Abstract

Abstract. We demonstrate improvements in CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations) dust extinction retrievals over northern Africa and Europe when corrections are applied regarding the Saharan dust lidar ratio assumption, the separation of the dust portion in detected dust mixtures, and the averaging scheme introduced in the Level 3 CALIPSO product. First, a universal, spatially constant lidar ratio of 58 sr instead of 40 sr is applied to individual Level 2 dust-related backscatter products. The resulting aerosol optical depths show an improvement compared with synchronous and collocated AERONET (Aerosol Robotic Network) measurements. An absolute bias of the order of −0.03 has been found, improving on the statistically significant biases of the order of −0.10 reported in the literature for the original CALIPSO product. When compared with the MODIS (Moderate-Resolution Imaging Spectroradiometer) collocated aerosol optical depth (AOD) product, the CALIPSO negative bias is even less for the lidar ratio of 58 sr. After introducing the new lidar ratio for the domain studied, we examine potential improvements to the climatological CALIPSO Level 3 extinction product: (1) by introducing a new methodology for the calculation of pure dust extinction from dust mixtures and (2) by applying an averaging scheme that includes zero extinction values for the nondust aerosol types detected. The scheme is applied at a horizontal spatial resolution of 1° × 1° for ease of comparison with the instantaneous and collocated dust extinction profiles simulated by the BSC-DREAM8b dust model. Comparisons show that the extinction profiles retrieved with the proposed methodology reproduce the well-known model biases per subregion examined. The very good agreement of the proposed CALIPSO extinction product with respect to AERONET, MODIS and the BSC-DREAM8b dust model makes this dataset an ideal candidate for the provision of an accurate and robust multiyear dust climatology over northern Africa and Europe.

Highlights

  • Since the launch of the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on board the Cloud– Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; Winker et al, 2009) satellite in June 2006, global aerosol and cloud profiles are provided to the scientific community through analysis of CALIOP backscatter observations at the operating wavelengths 532 and 1064 nm

  • Considering homogeneous CALIPSO profiles where only dust is detected in the atmospheric column, we found 1203 profile coincidences with a distance less or equal to 80 km from the reference Aerosol Robotic Network (AERONET) stations located in the domain of our interest

  • A significant absolute bias of the order of −0.1 is revealed by our dataset

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Summary

Introduction

Since the launch of the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on board the Cloud– Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; Winker et al, 2009) satellite in June 2006, global aerosol and cloud profiles are provided to the scientific community through analysis of CALIOP backscatter observations at the operating wavelengths 532 and 1064 nm. The domain of our application is northern Africa and Europe, and we wish to note that this methodology cannot be applied to mineral dusts different from those advected from the Sahara This point has been re-emphasized by the recent study of Schuster et al (2012) which implied that the use of a spatially constant LR for all CALIPSO dust retrievals is inappropriate and would produce positive bias for CALIPSO AODs over the Middle East, where the dust LR is lower than that for the Sahara (of the order of 43 sr). Satellite and ground-based observations together with their corresponding products and the dust model utilized for Saharan dust simulations used in this study, are described

The CALIPSO product
The AERONET product
The MODIS product
The BSC-DREAM8b dust model
Comparison methodology
Results and discussion
CALIPSO comparison with BSC-DREAM8b simulated dust fields
Conclusions
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