scholarly journals An Improved Beta Method for Ice Cloud Property Retrievals: Theory

2020 ◽  
Vol 125 (14) ◽  
Author(s):  
Masanori Saito ◽  
Ping Yang ◽  
Andrew K. Heidinger ◽  
Yue Li
Keyword(s):  
Cloud Property ◽  
Ice Cloud

scholarly journals Footprint-scale cloud type mixtures and their impacts on Atmospheric Infrared Sounder cloud property retrievals

2019 ◽  
Vol 12 (8) ◽  
pp. 4361-4377 ◽  
Author(s):  
Alexandre Guillaume ◽  
Brian H. Kahn ◽  
Eric J. Fetzer ◽  
Qing Yue ◽  
Gerald J. Manipon ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Deep Convection ◽  
Cloud Microphysics ◽  
Specific Humidity ◽  
Phase Detection ◽  
Cloud Type ◽  
Atmospheric Infrared Sounder ◽  
Cloud Particle ◽  
Cloud Property ◽  
Ice Cloud

Abstract. A method is described to classify cloud mixtures of cloud top types, termed cloud scenes, using cloud type classification derived from the CloudSat radar (2B-CLDCLASS). The scale dependence of the cloud scenes is quantified. For spatial scales at 45 km (15 km), only 18 (10) out of 256 possible cloud scenes account for 90 % of all observations and contain one, two, or three cloud types. The number of possible cloud scenes is shown to depend on spatial scale with a maximum number of 210 out of 256 possible scenes at a scale of 105 km and fewer cloud scenes at smaller and larger scales. The cloud scenes are used to assess the characteristics of spatially collocated Atmospheric Infrared Sounder (AIRS) thermodynamic-phase and ice cloud property retrievals within scenes of varying cloud type complexity. The likelihood of ice and liquid-phase detection strongly depends on the CloudSat-identified cloud scene type collocated with the AIRS footprint. Cloud scenes primarily consisting of cirrus, nimbostratus, altostratus, and deep convection are dominated by ice-phase detection, while stratocumulus, cumulus, and altocumulus are dominated by liquid- and undetermined-phase detection. Ice cloud particle size and optical thickness are largest for cloud scenes containing deep convection and cumulus and are smallest for cirrus. Cloud scenes with multiple cloud types have small reductions in information content and slightly higher residuals of observed and modeled radiance compared to cloud scenes with single cloud types. These results will help advance the development of temperature, specific humidity, and cloud property retrievals from hyperspectral infrared sounders that include cloud microphysics in forward radiative transfer models.

scholarly journals Validation of quasi-invariant ice cloud radiative quantities with MODIS satellite-based cloud property retrievals

2017 ◽  
Vol 194 ◽  
pp. 47-57 ◽  
Author(s):  
Jiachen Ding ◽  
Ping Yang ◽  
George W. Kattawar ◽  
Michael D. King ◽  
Steven Platnick ◽  
...  
Keyword(s):  
Cloud Property ◽  
Ice Cloud

Spaceborne Middle‐ and Far‐Infrared Observations Improving Nighttime Ice Cloud Property Retrievals

2020 ◽  
Vol 47 (18) ◽  
Author(s):  
Masanori Saito ◽  
Ping Yang ◽  
Xianglei Huang ◽  
Helen E. Brindley ◽  
Martin G. Mlynczak ◽  
...  
Keyword(s):  
Far Infrared ◽  
Infrared Observations ◽  
Cloud Property ◽  
Ice Cloud

scholarly journals Footprint-scale cloud type mixtures and their impacts on Atmospheric Infrared Sounder cloud property retrievals

2018 ◽  
Author(s):  
Alexandre Guillaume ◽  
Brian H. Kahn ◽  
Eric J. Fetzer ◽  
Qing Yue ◽  
Gerald J. Manipon ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Deep Convection ◽  
Cloud Microphysics ◽  
Specific Humidity ◽  
Phase Detection ◽  
Cloud Type ◽  
Atmospheric Infrared Sounder ◽  
Cloud Particle ◽  
Cloud Property ◽  
Ice Cloud

Abstract. A method is described to classify cloud mixtures of cloud top types, termed cloud scenes, using cloud type classification derived from the CloudSat radar (2B-CLDCLASS). The scale dependence of those cloud scenes is studied. For spatial scales near 45 km, only 16 out of 256 possible cloud scenes account for 90 % of all observations and contain either one, two, or three cloud types. The number of possible cloud scenes is shown to depend on spatial scale with a maximum number of 194 out of 256 possible scenes at a scale of 105 km and fewer cloud scenes at smaller and larger scales. The cloud scenes are used to assess the characteristics of spatially collocated Atmospheric Infrared Sounder (AIRS) thermodynamic phase and ice cloud property retrievals within scenes of varying cloud type complexity. The likelihood of ice and liquid phase detection strongly depends on the CloudSat-identified cloud scene type collocated with the AIRS footprint. Cloud scenes primarily consisting of cirrus, nimbostratus, altostratus and deep convection are dominated by ice phase detection, while stratocumulus, cumulus, and altocumulus are dominated by liquid and undetermined phase detection. Ice cloud particle size and optical thickness are largest for cloud scenes containing deep convection and cumulus, and are smallest for cirrus. Cloud scenes with multiple cloud types have small reductions in information content and slightly higher residuals of observed and modelled radiance compared to cloud scenes with single cloud types. These results will help advance the development of temperature, specific humidity, and cloud property retrievals from hyperspectral infrared sounders that include cloud microphysics in forward radiative transfer models.

scholarly journals Information Content of Ice Cloud Properties from Multi-Spectral, -Angle and -Polarization Observations

2020 ◽  
Vol 12 (16) ◽  
pp. 2548
Author(s):  
Manting Zhang ◽  
Shiwen Teng ◽  
Di Di ◽  
Xiuqing Hu ◽  
Husi Letu ◽  
...  
Keyword(s):  
Information Content ◽  
Degrees Of Freedom ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cloud Property ◽  
Additional Information ◽  
Ice Cloud ◽  
Cloud Properties ◽  
Spectral Angle

Ice clouds play an important role in the Earth’s radiation budget, while their microphysical and optical properties remain one of the major uncertainties in remote sensing and atmospheric studies. Many satellite-based multi-spectral, -angle and -polarization instruments have been launched in recent years, and it is unclear how these observations can be used to improve the understanding of ice cloud properties. This study discusses the impacts of multi-spectral, -angle and -polarization observations on ice cloud property retrievals by performing a theoretical information content (IC) analysis. Ice cloud properties, including the cloud optical thickness (COT), particle effective radius (Re) and particle habit (defined by the aspect ratio (AR) and the degree of surface roughness level (σ)), are considered. An accurate polarized radiative transfer model is used to simulate the top-of-atmosphere intensity and polarized observations at the cloud-detecting wavelengths of interest. The ice cloud property retrieval accuracy should be improved with the additional information from multi-spectral, -angle and -polarization observations, which is verified by the increased degrees of freedom for signal (DFS). Polarization observations at spectral wavelengths (i.e., 0.87 and 2.13 µm) are helpful in the improvement of ice cloud property retrievals, especially for small-sized particles. An optimal scheme to retrieve ice cloud properties is to comprise radiance intensity information at the 0.87, 1.24, 1.64 and 2.13 µm channels and polarization information (the degree of linear polarization, DOLP) at the 0.87 and 2.13 µm channels. As observations from multiple angles added, DFS clearly increases, while it becomes almost saturated when the number of angles reaches three. Besides, the retrieval of Re exhibits larger uncertainties, and the improvement in total DFS by adding multi-spectral, -angle and -polarization observations is mainly attributed to the improvement of Re retrieval. Our findings will benefit the future instrument design and the improvement in cloud property retrieval algorithms based on multi-spectral, -angle, and -polarization imagers.

scholarly journals Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

2020 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Lucie Leonarski ◽  
Laurent C.-Labonnote ◽  
Mathieu Compiègne ◽  
Jérôme Vidot ◽  
Anthony J. Baran ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Signal To Noise Ratio ◽  
Thermal Infrared ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Water Path ◽  
Ice Cloud ◽  
Ice Water Path ◽  
Ice Water

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).

scholarly journals MBL drizzle properties and their impact on cloud property retrievals

2015 ◽  
Vol 8 (4) ◽  
pp. 4307-4323
Author(s):  
P. Wu ◽  
X. Dong ◽  
B. Xi
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Property ◽  
Annual Means ◽  
Mean Differences ◽  
The Impact

Abstract. In this study, we retrieve and document drizzle properties, and investigate the impact of drizzle on cloud property retrievals from ground-based measurements at the ARM Azores site from June 2009 to December 2010. For the selected cloud and drizzle samples, the drizzle occurrence is 42.6% with a maximum of 55.8% in winter and a minimum of 35.6% in summer. The annual means of drizzle liquid water path LWPd, effective radius rd, and number concentration Nd for the rain (virga) samples are 5.48 (1.29) g m−2, 68.7 (39.5) μm, and 0.14 (0.38) cm−3. The seasonal mean LWPd values are less than 4% of the MWR-retrieved LWP values. The annual mean differences in cloud-droplet effective radius with and without drizzle are 0.12 and 0.38 μm, respectively, for the virga and rain samples. Therefore, we conclude that the impact of drizzle on cloud property retrievals is insignificant at the ARM Azores site.

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>

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