scholarly journals Use of spectral cloud emissivity to infer ice cloud boundaries: Methodology and assessment using CALIPSO cloud products

2019 ◽  
Author(s):  
Hye-Sil Kim ◽  
Bryan A. Baum ◽  
Yong-Sang Choi
Keyword(s):  
North Pacific Ocean ◽  
Weather Prediction ◽  
Single Layer ◽  
Ice Clouds ◽  
Ice Cloud ◽  
New Information ◽  
Infrared Imager ◽  
Cloud Temperature ◽  
Cloud Radiative Effects ◽  
Vertical Inhomogeneity

Abstract. Satellite-based operational cloud height retrievals generally assume a plane-parallel homogeneous cloud exists in each field of regard, or pixel, but this assumption ignores vertical inhomogeneity, which is of particular importance for optically thin, but geometrically thick, ice clouds. This study demonstrates that ice cloud emissivity uncertainties can be used to provide a reasonable range of ice cloud layer boundaries, i.e., the minimum to maximum heights. Here ice cloud emissivity uncertainties are obtained for three IR channels centered at 11, 12, and 13.3 µm. The range of cloud emissivities is used to infer a range of ice cloud temperature/heights, rather than a single value per pixel as provided by operational cloud retrievals. Our methodology is tested using MODIS observations over the western North Pacific Ocean during August 2015. We estimate minimum/maximum heights for three cloud regimes, i.e., single-layer thin and thick ice clouds, and multi-layered clouds. Our results are assessed through comparison with CALIOP Version 4 cloud products for a total of 11873 pixels. The cloud boundary heights for single-layer optically thin clouds show good agreement with those from CALIOP; bias for maximum (minimum) heights versus the cloud top (base) heights of CALIOP are 0.13 km (−1.01 km). For optically thick and multi-layered clouds, the biases of the estimated cloud heights from the cloud top/base become larger. Our method is applicable to measurements provided by most geostationary weather satellites including the GK-2A advanced multi-channel infrared imager. The vertically resolved heights for ice clouds can contribute new information for studies involving weather prediction and cloud radiative effects.

scholarly journals Use of spectral cloud emissivities and their related uncertainties to infer ice cloud boundaries: methodology and assessment using CALIPSO cloud products

2019 ◽  
Vol 12 (9) ◽  
pp. 5039-5054
Author(s):  
Hye-Sil Kim ◽  
Bryan A. Baum ◽  
Yong-Sang Choi
Keyword(s):  
North Pacific Ocean ◽  
Weather Prediction ◽  
Radiation Budget ◽  
Cloud Base ◽  
Ice Clouds ◽  
Ice Cloud ◽  
New Information ◽  
Infrared Imager ◽  
Cloud Temperature ◽  
Cloud Regimes

Abstract. Satellite-imager-based operational cloud property retrievals generally assume that a cloudy pixel can be treated as being plane-parallel with horizontally homogeneous properties. This assumption can lead to high uncertainties in cloud heights, particularly for the case of optically thin, but geometrically thick, clouds composed of ice particles. This study demonstrates that ice cloud emissivity uncertainties can be used to provide a reasonable range of ice cloud layer boundaries, i.e., the minimum to maximum heights. Here ice cloud emissivity uncertainties are obtained for three IR channels centered at 11, 12, and 13.3 µm. The range of cloud emissivities is used to infer a range of ice cloud temperature and heights, rather than a single value per pixel as provided by operational cloud retrievals. Our methodology is tested using MODIS observations over the western North Pacific Ocean during August 2015. We estimate minimum–maximum heights for three cloud regimes, i.e., single-layered optically thin ice clouds, single-layered optically thick ice clouds, and multilayered clouds. Our results are assessed through comparison with CALIOP version 4 cloud products for a total of 11873 pixels. The cloud boundary heights for single-layered optically thin clouds show good agreement with those from CALIOP; biases for maximum (minimum) heights versus the cloud-top (base) heights of CALIOP are 0.13 km (−1.01 km). For optically thick and multilayered clouds, the biases of the estimated cloud heights from the cloud top or cloud base become larger (0.30/−1.71 km, 1.41/−4.64 km). The vertically resolved boundaries for ice clouds can contribute new information for data assimilation efforts for weather prediction and radiation budget studies. Our method is applicable to measurements provided by most geostationary weather satellites including the GK-2A advanced multichannel infrared imager.

scholarly journals Statistics on clouds and their relation to thermodynamic conditions at Ny-Ålesund using ground-based sensor synergy

2018 ◽  
Author(s):  
Tatiana Nomokonova ◽  
Kerstin Ebell ◽  
Ulrich Löhnert ◽  
Marion Maturilli ◽  
Christoph Ritter ◽  
...  
Keyword(s):  
Microwave Radiometer ◽  
Single Layer ◽  
Mixed Phase ◽  
The Arctic ◽  
Time Data ◽  
Ice Clouds ◽  
Mean Values ◽  
Cloud Temperature ◽  
Thermodynamic Conditions ◽  
Mixed Phase Clouds

Abstract. The French–German Arctic Research Base AWIPEV at Ny-Ålesund, Svalbard, is an unique station for monitoring cloud related processes in the Arctic. For the first time, data from a set of ground-based instruments at AWIPEV observatory are analyzed to characterize the vertical structure of clouds. For this study, a 14-month dataset from Cloudnet combining observations from a ceilometer, a 94 GHz cloud radar and a microwave radiometer, is used. The total cloud occurrence of 81 %, with 44.8 % of multi-layer and 36 % of single-layer clouds was found. Among single-layer clouds the occurrence of liquid, ice and mixed-phase clouds was 6.4 %, 9 % and 20.6 %, respectively. It was found, that more than 90 % of single-layer liquid and mixed-phase clouds have LWP values lower than 100 and 200 g m2, respectively. Mean values of IWP for ice and mixed-phase clouds were found to be 273 and 164 g m2, respectively. The different types of single-layer clouds are also related to in-cloud temperature and relative humidity under which they occur. Statistics based on observations are compared to the ICON model output. Distinct differences in liquid phase occurrence in observations and the model at different environmental temperatures leading to higher occurrence of pure ice clouds and lower occurrence of mixed-phase clouds in the model at temperatures between −20° and −5 °C become evident. The analyzed dataset is useful for satellite validation and model evaluation.

scholarly journals Evaluation of AIRS Cloud-Thermodynamic-Phase Determination with CALIPSO

2014 ◽  
Vol 53 (4) ◽  
pp. 1012-1027 ◽  
Author(s):  
Hongchun Jin ◽  
Shaima L. Nasiri
Keyword(s):  
Single Layer ◽  
Atmospheric Infrared Sounder ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Effective Particle ◽  
Cloud Optical Thickness ◽  
Thermodynamic Phase ◽  
Pixel Scale ◽  
532 Nm ◽  
Heterogeneous Layer

AbstractAtmospheric Infrared Sounder (AIRS) infrared-based cloud-thermodynamic-phase retrievals are evaluated using the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud thermodynamic phase. The AIRS cloud phase is derived from spectral information contained within the 8–12-μm window, and CALIPSO provides coincident pixel-scale observations of cloud phase using the depolarization capability of the 532-nm channel. Comparisons are performed between the AIRS and CALIPSO cloud-phase observations for single-layer (48.5% of all clouds), heterogeneous-layer (45.9%), and multilayered (5.6%) clouds. The AIRS ice phase is in agreement with CALIPSO for more than 90% of coincident observations globally, with the largest discrepancies found in high latitudes and multilayered clouds. AIRS water phase generally follows CALIPSO spatial patterns, but the frequency is lower by about a factor of 2. The ice and water phases of AIRS both show misclassifications about 1% of the time when compared with CALIPSO. Not all clouds demonstrate strong phase signatures in the AIRS spectrum, which leads AIRS to classify unknown phase to around 10% of CALIPSO’s ice clouds and 60% of CALIPSO’s water clouds. This study shows that the algorithm is capable of detecting ice clouds within the AIRS field of view and can be used as the first step in further retrievals of ice-cloud optical thickness and effective particle size.

scholarly journals The Sentinel-3 SLSTR Atmospheric Motion Vectors Product at EUMETSAT

2021 ◽  
Vol 13 (9) ◽  
pp. 1702
Author(s):  
Kévin Barbieux ◽  
Olivier Hautecoeur ◽  
Maurizio De Bartolomei ◽  
Manuel Carranza ◽  
Régis Borde
Keyword(s):  
Land Surface ◽  
Weather Prediction ◽  
Forecast Model ◽  
Low Earth Orbit ◽  
Reference Image ◽  
Motion Vectors ◽  
Infrared Imager ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Leo Satellite

Atmospheric Motion Vectors (AMVs) are an important input to many Numerical Weather Prediction (NWP) models. EUMETSAT derives AMVs from several of its orbiting satellites, including the geostationary satellites (Meteosat), and its Low-Earth Orbit (LEO) satellites. The algorithm extracting the AMVs uses pairs or triplets of images, and tracks the motion of clouds or water vapour features from one image to another. Currently, EUMETSAT LEO satellite AMVs are retrieved from georeferenced images from the Advanced Very-High-Resolution Radiometer (AVHRR) on board the Metop satellites. EUMETSAT is currently preparing the operational release of an AMV product from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3 satellites. The main innovation in the processing, compared with AVHRR AMVs, lies in the co-registration of pairs of images: the images are first projected on an equal-area grid, before applying the AMV extraction algorithm. This approach has multiple advantages. First, individual pixels represent areas of equal sizes, which is crucial to ensure that the tracking is consistent throughout the processed image, and from one image to another. Second, this allows features that would otherwise leave the frame of the reference image to be tracked, thereby allowing more AMVs to be derived. Third, the same framework could be used for every LEO satellite, allowing an overall consistency of EUMETSAT AMV products. In this work, we present the results of this method for SLSTR by comparing the AMVs to the forecast model. We validate our results against AMVs currently derived from AVHRR and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). The release of the operational SLSTR AMV product is expected in 2022.

scholarly journals Effects of ice particle size vertical inhomogeneity on the passive remote sensing of ice clouds

2010 ◽  
Vol 115 (D17) ◽  
Author(s):  
Zhibo Zhang ◽  
Steven Platnick ◽  
Ping Yang ◽  
Andrew K. Heidinger ◽  
Jennifer M. Comstock
Keyword(s):  
Remote Sensing ◽  
Particle Size ◽  
Ice Clouds ◽  
Passive Remote Sensing ◽  
Vertical Inhomogeneity

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>

scholarly journals High-Resolution Seeded Simulations of Western North Pacific Ocean Tropical Cyclones in Two Future Extreme Climates

2018 ◽  
Vol 32 (2) ◽  
pp. 309-334
Author(s):  
J. G. McLay ◽  
E. A. Hendricks ◽  
J. Moskaitis
Keyword(s):  
High Resolution ◽  
Pacific Ocean ◽  
Tropical Cyclones ◽  
North Pacific ◽  
Western North Pacific ◽  
North Pacific Ocean ◽  
Weather Prediction ◽  
Bootstrap Analysis ◽  
Western North Pacific Ocean ◽  
The Future

ABSTRACT A variant of downscaling is devised to explore the properties of tropical cyclones (TCs) that originate in the open ocean of the western North Pacific Ocean (WestPac) region under extreme climates. This variant applies a seeding strategy in large-scale environments simulated by phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate-model integrations together with embedded integrations of Coupled Ocean–Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC), an operational, high-resolution, nonhydrostatic, convection-permitting numerical weather prediction (NWP) model. Test periods for the present day and late twenty-first century are sampled from two different integrations for the representative concentration pathway (RCP) 8.5 forcing scenario. Then seeded simulations for the present-day period are contrasted with similar seeded simulations for the future period. Reinforcing other downscaling studies, the seeding results suggest that the future environments are notably more conducive to high-intensity TC activity in the WestPac. Specifically, the future simulations yield considerably more TCs that exceed 96-kt (1 kt ≈ 0.5144 m s−1) intensity, and these TCs exhibit notably greater average life cycle maximum intensity and tend to spend more time above the 96-kt intensity threshold. Also, the future simulations yield more TCs that make landfall at >64-kt intensity, and the average landfall intensity of these storms is appreciably greater. These findings are supported by statistical bootstrap analysis as well as by a supplemental sensitivity analysis. Accounting for COAMPS-TC intensity forecast bias using a quantile-matching approach, the seeded simulations suggest that the potential maximum western North Pacific TC intensities in the future extreme climate may be approximately 190 kt.

scholarly journals On the origin of subvisible cirrus clouds in the tropical upper troposphere

2012 ◽  
Vol 12 (6) ◽  
pp. 14875-14926 ◽  
Author(s):  
M. Reverdy ◽  
V. Noel ◽  
H. Chepfer ◽  
B. Legras
Keyword(s):  
Cloud Formation ◽  
Formation Processes ◽  
Ice Clouds ◽  
Back Trajectories ◽  
Air Masses ◽  
Ice Cloud ◽  
And Behavior ◽  
Atmospheric Phenomena ◽  
Mean Variance ◽  
Lidar Observations

Abstract. Spaceborne lidar observations have recently revealed a previously undetected significant population of SubVisible Cirrus (SVC). We show them to be colder than −74 °C, with an optical depth below 0.0015 on average. The formation and persistence over time of this new cloud population could be related to several atmospheric phenomena. In this paper, we investigate the importance of external processes in the creation of this cloud population, vs. the traditional ice cloud formation theory through convection. The importance of three scenarios in the formation of the global SVC population is investigated through different approaches that include comparisons with data imaging from several spaceborne instruments and back-trajectories that document the history and behavior of air masses leading to a point in time and space where subvisible cirrus were detected. In order simplify the study of cloud formation processes, we singled out SVC with coherent temperature histories (mean variance lower than 4 K) according to back-trajectories along 5, 10 or 15 days (respectively 58, 25 and 11% of SVC). Our results suggest that external processes, including local increases in liquid and hygroscopic aerosol concentration (either through biomass burning or volcanic injection forming sulfate-based aerosols in the troposphere or the stratosphere) have no noticeable short-term or mid-term impact on the SVC population. On the other hand, we find that ~60% of air masses interacted with convective activity in the days before they led to cloud formation and detection, which correspond to 37 to 65% of SVC. These results put forward the important influence of classical cloud formation processes compared to external influences in forming SVC. They support the view that the SVC population observed by CALIOP is an extension of the general upper tropospheric ice clouds population with its extreme thinness as its only differentiating factor.

scholarly journals Detecting Generic Music Features with Single Layer Feedforward Network using Unsupervised Hebbian Computation

2020 ◽  
Vol 12 (2) ◽  
pp. 1-20
Author(s):  
Sourav Das ◽  
Anup Kumar Kolya
Keyword(s):  
Neural Network ◽  
Feature Detection ◽  
Feature Recognition ◽  
Hebbian Learning ◽  
Feature Learning ◽  
Single Layer ◽  
Feedforward Network ◽  
New Information ◽  
Unsupervised Training ◽  
And Performance

In this work, the authors extract information on distinct baseline features from a popular open-source music corpus and explore new recognition techniques by applying unsupervised Hebbian learning techniques on our single-layer neural network using the same dataset. They show the detailed empirical findings to simulate how such an algorithm can help a single layer feedforward network in training for music feature learning as patterns. The unsupervised training algorithm enhances the proposed neural network to achieve an accuracy of 90.36% for successful music feature detection. For comparative analysis against similar tasks, they put their results with the likes of several previous benchmark works. They further discuss the limitations and thorough error analysis of the work. They hope to discover and gather new information about this particular classification technique and performance, also further understand future potential directions that could improve the art of computational music feature recognition.

scholarly journals Longwave indirect effect of mineral dusts on ice clouds

2010 ◽  
Vol 10 (16) ◽  
pp. 7753-7761 ◽  
Author(s):  
Q. Min ◽  
R. Li
Keyword(s):  
Infrared Radiation ◽  
Mineral Dust ◽  
Dust Cloud ◽  
Thermal Infrared ◽  
Minor Role ◽  
Ice Clouds ◽  
Cloud Systems ◽  
Ice Cloud ◽  
Mineral Dusts ◽  
Thermal Infrared Radiation

Abstract. In addition to microphysical changes in clouds, changes in nucleation processes of ice cloud due to aerosols would result in substantial changes in cloud top temperature as mildly supercooled clouds are glaciated through heterogenous nucleation processes. Measurements from multiple sensors on multiple observing platforms over the Atlantic Ocean show that the cloud effective temperature increases with mineral dust loading with a slope of +3.06 °C per unit aerosol optical depth. The macrophysical changes in ice cloud top distributions as a consequence of mineral dust-cloud interaction exert a strong cooling effect (up to 16 Wm−2) of thermal infrared radiation on cloud systems. Induced changes of ice particle size by mineral dusts influence cloud emissivity and play a minor role in modulating the outgoing longwave radiation for optically thin ice clouds. Such a strong cooling forcing of thermal infrared radiation would have significant impacts on cloud systems and subsequently on climate.

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