Development of retrieval algorithms for the EarthCARE lidar using the EarthCARE simulator

The Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) is a combined ESA/JAXA mission to be flown in 2013. EarthCARE will study the spatial distribution of clouds and aerosols and their effects on radiation by combining active (Doppler radar, HSRL lidar) and passive sensors (multispectral imager, broadband radiometer). The aims of the EarthCARE mission will be pursued exploiting various synergies from combining two or more of the instruments (lidar+radar, lidar+msi or lidar+radar+msi). In this work two algorithms for the EarthCARE lidar are described, one for retrieving the feature mask and one for the extinction and Backscatter retrieval. Both algorithms have been integrated with the EarthCARE simulator (ECSIM) for testing and validation of the retrievals with synthetic data. The use of ECSIM has greatly facilitated the development and testing these two algorithms by providing “realistic” instrument data data sets with a know “truth” to compare with. The feature mask identifies 'significant return' in the lidar signal. As the signal strength of aerosol or very optically thin ice clouds on the single shot grid can be comparable to the noise levels it was chosen to rely on image reconstruction techniques and not on signal to noise ratios and thresholds. This type of algorithm ensures the derivation of a feature mask on the single shot resolution enabling both the use of variable masks, e.g. use only those profiles which are sure to have no clouds to derive the mean aerosol signals, and calculation of feature fractions which can result in a better determination of higher order products like extinction, backscatter and depolarization. Next to the ECSIM scenes the algorithm has been tested with Calipso data. The Rayleigh signal from a High-Spectral Resolution Lidar (HSRL) can be used to estimate the extinction profile in a rather direct manner by estimating the derivative of the range-corrected logarithmic signal. However, the applicability of this method is limited due to the high SNR required. In contrast, extinction information can also be extracted from the Mie signal channel which, in general, may be viewed as less accurate (since factors such as the extinction-to-backscatter ratio must be assumed) but more precise (since the sensitivity to the SNR ratio of the input data is much lower). To optimally use both signals and SNR ratio constraints an optimal-estimation based variational approach has been developed for the retrieval of lidar extinction and backscatter from HSRL lidar data. In this presentation, the algorithms will be described with an emphasis on the role ECSIM has played in the development process.