Aeolus L2A aerosol optical properties product: standard correct algorithm and Mie correct algorithm

Aeolus carries the Atmospheric LAser Doppler INstrument (ALADIN), the first high-spectral-resolution lidar (HSRL) in space. Although ALADIN is optimized to measure winds, its two measurement channels can also be used to derive optical properties of atmospheric particles, including a direct retrieval of the lidar ratio. This paper presents the standard correct algorithm and the Mie correct algorithm, the two main algorithms of the optical properties product called the Level-2A product, as they are implemented in version 3.12 of the processor, corresponding to the data labelled Baseline 12. The theoretical basis is the same as in Flamant et al. (2008). Here, we also show the in-orbit performance of these algorithms. We also explain the adaptation of the calibration method, which is needed to cope with unforeseen variations of the instrument radiometric performance due to the in-orbit strain of the primary mirror under varying thermal conditions. Then we discuss the limitations of the algorithms and future improvements. We demonstrate that the L2A product provides valuable information about airborne particles; in particular, we demonstrate the capacity to retrieve a useful lidar ratio from Aeolus observations. This is illustrated using Saharan dust aerosol observed in June 2020.

Liquid Phase Cloud Microphysical Property Estimates From CALIPSO Measurements

A neural-network algorithm that uses CALIPSO lidar measurements to infer droplet effective radius, extinction coefficient, liquid-water content, and droplet number concentration for water clouds is described and assessed. These results are verified against values inferred from High-Spectral-Resolution Lidar (HSRL) and Research Scanning Polarimeter (RSP) measurements made on an aircraft that flew under CALIPSO. The global cloud microphysical properties are derived from 14+ years of CALIPSO lidar measurements, and the droplet sizes are compared to corresponding values inferred from MODIS passive imagery. This new product will provide constraints to improve modeling of Earth’s water cycle and cloud-climate interactions.

Aeolus L2A Aerosol Optical Properties Product: Standard Correct Algorithm and Mie Correct Algorithm

Aeolus carries ALADIN, the first High Spectral Resolution Lidar (HSRL) in space. Although ALADIN was optimized to measure winds, its two measurement channels can also be used to derive optical properties of atmospheric particles, including a direct retrieval of the lidar ratio. This paper presents the two main algorithms of the optical properties product called Level 2A product, as they are implemented in version 3.12 of the processor, corresponding to the data labelled Baseline 12. The theoretical basis is the same as in Flamant et al. (2008). Here, we also show the in orbit performance of these algorithms. We also explain the adaptation of the calibration method, which is needed to cope with unforeseen variations of the instrument radiometric performance due to the in-orbit strain of the primary mirror under varying thermal conditions. Then we discuss the limitations of the algorithms and future improvements. We demonstrate that the L2A product provides valuable information about airborne particles, in particular we demonstrate the capacity to retrieve a useful lidar ratio from Aeolus observations. This is illustrated on a case of Saharan dust emission, observed in June 2020.

COLOR: CDOM-proxy retrieval from aeOLus ObseRvations

<p>The ESA Earth Explorer Wind Mission ADM-Aeolus (Atmospheric Dynamics Mission), successfully launched on 22 August 2018, has the aim to provide global observations of wind profiles, demonstrating the impact of wind profile data on operational weather forecasting and on climate research. Within the Aeolus+ Innovation program, ESA has launched an Invitation To Tender (ITT, ESA AO/1-9544/20/I/NS) to carry out studies aimed at exploring, developing and validating innovative products and applications and exploiting the novel nature of Aeolus data.</p><p>Lidar technique has been extensively employed in oceanography, mainly through shipborne and aircraft lidars [1],[2]. Recently, new applications using CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instrument on-board CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) demonstrated that satellite-borne lidar can give valuable information about ocean optical properties [3],[4].</p><p>Although Aeolus’s mission primary objectives and subsequent instrumental and sampling characteristics are not ideal for monitoring ocean sub-surface properties, the unprecedented type of measurements from this mission are expected to contain important and original information in terms of optical properties of the sensed ocean volume. Being the first HSRL (High Spectral Resolution Lidar) launched in space, ALADIN (Atmospheric LAser Doppler Instrument) of ADM-Aeolus gives an unprecedented new opportunity to investigate the information content of the 355 nm signal backscattered by the ocean sub-surface components.</p><p>Based on the above considerations, COLOR (CDOM-proxy retrieval from aeOLus ObseRvations), a selected Aeolus+ Innovation ITT project, aims to evaluate and document the feasibility of deriving an in-water AEOLUS prototype product from the analysis of the ocean sub-surface backscattered component of the 355 nm signal acquired by the ALADIN. The project focuses on the potential retrieval of the ocean optical properties at 355 nm: diffuse attenuation coefficient for downwelling irradiance, K<sub>d</sub> [m-1], and sub-surface hemispheric particulate backscatter coefficient, b<sub>bp</sub> [m-1]. In particular, being dominated by the absorption due to CDOM (Chromophoric Dissolved Organic Matter), K<sub>d</sub> coefficient at 355 nm, K<sub>d</sub>(355), can be used as a proxy to describe spatial and temporal variability of this variable, which contributes to regulating the Earth’s climate. An overview of the project and some preliminary results are presented.</p><p> </p><p>[1]  B. L. Collister, R. C. Zimmerman, C. I. Sukenik, V. J. Hill, e W. M. Balch, «Remote sensing of optical characteristics and particle distributions of the upper ocean using shipboard lidar», Remote Sens. Environ., vol. 215, pagg. 85–96, set. 2018, doi: 10.1016/j.rse.2018.05.032.</p><p>[2]  J. H. Churnside, J. W. Hair, C. A. Hostetler, e A. J. Scarino, «Ocean Backscatter Profiling Using High-Spectral-Resolution Lidar and a Perturbation Retrieval», Remote Sens., vol. 10, n. 12, Art. n. 12, dic. 2018, doi: 10.3390/rs10122003.</p><p>[3]  M. J. Behrenfeld et al., «Global satellite-observed daily vertical migrations of ocean animals», Nature, vol. 576, n. 7786, Art. n. 7786, dic. 2019, doi: 10.1038/s41586-019-1796-9.</p><p>[4]  D. Dionisi, V. E. Brando, G. Volpe, S. Colella, e R. Santoleri, «Seasonal distributions of ocean particulate optical properties from spaceborne lidar measurements in Mediterranean and Black sea», Remote Sens. Environ., vol. 247, pag. 111889, set. 2020, doi: 10.1016/j.rse.2020.111889.</p>