A weighted least squares approach to retrieve aerosol layer height over bright surfaces applied to GOME-2 measurements of the oxygen A band for forest fire cases over Europe
by S. Nanda (KNMI), J.P. Veefkind (KNMI), M. de Graaf (KNMI), M. Sneep (KNMI), P. Stammes (KNMI)J.F. de Haan (KNMI)A.F.J. Sanders (University of Bremen)A. Apituley (KNMI)O. Tuinder (KNMI)P.F. Levelt (KNMI)
This paper presents a weighted least squares approach to retrieve aerosol layer height from top-of-atmosphere reflectance measurements in the oxygen A band (758–770nm) over bright surfaces. A property of the measurement error covariance matrix is discussed, due to which photons travelling from the surface are given a higher preference over photons that scatter back from the aerosol layer. This is a potential source of biases in the estimation of aerosol properties over land, which can be mitigated by revisiting the design of the measurement error covariance matrix. The alternative proposed in this paper, which we call the dynamic scaling method, introduces a scene-dependent and wavelength-dependent modification in the measurement signal-to-noise ratio in order to influence this matrix. This method is generally applicable to other retrieval algorithms using weighted least squares. To test this method, synthetic experiments are done in addition to application to GOME-2A and GOME-2B measurements of the oxygen A band over the August 2010 Russian wildfires and the October 2017 Portugal wildfire plume over western Europe.
Example of modifying vector as a function of wavelength
Nanda, S., J.P. Veefkind, M. de Graaf, M. Sneep, P. Stammes, J.F. de Haan, A.F.J. Sanders, A. Apituley, O. Tuinder and P.F. Levelt, A weighted least squares approach to retrieve aerosol layer height over bright surfaces applied to GOME-2 measurements of the oxygen A band for forest fire cases over Europe