Assimilating aerosol optical properties related to size and absorption from POLDER/PARASOL with an ensemble data assimilation system

Assimilating aerosol optical properties related to size and absorption from POLDER/PARASOL with an ensemble data assimilation system

A data assimilation system for aerosol, based on an ensemble Kalman filter, has been developed for the ECHAM – Hamburg Aerosol Model (ECHAM-HAM) global aerosol model and applied to POLarization and Directionality of the Earth's Reflectances (POLDER)-derived observations of optical properties. T...

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Bibliographic Details
Published in:Atmospheric chemistry and physics 2021-02, Vol.21 (4), p.2637-2674
Main Authors: Tsikerdekis, Athanasios, Schutgens, Nick A. J, Hasekamp, Otto P
Format: Article
Language:eng
Subjects:
Absorption
Aerosol absorption
Aerosol optical depth
Aerosol optical properties
Aerosol Robotic Network
Aerosols
Albedo
Algorithms
Assimilation
Atmosphere
Atmospheric aerosols
Climate change
Covariance matrix
Data
Data assimilation
Data collection
Datasets
Dust
Estimates
Experiments
Global aerosols
Kalman filters
Mixing ratio
MODIS
Optical analysis
Optical properties
Optical thickness
Polders
Remote sensing
Satellites
Simulation
Spectroradiometers
State vectors
Vectors
Wavelength
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Summary:A data assimilation system for aerosol, based on an ensemble Kalman filter, has been developed for the ECHAM – Hamburg Aerosol Model (ECHAM-HAM) global aerosol model and applied to POLarization and Directionality of the Earth's Reflectances (POLDER)-derived observations of optical properties. The advantages of this assimilation system is that the ECHAM-HAM aerosol modal scheme carries both aerosol particle numbers and mass which are both used in the data assimilation system as state vectors, while POLDER retrievals in addition to aerosol optical depth (AOD) and the Ångström exponent (AE) also provide information related to aerosol absorption like aerosol absorption optical depth (AAOD) and single scattering albedo (SSA). The developed scheme can simultaneously assimilate combinations of multiple variables (e.g., AOD, AE, SSA) to optimally estimate mass mixing ratio and number mixing ratio of different aerosol species. We investigate the added value of assimilating AE, AAOD and SSA, in addition to the commonly used AOD, by conducting multiple experiments where different combinations of retrieved properties are assimilated. Results are evaluated with (independent) POLDER, Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target, MODIS Deep Blue and Aerosol Robotic Network (AERONET) observations. The experiment where POLDER AOD, AE and SSA are assimilated shows systematic improvement in mean error, mean absolute error and correlation for AOD, AE, AAOD and SSA compared to the experiment where only AOD is assimilated. The same experiment reduces the global ME against AERONET from 0.072 to 0.001 for AOD, from 0.273 to 0.009 for AE and from −0.012 to 0.002 for AAOD. Additionally, sensitivity experiments reveal the benefits of assimilating AE over AOD at a second wavelength or SSA over AAOD, possibly due to a simpler observation covariance matrix in the present data assimilation framework. We conclude that the currently available AE and SSA do positively impact data assimilation.
ISSN:1680-7324
1680-7316
1680-7324