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Journal articles on the topic 'The cloud'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 January 2023

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1

Koren, I., L. Oreopoulos, G. Feingold, L. A. Remer, and O. Altaratz. "How small is a small cloud?" Atmospheric Chemistry and Physics Discussions 8, no. 2 (2008): 6379–407. http://dx.doi.org/10.5194/acpd-8-6379-2008.

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Abstract. The interplay between clouds and aerosols and their contribution to the radiation budget is one of the largest uncertainties of climate change. Most work to date has separated cloudy and cloud-free areas in order to evaluate the individual radiative forcing of aerosols, clouds, and aerosol effects on clouds. Here we examine the size distribution and the optical properties of small, sparse cumulus clouds and the associated optical properties of what is considered a cloud-free atmosphere within the cloud field. We show that any separation between clouds and cloud free atmosphere will i

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2

Koren, I., L. Oreopoulos, G. Feingold, L. A. Remer, and O. Altaratz. "How small is a small cloud?" Atmospheric Chemistry and Physics 8, no. 14 (2008): 3855–64. http://dx.doi.org/10.5194/acp-8-3855-2008.

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Abstract. The interplay between clouds and aerosols and their contribution to the radiation budget is one of the largest uncertainties of climate change. Most work to date has separated cloudy and cloud-free areas in order to evaluate the individual radiative forcing of aerosols, clouds, and aerosol effects on clouds. Here we examine the size distribution and the optical properties of small, sparse cumulus clouds and the associated optical properties of what is considered a cloud-free atmosphere within the cloud field. We show that any separation between clouds and cloud free atmosphere will i

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Li, J., Z. Wu, Z. Hu, Y. Zhang, and M. Molinier. "AUTOMATIC CLOUD DETECTION METHOD BASED ON GENERATIVE ADVERSARIAL NETWORKS IN REMOTE SENSING IMAGES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 885–92. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-885-2020.

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Abstract. Clouds in optical remote sensing images seriously affect the visibility of background pixels and greatly reduce the availability of images. It is necessary to detect clouds before processing images. In this paper, a novel cloud detection method based on attentive generative adversarial network (Auto-GAN) is proposed for cloud detection. Our main idea is to inject visual attention into the domain transformation to detect clouds automatically. First, we use a discriminator (D) to distinguish between cloudy and cloud free images. Then, a segmentation network is used to detect the differ

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Coakley, James A., Michael A. Friedman, and William R. Tahnk. "Retrieval of Cloud Properties for Partly Cloudy Imager Pixels." Journal of Atmospheric and Oceanic Technology 22, no. 1 (2005): 3–17. http://dx.doi.org/10.1175/jtech-1681.1.

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Abstract Retrievals of cloud properties from satellite imagery often invoke the assumption that the fields of view are overcast when cloud-contaminated, even though a significant fraction are only partially cloud-covered. The overcast assumption leads to biases in the retrieved cloud properties: cloud amounts and droplet effective radii are typically overestimated, while visible optical depths, cloud altitudes, cloud liquid water amounts, and column droplet number concentrations are typically underestimated. In order to estimate these biases, a retrieval scheme was developed to obtain the prop

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Mieslinger, Theresa, Bjorn Stevens, Tobias Kölling, Manfred Brath, Martin Wirth, and Stefan A. Buehler. "Optically thin clouds in the trades." Atmospheric Chemistry and Physics 22, no. 10 (2022): 6879–98. http://dx.doi.org/10.5194/acp-22-6879-2022.

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Abstract. We develop a new method to describe the total cloud cover including optically thin clouds in trade wind cumulus cloud fields. Climate models and large eddy simulations commonly underestimate the cloud cover, while estimates from observations largely disagree on the cloud cover in the trades. Currently, trade wind clouds significantly contribute to the uncertainty in climate sensitivity estimates derived from model perturbation studies. To simulate clouds well, especially how they change in a future climate, we have to know how cloudy it is. In this study we develop a method to quanti

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Sun, J., H. Leighton, M. K. Yau, and P. Ariya. "Numerical evidence for cloud droplet nucleation at the cloud-environment interface." Atmospheric Chemistry and Physics Discussions 12, no. 7 (2012): 17723–42. http://dx.doi.org/10.5194/acpd-12-17723-2012.

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Abstract. Cumulus clouds have long been recognized as being the results of ascending moist air from below the cloud base. Cloud droplet nucleation is understood to take place near the cloud base and inside accelerating rising cloudy air. Here we describe circumstances under which cloud droplet nucleation takes place at the interface of ascending cloudy air and clear air. Evaporation is normally expected to occur at this interface. However, continuity of moving air requires cloud-free air above the boundary of rising cloudy air to move upwards in response to the gradient force of perturbation p

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Sun, J., H. Leighton, M. K. Yau, and P. Ariya. "Numerical evidence for cloud droplet nucleation at the cloud-environment interface." Atmospheric Chemistry and Physics 12, no. 24 (2012): 12155–64. http://dx.doi.org/10.5194/acp-12-12155-2012.

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Abstract. Cumulus clouds have long been recognized as being the results of ascending moist air from below the cloud base. Cloud droplet nucleation is understood to take place near the cloud base and inside accelerating rising cloudy air. Here we describe circumstances under which cloud droplet nucleation takes place at the interface of ascending cloudy air and clear air. Evaporation is normally expected to occur at this interface. However, continuity of moving air requires cloud-free air above the boundary of rising cloudy air to move upwards in response to the gradient force of perturbation p

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Lu, Shiming, Mingjun He, Shuangyan He, et al. "An Improved Cloud Masking Method for GOCI Data over Turbid Coastal Waters." Remote Sensing 13, no. 14 (2021): 2722. http://dx.doi.org/10.3390/rs13142722.

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Clouds severely hinder the radiative transmission of visible light; thus, correctly masking cloudy and non-cloudy pixels is a preliminary step in processing ocean color remote sensing data. However, cloud masking over turbid waters is prone to misjudgment, leading to loss of non-cloudy pixel data. This research proposes an improved cloud masking method over turbid water to classify cloudy and non-cloudy pixels based on spectral variability of Rayleigh-corrected reflectance acquired by the Geostationary Ocean Color Imager (GOCI). Compared with other existing cloud masking methods, we demonstrat

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9

Kim, Hye-Sil, Bryan A. Baum, and Yong-Sang Choi. "Use of spectral cloud emissivities and their related uncertainties to infer ice cloud boundaries: methodology and assessment using CALIPSO cloud products." Atmospheric Measurement Techniques 12, no. 9 (2019): 5039–54. http://dx.doi.org/10.5194/amt-12-5039-2019.

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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 c

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10

Massons, J., D. Domingo, and J. Lorente. "Seasonal cycle of cloud cover analyzed using Meteosat images." Annales Geophysicae 16, no. 3 (1998): 331–41. http://dx.doi.org/10.1007/s00585-998-0331-3.

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Abstract. A cloud-detection method was used to retrieve cloudy pixels from Meteosat images. High spatial resolution (one pixel), monthly averaged cloud-cover distribution was obtained for a 1-year period. The seasonal cycle of cloud amount was analyzed. Cloud parameters obtained include the total cloud amount and the percentage of occurrence of clouds at three altitudes. Hourly variations of cloud cover are also analyzed. Cloud properties determined are coherent with those obtained in previous studies.Key words. Cloud cover · Meteosat

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Stubenrauch, C. J., S. Cros, A. Guignard, and N. Lamquin. "A 6-year global cloud climatology from the Atmospheric InfraRed Sounder AIRS and a statistical analysis in synergy with CALIPSO and CloudSat." Atmospheric Chemistry and Physics Discussions 10, no. 3 (2010): 8247–96. http://dx.doi.org/10.5194/acpd-10-8247-2010.

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Abstract. We present a six-year global climatology of cloud properties, obtained from observations of the Atmospheric Infrared Sounder (AIRS) onboard the NASA Aqua satellite. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined with CloudSat observations, both missions launched as part of the A-Train in 2006, provide a unique opportunity to evaluate the retrieved AIRS cloud properties such as cloud amount and height as well as to explore the vertical structure of different cloud types. AIRS-LMD cloud detection agrees with CALIPSO about 85% over ocean and about

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Stubenrauch, C. J., S. Cros, A. Guignard, and N. Lamquin. "A 6-year global cloud climatology from the Atmospheric InfraRed Sounder AIRS and a statistical analysis in synergy with CALIPSO and CloudSat." Atmospheric Chemistry and Physics 10, no. 15 (2010): 7197–214. http://dx.doi.org/10.5194/acp-10-7197-2010.

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Abstract. We present a six-year global climatology of cloud properties, obtained from observations of the Atmospheric Infrared Sounder (AIRS) onboard the NASA Aqua satellite. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined with CloudSat observations, both missions launched as part of the A-Train in 2006, provide a unique opportunity to evaluate the retrieved AIRS cloud properties such as cloud amount and height. In addition, they permit to explore the vertical structure of different cloud types. AIRS-LMD cloud detection agrees with CALIPSO about 85% over o

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13

Hutchison, Keith D., Barbara D. Iisager, Thomas J. Kopp, and John M. Jackson. "Distinguishing Aerosols from Clouds in Global, Multispectral Satellite Data with Automated Cloud Classification Algorithms." Journal of Atmospheric and Oceanic Technology 25, no. 4 (2008): 501–18. http://dx.doi.org/10.1175/2007jtecha1004.1.

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Abstract A new approach is presented to distinguish between clouds and heavy aerosols with automated cloud classification algorithms developed for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program. These new procedures exploit differences in both spectral and textural signatures between clouds and aerosols to isolate pixels originally classified as cloudy by the Visible/Infrared Imager/Radiometer Suite (VIIRS) cloud mask algorithm that in reality contains heavy aerosols. The procedures have been tested and found to accurately distinguish clouds from dust,

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14

Hayes, J. "Clout of the cloud (cloud computing)." Engineering & Technology 4, no. 6 (2009): 60–61. http://dx.doi.org/10.1049/et.2009.0611.

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15

Wang, P., P. Stammes, R. van der A, G. Pinardi, and M. van Roozendael. "FRESCO+: an improved O<sub>2</sub> A-band cloud retrieval algorithm for tropospheric trace gas retrievals." Atmospheric Chemistry and Physics Discussions 8, no. 3 (2008): 9697–729. http://dx.doi.org/10.5194/acpd-8-9697-2008.

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Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective

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Wang, P., P. Stammes, R. van der A, G. Pinardi, and M. van Roozendael. "FRESCO+: an improved O<sub>2</sub> A-band cloud retrieval algorithm for tropospheric trace gas retrievals." Atmospheric Chemistry and Physics 8, no. 21 (2008): 6565–76. http://dx.doi.org/10.5194/acp-8-6565-2008.

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Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective

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17

Sanchez, Adriana, Nicole M. Hughes, and William K. Smith. "Importance of natural cloud regimes to ecophysiology in the alpine species, Caltha leptosepala and Arnica parryi, Snowy Range Mountains, southeast Wyoming, USA." Functional Plant Biology 42, no. 2 (2015): 186. http://dx.doi.org/10.1071/fp14096.

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The south-central Rocky Mountains, USA, are characterised by a dry, continental mesoclimate with typical convective cloud formation during the afternoon. Little is known about the specific influence of such predictable cloud patterns on the microclimate and ecophysiology of associated species. During the summer of 2012, days with afternoon clouds were most common (50% of all days) compared with completely clear (24%) or cloudy days (6.5%). In two representative alpine species, Caltha leptosepala DC. and Arnica parryi A. Gray, fully overcast days reduced mean daily photosynthesis (A) by nearly

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18

Harshvardhan, Guang Guo, Robert N. Green, Zheng Qu, and Takashi Y. Nakajima. "Remotely Sensed Microphysical and Thermodynamic Properties of Nonuniform Water Cloud Fields." Journal of the Atmospheric Sciences 61, no. 21 (2004): 2574–87. http://dx.doi.org/10.1175/jas3301.1.

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Abstract Visible and near-infrared reflected radiances have been used to estimate the cloud optical depth and effective radius of cloud-filled global area coverage (GAC) pixels from the Advanced Very High Resolution Radiometer (AVHRR) for two cases in the North Atlantic Ocean. One is representative of clouds having low concentrations of cloud condensation nuclei (CCN), while the other is an example of maritime clouds forming in continental air, in this case, intruding from Europe around a cutoff low pressure system. It is shown that an estimate of the cloud drop concentration can be obtained f

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19

Xia, Shuang, Alberto Mestas-Nuñez, Hongjie Xie, Jiakui Tang, and Rolando Vega. "Characterizing Variability of Solar Irradiance in San Antonio, Texas Using Satellite Observations of Cloudiness." Remote Sensing 10, no. 12 (2018): 2016. http://dx.doi.org/10.3390/rs10122016.

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Since the main attenuation of solar irradiance reaching the earth’s surface is due to clouds, it has been hypothesized that global horizontal irradiance attenuation and its temporal variability at a given location could be characterized simply by cloud properties at that location. This hypothesis is tested using global horizontal irradiance measurements at two stations in San Antonio, Texas, and satellite estimates of cloud types and cloud layers from the Geostationary Operational Environmental Satellite (GOES) Surface and Insolation Product. A modified version of an existing solar attenuation

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20

Balmes, Kelly, and Qiang Fu. "An Investigation of Optically Very Thin Ice Clouds from Ground-Based ARM Raman Lidars." Atmosphere 9, no. 11 (2018): 445. http://dx.doi.org/10.3390/atmos9110445.

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Optically very thin ice clouds from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and ground-based Raman lidars (RL) at the atmospheric radiation measurement (ARM) sites of the Southern Great Plains (SGP) and Tropical Western Pacific (TWP) are analyzed. The optically very thin ice clouds, with ice cloud column optical depths below 0.01, are about 23% of the transparent ice-cloudy profiles from the RL, compared to 4–7% from CALIPSO. The majority (66–76%) of optically very thin ice clouds from the RLs are found to be adjacent to ice clouds with ice cloud column

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Utrillas, María Pilar, María José Marín, Víctor Estellés, et al. "Comparison of Cloud Amounts Retrieved with Three Automatic Methods and Visual Observations." Atmosphere 13, no. 6 (2022): 937. http://dx.doi.org/10.3390/atmos13060937.

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Four methods have been used for the estimation of the total cloud amount and cloud amount for low clouds: visual observations, the Long method applied on pyranometer measurements, the Automatic Partial Cloud Amount Detection Algorithm (APCADA) method applied on pyrgeometers measurements, and ceilometer measurements of the cloud base height. Records from meteorological observers indicate that clear days (0–1 octa) represent the most frequent cloud amount for low clouds. In contrast, the total cloud amount is more aleatory. Results obtained from the Long method show maximum frequency in the extr

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Chen, Xidong, Liangyun Liu, Yuan Gao, Xiao Zhang, and Shuai Xie. "A Novel Classification Extension-Based Cloud Detection Method for Medium-Resolution Optical Images." Remote Sensing 12, no. 15 (2020): 2365. http://dx.doi.org/10.3390/rs12152365.

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Accurate cloud detection using medium-resolution multispectral satellite imagery (such as Landsat and Sentinel data) is always difficult due to the complex land surfaces, diverse cloud types, and limited number of available spectral bands, especially in the case of images without thermal bands. In this paper, a novel classification extension-based cloud detection (CECD) method was proposed for masking clouds in the medium-resolution images. The new method does not rely on thermal bands and can be used for masking clouds in different types of medium-resolution satellite imagery. First, with the

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Ahlgrimm, Maike, David A. Randall, and Martin Köhler. "Evaluating Cloud Frequency of Occurrence and Cloud-Top Height Using Spaceborne Lidar Observations." Monthly Weather Review 137, no. 12 (2009): 4225–37. http://dx.doi.org/10.1175/2009mwr2937.1.

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Abstract A strategy for model evaluation using spaceborne lidar observations is presented. Observations from the Geoscience Laser Altimeter System are recast onto the model grid to assess the ability of two versions of the Integrated Forecasting System to model marine stratocumulus clouds. The two model versions differ primarily in their treatment of clear and cloudy boundary layers. For each grid column, a representative cloud fraction and cloud-top height are derived from the observations, as well as from the model. By applying the same threshold criteria for cloud fraction and cloud-top hei

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Chang, Fu-Lung, and James A. Coakley. "Relationships between Marine Stratus Cloud Optical Depth and Temperature: Inferences from AVHRR Observations." Journal of Climate 20, no. 10 (2007): 2022–36. http://dx.doi.org/10.1175/jcli4115.1.

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Abstract Studies using International Satellite Cloud Climatology Project (ISCCP) data have reported decreases in cloud optical depth with increasing temperature, thereby suggesting a positive feedback in cloud optical depth as climate warms. The negative cloud optical depth and temperature relationships are questioned because ISCCP employs threshold assumptions to identify cloudy pixels that have included partly cloudy pixels. This study applies the spatial coherence technique to one month of Advanced Very High Resolution Radiometer (AVHRR) data over the Pacific Ocean to differentiate overcast

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Yang, S., and X. Zou. "Temperature Profiles and Lapse Rate Climatology in Altostratus and Nimbostratus Clouds Derived from GPS RO Data." Journal of Climate 26, no. 16 (2013): 6000–6014. http://dx.doi.org/10.1175/jcli-d-12-00646.1.

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Abstract Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation (RO) refractivity profiles in altostratus and nimbostratus clouds from 2007 to 2010 are first identified based on collocated CloudSat data. Vertical temperature profiles in these clouds are then retrieved from cloudy refractivity profiles. Contributions of cloud liquid water content and ice water content are also included in the retrieval algorithm. The temperature profiles and their lapse rates are compared with those from a standard GPS RO wet retrieval without including cloud effects.

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Xu, Wenjing, and Daren Lyu. "Evaluation of Cloud Mask and Cloud Top Height from Fengyun-4A with MODIS Cloud Retrievals over the Tibetan Plateau." Remote Sensing 13, no. 8 (2021): 1418. http://dx.doi.org/10.3390/rs13081418.

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The Tibetan Plateau (TP) has profound thermal and dynamic influences on the atmospheric circulation, energy, and water cycles of the climate system, which make the clouds over the TP the forefront of atmospheric and climate science. However, the highest altitude and most complex terrain of the TP make the retrieval of cloud properties challenging. In order to understand the performance and limitations of cloud retrievals over the TP derived from the state-of-the-art Advanced Geosynchronous Radiation Imager (AGRI) onboard the new generation of Chinese Geostationary (GEO) meteorological satellit

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Sedlar, Joseph. "Implications of Limited Liquid Water Path on Static Mixing within Arctic Low-Level Clouds." Journal of Applied Meteorology and Climatology 53, no. 12 (2014): 2775–89. http://dx.doi.org/10.1175/jamc-d-14-0065.1.

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AbstractObservations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%–30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and o

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Gielen, C., M. Van Roozendael, F. Hendrick, et al. "A simple and versatile cloud-screening method for MAX-DOAS retrievals." Atmospheric Measurement Techniques 7, no. 10 (2014): 3509–27. http://dx.doi.org/10.5194/amt-7-3509-2014.

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Abstract. We present a cloud-screening method based on differential optical absorption spectroscopy (DOAS) measurements, more specifically using intensity measurements and O4 differential slant-column densities (DSCDs). Using the colour index (CI), i.e. the ratio of the radiance at two wavelengths, we define different sky conditions including clear, thin clouds/polluted, fully-cloudy, and heavily polluted. We also flag the presence of broken and scattered clouds. The O4 absorption is a good tracer for cloud-induced light-path changes and is used to detect clouds and discriminate between instan

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Gielen, C., M. Van Roozendael, F. Hendrick, et al. "A simple and versatile cloud-screening method for MAX-DOAS retrievals." Atmospheric Measurement Techniques Discussions 7, no. 6 (2014): 5883–920. http://dx.doi.org/10.5194/amtd-7-5883-2014.

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Abstract. We present a cloud-screening method based on differential optical absorption spectroscopy (DOAS) measurements, more specifically using zenith sky spectra and O4 differential slant-column densities (DSCDs). Using the colour index (CI), i.e. the ratio of the radiance at two wavelengths, we define different sky conditions including clear, thin clouds/polluted, fully-cloudy, and heavily polluted. We also flag the presence of broken and scattered clouds. The O4 absorption is a good tracer for cloud-induced light-path changes and is used to detect clouds and discriminate between instances

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Luffarelli, Marta, Yves Govaerts, and Lucio Franceschini. "Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations." Atmosphere 13, no. 5 (2022): 691. http://dx.doi.org/10.3390/atmos13050691.

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The Combined Inversion of Surface and AeRosols (CISAR) algorithm for the joint retrieval of surface and aerosol single scattering properties has been further developed in order to extend the retrieval to clouds and overcome the need for an external cloud mask. Pixels located in the transition zone between pure cloud and pure aerosol are often discarded by both aerosol and cloud algorithms, despite being essential for studying aerosol–cloud interactions, which still represent the largest source of uncertainty in climate predictions. The proposed approach aims at filling this gap and deepening t

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Luffarelli, Marta, Yves Govaerts, and Lucio Franceschini. "Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations." Atmosphere 13, no. 5 (2022): 691. http://dx.doi.org/10.3390/atmos13050691.

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The Combined Inversion of Surface and AeRosols (CISAR) algorithm for the joint retrieval of surface and aerosol single scattering properties has been further developed in order to extend the retrieval to clouds and overcome the need for an external cloud mask. Pixels located in the transition zone between pure cloud and pure aerosol are often discarded by both aerosol and cloud algorithms, despite being essential for studying aerosol–cloud interactions, which still represent the largest source of uncertainty in climate predictions. The proposed approach aims at filling this gap and deepening t

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Wang, P., O. N. E. Tuinder, L. G. Tilstra, M. de Graaf, and P. Stammes. "Interpretation of FRESCO cloud retrievals in case of absorbing aerosol events." Atmospheric Chemistry and Physics 12, no. 19 (2012): 9057–77. http://dx.doi.org/10.5194/acp-12-9057-2012.

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Abstract. Cloud and aerosol information is needed in trace gas retrievals from satellite measurements. The Fast REtrieval Scheme for Clouds from the Oxygen A band (FRESCO) cloud algorithm employs reflectance spectra of the O2 A band around 760 nm to derive cloud pressure and effective cloud fraction. In general, clouds contribute more to the O2 A band reflectance than aerosols. Therefore, the FRESCO algorithm does not correct for aerosol effects in the retrievals and attributes the retrieved cloud information entirely to the presence of clouds, and not to aerosols. For events with high aerosol

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Dinh, Tra, and Stephan Fueglistaler. "Cirrus, Transport, and Mixing in the Tropical Upper Troposphere." Journal of the Atmospheric Sciences 71, no. 4 (2014): 1339–52. http://dx.doi.org/10.1175/jas-d-13-0147.1.

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Abstract The impact of cloud radiative heating on transport time scales from the tropical upper troposphere to the stratosphere is studied in two-dimensional numerical simulations. Clouds are idealized as sources of radiative heating and are stochastically distributed in space and time. A spatial probability function constrains clouds to occur in only part of the domain to depict heterogeneously distributed clouds in the atmosphere. The transport time from the lower to upper boundaries (age of air) is evaluated with trajectories. The spectra of age of air obtained in the simulations are bimoda

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Cho, Hyoun-Myoung, Shaima L. Nasiri, and Ping Yang. "Application of CALIOP Measurements to the Evaluation of Cloud Phase Derived from MODIS Infrared Channels." Journal of Applied Meteorology and Climatology 48, no. 10 (2009): 2169–80. http://dx.doi.org/10.1175/2009jamc2238.1.

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Abstract In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) infrared-based cloud thermodynamic phase retrievals are evaluated using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals for the 6 months from January to June of 2008. The CALIOP 5-km cloud-layer product provides information on cloud opacity, cloud-top height, midlayer cloud temperature, and cloud thermodynamic phase. Comparisons are made between MODIS IR phase and CALIOP observations for single-layer clouds (54% of the cloudy CALIOP scenes) and for the top layer of the CALIOP scenes. Both CALIOP

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Tjernström, Michael, Joseph Sedlar, and Matthew D. Shupe. "How Well Do Regional Climate Models Reproduce Radiation and Clouds in the Arctic? An Evaluation of ARCMIP Simulations." Journal of Applied Meteorology and Climatology 47, no. 9 (2008): 2405–22. http://dx.doi.org/10.1175/2008jamc1845.1.

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Abstract Downwelling radiation in six regional models from the Arctic Regional Climate Model Intercomparison (ARCMIP) project is systematically biased negative in comparison with observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment, although the correlations with observations are relatively good. In this paper, links between model errors and the representation of clouds in these models are investigated. Although some modeled cloud properties, such as the cloud water paths, are reasonable in a climatological sense, the temporal correlation of model cloud properties w

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Wind, Galina, Steven Platnick, Michael D. King, et al. "Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band." Journal of Applied Meteorology and Climatology 49, no. 11 (2010): 2315–33. http://dx.doi.org/10.1175/2010jamc2364.1.

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Abstract Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System (EOS) Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that present difficulties for retrieving cloud effective radius using single-layer plane-parallel cloud models. The algorithm uses the MODIS 0.94-μm water vapor band along with CO2 bands to obtain two above-

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Tompkins, Adrian M., and Francesca Di Giuseppe. "An Interpretation of Cloud Overlap Statistics." Journal of the Atmospheric Sciences 72, no. 8 (2015): 2877–89. http://dx.doi.org/10.1175/jas-d-14-0278.1.

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Abstract Observational studies have shown that the vertical overlap of cloudy layers separated by clear sky can exceed that of the random overlap assumption, suggesting a tendency toward minimum overlap. In addition, the rate of decorrelation of vertically continuous clouds with increasing layer separation is sensitive to the horizontal scale of the cloud scenes used. The authors give a heuristic argument that these phenomena result from data truncation, where overcast or single cloud layers are removed from the analysis. This occurs more frequently as the cloud sampling scale falls progressiv

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Wang, P., O. N. E. Tuinder, L. G. Tilstra, and P. Stammes. "Interpretation of FRESCO cloud retrievals in case of absorbing aerosol events." Atmospheric Chemistry and Physics Discussions 11, no. 12 (2011): 32685–721. http://dx.doi.org/10.5194/acpd-11-32685-2011.

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Abstract. Cloud and aerosol information is needed in trace gas retrievals from satellite measurements. The Fast REtrieval Scheme for Clouds from the Oxygen A band (FRESCO) cloud algorithm employs reflectance spectra of the O2 A band around 760 nm to derive cloud pressure and effective cloud fraction. In general, clouds contribute more to the O2 A band reflectance than aerosols. Therefore, the FRESCO algorithm does not correct for aerosol effects in the retrievals and attributes the retrieved cloud information entirely to the presence of clouds, and not to aerosols. For events with high aerosol

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Yue, Zhiguo, Daniel Rosenfeld, Guihua Liu, et al. "Automated Mapping of Convective Clouds (AMCC) Thermodynamical, Microphysical, and CCN Properties from SNPP/VIIRS Satellite Data." Journal of Applied Meteorology and Climatology 58, no. 4 (2019): 887–902. http://dx.doi.org/10.1175/jamc-d-18-0144.1.

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AbstractThe advent of the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi NPP (SNPP) satellite made it possible to retrieve a new class of convective cloud properties and the aerosols that they ingest. An automated mapping system of retrieval of some properties of convective cloud fields over large areas at the scale of satellite coverage was developed and is presented here. The system is named Automated Mapping of Convective Clouds (AMCC). The input is level-1 VIIRS data and meteorological gridded data. AMCC identifies the cloudy pixels of convective elements; retrieves fo

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Lin, L., X. Zou, R. Anthes, and Y.-H. Kuo. "COSMIC GPS Radio Occultation Temperature Profiles in Clouds." Monthly Weather Review 138, no. 4 (2010): 1104–18. http://dx.doi.org/10.1175/2009mwr2986.1.

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Abstract Thermodynamic states in clouds are closely related to physical processes such as phase changes of water and longwave and shortwave radiation. Global Positioning System (GPS) radio occultation (RO) data are not affected by clouds and have high vertical resolution, making them ideally suited to cloud profiling on a global basis. By comparing the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) RO refractivity data with those of the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis and ECMWF analy

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Marchant, Benjamin, Steven Platnick, Kerry Meyer, G. Thomas Arnold, and Jérôme Riedi. "MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP." Atmospheric Measurement Techniques 9, no. 4 (2016): 1587–99. http://dx.doi.org/10.5194/amt-9-1587-2016.

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Abstract. Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budg

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Marchant, B., S. Platnick, K. Meyer, G. T. Arnold, and J. Riedi. "MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP." Atmospheric Measurement Techniques Discussions 8, no. 11 (2015): 11893–924. http://dx.doi.org/10.5194/amtd-8-11893-2015.

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Abstract. Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budg

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Dong, Xiquan, Baike Xi, and Patrick Minnis. "A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II: Cloud Fraction and Surface Radiative Forcing." Journal of Climate 19, no. 9 (2006): 1765–83. http://dx.doi.org/10.1175/jcli3710.1.

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Abstract Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0–3 km), middle (3–6 km), and high clouds (&gt;6 km) using ARM SCF ground-based paired lidar–radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers a

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Bugliaro, L., T. Zinner, C. Keil, et al. "Validation of cloud property retrievals with simulated satellite radiances: a case study for SEVIRI." Atmospheric Chemistry and Physics Discussions 10, no. 9 (2010): 21931–88. http://dx.doi.org/10.5194/acpd-10-21931-2010.

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Abstract. Validation of cloud properties retrieved from passive spaceborne imagers is essential for cloud and climate applications but complicated due to the large differences in scale and observation geometry between the satellite footprint and the independent ground based or airborne observations. Here we illustrate and demonstrate an alternative approach: starting from the output of the COSMO-EU weather model of the German Weather Service realistic three-dimensional cloud structures at a spatial scale of 2.33 km are produced by statistical downscaling and microphysical properties are associ

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Romps, David M., and Andrew M. Vogelmann. "Methods for Estimating 2D Cloud Size Distributions from 1D Observations." Journal of the Atmospheric Sciences 74, no. 10 (2017): 3405–17. http://dx.doi.org/10.1175/jas-d-17-0105.1.

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Abstract The two-dimensional (2D) size distribution of clouds in the horizontal plane plays a central role in the calculation of cloud cover, cloud radiative forcing, convective entrainment rates, and the likelihood of precipitation. Here, a simple method is proposed for calculating the area-weighted mean cloud size and for approximating the 2D size distribution from the 1D cloud-chord lengths measured by aircraft and vertically pointing lidar and radar. This simple method (which is exact for square clouds) compares favorably against the inverse Abel transform (which is exact for circular clou

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Kotarba, Andrzej Z. "Calibration of global MODIS cloud amount using CALIOP cloud profiles." Atmospheric Measurement Techniques 13, no. 9 (2020): 4995–5012. http://dx.doi.org/10.5194/amt-13-4995-2020.

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Abstract. The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection procedure classifies instantaneous fields of view (IFOVs) as either “confident clear”, “probably clear”, “probably cloudy”, or “confident cloudy”. The cloud amount calculation requires quantitative cloud fractions to be assigned to these classes. The operational procedure used by the MODIS Science Team assumes that confident clear and probably clear IFOVs are cloud-free (cloud fraction 0 %), while the remaining categories are completely filled with clouds (cloud fraction 100 %). This study demonstrates that thi

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Grabowski, Wojciech W. "Representation of Turbulent Mixing and Buoyancy Reversal in Bulk Cloud Models." Journal of the Atmospheric Sciences 64, no. 10 (2007): 3666–80. http://dx.doi.org/10.1175/jas4047.1.

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Abstract This paper discusses the representation of subgrid-scale turbulent mixing in bulk models of warm (ice free) clouds, which assume instantaneous adjustment to grid-scale saturation. This is a reasonable assumption for condensation of water vapor because supersaturations inside clouds are typically small (∼0.1% or smaller), except near cloud bases where about an order of magnitude larger supersaturations are anticipated. For the cloud evaporation, however, instantaneous adjustment to grid-scale saturation is questionable, especially when evaporation occurs as a result of turbulent mixing

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Zuidema, P., B. Baker, Y. Han, et al. "An Arctic Springtime Mixed-Phase Cloudy Boundary Layer Observed during SHEBA." Journal of the Atmospheric Sciences 62, no. 1 (2005): 160–76. http://dx.doi.org/10.1175/jas-3368.1.

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Abstract The microphysical characteristics, radiative impact, and life cycle of a long-lived, surface-based mixed-layer, mixed-phase cloud with an average temperature of approximately −20°C are presented and discussed. The cloud was observed during the Surface Heat Budget of the Arctic experiment (SHEBA) from 1 to 10 May 1998. Vertically resolved properties of the liquid and ice phases are retrieved using surface-based remote sensors, utilize the adiabatic assumption for the liquid component, and are aided by and validated with aircraft measurements from 4 and 7 May. The cloud radar ice microp

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Jones, David. "Cloud-chamber clouds." Nature 417, no. 6891 (2002): 808. http://dx.doi.org/10.1038/417808a.

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Di Natale, Gianluca, Giovanni Bianchini, Massimo Del Guasta, et al. "Characterization of the Far Infrared Properties and Radiative Forcing of Antarctic Ice and Water Clouds Exploiting the Spectrometer-LiDAR Synergy." Remote Sensing 12, no. 21 (2020): 3574. http://dx.doi.org/10.3390/rs12213574.

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Optical and microphysical cloud properties are retrieved from measurements acquired in 2013 and 2014 at the Concordia base station in the Antarctic Plateau. Two sensors are used synergistically: a Fourier transform spectroradiometer named REFIR-PAD (Radiation Explorer in Far Infrared-Prototype for Applications and Developments) and a backscattering-depolarization LiDAR. First, in order to identify the cloudy scenes and assess the cloud thermodynamic phase, the REFIR-PAD spectral radiances are ingested by a machine learning algorithm called Cloud Identification and Classification (CIC). For eac

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