Birs- 23w5093: Mathematical Approaches of Atmospheric Constituents Data Assimilation and Inverse Modeling
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Title: NOAA efforts in chemical data assimilation and inverse modeling, an overview
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Title: CAMS air quality and GHG and methane monitoring and inversion
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Title: Mathematics of chemical data assimilation and inverse modeling
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Title: Continuous formulation of advective dynamics and variance loss
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Title: On the observability quest for chemistry data assimilation and emission inversion
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Title: The representativeness of observations and emissions for air quality analyses on regional scales
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Title: Constituent data assimilation plans of the GMAO at NASA
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Title: Challenges and opportunities in inverse modeling: A case with Carbon Monoxide sources
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Title: Characterizing model errors in inverse modelling of CH4 and CO2 fluxes using weak constraint 4D-Var
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Title: Assessing wildfire emissions of CO using 4D-Var inverse modeling
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Title: On variational Fokker-Planck filters and smoothers
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Title: Coupling of meteorology and tracers in data assimilation systems
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Title: Development of the ECCC’s national carbon flux inversion system
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Title: Applying analytical inversion and 4D-Var to estimate sources of methane and air pollutants
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Title: Using process control theory to estimate sea spray emissions in GEOS-Chem
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Title: Inverse modeling with HYSPLIT Lagrangian dispersion model
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Title: Utilizing machine learning to optimize the choice of error distribution in data assimilation
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Title: Online model error correction with neural networks – from theory to the ECMWF forecasting system
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Title: Towards CO2 plume detection and source inversion from satellites using deep neural networks
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Title: Overview of the role of Machine learning in atmospheric research
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