Abstract
Abstract. 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.
Highlights
Atmospheric aerosol is a key factor that modifies the effects and intensity of climate change, due to its participation in numerous atmospheric processes that may alter the radiative budget of the planet (Boucher et al, 2013)
The results indicate that a positive bias of the model against Moderate Resolution Imaging Spectroradiometer (MODIS)-DT AOD550 is most probably driven by an overestimation of sea salt (SS) emission fluxes, since these two spatial patterns match (Fig. S4a and e)
We first evaluate the impact of data assimilation by evaluating the daily forecast, starting from the latest analysis, with POLarization and Directionality of the Earth’s Reflectances (POLDER) data not yet assimilated
Summary
Atmospheric aerosol is a key factor that modifies the effects and intensity of climate change, due to its participation in numerous atmospheric processes that may alter the radiative budget of the planet (Boucher et al, 2013). Retrieved aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer Dark Target algorithm (MODIS-DT) has been extensively assimilated (Benedetti et al, 2009; Dai et al, 2014; Escribano et al, 2017; Huneeus et al, 2012; Schutgens et al, 2012; Di Tomaso et al, 2017; Xu et al, 2013; Yumimoto and Takemura, 2011) or used for validation as independent observations (Dai et al, 2019; Schutgens et al, 2010a, b) in past studies. Retrieved AOD from the POLarization and Directionality of the Earth’s Reflectances (POLDER) Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm (Dubovik et al, 2011) was assimilated by Chen et al (2019)
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