基本信息
浏览量:373
职业迁徙
个人简介
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
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
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
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
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
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.
Professional Societies
American Meteorological Society, 1985 - Present
Former President of the Milwaukee Chapter of the American Meteorological Society (1993).
American Geophysical Union, 1995 - Present
American Association for the Advancement of Science, 2000 - Present
Teaching Experience
Graduate/undergraduate courses taught at the University of Wisconsin-Milwaukee:
Survey of Meteorology (undergraduate)
Earth, Air, Wind and Fire (undergraduate)
Weather: Principles and Forecasting (undergraduate)
Dynamic Meteorology I (undergraduate/graduate)
Dynamic Meteorology II (undergraduate/graduate)
Advanced Synoptic Meteorology I (undergraduate/graduate)
Advanced Synoptic Meteorology II (undergraduate/graduate)
Physical Oceanography (undergraduate/graduate)
Numerical Weather Prediction (graduate)
Topics on ENSO (graduate)
Introduction to McIdas (undergraduate)
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
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
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
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
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
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.
Professional Societies
American Meteorological Society, 1985 - Present
Former President of the Milwaukee Chapter of the American Meteorological Society (1993).
American Geophysical Union, 1995 - Present
American Association for the Advancement of Science, 2000 - Present
Teaching Experience
Graduate/undergraduate courses taught at the University of Wisconsin-Milwaukee:
Survey of Meteorology (undergraduate)
Earth, Air, Wind and Fire (undergraduate)
Weather: Principles and Forecasting (undergraduate)
Dynamic Meteorology I (undergraduate/graduate)
Dynamic Meteorology II (undergraduate/graduate)
Advanced Synoptic Meteorology I (undergraduate/graduate)
Advanced Synoptic Meteorology II (undergraduate/graduate)
Physical Oceanography (undergraduate/graduate)
Numerical Weather Prediction (graduate)
Topics on ENSO (graduate)
Introduction to McIdas (undergraduate)
研究兴趣
论文共 368 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETYno. 1 (2024): E176-E192
A. B. Collow, A. B. Collow, P. R. Colarco,A. M. da Silva, V. Buchard, V. Buchard, H. Bian, H. Bian, M. Chin, S. Das, S. Das, R. Govindaraju,
Geoscientific Model Development (2024): 1443-1468
Gregory L. Schuster,Elisabeth Andrews, Eduard Chemyakin,Mian Chin, Jacek Chowdhary,Cheng Dang,Yevgeny Derimian,Arlindo da Silva,Fabrice Ducos,William Reed Espinosa, Philippe Lesueur,Richard Moore,
crossref(2024)
Geoscientific Model Development (2024): 795-813
LANCET PLANETARY HEALTHno. 12 (2023): e963-e975
H. Lv,A. da Silva, A. I. Figueroa,C. Guillemard, I. Fernández Aguirre,L. Camosi,L. Aballe,M. Valvidares,S. O. Valenzuela,J. Schubert,M. Schmidbauer,J. Herfort,
arxiv(2023)
引用1浏览0WOS引用
1
0
Euclid Collaboration, T. Castro,A. Fumagalli,R. E. Angulo, S. Bocquet,S. Borgani,C. Carbone, J. Dakin, K. Dolag, C. Giocoli, P. Monaco, A. Ragagnin,
arxiv(2023)
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn