Improved cloud-phase determination of low-level liquid and mixed-phase clouds by enhanced polarimetric lidar

Abstract. The unambiguous retrieval of cloud phase from polarimetric lidar observations is dependent on the assumption that only cloud scattering processes affect polarization measurements. A systematic bias of the traditional lidar depolarization ratio can occur due to a lidar system's inability to accurately measure the entire backscattered signal dynamic range, and these biases are not always identifiable in traditional polarimetric lidar systems. This results in a misidentification of liquid water in clouds as ice, which has broad implications on evaluating surface energy budgets. The Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland employs multiple planes of linear polarization, and photon counting and analog detection schemes, to self evaluate, correct, and optimize signal combinations to improve cloud classification. Using novel measurements of diattenuation that are sensitive to both horizontally oriented ice crystals and counting system nonlinear effects, unambiguous measurements are possible by over constraining polarization measurements. This overdetermined capability for cloud-phase determination allows for system errors to be identified and quantified in terms of their impact on cloud properties. It is shown that lidar system dynamic range effects can cause errors in cloud-phase fractional occurrence estimates on the order of 30 % causing errors in attribution of cloud radiative effects on the order of 10–30 %. This paper presents a method to identify and remove lidar system effects from atmospheric polarization measurements and uses co-located sensors at Summit to evaluate this method. Enhanced measurements are achieved in this work with non-orthogonal polarization retrievals as well as analog and photon counting detection facilitating a more complete attribution of radiative effects linked to cloud properties.

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Improved Cloud Phase Determination of Low Level Liquid and Mixed Phase Clouds by Enhanced Polarimetric Lidar

10.5194/amt-2017-327 ◽

2017 ◽

Author(s):

Robert A. Stillwell ◽

Ryan R. Neely III ◽

Jeffrey P. Thayer ◽

Matthew D. Shupe ◽

David D. Turner

Keyword(s):

Dynamic Range ◽

Photon Counting ◽

Energy Budgets ◽

Systematic Bias ◽

Lidar System ◽

Phase Determination ◽

Polarization Measurements ◽

Cloud Properties ◽

Signal Dynamic Range ◽

Mixed Phase Clouds

Abstract. The unambiguous retrieval of cloud phase from polarimetric lidar observations is dependent on the assumption that only cloud scattering processes affect polarization measurements. A systematic bias of the traditional lidar depolarization ratio can occur due to a lidar system's inability to accurately measure the entire backscattered signal dynamic range, and these biases are not always identifiable in traditional polarimetric lidar systems. This results in a misidentification of liquid water in clouds as ice, which has broad implications on evaluating surface energy budgets. The Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland employs multiple planes of linear polarization, and photon counting and analog detection schemes, to self evaluate, correct, and optimize signal combinations to improve cloud classification. Using novel measurements of diattenuation that are sensitive to both horizontally oriented ice crystals and counting system non-linear effects, unambiguous measurements are possible by over constraining polarization measurements. This overdetermined capability for cloud phase determination allows for system errors to be identified and quantified in terms of their impact on cloud properties. It is shown that lidar system dynamic range effects can cause errors in cloud phase fractional occurrence estimates on the order of 30% causing errors in attribution of cloud radiative effects on the order of 10%-30%. This paper presents a method to identify and remove lidar system effects from atmospheric polarization measurements and uses co-located sensors at Summit to validate this method.

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Low-Level, Liquid-Only and Mixed-Phase Cloud Identification by Polarimetric Lidar

10.5194/amt-2016-303 ◽

2016 ◽

Author(s):

Robert A. Stillwell ◽

Ryan R. Neely III ◽

Jeffrey P. Thayer ◽

Matthew D. Shupe ◽

Michael O'Neill

Keyword(s):

Surface Energy ◽

Dynamic Range ◽

Photon Counting ◽

Mixed Phase ◽

Orthogonal Polarization ◽

Polar Regions ◽

Systematic Bias ◽

Polarization Component ◽

Low Level ◽

Mixed Phase Clouds

Abstract. The measurement of low-level, liquid-only and mixed-phase clouds in the polar regions is a necessary building block to understand the regional surface energy and mass budgets over ice sheets. The unambiguous retrieval of cloud phase from polarimetric lidar observations is dependent on the assumption that only cloud scattering processes alter the transmitted polarization. However, due to clouds varying in range, optical depth, and scatterer size and shape, most atmospheric lidar systems must observe high dynamic ranges in scattered signal strengths. Depending on the polarization component measured, these signals can far exceed the linear range of a detection system. Thus, due to the high optical thickness and predominately low-lying nature of liquid-only and mixed-phase clouds in the polar regions, relative to ice only clouds, a systematic overestimate of the traditional depolarization ratio, which uses the co-polarized and cross-polarized signals, can occur due to the large dynamic range signals. For both liquid-only and mixed-phase clouds, this results in a misidentification of liquid water in clouds as ice, which has broad implications on evaluating surface energy budgets. The Clouds Aerosol Polarization and Backscatter Lidar (CAPABL) at Summit, Greenland employs multiple planes of linear polarization, and photon counting and analog detection schemes, to self evaluate, correct, and optimize signal combinations to improve cloud classification. For example, an examination of observations of liquid-only and mixed-phase clouds at Summit shows as much as a 2 kilometer offset in median cloud height of those identified as liquid due to a systematic bias in photon counting signals. At a constant altitude, more than 94 % of the liquid pixels identified with analog signals can be misidentified as ice with photon counting signals. This results in a possible error of fractional occurrence of cloud liquid of approximately 30 %. It is shown that by observing polarization planes that are non-orthogonal, the dynamic range of observed signals is reduced, the coverage of the expected signal dynamic range is increased, and more linear response can be captured. Using non-orthogonal polarization observations is shown to enhance measurement sensitivity increasing the effective sampling range for CAPABL by as much as 18 % or approximately 1.5 km.

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Multi-sensor measurements of mixed-phase clouds above Greenland

EPJ Web of Conferences ◽

10.1051/epjconf/201817608006 ◽

2018 ◽

Vol 176 ◽

pp. 08006

Author(s):

Robert A. Stillwell ◽

Matthew D. Shupe ◽

Jeffrey P. Thayer ◽

Ryan R. Neely ◽

David D. Turner

Keyword(s):

Dynamic Range ◽

Photon Counting ◽

Mixed Phase ◽

The Arctic ◽

Orthogonal Polarization ◽

Large Signal ◽

Phase Classification ◽

Signal Dynamic Range ◽

Cloud Parameter ◽

Mixed Phase Clouds

Liquid-only and mixed-phase clouds in the Arctic strongly affect the regional surface energy and ice mass budgets, yet much remains unknown about the nature of these clouds due to the lack of intensive measurements. Lidar measurements of these clouds are challenged by very large signal dynamic range, which makes even seemingly simple tasks, such as thermodynamic phase classification, difficult. This work focuses on a set of measurements made by the Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland and its retrieval algorithms, which use both analog and photon counting as well as orthogonal and non-orthogonal polarization retrievals to extend dynamic range and improve overall measurement quality and quantity. Presented here is an algorithm for cloud parameter retrievals that leverages enhanced dynamic range retrievals to classify mixed-phase clouds. This best guess retrieval is compared to co-located instruments for validation.

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Detectivity optimization to detect of ultraweak light fluxes with an EM-CCD as binary photon counter array

Scientific Reports ◽

10.1038/s41598-021-82611-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Ibtissame Khaoua ◽

Guillaume Graciani ◽

Andrey Kim ◽

François Amblard

Keyword(s):

Dynamic Range ◽

Signal To Noise Ratio ◽

Photon Counting ◽

Detection Methods ◽

Strong Nonlinearity ◽

Wide Range ◽

Depth Analysis ◽

Spatially Extended ◽

Extended Sources ◽

Photon Counting Mode

AbstractFor a wide range of purposes, one faces the challenge to detect light from extremely faint and spatially extended sources. In such cases, detector noises dominate over the photon noise of the source, and quantum detectors in photon counting mode are generally the best option. Here, we combine a statistical model with an in-depth analysis of detector noises and calibration experiments, and we show that visible light can be detected with an electron-multiplying charge-coupled devices (EM-CCD) with a signal-to-noise ratio (SNR) of 3 for fluxes less than $$30\,{\text{photon}}\,{\text{s}}^{ - 1} \,{\text{cm}}^{ - 2}$$ 30 photon s - 1 cm - 2 . For green photons, this corresponds to 12 aW $${\text{cm}}^{ - 2}$$ cm - 2 ≈ $$9{ } \times 10^{ - 11}$$ 9 × 10 - 11 lux, i.e. 15 orders of magnitude less than typical daylight. The strong nonlinearity of the SNR with the sampling time leads to a dynamic range of detection of 4 orders of magnitude. To detect possibly varying light fluxes, we operate in conditions of maximal detectivity $${\mathcal{D}}$$ D rather than maximal SNR. Given the quantum efficiency $$QE\left( \lambda \right)$$ Q E λ of the detector, we find $${ \mathcal{D}} = 0.015\,{\text{photon}}^{ - 1} \,{\text{s}}^{1/2} \,{\text{cm}}$$ D = 0.015 photon - 1 s 1 / 2 cm , and a non-negligible sensitivity to blackbody radiation for T > 50 °C. This work should help design highly sensitive luminescence detection methods and develop experiments to explore dynamic phenomena involving ultra-weak luminescence in biology, chemistry, and material sciences.

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Small All-Range Lidar for Asteroid and Comet Core Missions

Sensors ◽

10.3390/s21093081 ◽

2021 ◽

Vol 21 (9) ◽

pp. 3081

Author(s):

Xiaoli Sun ◽

Daniel R. Cremons ◽

Erwan Mazarico ◽

Guangning Yang ◽

James B. Abshire ◽

...

Keyword(s):

Fiber Lasers ◽

Dynamic Range ◽

Photon Counting ◽

Avalanche Photodiode ◽

Integration Time ◽

Sample Collection ◽

Long Distance ◽

Linear Mode ◽

Internal Gain ◽

Pseudo Noise

We report the development of a new type of space lidar specifically designed for missions to small planetary bodies for both topographic mapping and support of sample collection or landing. The instrument is designed to have a wide dynamic range with several operation modes for different mission phases. The laser transmitter consists of a fiber laser that is intensity modulated with a return-to-zero pseudo-noise (RZPN) code. The receiver detects the coded pulse-train by correlating the detected signal with the RZPN kernel. Unlike regular pseudo noise (PN) lidars, the RZPN kernel is set to zero outside laser firing windows, which removes most of the background noise over the receiver integration time. This technique enables the use of low peak-power but high pulse-rate lasers, such as fiber lasers, for long-distance ranging without aliasing. The laser power and the internal gain of the detector can both be adjusted to give a wide measurement dynamic range. The laser modulation code pattern can also be reconfigured in orbit to optimize measurements to different measurement environments. The receiver uses a multi-pixel linear mode photon-counting HgCdTe avalanche photodiode (APD) array with near quantum limited sensitivity at near to mid infrared wavelengths where many fiber lasers and diode lasers operate. The instrument is modular and versatile and can be built mostly with components developed by the optical communication industry.

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Measurement of synchrotron-radiation-excited Kossel patterns

Journal of Synchrotron Radiation ◽

10.1107/s1600577515019037 ◽

2016 ◽

Vol 23 (1) ◽

pp. 214-218 ◽

Cited By ~ 5

Author(s):

G. Bortel ◽

G. Faigel ◽

M. Tegze ◽

A. Chumakov

Keyword(s):

High Resolution ◽

Dynamic Range ◽

Structural Information ◽

Photon Counting ◽

Spot Size ◽

Low Noise ◽

X Rays ◽

Technical Problems ◽

Pixel Detectors ◽

Exciting Beam

Kossel line patterns contain information on the crystalline structure, such as the magnitude and the phase of Bragg reflections. For technical reasons, most of these patterns are obtained using electron beam excitation, which leads to surface sensitivity that limits the spatial extent of the structural information. To obtain the atomic structure in bulk volumes, X-rays should be used as the excitation radiation. However, there are technical problems, such as the need for high resolution, low noise, large dynamic range, photon counting, two-dimensional pixel detectors and the small spot size of the exciting beam, which have prevented the widespread use of Kossel pattern analysis. Here, an experimental setup is described, which can be used for the measurement of Kossel patterns in a reasonable time and with high resolution to recover structural information.

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Detector commissioning and development for PETRA-III

Diamond Light Source Proceedings ◽

10.1017/s2044820110000043 ◽

2010 ◽

Vol 1 (SRMS-7) ◽

Cited By ~ 1

Author(s):

David Pennicard ◽

Heinz Graafsma ◽

Michael Lohmann

Keyword(s):

High Speed ◽

Materials Science ◽

Dynamic Range ◽

Photon Counting ◽

High Energy ◽

X Rays ◽

Silicon Detectors ◽

Time Resolved ◽

Wide Range ◽

Synchrotron Light

The new synchrotron light source PETRA-III produced its first beam last year. The extremely high brilliance of PETRA-III and the large energy range of many of its beamlines make it useful for a wide range of experiments, particularly in materials science. The detectors at PETRA-III will need to meet several requirements, such as operation across a wide dynamic range, high-speed readout and good quantum efficiency even at high photon energies. PETRA-III beamlines with lower photon energies will typically be equipped with photon-counting silicon detectors for two-dimensional detection and silicon drift detectors for spectroscopy and higher-energy beamlines will use scintillators coupled to cameras or photomultiplier tubes. Longer-term developments include ‘high-Z’ semiconductors for detecting high-energy X-rays, photon-counting readout chips with smaller pixels and higher frame rates and pixellated avalanche photodiodes for time-resolved experiments.

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Improvements to the Geostationary Visible Imager Ray-Matching Calibration Algorithm for CERES Edition 4

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-16-0113.1 ◽

2016 ◽

Vol 33 (12) ◽

pp. 2679-2698 ◽

Cited By ~ 26

Author(s):

David R. Doelling ◽

Conor O. Haney ◽

Benjamin R. Scarino ◽

Arun Gopalan ◽

Rajendra Bhatt

Keyword(s):

Dynamic Range ◽

Spectral Band ◽

Radiant Energy ◽

Convective Cloud ◽

Energy System ◽

Processing Scheme ◽

Matching Algorithm ◽

Cloud Properties ◽

Calibration Algorithm ◽

The Difference

AbstractThe Clouds and the Earth’s Radiant Energy System (CERES) project relies on geostationary imager–derived TOA broadband fluxes and cloud properties to account for the regional diurnal fluctuations between the Terra and Aqua CERES and MODIS measurements. The CERES project employs a ray-matching calibration algorithm in order to transfer the Aqua MODIS calibration to the geostationary (GEO) imagers, thereby allowing the derivation of consistent fluxes and cloud retrievals across the 16 GEO imagers utilized in the CERES record. The CERES Edition 4 processing scheme grants the opportunity to recalibrate the GEO record using an improved GEO/MODIS all-sky ocean ray-matching algorithm. Using a graduated angle matching method, which is most restrictive for anisotropic clear-sky ocean radiances and least restrictive for isotropic bright cloud radiances, reduces the bidirectional bias while preserving the dynamic range. Furthermore, SCIAMACHY hyperspectral radiances are used to account for both the solar incoming and Earth-reflected spectra in order to correct spectral band differences. As a result, the difference between the linear regression offset and the maintained GEO space count was reduced, and the calibration slopes computed from the linear fit and the regression through the space count agreed to within 0.4%. A deep convective cloud (DCC) ray-matching algorithm is also presented. The all-sky ocean and DCC ray-matching timeline gains are within 0.7% of one another. Because DCC are isotropic and the brightest, Earth targets with near-uniform visible spectra, the temporal standard error of GEO imager gains, are reduced by up to 60% from that of all-sky ocean targets.

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An assessment of cloud top thermodynamic phase products obtained from A-Train passive and active sensors

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-6-8371-2013 ◽

2013 ◽

Vol 6 (5) ◽

pp. 8371-8411 ◽

Cited By ~ 5

Author(s):

S. Zeng ◽

J. Riedi ◽

F. Parol ◽

C. Cornet ◽

F. Thieuleux

Keyword(s):

General Circulation ◽

Supercooled Liquid ◽

General Circulation Models ◽

Global Scale ◽

Orthogonal Polarization ◽

Liquid Droplets ◽

High Confidence ◽

Cloud Properties ◽

Fractional Cloud ◽

Thermodynamic Phase

Abstract. The A-Train observations provide an unprecedented opportunity for the production of high quality dataset describing cloud properties. We illustrate in this study the use of one year of coincident POLDER (Polarization and Directionality of the Earth Reflectance), MODIS (MODerate Resolution Imaging Spectroradiometer) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations to establish a reference dataset for the description of cloud top thermodynamic phase at global scale. We present the results of an extensive comparison between POLDER and MODIS cloud top phase products and discuss those in view of cloud vertical structure and optical properties derived simultaneously from collocated CALIOP active measurements. These results allow to identify and quantify potential biases present in the 3 considered dataset. Among those, we discuss the impacts of observation geometry, thin cirrus in multilayered and single layered cloud systems, supercooled liquid droplets, aerosols, fractional cloud cover and snow/ice or bright surfaces on global statistics of cloud phase derived from POLDER and MODIS passive measurements. Based on these analysis we define criteria for the selection of high confidence cloud phase retrievals which in turn can serve for the establishment of a reference cloud phase product. This high confidence joint product derived from POLDER/PARASOL and MODIS/Aqua can be used in the future as a benchmark for the evaluation of other cloud climatologies, for the assessment of cloud phase representation in models and the development of better cloud phase parametrization in the general circulation models (GCMs).

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High Dynamic Range Imaging with TDC-Based CMOS SPAD Arrays

Instruments ◽

10.3390/instruments3030038 ◽

2019 ◽

Vol 3 (3) ◽

pp. 38 ◽

Cited By ~ 1

Author(s):

Majid Zarghami ◽

Leonardo Gasparini ◽

Matteo Perenzoni ◽

Lucio Pancheri

Keyword(s):

Dynamic Range ◽

Single Photon ◽

Photon Counting ◽

Complementary Metal Oxide Semiconductor ◽

High Dynamic Range ◽

Oxide Semiconductor ◽

Photon Flux ◽

Integration Time ◽

Rate Dependent ◽

High Dynamic

This paper investigates the use of image sensors based on complementary metal–oxide–semiconductor (CMOS) single-photon avalanche diodes (SPADs) in high dynamic range (HDR) imaging by combining photon counts and timestamps. The proposed method is validated experimentally with an SPAD detector based on a per-pixel time-to-digital converter (TDC) architecture. The detector, featuring 32 × 32 pixels with 44.64-µm pitch, 19.48% fill factor, and time-resolving capability of ~295-ps, was fabricated in a 150-nm CMOS standard technology. At high photon flux densities, the pixel output is saturated when operating in photon-counting mode, thus limiting the DR of this imager. This limitation can be overcome by exploiting the distribution of photon arrival times in each pixel, which shows an exponential behavior with a decay rate dependent on the photon flux level. By fitting the histogram curve with the exponential decay function, the extracted time constant is used to estimate the photon count. This approach achieves 138.7-dB dynamic range within 30-ms of integration time, and can be further extended by using a timestamping mechanism with a higher resolution.

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