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1
Sedlar, Joseph. "Implications of Limited Liquid Water Path on Static Mixing within Arctic Low-Level Clouds." Journal of Applied Meteorology and Climatology 53, no. 12 (December 2014): 2775–89. http://dx.doi.org/10.1175/jamc-d-14-0065.1.
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AbstractObservations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%–30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and optically thick LWP subclasses. Clouds with larger LWPs tend to have a deeper in-cloud mixed layer relative to optically thinner clouds. However, both cloud LWP subclasses are frequently characterized by an in-cloud stable layer above the mixed layer top. The depth of the stable layer generally correlates with an increased temperature gradient across the layer. This layer often contains a specific humidity inversion, but it is more frequently present when cloud LWP is optically thinner (LWP < 50 g m−2). It is suggested that horizontal thermodynamic advection plays a key role modifying the vertical extent of in-cloud mixing and likewise the depth of in-cloud stable layers. Furthermore, longwave atmospheric opacity above the cloud top is generally enhanced during cases with optically thinner clouds. Thermodynamic advection, cloud condensate distribution within the stable layer, and enhanced atmospheric radiation above the cloud are found to introduce a thermodynamic–radiative feedback that potentially modifies the extent of LWP and subsequent in-cloud mixing.
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Li, J., Z. Wu, Z. Hu, Y. Zhang, and M. Molinier. "AUTOMATIC CLOUD DETECTION METHOD BASED ON GENERATIVE ADVERSARIAL NETWORKS IN REMOTE SENSING IMAGES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 885–92. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-885-2020.
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Abstract. Clouds in optical remote sensing images seriously affect the visibility of background pixels and greatly reduce the availability of images. It is necessary to detect clouds before processing images. In this paper, a novel cloud detection method based on attentive generative adversarial network (Auto-GAN) is proposed for cloud detection. Our main idea is to inject visual attention into the domain transformation to detect clouds automatically. First, we use a discriminator (D) to distinguish between cloudy and cloud free images. Then, a segmentation network is used to detect the 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.
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Pangaud, Thomas, Nadia Fourrie, Vincent Guidard, Mohamed Dahoui, and Florence Rabier. "Assimilation of AIRS Radiances Affected by Mid- to Low-Level Clouds." Monthly Weather Review 137, no. 12 (December 1, 2009): 4276–92. http://dx.doi.org/10.1175/2009mwr3020.1.
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Abstract An approach to make use of Atmospheric Infrared Sounder (AIRS) cloud-affected infrared radiances has been developed at Météo-France in the context of the global numerical weather prediction model. The method is based on (i) the detection and the characterization of clouds by the CO2-slicing algorithm and (ii) the identification of clear–cloudy channels using the ECMWF cloud-detection scheme. Once a hypothetical cloud-affected pixel is detected by the CO2-slicing scheme, the cloud-top pressure and the effective cloud fraction are provided to the radiative transfer model simultaneously with other atmospheric variables to simulate cloud-affected radiances. Furthermore, the ECMWF scheme flags each channel of the pixel as clear or cloudy. In the current configuration of the assimilation scheme, channels affected by clouds whose cloud-top pressure ranges between 600 and 950 hPa are assimilated over sea in addition to clear channels. Results of assimilation experiments are presented. On average, 3.5% of additional pixels are assimilated over the globe but additional assimilated channels are much more numerous for mid- to high latitudes (10% of additional assimilated channels on average). Encouraging results are found in the quality of the analyses: background departures of AIRS observations are reduced, especially for surface channels, which are globally 4 times smaller, and the analysis better fits some conventional and satellite data. Global forecasts are slightly improved for the geopotential field. These improvements are significant up to the 72-h forecast range. Predictability improvements have been obtained for a case study: a low pressure system that affected the southeastern part of Italy in September 2006. The trajectory, intensity, and the whole development of the cyclogenesis are better predicted, whatever the forecast range, for this case study.
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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.
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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.
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Liu, X., M. J. Newchurch, and J. H. Kim. "Occurrence of ozone anomalies over cloudy areas in TOMS version-7 level-2 data." Atmospheric Chemistry and Physics Discussions 3, no. 1 (January 13, 2003): 187–223. http://dx.doi.org/10.5194/acpd-3-187-2003.
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Abstract. This study investigates anomalous ozone distributions over cloudy areas in Nimbus-7 (N7) and Earth-Probe (EP) TOMS version-7 data and analyzes the causes for ozone anomaly formation. A 5°-longitude by 5°-latitude region is defined to contain a Positive Ozone Anomaly (POA) or Negative Ozone Anomaly (NOA) if the correlation coefficient between total ozone and reflectivity is ≥0.5 or ≥− 0.5. The average fractions of ozone anomalies among all cloud fields are 31.8+/−7.7% and 35.8+\\−7.7% in the N7 and EP TOMS data, respectively. Some ozone anomalies are caused by ozone retrieval errors, and others are caused by actual geophysical phenomena. Large cloud-height errors are found in the TOMS version-7 algorithm in comparison to the Temperature Humidity Infrared Radiometer (THIR) cloud data. On average, cloud-top pressures are overestimated by ~200 hPa (THIR cloud-top pressure ≤ 200 hPa) for high-altitude clouds and underestimated by ~150 hPa for low-altitude clouds (THIR cloud-top pressure ≥750 hPa). Most tropical NOAs result from negative errors induced by large cloud-height errors, and most tropical POAs are caused by positive errors due to intra-cloud ozone absorption enhancement. However, positive and negative errors offset each other, reducing the ozone anomaly occurrence in TOMS data. Large ozone/reflectivity slopes for mid-latitude POAs show seasonal variation consistent with total ozone fluctuation, indicating that they result mainly from synoptic and planetary wave disturbances. POAs with an occurrence fraction of 30–60% occur in regions of marine stratocumulus off the west coast of South Africa and off the west coast of South America. Both fractions and ozone/reflectivity slopes of these POAs show seasonal variations consistent with that in the tropospheric ozone. About half the ozone/reflectivity slope can be explained by ozone retrieval errors over clear and cloudy areas. The remaining slope may result from there being more ozone production because of rich ozone precursors and higher j-values over high-frequency, low-altitude clouds than in clear areas. Ozone anomalies due to ozone retrieval errors have important implications in TOMS applications such as tropospheric ozone derivation and analysis of ozone seasonal variation.
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Liu, X., M. J. Newchurch, and J. H. Kim. "Occurrence of ozone anomalies over cloudy areas in TOMS version-7 level-2 data." Atmospheric Chemistry and Physics 3, no. 4 (August 1, 2003): 1113–29. http://dx.doi.org/10.5194/acp-3-1113-2003.
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Abstract. This study investigates anomalous ozone distributions over cloudy areas in Nimbus-7 (N7) and Earth-Probe (EP) TOMS version-7 data and analyzes the causes for ozone anomaly formation. A 5°-longitude by 5°-latitude region is defined to contain a Positive Ozone Anomaly (POA) or Negative Ozone Anomaly (NOA) if the correlation coefficient between total ozone and reflectivity is > 0.5 or < -0.5. The average fractions of ozone anomalies among all cloud fields are 31.8 ± 7.7% and 35.8 ± 7.7% in the N7 and EP TOMS data, respectively. Some ozone anomalies are caused by ozone retrieval errors, and others are caused by actual geophysical phenomena. Large cloud-height errors are found in the TOMS version-7 algorithm in comparison to the Temperature Humidity Infrared Radiometer (THIR) cloud data. On average, cloud-top pressures are overestimated by ~200 hPa (THIR cloud-top pressure < 200 hPa) for high-altitude clouds and underestimated by ~150 hPa for low-altitude clouds (THIR cloud-top pressure > 750 hPa). Most tropical NOAs result from negative errors induced by large cloud-height errors, and most tropical POAs are caused by positive errors due to intra-cloud ozone absorption enhancement. However, positive and negative errors offset each other, reducing the ozone anomaly occurrence in TOMS data. Large ozone/reflectivity slopes for mid-latitude POAs show seasonal variation consistent with total ozone fluctuation, indicating that they result mainly from synoptic and planetary wave disturbances. POAs with an occurrence fraction of 30--60% occur in regions of marine stratocumulus off the west coast of South Africa and off the west coast of South America. Both fractions and ozone/reflectivity slopes of these POAs show seasonal variations consistent with that in the tropospheric ozone. About half the ozone/reflectivity slope can be explained by ozone retrieval errors over clear and cloudy areas. The remaining slope may result from there being more ozone production because of rich ozone precursors and higher photolysis rates over high-frequency, low-altitude clouds than in clear areas. Ozone anomalies due to ozone retrieval errors have important implications in TOMS applications such as tropospheric ozone derivation and analysis of ozone seasonal variation.
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Adebiyi, Adeyemi A., Paquita Zuidema, Ian Chang, Sharon P. Burton, and Brian Cairns. "Mid-level clouds are frequent above the southeast Atlantic stratocumulus clouds." Atmospheric Chemistry and Physics 20, no. 18 (September 25, 2020): 11025–43. http://dx.doi.org/10.5194/acp-20-11025-2020.
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Abstract. Shortwave-absorbing aerosols seasonally overlay extensive low-level stratocumulus clouds over the southeast Atlantic. While much attention has focused on the interactions between the low-level clouds and the overlying aerosols, few studies have focused on the mid-level clouds that also occur over the region. The presence of mid-level clouds over the region complicates the space-based remote-sensing retrievals of cloud properties and the evaluation of cloud radiation budgets. Here we characterize the mid-level clouds over the southeast Atlantic using lidar- and radar-based satellite cloud retrievals and observations collected in September 2016 during the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign. We find that mid-level clouds over the southeast Atlantic are relatively common, with the majority of the clouds occurring between altitudes of 5 and 7 km and at temperatures between 0 and −20 ∘C. The mid-level clouds occur at the top of a moist mid-tropospheric smoke-aerosol layer, most frequently between August and October, and closer to the southern African coast than farther offshore. They occur more frequently during the night than during the day. Between July and October, approximately 64 % of the mid-level clouds had a geometric cloud thickness less than 1 km, corresponding to a cloud optical depth of less than 4. A lidar-based depolarization–backscatter relationship for September 2016 indicates that the mid-level clouds are liquid-only clouds with no evidence of the existence of ice. In addition, a polarimeter-derived cloud droplet size distribution indicates that approximately 85 % of the September 2016 mid-level clouds had an effective radius less than 7 µm, which could further discourage the ability of the clouds to glaciate. These clouds are mostly associated with synoptically modulated mid-tropospheric moisture outflow that can be linked to the detrainment from the continental-based clouds. Overall, the supercooled mid-level clouds reduce the radiative cooling rates of the underlying low-altitude cloud tops by approximately 10 K d−1, thus influencing the regional cloud radiative budget.
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Adler, Bianca, Norbert Kalthoff, and Leonhard Gantner. "Nocturnal low-level clouds over southern West Africa analysed using high-resolution simulations." Atmospheric Chemistry and Physics 17, no. 2 (January 20, 2017): 899–910. http://dx.doi.org/10.5194/acp-17-899-2017.
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Abstract. We performed a high-resolution numerical simulation to study the development of extensive low-level clouds that frequently form over southern West Africa during the monsoon season. This study was made in preparation for a field campaign in 2016 within the Dynamics-aerosol-chemistry-cloud interactions in West Africa (DACCIWA) project and focuses on an area around the city of Savè in southern Benin. Nocturnal low-level clouds evolve a few hundred metres above the ground around the same level as a distinct low-level jet. Several processes are found to determine the spatio-temporal evolution of these clouds including (i) significant cooling of the nocturnal atmosphere caused by horizontal advection with the south-westerly monsoon flow during the first half of the night, (ii) vertical cold air advection due to gravity waves leading to clouds in the wave crests and (iii) enhanced convergence and upward motion upstream of existing clouds that trigger new clouds. The latter is caused by an upward shift of the low-level jet in cloudy areas leading to horizontal convergence in the lower part and to horizontal divergence in the upper part of the cloud layer. Although this single case study hardly allows for a generalisation of the processes found, the results added to the optimisation of the measurements strategy for the field campaign and the observations will be used to test the hypotheses for cloud formation resulting from this study.
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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.
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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.
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Zhang, L., P. van Oosterom, and H. Liu. "VISUALIZATION OF POINT CLOUD MODELS IN MOBILE AUGMENTED REALITY USING CONTINUOUS LEVEL OF DETAIL METHOD." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-4/W1-2020 (September 3, 2020): 167–70. http://dx.doi.org/10.5194/isprs-archives-xliv-4-w1-2020-167-2020.
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Abstract. Point clouds have become one of the most popular sources of data in geospatial fields due to their availability and flexibility. However, because of the large amount of data and the limited resources of mobile devices, the use of point clouds in mobile Augmented Reality applications is still quite limited. Many current mobile AR applications of point clouds lack fluent interactions with users. In our paper, a cLoD (continuous level-of-detail) method is introduced to filter the number of points to be rendered considerably, together with an adaptive point size rendering strategy, thus improve the rendering performance and remove visual artifacts of mobile AR point cloud applications. Our method uses a cLoD model that has an ideal distribution over LoDs, with which can remove unnecessary points without sudden changes in density as present in the commonly used discrete level-of-detail approaches. Besides, camera position, orientation and distance from the camera to point cloud model is taken into consideration as well. With our method, good interactive visualization of point clouds can be realized in the mobile AR environment, with both nice visual quality and proper resource consumption.
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Karlsson, Linn, Radovan Krejci, Makoto Koike, Kerstin Ebell, and Paul Zieger. "A long-term study of cloud residuals from low-level Arctic clouds." Atmospheric Chemistry and Physics 21, no. 11 (June 14, 2021): 8933–59. http://dx.doi.org/10.5194/acp-21-8933-2021.
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Abstract. To constrain uncertainties in radiative forcings associated with aerosol–cloud interactions, improved understanding of Arctic cloud formation is required, yet long-term measurements of the relevant cloud and aerosol properties remain sparse. We present the first long-term study of cloud residuals, i.e. particles that were involved in cloud formation and cloud processes, in Arctic low-level clouds measured at Zeppelin Observatory, Svalbard. To continuously sample cloud droplets and ice crystals and separate them from non-activated aerosol, a ground-based counter-flow virtual impactor inlet system (GCVI) was used. A detailed evaluation of the GCVI measurements, using concurrent cloud particle size distributions, meteorological parameters, and aerosol measurements, is presented for both warm and cold clouds, and the potential contribution of sampling artefacts is discussed in detail. We find an excellent agreement of the GCVI sampling efficiency of liquid clouds using two independent approaches. The 2-year data set of cloud residual size distributions and number concentrations reveals that the cloud residuals follow the typical seasonal cycle of Arctic aerosol, with a maximum concentration in spring and summer and a minimum concentration in the late autumn and winter months. We observed average activation diameters in the range of 58–78 nm for updraught velocities below 1 m s−1. A cluster analysis also revealed cloud residual size distributions that were dominated by Aitken mode particles down to around 20–30 nm. During the winter months, some of these small particles may be the result of ice, snow, or ice crystal shattering artefacts in the GCVI inlet; however, cloud residuals down to 20 nm in size were also observed during conditions when artefacts are less likely.
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Carbajal Henken, C. K., R. Lindstrot, R. Preusker, and J. Fischer. "FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations." Atmospheric Measurement Techniques 7, no. 11 (November 25, 2014): 3873–90. http://dx.doi.org/10.5194/amt-7-3873-2014.
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Abstract. A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud), is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR) and the Medium Resolution Imaging Spectrometer (MERIS), both mounted on the polar-orbiting Environmental Satellite (Envisat), are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA) Climate Change Initiative (CCI) project, the first global cloud property retrievals have been conducted for the years 2007–2009. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: −0.28, 0.41 μm and −0.18 g m−2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root-mean-square deviation. Furthermore, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several Atmospheric Radiation Measurement (ARM) sites. FAME-C mostly shows an underestimation of cloud top heights when compared to radar observations. The lowest bias of −0.3 km is found for AATSR cloud top heights for single-layer clouds, while the highest bias of −3.0 km is found for AATSR cloud top heights for multilayer clouds. Variability is low for MERIS cloud top heights for low-level clouds, and high for MERIS cloud top heights for mid-level and high-level single-layer clouds, as well as for both AATSR and MERIS cloud top heights for multilayer clouds.
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Dawe, J. T., and P. H. Austin. "Statistical analysis of a LES shallow cumulus cloud ensemble using a cloud tracking algorithm." Atmospheric Chemistry and Physics Discussions 11, no. 8 (August 17, 2011): 23231–73. http://dx.doi.org/10.5194/acpd-11-23231-2011.
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Abstract. A technique for the tracking of individual clouds in a Large Eddy Simulation (LES) is presented. We use this technique on a LES of a shallow cumulus cloud field based upon the Barbados Oceanographic and Meteorological Experiment (BOMEX) to calculate statistics of cloud height, lifetime, and other physical properties for individual clouds in the model. We also examine the question of nature versus nurture in shallow cumulus clouds: do properties at cloud base determine the upper-level properties of the clouds (nature), or are cloud properties determined by the environmental conditions they encounter (nurture). We find that clouds which ascend through an environment that has been pre-moistened by previous cloud activity are no more likely to reach the inversion than clouds that ascend through a drier environment. Cloud base thermodynamic properties are uncorrelated with upper-level cloud properties, while mean fractional entrainment and detrainment rate displays moderate correlations with cloud properties up to the inversion. Conversely, cloud base area correlates well with upper-level cloud area and maximum cloud height. We conclude that cloud thermodynamic properties are primarily influenced by entrainment and detrainment processes, cloud area and height are primarily influenced by cloud base area, and thus nature and nurture both play roles in the dynamics of BOMEX shallow cumulus clouds.
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Dawe, J. T., and P. H. Austin. "Statistical analysis of an LES shallow cumulus cloud ensemble using a cloud tracking algorithm." Atmospheric Chemistry and Physics 12, no. 2 (January 26, 2012): 1101–19. http://dx.doi.org/10.5194/acp-12-1101-2012.
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Abstract. A technique for the tracking of individual clouds in a Large Eddy Simulation (LES) is presented. We use this technique on an LES of a shallow cumulus cloud field based upon the Barbados Oceanographic and Meteorological Experiment (BOMEX) to calculate statistics of cloud height, lifetime, and other physical properties for individual clouds in the model. We also examine the question of nature versus nurture in shallow cumulus clouds: do properties at cloud base determine the upper-level properties of the clouds (nature), or are cloud properties determined by the environmental conditions they encounter (nurture). We find that clouds which ascend through an environment that has been pre-moistened by previous cloud activity are no more likely to reach the inversion than clouds that ascend through a drier environment. Cloud base thermodynamic properties are uncorrelated with upper-level cloud properties, while mean fractional entrainment and detrainment rates display moderate correlations with cloud properties up to the inversion. Conversely, cloud base area correlates well with upper-level cloud area and maximum cloud height. We conclude that cloud thermodynamic properties are primarily influenced by entrainment and detrainment processes, cloud area and height are primarily influenced by cloud base area, and thus nature and nurture both play roles in the dynamics of BOMEX shallow cumulus clouds.
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Taylor, Jonathan W., Sophie L. Haslett, Keith Bower, Michael Flynn, Ian Crawford, James Dorsey, Tom Choularton, et al. "Aerosol influences on low-level clouds in the West African monsoon." Atmospheric Chemistry and Physics 19, no. 13 (July 4, 2019): 8503–22. http://dx.doi.org/10.5194/acp-19-8503-2019.
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Abstract. Low-level clouds (LLCs) cover a wide area of southern West Africa (SWA) during the summer monsoon months and have an important cooling effect on the regional climate. Previous studies of these clouds have focused on modelling and remote sensing via satellite. We present the first comprehensive set of in situ measurements of cloud microphysics from the region, taken during June–July 2016, as part of the DACCIWA (Dynamics–aerosol–chemistry–cloud interactions in West Africa) campaign. This novel dataset allows us to assess spatial, diurnal, and day-to-day variation in the properties of these clouds over the region. LLCs developed overnight and mean cloud cover peaked a few hundred kilometres inland around 10:00 local solar time (LST), before clouds began to dissipate and convection intensified in the afternoon. Regional variation in LLC cover was largely orographic, and no lasting impacts in cloud cover related to pollution plumes were observed downwind of major population centres. The boundary layer cloud drop number concentration (CDNC) was locally variable inland, ranging from 200 to 840 cm−3 (10th and 90th percentiles at standard temperature and pressure), but showed no systematic regional variations. Enhancements were seen in pollution plumes from the coastal cities but were not statistically significant across the region. A significant fraction of accumulation mode aerosols, and therefore cloud condensation nuclei, were from ubiquitous biomass burning smoke transported from the Southern Hemisphere. To assess the relative importance of local and transported aerosol on the cloud field, we isolated the local contribution to the aerosol population by comparing inland and offshore size and composition measurements. A parcel model sensitivity analysis showed that doubling or halving local emissions only changed the calculated cloud drop number concentration by 13 %–22 %, as the high background meant local emissions were a small fraction of total aerosol. As the population of SWA grows, local emissions are expected to rise. Biomass burning smoke transported from the Southern Hemisphere is likely to dampen any effect of these increased local emissions on cloud–aerosol interactions. An integrative analysis between local pollution and Central African biomass burning emissions must be considered when predicting anthropogenic impacts on the regional cloud field during the West African summer monsoon.
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Xu, Wenjing, and Daren Lyu. "Evaluation of Cloud Mask and Cloud Top Height from Fengyun-4A with MODIS Cloud Retrievals over the Tibetan Plateau." Remote Sensing 13, no. 8 (April 7, 2021): 1418. http://dx.doi.org/10.3390/rs13081418.
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The Tibetan Plateau (TP) has profound thermal and dynamic influences on the atmospheric circulation, energy, and water cycles of the climate system, which make the clouds over the TP the forefront of atmospheric and climate science. However, the highest altitude and most complex terrain of the TP make the retrieval of cloud properties challenging. In order to understand the performance and limitations of cloud retrievals over the TP derived from the state-of-the-art Advanced Geosynchronous Radiation Imager (AGRI) onboard the new generation of Chinese Geostationary (GEO) meteorological satellites Fengyun-4 (FY-4), a three-month comparison was conducted between FY-4A/AGRI and the Moderate Resolution Imaging Spectroradiometer (MODIS) for both cloud detection and cloud top height (CTH) pixel-level retrievals. For cloud detection, the AGRI and MODIS cloud mask retrievals showed a fractional agreement of 0.93 for cloudy conditions and 0.73 for clear scenes. AGRI tended to miss lower CTH clouds due to the lack of thermal contrast between the clouds and the surface of the TP. For cloud top height retrievals, the comparison showed that on average, AGRI underestimated the CTH relative to MODIS by 1.366 ± 2.235 km, and their differences presented a trend of increasing with height.
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Ehrlich, A., E. Bierwirth, M. Wendisch, J. F. Gayet, G. Mioche, A. Lampert, and J. Heintzenberg. "Cloud phase identification of low-level Arctic clouds from airborne spectral radiation measurements: test of three approaches." Atmospheric Chemistry and Physics Discussions 8, no. 4 (August 20, 2008): 15901–39. http://dx.doi.org/10.5194/acpd-8-15901-2008.
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Abstract. Boundary layer clouds were investigated with a complementary set of remote sensing and in situ instruments during the Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) campaign in March and April 2007. The clouds that formed in a cold air outbreak over the open Greenland sea showed a variety in their thermodynamic state. Beside the predominant mixed-phase clouds pure liquid and ice clouds were observed. Utilizing the measurements of solar radiation reflected by the clouds three methods to retrieve the thermodynamic phase of the cloud were defined and compared. Two ice indices IS and IP were obtained by analyzing the spectral pattern of the cloud top reflectance in the near infrared (1500–1800 nm wavelength) characterized by ice and water absorption. A third ice index IA is based on the different side scattering of spherical liquid water particles and nonspherical ice crystals which was recorded in simultaneous measurements of cloud albedo and reflectance. Radiative transfer simulations showed that IS, IP and IA range between 5 to 80, 0 to 20 and 1 to 1.25, respectively, with lowest values indicating pure liquid water clouds and highest values pure ice clouds. IS and IP were found to be strongly sensitive to the effective diameter of the ice crystals present in the cloud. Therefore the identification of mixed-phase clouds requires a priori knowledge of the ice crystal dimension. IA has the disadvantage that this index is mainly dominated by the uppermost cloud layer (τ<1.5). Typical boundary layer mixed-phase clouds with a liquid cloud top layer will be identified as pure liquid water clouds. All three methods were applied to measurements above a cloud field observed during ASTAR 2007. The comparison with independent in situ microphysical measurements showed a good agreement in identifying the dominant mixed-phase clouds and a pure ice cloud at the edge of the cloud field.
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Eguchi, Nawo, and Yukio Yoshida. "A high-level cloud detection method utilizing the GOSAT TANSO-FTS water vapor saturated band." Atmospheric Measurement Techniques 12, no. 1 (January 18, 2019): 389–403. http://dx.doi.org/10.5194/amt-12-389-2019.
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Abstract. A detection method for high-level clouds, such as ice clouds, is developed using the water vapor saturated channels of the solar reflected spectrum observed by the Greenhouse gases Observing SATellite (GOSAT) Thermal And Near-infrared Sensor for carbon Observation Fourier Transform Spectrometer (TANSO-FTS). The clouds detected by this method are optically relatively thin (0.01 or less) and located at high altitude. Approximately 85 % of the results from this method for clouds with cloud-top altitude above 5 km agree with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud classification. GOSAT has been operating since April 2009 with a 3-day repeat cycle for a pointwise geolocation pattern, providing a spectral data record that exceeds 9 years. Cloud information derived from GOSAT TANSO-FTS spectra could be powerful data for understanding the variability in cirrus cloud on temporal scales from synoptic to interannual.
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Zouzoua, Maurin, Fabienne Lohou, Paul Assamoi, Marie Lothon, Véronique Yoboue, Cheikh Dione, Norbert Kalthoff, et al. "Breakup of nocturnal low-level stratiform clouds during the southern West African monsoon season." Atmospheric Chemistry and Physics 21, no. 3 (February 10, 2021): 2027–51. http://dx.doi.org/10.5194/acp-21-2027-2021.
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Abstract. Within the framework of the DACCIWA (Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa) project and based on a field experiment conducted in June and July 2016, we analyze the daytime breakup of continental low-level stratiform clouds in southern West Africa. We use the observational data gathered during 22 precipitation-free occurrences at Savè, Benin. Our analysis, which starts from the stratiform cloud formation usually at night, focuses on the role played by the coupling between cloud and surface in the transition towards shallow convective clouds during daytime. It is based on several diagnostics, including the Richardson number and various cloud macrophysical properties. The distance between the cloud base height and lifting condensation level is used as a criterion of coupling. We also make an attempt to estimate the most predominant terms of the liquid water path budget in the early morning. When the nocturnal low-level stratiform cloud forms, it is decoupled from the surface except in one case. In the early morning, the cloud is found coupled with the surface in 9 cases and remains decoupled in the 13 other cases. The coupling, which occurs within the 4 h after cloud formation, is accompanied by cloud base lowering and near-neutral thermal stability in the subcloud layer. Further, at the initial stage of the transition, the stratiform cloud base is slightly cooler, wetter and more homogeneous in coupled cases. The moisture jump at the cloud top is usually found to be lower than 2 g kg−1 and the temperature jump within 1–5 K, which is significantly smaller than typical marine stratocumulus and explained by the monsoon flow environment in which the stratiform cloud develops over West Africa. No significant difference in liquid water path budget terms was found between coupled and decoupled cases. In agreement with previous numerical studies, we found that the stratiform cloud maintenance before sunrise results from the interplay between the predominant radiative cooling, entrainment and large-scale subsidence at its top. Three transition scenarios were observed depending on the state of coupling at the initial stage. In coupled cases, the low-level stratiform cloud remains coupled until its breakup. In five of the decoupled cases, the cloud couples with the surface as the lifting condensation level rises. In the eight remaining cases, the stratiform cloud remains hypothetically decoupled from the surface throughout its life cycle since the height of its base remains separated from the condensation level. In cases of coupling during the transition, the stratiform cloud base lifts with the growing convective boundary layer roughly between 06:30 and 08:00 UTC. The cloud deck breakup, occurring at 11:00 UTC or later, leads to the formation of shallow convective clouds. When the decoupling subsists, shallow cumulus clouds form below the stratiform cloud deck between 06:30 and 09:00 UTC. The breakup time in this scenario has a stronger variability and occurs before 11:00 UTC in most cases. Thus, we argue that the coupling with the surface during daytime hours has a crucial role in the low-level stratiform cloud maintenance and its transition towards shallow convective clouds.
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Stengel, Martin, Cornelia Schlundt, Stefan Stapelberg, Oliver Sus, Salomon Eliasson, Ulrika Willén, and Jan Fokke Meirink. "Comparing ERA-Interim clouds with satellite observations using a simplified satellite simulator." Atmospheric Chemistry and Physics 18, no. 23 (December 12, 2018): 17601–14. http://dx.doi.org/10.5194/acp-18-17601-2018.
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Abstract. An evaluation of the ERA-Interim clouds using satellite observations is presented. To facilitate such an evaluation in a proper way, a simplified satellite simulator has been developed and applied to 6-hourly ERA-Interim reanalysis data covering the period of 1982 to 2014. The simulator converts modelled cloud fields, for example those of the ERA-Interim reanalysis, to simulated cloud fields by accounting for specific characteristics of passive imaging satellite sensors such as the Advanced Very High Resolution Radiometer (AVHRR), which form the basis of many long-term observational datasets of cloud properties. It is attempted to keep the simulated cloud fields close to the original modelled cloud fields to allow a quality assessment of the latter based on comparisons of the simulated clouds fields with the observations. Applying the simulator to ERA-Interim data, this study firstly focuses on the spatial distribution and frequency of clouds (total cloud fraction) and on their vertical position, using cloud-top pressure to express the cloud fraction of high-level, mid-level and low-level clouds. Furthermore, the cloud-top thermodynamic phase is investigated. All comparisons incorporate knowledge of systematic uncertainties in the satellite observations and are further stratified by accounting for the limited sensitivity of the observations to clouds with very low cloud optical thickness (COT). The comparisons show that ERA-Interim cloud fraction is generally too low nearly everywhere on the globe except in the polar regions. This underestimation is caused by a lack of mid-level and/or low-level clouds, for which the comparisons only show a minor sensitivity to the cloud optical thickness thresholds applied. The amount of ERA-Interim high-level clouds, being higher than in the observations, agrees with the observations within their estimated uncertainties. Removing the optically very thin clouds (COT <0.15) from the model fields improves the agreement with the observations for high-level cloud fraction locally (e.g. in the tropics), while for the mid-latitude regions, the best agreement for high-level cloud fraction is found when removing all clouds with COT <1.0. Comparisons of the cloud thermodynamic phase at the cloud top reveal a too high relative ice cloud frequency in ERA-Interim, being most pronounced in the higher latitudes. Indications are found that this is due to the suppression of liquid cloud occurrence for temperatures below −23 ∘C in ERA-Interim. The application of this simulator facilitates a more effective use of passive satellite observations of clouds in the evaluation of modelled cloudiness, for example in reanalyses.
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Rosenfeld, Daniel, Yannian Zhu, Minghuai Wang, Youtong Zheng, Tom Goren, and Shaocai Yu. "Aerosol-driven droplet concentrations dominate coverage and water of oceanic low-level clouds." Science 363, no. 6427 (January 17, 2019): eaav0566. http://dx.doi.org/10.1126/science.aav0566.
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A lack of reliable estimates of cloud condensation nuclei (CCN) aerosols over oceans has severely limited our ability to quantify their effects on cloud properties and extent of cooling by reflecting solar radiation—a key uncertainty in anthropogenic climate forcing. We introduce a methodology for ascribing cloud properties to CCN and isolating the aerosol effects from meteorological effects. Its application showed that for a given meteorology, CCN explains three-fourths of the variability in the radiative cooling effect of clouds, mainly through affecting shallow cloud cover and water path. This reveals a much greater sensitivity of cloud radiative forcing to CCN than previously reported, which means too much cooling if incorporated into present climate models. This suggests the existence of compensating aerosol warming effects yet to be discovered, possibly through deep clouds.
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Miles, Natasha L., Johannes Verlinde, and Eugene E. Clothiaux. "Cloud Droplet Size Distributions in Low-Level Stratiform Clouds." Journal of the Atmospheric Sciences 57, no. 2 (January 2000): 295–311. http://dx.doi.org/10.1175/1520-0469(2000)057<0295:cdsdil>2.0.co;2.
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Dai, Peiyu, Shunping Ji, and Yongjun Zhang. "Gated Convolutional Networks for Cloud Removal From Bi-Temporal Remote Sensing Images." Remote Sensing 12, no. 20 (October 19, 2020): 3427. http://dx.doi.org/10.3390/rs12203427.
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Pixels of clouds and cloud shadows in a remote sensing image impact image quality, image interpretation, and subsequent applications. In this paper, we propose a novel cloud removal method based on deep learning that automatically reconstructs the invalid pixels with the auxiliary information from multi-temporal images. Our method’s innovation lies in its feature extraction and loss functions, which reside in a novel gated convolutional network (GCN) instead of a series of common convolutions. It takes the current cloudy image, a recent cloudless image, and the mask of clouds as input, without any requirements of external training samples, to realize a self-training process with clean pixels in the bi-temporal images as natural training samples. In our feature extraction, gated convolutional layers, for the first time, are introduced to discriminate cloudy pixels from clean pixels, which make up for a common convolution layer’s lack of the ability to discriminate. Our multi-level constrained joint loss function, which consists of an image-level loss, a feature-level loss, and a total variation loss, can achieve local and global consistency both in shallow and deep levels of features. The total variation loss is introduced into the deep-learning-based cloud removal task for the first time to eliminate the color and texture discontinuity around cloud outlines needing repair. On the WHU cloud dataset with diverse land cover scenes and different imaging conditions, our experimental results demonstrated that our method consistently reconstructed the cloud and cloud shadow pixels in various remote sensing images and outperformed several mainstream deep-learning-based methods and a conventional method for every indicator by a large margin.
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Stubenrauch, C. J., S. Cros, A. Guignard, and N. Lamquin. "A 6-year global cloud climatology from the Atmospheric InfraRed Sounder AIRS and a statistical analysis in synergy with CALIPSO and CloudSat." Atmospheric Chemistry and Physics Discussions 10, no. 3 (March 30, 2010): 8247–96. http://dx.doi.org/10.5194/acpd-10-8247-2010.
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Abstract. We present a six-year global climatology of cloud properties, obtained from observations of the Atmospheric Infrared Sounder (AIRS) onboard the NASA Aqua satellite. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined with CloudSat observations, both missions launched as part of the A-Train in 2006, provide a unique opportunity to evaluate the retrieved AIRS cloud properties such as cloud amount and height as well as to explore the vertical structure of different cloud types. AIRS-LMD cloud detection agrees with CALIPSO about 85% over ocean and about 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.
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Stubenrauch, C. J., S. Cros, A. Guignard, and N. Lamquin. "A 6-year global cloud climatology from the Atmospheric InfraRed Sounder AIRS and a statistical analysis in synergy with CALIPSO and CloudSat." Atmospheric Chemistry and Physics 10, no. 15 (August 6, 2010): 7197–214. http://dx.doi.org/10.5194/acp-10-7197-2010.
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Abstract. We present a six-year global climatology of cloud properties, obtained from observations of the Atmospheric Infrared Sounder (AIRS) onboard the NASA Aqua satellite. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined with CloudSat observations, both missions launched as part of the A-Train in 2006, provide a unique opportunity to evaluate the retrieved AIRS cloud properties such as cloud amount and height. In addition, they permit to explore the vertical structure of different cloud types. AIRS-LMD cloud detection agrees with CALIPSO about 85% over 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.
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Schreiner, Anthony J., Steven A. Ackerman, Bryan A. Baum, and Andrew K. Heidinger. "A Multispectral Technique for Detecting Low-Level Cloudiness near Sunrise." Journal of Atmospheric and Oceanic Technology 24, no. 10 (October 1, 2007): 1800–1810. http://dx.doi.org/10.1175/jtech2092.1.
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Abstract A technique using the Geostationary Operational Environmental Satellite (GOES) sounder radiance data has been developed to improve detection of low clouds and fog just after sunrise. The technique is based on a simple difference method using the shortwave (3.7 μm) and longwave (11.0 μm) window bands in the infrared range of the spectrum. The time period just after sunrise is noted for the difficulty in being able to correctly identify low clouds and fog over land. For the GOES sounder cloud product this difficulty is a result of the visible reflectance of the low clouds falling below the “cloud” threshold over land. By requiring the difference between the 3.7- and the 11.0-μm bands to be greater than 5.0 K, successful discrimination of low clouds and fog is found 85% of the time for 21 cases from 14 September 2005 to 6 March 2006 over the GOES-12 sounder domain. For these 21 clear and cloudy cases the solar zenith angle ranged from 87° to 77°; however, the range of solar zenith angles for cloudy cases was from 85° to 77°. The success rate further improved to 95% (20 out of 21 cases) by including a difference threshold of 5.0 K between the 3.7- and 4.0-μm bands, requiring that the 11.0-μm band be greater than 260 K, and limiting the test to fields of view where the surface elevation is below 999 m. These final three limitations were needed to more successfully deal with cases involving snow cover and dead vegetation. To ensure that only the time period immediately after sunrise is included the solar zenith angle threshold for application of these tests is between 89° and 70°.
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Narendra Reddy, Nelli, Madineni Venkat Ratnam, Ghouse Basha, and Varaha Ravikiran. "Cloud vertical structure over a tropical station obtained using long-term high-resolution radiosonde measurements." Atmospheric Chemistry and Physics 18, no. 16 (August 17, 2018): 11709–27. http://dx.doi.org/10.5194/acp-18-11709-2018.
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Abstract. Cloud vertical structure, including top and base altitudes, thickness of cloud layers, and the vertical distribution of multilayer clouds, affects large-scale atmosphere circulation by altering gradients in the total diabatic heating and cooling and latent heat release. In this study, long-term (11 years) observations of high-vertical-resolution radiosondes are used to obtain the cloud vertical structure over a tropical station at Gadanki (13.5∘ N, 79.2∘ E), India. The detected cloud layers are verified with independent observations using cloud particle sensor (CPS) sonde launched from the same station. High-level clouds account for 69.05 %, 58.49 %, 55.5 %, and 58.6 % of all clouds during the pre-monsoon, monsoon, post-monsoon, and winter seasons, respectively. The average cloud base (cloud top) altitudes for low-level, middle-level, high-level, and deep convective clouds are 1.74 km (3.16 km), 3.59 km (5.55 km), 8.79 km (10.49 km), and 1.22 km (11.45 km), respectively. Single-layer, two-layer, and three-layer clouds account for 40.80 %, 30.71 %, and 19.68 % of all cloud configurations, respectively. Multilayer clouds occurred more frequently during the monsoon with 34.58 %. Maximum cloud top altitude and cloud thickness occurred during the monsoon season for single-layer clouds and the uppermost layer of multiple-layer cloud configurations. In multilayer cloud configurations, diurnal variations in the thickness of upper-layer clouds are larger than those of lower-layer clouds. Heating and cooling in the troposphere and lower stratosphere due to these cloud layers are also investigated and peak cooling (peak warming) is found below (above) the cold-point tropopause (CPT) altitude. The magnitude of cooling (warming) increases from single-layer to four- or more-layer cloud occurrence. Further, the vertical structure of clouds is also studied with respect to the arrival date of the Indian summer monsoon over Gadanki.
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Kumar, Brijesh, and Amrita Saraswat. "Security on Cloud using High Level Encryption Techniques." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (October 31, 2017): 915–18. http://dx.doi.org/10.31142/ijtsrd4712.
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Song, Hua, Wuyin Lin, Yanluan Lin, Audrey B. Wolf, Leo J. Donner, Anthony D. Del Genio, Roel Neggers, Satoshi Endo, and Yangang Liu. "Evaluation of Cloud Fraction Simulated by Seven SCMs against the ARM Observations at the SGP Site*." Journal of Climate 27, no. 17 (August 28, 2014): 6698–719. http://dx.doi.org/10.1175/jcli-d-13-00555.1.
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Abstract This study evaluates the performances of seven single-column models (SCMs) by comparing simulated cloud fraction with observations at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site from January 1999 to December 2001. Compared with the 3-yr mean observational cloud fraction, the ECMWF SCM underestimates cloud fraction at all levels and the GISS SCM underestimates cloud fraction at levels below 200 hPa. The two GFDL SCMs underestimate lower-to-middle level cloud fraction but overestimate upper-level cloud fraction. The three Community Atmosphere Model (CAM) SCMs overestimate upper-level cloud fraction and produce lower-level cloud fraction similar to the observations but as a result of compensating overproduction of convective cloud fraction and underproduction of stratiform cloud fraction. Besides, the CAM3 and CAM5 SCMs both overestimate midlevel cloud fraction, whereas the CAM4 SCM underestimates. The frequency and partitioning analyses show a large discrepancy among the seven SCMs: Contributions of nonstratiform processes to cloud fraction production are mainly in upper-level cloudy events over the cloud cover range 10%–80% in SCMs with prognostic cloud fraction schemes and in lower-level cloudy events over the cloud cover range 15%–50% in SCMs with diagnostic cloud fraction schemes. Further analysis reveals different relationships between cloud fraction and relative humidity (RH) in the models and observations. The underestimation of lower-level cloud fraction in most SCMs is mainly due to the larger threshold RH used in models. The overestimation of upper-level cloud fraction in the three CAM SCMs and two GFDL SCMs is primarily due to the overestimation of RH and larger mean cloud fraction of cloudy events plus more occurrences of RH around 40%–80%, respectively.
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Marchant, Benjamin, Steven Platnick, Kerry Meyer, G. Thomas Arnold, and Jérôme Riedi. "MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP." Atmospheric Measurement Techniques 9, no. 4 (April 11, 2016): 1587–99. http://dx.doi.org/10.5194/amt-9-1587-2016.
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Abstract. Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy 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.
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Marchant, B., S. Platnick, K. Meyer, G. T. Arnold, and J. Riedi. "MODIS Collection 6 shortwave-derived cloud phase classification algorithm and comparisons with CALIOP." Atmospheric Measurement Techniques Discussions 8, no. 11 (November 16, 2015): 11893–924. http://dx.doi.org/10.5194/amtd-8-11893-2015.
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Abstract. Cloud thermodynamic phase (ice, liquid, undetermined) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy 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.
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Rossow, William B., and Yuanchong Zhang. "Evaluation of a Statistical Model of Cloud Vertical Structure Using Combined CloudSat and CALIPSO Cloud Layer Profiles." Journal of Climate 23, no. 24 (December 15, 2010): 6641–53. http://dx.doi.org/10.1175/2010jcli3734.1.
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Abstract A model of the three-dimensional distribution of clouds was developed from the statistics of cloud layer occurrence from the International Satellite Cloud Climatology Project (ISCCP) and the statistics of cloud vertical structure (CVS) from an analysis of radiosonde humidity profiles. The CVS model associates each cloud type, defined by cloud-top pressure of the topmost cloud layer and total column optical thickness, with a particular CVS. The advent of satellite cloud radar (CloudSat) and lidar [Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements (together C&C) of CVS allows for a quantitative evaluation of this statistical model. The zonal monthly-mean cloud layer distribution from the ISCCP CVS agrees with that from C&C to within 10% (when normalized to the same total cloud amount). The largest differences are an overestimate of middle-level cloudiness in winter polar regions, an overestimate of cloud-top pressures of the highest-level clouds, especially in the tropics, and an underestimate of low-level cloud amounts over southern midlatitude oceans. A more severe test of the hypothesized relationship is made by comparing CVS for individual satellite pixels. The agreement of CVS is good for isolated low-level clouds and reasonably good when the uppermost cloud layer is a high-level cloud; however, the agreement is not good when the uppermost cloud layer is a middle-level cloud, even when ISCCP correctly locates cloud top. An improved CVS model combining C&C and ISCCP may require classification at spatial scales larger than individual satellite pixels.
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Cesana, G., D. E. Waliser, D. Henderson, T. S. L’Ecuyer, X. Jiang, and J. L. F. Li. "The Vertical Structure of Radiative Heating Rates: A Multimodel Evaluation Using A-Train Satellite Observations." Journal of Climate 32, no. 5 (February 7, 2019): 1573–90. http://dx.doi.org/10.1175/jcli-d-17-0136.1.
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Abstract We assess the vertical distribution of radiative heating rates (RHRs) in climate models using a multimodel experiment and A-Train satellite observations, for the first time. As RHRs rely on the representation of cloud amount and properties, we first compare the modeled vertical distribution of clouds directly against lidar–radar combined cloud observations (i.e., without simulators). On a near-global scale (50°S–50°N), two systematic differences arise: an excess of high-level clouds around 200 hPa in the tropics, and a general lack of mid- and low-level clouds compared to the observations. Then, using RHR profiles calculated with constraints from A-Train and reanalysis data, along with their associated maximum uncertainty estimates, we show that the excess clouds and ice water content in the upper troposphere result in excess infrared heating in the vicinity of and below the clouds as well as a lack of solar heating below the clouds. In the lower troposphere, the smaller cloud amount and the underestimation of cloud-top height is coincident with a shift of the infrared cooling to lower levels, substantially reducing the greenhouse effect, which is slightly compensated by an erroneous excess absorption of solar radiation. Clear-sky RHR differences between the observations and the models mitigate cloudy RHR biases in the low levels while they enhance them in the high levels. Finally, our results indicate that a better agreement between observed and modeled cloud profiles could substantially improve the RHR profiles. However, more work is needed to precisely quantify modeled cloud errors and their subsequent effect on RHRs.
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Sporre, M. K., E. Swietlicki, P. Glantz, and M. Kulmala. "Aerosol indirect effects on continental low-level clouds over Sweden and Finland." Atmospheric Chemistry and Physics Discussions 14, no. 9 (May 21, 2014): 12931–66. http://dx.doi.org/10.5194/acpd-14-12931-2014.
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Abstract. Aerosol effects on low-level clouds over the nordic countries are investigated by combining in situ ground-based aerosol measurements with remote sensing data of clouds and precipitation. Ten years of number size distribution data from two aerosol measurement stations (Vavihill, Sweden and Hyytiälä, Finland) provide aerosol number concentrations in the atmospheric boundary layer. This is combined with cloud satellite data from the Moderate Resolution Imaging Spectroradiometer and weather radar data from the Baltic Sea Experiment. Also, how the meteorological conditions affect the clouds are investigated using reanalysis data from the European Centre for Medium-Range Forecasts. The cloud droplet effective radius is found to decrease when the aerosol number concentration increases, while the cloud optical thickness does not vary with boundary layer aerosol number concentrations. Furthermore, the aerosol cloud interaction parameter (ACI), a measure of how the effective radius is influenced by the number concentration of cloud active particles, is found to be somewhere between 0.10 and 0.18 and the magnitude of the ACI is greatest when the number concentration of particles with a diameter larger than 130 nm is used. Lower precipitation intensity in the weather radar images is associated with higher aerosol number concentrations. In addition, at Hyytiälä the particle number concentrations is generally higher for non-precipitating cases than for precipitating cases. The apparent absence of the first indirect effect of aerosols on low-level clouds over land raises questions regarding the magnitude of the indirect aerosol radiative forcing.
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Sporre, M. K., E. Swietlicki, P. Glantz, and M. Kulmala. "Aerosol indirect effects on continental low-level clouds over Sweden and Finland." Atmospheric Chemistry and Physics 14, no. 22 (November 19, 2014): 12167–79. http://dx.doi.org/10.5194/acp-14-12167-2014.
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Abstract. Aerosol effects on low-level clouds over the Nordic Countries are investigated by combining in situ ground-based aerosol measurements with remote sensing data of clouds and precipitation. Ten years of number size distribution data from two aerosol measurement stations (Vavihill, Sweden and Hyytiälä, Finland) provide aerosol number concentrations in the atmospheric boundary layer. This is combined with cloud satellite data from the Moderate Resolution Imaging Spectroradiometer and weather radar data from the Baltic Sea Experiment. Also, how the meteorological conditions affect the clouds is investigated using reanalysis data from the European Centre for Medium-Range Weather Forecasts. The cloud droplet effective radius is found to decrease when the aerosol number concentration increases, while the cloud optical thickness does not vary with boundary layer aerosol number concentrations. Furthermore, the aerosol–cloud interaction parameter (ACI), a measure of how the effective radius is influenced by the number concentration of cloud active particles, is found to be somewhere between 0.10 and 0.18 and the magnitude of the ACI is greatest when the number concentration of particles with a diameter larger than 130 nm is used. Lower precipitation intensity in the weather radar images is associated with higher aerosol number concentrations. In addition, at Hyytiälä the particle number concentrations is generally higher for non-precipitating cases than for precipitating cases. The apparent absence of the first indirect effect of aerosols on low-level clouds over land raises questions regarding the magnitude of the indirect aerosol radiative forcing.
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Chang, Fu-Lung, and James A. Coakley. "Relationships between Marine Stratus Cloud Optical Depth and Temperature: Inferences from AVHRR Observations." Journal of Climate 20, no. 10 (May 15, 2007): 2022–36. http://dx.doi.org/10.1175/jcli4115.1.
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Abstract Studies using International Satellite Cloud Climatology Project (ISCCP) data have reported decreases in cloud optical depth with increasing temperature, thereby suggesting a positive feedback in cloud optical depth as climate warms. The negative cloud optical depth and temperature relationships are questioned because ISCCP employs threshold assumptions to identify cloudy pixels that have included partly cloudy pixels. This study applies the spatial coherence technique to one month of Advanced Very High Resolution Radiometer (AVHRR) data over the Pacific Ocean to differentiate overcast pixels from the partly cloudy pixels and to reexamine the cloud optical depth–temperature relationships. For low-level marine stratus clouds studied here, retrievals from partly cloudy pixels showed 30%–50% smaller optical depths, 1°–4°C higher cloud temperatures, and slightly larger droplet effective radii, when they were compared to retrievals from the overcast pixels. Despite these biases, retrievals for the overcast and partly cloudy pixels show similar negative cloud optical depth–temperature relationships and their magnitudes agree with the ISCCP results for the midlatitude and subtropical regions. There were slightly negative droplet effective radius–temperature relationships, and considerable positive cloud liquid water content–temperature relationships indicated by aircraft measurements. However, cloud thickness decreases appear to be the main reason why cloud optical depth decreases with increasing temperature. Overall, cloud thickness thinning may explain why similar negative cloud optical depth–temperature relationships are found in both overcast and partly cloudy pixels. In addition, comparing the cloud-top temperature to the air temperature at 740 hPa indicates that cloud-top height generally rises with warming. This suggests that the cloud thinning is mainly due to the ascending of cloud base. The results presented in this study are confined to the midlatitude and subtropical Pacific and may not be applicable to the Tropics or other regions.
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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.
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Abstract Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System (EOS) Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that present difficulties for retrieving cloud effective radius using single-layer plane-parallel cloud models. The algorithm uses the MODIS 0.94-μm water vapor band along with CO2 bands to obtain two above-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.
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Wang, P., and P. Stammes. "Evaluation of SCIAMACHY Oxygen A band cloud heights using Cloudnet measurements." Atmospheric Measurement Techniques 7, no. 5 (May 19, 2014): 1331–50. http://dx.doi.org/10.5194/amt-7-1331-2014.
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Abstract. Two SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) O2 A band cloud height products are evaluated using ground-based radar/lidar measurements between January 2003 and December 2011. The products are the ESA (European Space Agency) Level 2 (L2) version 5.02 cloud top height and the FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A band) version 6 cloud height. The radar/lidar profiles are obtained at the Cloudnet sites of Cabauw and Lindenberg, and are averaged for 1 h centered at the SCIAMACHY overpass time. In total we have 217 cases of single-layer clouds and 204 cases of multilayer clouds. We find that the ESA L2 cloud top height has a better agreement with the Cloudnet cloud top height than the Cloudnet cloud middle height. The ESA L2 cloud top height is on average 0.4 km higher than the Cloudnet cloud top height, with a standard deviation of 3.1 km. The FRESCO cloud height is closer to the Cloudnet cloud middle height than the Cloudnet cloud top height. The mean difference between the FRESCO cloud height and the Cloudnet cloud middle height is −0.1 km with a standard deviation of 1.9 km. The ESA L2 cloud top height is higher than the FRESCO cloud height. The differences between the SCIAMACHY cloud (top) height and the Cloudnet cloud top height are linked to cloud optical thickness. The SCIAMACHY cloud height products are further compared to the Cloudnet cloud top height and the Cloudnet cloud middle height in 1 km bins. For single-layer clouds, the difference between the ESA L2 cloud top height and the Cloudnet cloud top height is less than 1 km for each cloud bin at 3–7 km. The difference between the FRESCO cloud height and the Cloudnet cloud middle height is less than 1 km for each cloud bin at 0–6 km. The results are similar for multilayer clouds, but the percentage of cases having a bias within 1 km is smaller than for single-layer clouds. We may conclude that the FRESCO cloud height is accurate for low and middle level clouds, whereas the ESA L2 cloud top height is more accurate for middle level clouds. Both products are less accurate for high clouds.
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Jammalamadaka, Sastry Kodanda Rama, Kamesh Bala Krishna Duvvuri, Devi Anusha CH, Padmini P, and Siva Anjaneyulu G. "Building Fault Tollrence within Clouds at Network Level." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 4 (August 1, 2016): 1560. http://dx.doi.org/10.11591/ijece.v6i4.10676.
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<span>Cloud computing technologies and infrastructure facilities are coming up in a big way making it cost effective for the users to implement their IT based solutions to run business in most cost-effective and economical way. Many intricate issues however, have cropped-up which must be addressed to be able to use clouds the purpose for which they are designed and implemented. Among all, fault tolerance and securing the data stored on the clouds takes most of the importance. Continuous availability of the services is dependent on many factors. Faults bound to happen within a network, software, and platform or within the infrastructure which are all used for establishing the cloud. The network that connects various servers, devices, peripherals etc., have to be fault tolerant to start-with so that intended and un-interrupted services to the user can be made available. A novel network design method that leads to achieve high availability of the network and thereby the cloud itself has been presented in this paper</span>
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Jammalamadaka, Sastry Kodanda Rama, Kamesh Bala Krishna Duvvuri, Devi Anusha CH, Padmini P, and Siva Anjaneyulu G. "Building Fault Tollrence within Clouds at Network Level." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 4 (August 1, 2016): 1560. http://dx.doi.org/10.11591/ijece.v6i4.pp1560-1569.
Full textAbstract:
<span>Cloud computing technologies and infrastructure facilities are coming up in a big way making it cost effective for the users to implement their IT based solutions to run business in most cost-effective and economical way. Many intricate issues however, have cropped-up which must be addressed to be able to use clouds the purpose for which they are designed and implemented. Among all, fault tolerance and securing the data stored on the clouds takes most of the importance. Continuous availability of the services is dependent on many factors. Faults bound to happen within a network, software, and platform or within the infrastructure which are all used for establishing the cloud. The network that connects various servers, devices, peripherals etc., have to be fault tolerant to start-with so that intended and un-interrupted services to the user can be made available. A novel network design method that leads to achieve high availability of the network and thereby the cloud itself has been presented in this paper</span>
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Aebi, Christine, Julian Gröbner, Niklaus Kämpfer, and Laurent Vuilleumier. "Cloud radiative effect, cloud fraction and cloud type at two stations in Switzerland using hemispherical sky cameras." Atmospheric Measurement Techniques 10, no. 12 (November 30, 2017): 4587–600. http://dx.doi.org/10.5194/amt-10-4587-2017.
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Abstract. The current study analyses the cloud radiative effect during the daytime depending on cloud fraction and cloud type at two stations in Switzerland over a time period of 3 to 5 years. Information on fractional cloud coverage and cloud type is retrieved from images taken by visible all-sky cameras. Cloud-base height (CBH) data are retrieved from a ceilometer and integrated water vapour (IWV) data from GPS measurements. The longwave cloud radiative effect (LCE) for low-level clouds and a cloud coverage of 8 oktas has a median value between 59 and 72 Wm−2. For mid- and high-level clouds the LCE is significantly lower. It is shown that the fractional cloud coverage, the CBH and IWV all have an influence on the magnitude of the LCE. These observed dependences have also been modelled with the radiative transfer model MODTRAN5. The relative values of the shortwave cloud radiative effect (SCErel) for low-level clouds and a cloud coverage of 8 oktas are between −90 and −62 %. Also here the higher the cloud is, the less negative the SCErel values are. In cases in which the measured direct radiation value is below the threshold of 120 Wm−2 (occulted sun) the SCErel decreases substantially, while cases in which the measured direct radiation value is larger than 120 Wm−2 (visible sun) lead to a SCErel of around 0 %. In 14 and 10 % of the cases in Davos and Payerne respectively a cloud enhancement has been observed with a maximum in the cloud class cirrocumulus–altocumulus at both stations. The calculated median total cloud radiative effect (TCE) values are negative for almost all cloud classes and cloud coverages.
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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.
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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.
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Naud, C. M., J. P. Muller, E. E. Clothiaux, B. A. Baum, and W. P. Menzel. "Intercomparison of multiple years of MODIS, MISR and radar cloud-top heights." Annales Geophysicae 23, no. 7 (October 14, 2005): 2415–24. http://dx.doi.org/10.5194/angeo-23-2415-2005.
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Abstract. Radar cloud-top heights were retrieved at both the Chilbolton Facility for Atmospheric and Radio Research, UK (CFARR) and the ARM Southern Great Plain site, USA (SGP), using millimetre wave cloud radars and identical algorithms. The resulting cloud-top heights were used for comparison with MODIS and MISR retrieved cloud-top heights, from March 2000 to October 2003. Both imaging instruments reside on the NASA Earth Observing System (EOS) Terra platform launched in 1999. MODIS and MISR cloud-top products were from the recent collections (4 and 3, respectively) that cover the entire mission. The cloud characteristics are different at each ground site, with clouds generally residing at higher altitudes at SGP, but with a greater occurrence of broken or multilayered clouds at CFARR. A method is presented to automatically eliminate scenes where clouds are of a broken nature, since it is difficult in these conditions to ensure that ground-based and satellite measurements refer to the same cloud deck. The intercomparison between MODIS and radar cloud-top heights reveals that MODIS cloud-top heights agree with radar within about 1km for mid- and high-level clouds. However, this accuracy is degraded to nearly 3 km for low-level clouds. MISR cloud-top heights are found to agree with radar cloud-top heights to within 0.6 km, which is in line with theoretical expectations. In single-level cloud situations MODIS and MISR cloud-top heights tend to agree within 1 km. This comparison also reveals that the loss of radar sensitivity during 2001 resulted in the CFARR instrument being less accurate for high-level cloud-top height measurements. Keywords. Atmospheric composition and structure (Instruments and techniques)
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Huo, Juan, and Daren Lu. "Physical Properties of High-Level Cloud over Land and Ocean from CloudSat–CALIPSO Data." Journal of Climate 27, no. 23 (December 1, 2014): 8966–78. http://dx.doi.org/10.1175/jcli-d-14-00329.1.
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Abstract Unlike other cloud types, high-level clouds play an important role, often imposing a warming effect, in the earth–atmosphere radiative energy budget. In this paper, macro- and microphysical characteristics of cirrus clouds, such as their occurrence frequency, geometric scale, water content, and particle size, over northern China (land area, herein called the L area) and the Pacific Ocean (ocean area, herein the O area) are analyzed and compared based on CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) products from 1 January 2007 to 31 December 2010. Over both areas, statistical analysis shows that cirrus occurrence approached 33% in summer whereas it was only ~10% in winter, >50% of cirrus cloud thicknesses were in the range of ~(0.25–1.5) km, there were >98% ice particles in high-level clouds, and temperature had a closer linear relationship with ice effective radius (IER) than height. Also, the seasonal difference of this linear relationship is minor over both land and ocean. Comparisons reveal that the mean occurrence frequency, mean cloud thickness, range of cloud-base and cloud-top height, IER, and ice water content of cirrus in summer were generally greater in winter, and greater over the O area than over the L area. However, the relationship between IER and temperature over land is close to that over ocean.
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Lima, Prijith, Sesha Sai, Rao, Niranjan, and Ramana. "Retrieval and Validation of Cloud Top Temperature from the Geostationary Satellite INSAT-3D." Remote Sensing 11, no. 23 (November 27, 2019): 2811. http://dx.doi.org/10.3390/rs11232811.
Full textAbstract:
Investigation of cloud top temperature (CTT) and its diurnal variation is highly reliant on high spatial and temporal resolution satellite data, which is lacking over the Indian region. An algorithm has been developed for detection of clouds and retrieval of CTT from the geostationary satellite INSAT-3D. These retrievals are validated (inter-compared) with collocated in-situ (satellite) measurements with specific intent to generate climate-quality data. The cloud detection algorithm employs nine different tests, in accordance with solar illumination, satellite angle and surface type conditions to generate pixel-resolution cloud mask. Validation of cloud mask with cloud-aerosol lidar with orthogonal polarization (CALIOP) shows that probability of detection (POD) of cloudy (clear) sky is 81% (85%), with 83% hit rate. The algorithm is also implemented on similar channels of moderate resolution imaging spectroradiometer (MODIS), which provides 88% (83%) POD of cloudy (clear) sky, with 86% hit rate. CTT retrieval is done at the pixel level, for all cloud pixels, by employing appropriate methods for various types of clouds. Comparison of CTT with radiosonde and cloud-aerosol lidar and infrared pathfinder satellite observations (CALIPSO) shows mean absolute error less than 3%. The study also examines sensitivity of retrieved CTT to the cloud classification scheme and retrieval criteria. Validation results and their close agreements with those of similar satellites demonstrate the reliability of the retrieved product for climate studies.
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Dearden, Christopher, Adrian Hill, Hugh Coe, and Tom Choularton. "The role of droplet sedimentation in the evolution of low-level clouds over southern West Africa." Atmospheric Chemistry and Physics 18, no. 19 (October 9, 2018): 14253–69. http://dx.doi.org/10.5194/acp-18-14253-2018.
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Abstract. Large-eddy simulations are performed to investigate the influence of cloud microphysics on the evolution of low-level clouds that form over southern West Africa during the monsoon season. We find that, even in clouds that are not precipitating, the size of cloud droplets has a non-negligible effect on liquid water path. This is explained through the effects of droplet sedimentation, which acts to remove liquid water from the entrainment zone close to cloud top, increasing the liquid water path. Sedimentation also produces a more heterogeneous cloud structure and lowers cloud base height. Our results imply that an appropriate parameterization of the effects of sedimentation is required to improve the representation of the diurnal cycle of the atmospheric boundary layer over southern West Africa in large-scale models.
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Shin, Jihoon, and Sungsu Park. "The relationship between low-level cloud amount and its proxies over the globe by cloud type." Atmospheric Chemistry and Physics 20, no. 5 (March 13, 2020): 3041–60. http://dx.doi.org/10.5194/acp-20-3041-2020.
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Abstract. We extend upon previous work to examine the relationship between low-level cloud amount (LCA) and various proxies for LCA – estimated low-level cloud fraction (ELF), lower tropospheric stability (LTS), and estimated inversion strength (EIS) – by low-level cloud type (CL) over the globe using individual surface and upper-air observations. Individual CL has its own distinct environmental structure, and therefore our extended analysis by CL can provide insights into the strengths and weaknesses of various proxies and help to improve them. Overall, ELF performs better than LTS and EIS in diagnosing the variations in LCA among various CLs, indicating that a previously identified superior performance of ELF compared to LTS and EIS as a global proxy for LCA comes from its realistic correlations with various CLs rather than with a specific CL. However, ELF, LTS, and EIS have a problem in diagnosing the changes in LCA when noCL (no low-level cloud) is reported and also when Cu (cumulus) is reported over deserts where background stratus does not exist. This incorrect diagnosis of noCL as a cloudy condition is more clearly seen in the analysis of individual CL frequencies binned by proxy values. If noCL is excluded, ELF, LTS, and EIS have good inter-CL correlations with the amount when present (AWP) of individual CLs. In the future, an advanced ELF needs to be formulated to deal with the decrease in LCA when the inversion base height is lower than the lifting condensation level to diagnose cumulus updraft fraction, as well as the amount of stratiform clouds and detrained cumulus, and to parameterize the scale height as a function of appropriate environmental variables.
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Yue, Zhiguo, Daniel Rosenfeld, Guihua Liu, Jin Dai, Xing Yu, Yannian Zhu, Eyal Hashimshoni, Xiaohong Xu, Ying Hui, and Oliver Lauer. "Automated Mapping of Convective Clouds (AMCC) Thermodynamical, Microphysical, and CCN Properties from SNPP/VIIRS Satellite Data." Journal of Applied Meteorology and Climatology 58, no. 4 (April 2019): 887–902. http://dx.doi.org/10.1175/jamc-d-18-0144.1.
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AbstractThe advent of the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi NPP (SNPP) satellite made it possible to retrieve a new class of convective cloud properties and the aerosols that they ingest. An automated mapping system of retrieval of some properties of convective cloud fields over large areas at the scale of satellite coverage was developed and is presented here. The system is named Automated Mapping of Convective Clouds (AMCC). The input is level-1 VIIRS data and meteorological gridded data. AMCC identifies the cloudy pixels of convective elements; retrieves for each pixel its temperature T and cloud drop effective radius re; calculates cloud-base temperature Tb based on the warmest cloudy pixels; calculates cloud-base height Hb and pressure Pb based on Tb and meteorological data; calculates cloud-base updraft Wb based on Hb; calculates cloud-base adiabatic cloud drop concentrations Nd,a based on the T–re relationship, Tb, and Pb; calculates cloud-base maximum vapor supersaturation S based on Nd,a and Wb; and defines Nd,a/1.3 as the cloud condensation nuclei (CCN) concentration NCCN at that S. The results are gridded 36 km × 36 km data points at nadir, which are sufficiently large to capture the properties of a field of convective clouds and also sufficiently small to capture aerosol and dynamic perturbations at this scale, such as urban and land-use features. The results of AMCC are instrumental in observing spatial covariability in clouds and CCN properties and for obtaining insights from such observations for natural and man-made causes. AMCC-generated maps are also useful for applications from numerical weather forecasting to climate models.
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Lihavainen, H., V. M. Kerminen, M. Komppula, A. P. Hyvärinen, J. Laakia, S. Saarikoski, U. Makkonen, et al. "Measurements of the relation between aerosol properties and microphysics and chemistry of low level liquid water clouds in Northern Finland." Atmospheric Chemistry and Physics 8, no. 23 (December 1, 2008): 6925–38. http://dx.doi.org/10.5194/acp-8-6925-2008.
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Abstract. Physical and chemical properties of boundary layer clouds, together with relevant aerosol properties, were investigated during the first Pallas Cloud Experiment (First Pace) conducted in northern Finland between 20 October and 9 November 2004. Two stations located 6 km apart from each other at different altitudes were employed in measurements. The low-altitude station was always below the cloud layer, whereas the high-altitude station was inside clouds about 75% of the time during the campaign. Direct measurements of cloud droplet populations showed that our earlier approach of determining cloud droplet residual particle size distributions and corresponding activated fractions using continuous aerosol number size distribution measurements at the two stations is valid, as long as the cloud events are carefully screened to exclude precipitating clouds and to make sure the same air mass has been measured at both stations. We observed that a non-negligible fraction of cloud droplets originated from Aitken mode particles even at moderately-polluted air masses. We found clear evidence on first indirect aerosol effect on clouds but demonstrated also that no simple relation between the cloud droplet number concentration and aerosol particle number concentration exists for this type of clouds. The chemical composition of aerosol particles was dominated by particulate organic matter (POM) and sulphate in continental air masses and POM, sodium and chlorine in marine air masses. The inorganic composition of cloud water behaved similarly to that of the aerosol phase and was not influenced by inorganic trace gases.
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Blythe, Kurt. "A Faceted Catalogue Aids Doctoral-Level Searchers." Evidence Based Library and Information Practice 3, no. 3 (September 3, 2008): 80. http://dx.doi.org/10.18438/b8jk6v.
Full textAbstract:
A Review of:
Olson, Tod A. “Utility of a Faceted Catalog for Scholarly Research” Library Hi Tech 25.4 (2007): 550-61.
Objective – To learn whether a faceted catalogue and word cloud aids in the discovery process.
Design – User study.
Setting – Large academic research library in the United States.
Subjects – Twelve PhD candidates in the humanities, the majority of whom are engaged with researching, proposing, or writing their dissertations.
Methods – The library’s entire catalogue of 5.2 million records was loaded into the AquaBrowser OPAC search interface. A pilot study was conducted using three humanities graduate students employed by the library. Following the pilot, the main study was conducted using graduate students in the humanities. Graduate students in the social sciences were desired for the study, but were not able to be contacted due to time constraints. Once selected, the test subjects were asked to use an interface that offered both facets and tag clouds for enhanced search quality. Test subjects were allowed to choose the topic they would like to research; all chose to research their dissertation topic. A moderator and recorder facilitated research conducted with the faceted catalogue. The moderator ensured that students commented on their findings, cleared up any confusion with using the interface, and kept the students on task. Only when students remarked that a new discovery had been made were those discoveries noted. The impact to the discovery process of faceted navigation and AquaBrowser’s word cloud was studied while the impact of relevance ranking was not.
Main Results – The article asserts that results from both the pilot and main study were sufficiently similar to justify combining them for the paper, but the advantage that students employed by the library might have over other students is not discussed. Nine of the twelve students used in the study found new results using the faceted catalogue and word cloud. The responses of the user group to the faceted catalogue and word cloud were “overwhelmingly positive” (555). However, since students were allowed to move freely between the word cloud and faceted navigation tool, it is difficult to attribute new discoveries solely to one or the other. However, when a new discovery could be “attributed primarily to one factor or another” (555) it was noted. The faceted navigation tool aided discovery at least four times and the word cloud aided discovery at least six.
Conclusion – A faceted catalogue interface with a word cloud feature clearly aids in the discovery process for more advanced researchers—those with specialized subject knowledge, familiarity with their library’s collection, and experience in researching their area. However, facets and word clouds have limitations: records with limited cataloguing have little to offer faceted navigation; catalogue records from diverse providers introduce controlled vocabularies beyond LCSH and MeSH into search returns, resulting in the same word potentially appearing multiple times in the same return albeit with different meanings; the word cloud may contain certain words that researchers feel to be irrelevant. Despite these issues, the use of word clouds and faceted navigation (and relevance ranking) appears to be beneficial to research conducted by experienced subject searchers in the humanities.