Journal articles on the topic 'Clouds'
To see the other types of publications on this topic, follow the link: Clouds.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Clouds.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
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 (March 28, 2008): 6379–407. http://dx.doi.org/10.5194/acpd-8-6379-2008.
Full textAbstract:
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 incur errors in the calculated radiative forcing. The nature of small cumulus cloud size distributions suggests that at any resolution, a significant fraction of the clouds are missed, and their optical properties are relegated to the apparent cloud-free optical properties. At the same time, the cloudy portion incorporates significant contribution from non-cloudy pixels. We show that the largest contribution to the total cloud reflectance comes from the smallest clouds and that the spatial resolution changes the apparent energy flux of a broken cloudy scene. When changing the resolution from 30 m to 1 km (Landsat to MODIS) the average "cloud-free" reflectance at 1.65 μm increases more than 25%, the cloud reflectance decreases by half, and the cloud coverage doubles, resulting in an important impact on climate forcing estimations. The apparent aerosol forcing is on the order of 0.5 to 1 Wm−2 per cloud field.
2
Korshunova, N. N., and T. V. Dementieva . "Changes in cloud characteristics on the territory of Russia." Hydrometeorological research and forecasting 3 (September 30, 2023): 139–51. http://dx.doi.org/10.37162/2618-9631-2023-3-139-151.
Full textAbstract:
Such characteristics of the cloud cover as the frequency of cloudy (8-10/10) and clear (0-2/10) sky are investigated. The analysis of the seasonal frequency of these characteristics revealed some regional features. To be included in the national cloud monitoring system, the normals for the new base period of 1991-2020 for the average amount of total and low-level clouds, the frequency of cases with different sky conditions (clear, semi-cloudy, cloudy) for total and low-level clouds, as well as the frequency of various forms of clouds were calculated. Long-term changes in the frequency of clear and cloudy sky are analyzed, which revealed an almost universal decrease in the frequency of clear sky for the total cloud cover in all seasons. Keywords: total cloud cover, low-level clouds, cloud forms, cloudy sky, clear sky All-R
3
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 (July 21, 2008): 3855–64. http://dx.doi.org/10.5194/acp-8-3855-2008.
Full textAbstract:
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 incur errors in the calculated radiative forcing. The nature of small cumulus cloud size distributions suggests that at any resolution, a significant fraction of the clouds are missed, and their optical properties are relegated to the apparent cloud-free optical properties. At the same time, the cloudy portion incorporates significant contribution from non-cloudy pixels. We show that the largest contribution to the total cloud reflectance comes from the smallest clouds and that the spatial resolution changes the apparent energy flux of a broken cloudy scene. When changing the resolution from 30 m to 1 km (Landsat to MODIS) the average "cloud-free" reflectance at 1.65 μm increases from 0.0095 to 0.0115 (>20%), the cloud reflectance decreases from 0.13 to 0.066 (~50%), and the cloud coverage doubles, resulting in an important impact on climate forcing estimations. The apparent aerosol forcing is on the order of 0.5 to 1 Wm−2 per cloud field.
4
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 (December 12, 2018): 2016. http://dx.doi.org/10.3390/rs10122016.
Full textAbstract:
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 variability index, albeit having a better physical foundation, is used. The analysis is conducted for different cloud conditions and solar elevations. It is found that under cloudy-sky conditions, there is less attenuation under water clouds than those under opaque ice clouds (optically thick ice clouds) and multilayered clouds. For cloud layers, less attenuation was found for the low/mid layers than for the high layer. Cloud enhancement occurs more frequently for water clouds and less frequently for mixed phase and cirrus clouds and it occurs with similar frequency at all three levels. The temporal variability of solar attenuation is found to decrease with an increasing temporal sampling interval and to be largest for water clouds and smallest for multilayered and partly cloudy conditions. This work presents a first step towards estimating solar energy potential in the San Antonio area indirectly using available estimates of cloudiness from GOES satellites.
5
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.
Full textAbstract:
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 difference between cloudy and cloud-free images (i.e. clouds). Last, a generator (G) is used to fill in the different regions in cloud image in order to confuse the discriminator. Auto-GAN only requires images and their labels (1 for a cloud-free image, 0 for a cloudy image) in the training phase which is more time-saving to acquire than existing methods based on CNNs that require pixel-level labels. Auto-GAN is applied to cloud detection in Sentinel-2A Level 1C imagery. The results indicate that Auto-GAN method performs well in cloud detection over different land surfaces.
6
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.
Full textAbstract:
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 50% relative to fully clear days. Mean afternoon A was significantly lower on fully cloudy days relative to days with afternoon clouds only or no clouds in both species. Notably, A did not differ during afternoon cloud days relative to clear afternoons. Afternoon clouds significantly reduced transpiration (E) in C. leptosepala relative to clear days, and both species showed mean reductions in plant water stress (i.e. higher Ψ), though this difference was not significant. Water use efficiency (WUE) (A/E) decreased from morning to afternoon, especially on cloudy days, and the presence of clouds had a positive effect on the light reactions of photosynthesis based on fluorescence measurements (Fv′/Fm′), in both species. Cloudy days were characterised by higher Fv/Fm than afternoon clouds and clear days during both the morning and the afternoon (especially for A. parryi) and recovery to near pre-dawn values for cloudy and afternoon cloud day types, but not clear days. Overall, similar ecophysiological advantages of this typical afternoon cloud pattern was apparent in both species, although their spatial microsite differences related to winter snow accumulation may also play an important role.
7
Balmes, Kelly, and Qiang Fu. "An Investigation of Optically Very Thin Ice Clouds from Ground-Based ARM Raman Lidars." Atmosphere 9, no. 11 (November 14, 2018): 445. http://dx.doi.org/10.3390/atmos9110445.
Full textAbstract:
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 optical depths greater than 0.01. The temporal structure of RL-observed optically very thin ice clouds indicates a clear sky–cloud continuum. Global cloudiness estimates from CALIPSO observations leveraged with high-sensitivity RL observations suggest that CALIPSO may underestimate the global cloud fraction when considering optically very thin ice clouds.
8
Schulte, Richard M., Matthew D. Lebsock, and John M. Haynes. "What CloudSat cannot see: liquid water content profiles inferred from MODIS and CALIOP observations." Atmospheric Measurement Techniques 16, no. 14 (July 25, 2023): 3531–46. http://dx.doi.org/10.5194/amt-16-3531-2023.
Full textAbstract:
Abstract. Single-layer nonprecipitating warm clouds are integral to Earth's climate, and accurate estimates of cloud liquid water content for these clouds are critical for constraining cloud models and understanding climate feedbacks. As the only cloud-sensitive radar currently in space, CloudSat provides very important cloud-profiling capabilities. However, a significant fraction of clouds is missed by CloudSat because they are either too thin or too close to the Earth's surface. We find that the CloudSat Radar-Visible Optical Depth Cloud Water Content Product, 2B-CWC-RVOD, misses about 73 % of nonprecipitating liquid cloudy pixels and about 63 % of total nonprecipitating liquid cloud water content compared to coincident Moderate Resolution Imaging Spectroradiometer (MODIS) observations. Those percentages increase to 84 % and 69 %, respectively, if MODIS “partly cloudy” pixels are included. We develop a method, based on adiabatic parcel theory but modified to account for the fact that observed clouds are often subadiabatic, to estimate profiles of cloud liquid water content based on MODIS observations of cloud-top effective radius and cloud optical depth combined with lidar observations of cloud-top height. We find that, for cloudy pixels that are detected by CloudSat, the resulting subadiabatic profiles of cloud water are similar to what is retrieved from CloudSat. For cloudy pixels that are not detected by CloudSat, the subadiabatic profiles can be used to supplement the CloudSat profiles, recovering much of the missing cloud water and generating realistic-looking merged profiles of cloud water. Adding this missing cloud water to the CWC-RVOD product increases the mean cloud liquid water path by 228 % for single-layer nonprecipitating warm clouds. This method will be included in a subsequent reprocessing of the 2B-CWC-RVOD algorithm.
9
Su, Tianning, Youtong Zheng, and Zhanqing Li. "Methodology to determine the coupling of continental clouds with surface and boundary layer height under cloudy conditions from lidar and meteorological data." Atmospheric Chemistry and Physics 22, no. 2 (January 27, 2022): 1453–66. http://dx.doi.org/10.5194/acp-22-1453-2022.
Full textAbstract:
Abstract. The states of coupling between clouds and surface or boundary layer have been investigated much more extensively for marine stratocumulus clouds than for continental low clouds, partly due to more complex thermodynamic structures over land. A manifestation is a lack of robust remote sensing methods to identify coupled and decoupled clouds over land. Following the idea for determining cloud coupling over the ocean, we have generalized the concept of coupling and decoupling to low clouds over land, based on potential temperature profiles. Furthermore, by using ample measurements from lidar and a suite of surface meteorological instruments at the U.S. Department of Energy's Atmospheric Radiation Measurement Program's Southern Great Plains site from 1998 to 2019, we have developed a method to simultaneously retrieve the planetary boundary layer (PBL) height (PBLH) and coupled states under cloudy conditions during the daytime. The new lidar-based method relies on the PBLH, the lifted condensation level, and the cloud base to diagnose the cloud coupling. The coupled states derived from this method are highly consistent with those derived from radiosondes. Retrieving the PBLH under cloudy conditions, which has been a persistent problem in lidar remote sensing, is resolved in this study. Our method can lead to high-quality retrievals of the PBLH under cloudy conditions and the determination of cloud coupling states. With the new method, we find that coupled clouds are sensitive to changes in the PBL with a strong diurnal cycle, whereas decoupled clouds and the PBL are weakly related. Since coupled and decoupled clouds have distinct features, our new method offers an advanced tool to separately investigate them in climate systems.
10
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 (April 1, 2008): 501–18. http://dx.doi.org/10.1175/2007jtecha1004.1.
Full textAbstract:
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, smoke, volcanic ash, and industrial pollution over both land and ocean backgrounds in global datasets collected by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. This new methodology relies strongly upon data collected in the 0.412-μm bandpass, where smoke has a maximum reflectance in the VIIRS bands while dust simultaneously has a minimum reflectance. The procedures benefit from the VIIRS design, which is dual gain in this band, to avoid saturation in cloudy conditions. These new procedures also exploit other information available from the VIIRS cloud mask algorithm in addition to cloud confidence, including the phase of each cloudy pixel, which is critical to identify water clouds and restrict the use of spectral tests that would misclassify ice clouds as heavy aerosols. Comparisons between results from these new procedures, automated cloud analyses from VIIRS heritage algorithms, manually generated analyses, and MODIS imagery show the effectiveness of the new procedures and suggest that it is feasible to identify and distinguish between clouds and heavy aerosols in a single cloud mask algorithm.
11
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 (January 1, 2005): 3–17. http://dx.doi.org/10.1175/jtech-1681.1.
Full textAbstract:
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 properties of clouds for partially covered imager fields of view. The partly cloudy pixel retrieval scheme is applicable to single-layered cloud systems and invokes the assumption that clouds that only partially cover a field of view are at the same altitude as nearby clouds from the same layer that completely cover imager pixels. The properties of the retrieval are illustrated through its application to 2-km Visible and Infrared Scanner (VIRS) data from the Tropical Rainfall Measuring Mission (TRMM) for a marine stratocumulus scene. The scene was chosen because the cloud properties are typical of such systems based on an analysis of VIRS data for February and March 1998. Comparisons of properties for clouds in partly cloudy pixels and those for clouds in nearby overcast pixels reveal that the optical depths and droplet effective radii are generally smaller for the clouds in the partly cloudy pixels. In addition, for pixel-scale cloud fractions between 0.2 and 0.8, optical depth, droplet effective radius, and column droplet number concentration decrease slowly with decreasing cloud cover fraction. The changes are only about 20%–30%, while cloud cover fraction changes by 80%. For comparison, changes in optical depth and column number concentration retrieved using a threshold method decrease by 80%–90%. As long as the cloud cover in partly cloudy pixels is greater than about 0.1, uncertainties in the estimates of the cloud altitudes and of the radiances for the cloud-free portions of the fields of view give rise to uncertainties in the retrieved cloud properties that are comparable to the uncertainties in the properties retrieved for overcast pixels.
12
Gielen, C., M. Van Roozendael, F. Hendrick, G. Pinardi, T. Vlemmix, V. De Bock, H. De Backer, et al. "A simple and versatile cloud-screening method for MAX-DOAS retrievals." Atmospheric Measurement Techniques 7, no. 10 (October 13, 2014): 3509–27. http://dx.doi.org/10.5194/amt-7-3509-2014.
Full textAbstract:
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 instances of high aerosol optical depth (AOD) and high cloud optical depth (COD). We apply our cloud screening to MAX-DOAS (multi-axis DOAS) retrievals at three different sites with different typical meteorological conditions, more specifically suburban Beijing (39.75° N, 116.96° E), Brussels (50.78° N, 4.35° E) and Jungfraujoch (46.55° N, 7.98° E). We find that our cloud screening performs well characterizing the different sky conditions. The flags based on the colour index are able to detect changes in visibility due to aerosols and/or (scattered) clouds. The O4-based multiple-scattering flag is able to detect optically thick clouds, and is needed to correctly identify clouds for sites with extreme aerosol pollution. Removing data taken under cloudy conditions results in a better agreement, in both correlation and slope, between the MAX-DOAS AOD retrievals and measurements from other co-located instruments.
13
Gielen, C., M. Van Roozendael, F. Hendrick, G. Pinardi, T. Vlemmix, V. De Bock, H. De Backer, et al. "A simple and versatile cloud-screening method for MAX-DOAS retrievals." Atmospheric Measurement Techniques Discussions 7, no. 6 (June 12, 2014): 5883–920. http://dx.doi.org/10.5194/amtd-7-5883-2014.
Full textAbstract:
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 of high aerosol optical depth (AOD) and high cloud optical depth (COD). We apply our cloud screening to MAX-DOAS (multi-axis DOAS) retrievals at three different sites with different typical meteorological conditions, more specifically suburban Beijing (39.75° N, 116.96° E), Brussels (50.78° N, 4.35° E) and Jungfraujoch (46.55° N, 7.98° E). We find that our cloud screening performs well characterizing the different sky conditions. The flags based on the colour index are able to detect changes in visibility due to aerosols and/or (scattered) clouds. The O4-based multiple-scattering flag is able to detect optically thick clouds, and is needed to correctly identify clouds for sites with extreme aerosol pollution. Removing data taken under cloudy conditions results in a better agreement, in both correlation and slope, between the AOD retrievals and measurements from other co-located instruments.
14
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 (August 6, 2013): 6000–6014. http://dx.doi.org/10.1175/jcli-d-12-00646.1.
Full textAbstract:
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. On average, the temperatures from cloudy retrieval are about 0.5–1.0 K warmer than the GPS RO wet retrieval, except for the altitudes near the nimbostratus base. The differences of temperature between the two methods are largest in summer and smallest in winter. The lapse rate in altostratus clouds is around 6.5°–7.5°C km−1 and does not vary greatly with height. On the contrary, the lapse rate increases significantly with height in nimbostratus clouds, from about 2.5°–3.5°C km−1 near the cloud base to about 5.0°–6.0°C km−1 at cloud center and 6.5°–7.5°C km−1 below the cloud top. Seasonal variability of lapse rate derived from the cloudy retrieval is larger than that derived from the wet retrieval. The lapse rate within clouds is smaller in summer and larger in winter. The mean lapse rate decreases with temperature in all seasons.
15
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 (October 1, 2009): 2169–80. http://dx.doi.org/10.1175/2009jamc2238.1.
Full textAbstract:
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 and MODIS retrieve larger fractions of water clouds in the single-layer cases than in the top-layer cases, demonstrating that focusing on only single-layer clouds may introduce a water-cloud bias. Of the single-layer clouds, 60% are transparent and 40% are opaque (defined by the lack of a CALIOP ground return). MODIS tends to classify single-layer clouds with midlayer temperatures below −40°C as ice; around −30°C nearly equally as ice, mixed, and unknown; between −28° and −15°C as mixed; and above 0°C as water. Ninety-five percent of the single-layer CALIOP clouds not detected by MODIS are transparent. Approximately ⅓ of transparent single-layer clouds with temperatures below −30°C are not detected by MODIS and close to another ⅓ are classified as ice, with the rest assigned as water, mixed, or unknown. CALIOP classes nearly all of these transparent cold clouds as ice.
16
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 (September 1, 2008): 2405–22. http://dx.doi.org/10.1175/2008jamc1845.1.
Full textAbstract:
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 with observations is poor. The vertical distribution of cloud water is distinctly different among the different models; some common features also appear. Most models underestimate the presence of high clouds, and, although the observed preference for low clouds in the Arctic is present in most of the models, the modeled low clouds are too thin and are displaced downward. Practically all models show a preference to locate the lowest cloud base at the lowest model grid point. In some models this happens also to be where the observations show the highest occurrence of the lowest cloud base; it is not possible to determine if this result is just a coincidence. Different factors contribute to model surface radiation errors. For longwave radiation in summer, a negative bias is present both for cloudy and clear conditions, and intermodel differences are smaller when clouds are present. There is a clear relationship between errors in cloud-base temperature and radiation errors. In winter, in contrast, clear-sky cases are modeled reasonably well, but cloudy cases show a very large intermodel scatter with a significant bias in all models. This bias likely results from a complete failure in all of the models to retain liquid water in cold winter clouds. All models overestimate the cloud attenuation of summer solar radiation for thin and intermediate clouds, and some models maintain this behavior also for thick clouds.
17
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 (May 30, 2022): 6879–98. http://dx.doi.org/10.5194/acp-22-6879-2022.
Full textAbstract:
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 quantify the cloud cover from a cloud-free perspective. Using well-known radiative transfer relations we retrieve the cloud-free contribution in high-resolution satellite observations of trade cumulus cloud fields during EUREC4A. Knowing the cloud-free part, we can investigate the remaining cloud-related contributions consisting of areas detected by common cloud-masking algorithms and undetected areas related to optically thin clouds. We find that the cloud-mask cloud cover underestimates the total cloud cover by 33 %. Aircraft lidar measurements support our findings by showing a high abundance of optically thin clouds during EUREC4A. Mixing the undetected optically thin clouds into the cloud-free signal can cause an underestimation of the cloud radiative effect of up to −7.5 %. We further discuss possible artificial correlations in aerosol–cloud cover interaction studies that might arise from undetected optically thin low clouds. Our analysis suggests that the known underestimation of trade wind cloud cover and simultaneous overestimation of cloud brightness in models are even higher than assumed so far.
18
Witte, M. K., P. Y. Chuang, and G. Feingold. "On clocks and clouds." Atmospheric Chemistry and Physics Discussions 13, no. 9 (September 6, 2013): 23461–90. http://dx.doi.org/10.5194/acpd-13-23461-2013.
Full textAbstract:
Abstract. Cumulus clouds exhibit a life cycle that consists of: (a) the growth phase (increasing size, most notably in the vertical direction); (b) the mature phase (growth ceases; any precipitation that develops is strongest during this period); and (c) the dissipation phase (cloud dissipates because of precipitation and/or entrainment; no more dynamical support). Although radar can track clouds over time and give some sense of the age of a cloud, most aircraft in situ measurements lack temporal context. We use large eddy simulations of trade wind cumulus cloud fields from cases during the Barbados Oceanographic and Meteorological Experiment (BOMEX) and Rain In Cumulus over the Ocean (RICO) campaigns to demonstrate a potential cumulus cloud "clock". We find that the volume-averaged total water mixing ratio rt is a useful cloud clock for the 12 clouds studied. A cloud's initial rt is set by the subcloud mixed-layer mean rt and decreases monotonically from the initial value due primarily to entrainment. The clock is insensitive to aerosol loading, environmental sounding and extrinsic cloud properties such as lifetime and volume. In some cases (more commonly for larger clouds), multiple pulses of buoyancy occur, which complicate the cumulus clock by replenishing rt. The clock is most effectively used to classify clouds by life phase.
19
Witte, M. K., P. Y. Chuang, and G. Feingold. "On clocks and clouds." Atmospheric Chemistry and Physics 14, no. 13 (July 3, 2014): 6729–38. http://dx.doi.org/10.5194/acp-14-6729-2014.
Full textAbstract:
Abstract. Cumulus clouds exhibit a life cycle that consists of (a) the growth phase (increasing size, most notably in the vertical direction); (b) the mature phase (growth ceases; any precipitation that develops is strongest during this period); and (c) the dissipation phase (cloud dissipates because of precipitation and/or entrainment; no more dynamical support). Although radar can track clouds over time and give some sense of the age of a cloud, most aircraft in situ measurements lack temporal context. We use large eddy simulations of trade wind cumulus cloud fields from cases during the Barbados Oceanographic and Meteorological Experiment (BOMEX) and Rain In Cumulus over the Ocean (RICO) campaigns to demonstrate a potential cumulus cloud "clock." We find that the volume-averaged total water mixing ratio rt is a useful cloud clock for the 12 clouds studied. A cloud's initial rt is set by the subcloud mixed-layer mean rt and decreases monotonically from the initial value due primarily to entrainment. The clock is insensitive to aerosol loading, environmental sounding and extrinsic cloud properties such as lifetime and volume. In some cases (more commonly for larger clouds), multiple pulses of buoyancy occur, which complicate the cumulus clock by replenishing rt. The clock is most effectively used to classify clouds by life phase.
20
Lei, Siliang, Xijuan Zhu, Yuxiang Ling, Shiwen Teng, and Bin Yao. "Tropical Tropopause Layer Cloud Properties from Spaceborne Active Observations." Remote Sensing 15, no. 5 (February 22, 2023): 1223. http://dx.doi.org/10.3390/rs15051223.
Full textAbstract:
A significant part of clouds in the tropics appears over the tropopause due to intense convections and in situ condensation activity. These tropical tropopause layer (TTL) clouds not only play an important role in the radiation budget over the tropics, but also in water vapor and other chemical material transport from the troposphere to the stratosphere. This study quantifies and analyzes the properties of TTL clouds based on spaceborne active observations, which provide one of the most reliable sources of information on cloud vertical distributions. We use four years (2007–2010) of observations from the joint Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat and consider all cloudy pixels with top height above the tropopause as TTL clouds. The occurrence frequency of TTL clouds during the nighttime is found to be almost 13% and can reach ~50–60% in areas with frequent convections. The annual averages of tropical tropopause height, tropopause temperature, and cloud top height are 16.2 km, −80.7 °C, and 16.6 km, respectively, and the average cloud top exceeds tropopause by approximately 500 m. More importantly, the presence of TTL clouds causes tropopause temperature to be ~3–4 °C colder than in the all-sky condition. It also lifts the tropopause heights ~160 m during the nighttime and lowers the heights ~84 m during the daytime. From a cloud type aspect, ~91% and ~4% of the TTL clouds are high clouds and altostratus, and only ~5% of them are associated with convections (i.e., nimbostratus and deep convective clouds). Approximately 30% of the TTL clouds are single-layer clouds, and multi-layer clouds are dominated by those with 2–3 separated layers.
21
Shikwambana, Lerato, and Venkataraman Sivakumar. "Observation of Clouds Using the CSIR Transportable LIDAR: A Case Study over Durban, South Africa." Advances in Meteorology 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/4184512.
Full textAbstract:
The Council for Scientific and Industrial Research (CSIR) transportable Light Detection And Ranging (LIDAR) was used to collect data over Durban (29.9°S, 30.9°E) during 20–23 November 2012. Aerosol measurements have been carried out in the past over Durban; however, no cloud measurements using LIDAR have ever been performed. Therefore, this study further motivates the continuation of LIDAR for atmospheric research over Durban. Low level clouds were observed on 20–22 November 2012 and high level clouds were observed on 23 November 2012. The low level cloud could be classified as stratocumulus clouds, whereas the high level clouds could be classified as cirrus clouds. Low level cloud layers showed high extinction coefficients values ranging between 0.0009 and 0.0044 m−1, whereas low extinction coefficients for high level clouds were observed at values ranging between 0.000001 and 0.000002 m−1. Optical depth showed a high variability for 20 and 21 November 2012. This indicates a change in the composition and/or thickness of the cloud. For 22 and 23 November 2012, almost similar values of optical depth were observed. Cloud-Aerosol LIDAR and Infrared Pathfinder Satellite Observations (CALIPSO) revealed high level clouds while the CSIR LIDAR could not. However, the two instruments complement each other well to describe the cloudy condition.
22
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 (March 30, 2010): 8247–96. http://dx.doi.org/10.5194/acpd-10-8247-2010.
Full textAbstract:
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 75% over land. Global cloud amount has been estimated as about 66% to 74%, depending on the weighting of not cloudy AIRS footprints by partial cloud cover (0 or 0.3). 40% of all clouds are high clouds, and about 44% of all clouds are single layer low-level clouds. The "radiative" cloud height determined by the AIRS-LMD retrieval corresponds well to the height of the maximum backscatter signal and of the "apparent middle" of the cloud. Whereas the real cloud thickness of high opaque clouds often fills the whole troposphere, their "apparent" cloud thickness (at which optical depth reaches about 5) is on average only 2.5 km. The real geometrical thickness of optically thin cirrus as identified by AIRS-LMD is identical to the "apparent" cloud thickness with an average of about 2.5 km in the tropics and midlatitudes. High clouds in the tropics have slightly more diffusive cloud tops than at higher latitudes. In general, the depth of the maximum backscatter signal increases nearly linearly with increasing "apparent" cloud thickness. For the same "apparent" cloud thickness optically thin cirrus show a maximum backscatter about 10% deeper inside the cloud than optically thicker clouds. We also show that only the geometrically thickest opaque clouds and (the probably surrounding anvil) cirrus penetrate the stratosphere in the tropics.
23
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 (August 6, 2010): 7197–214. http://dx.doi.org/10.5194/acp-10-7197-2010.
Full textAbstract:
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 ocean and about 75% over land. Global cloud amount has been estimated from 66% to 74%, depending on the weighting of not cloudy AIRS footprints by partial cloud cover from 0 to 0.3. 42% of all clouds are high clouds, and about 42% of all clouds are single layer low-level clouds. The "radiative" cloud height determined by the AIRS-LMD retrieval corresponds well to the height of the maximum backscatter signal and of the "apparent middle" of the cloud. Whereas the real cloud thickness of high opaque clouds often fills the whole troposphere, their "apparent" cloud thickness (at which optical depth reaches about 5) is on average only 2.5 km. The real geometrical thickness of optically thin cirrus as identified by AIRS-LMD is identical to the "apparent" cloud thickness with an average of about 2.5 km in the tropics and midlatitudes. High clouds in the tropics have slightly more diffusive cloud tops than at higher latitudes. In general, the depth of the maximum backscatter signal increases nearly linearly with increasing "apparent" cloud thickness. For the same "apparent" cloud thickness optically thin cirrus show a maximum backscatter about 10% deeper inside the cloud than optically thicker clouds. We also show that only the geometrically thickest opaque clouds and (the probably surrounding anvil) cirrus penetrate the stratosphere in the tropics.
24
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 (May 1, 2006): 1765–83. http://dx.doi.org/10.1175/jcli3710.1.
Full textAbstract:
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 (>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 and precision infrared radiometer measurements with uncertainties of ∼10 W m−2. The annual averages of total and single-layered low-, middle-, and high-cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total- and low-cloud amounts peak during January and February and reach a minimum during July and August; high clouds occur more frequently than other types of clouds with a peak in summer. The average annual downwelling surface SW fluxes for total and low clouds (151 and 138 W m−2, respectively) are less than those under middle and high clouds (188 and 201 W m−2, respectively), but the downwelling LW fluxes (349 and 356 W m−2) underneath total and low clouds are greater than those from middle and high clouds (337 and 333 W m−2). Low clouds produce the largest LW warming (55 W m−2) and SW cooling (−91 W m−2) effects with maximum and minimum absolute values in spring and summer, respectively. High clouds have the smallest LW warming (17 W m−2) and SW cooling (−37 W m−2) effects at the surface. All-sky SW cloud radiative forcing (CRF) decreases and LW CRF increases with increasing cloud fraction with mean slopes of −0.984 and 0.616 W m−2 %−1, respectively. Over the entire diurnal cycle, clouds deplete the amount of surface insolation more than they add to the downwelling LW flux. The calculated CRFs do not appear to be significantly affected by uncertainties in data sampling and clear-sky screening. Traditionally, cloud radiative forcing includes not only the radiative impact of the hydrometeors, but also the changes in the environment. Taken together over the ARM SCF, changes in humidity and surface albedo between clear and cloudy conditions offset ∼20% of the NET radiative forcing caused by the cloud hydrometeors alone. Variations in water vapor, on average, account for 10% and 83% of the SW and LW CRFs, respectively, in total cloud cover conditions. The error analysis further reveals that the cloud hydrometeors dominate the SW CRF, while water vapor changes are most important for LW flux changes in cloudy skies. Similar studies over other locales are encouraged where water and surface albedo changes from clear to cloudy conditions may be much different than observed over the ARM SCF.
25
Marinou, Eleni, Kalliopi Artemis Voudouri, Ioanna Tsikoudi, Eleni Drakaki, Alexandra Tsekeri, Marco Rosoldi, Dragos Ene, et al. "Geometrical and Microphysical Properties of Clouds Formed in the Presence of Dust above the Eastern Mediterranean." Remote Sensing 13, no. 24 (December 9, 2021): 5001. http://dx.doi.org/10.3390/rs13245001.
Full textAbstract:
In this work, collocated lidar–radar observations are used to retrieve the vertical profiles of cloud properties above the Eastern Mediterranean. Measurements were performed in the framework of the PRE-TECT experiment during April 2017 at the Greek atmospheric observatory of Finokalia, Crete. Cloud geometrical and microphysical properties at different altitudes were derived using the Cloudnet target classification algorithm. We found that the variable atmospheric conditions that prevailed above the region during April 2017 resulted in complex cloud structures. Mid-level clouds were observed in 38% of the cases, high or convective clouds in 58% of the cases, and low-level clouds in 2% of the cases. From the observations of cloudy profiles, pure ice phase occurred in 94% of the cases, mixed-phase clouds were observed in 27% of the cases, and liquid clouds were observed in 8.7% of the cases, while Drizzle or rain occurred in 12% of the cases. The significant presence of Mixed-Phase Clouds was observed in all the clouds formed at the top of a dust layer, with three times higher abundance than the mean conditions (26% abundance at −15 °C). The low-level clouds were formed in the presence of sea salt and continental particles with ice abundance below 30%. The derived statistics on clouds’ high-resolution vertical distributions and thermodynamic phase can be combined with Cloudnet cloud products and lidar-retrieved aerosol properties to study aerosol-cloud interactions in this understudied region and evaluate microphysics parameterizations in numerical weather prediction and global climate models.
26
Zhao, Xiaoyi, Kristof Bognar, Vitali Fioletov, Andrea Pazmino, Florence Goutail, Luis Millán, Gloria Manney, Cristen Adams, and Kimberly Strong. "Assessing the impact of clouds on ground-based UV–visible total column ozone measurements in the high Arctic." Atmospheric Measurement Techniques 12, no. 4 (April 18, 2019): 2463–83. http://dx.doi.org/10.5194/amt-12-2463-2019.
Full textAbstract:
Abstract. Zenith-Sky scattered light Differential Optical Absorption Spectroscopy (ZS-DOAS) has been used widely to retrieve total column ozone (TCO). ZS-DOAS measurements have the advantage of being less sensitive to clouds than direct-sun measurements. However, the presence of clouds still affects the quality of ZS-DOAS TCO. Clouds are thought to be the largest contributor to random uncertainty in ZS-DOAS TCO, but their impact on data quality still needs to be quantified. This study has two goals: (1) to investigate whether clouds have a significant impact on ZS-DOAS TCO, and (2) to develop a cloud-screening algorithm to improve ZS-DOAS measurements in the Arctic under cloudy conditions. To quantify the impact of weather, 8 years of measured and modelled TCO have been used, along with information about weather conditions at Eureka, Canada (80.05∘ N, 86.41∘ W). Relative to direct-sun TCO measurements by Brewer spectrophotometers and modelled TCO, a positive bias is found in ZS-DOAS TCO measured in cloudy weather, and a negative bias is found for clear conditions, with differences of up to 5 % between clear and cloudy conditions. A cloud-screening algorithm is developed for high latitudes using the colour index calculated from ZS-DOAS spectra. The quality of ZS-DOAS TCO datasets is assessed using a statistical uncertainty estimation model, which suggests a 3 %–4 % random uncertainty. The new cloud-screening algorithm reduces the random uncertainty by 0.6 %. If all measurements collected during cloudy conditions, as identified using the weather station observations, are removed, the random uncertainty is reduced by 1.3 %. This work demonstrates that clouds are a significant contributor to uncertainty in ZS-DOAS TCO and proposes a method that can be used to screen clouds in high-latitude spectra.
27
Chou, Ming-Dah, Kyu-Tae Lee, Si-Chee Tsay, and Qiang Fu. "Parameterization for Cloud Longwave Scattering for Use in Atmospheric Models." Journal of Climate 12, no. 1 (January 1, 1999): 159–69. http://dx.doi.org/10.1175/1520-0442-12.1.159.
Full textAbstract:
Abstract A parameterization for the scattering of thermal infrared (longwave) radiation by clouds has been developed based on discrete-ordinate multiple-scattering calculations. The effect of backscattering is folded into the emission of an atmospheric layer and the absorption between levels by scaling the cloud optical thickness. The scaling is a function of the single-scattering albedo and asymmetry factor. For wide ranges of cloud particle size, optical thickness, height, and atmospheric conditions, flux errors induced by the parameterization are small. They are <4 W m−2 (2%) in the upward flux at the top of the atmosphere and <2 W m−2 (1%) in the downward flux at the surface. Compared to the case that scattering by clouds is neglected, the flux errors are more than a factor of 2 smaller. The maximum error in cooling rate is ≈8%, which occurs at the top of clouds, as well as at the base of high clouds where the difference between the cloud and surface temperatures is large. With the scaling approximation, radiative transfer equations for a cloudy atmosphere are identical with those for a clear atmosphere, and the difficulties in applying a multiple-scattering algorithm to a partly cloudy atmosphere (assuming homogeneous clouds) are avoided. The computational efficiency is practically the same as that for a clear atmosphere. The parameterization represents a significant reduction in one source of the errors involved in the calculation of longwave cooling in cloudy atmospheres.
28
Dinh, Tra, and Stephan Fueglistaler. "Cirrus, Transport, and Mixing in the Tropical Upper Troposphere." Journal of the Atmospheric Sciences 71, no. 4 (March 27, 2014): 1339–52. http://dx.doi.org/10.1175/jas-d-13-0147.1.
Full textAbstract:
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 bimodal, with the first mode composed of trajectories that remain in the cloudy part of the domain during their passages from the lower to upper boundaries, and the second mode composed of the remaining trajectories that visit the cloud-free regions. For the first group of trajectories only, the mean age scales inversely with the time-mean radiative heating in cloudy air, and the one-dimensional advection–diffusion equation provides an adequate model for transport. However, the exchange between the cloudy and cloud-free regions renders the mean age over all trajectories (including those that visit the cloud-free region) much longer than the time expected if all air parcels remain in cloudy air. In addition, the overall mean age is not inversely proportional to the time-mean heating rate in cloudy air. Sensitivity calculations further show that the sizes, durations, and amplitudes of the individual clouds are also important to the transport time. The results show that the frequently used decomposition of radiative heating into clear-sky and cloud radiative heating may give incorrect interpretations regarding the time scale of transport into the stratosphere.
29
Sullivan, Colin H., L. M. Fissel, P. K. King, C.-Y. Chen, Z.-Y. Li, and J. D. Soler. "Characterizing the magnetic fields of nearby molecular clouds using submillimeter polarization observations." Monthly Notices of the Royal Astronomical Society 503, no. 4 (March 16, 2021): 5006–24. http://dx.doi.org/10.1093/mnras/stab596.
Full textAbstract:
ABSTRACT Of all the factors that influence star formation, magnetic fields are perhaps the least well understood. The goal of this paper is to characterize the 3D magnetic field properties of nearby molecular clouds through various methods of statistically analysing maps of polarized dust emission. Our study focuses on nine clouds, with data taken from the Planck Sky Survey as well as data from the Balloon-borne Large Aperture Submillimeter Telescope for Polarimetry observations of Vela C. We compare the distributions of polarization fraction (p), dispersion in polarization angles ($\mathcal {S}$), and hydrogen column density (NH) for each of our targeted clouds. To broaden the scope of our analysis, we compare the distributions of our clouds’ polarization observables with measurements from synthetic polarization maps generated from numerical simulations. We also use the distribution of polarization fraction measurements to estimate the inclination angle of each cloud’s cloud-scale magnetic field. We obtain a range of inclination angles associated with our clouds, varying from 16○ to 69○. We establish inverse correlations between p and both $\mathcal {S}$ and NH in almost every cloud, but we are unable to establish a statistically robust $\mathcal {S}$ versus NH trend. By comparing the results of these different statistical analysis techniques, we are able to propose a more comprehensive view of each cloud’s 3D magnetic field properties. These detailed cloud analyses will be useful in the continued studies of cloud-scale magnetic fields and the ways in which they affect star formation within these molecular clouds.
30
Lasota, Elżbieta, Witold Rohm, Chian-Yi Liu, and Paweł Hordyniec. "Cloud Detection from Radio Occultation Measurements in Tropical Cyclones." Atmosphere 9, no. 11 (October 25, 2018): 418. http://dx.doi.org/10.3390/atmos9110418.
Full textAbstract:
Tropical cyclones (TC) are one of the main producers of clouds in the tropics and subtropics. Hence, most of the clouds in TCs are dense, with large water and ice content, and provide conditions conducive to investigate clouds’ impact on Radio Occultation (RO) measurements. Although the RO technique is considered insensitive to clouds, recent studies show a refractivity positive bias in cloudy conditions. In this study, we analyzed the RO bending angle sensitivity to cloud content during tropical cyclone seasons between 2007 and 2010. Thermodynamic parameters were obtained from the ERA-Interim reanalysis, whereas the water and ice cloud contents were retrieved from the CloudSat profiles. Our experiments confirm the positive mean RO refractivity bias in cloudy conditions that reach up to more than 0.5% at the geometric height of around 7 km. A similar bias but larger and shifted up is visible in bending angle anomaly (1.6%). Our results reveal that the influence of clouds is significant and can exceed the RO bending angle standard deviation for 21 out of 50 (42%) investigated profiles. Mean clouds’ impact is detectable between 9.0 and 10.5 km, while, in the case of single events, clouds in most of the observations are significant between 8 and 14 km. Almost 15% of the detectable clouds reach 16 km height, while the influence of the clouds below 5 km is insignificant. For more than half of the significant cases, the detection range is less than 3 km but for one observation this range spreads to 7–8 km.
31
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 (September 19, 2019): 5039–54. http://dx.doi.org/10.5194/amt-12-5039-2019.
Full textAbstract:
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.
32
Sirch, Tobias, Luca Bugliaro, Tobias Zinner, Matthias Möhrlein, and Margarita Vazquez-Navarro. "Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants." Atmospheric Measurement Techniques 10, no. 2 (February 2, 2017): 409–29. http://dx.doi.org/10.5194/amt-10-409-2017.
Full textAbstract:
Abstract. A novel approach for the nowcasting of clouds and direct normal irradiance (DNI) based on the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellite is presented for a forecast horizon up to 120 min. The basis of the algorithm is an optical flow method to derive cloud motion vectors for all cloudy pixels. To facilitate forecasts over a relevant time period, a classification of clouds into objects and a weighted triangular interpolation of clear-sky regions are used. Low and high level clouds are forecasted separately because they show different velocities and motion directions. Additionally a distinction in advective and convective clouds together with an intensity correction for quickly thinning convective clouds is integrated. The DNI is calculated from the forecasted optical thickness of the low and high level clouds. In order to quantitatively assess the performance of the algorithm, a forecast validation against MSG/SEVIRI observations is performed for a period of 2 months. Error rates and Hanssen–Kuiper skill scores are derived for forecasted cloud masks. For a forecast of 5 min for most cloud situations more than 95 % of all pixels are predicted correctly cloudy or clear. This number decreases to 80–95 % for a forecast of 2 h depending on cloud type and vertical cloud level. Hanssen–Kuiper skill scores for cloud mask go down to 0.6–0.7 for a 2 h forecast. Compared to persistence an improvement of forecast horizon by a factor of 2 is reached for all forecasts up to 2 h. A comparison of forecasted optical thickness distributions and DNI against observations yields correlation coefficients larger than 0.9 for 15 min forecasts and around 0.65 for 2 h forecasts.
33
Lu, Shiming, Mingjun He, Shuangyan He, Shuo He, Yunhe Pan, Wenbin Yin, and Peiliang Li. "An Improved Cloud Masking Method for GOCI Data over Turbid Coastal Waters." Remote Sensing 13, no. 14 (July 10, 2021): 2722. http://dx.doi.org/10.3390/rs13142722.
Full textAbstract:
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 demonstrated that this improved method can identify the spatial positions and shapes of clouds more realistically, and more accurate pixels of turbid waters were retained. This improved method can be effectively applied in typical turbid coastal waters. It has potential to be used in cloud masking procedures of spaceborne ocean color sensors without short-wave infrared bands.
34
Newchurch, M. J., D. Sun, J. H. Kim, and X. Liu. "Tropical tropospheric ozone derived using Clear-Cloudy Pairs (CCP) of TOMS measurements." Atmospheric Chemistry and Physics Discussions 3, no. 1 (January 13, 2003): 225–52. http://dx.doi.org/10.5194/acpd-3-225-2003.
Full textAbstract:
Abstract. Using TOMS total-ozone measurements over high-altitude cloud locations and nearby paired clear locations, we describe the Clear-Cloudy Pairs (CCP) method for deriving tropical tropospheric ozone. The high-altitude clouds are identified by measured 380 nm reflectivities greater than 80% and Temperature Humidity InfraRed (THIR) measured cloud-top pressures less than 200 hPa. To account for locations without high-altitude clouds, we apply a zonal sine fitting to the stratospheric ozone derived from available cloudy points, resulting in a wave-one amplitude of about 4 DU. THIR data is unavailable after November 1984, so we extend the CCP method by using a reflectivity threshold of 90% to identify high-altitude clouds and remove the influence of high-reflectivity-but-low-altitude clouds with a lowpass frequency filter. We correct ozone retrieval errors associated with clouds, and ozone retrieval errors due to sun glint and aerosols. Comparing CCP results with Southern Hemisphere ADditional OZonesondes (SHADOZ) tropospheric ozone indicates that CCP tropospheric ozone and ozonesonde measurements are highly consistent. The most significant difference between CCP and ozonesonde tropospheric ozone can be explained by the low Total Ozone Mapping Spectrometer (TOMS) retrieval efficiency of ozone in the lower troposphere.
35
Tompkins, Adrian M., and Francesca Di Giuseppe. "An Interpretation of Cloud Overlap Statistics." Journal of the Atmospheric Sciences 72, no. 8 (August 1, 2015): 2877–89. http://dx.doi.org/10.1175/jas-d-14-0278.1.
Full textAbstract:
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 progressively below the typical cloud system scale. The postulate is supported by sampling artificial cyclic and subsequently more realistic fractal cloud scenes at various length scales. The fractal clouds indicate that the degree of minimal overlap diagnosed in previous studies for discontinuous clouds could result from sampling randomly overlapped clouds at spatial scales that are 30%–80% of the cloud system scale. Removing scenes with cloud cover exceeding 50% from the analysis reduces the impact of data truncation, with discontinuous clouds not minimally overlapped and the decorrelation of continuous clouds less sensitive to the sampling scale. Using CloudSat–CALIPSO data, a decorrelation length scale of approximately 4.0 km is found. In light of these results, the previously documented dependence of overlap decorrelation length scale on latitude is not entirely a physical phenomenon but can be reinterpreted as resulting from sampling cloud systems that increase significantly in size from the tropics to midlatitudes using a fixed sampling scale.
36
Yu, Haixiao, Jinji Ma, Safura Ahmad, Erchang Sun, Chao Li, Zhengqiang Li, and Jin Hong. "Three-Dimensional Cloud Structure Reconstruction from the Directional Polarimetric Camera." Remote Sensing 11, no. 24 (December 4, 2019): 2894. http://dx.doi.org/10.3390/rs11242894.
Full textAbstract:
Clouds affect radiation transmission through the atmosphere, which impacts the Earth’ s energy balance and climate. Currently, the study of clouds is mostly based on a two-dimensional (2-D) plane rather than a three-dimensional (3-D) space. However, 3-D cloud reconstruction is playing an important role not only in a radiation transmission calculation but in forecasting climate change as well. Currently, the study of clouds is mostly based on 2-D single angle satellite observation data while the importance of a 3-D structure of clouds in atmospheric radiation transmission is ignored. 3-D structure reconstruction would improve the radiation transmission accuracy of the cloudy atmosphere based on multi-angle observations data. Characterizing the 3-D structure of clouds is crucial for an extensive study of this complex intermediate medium in the atmosphere. In addition, it is also a great carrier for visualization of its parameters. Special attributes and the shape of clouds can be clearly illustrated in a 3-D cloud while these are difficult to describe in a 2-D plane. It provides a more intuitive expression for the study of complex cloud systems. In order to reconstruct a 3-D cloud structure, we develop and explore a ray casting algorithm applied to data from the Directional Polarimetric Camera (DPC), which is onboard the GF-5 satellite. In this paper, we use DPC with characteristics of imaging multiple angles of the same target, and characterize observations of clouds from different angles in 3-D space. This feature allows us to reconstruct 3-D clouds from different angles of observations. In terms of verification, we use cloud profile data provided by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to compare with the results of reconstructed 3-D clouds based on DPC data. This shows that the reconstruction method has good accuracy and effectiveness. This 3-D cloud reconstruction method would lay a scientific reference for future analysis on the role of clouds in the atmosphere and for the construction of 3-D structures of aerosols.
37
Lin, L., X. Zou, R. Anthes, and Y.-H. Kuo. "COSMIC GPS Radio Occultation Temperature Profiles in Clouds." Monthly Weather Review 138, no. 4 (April 1, 2010): 1104–18. http://dx.doi.org/10.1175/2009mwr2986.1.
Full textAbstract:
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 analysis for soundings in clouds and clear air separately, a systematic bias of opposite sign was found between large-scale global analyses and the GPS RO observations under cloudy and clear-sky conditions. As a modification to the standard GPS RO wet temperature retrieval that does not distinguish between cloudy- and clear-sky conditions, a new cloudy retrieval algorithm is proposed to incorporate the knowledge that in-cloud specific humidity (which affects the GPS refractivities) should be close to saturation. To implement this new algorithm, a linear regression model for a sounding-dependent relative humidity parameter α is first developed based on a high correlation between relative humidity and ice water content. In the absence of ice water content information, α takes an empirical value of 85%. The in-cloud temperature profile is then retrieved from GPS RO data modeled by a weighted sum of refractivities with and without the assumption of saturation. Compared to the standard wet retrieval, the cloudy temperature retrieval is consistently warmer within clouds by ∼2 K and slightly colder near the cloud top (∼1 K) and cloud base (1.5 K), leading to a more rapid increase of the lapse rate with height in the upper half of the cloud, from a nearly constant moist lapse rate below and at the cloud middle (∼6°C km−1) to a value of 7.7°C km−1, which must be closer to the dry lapse rate than the standard wet retrieval.
38
Di Natale, Gianluca, Giovanni Bianchini, Massimo Del Guasta, Marco Ridolfi, Tiziano Maestri, William Cossich, Davide Magurno, and Luca Palchetti. "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 (October 31, 2020): 3574. http://dx.doi.org/10.3390/rs12213574.
Full textAbstract:
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 each of the identified cloudy scenes, the nearest (in time) LiDAR backscattering profile is processed by the Polar Threshold (PT) algorithm that allows derivation of the cloud top and bottom heights. Subsequently, using the CIC and PT results as external constraints, the Simultaneous Atmospheric and Clouds Retrieval (SACR) code is applied to the REFIR-PAD spectral radiances. SACR simultaneously retrieves cloud optical depth and effective dimensions and atmospheric vertical profiles of water vapor and temperature. The analysis determines an average effective diameter of 28 μm with an optical depth of 0.76 for the ice clouds. Water clouds are only detected during the austral Summer, and the retrieved properties provide an average droplet diameter of 9 μm and average optical depth equal to four. The estimated retrieval error is about 1% for the ice crystal/droplet size and 2% for the cloud optical depth. The sensitivity of the retrieved parameters to the assumed crystal shape is also assessed. New parametrizations of the optical depth and the longwave downwelling forcing for Antarctic ice and water clouds, as a function of the ice/liquid water path, are presented. The longwave downwelling flux, computed from the top of the atmosphere to the surface, ranges between 70 and 220 W/m2. The estimated cloud longwave forcing at the surface is (31 ± 7) W/m2 and (29 ± 6) W/m2 for ice clouds and (64 ± 12) and (62 ± 11) W/m2 for water clouds, in 2013 and 2014, respectively. The total average cloud forcing for the two years investigated is (46 ± 9) W/m2.
39
Heiblum, Reuven H., Lital Pinto, Orit Altaratz, Guy Dagan, and Ilan Koren. "Core and margin in warm convective clouds – Part 1: Core types and evolution during a cloud's lifetime." Atmospheric Chemistry and Physics 19, no. 16 (August 26, 2019): 10717–38. http://dx.doi.org/10.5194/acp-19-10717-2019.
Full textAbstract:
Abstract. The properties of a warm convective cloud are determined by the competition between the growth and dissipation processes occurring within it. One way to observe and follow this competition is by partitioning the cloud to core and margin regions. Here we look at three core definitions, namely positive vertical velocity (Wcore), supersaturation (RHcore), and positive buoyancy (Bcore), and follow their evolution throughout the lifetime of warm convective clouds. Using single cloud and cloud field simulations with bin-microphysics schemes, we show that the different core types tend to be subsets of one another in the following order: Bcore⊆RHcore⊆Wcore. This property is seen for several different thermodynamic profile initializations and is generally maintained during the growing and mature stages of a cloud's lifetime. This finding is in line with previous works and theoretical predictions showing that cumulus clouds may be dominated by negative buoyancy at certain stages of their lifetime. The RHcore–Wcore pair is most interchangeable, especially during the growing stages of the cloud. For all three definitions, the core–shell model of a core (positive values) at the center of the cloud surrounded by a shell (negative values) at the cloud periphery applies to over 80 % of a typical cloud's lifetime. The core–shell model is less appropriate in larger clouds with multiple cores displaced from the cloud center. Larger clouds may also exhibit buoyancy cores centered near the cloud edge. During dissipation the cores show less overlap, reduce in size, and may migrate from the cloud center.
40
Dagan, Guy, Ilan Koren, Orit Altaratz, and Reuven H. Heiblum. "Time-dependent, non-monotonic response of warm convective cloud fields to changes in aerosol loading." Atmospheric Chemistry and Physics 17, no. 12 (June 20, 2017): 7435–44. http://dx.doi.org/10.5194/acp-17-7435-2017.
Full textAbstract:
Abstract. Large eddy simulations (LESs) with bin microphysics are used here to study cloud fields' sensitivity to changes in aerosol loading and the time evolution of this response. Similarly to the known response of a single cloud, we show that the mean field properties change in a non-monotonic trend, with an optimum aerosol concentration for which the field reaches its maximal water mass or rain yield. This trend is a result of competition between processes that encourage cloud development versus those that suppress it. However, another layer of complexity is added when considering clouds' impact on the field's thermodynamic properties and how this is dependent on aerosol loading. Under polluted conditions, rain is suppressed and the non-precipitating clouds act to increase atmospheric instability. This results in warming of the lower part of the cloudy layer (in which there is net condensation) and cooling of the upper part (net evaporation). Evaporation at the upper part of the cloudy layer in the polluted simulations raises humidity at these levels and thus amplifies the development of the next generation of clouds (preconditioning effect). On the other hand, under clean conditions, the precipitating clouds drive net warming of the cloudy layer and net cooling of the sub-cloud layer due to rain evaporation. These two effects act to stabilize the atmospheric boundary layer with time (consumption of the instability). The evolution of the field's thermodynamic properties affects the cloud properties in return, as shown by the migration of the optimal aerosol concentration toward higher values.
41
Liu, Ruyu, Zhiyong Zhang, Liting Dai, Guodao Zhang, and Bo Sun. "MFTR-Net: A Multi-Level Features Network with Targeted Regularization for Large-Scale Point Cloud Classification." Sensors 23, no. 8 (April 10, 2023): 3869. http://dx.doi.org/10.3390/s23083869.
Full textAbstract:
There are some irregular and disordered noise points in large-scale point clouds, and the accuracy of existing large-scale point cloud classification methods still needs further improvement. This paper proposes a network named MFTR-Net, which considers the local point cloud’s eigenvalue calculation. The eigenvalues of 3D point cloud data and the 2D eigenvalues of projected point clouds on different planes are calculated to express the local feature relationship between adjacent point clouds. A regular point cloud feature image is constructed and inputs into the designed convolutional neural network. The network adds TargetDrop to be more robust. The experimental result shows that our methods can learn more high-dimensional feature information, further improving point cloud classification, and our approach can achieve 98.0% accuracy with the Oakland 3D dataset.
42
Lonardi, Michael, Elisa F. Akansu, André Ehrlich, Mauro Mazzola, Christian Pilz, Matthew D. Shupe, Holger Siebert, and Manfred Wendisch. "Tethered balloon-borne observations of thermal-infrared irradiance and cooling rate profiles in the Arctic atmospheric boundary layer." Atmospheric Chemistry and Physics 24, no. 3 (February 14, 2024): 1961–78. http://dx.doi.org/10.5194/acp-24-1961-2024.
Full textAbstract:
Abstract. Clouds play an important role in controlling the radiative energy budget of the Arctic atmospheric boundary layer. To quantify the impact of clouds on the radiative heating or cooling of the lower atmosphere and of the surface, vertical profile observations of thermal-infrared irradiances were collected using a radiation measurement system carried by a tethered balloon. We present 70 profiles of thermal-infrared radiative quantities measured in summer 2020 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and in autumn 2021 and spring 2022 in Ny-Ålesund, Svalbard. Measurements are classified into four groups: cloudless, low-level liquid-bearing cloud, elevated liquid-bearing cloud, and elevated ice cloud. Cloudless cases display an average radiative cooling rate of about −2 K d−1 throughout the atmospheric boundary layer. Instead, low-level liquid-bearing clouds are characterized by a radiative cooling up to −80 K d−1 within a shallow layer at cloud top, while no temperature tendencies are identified underneath the cloud layer. Radiative transfer simulations are performed to quantify the sensitivity of radiative cooling rates to cloud microphysical properties. In particular, cloud top cooling is strongly driven by the liquid water path, especially in optically thin clouds, while for optically thick clouds the cloud droplet number concentration has an increased influence. Additional radiative transfer simulations are used to demonstrate the enhanced radiative importance of the liquid relative to ice clouds. To analyze the temporal evolution of thermal-infrared radiation profiles during the transitions from a cloudy to a cloudless atmosphere, a respective case study is investigated.
43
Sonkaew, T., V. V. Rozanov, C. von Savigny, A. Rozanov, H. Bovensmann, and J. P. Burrows. "Cloud sensitivity studies for stratospheric and lower mesospheric ozone profile retrievals from measurements of limb-scattered solar radiation." Atmospheric Measurement Techniques 2, no. 2 (November 4, 2009): 653–78. http://dx.doi.org/10.5194/amt-2-653-2009.
Full textAbstract:
Abstract. Clouds in the atmosphere play an important role in reflection, absorption and transmission of solar radiation and thus affect trace gas retrievals. The main goal of this paper is to examine the sensitivity of stratospheric and lower mesospheric ozone retrievals from limb-scattered radiance measurements to clouds using the SCIATRAN radiative transfer model and retrieval package. The retrieval approach employed is optimal estimation, and the considered clouds are vertically and horizontally homogeneous. Assuming an aerosol-free atmosphere and Mie phase functions for cloud particles, we compute the relative error of ozone profile retrievals in a cloudy atmosphere if clouds are neglected in the retrieval. To access altitudes from the lower stratosphere up to the lower mesosphere, we combine the retrievals in the Chappuis and Hartley ozone absorption bands. We find significant cloud sensitivity of the limb ozone retrievals in the Chappuis bands at lower stratospheric altitudes. The relative error in the retrieved ozone concentrations gradually decreases with increasing altitude and becomes negligible above approximately 40 km. The parameters with the largest impact on the ozone retrievals are cloud optical thickness, ground albedo and solar zenith angle. Clouds with different geometrical thicknesses or different cloud altitudes have a similar impact on the ozone retrievals for a given cloud optical thickness value, if the clouds are outside the field of view of the instrument. The effective radius of water droplets has a small influence on the error, i.e., less than 0.5% at altitudes above the cloud top height. Furthermore, the impact of clouds on the ozone profile retrievals was found to have a rather small dependence on the solar azimuth angle (less than 1% for all possible azimuth angles). For the most frequent cloud types, the total error is below 6% above 15 km altitude, if clouds are completely neglected in the retrieval. Neglecting clouds in the ozone profile retrievals generally leads to a low bias for a low ground albedo and to a high bias for a high ground albedo, assuming that the ground albedo is well known.
44
Yuan, T. "Cloud macroscopic organization: order emerging from randomness." Atmospheric Chemistry and Physics 11, no. 15 (August 1, 2011): 7483–90. http://dx.doi.org/10.5194/acp-11-7483-2011.
Full textAbstract:
Abstract. Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent γ close to 2. γ is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.
45
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 (April 11, 2016): 1587–99. http://dx.doi.org/10.5194/amt-9-1587-2016.
Full textAbstract:
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 budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.
46
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 (November 16, 2015): 11893–924. http://dx.doi.org/10.5194/amtd-8-11893-2015.
Full textAbstract:
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 budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.
47
Jones, David. "Cloud-chamber clouds." Nature 417, no. 6891 (June 2002): 808. http://dx.doi.org/10.1038/417808a.
Full text
48
Wind, Galina, Steven Platnick, Michael D. King, Paul A. Hubanks, Michael J. Pavolonis, Andrew K. Heidinger, Ping Yang, and Bryan A. Baum. "Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band." Journal of Applied Meteorology and Climatology 49, no. 11 (November 1, 2010): 2315–33. http://dx.doi.org/10.1175/2010jamc2364.1.
Full textAbstract:
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-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94-μm methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases.
49
Newchurch, M. J., D. Sun, J. H. Kim, and X. Liu. "Tropical tropospheric ozone derived using Clear-Cloudy Pairs (CCP) of TOMS measurements." Atmospheric Chemistry and Physics 3, no. 3 (June 11, 2003): 683–95. http://dx.doi.org/10.5194/acp-3-683-2003.
Full textAbstract:
Abstract. Using TOMS total-ozone measurements over high-altitude cloud locations and nearby paired clear locations, we describe the Clear-Cloudy Pairs (CCP) method for deriving tropical tropospheric ozone. The high-altitude clouds are identified by measured 380 nm reflectivities greater than 80% and Temperature Humidity InfraRed (THIR) measured cloud-top pressures less than 200 hPa. To account for locations without high-altitude clouds, we apply a zonal sine fitting to the stratospheric ozone derived from available cloudy points, resulting in a wave-one amplitude of about 4 DU. THIR data is unavailable after November 1984, so we extend the CCP method by using a reflectivity threshold of 90% to identify high-altitude clouds and remove the influence of high-reflectivity-but-low-altitude clouds with a lowpass frequency filter. We correct ozone retrieval errors associated with clouds, and ozone retrieval errors due to sun glint and aerosols. Comparing CCP results with Southern Hemisphere ADditional OZonesondes (SHADOZ) tropospheric ozone indicates that CCP tropospheric ozone and ozonesonde measurements agree, on average, to within 3 ± 1 DU standard error of the mean. The most significant difference between CCP and ozonesonde tropospheric ozone can be explained by the low Total Ozone Mapping Spectrometer (TOMS) version-7 retrieval efficiency of ozone in the lower troposphere.
50
Turner, D. D. "Arctic Mixed-Phase Cloud Properties from AERI Lidar Observations: Algorithm and Results from SHEBA." Journal of Applied Meteorology 44, no. 4 (April 1, 2005): 427–44. http://dx.doi.org/10.1175/jam2208.1.
Full textAbstract:
Abstract A new approach to retrieve microphysical properties from mixed-phase Arctic clouds is presented. This mixed-phase cloud property retrieval algorithm (MIXCRA) retrieves cloud optical depth, ice fraction, and the effective radius of the water and ice particles from ground-based, high-resolution infrared radiance and lidar cloud boundary observations. The theoretical basis for this technique is that the absorption coefficient of ice is greater than that of liquid water from 10 to 13 μm, whereas liquid water is more absorbing than ice from 16 to 25 μm. MIXCRA retrievals are only valid for optically thin (τvisible < 6) single-layer clouds when the precipitable water vapor is less than 1 cm. MIXCRA was applied to the Atmospheric Emitted Radiance Interferometer (AERI) data that were collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment from November 1997 to May 1998, where 63% of all of the cloudy scenes above the SHEBA site met this specification. The retrieval determined that approximately 48% of these clouds were mixed phase and that a significant number of clouds (during all 7 months) contained liquid water, even for cloud temperatures as low as 240 K. The retrieved distributions of effective radii for water and ice particles in single-phase clouds are shown to be different than the effective radii in mixed-phase clouds.