Aeolus aerosol and cloud product

2021 ◽  
Author(s):  
Thomas Flament ◽  
Alain Dabas ◽  
Dimitri Trapon ◽  
Adrien Lacour ◽  
Frithjof Ehlers ◽  
...  
Keyword(s):  
Optical Properties ◽  
Spectral Resolution ◽  
Aerosol Particles ◽  
High Spectral Resolution ◽  
Extinction Coefficients ◽  
Direct Estimation ◽  
Rayleigh Channel ◽  
Aerosol Classification ◽  
Lidar Ratio ◽  
European Satellite

<p>The European Satellite has the first space-borne high-spectral resolution UV lidar onboard called ALADIN. Two detection channels, a broadband (Rayleigh channel) and a narrowband (Mie channel), are implemented. Carefully calibrated, this combination offers the possibility to derive independent estimates of the backscatter and extinction coefficients of clouds andaerosols, leading to a direct estimation of the lidar ratio, useful for aerosol classification.</p><p>The presentation will show how the official processor of the mission works for the retrieval of optical properties of cloud and aerosol particles, with a focus on the currently available products (called L2A). The potential of the L2A processor will be illustrated by results obtained on data acquired since Aeolus launch and by comparisons to ground based lidars in the frame of Cal/Val activities.</p><p>The L2A product will become publicly available during Spring 2021. Thus, this is also an opportunity to introduce a few practical aspects about its usage.</p>

Aeolus aerosol and cloud product

2020 ◽  
Author(s):  
Alain Dabas ◽  
Thomas Flament ◽  
Dimitri Trapon ◽  
Dorit Huber
Keyword(s):  
Optical Properties ◽  
Spectral Resolution ◽  
Aerosol Particles ◽  
Real Data ◽  
High Spectral Resolution ◽  
Extinction Coefficients ◽  
Rayleigh Channel

<p>Aeolus is a high-spectral resolution UV lidar. It implements two detection channels, a broadband (Rayleigh channel) and a narrowband (Mie channel). Carefully calibrated, the combination offers the possibility to derive independent estimates of the backscatter and extinction coefficients of the clouds and the aerosols, thus opening the possibility to acquire an information on their nature with the extinction-to-backscatter ratio. The presentation will show how the level-2A processor of the mission works for the retrieval of optical properties of cloud and aerosol particles, what products can be obtained with what limitations. The potential of L2A processor will be illustrated by results obtained on real data acquired since AEOLUS launch.</p>

scholarly journals Optimization of Aeolus' aerosol optical properties by maximum-likelihood estimation

2022 ◽  
Vol 15 (1) ◽  
pp. 185-203
Author(s):  
Frithjof Ehlers ◽  
Thomas Flament ◽  
Alain Dabas ◽  
Dimitri Trapon ◽  
Adrien Lacour ◽  
...  
Keyword(s):  
Optical Properties ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Positive Impact ◽  
European Space Agency ◽  
Likelihood Estimation ◽  
High Spectral Resolution ◽  
Extinction Coefficients ◽  
Lidar Ratio ◽  
Ground Based Lidar

Abstract. The European Space Agency (ESA) Earth Explorer Mission Aeolus was launched in August 2018, carrying the first Doppler wind lidar in space. Its primary payload, the Atmospheric LAser Doppler INstrument (ALADIN), is an ultraviolet (UV) high-spectral-resolution lidar (HSRL) measuring atmospheric backscatter from air molecules and particles in two separate channels. The primary mission product is globally distributed line-of-sight wind profile observations in the troposphere and lower stratosphere. Atmospheric optical properties are provided as a spin-off product. Being an HSRL, Aeolus is able to independently measure the particle extinction coefficients, co-polarized particle backscatter coefficients and the co-polarized lidar ratio (the cross-polarized return signal is not measured). This way, the retrieval is independent of a priori lidar ratio information. The optical properties are retrieved using the standard correct algorithm (SCA), which is an algebraic inversion scheme and therefore sensitive to measurement noise. In this work, we reformulate the SCA into a physically constrained maximum-likelihood estimation (MLE) problem and demonstrate a predominantly positive impact and considerable noise suppression capabilities. These improvements originate from the use of all available information by the MLE in conjunction with the expected physical bounds concerning positivity and the expected range of the lidar ratio. To consolidate and to illustrate the improvements, the new MLE algorithm is evaluated against the SCA on end-to-end simulations of two homogeneous scenes and for real Aeolus data collocated with measurements by a ground-based lidar and the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The largest improvements were seen in the retrieval precision of the extinction coefficients and lidar ratio ranging up to 1 order of magnitude or more in some cases due to effective noise dampening. In real data cases, the increased precision of MLE with respect to the SCA is demonstrated by increased horizontal homogeneity and better agreement with the ground truth, though proper uncertainty estimation of MLE results is challenged by the constraints, and the accuracy of MLE and SCA retrievals can depend on calibration errors, which have not been considered.

scholarly journals Retrieval of Aerosol Optical Properties Based on High Spectral Resolution Lidar

2020 ◽  
Vol 237 ◽  
pp. 08018
Author(s):  
Da Xiao ◽  
Tianfen Zhong ◽  
Xue Shen ◽  
Nanchao Wang ◽  
Yuhang Rong ◽  
...  
Keyword(s):  
Optical Properties ◽  
Spectral Resolution ◽  
High Spectral Resolution ◽  
Urban Aerosol ◽  
Aerosol Optical Properties ◽  
Climate Research ◽  
Atmospheric Remote Sensing ◽  
Retrieval Algorithms ◽  
Lidar Ratio ◽  
High Spectral Resolution Lidar

The detection of clouds and aerosols is important for climate research. Lidar has been widely used in atmospheric remote sensing research because of its high spatial and temporal resolution and ability to detect profiles. High spectral resolution lidar (HSRL) accurately calculates the optical properties of aerosols and clouds without relying on any assumptions. Based on the 532nm iodine HSRL system, the lidar ratio of the urban aerosol in Hangzhou is 40-50sr, and the average lidar ratio of the cirrus is 24.79sr, demonstrating that the HSRL system and retrieval algorithms accurately obtain the optical properties of clouds and aerosols.

scholarly journals Optimization of Aeolus Optical Properties Products by Maximum-Likelihood Estimation

2021 ◽  
Author(s):  
Frithjof Ehlers ◽  
Thomas Flament ◽  
Alain Dabas ◽  
Dimitri Trapon ◽  
Adrien Lacour ◽  
...  
Keyword(s):  
Optical Properties ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Positive Impact ◽  
European Space Agency ◽  
Likelihood Estimation ◽  
High Spectral Resolution ◽  
Extinction Coefficients ◽  
Lidar Ratio ◽  
Ground Based Lidar

Abstract. The European Space Agency (ESA) Earth Explorer Mission, Aeolus, was launched in August 2018 and embarks the first Doppler Wind Lidar in space. Its primary payload, the Aeolus LAser Doppler INstrument (Aladin) is a Ultra Violet (UV) High Spectral Resolution Lidar (HSRL) measuring atmospheric backscatter from air molecules and particles in two separate channels. The primary mission product is globally distributed line-of-sight wind profile observations in the troposphere and lower stratosphere. Atmospheric optical properties are provided as a spin-off product. Being and HSRL, Aeolus is able to independently measure the particle extinction coefficients, co-polarized particle backscatter coefficients and the co-polarized lidar ratio. This way, the retrieval is independent of a-priori information. The optical properties are retrieved using the Standard Correct Algorithm (SCA), which is an algebraic inversion scheme to a (partly) ill-posed problem and therefore sensitive to measurement noise. In this work, we rephrase the SCA into a physically constrained Maximum Likelihood Estimation (MLE) problem and demonstrate predominantly positive impact and considerable noise suppression capabilities. These improvements originate from the use of all available information within the SCA in conjunction with the expected physical bounds concerning the expected range of the lidar ratio. The new MLE algorithm is equally evaluated against the SCA on end-to-end simulations of two homogeneous scenes and for real Aelous data collocated with measurements by a ground-based lidar and the CALIPSO satellite to consolidate and to illustrate the improvements. The largest improvements were seen in the retrieval of the extinction coefficients and lidar ratio ranging up to one order of magnitude or more in some cases due to an effective noise dampening.

scholarly journals Aerosol classification from airborne HSRL and comparisons with the CALIPSO vertical feature mask

2013 ◽  
Vol 6 (1) ◽  
pp. 1815-1858 ◽  
Author(s):  
S. P. Burton ◽  
R. A. Ferrare ◽  
M. A. Vaughan ◽  
A. H. Omar ◽  
R. R. Rogers ◽  
...  
Keyword(s):  
High Spectral Resolution ◽  
Dependent Observations ◽  
Aerosol Retrieval ◽  
Direct Measurements ◽  
Aerosol Classification ◽  
Lidar Ratio ◽  
Langley Research Center ◽  
High Spectral Resolution Lidar ◽  
Aerosol Types ◽  
Aerosol Type

Abstract. Aerosol classification products from the NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL-1) on the NASA B200 aircraft are compared with coincident V3.01 aerosol classification products from the CALIOP instrument on the CALIPSO satellite. For CALIOP, aerosol classification is a key input to the aerosol retrieval, and must be inferred using aerosol loading-dependent observations and location information. In contrast, HSRL-1 makes direct measurements of aerosol intensive properties, including the lidar ratio, that provide information on aerosol type. In this study, comparisons are made for 109 underflights of the CALIOP orbit track. We find that 62% of the CALIOP marine layers and 54% of the polluted continental layers agree with HSRL-1 classification results. In addition, 80% of the CALIOP desert dust layers are classified as either dust or dusty mix by HSRL-1. However, agreement is less for CALIOP smoke (13%) and polluted dust (35%) layers. Specific case studies are examined, giving insight into the performance of the CALIOP aerosol type algorithm. In particular, we find that the CALIOP polluted dust type is overused due to an attenuation-related depolarization bias. Furthermore, the polluted dust type frequently includes mixtures of dust plus marine aerosol. Finally, we find that CALIOP's identification of internal boundaries between different aerosol types in contact with each other frequently do not reflect the actual transitions between aerosol types accurately. Based on these findings, we give recommendations which may help to improve the CALIOP aerosol type algorithms.

Aerosol classification method based on high spectral resolution lidar

2017 ◽  
Vol 46 (4) ◽  
pp. 411001
Author(s):  
刘秉义 Liu Bingyi ◽  
庄全风 Zhuang Quanfeng ◽  
秦胜光 Qin Shengguang ◽  
吴松华 Wu Songhua ◽  
刘金涛 Liu Jintao
Keyword(s):  
Spectral Resolution ◽  
Classification Method ◽  
High Spectral Resolution ◽  
Aerosol Classification ◽  
High Spectral Resolution Lidar

scholarly journals Aerosol classification using airborne High Spectral Resolution Lidar measurements – methodology and examples

2012 ◽  
Vol 5 (1) ◽  
pp. 73-98 ◽  
Author(s):  
S. P. Burton ◽  
R. A. Ferrare ◽  
C. A. Hostetler ◽  
J. W. Hair ◽  
R. R. Rogers ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
High Spectral Resolution ◽  
Color Ratio ◽  
Lidar Measurements ◽  
Aerosol Classification ◽  
Langley Research Center ◽  
High Spectral Resolution Lidar ◽  
Aerosol Types ◽  
532 Nm ◽  
Aerosol Type

Abstract. The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) on the NASA B200 aircraft has acquired extensive datasets of aerosol extinction (532 nm), aerosol optical depth (AOD) (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles during 18 field missions that have been conducted over North America since 2006. The lidar measurements of aerosol intensive parameters (lidar ratio, depolarization, backscatter color ratio, and spectral depolarization ratio) are shown to vary with location and aerosol type. A methodology based on observations of known aerosol types is used to qualitatively classify the extensive set of HSRL aerosol measurements into eight separate types. Several examples are presented showing how the aerosol intensive parameters vary with aerosol type and how these aerosols are classified according to this new methodology. The HSRL-based classification reveals vertical variability of aerosol types during the NASA ARCTAS field experiment conducted over Alaska and northwest Canada during 2008. In two examples derived from flights conducted during ARCTAS, the HSRL classification of biomass burning smoke is shown to be consistent with aerosol types derived from coincident airborne in situ measurements of particle size and composition. The HSRL retrievals of AOD and inferences of aerosol types are used to apportion AOD to aerosol type; results of this analysis are shown for several experiments.

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