scholarly journals Halo ratio from ground based all-sky imaging

2018 ◽  
Author(s):  
Paolo Dandini ◽  
Zbigniew Ulanowski ◽  
David Campbell ◽  
Richard Kaye
Keyword(s):  
Brightness Temperature ◽  
Quantitative Measure ◽  
Detection Algorithm ◽  
Fluctuation Analysis ◽  
Image Brightness ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Scattering Phase ◽  
Scattering Phase Function ◽  
Image Transformations

Abstract. The halo ratio (HR) is a quantitative measure characterizing the occurrence of the 22° halo peak associated with cirrus. We propose to obtain it from the scattering phase function (SPF) derived from all-sky imaging. Ground based fisheye cameras are used to retrieve the SPF by implementing the necessary image transformations and corrections. These consist of geometric correction of lens distortion by utilizing positions of known stars in a camera image, transforming the images from the zenith-centred to the light-source-centred system of coordinates, correcting for the air mass and for vignetting, the latter using independent measurements from a sun photometer. The SPF is then determined by averaging the image brightness over the azimuth angle and the HR by calculating the ratio of the SPF at two scattering angles in the vicinity of the 22° halo peak. In variance from previous suggestions we select these angles to be 20° and 23°, on the basis of our observations. HR time series have been obtained under various cloud conditions, including halo cirrus, non-halo cirrus and scattered cumulus. While the HR measured in this way is found to be sensitive to the halo status of cirrus, showing values typically > 1 under halo producing clouds, similar HR values, mostly artefacts associated with bright cloud edges, can also be occasionally observed under scattered cumulus. Given that the HR is an ice cloud characteristic, a separate cirrus detection algorithm is necessary to screen out non-ice clouds before deriving reliable HR statistics. Here we propose utilizing sky brightness temperature from infrared radiometry: both its absolute value and the magnitude of fluctuations obtained through detrended fluctuation analysis. The brightness temperature data permits the detection of cirrus in most but not all instances.

scholarly journals Halo ratio from ground-based all-sky imaging

2019 ◽  
Vol 12 (2) ◽  
pp. 1295-1309 ◽  
Author(s):  
Paolo Dandini ◽  
Zbigniew Ulanowski ◽  
David Campbell ◽  
Richard Kaye
Keyword(s):  
Brightness Temperature ◽  
Quantitative Measure ◽  
Detection Algorithm ◽  
Fluctuation Analysis ◽  
Image Brightness ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Scattering Phase ◽  
Scattering Phase Function ◽  
Image Transformations

Abstract. The halo ratio (HR) is a quantitative measure characterizing the occurrence of the 22∘ halo peak associated with cirrus. We propose to obtain it from an approximation to the scattering phase function (SPF) derived from all-sky imaging. Ground-based fisheye cameras are used to retrieve the SPF by implementing the necessary image transformations and corrections. These consist of geometric camera characterization by utilizing positions of known stars in a camera image, transforming the images from the zenith-centred to the light-source-centred system of coordinates and correcting for the air mass and for vignetting, the latter using independent measurements from a sun photometer. The SPF is then determined by averaging the image brightness over the azimuth angle and the HR by calculating the ratio of the SPF at two scattering angles in the vicinity of the 22∘ halo peak. In variance from previous suggestions we select these angles to be 20 and 23∘, on the basis of our observations. HR time series have been obtained under various cloud conditions, including halo cirrus, non-halo cirrus and scattered cumuli. While the HR measured in this way is found to be sensitive to the halo status of cirrus, showing values typically >1 under halo-producing clouds, similar HR values, mostly artefacts associated with bright cloud edges, can also be occasionally observed under scattered cumuli. Given that the HR is an ice cloud characteristic, a separate cirrus detection algorithm is necessary to screen out non-ice clouds before deriving reliable HR statistics. Here we propose utilizing sky brightness temperature from infrared radiometry: both its absolute value and the magnitude of fluctuations obtained through detrended fluctuation analysis. The brightness temperature data permit the detection of cirrus in most but not all instances.

A Comparison of Aphelion Cloud Belt Phase Functions Before and After the Mars Year 34 Global Dust Storm

2021 ◽  
Author(s):  
Alex Innanen ◽  
Brittney Cooper ◽  
Charissa Campbell ◽  
Scott Guzewich ◽  
Jacob Kloos ◽  
...  
Keyword(s):  
Dust Storm ◽  
Phase Function ◽  
Dust Storms ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Water Ice ◽  
Ice Cloud ◽  
Sky Survey ◽  
Scattering Phase ◽  
Scattering Phase Function

<p>1. INTRODUCTION</p><p>The Mars Science Laboratory (MSL) is located in Gale Crater (4.5°S, 137.4°E), and has been performing cloud observations for the entirety of its mission, since its landing in 2012 [eg. 1,2,3]. One such observation is the Phase Function Sky Survey (PFSS), developed by Cooper et al [3] and instituted in Mars Year (MY) 34 to determine the scattering phase function of Martian water-ice clouds. The clouds of interest form during the Aphelion Cloud Belt (ACB) season (L<sub>s</sub>=50°-150°), a period of time during which there is an increase in the formation of water-ice clouds around the Martian equator [4]. The PFSS observation was also performed during the MY 35 ACB season and the current MY 36 ACB season.</p><p>Following the MY 34 ACB season, Mars experienced a global dust storm which lasted from L<sub>s</sub>~188° to L<sub>s</sub>~250° of that Mars year [5]. Global dust storms are planet-encircling storms which occur every few Mars years and can significantly impact the atmosphere leading to increased dust aerosol sizes [6], an increase in middle atmosphere water vapour [7], and the formation of unseasonal water-ice clouds [8]. While the decrease in visibility during the global dust storm itself made cloud observation difficult, comparing the scattering phase function prior to and following the global dust storm can help to understand the long-term impacts of global dust storms on water-ice clouds.</p><p>2. METHODS</p><p>The PFSS consists of 9 cloud movies of three frames each, taken using MSL’s navigation cameras, at a variety of pointings in order to observe a large range of scattering angles. The goal of the PFSS is to characterise the scattering properties of water-ice clouds and to determine ice crystal geometry.  In each movie, clouds are identified using mean frame subtraction, and the phase function is computed using the formula derived by Cooper et al [3]. An average phase function can then be computed for the entirety of the ACB season.</p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.eda718c85da062913791261/sdaolpUECMynit/1202CSPE&app=m&a=0&c=67584351a5c2fde95856e0760f04bbf3&ct=x&pn=gnp.elif&d=1" alt="Figure 1 – Temporal Distribution of Phase Function Sky Survey Observations for Mars Years 34 and 35" width="800" height="681"></p><p>Figure 1 shows the temporal distributions of PFSS observations taken during MYs 34 and 35. We aim to capture both morning and afternoon observations in order to study any diurnal variability in water-ice clouds.</p><p>3. RESULTS AND DISCUSSION</p><p>There were a total of 26 PFSS observations taken in MY 35 between L<sub>s</sub>~50°-160°, evenly distributed between AM and PM observations. Typically, times further from local noon (i.e. earlier in the morning or later in the afternoon) show stronger cloud features, and run less risk of being obscured by the presence of the sun. In all movies in which clouds are detected, a phase function can be calculated, and an average phase function determined for the whole ACB season.  </p><p>Future work will look at the water-ice cloud scattering properties for the MY 36 ACB season, allowing us to get more information about the interannual variability of the ACB and to further constrain the ice crystal habit. The PFSS observations will not only assist in our understanding of the long-term atmospheric impacts of global dust storms but also add to a more complete image of time-varying water-ice cloud properties.</p>

Effect of Cavities on the Optical Properties of Bullet Rosettes: Implications for Active and Passive Remote Sensing of Ice Cloud Properties

2008 ◽  
Vol 47 (9) ◽  
pp. 2311-2330 ◽  
Author(s):  
Ping Yang ◽  
Zhibo Zhang ◽  
George W. Kattawar ◽  
Stephen G. Warren ◽  
Bryan A. Baum ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Phase Function ◽  
Hollow Structure ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Effective Particle Size ◽  
Effective Particle ◽  
Scattering Phase ◽  
Scattering Phase Function

Abstract Bullet rosette particles are common in ice clouds, and the bullets may often be hollow. Here the single-scattering properties of randomly oriented hollow bullet rosette ice particles are investigated. A bullet, which is an individual branch of a rosette, is defined as a hexagonal column attached to a hexagonal pyramidal tip. For this study, a hollow structure is included at the end of the columnar part of each bullet branch and the shape of the hollow structure is defined as a hexagonal pyramid. A hollow bullet rosette may have between 2 and 12 branches. An improved geometric optics method is used to solve for the scattering of light in the particle. The primary optical effect of incorporating a hollow end in each of the bullets is to decrease the magnitude of backscattering. In terms of the angular distribution of scattered energy, the hollow bullets increase the scattering phase function values within the forward scattering angle region from 1° to 20° but decrease the phase function values at side- and backscattering angles of 60°–180°. As a result, the presence of hollow bullets tends to increase the asymmetry factor. In addition to the scattering phase function, the other elements of the phase matrix are also discussed. The backscattering depolarization ratios for hollow and solid bullet rosettes are found to be very different. This may have an implication for active remote sensing of ice clouds, such as from polarimetric lidar measurements. In a comparison of solid and hollow bullet rosettes, the effect of the differences on the retrieval of both the ice cloud effective particle size and optical thickness is also discussed. It is found that the presence of hollow bullet rosettes acts to decrease the inferred effective particle size and to increase the optical thickness in comparison with the use of solid bullet rosettes.

scholarly journals Combination of AIRS Dual CO2 Absorption Bands to Develop an Ice Clouds Detection Algorithm in Different Atmospheric Layers

2019 ◽  
Vol 12 (1) ◽  
pp. 6 ◽  
Author(s):  
Liwen Wang ◽  
Youfei Zheng ◽  
Chao Liu ◽  
Zeyi Niu ◽  
Jingxin Xu ◽  
...  
Keyword(s):  
Linear Relationship ◽  
Weighting Function ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Orthogonal Polarization ◽  
Co2 Absorption ◽  
Cloud Detection ◽  
Absorption Bands ◽  
Ice Clouds ◽  
Ice Cloud

The use of infrared (IR) sensors to detect clouds in different layers of the atmosphere is a big challenge, especially for ice clouds. This study aims to improve ice cloud detection using Lin’s algorithm and apply it to Atmospheric Infrared Sounder (AIRS). To achieve these objectives, the scattering and emission characteristics of clouds as perceived by AIRS longwave infrared (LWIR, ~15 μm) and shortwave infrared (SWIR, ~4.3 μm) CO2 absorption bands are applied for ice cloud detection. Hence, the weighting function peak (WFP), cut-off pressure, and correlation coefficients between the brightness temperatures (BTs) of LWIR and SWIR channels are used to pair the LWIR and SWIR channels. After that, the linear relationship between the clear-sky BTs of the paired LWIR and SWIR channels is established by the cloud scattering and emission Index (CESI). However, the linear relationship fails in the presence of ice clouds. Comparing these results with collocated Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations show that the probability of detection of ice clouds for Pair-8 (WFP~330hPa), Pair-19 (WFP~555hPa), and Pair-24 (WFP~866hPa) are 0.63, 0.71, and 0.73 in the daytime and 0.46, 0.62, and 0.7 in the nighttime at a false alarm rate of 0.1 when ice clouds top pressure above 330 hPa, 555 hPa, and 866 hPa, respectively. Furthermore, the thresholds of the three pairs are 2.4 K, 3 K, and 8.7 K in the daytime and 1.7 K, 1.7 K, and 4.4 K in the nighttime at the highest Heike Skill Score (HSS). The error of HSS values based on thresholds of ice clouds is between 0.01 and 0.02 which is comparable with the ice cloud detection results in both day and night conditions. It is shown that Pair-8 (WFP~330hPa) can detect opaque and thick ice clouds above its WFP altitude over the tropical areas but it is unable to observe ice clouds over the mid-latitude while Pair-19 and Pair-24 can identify ice clouds above their WFP altitude.

scholarly journals Passive Remote Sensing of Ice Cloud Properties at Terahertz Wavelengths Based on Genetic Algorithm

2021 ◽  
Vol 13 (4) ◽  
pp. 735
Author(s):  
Lei Liu ◽  
Chensi Weng ◽  
Shulei Li ◽  
Letu Husi ◽  
Shuai Hu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Genetic Algorithm ◽  
Brightness Temperature ◽  
Absolute Error ◽  
Ice Clouds ◽  
Water Path ◽  
Ice Cloud ◽  
Ice Water Path ◽  
The Absolute ◽  
Ice Water

Ice clouds play a critical role in the balance of the earth–atmosphere radiation system, but there are some limitations in the existing remote sensing methods for ice clouds. Terahertz wave is expected to be the best waveband for retrieving ice clouds, with terahertz wavelengths in the order of the size of typical ice cloud particles. An inversion method for the remote sensing of ice clouds at terahertz wavelengths based on genetic algorithm is proposed in this paper. First, suitable channel sets in the terahertz band, which are mainly a combination of absorption lines and window regions, are determined. Then, to improve the efficiency of the generation of the retrieval database, based on the brightness temperature simulated by the atmospheric radiative transfer simulator (ARTS) for different cloud parameters, a fast forward operator is constructed using three-dimensional interpolation to simulate the brightness temperature difference between clear sky and a cloudy scene. Finally, an inversion model to retrieve the ice cloud base height, the effective particle diameter and the ice water path is established based on the genetic algorithm, and an analysis of the inversion errors is performed. The results show that the forward operator, constructed by the nearest interpolation, can accurately calculate the brightness temperature difference at a high speed. The proposed inversion method at terahertz wavelengths based on the genetic algorithm can achieve the expected scientific requirement. The absolute error of the cloud height is around 0.2 km, and the absolute error of the low ice water path (below 20 g/m2) is small, while the relative error of the high ice water path is generally maintained at around 10%, and the absolute error of the effective particle diameter is mostly around 4 μm.

Sign in / Sign up

Export Citation Format

Share Document