EGU General Assembly 2021
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Aerosol emission estimation using SPEXone observational capabilities and Observing System Simulation Experiments (OSSEs) 

Athanasios Tsikerdekis1,2, Nick Schutgens2, Guangliang Fu1, and Otto Hasekamp1
Athanasios Tsikerdekis et al.
  • 1SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
  • 2Department of Earth Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands

A top-down approach for aerosol emission estimation from polarimetric retrievals of aerosol amount, size, and absorption is employed . The method uses a fixed-lag ensemble Kalman smoother (LETKF-Smoother) under the framework of Observing System Simulation Experiments (OSSEs), in order to evaluate the observational capabilities of a satellite with near perfect global coverage as well as of the future multi-angle polarimeter instrument, SPEXone. ECHAM-HAM is used for the nature runs (NATs), the control (CTL) and the data assimilation (DAS) experiments. The ensemble is composed by 32 simulations where the default aerosol emissions for all species are perturbed with factors taken from a Gaussian distribution. Synthetic observations, specifically Aerosol Optical Depth at 550nm (AOD550), Angstrom Exponent 550nm to 865nm (AE550-865) and Single Scattering Albedo at 550nm (SSA550) are assimilated in order to estimate the aerosol emission fluxes of desert dust (DU), sea salt (SS), organic carbon (OC), black carbon (BC) and sulphates (SO4), along with the emission fluxes of two SO4 precursor gases (SO2, DMS). The synthetic observations are sampled from the NATs according to two satellite observing systems, with different spatial coverage capabilities. The first, is an idealized sensor that retrieves observations over the whole globe in 2days even under cloudy conditions, hence is named PERFECT. The second, is the sensor SPEXone, a hyperspectral multi-angle polarimeter with a narrow swath (100km), that will be a part of the NASA PACE mission. The assimilated observations sampled using the PERFECT sensor, estimate the emission of all aerosol species with a global relative Mean Absolute Error (MAE) equal or lower than 5% (except SO4). Despite its limited coverage, the SPEXone sampling bares similar results, although MAE is a bit larger for Dust and Sea Salt. Further, experiments show that doubling the measurement error on the assimilated observations, increases additionally the global relative MAE by less than 10%. In addition, the role of biased meteorology on emission estimation was quantified by using two different datasets (ERA5 and ERAi) to nudge the U and V wind components of the model. The results reveal that when the wind of NAT and DAS are nudged to different datasets the global relative MAE of SS grows by 24%, while the estimated emissions of DU, OC, BC and SO2 are negatively affected to a smaller extent (~10%). The upcoming SPEXone sensor will provide observations related to aerosol amount size and absorption, with sufficient coverage and accuracy, in order to estimate aerosol emission accurately.

How to cite: Tsikerdekis, A., Schutgens, N., Fu, G., and Hasekamp, O.: Aerosol emission estimation using SPEXone observational capabilities and Observing System Simulation Experiments (OSSEs) , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8896,, 2021.


Display file

Comments on the display

to access the discussion