ATLID, ESA atmospheric backscatter LIDAR for the ESA EarthCARE mission

Carmo, J. Pereira do; Villèle, Géraud de; Hélière, Arnaud; Wallace, Kotska; Lefebvre, Alain; Chassat, François

doi:10.1007/s12567-019-00284-6

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…where σ m and σ p are the molecular and particulate scattering coefficients, respectively, P m and P p are the molecular and particulate phase functions at 180 • , respectively, and γ is a factor that takes into account the multiple-scattering effects (Platt, 1973). In the same way, ATB(r) m and ATB(r) p , by voluntarily omitting r, assuming that σ m and σ p are vertically constant, and introducing the thickness r to lighten the writing, can be expressed as ATB m = P m σ m e −2(σ m +γ σ p) r ATB p = P p σ p e −2(σ m +γ σ p) r .…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, the Mie receiver is a Fizeau spectrometer combined with a chargecoupled detector that measures the spectrum of the return around the emitted laser wavelength using 16 different frequency bins (Reitebuch et al, 2018;Stoffelen et al, 2005). The ATmospheric LIDar (ATLID) signals of the EarthCARE mission will be optically filtered in such a way that the atmospheric Mie and Rayleigh scattering contributions are separated and independently measured (Pereira do Carmo et al, 2019). The radar echoes of the Cloud Profiling Radar (CPR) of the EarthCARE mission will be input to autocovariance analysis by means of the pulse-pair processing technique for the estimation of the Doppler properties (Kollias et al, 2014(Kollias et al, , 2018Zrnić, 1977).…”

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confidence: 99%

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McRALI: a Monte Carlo high-spectral-resolution lidar and Doppler radar simulator for three-dimensional cloudy atmosphere remote sensing

et al. 2021

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Abstract. The aim of this paper is to present the Monte Carlo code McRALI that provides simulations under multiple-scattering regimes of polarized high-spectral-resolution (HSR) lidar and Doppler radar observations for a three-dimensional (3D) cloudy atmosphere. The effects of nonuniform beam filling (NUBF) on HSR lidar and Doppler radar signals related to the EarthCARE mission are investigated with the help of an academic 3D box cloud characterized by a single isolated jump in cloud optical depth, assuming vertically constant wind velocity. Regarding Doppler radar signals, it is confirmed that NUBF induces a severe bias in velocity estimates. The correlation of the NUBF bias of Doppler velocity with the horizontal gradient of reflectivity shows a correlation coefficient value around 0.15 m s−1 (dBZ km-1)-1, close to that given in the scientific literature. Regarding HSR lidar signals, we confirm that multiple-scattering processes are not negligible. We show that NUBF effects on molecular, particulate, and total attenuated backscatter are mainly due to unresolved variability of cloud inside the receiver field of view and, to a lesser extent, to the horizontal photon transport. This finding gives some insight into the reliability of lidar signal modeling using independent column approximation (ICA).

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

McRALI: a Monte Carlo high-spectral-resolution lidar and Doppler radar simulator for three-dimensional cloudy atmosphere remote sensing

et al. 2021

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“…With the completion of the full instrument assembly in 2019 [8], ATLID has been subjected to an ambient performance test campaign [9,10], followed by a successful environmental qualification test campaign, including performance calibration and characterisation in thermal vacuum conditions. ATLID has been successfully operated as a self-standing instrument and all performance aspects, including transmitter and receiver characteristics, have been found to be in line with targeted expectations and compliant with all major science, in-flight, end of life, performance requirements.…”

Section: Discussionmentioning

confidence: 99%

“…ATLID [9] is a high spectral Resolution LIDAR, operating in the ultra-violet spectral domain (355 nm), which takes benefit of the distinct interactions of light with molecules and aerosols that leads to different spectra scattering effects. Whereas the Brownian motion of molecules induces a wide broadening of the incident light spectrum, the scattering with an aerosol does not affect the spectral shape of the incident light.…”

Section: Atlid Measurement Principlementioning

confidence: 99%

ATmospheric LIDar (ATLID): European Space Agency Instrument Ready to Measure Aerosols and Thin Clouds in Atmosphere

Carmo¹,

Villèle²,

Wallace³

et al. 2020

Preprint

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ATLID (ATmospheric LIDar) is the atmospheric backscatter LIDAR (Light Detection and Ranging) on board of the EarthCARE (Earth Cloud, Aerosol and Radiation Explorer) mission, the sixth Earth Explorer Mission of the ESA (European Space Agency) Living Planet Programme [1-5]. ATLID’s purpose is to provide vertical profiles of optically thin cloud and aerosol layers, as well as the altitude of cloud boundaries [6-10]. In order to achieve this objective ATLID emits short duration laser pulses in the UV, at a repetition rate of 51 Hz, while pointing in a near nadir direction along track of the satellite trajectory. The atmospheric backscatter signal is then collected by its 620 mm aperture telescope, filtered through the optics of the instrument focal plane assembly, in order to separate and measure the atmospheric Mie and Rayleigh scattering signals. With the completion of the full instrument assembly in 2019, ATLID has been subjected to an ambient performance test campaign, followed by a successful environmental qualification test campaign, including performance calibration and characterization in thermal vacuum conditions. In this paper the design and operational principle of ATLID is recalled and the major performance test results are presented, addressing the main key receiver and emitter characteristics. Finally, the estimated instrument, in-orbit, flight predictions are presented; these indicate compliance of the ALTID instrument performance against its specification and that it will meet its mission science objectives for the EarthCARE mission, to be launched in 2023.

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ALiDAn: Spatiotemporal and Multiwavelength Atmospheric Lidar Data Augmentation

Vainiger

Shubi

Schechner

et al. 2022

IEEE Trans. Geosci. Remote Sensing

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Methods based on statistical learning have become prevalent in various signal processing disciplines and have recently gained traction in atmospheric lidar studies. Nonetheless, such methods often require large quantities of annotated or resolved data. Such data is rare and requires effort, especially when exploring evolving phenomena. Existing simulators and databases primarily focus on atmospheric vertical profiles. We propose the Atmospheric Lidar Data Augmentation (ALiDAn) framework to fill this gap. ALiDAn serves as an end-to-end generation and augmentation framework of spatiotemporal and multiwavelength resolved lidar simulated data. ALiDAn employs a hybrid approach of physical models, data statistics, and sampling processes. Additionally, it takes into account geographical and seasonal characteristics of aerosols, meteorological conditions, along with short-and long-term phenomena that affect lidar measurements. This approach can provide diversified data and robust benchmarks to assist in developing and validating new lidar processing algorithms. We demonstrate simulations compatible with a pulsed time-of-flight lidar. Our approach leverages a broader use of existing databases and can inspire similar data augmentation to other types of lidars and active sensors.

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ATLID, ESA atmospheric backscatter LIDAR for the ESA EarthCARE mission

Cited by 6 publications

References 5 publications

McRALI: a Monte Carlo high-spectral-resolution lidar and Doppler radar simulator for three-dimensional cloudy atmosphere remote sensing

McRALI: a Monte Carlo high-spectral-resolution lidar and Doppler radar simulator for three-dimensional cloudy atmosphere remote sensing

ATmospheric LIDar (ATLID): European Space Agency Instrument Ready to Measure Aerosols and Thin Clouds in Atmosphere

ALiDAn: Spatiotemporal and Multiwavelength Atmospheric Lidar Data Augmentation

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