergraduate)
  4. Dynamic Meteorology I (undergraduate/graduate)
  5. Dynamic Meteorology II (undergraduate/graduate)
  6. Advanced Synoptic Meteorology I (undergraduate/graduate)
  7. Advanced Synoptic Meteorology II (undergraduate/graduate)
  8. Physical Oceanography (undergraduate/graduate)
  9. Numerical Weather Prediction (graduate)
  10. Topics on ENSO (graduate)
  11. Introduction to McIdas (undergraduate)
     

Publications

Refereed

Kahn, R. A., E. Andrews, C. A. Brock, et al. M. Chin, G. Feingold, A. Gettelman, R. C. Levy, D. M. Murphy, A. Nenes, J. R. Pierce, T. Popp, J. Redemann, A. M. Sayer, A. da Silva, L. Sogacheva, and P. Stier. 2023. Reducing Aerosol Forcing Uncertainty By Combining Models with Satellite and Within‐the‐Atmosphere Observations: A Three‐Way Street Reviews of Geophysics [10.1029/2022rg000796]

Kopacz, M., V. Breeze, S. Kondragunta, et al. G. Frost, S. Anenberg, L. Bruhwiler, S. Davis, A. da Silva, J. de Gouw, R. Duren, L. Flynn, A. Gaudel, M. Geigert, G. Goldman, J. Joiner, B. McDonald, L. Ott, V.-H. Peuch, S. E. Pusede, I. Stajner, C. Seftor, C. Sweeney, L. C. Valin, J. Wang, J. Whetstone, and S. Kalluri. 2023. Global Atmospheric Composition Needs from Future Ultraviolet–Visible–Near-Infrared (UV–Vis–NIR) NOAA Satellite Instruments Bulletin of the American Meteorological Society 104 (3): E623-E630 [10.1175/bams-d-22-0266.1]

Collow, A. B., V. Buchard, P. R. Colarco, et al. A. M. da Silva, R. Govindaraju, E. P. Nowottnick, S. Burton, R. Ferrare, C. Hostetler, and L. Ziemba. 2022. An evaluation of biomass burning aerosol mass, extinction, and size distribution in GEOS using observations from CAMP<sup>2</sup>Ex Atmospheric Chemistry and Physics 22 (24): 16091-16109 [10.5194/acp-22-16091-2022]

LeBlanc, S. E., M. Segal-Rozenhaimer, J. Redemann, et al. C. Flynn, R. R. Johnson, S. E. Dunagan, R. Dahlgren, J. Kim, M. Choi, A. da Silva, P. Castellanos, Q. Tan, L. Ziemba, K. Lee Thornhill, and M. Kacenelenbogen. 2022. Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties Atmospheric Chemistry and Physics 22 (17): 11275-11304 [10.5194/acp-22-11275-2022]

Go, S., A. Lyapustin, G. L. Schuster, et al. M. Choi, P. Ginoux, M. Chin, O. Kalashnikova, O. Dubovik, J. Kim, A. da Silva, B. Holben, and J. S. Reid. 2022. Inferring iron-oxide species content in atmospheric mineral dust from DSCOVR EPIC observations Atmospheric Chemistry and Physics 22 (2): 1395-1423 [10.5194/acp-22-1395-2022]

Wind, G., A. M. da Silva, K. G. Meyer, S. Platnick, and P. M. Norris. 2022. Analysis of the MODIS above-cloud aerosol retrieval algorithm using MCARS Geoscientific Model Development 15 (1): 1-14 [10.5194/gmd-15-1-2022]

Marshak, A., A. Ackerman, A. Da Silva, et al. T. Eck, B. Holben, R. Kahn, R. Kleidman, K. Knobelspiesse, R. C. Levy, A. Lyapustin, L. Oreopoulos, L. Remer, O. Torres, T. Varnai, G. Wen, and J. Yorks. 2021. Aerosol properties in cloudy environments from remote sensing observations: a review of the current state of knowledge Bulletin of the American Meteorological Society 1-57 [10.1175/bams-d-20-0225.1]

Xu, F., L. Gao, J. Redemann, et al. C. Flynn, W. R. Espinosa, A. M. Da Silva, S. Stamnes, S. Burton, X. Liu, R. Ferrare, B. Cairns, and O. Dubovik. 2021. A Combined Lidar-Polarimeter Inversion Approach for Aerosol Remote Sensing Over Ocean Frontiers in Remote Sensing 2 (2):

Yasunari, T. J., H. Nakamura, K.-M. Kim, et al. N. Choi, M.-I. Lee, Y. Tachibana, and A. M. da Silva. 2021. Relationship between circum-Arctic atmospheric wave patterns and large-scale wildfires in boreal summer Environmental Research Letters 16 (6): 064009 [10.1088/1748-9326/abf7ef]

Redemann, J., R. Wood, P. Zuidema, et al. S. J. Doherty, B. Luna, S. E. LeBlanc, M. S. Diamond, Y. Shinozuka, I. Y. Chang, R. Ueyama, L. Pfister, J.-M. Ryoo, A. N. Dobracki, A. M. da Silva, K. M. Longo, M. S. Kacenelenbogen, C. J. Flynn, K. Pistone, N. M. Knox, S. J. Piketh, J. M. Haywood, P. Formenti, M. Mallet, P. Stier, A. S. Ackerman, S. E. Bauer, A. M. Fridlind, G. R. Carmichael, P. E. Saide, G. A. Ferrada, S. G. Howell, S. Freitag, B. Cairns, B. N. Holben, K. D. Knobelspiesse, S. Tanelli, T. S. L'Ecuyer, A. M. Dzambo, O. O. Sy, G. M. McFarquhar, M. R. Poellot, S. Gupta, J. R. O'Brien, A. Nenes, M. E. Kacarab, J. P. Wong, J. D. Small-Griswold, K. L. Thornhill, D. Noone, J. R. Podolske, K. S. Schmidt, P. Pilewskie, H. Chen, S. P. Cochrane, A. J. Sedlacek, T. J. Lang, E. Stith, M. Segal-Rozenhaimer, R. A. Ferrare, S. P. Burton, C. A. Hostetler, D. J. Diner, S. E. Platnick, J. S. Myers, K. G. Meyer, D. A. Spangenberg, H. Maring, and L. Gao. 2021. An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol-cloud-radiation interactions in the Southeast Atlantic basin Atmospheric Chemistry and Physics [10.5194/acp-21-1507-2021]

Knobelspiesse, K., H. M. Barbosa, C. Bradley, et al. C. Bruegge, B. Cairns, G. Chen, J. Chowdhary, A. Cook, A. Di Noia, B. van Diedenhoven, D. J. Diner, R. Ferrare, G. Fu, M. Gao, M. Garay, J. Hair, D. Harper, G. van Harten, O. Hasekamp, M. Helmlinger, C. Hostetler, O. Kalashnikova, A. Kupchock, K. Longo De Freitas, H. Maring, J. V. Martins, B. McBride, M. McGill, K. Norlin, A. Puthukkudy, B. Rheingans, J. Rietjens, F. C. Seidel, A. da Silva, M. Smit, S. Stamnes, Q. Tan, S. Val, A. Wasilewski, F. Xu, X. Xu, and J. Yorks. 2020. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) airborne field campaign Earth System Science Data 12 (3): 2183-2208 [10.5194/essd-12-2183-2020]

Pérez-Ramírez, D., D. N. Whiteman, I. Veselovskii, et al. M. Korenski, P. R. Colarco, and A. M. da Silva. 2020. Optimized profile retrievals of aerosol microphysical properties from simulated spaceborne multiwavelength Lidar Journal of Quantitative Spectroscopy and Radiative Transfer 246 106932 [10.1016/j.jqsrt.2020.106932]

Ukhov, A., S. Mostamandi, N. Krotkov, et al. J. Flemming, A. Silva, C. Li, V. Fioletov, C. McLinden, A. Anisimov, Y. M. Alshehri, and G. Stenchikov. 2020. Study of SO Pollution in the Middle East Using MERRA‐2, CAMS Data Assimilation Products, and High‐Resolution WRF‐Chem Simulations Journal of Geophysical Research: Atmospheres 125 (6): [10.1029/2019jd031993]

Fu, G., O. Hasekamp, J. Rietjens, et al. M. Smit, A. Di Noia, D. Diner, F. Xu, M. Gao, S. Burton, C. Hostetler, J. Hair, R. Ferrare, K. D. Knobelspiesse, B. Cairns, A. P. Wasilewski, and A. M. Da Silva. 2020. Aerosol retrievals from different polarimeters during the ACEPOL campaign using a common retrieval algorithm Atmospheric Measurement Techniques 13 553-573 [10.5194/amt-13-553-2020]

Lee, S., M.-I. Lee, C.-K. Song, K.-M. Kim, and A. M. da Silva. 2020. Interannual variation of the East Asia Jet Stream and its impact on the horizontal distribution of aerosol in boreal spring Atmospheric Environment 223 117296 [10.1016/j.atmosenv.2020.117296]

Pan, X., C. Ichoku, M. Chin, et al. H. Bian, A. Darmenov, P. Colarco, L. Ellison, T. Kucsera, A. da Silva, J. Wang, T. Oda, and G. Cui. 2020. Six Global Biomass Burning Emission Datasets: Inter-comparison and Application in one Global Aerosol Model Atmos. Chem. Phys 20 (2): 969–994 [10.5194/acp-20-969-2020]

Bian, H., K. Froyd, D. M. Murphy, et al. J. Dibb, M. Chin, P. R. Colarco, A. Darmenov, A. da Silva, T. L. Kucsera, G. Schill, H. Yu, P. Bui, M. Dollner, B. Weinzierl, and A. Smirnov. 2019. Observationally constrained analysis of sea salt aerosol in the marine atmosphere Atmospheric Chemistry and Physics 19 10773-10785 [10.5194/acp-19-10773-2019]

Pérez-Ramírez, D., D. N. Whiteman, I. Veselovskii, et al. P. Colarco, M. Korenski, and A. da Silva. 2019. Retrievals of aerosol single scattering albedo by multiwavelength lidar measurements: Evaluations with NASA Langley HSRL-2 during discover-AQ field campaigns Remote Sensing of Environment 222 144-164 [10.1016/j.rse.2018.12.022]

Xian, P., J. S. Reid, E. J. Hyer, et al. C. R. Sampson, J. I. Rubin, M. Ades, N. Asencio, S. Basart, A. Benedetti, P. Bhattacharjee, M. E. Brooks, P. R. Colarco, A. Da Silva, T. F. Eck, J. Guth, O. Jorba, R. Kouznetsov, Z. Kipling, M. Sofiev, C. P. Carcia‐Pando, Y. Pradhan, T. Tanaka, J. Wang, D. L. Westphal, K. Yumimoto, and J. Zhang. 2019. Current State of the global operational aerosol multi‐model ensemble: an update from the International Cooperative for Aerosol Prediction (ICAP) Quarterly Journal of the Royal Meteorological Society 145 (S1): 176-209 [10.1002/qj.3497]

Castellanos, P., A. da Silva, A. Darmenov, et al. V. Buchard, R. Govindaraju, P. Ciren, and S. Kondragunta. 2018. A Geostationary Instrument Simulator for Aerosol Observing System Simulation Experiments Atmosphere 10 (1): 2 [10.3390/atmos10010002]

Liu, F., S. Choi, C. Li, et al. V. E. Fioletov, C. A. McLinden, J. Joiner, N. A. Krotkov, H. Bian, G. Janssens-Maenhout, A. S. Darmenov, and A. M. da Silva. 2018. A new global anthropogenic SO2 emission inventory for the last decade: a mosaic of satellite-derived and bottom-up emissions Atmospheric Chemistry and Physics 18 (22): 16571-16586 [10.5194/acp-18-16571-2018]

Hu, L., C. A. Keller, M. S. Long, et al. T. Sherwen, B. Auer, A. Da Silva, J. E. Nielsen, S. Pawson, M. A. Thompson, A. L. Trayanov, K. R. Travis, S. K. Grange, M. J. Evans, and D. J. Jacob. 2018. Global simulation of tropospheric chemistry at 12.5&amp;thinsp;km resolution: performance and evaluation of the GEOS-Chem chemical module (v10-1) within the NASA GEOS Earth system model (GEOS-5 ESM) Geoscientific Model Development 11 (11): 4603-4620 [10.5194/gmd-11-4603-2018]

Benedetti, A., J. S. Reid, P. Knippertz, et al. J. H. Marsham, F. Di Giuseppe, S. Rémy, S. Basart, O. Boucher, I. M. Brooks, L. Menut, L. Mona, P. Laj, G. Pappalardo, A. Wiedensohler, A. Baklanov, M. Brooks, P. R. Colarco, E. Cuevas, A. da Silva, J. Escribano, J. Flemming, N. Huneeus, O. Jorba, S. Kazadzis, S. Kinne, T. Popp, P. K. Quinn, T. T. Sekiyama, T. Tanaka, and E. Terradellas. 2018. Status and future of numerical atmospheric aerosol prediction with a focus on data requirements Atmospheric Chemistry and Physics 18 (14): 10615-10643 [10.5194/acp-18-10615-2018]

Choi, S., N. Theys, R. J. Salawitch, et al. P. A. Wales, J. Joiner, T. P. Canty, K. Chance, R. M. Suleiman, S. P. Palm, R. I. Cullather, A. S. Darmenov, A. da Silva, T. P. Kurosu, F. Hendrick, and M. Van Roozendael. 2018. Link Between Arctic Tropospheric BrO Explosion Observed From Space and Sea-Salt Aerosols From Blowing Snow Investigated Using Ozone Monitoring Instrument BrO Data and GEOS-5 Data Assimilation System Journal of Geophysical Research: Atmospheres 123 [10.1029/2017jd026889]

Eck, T. F., B. N. Holben, J. S. Reid, et al. P. Xian, D. M. Giles, A. Sinyuk, A. Smirnov, J. S. Schafer, I. Slutsker, J. Kim, J.-H. Koo, M. Choi, K. C. Kim, I. Sano, A. Arola, A. M. Sayer, R. C. Levy, L. A. Munchak, N. T. O’Neill, A. Lyapustin, N. C. Hsu, C. A. Randles, A. M. Da Silva, V. Buchard, R. C. Govindaraju, E. Hyer, J. H. Crawford, P. Wang, and X. Xia. 2018. Observations of the Interaction and Transport of Fine Mode Aerosols with Cloud and/or Fog in Northeast Asia from Aerosol Robotic Network (AERONET) and Satellite Remote Sensing Journal of Geophysical Research: Atmospheres [10.1029/2018JD028313]

Yasunari, T. J., K.-M. Kim, A. M. da Silva, et al. M. Hayasaki, M. Akiyama, and N. Murao. 2018. Extreme air pollution events in Hokkaido, Japan, traced back to early snowmelt and large-scale wildfires over East Eurasia: Case studies Scientific Reports 8 (1): 6413 [10.1038/s41598-018-24335-w]

Nowottnick, E. P., P. R. Colarco, S. A. Braun, et al. D. O. Barahona, A. da Silva, D. L. Hlavka, M. J. McGill, and J. R. Spackman. 2018. Dust Impacts on the 2012 Hurricane Nadine Track during the NASA HS3 Field Campaign Journal of the Atmospheric Sciences JAS-D-17-0237.1 [10.1175/jas-d-17-0237.1]

Veselovskii, I., P. Goloub, T. Podvin, et al. D. Tanre, A. da Silva, P. Colarco, P. Castellanos, M. Korenskiy, Q. Hu, D. N. Whiteman, D. Pérez-Ramírez, P. Augustin, M. Fourmentin, and A. Kolgotin. 2018. Characterization of smoke and dust episode over West Africa: comparison of MERRA-2 modeling with multiwavelength Mie–Raman lidar observations Atmospheric Measurement Techniques 11 (2): 949-969 [10.5194/amt-11-949-2018]

Nielsen, J. E., S. Pawson, A. Molod, et al. B. Auer, A. M. da Silva, A. R. Douglass, B. Duncan, Q. Liang, M. Manyin, L. D. Oman, W. Putman, S. E. Strahan, and K. Wargan. 2017. Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model Journal of Advances in Modeling Earth Systems [10.1002/2017ms001011]

Sullivan, R. C., R. C. Levy, A. M. da Silva, and S. C. Pryor. 2017. Developing and diagnosing climate change indicators of regional aerosol optical properties Scientific Reports 7 (1): 18093 [10.1038/s41598-017-18402-x]

Colarco, P. R., S. Gassó, C. Ahn, et al. V. Buchard, A. M. da Silva, and O. Torres. 2017. Simulation of the Ozone Monitoring Instrument aerosol index using the NASA Goddard Earth Observing System aerosol reanalysis products Atmospheric Measurement Techniques 10 (11): 4121-4134 [10.5194/amt-10-4121-2017]

Randles, C. A., A. M. da Silva, V. Buchard, et al. P. R. Colarco, A. Darmenov, R. Govindaraju, A. Smirnov, B. Holben, R. Ferrare, J. Hair, Y. Shinozuka, and C. J. Flynn. 2017. The MERRA-2 Aerosol Reanalysis, 1980 – onward, Part I: System Description and Data Assimilation Evaluation Journal of Climate 30 (17): 6823-6850 [10.1175/jcli-d-16-0609.1]

Buchard, V., C. A. Randles, A. M. da Silva, et al. A. Darmenov, P. R. Colarco, R. Govindaraju, R. Ferrare, J. Hair, A. J. Beyersdorf, L. D. Ziemba, and H. Yu. 2017. The MERRA-2 Aerosol Reanalysis, 1980 -- onward, Part II: Evaluation and Case Studies Journal of Climate JCLI-D-16-0613.1 [10.1175/jcli-d-16-0613.1]

Gelaro, R., W. McCarty, M. J. Suárez, et al. R. Todling, A. Molod, L. Takacs, C. Randles, A. Darmenov, M. G. Bosilovich, R. Reichle, K. Wargan, L. Coy, R. Cullather, C. Draper, S. Akella, V. Buchard, A. Conaty, A. da Silva, W. Gu, G.-K. Kim, R. Koster, R. Lucchesi, D. Merkova, J. E. Nielsen, G. Partyka, S. Pawson, W. Putman, M. Rienecker, S. D. Schubert, M. Sienkiewicz, and B. Zhao. 2017. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) Journal of Climate 30 5419–5454 [10.1175/jcli-d-16-0758.1]

Yasunari, T. J., M. Niwano, Y. Fujiyoshi, et al. A. Shimizu, M. Hayasaki, T. Aoki, A. M. da Silva, B. N. Holben, S. Matoba, N. Murao, S. Yamagata, and K.-M. Kim. 2017. An Unreported Asian Dust (Kosa) Event in Hokkaido, Japan: A Case Study of 7 March 2016 SOLA 13 (0): 96-101 [10.2151/sola.2017-018]

Provençal, S., V. Buchard, A. M. da Silva, R. Leduc, and N. Barrette. 2017. Evaluation of PM surface concentrations simulated by Version 1 of NASA's MERRA Aerosol Reanalysis over Europe Atmospheric Pollution Research 8 (2): 374-382 [10.1016/j.apr.2016.10.009]

Provençal, S., V. Buchard, A. M. da Silva, et al. R. Leduc, N. Barrette, E. Elhacham, and S.-H. Wang. 2017. Evaluation of PM2. 5 Surface Concentrations Simulated by Version 1 of NASA’s MERRA Aerosol Reanalysis over Israel and Taiwan Aerosol and Air Quality Research 17 (1): 253--261 [10.4209/aaqr.2016.04.0145]

Hughes, E. J., J. Yorks, N. A. Krotkov, A. M. da Silva, and M. McGill. 2016. Using CATS Near-Realtime Lidar Observations to Monitor and Constrain Volcanic Sulfur Dioxide (SO2) Forecasts Geophysical Research Letters [10.1002/2016gl070119]

Wind, G., A. M. da Silva, P. M. Norris, et al. S. Platnick, S. Mattoo, and R. C. Levy. 2016. Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters – Part 2: Aerosols Geosci. Model Dev. 9 (7): 2377-2389 [10.5194/gmd-9-2377-2016]

Norris, P. M., and A. M. da Silva. 2016. Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results Q.J.R. Meteorol. Soc. 142 (699): 2528-2540 [10.1002/qj.2844]

Norris, P. M., and A. M. da Silva. 2016. Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 1: Method Q.J.R. Meteorol. Soc. 142 (699): 2505-2527 [10.1002/qj.2843]

Theurich, G., C. DeLuca, T. Campbell, et al. F. Liu, K. Saint, M. Vertenstein, J. Chen, R. Oehmke, J. Doyle, T. Whitcomb, A. Wallcraft, M. Iredell, T. Black, A. M. Da Silva, T. Clune, R. Ferraro, P. Li, M. Kelley, I. Aleinov, V. Balaji, N. Zadeh, R. Jacob, B. Kirtman, F. Giraldo, D. McCarren, S. Sandgathe, S. Peckham, and R. Dunlap. 2016. The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability Bulletin of the American Meteorological Society 97 (7): 1229-1247 [10.1175/bams-d-14-00164.1]

Lu, C.-H., A. da Silva, J. Wang, et al. S. Moorthi, M. Chin, P. Colarco, Y. Tang, P. S. Bhattacharjee, S.-P. Chen, H.-Y. Chuang, H.-M. H. Juang, J. McQueen, and M. Iredell. 2016. The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP Geosci. Model Dev. 9 (5): 1905-1919 [10.5194/gmd-9-1905-2016]

Buchard, V., A. da Silva, C. Randles, et al. P. Colarco, R. Ferrare, J. Hair, C. Hostetler, J. Tackett, and D. Winker. 2016. Evaluation of the surface PM2.5 in Version 1 of the NASA MERRA Aerosol Reanalysis over the United States Atmospheric Environment 125 (Part A): 100-111 [10.1016/j.atmosenv.2015.11.004]

Yasunari, T. J., P. R. Colarco, W. K. Lau, et al. K. Osada, M. Kido, S. P. Mahanama, K.-M. Kim, and A. M. Da Silva. 2016. Total dust deposition flux during precipitation in Toyama, Japan, in the spring of 2009: A sensitivity analysis with the NASA GEOS-5 Model Atmospheric Research 167 298–313 [10.1016/j.atmosres.2015.08.005]

Randles, C. A., A. M. Da Silva, V. J. Buchard, et al. A. S. Darmenov, P. R. Colarco, V. Aquila, H. Bian, E. P. Nowottnick, X. Pan, H. Yu, and R. C. Govindaraju. 2016. The MERRA-2 Aerosol Assimilation Technical Report Series on Global Modeling and Data Assimilation 45

Nowottnick, E. P., P. R. Colarco, E. J. Welton, and A. M. Da Silva. 2015. Use of the CALIOP vertical feature mask for evaluating global aerosol models Atmospheric Measurement Techniques 8 3647-3669 [10.5194/amt-8-3647-2015]

Kouatchou, J., A. Da Silva, and A. Oloso. 2015. SIVO-PyD: A Python Distribution for Scientific Computing Visualization NASA Tech Brief GSC-16530-1

Kishcha, P., A. da Silva, B. Starobinets, et al. C. Long, O. Kalashnikova, and P. Alpert. 2015. Saharan dust as a causal factor of hemispheric asymmetry in aerosols and cloud cover over the tropical Atlantic Ocean International Journal of Remote Sensing 36 (13): 3423-3445 [10.1080/01431161.2015.1060646]

Buchard, V. J., A. M. Da Silva, P. R. Colarco, et al. A. S. Darmenov, C. A. Randles, R. C. Govindaraju, O. Torres, J. Campbell, and R. Spurr. 2015. Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis Atmos. Chem. Phys. 15 5743-5760 [10.5194/acp-15-5743-2015]

Bosilovich, M. G., J.-D. Chern, D. M. Mocko, F. R. Robertson, and A. M. da Silva. 2015. Evaluating observation influence on regional water budgets in reanalyses J. Climate 28 (9): 3631-3649 [10.1175/JCLI-D-14-00623.1]

Huang, M., K. W. Bowman, G. R. Carmichael, et al. M. Lee, T. Chai, S. N. Spak, D. K. Henze, A. S. Darmenov, and A. M. da Silva. 2015. Improved western U.S. background ozone estimates via constraining nonlocal and local source contributions using Aura TES and OMI observations J. Geophys. Res. Atmos. 120 (8): 3572-3592 [10.1002/2014jd022993]

Long, M. S., R. Yantosca, J. E. Nielsen, et al. C. A. Keller, A. da Silva, M. P. Sulprizio, S. Pawson, and D. J. Jacob. 2015. Development of a grid-independent GEOS-Chem chemical transport model (v9-02) as an atmospheric chemistry module for Earth system models Geosci. Model Dev. 8 (3): 595-602 [10.5194/gmd-8-595-2015]

Sessions, W. R., J. S. Reid, A. Benedetti, et al. P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama, T. Y. Tanaka, J. M. Baldasano, S. Basart, M. E. Brooks, T. F. Eck, M. Iredell, J. A. Hansen, O. C. Jorba, H.-M. H. Juang, P. Lynch, J.-J. Morcrette, S. Moorthi, J. Mulcahy, Y. Pradhan, M. Razinger, C. B. Sampson, J. Wang, and D. L. Westphal. 2015. Corrigendum to "Development towards a global operational aerosol consensus: basic climatological characteristics of the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME)" published in Atmos. Chem. Phys., 15, 335–362, 2015 Atmos. Chem. Phys. 15 (5): 2533-2534 [10.5194/acp-15-2533-2015]

Bingqi Yi, Ping Yang, A. Dessler, and A. M. da Silva. 2015. Response of Aerosol Direct Radiative Effect to the East Asian Summer Monsoon IEEE Geosci. Remote Sensing Lett. 12 (3): 597-600 [10.1109/lgrs.2014.2352630]

Barre, J., D. Edwards, H. Worden, A. M. Da Silva, and W. A. Lahoz. 2015. On the feasibility of monitoring Carbon Monoxide in the lower troposphere from a constellation of Northern Hemisphere geostationary satellites. (Part 1) Atmos. Environ 113 63-77 [10.1016/j.atmosenv.2015.04.069]

Saide, P., D. A. Peterson, A. da Silva, et al. B. Anderson, L. D. Ziemba, G. Diskin, G. Sachse, J. Hair, C. Butler, M. Fenn, J. L. Jimenez, P. Campuzano-Jost, A. E. Perring, J. P. Schwarz, M. Z Markovic, P. Russell, J. Redemann, Y. Shinozuka, D. G. Streets, F. Yan, J. Dibb, R. Yokelson, O. B. Toon, E. Hyer, and G. R. Carmichael. 2015. Revealing important nocturnal and day-to-day variations in fire smoke emissions through a multiplatform inversion Geophys. Res. Lett 42 3609-3618 [10.1002/2015GL063737]

Sessions, W., J. S. Reid, A. Benedetti, et al. P. Colarco, A. da Silva, S. Lu, T. Sekiyama, T. Y. Tanaka, J. M. Baldasano, S. Basart, M. Brooks, T. F. Eck, M. Iredell, J. A. Hansen, O. Jorba, H.-M. Juang, P. Lynch, J.-J. Morcrette, S. Moorthi, J. Mulcahy, Y. Pradhan, M. Razinger, C. B. Sampson, J. Wang, and D. L. Westphal. 2015. Development towards a global operational aerosol consensus: Basic climatological characteristics of the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME) Atmos. Chem. Phys 15 335-362 [10.5194/acp-15-335-2015]

Saide, P. E., S. N. Spak, R. B. Pierce, et al. J. A. Otkin, T. K. Schaack, A. K. Heidinger, A. M. da Silva, M. Kacenelenbogen, J. Redemann, and G. R. Carmichael. 2015. Central American biomass burning smoke can increase tornado severity in the U.S Geophys. Res. Lett 42 956-965 [10.1002/2014GL062826]

Zhang, F., J. Wang, C. M. Ichoku, et al. E. J. Hyer, Z. Yang, C. Ge, S. Su, X. Zhang, S. Kondragunta, J. W. Kaiser, C. Wiedinmyer, and A. M. Da Silva. 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 Letters 9 (7): 075002 (14 pp) [10.1088/1748-9326/9/7/075002]

Keller, C. A., M. S. Long, R. M. Yantosca, et al. A. M. Da Silva, S. Pawson, and D. J. Jacob. 2014. HEMCO v1.0: a versatile, ESMF-compliant component for calculating emissions in atmospheric models Geoscientific Model Development 7 (4): 1409-1417 [10.5194/gmd-7-1409-2014]

Kishcha, P., A. M. Da Silva, B. Starobinets, and P. Alpert. 2014. Air pollution over the Ganges basin and northwest Bay of Bengal in the early postmonsoon season based on NASA MERRAero data J. Geophys. Res. Atmos. 119 (3): 1555-1570 [10.1002/2013JD020328]

Buchard, V. J., A. M. Da Silva, P. R. Colarco, et al. N. A. Krotkov, R. R. Dickerson, J. W. Stehr, G. Mount, E. Spinei, H. L. Arkinson, and H. He. 2014. Evaluation of GEOS-5 sulfur dioxide simulations during the Frostburg, MD 2010 field campaign Atmos. Chem. Phys. 14 (4): 1929-1941 [10.5194/acp-14-1929-2014]

Yasunari, T., W. K. Lau, P. R. Colarco, et al. A. M. Da Silva, T. Aoki, K. Aoki, N. Murao, S. Yamagata, Y. Kodama, and S. P. Mahanama. 2014. The GOddard SnoW Impurity Module (GOSWIM) for the NASA GEOS-5 Earth System Model: Preliminary Comparisons with Observations in Sapporo, Japan SOLA 10 (0): 50-56 [10.2151/sola.2014-011]

Matsui, T., C. M. Ichoku, C. A. Randles, et al. T. L. Yuan, A. M. Da Silva, P. R. Colarco, D. Kim, R. C. Levy, A. M. Sayer, M. Chin, D. Giles, B. N. Holben, E. J. Welton, T. F. Eck, and L. A. Remer. 2014. Current and Future Perspectives of Aerosol Research at NASA Goddard Space Flight Center Bulletin of the American Meteorological Society early view [10.1175/ BAMS-D-13-00153.1]

Reale, O., W. K. Lau, A. M. Da Silva, and T. Matsui. 2014. Impact of assimilated and interactive aerosol on tropical cyclogenesis Geophys. Res. Lett 41 (9): 3282-3288 [10.1002/2014GL059918]

Gupta, P., M. Khan, A. M. Da Silva, and F. Patadia. 2013. MODIS aerosol optical depth observations over urban areas in Pakistan: Quantity and quality of the data for air quality monitoring Atmospheric Pollution Research 4 (1): 43-52 [10.5094/APR.2013.005]

Palmer, P., M. Parrington, J. Lee, S. Pawson, and A. da Silva. 2013. Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS) experiment: design, execution and science overview Atmos. Chem. Phys. 13 (13): 6239-6261 [10.5194/acp-13-6239-2013]

Guan, B., D. E. Waliser, J.-L. F. Li, and A. da Silva. 2013. Evaluating the impact of orbital sampling on satellite-climate model comparisons J. Geophys. Res. Atmos. 118 (2): 355-369 [10.1029/2012JD018590]

Bian, H., P. R. Colarco, M. Chin, et al. G. Chen, J. M. Rodriguez, Q. Liang, D. Blake, D.-C. A. Chu, A. M. Da Silva, A. S. Darmenov, G. Diskin, H. E. Fuelberg, G. Huey, Y. Kondo, J. E. Nielsen, X. Pan, and A. Wisthaler. 2013. Source attributions of pollution to the Western Arctic during the NASA ARCTAS field campaign Atmos. Chem. Phys. 13 (9): 4707-4721 [10.5194/acp-13-4707-2013]

Gorkavyi, N., D. Rault, P. Newman, A. M. Da Silva, and A. E. Dudorov. 2013. New stratospheric dust belt due to the Chelyabinsk bolide Geophys. Res. Lett 40 (17): 4728-4733 [10.1002/grl.50788]

Wind, G., A. M. Da Silva, P. M. Norris, and S. E. Platnick. 2013. Multi-sensor cloud retrieval simulator and remote sensing from model parameters – Part 1: Synthetic sensor radiance formulation Geosci. Model Dev. 6 (6): 2049-2062 [10.5194/gmd-6-2049-2013]

Randles, C. A., P. R. Colarco, and A. M. Da Silva. 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. Atmos. 118 (1): 149–169 [10.1029/2012JD018388]

Choi, S., Y. Wang, R. J. Salawitch, et al. T. Canty, J. Joiner, T. Zeng, T. P. Kurosu, K. Chance, A. Richter, L. G. Huey, J. Liao, J. A. Neuman, J. B. Nowak, J. E. Dibb, A. J. Weinheimer, G. Diskin, T. B. Ryerson, A. da Silva, J. Curry, D. Kinnison, S. Tilmes, and P. F. Levelt. 2012. Analysis of satellite-derived Arctic tropospheric BrO columns in conjunction with aircraft measurements during ARCTAS and ARCPAC Atmos. Chem. Phys. 12 (3): 1255-1285 [10.5194/acp-12-1255-2012]

Witte, J. C., A. R. Douglass, A. da Silva, et al. O. Torres, R. Levy, and B. N. Duncan. 2011. NASA A-Train and Terra observations of the 2010 Russian wildfires Atmos. Chem. Phys. 11 (17): 9287-9301 [10.5194/acp-11-9287-2011]

Van Donkelaar, A., R. V. Martin, R. C. Levy, et al. A. M. Da Silva, M. Krzyzanowski, N. E. Chubarova, E. Semutnikova, and A. J. Cohen. 2011. Satellite-based estimates of ground-level fine particulate matter during extreme events: A case study of the Moscow fires in 2010 Atmospheric Environment 45 (34): 6225-6232 [10.1016/j.atmosenv.2011.07.068]

Rienecker, M. M., M. J. Suarez, R. Gelaro, et al. R. Todling, J. Bacmeister, E. Liu, M. G. Bosilovich, S. D. Schubert, L. Takacs, G.-K. Kim, S. Bloom, J. Chen, D. Collins, A. Conaty, A. da Silva, W. Gu, J. Joiner, R. D. Koster, R. Lucchesi, A. Molod, T. Owens, S. Pawson, P. Pegion, C. R. Redder, R. H. Reichle, F. R. Robertson, A. G. Ruddick, M. Sienkiewicz, and J. Woollen. 2011. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications J. Climate 24 (14): 3624-3648 [10.1175/JCLI-D-11-00015.1]

Nowottnick, E., P. R. Colarco, A. M. Da Silva, D. L. Hlavka, and M. J. Mcgill. 2011. The fate of Saharan dust across the Atlantic and implications for a Central American dust barrier Atmos. Chem. Phys. 11 (16): 8415-8431 [10.5194/acp-11-8415-2011]

Reale, O., W. K. Lau, and A. M. Da Silva. 2011. Impact of Interactive Aerosol on the African Easterly Jet in the NASA GEOS-5 Global Forecasting System Weather and Forecasting 26 (4): 504-519 [10.1175/WAF-D-10-05025.1]

Salawitch, R. J., T. Canty, T. Kurosu, et al. K. Chance, Q. Liang, A. M. Da Silva, S. Pawson, J. E. Nielsen, J. M. Rodriguez, and P. K. Bhartia. 2010. A new interpretation of total column BrO during Arctic spring Geophysical Research Letters 37 (21): L21805 [10.1029/2010GL043798]

Wong, S., A. E. Dessler, N. M. Mahowald, P. R. Colarco, and A. da Silva. 2008. Long-term variability in Saharan dust transport and its link to North Atlantic sea surface temperature Geophysical Research Letters 35 (7): [10.1029/2007gl032297]

Zhou, S., V. Balaji, C. A. Cruz, et al. A. M. Da Silva, C. Hill, E. Kluzek, S. Smithline, and A. L. Trayanov. 2007. Cross-organization interoperability experiments of weather and climate models with the Earth System Modeling Framework Concurrency and Computation: Practice and Experience 19 (5): 583–592 [10.1002/cpe.1120]

Weaver, C. J., A. M. Da Silva, M. Chin, et al. P. Ginoux, O. Dubovik, D. Flittner, A. Zia, L. A. Remer, B. N. Holben, and W. Gregg. 2007. Direct insertion of MODIS radiances in a global aerosol transport model J Atmos Sci 64 (3): 808-826 [10.1175/JAS3838.1]

Joiner, J., E. Brin, R. Treadon, et al. J. Derber, P. Van Delst, A. M. da Silva, J. Le Marshall, P. Poli, D. Atlas, D. R. Bungato, and C. Cruz. 2007. Effects of data selection and error specification on the assimilation of AIRS data Quart J Roy Meteor Soc 133 (622): 181-196 [10.1002/qj.8]

Norris, P. M., and A. M. da Silva. 2007. Assimilation of Satellite Cloud Data into the GMAO Finite-Volume Data Assimilation System Using a Parameter Estimation Method. Part I: Motivation and Algorithm Description J. Atmos. Sci. 64 (11): 3880-3895 [10.1175/2006JAS2046.1]

Bosilovich, M. G., J. Radakovich, A. M. Da Silva, R. Todling, and F. Verter. 2007. Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System Journal of the Meteorological Society of Japan 85A

Tan, W. W., M. A. Geller, S. Pawson, and A. da Silva. 2004. A case study of excessive subtropical transport in the stratosphere of a data assimilation system J. Geophys. Res. 109 (D11): D11102 [10.1029/2003JD004057]

Yang, R., S. Cohn, A. da Silva, J. Joiner, and P. R. Houser. 2003. Tangent linear analysis of the Mosaic land surface model J. Geophys. Res. 108 (D2): 4054 [10.1029/2002JD002410]

Dee, D. P., and A. da Silva. 2003. The Choice of Variable for Atmospheric Moisture Analysis Mon. Wea. Rev. 131 (1): 155-171 [10.1175/1520-0493(2003)131<0155:TCOVFA>2.0.CO;2]

Coy, L., I. Stajner, A. M. da Silva, et al. J. Joiner, R. B. Rood, P. Pawson, and S. J. Lin. 2003. High-Frequency Planetary Waves in the Polar Middle Atmosphere as Seen in a Data Assimilation System J. Atmos. Sci. 60 (24): 2975-2992 [10.1175/1520-0469(2003)060<2975:HPWITP>2.0.CO;2]

Yang, R., S. E. Cohn, A. da Silva, J. Joiner, and P. Houser. 2003. Tangent linear analysis of the Mosaic land surface model J Geophys Res 108 (D2): 12-1 - 12-16

Dee, D. P., L. Rukhovets, R. Todling, A. M. da Silva, and J. W. Larson. 2001. An adaptive buddy check for observational quality control Quarterly Journal of the Royal Meteorological Society 127 (577): 2451-2471 [10.1002/qj.49712757714]

Hou, A. Y., S. Zhang, A. M. da Silva, et al. W. S. Olson, C. Kummerow, and J. Simpson. 2001. Improving global analysis and short-range forecast using rainfall and moisture observations derived from TRMM and SSM/I passive microwave instruments Bull Amer Meteor Soc 82 659-679

Hou, A. Y., D. Ledvina, A. M. Da Silva, et al. S. Zhang, J. Joiner, R. Atlas, G. J. Huffman, and C. Kummerow. 2000. Assimilation of SSM/I-Derived Surface Rainfall and Total Precipitable Water for Improving the GEOS Analysis for Climate Studies Mon. Wea. Rev. 128 (3): 509-537 [10.1175/1520-0493(2000)128<0509:AOSIDS>2.0.CO;2]

Joiner, J., and A. M. Da Silva. 1998. Efficient Methods to Assimilate Satellite Retrievals Based on Information Content Q.J.R. Meteorol. Soc. 125 (549): 1669-1694 [10.1002/qj.49712454915]

Cohn, S. E., A. Da Silva, J. Guo, M. Sienkiewicz, and D. Lamich. 1998. Assessing the Effects of Data Selection with the DAO Physical-Space Statistical Analysis System* Monthly Weather Review 126 (11): 2913--2926

Non-Refereed

Kim, J. G., S. R. Akella, A. M. Da Silva, R. Todling, and W. R. Mccarty. 2018. Preliminary evaluation of influence of aerosols on the simulation of brightness temperature in the NASA’s Goddard Earth Observing System Atmospheric Data Assimilation System NASA Technical Report Series on Global Modeling and Data Assimilation, NASA/TM-2018-104606 49 44pp

Errico, R. M., N. C. Prive, D. Carvalho, et al. M. E. Sienkiewicz, A. El Akkraoui, J. Guo, R. Todling, W. R. Mccarty, W. M. Putman, A. M. Da Silva, R. Gelaro, and I. Moradi. 2017. Description of the GMAO OSSE for Weather Analysis Software Package: Version 3 NASA Technical Report Series on Global Modeling and Data Assimilation, NASA/TM-2017-104606 48 156 pp.

Darmenov, A. S., and A. M. Da Silva. 2015. The Quick Fire Emissions Dataset (QFED): Documentation of versions 2.1, 2.2 and 2.4 NASA Technical Report Series on Global Modeling and Data Assimilation 38 (NASA/TM–2015–104606):

Davies, D. K., K. J. Murphy, K. Michael, et al. I. Becker-Reshef, C. O. Justice, R. A. Boller, S. A. Braun, J. E. Schmaltz, M. Wong, A. N. Pasch, T. S. Dye, A. M. Da Silva, H. M. Goodman, and P. J. Morin. 2015. The Use of NASA LANCE Imagery and Data for Near Real-Time Applications Time-Sensitive Remote Sensing 165-182 [10.1007/978-1-4939-2602-2_11]

Gelaro, R., W. M. Putman, S. Pawson, et al. C. S. Draper, A. M. Molod, P. M. Norris, L. E. Ott, N. C. Privé, O. Reale, D. Achuthavarier, M. G. Bosilovich, V. J. Buchard, W. C. Chao, L. Coy, R. I. Cullather, A. M. Da Silva, A. S. Darmenov, R. M. Errico, M. Fuentes, M.-J. Kim, R. D. Koster, W. R. Mccarty, J. Nattala, G. S. Partyka, S. D. Schubert, G. R. Vernieres, Y. V. Vikhliaev, and K. Wargan. 2015. Evaluation of the 7-km GEOS-5 Nature Run NASA Technical Report Series on Global Modeling and Data Assimilation 36 (NASA/TM-2014-104606):

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