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1
Tompkins, Adrian M., and Francesca Di Giuseppe. "An Interpretation of Cloud Overlap Statistics." Journal of the Atmospheric Sciences 72, no. 8 (August 1, 2015): 2877–89. http://dx.doi.org/10.1175/jas-d-14-0278.1.
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Abstract Observational studies have shown that the vertical overlap of cloudy layers separated by clear sky can exceed that of the random overlap assumption, suggesting a tendency toward minimum overlap. In addition, the rate of decorrelation of vertically continuous clouds with increasing layer separation is sensitive to the horizontal scale of the cloud scenes used. The authors give a heuristic argument that these phenomena result from data truncation, where overcast or single cloud layers are removed from the analysis. This occurs more frequently as the cloud sampling scale falls progressively below the typical cloud system scale. The postulate is supported by sampling artificial cyclic and subsequently more realistic fractal cloud scenes at various length scales. The fractal clouds indicate that the degree of minimal overlap diagnosed in previous studies for discontinuous clouds could result from sampling randomly overlapped clouds at spatial scales that are 30%–80% of the cloud system scale. Removing scenes with cloud cover exceeding 50% from the analysis reduces the impact of data truncation, with discontinuous clouds not minimally overlapped and the decorrelation of continuous clouds less sensitive to the sampling scale. Using CloudSat–CALIPSO data, a decorrelation length scale of approximately 4.0 km is found. In light of these results, the previously documented dependence of overlap decorrelation length scale on latitude is not entirely a physical phenomenon but can be reinterpreted as resulting from sampling cloud systems that increase significantly in size from the tropics to midlatitudes using a fixed sampling scale.
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O’Dell, Christopher W., Peter Bauer, and Ralf Bennartz. "A Fast Cloud Overlap Parameterization for Microwave Radiance Assimilation." Journal of the Atmospheric Sciences 64, no. 11 (November 1, 2007): 3896–909. http://dx.doi.org/10.1175/2006jas2133.1.
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Abstract The assimilation of cloud- and rain-affected radiances in numerical weather prediction systems requires fast and accurate radiative transfer models. One of the largest sources of modeling errors originates from the assumptions regarding the vertical and horizontal subgrid-scale variability of model clouds and precipitation. In this work, cloud overlap assumptions are examined in the context of microwave radiative transfer and used to develop an accurate reference model. A fast cloud overlap algorithm is presented that allows for the accurate simulation of microwave radiances with a small number of radiative transfer calculations. In particular, the errors for a typical two-column approach currently used operationally are found to be relatively large for many cases of cloudy fields containing precipitation, even those with an overall cloud fraction of unity; these errors are largely eliminated by using the new approach presented here, at the cost of a slight increase in computation time. Radiative transfer cloud overlap errors are also evident in simulations when compared to actual satellite observations, in that the biases are somewhat reduced when applying a more accurate treatment of cloud overlap.
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Wu, Xiaoqing, and Xin-Zhong Liang. "Radiative Effects of Cloud Horizontal Inhomogeneity and Vertical Overlap Identified from a Monthlong Cloud-Resolving Model Simulation." Journal of the Atmospheric Sciences 62, no. 11 (November 1, 2005): 4105–12. http://dx.doi.org/10.1175/jas3565.1.
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Abstract The representation of subgrid horizontal and vertical variability of clouds in radiation schemes remains a major challenge for general circulation models (GCMs) due to the lack of cloud-scale observations and incomplete physical understanding. The development of cloud-resolving models (CRMs) in the last decade provides a unique opportunity to make progress in this area of research. This paper extends the study of Wu and Moncrieff to quantify separately the impacts of cloud horizontal inhomogeneity (optical property) and vertical overlap (geometry) on the domain-averaged shortwave and longwave radiative fluxes at the top of the atmosphere and the surface, and the radiative heating profiles. The diagnostic radiation calculations using the monthlong CRM-simulated tropical cloud optical properties and cloud fraction show that both horizontal inhomogeneity and vertical overlap of clouds are equally important for obtaining accurate radiative fluxes and heating rates. This study illustrates an objective approach to use long-term CRM simulations to separate cloud overlap and inhomogeneity effects, based on which GCM representation (such as mosaic treatment) of subgrid cloud–radiation interactions can be evaluated and improved.
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Naud, Catherine M., Anthony Del Genio, Gerald G. Mace, Sally Benson, Eugene E. Clothiaux, and Pavlos Kollias. "Impact of Dynamics and Atmospheric State on Cloud Vertical Overlap." Journal of Climate 21, no. 8 (April 15, 2008): 1758–70. http://dx.doi.org/10.1175/2007jcli1828.1.
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Abstract The observation and representation in general circulation models (GCMs) of cloud vertical overlap are the objects of active research due to their impacts on the earth’s radiative budget. Previous studies have found that vertically contiguous cloudy layers show a maximum overlap between layers up to several kilometers apart but tend toward a random overlap as separations increase. The decorrelation length scale that characterizes the progressive transition from maximum to random overlap changes from one location and season to another and thus may be influenced by large-scale vertical motion, wind shear, or convection. Observations from the U.S. Department of Energy Atmospheric Radiation Measurement program ground-based radars and lidars in midlatitude and tropical locations in combination with reanalysis meteorological fields are used to evaluate how dynamics and atmospheric state influence cloud overlap. For midlatitude winter months, strong synoptic-scale upward motion maintains conditions closer to maximum overlap at large separations. In the tropics, overlap becomes closer to maximum as convective stability decreases. In midlatitude subsidence and tropical convectively stable situations, where a smooth transition from maximum to random overlap is found on average, large wind shears sometimes favor minimum overlap. Precipitation periods are discarded from the analysis but, when included, maximum overlap occurs more often at large separations. The results suggest that a straightforward modification of the existing GCM mixed maximum–random overlap parameterization approach that accounts for environmental conditions can capture much of the important variability and is more realistic than approaches that are only based on an exponential decay transition from maximum to random overlap.
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Li, J., J. Huang, K. Stamnes, T. Wang, Q. Lv, and H. Jin. "A global survey of cloud overlap based on CALIPSO and CloudSat measurements." Atmospheric Chemistry and Physics 15, no. 1 (January 15, 2015): 519–36. http://dx.doi.org/10.5194/acp-15-519-2015.
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Abstract. Using 2B-CLDCLASS-LIDAR (radar–lidar) cloud classification and 2B-FLXHR-LIDAR radiation products from CloudSat over 4 years, this study evaluates the co-occurrence frequencies of different cloud types, analyzes their along-track horizontal scales and cloud radiative effects (CREs), and utilizes the vertical distributions of cloud types to evaluate cloud-overlap assumptions. The statistical results show that high clouds, altostratus (As), altocumulus (Ac) and cumulus (Cu) tend to coexist with other cloud types. However, stratus (St) (or stratocumulus, Sc), nimbostratus (Ns) and convective clouds are much more likely to exhibit individual features than other cloud types. On average, altostratus-over-stratus/stratocumulus cloud systems have a maximum horizontal scale of 17.4 km, with a standard deviation of 23.5 km. Altocumulus-over-cumulus cloud types have a minimum scale of 2.8 km, with a standard deviation of 3.1 km. By considering the weight of each multilayered cloud type, we find that the global mean instantaneous net CREs of multilayered cloud systems during the daytime are approximately −41.3 and −50.2 W m−2, which account for 40.1 and 42.3% of the global mean total net CREs at the top of the atmosphere (TOA) and at the surface, respectively. The radiative contributions of high-over-altocumulus and high-over-stratus/stratocumulus (or cumulus) in the all multilayered cloud systems are dominant due to their frequency. Considering the overlap of cloud types, the cloud fraction based on the random overlap assumption is underestimated over vast oceans, except in the west-central Pacific Ocean warm pool. Obvious overestimations mainly occur over tropical and subtropical land masses. In view of a lower degree of overlap than that predicted by the random overlap assumption to occur over the vast ocean, particularly poleward of 40° S, the study therefore suggests that a linear combination of minimum and random overlap assumptions may further improve the predictions of actual cloud fractions for multilayered cloud types (e.g., As + St/Sc and Ac + St/Sc) over the Southern Ocean. The establishment of a statistical relationship between multilayered cloud types and the environmental conditions (e.g., atmospheric vertical motion, convective stability and wind shear) would be useful for parameterization design of cloud overlap in numerical models.
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Črnivec, Nina, and Bernhard Mayer. "The incorporation of the Tripleclouds concept into the <i>δ</i>-Eddington two-stream radiation scheme: solver characterization and its application to shallow cumulus clouds." Atmospheric Chemistry and Physics 20, no. 17 (September 14, 2020): 10733–55. http://dx.doi.org/10.5194/acp-20-10733-2020.
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Abstract. The treatment of unresolved cloud–radiation interactions in weather and climate models has considerably improved over the recent years, compared to conventional plane-parallel radiation schemes, which previously persisted in these models for multiple decades. One such improvement is the state-of-the-art Tripleclouds radiative solver, which has one cloud-free and two cloudy regions in each vertical model layer and is thereby capable of representing cloud horizontal inhomogeneity. Inspired by the Tripleclouds concept, primarily introduced by Shonk and Hogan (2008), we incorporated a second cloudy region into the widely employed δ-Eddington two-stream method with the maximum-random overlap assumption for partial cloudiness. The inclusion of another cloudy region in the two-stream framework required an extension of vertical overlap rules. While retaining the maximum-random overlap for the entire layer cloudiness, we additionally assumed the maximum overlap of optically thicker cloudy regions in pairs of adjacent layers. This extended overlap formulation implicitly places the optically thicker region towards the interior of the cloud, which is in agreement with the core–shell model for convective clouds. The method was initially applied on a shallow cumulus cloud field, evaluated against a three-dimensional benchmark radiation computation. Different approaches were used to generate a pair of cloud condensates characterizing the two cloudy regions, testing various condensate distribution assumptions along with global cloud variability estimate. Regardless of the exact condensate setup, the radiative bias in the vast majority of Tripleclouds configurations was considerably reduced compared to the conventional plane-parallel calculation. Whereas previous studies employing the Tripleclouds concept focused on researching the top-of-the-atmosphere radiation budget, the present work applies Tripleclouds to atmospheric heating rate and net surface flux. The Tripleclouds scheme was implemented in the comprehensive libRadtran radiative transfer package and can be utilized to further address key scientific issues related to unresolved cloud–radiation interplay in coarse-resolution atmospheric models.
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Astin, I., and L. Di Girolamo. "Technical Note: The horizontal scale dependence of the cloud overlap parameter α." Atmospheric Chemistry and Physics 14, no. 18 (September 19, 2014): 9917–22. http://dx.doi.org/10.5194/acp-14-9917-2014.
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Abstract. The cloud overlap parameter α relates the combined cloud fraction between two altitude levels in a grid box to the cloud fraction as derived under the maximum and random overlap assumptions. In a number of published studies in this and other journals, it is found that α tends to increase with an increasing scale. In this Technical Note, we investigate this analytically by considering what happens to α when two grid boxes are merged to give a grid box with twice the area. Assuming that α depends only on scale, then between any two fixed altitudes, there will be a linear relationship between the values of α on the two scales. We illustrate this by finding the relationship when cloud cover fractions are assumed to be uniformly distributed, but with varying degrees of horizontal and vertical correlation. Based on this, we conclude that α increases with scale if its value is less than the vertical correlation coefficient in cloud fraction between the two altitude levels. This occurs when the clouds are deeper than would be expected at random (i.e. for exponentially distributed cloud depths).
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Li, J., J. Huang, K. Stamnes, T. Wang, Y. Yi, X. Ding, Q. Lv, and H. Jin. "Distributions and radiative forcings of various cloud types based on active and passive satellite datasets – Part 1: Geographical distributions and overlap of cloud types." Atmospheric Chemistry and Physics Discussions 14, no. 7 (April 25, 2014): 10463–514. http://dx.doi.org/10.5194/acpd-14-10463-2014.
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Abstract. Based on four year' 2B-CLDCLASS-Lidar (Radar-Lidar) cloud classification product from CloudSat, we analyze the geographical distributions of different cloud types and their co-occurrence frequency across different seasons, moreover, utilize the vertical distributions of cloud type to further evaluate the cloud overlap assumptions. The statistical results show that more high clouds, altocumulus, stratocumulus or stratus and cumulus are identified in the Radar-Lidar cloud classification product compared to previous results from Radar-only cloud classification (2B-CLDCLASS product from CloudSat). In particularly, high clouds and cumulus cloud fractions increased by factors 2.5 and 4–7, respectively. The new results are in more reasonable agreement with other datasets (typically the International Satellite Cloud Climatology Project (ISCCP) and surface observer reports). Among the cloud types, altostratus and altocumulus are more popular over the arid/semi-arid land areas of the Northern and Southern Hemispheres, respectively. These features weren't observed by using the ISCCP D1 dataset. For co-occurrence of cloud types, high cloud, altostratus, altocumulus and cumulus are much more likely to co-exist with other cloud types. However, stratus/stratocumulus, nimbostratus and convective clouds are much more likely to exhibit individual features. After considering the co-occurrence of cloud types, the cloud fraction based on the random overlap assumption is underestimated over the vast ocean except in the west-central Pacific Ocean warm pool. Obvious overestimations are mainly occurring over land areas in the tropics and subtropics. The investigation therefore indicates that incorporate co-occurrence information of cloud types based on Radar-Lidar cloud classification into the overlap assumption schemes used in the current GCMs possible be able to provide an better predictions for vertically projected total cloud fraction.
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Oreopoulos, L., D. Lee, Y. C. Sud, and M. J. Suarez. "Radiative impacts of cloud heterogeneity and overlap in an atmospheric General Circulation Model." Atmospheric Chemistry and Physics 12, no. 19 (October 4, 2012): 9097–111. http://dx.doi.org/10.5194/acp-12-9097-2012.
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Abstract. The radiative impacts of horizontal heterogeneity of layer cloud condensate, and vertical overlap of both condensate and cloud fraction are examined with the aid of a new radiation package operating in the GEOS-5 Atmospheric General Circulation Model. The impacts are examined in terms of diagnostic top-of-the atmosphere shortwave (SW) and longwave (LW) cloud radiative effect (CRE) calculations for a range of assumptions and overlap parameter specifications. The investigation is conducted for two distinct cloud schemes, one that comes with the standard GEOS-5 distribution, and another used experimentally for its enhanced cloud microphysical capabilities. Both schemes are coupled to a cloud generator allowing arbitrary cloud overlap specification. Results show that cloud overlap radiative impacts are significantly stronger in the operational cloud scheme where a change of cloud fraction overlap from maximum-random to generalized results in global changes of SW and LW CRE of ~4 Wm−2, and zonal changes of up to ~10 Wm−2. This is an outcome of fewer occurrences (compared to the other scheme) of large layer cloud fractions and fewer multi-layer situations where large numbers of atmospheric layers are simultaneously cloudy, both conditions that make overlap details more important. The impact of the specifics of condensate distribution overlap on CRE is much weaker. Once generalized overlap is adopted, both cloud schemes are only modestly sensitive to the exact values of the overlap parameters. When one of the CRE components is overestimated and the other underestimated, both cannot be driven simoultaneously towards observed values by adjustments to cloud condensate heterogeneity and overlap specifications alone.
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Brooks, Malcolm E., Robin J. Hogan, and Anthony J. Illingworth. "Parameterizing the Difference in Cloud Fraction Defined by Area and by Volume as Observed with Radar and Lidar." Journal of the Atmospheric Sciences 62, no. 7 (July 1, 2005): 2248–60. http://dx.doi.org/10.1175/jas3467.1.
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Abstract Most current general circulation models (GCMs) calculate radiative fluxes through partially cloudy grid boxes by weighting clear and cloudy fluxes by the fractional area of cloud cover (Ca), but most GCM cloud schemes calculate cloud fraction as the volume of the grid box that is filled with cloud (Cυ). In this paper, 1 yr of cloud radar and lidar observations from Chilbolton in southern England, are used to examine this discrepancy. With a vertical resolution of 300 m it is found that, on average, Ca is 20% greater than Cυ, and with a vertical resolution of 1 km, Ca is greater than Cυ by a factor of 2. The difference is around a factor of 2 larger for liquid water clouds than for ice clouds, and also increases with wind shear. Using Ca rather than Cυ, calculated on an operational model grid, increases the mean total cloud cover from 53% to 63%, and so is of similar importance to the cloud overlap assumption. A simple parameterization, Ca = [1 + e(−f )(C−1υ − 1)]−1, is proposed to correct for this underestimate based on the observation that the observed relationship between the mean Ca and Cυ is symmetric about the line Ca = 1 − Cυ. The parameter f is a simple function of the horizontal (H) and vertical (V) grid-box dimensions, where for ice clouds f = 0.0880 V 0.7696 H−0.2254 and for liquid clouds f = 0.1635 V 0.6694 H−0.1882. Implementing this simple parameterization, which excludes the effect of wind shear, on an independent 6-month dataset of cloud radar and lidar observations, accounts for the mean underestimate of Ca for all horizontal and vertical resolutions considered to within 3% of the observed Ca, and reduces the rms error for each individual box from typically 100% to approximately 30%. Small biases remain for both weakly and strongly sheared cases, but this is significantly reduced by incorporating a simple shear dependence in the calculation of the parameter f, which also slightly improves the overall performance of the parameterization for all of the resolutions considered.
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Oreopoulos, L., D. Lee, Y. C. Sud, and M. J. Suarez. "Radiative impacts of cloud heterogeneity and overlap in an atmospheric General Circulation Model." Atmospheric Chemistry and Physics Discussions 12, no. 5 (May 12, 2012): 12287–329. http://dx.doi.org/10.5194/acpd-12-12287-2012.
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Abstract. The radiative impacts of introducing horizontal heterogeneity of layer cloud condensate, and vertical overlap of condensate and cloud fraction are examined with the aid of a new radiation package operating in the GEOS-5 Atmospheric General Circulation Model. The impacts are examined in terms of diagnostic top-of-the atmosphere shortwave (SW) and longwave (LW) cloud radiative effect (CRE) calculations for a range of assumptions and parameter specifications about the overlap. The investigation is conducted for two distinct cloud schemes, the one that comes with the standard GEOS-5 distribution, and another which has been recently used experimentally for its enhanced cloud microphysical capabilities; both are coupled to a cloud generator allowing arbitrary cloud overlap specification. We find that cloud overlap radiative impacts are significantly stronger for the operational cloud scheme for which a change of cloud fraction overlap from maximum-random to generalized results to global changes of SW and LW CRE of ∼4 W m−2, and zonal changes of up to ∼10 W m−2. This is because of fewer occurrences compared to the other scheme of large layer cloud fractions and of multi-layer situations with large numbers of atmospheric layers being simultaneously cloudy, conditions that make overlap details more important. The impact on CRE of the details of condensate distribution overlap is much weaker. Once generalized overlap is adopted, both cloud schemes are only modestly sensitive to the exact values of the overlap parameters. We also find that if one of the CRE components is overestimated and the other underestimated, both cannot be driven towards observed values by adjustments to cloud condensate heterogeneity and overlap alone.
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Li, Jiming, Qiaoyi Lv, Bida Jian, Min Zhang, Chuanfeng Zhao, Qiang Fu, Kazuaki Kawamoto, and Hua Zhang. "The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau." Atmospheric Chemistry and Physics 18, no. 10 (May 25, 2018): 7329–43. http://dx.doi.org/10.5194/acp-18-7329-2018.
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Abstract. Studies have shown that changes in cloud cover are responsible for the rapid climate warming over the Tibetan Plateau (TP) in the past 3 decades. To simulate the total cloud cover, atmospheric models have to reasonably represent the characteristics of vertical overlap between cloud layers. Until now, however, this subject has received little attention due to the limited availability of observations, especially over the TP. Based on the above information, the main aim of this study is to examine the properties of cloud overlaps over the TP region and to build an empirical relationship between cloud overlap properties and large-scale atmospheric dynamics using 4 years (2007–2010) of data from the CloudSat cloud product and collocated ERA-Interim reanalysis data. To do this, the cloud overlap parameter α, which is an inverse exponential function of the cloud layer separation D and decorrelation length scale L, is calculated using CloudSat and is discussed. The parameters α and L are both widely used to characterize the transition from the maximum to random overlap assumption with increasing layer separations. For those non-adjacent layers without clear sky between them (that is, contiguous cloud layers), it is found that the overlap parameter α is sensitive to the unique thermodynamic and dynamic environment over the TP, i.e., the unstable atmospheric stratification and corresponding weak wind shear, which leads to maximum overlap (that is, greater α values). This finding agrees well with the previous studies. Finally, we parameterize the decorrelation length scale L as a function of the wind shear and atmospheric stability based on a multiple linear regression. Compared with previous parameterizations, this new scheme can improve the simulation of total cloud cover over the TP when the separations between cloud layers are greater than 1 km. This study thus suggests that the effects of both wind shear and atmospheric stability on cloud overlap should be taken into account in the parameterization of decorrelation length scale L in order to further improve the calculation of the radiative budget and the prediction of climate change over the TP in the atmospheric models.
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Astin, I., and L. Di Girolamo. "Technical Note: The horizontal scale-dependence of the cloud overlap parameter alpha." Atmospheric Chemistry and Physics Discussions 14, no. 7 (April 15, 2014): 9801–13. http://dx.doi.org/10.5194/acpd-14-9801-2014.
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Abstract. The cloud overlap parameter alpha relates the combined cloud fraction between two altitude levels in a grid box to the cloud fraction as derived under the maximum and random overlap assumptions. In a number of published studies in this and other journals it is found that alpha tends to increase with increasing scale. In this technical note, we investigate this analytically by considering what happens to alpha when two grid boxes are merged to give a grid box with twice the area. Assuming that alpha depends only on scale then, between any two fixed altitudes, there will be a linear relationship between the values of alpha at the two scales. We illustrate this by finding the relationship when cloud cover fractions are assumed to be uniformly distributed, but with varying degrees of horizontal and vertical correlation. Based on this, we conclude that alpha increases with scale if its value is less than the vertical correlation coefficient in cloud fraction between the two altitude levels. This occurs when the cloud are deeper than would be expected at random (i.e. for exponentially distributed cloud depths). However, the degree of scale-dependence is controlled by the horizontal correlation coefficient in the cloud fraction between adjacent grid boxes, being greatest when this correlation is zero. Trivially, there is no scale-dependence when this correlation is one. The observed, generally strong, scale-dependence would thus indicate that the horizontal correlation is small.
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Oreopoulos, L., and P. M. Norris. "An analysis of cloud overlap at a midlatitude atmospheric observation facility." Atmospheric Chemistry and Physics 11, no. 12 (June 16, 2011): 5557–67. http://dx.doi.org/10.5194/acp-11-5557-2011.
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Abstract. An analysis of cloud overlap based on high temporal and vertical resolution retrievals of cloud condensate from a suite of ground instruments is performed at a mid-latitude atmospheric observation facility. Two facets of overlap are investigated: cloud fraction overlap, expressed in terms of a parameter "α" indicating the relative contributions of maximum and random overlap, and overlap of horizontal distributions of condensate, expressed in terms of the correlation coefficient of condensate ranks. The degree of proximity to the random and maximum overlap assumptions is also expressed in terms of a decorrelation length, a convenient scalar parameter for overlap parameters assumed to decay exponentially with separation distance. Both cloud fraction overlap and condensate overlap show significant seasonal variations with a clear tendency for more maximum overlap in the summer months. More maximum overlap is also generally observed when the domain size used to define cloud fractions increases. These tendencies also exist for rank correlations, but are significantly weaker. Hitherto unexplored overlap parameter dependencies are investigated by analyzing mean parameter differences at fixed separation distance within different layers of the atmospheric column, and by searching for possible systematic relationships between alpha and rank correlation. We find that for the same separation distance the overlap parameters are significantly distinct in different atmospheric layers, and that random cloud fraction overlap is usually associated with more randomly overlapped condensate ranks.
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Ovchinnikov, Mikhail, Kyo‐Sun Sunny Lim, Vincent E. Larson, May Wong, Katherine Thayer‐Calder, and Steven J. Ghan. "Vertical overlap of probability density functions of cloud and precipitation hydrometeors." Journal of Geophysical Research: Atmospheres 121, no. 21 (November 5, 2016): 12,966–12,984. http://dx.doi.org/10.1002/2016jd025158.
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Pavolonis, Michael J., and Andrew K. Heidinger. "Daytime Cloud Overlap Detection from AVHRR and VIIRS." Journal of Applied Meteorology 43, no. 5 (May 1, 2004): 762–78. http://dx.doi.org/10.1175/2099.1.
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Abstract Two algorithms for detecting multilayered cloud systems with satellite data are presented. The first algorithm utilizes data in the 0.65-, 11-, and 12-μm regions of the spectrum that are available on the Advanced Very High Resolution Radiometer (AVHRR). The second algorithm incorporates two different techniques to detect cloud overlap: the same technique used in the first algorithm and an additional series of spectral tests that now include data from the 1.38- and 1.65-μm near-infrared regions that are available on the Moderate Resolution Imaging Spectroradiometer (MODIS) and will be available on the Visible/Infrared Imager/Radiometer Suite (VIIRS). VIIRS is the imager that will replace the AVHRR on the next generation of polar-orbiting satellites. Both algorithms were derived assuming that a scene with cloud overlap consists of a semitransparent ice cloud that overlaps a cloud composed of liquid water droplets. Each algorithm was tested on three different MODIS scenes. In all three cases, the second (VIIRS) algorithm was able to detect more cloud overlap than the first (AVHRR) algorithm. Radiative transfer calculations indicate that the VIIRS algorithm will be more effective than the AVHRR algorithm when the visible optical depth of the ice cloud is greater than 3. Both algorithms will work best when the visible optical depth of the water cloud is greater than 5. Model sensitivity studies were also performed to assess the sensitivity of each algorithm to various parameters. It was found that the AVHRR algorithm is most sensitive to cloud particle size and the VIIRS near-infrared test is most sensitive to cloud vertical location. When validating each algorithm using cloud radar data, the VIIRS algorithm was shown to be more effective at detecting cloud overlap than the AVHRR algorithm; however, the VIIRS algorithm was slightly more prone to false cloud overlap detection.
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Oreopoulos, L., and P. M. Norris. "An analysis of cloud overlap at a midlatitude atmospheric observation facility." Atmospheric Chemistry and Physics Discussions 11, no. 1 (January 7, 2011): 597–625. http://dx.doi.org/10.5194/acpd-11-597-2011.
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Abstract. An analysis of cloud overlap based on high temporal and vertical resolution retrievals of cloud condensate from a suite of ground instruments is performed at a mid-latitude observational facility. Two facets of overlap are investigated: cloud fraction overlap, expressed in terms of a parameter "alpha" indicating the relative contributions of maximum and random overlap, and overlap of horizontal distributions of condendsate, expressed in terms of the correlation coefficient of condensate ranks. The degree of proximity to the random and maximum overlap assumptions is also expressed in terms of a decorrelation length, a convenient scalar parameter that emerges under the assumption that overlap parameters decay exponentially with separation distance. Both cloud fraction overlap and condensate overlap show significant seasonal variations with a clear tendency for overlap to be closer to maximum for summer months. A tendency for more maximum overlap is also observed as the size of the domain used to define cloud fractions increases. These dependencies are significantly weaker for rank correlations. Hitherto unexplored overlap parameter dependencies are investigated by analyzing mean parameter value differences at fixed separation distance within different layers of the atmospheric column, and by searching for possible systematic relationships between alpha and rank correlation. We find that for the same separation distance the overlap parameters are significantly distinct in different atmospheric layers, and that a tendency exists for random cloud fraction overlap to be generally in sync with more random overlap of condensate ranks.
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Devasthale, A., and M. A. Thomas. "A global survey of aerosol-liquid water cloud overlap based on four years of CALIPSO-CALIOP data." Atmospheric Chemistry and Physics Discussions 10, no. 9 (September 27, 2010): 22109–30. http://dx.doi.org/10.5194/acpd-10-22109-2010.
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Abstract. The presence of aerosols over highly reflective liquid water cloud tops poses a big challenge in simulating their radiative impacts. Particularly, absorbing aerosols, such as smoke, may have significant impact in such situations and even change the sign of net radiative forcing. Until now, it was not possible to obtain information on such overlap events realistically from the existing passive satellite sensors. However, the CALIOP instrument onboard NASA's CALIPSO satellite allows us to examine these events with an unprecedented accuracy. Using four years of collocated CALIPSO 5 km Aerosol and Cloud Layer Version 3 Products (June 2006–May 2010), we quantify, for the first time, the macrophysical characteristics of overlapping aerosol and water cloud layers globally. We investigate seasonal variability in these characteristics over six latitude bands to understand the hemispheric differences. We compute a) the percentage cases when such overlap is seen globally and seasonally when all aerosol types are included (AAO case) in the analysis, b) the joint histograms of aerosol layer base height and cloud layer top height, and c) the joint histograms of aerosol and cloud geometrical thicknesses in such overlap cases. We also investigate frequency of smoke aerosol-cloud overlap (SAO case). The results show a distinct seasonality in overlap frequency in both AAO and SAO cases. Globally, the frequency is highest during JJA months in AAO case, while for the SAO case, it is highest in SON months. The seasonal mean overlap frequency can regionally exceed 20% in AAO case and 10% in SAO case. There is a tendency that the vertical separation between aerosol and cloud layers increases from high to low latitude regions in the both hemispheres. In about 5–10% cases the vertical distance between aerosol and cloud layers is less than 100 m, while about in 45–60% cases it less than a kilometer in the annual means for different latitudinal bands. The frequency of occurrence of thicker aerosol layers gradually increases from poles to tropics. In about 70–80% cases, aerosol layers are less than a kilometer thick, while in about 18–22% cases they are 1–2 km thick. The frequency of aerosol layers 2–3 km thick is about 4–5% in the tropical belts during overlap events. The results further highlight spatial and temporal variations in aerosol-liquid water cloud overlap and suggest that the frequency of occurrence of such overlap events is far from being negligible globally.
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Turner, D. D., M. D. Shupe, and A. B. Zwink. "Characteristic Atmospheric Radiative Heating Rate Profiles in Arctic Clouds as Observed at Barrow, Alaska." Journal of Applied Meteorology and Climatology 57, no. 4 (April 2018): 953–68. http://dx.doi.org/10.1175/jamc-d-17-0252.1.
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AbstractA 2-yr cloud microphysical property dataset derived from ground-based remote sensors at the Atmospheric Radiation Measurement site near Barrow, Alaska, was used as input into a radiative transfer model to compute radiative heating rate (RHR) profiles in the atmosphere. Both the longwave (LW; 5–100 μm) and shortwave (SW; 0.2–5 μm) RHR profiles show significant month-to-month variability because of seasonal dependence in the vertical profiles of cloud liquid and ice water contents, with additional contributions from the seasonal dependencies of solar zenith angle, water vapor amount, and temperature. The LW and SW RHR profiles were binned to provide characteristic profiles as a function of cloud type and liquid water path (LWP). Single-layer liquid-only clouds are shown to have larger (10–30 K day−1) LW radiative cooling rates at the top of the cloud layer than single-layer mixed-phase clouds; this is due primarily to differences in the vertical distribution of liquid water between the two classes. However, differences in SW RHR profiles at the top of these two classes of clouds are less than 3 K day−1. The absolute value of the RHR in single-layer ice-only clouds is an order of magnitude smaller than in liquid-bearing clouds. Furthermore, for double-layer cloud systems, the phase and condensed water path of the upper cloud strongly modulate the radiative cooling both at the top and within the lower-level cloud. While sensitivity to cloud overlap and phase has been shown previously, the characteristic RHR profiles are markedly different between the different cloud classifications.
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Wang, Xiaocong, Hao Miao, Yimin Liu, and Qing Bao. "Dependence of cloud radiation on cloud overlap, horizontal inhomogeneity, and vertical alignment in stratiform and convective regions." Atmospheric Research 249 (February 2021): 105358. http://dx.doi.org/10.1016/j.atmosres.2020.105358.
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Chaudhry, Muhammad Hamid, Anuar Ahmad, and Qudsia Gulzar. "Impact of UAV Surveying Parameters on Mixed Urban Landuse Surface Modelling." ISPRS International Journal of Geo-Information 9, no. 11 (October 31, 2020): 656. http://dx.doi.org/10.3390/ijgi9110656.
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Unmanned Aerial Vehicles (UAVs) as a surveying tool are mainly characterized by a large amount of data and high computational cost. This research investigates the use of a small amount of data with less computational cost for more accurate three-dimensional (3D) photogrammetric products by manipulating UAV surveying parameters such as flight lines pattern and image overlap percentages. Sixteen photogrammetric projects with perpendicular flight plans and a variation of 55% to 85% side and forward overlap were processed in Pix4DMapper. For UAV data georeferencing and accuracy assessment, 10 Ground Control Points (GCPs) and 18 Check Points (CPs) were used. Comparative analysis was done by incorporating the median of tie points, the number of 3D point cloud, horizontal/vertical Root Mean Square Error (RMSE), and large-scale topographic variations. The results show that an increased forward overlap also increases the median of the tie points, and an increase in both side and forward overlap results in the increased number of point clouds. The horizontal accuracy of 16 projects varies from ±0.13m to ±0.17m whereas the vertical accuracy varies from ± 0.09 m to ± 0.32 m. However, the lowest vertical RMSE value was not for highest overlap percentage. The tradeoff among UAV surveying parameters can result in high accuracy products with less computational cost.
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Qian, Y., C. N. Long, H. Wang, J. M. Comstock, S. A. McFarlane, and S. Xie. "Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations." Atmospheric Chemistry and Physics 12, no. 4 (February 17, 2012): 1785–810. http://dx.doi.org/10.5194/acp-12-1785-2012.
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Abstract. Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulated in the IPCC AR4 GCMs against ARM long-term ground-based measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity. Comparisons are performed for three climate regimes as represented by the Department of Energy Atmospheric Radiation Measurement (ARM) sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). Our intercomparisons of three independent measurements of CF or sky-cover reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The total sky imager (TSI) produces smaller total cloud fraction (TCF) compared to a radar/lidar dataset for highly cloudy days (CF > 0.8), but produces a larger TCF value than the radar/lidar for less cloudy conditions (CF < 0.3). The compensating errors in lower and higher CF days result in small biases of TCF between the vertically pointing radar/lidar dataset and the hemispheric TSI measurements as multi-year data is averaged. The unique radar/lidar CF measurements enable us to evaluate seasonal variation of cloud vertical structures in the GCMs. Both inter-model deviation and model bias against observation are investigated in this study. Another unique aspect of this study is that we use simultaneous measurements of CF and surface radiative fluxes to diagnose potential discrepancies among the GCMs in representing other cloud optical properties than TCF. The results show that the model-observation and inter-model deviations have similar magnitudes for the TCF and the normalized cloud effect, and these deviations are larger than those in surface downward solar radiation and cloud transmissivity. This implies that other dimensions of cloud in addition to cloud amount, such as cloud optical thickness and/or cloud height, have a similar magnitude of disparity as TCF within the GCMs, and suggests that the better agreement among GCMs in solar radiative fluxes could be a result of compensating effects from errors in cloud vertical structure, overlap assumption, cloud optical depth and/or cloud fraction. The internal variability of CF simulated in ensemble runs with the same model is minimal. Similar deviation patterns between inter-model and model-measurement comparisons suggest that the climate models tend to generate larger biases against observations for those variables with larger inter-model deviation. The GCM performance in simulating the probability distribution, transmissivity and vertical profiles of cloud are comprehensively evaluated over the three ARM sites. The GCMs perform better at SGP than at the other two sites in simulating the seasonal variation and probability distribution of TCF. However, the models remarkably underpredict the TCF at SGP and cloud transmissivity is less susceptible to the change of TCF than observed. In the tropics, most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels. The high-level CF is much larger in the GCMs than the observations and the inter-model variability of CF also reaches a maximum at high levels in the tropics, indicating discrepancies in the representation of ice cloud associated with convection in the models. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near the surface over the Arctic.
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Heiblum, Reuven H., Lital Pinto, Orit Altaratz, Guy Dagan, and Ilan Koren. "Core and margin in warm convective clouds – Part 2: Aerosol effects on core properties." Atmospheric Chemistry and Physics 19, no. 16 (August 26, 2019): 10739–55. http://dx.doi.org/10.5194/acp-19-10739-2019.
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Abstract. The effects of aerosol on warm convective cloud cores are evaluated using single cloud and cloud field simulations. Three core definitions are examined: positive vertical velocity (Wcore), supersaturation (RHcore), and positive buoyancy (Bcore). As presented in Part 1 (Heiblum et al., 2019), the property Bcore⊆RHcore⊆Wcore is seen during growth of warm convective clouds. We show that this property is kept irrespective of aerosol concentration. During dissipation core fractions generally decrease with less overlap between cores. However, for clouds that develop in low aerosol concentrations capable of producing precipitation, Bcore and subsequently Wcore volume fractions may increase during dissipation (i.e., loss of cloud mass). The RHcore volume fraction decreases during cloud lifetime and shows minor sensitivity to aerosol concentration. It is shown that a Bcore forms due to two processes: (i) convective updrafts – condensation within supersaturated updrafts and release of latent heat – and (ii) dissipative downdrafts – subsaturated cloudy downdrafts that warm during descent and “undershoot” the level of neutral buoyancy. The former process occurs during cloud growth for all aerosol concentrations. The latter process only occurs for low aerosol concentrations during dissipation and precipitation stages where large mean drop sizes permit slow evaporation rates and subsaturation during descent. The aerosol effect on the diffusion efficiencies plays a crucial role in the development of the cloud and its partition to core and margin. Using the RHcore definition, it is shown that the total cloud mass is mostly dictated by core processes, while the total cloud volume is mostly dictated by margin processes. Increase in aerosol concentration increases the core (mass and volume) due to enhanced condensation but also decreases the margin due to evaporation. In clean clouds larger droplets evaporate much slower, enabling preservation of cloud size, and even increase by detrainment and dilution (volume increases while losing mass). This explains how despite having smaller cores and less mass, cleaner clouds may live longer and grow to larger sizes.
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Devasthale, A., and M. A. Thomas. "A global survey of aerosol-liquid water cloud overlap based on four years of CALIPSO-CALIOP data." Atmospheric Chemistry and Physics 11, no. 3 (February 10, 2011): 1143–54. http://dx.doi.org/10.5194/acp-11-1143-2011.
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Abstract. Simulating the radiative impacts of aerosols located above liquid water clouds presents a significant challenge. In particular, absorbing aerosols, such as smoke, may have significant impact in such situations and even change the sign of net radiative forcing. It is not possible to reliably obtain information on such overlap events from existing passive satellite sensors. However, the CALIOP instrument onboard NASA's CALIPSO satellite allows us to examine these events with unprecedented accuracy. Using four years of collocated CALIPSO 5 km Aerosol and Cloud Layer Version 3 Products (June 2006–May 2010), we quantify, for the first time, the characteristics of overlapping aerosol and water cloud layers globally. We investigate seasonal variability in these characteristics over six latitude bands to understand the hemispheric differences when all aerosol types are included in the analysis (the AAO case). We also investigate frequency of smoke aerosol-cloud overlap (the SAO case). Globally, the frequency is highest during the JJA months in the AAO case, while for the SAO case, it is highest in the SON months. The seasonal mean overlap frequency can regionally exceed 20% in the AAO case and 10% in the SAO case. In about 5–10% cases the vertical distance between aerosol and cloud layers is less than 100 m, while about in 45–60% cases it less than a kilometer in the annual means for different latitudinal bands. In about 70–80% cases, aerosol layers are less than a kilometer thick, while in about 18–22% cases they are 1–2 km thick. The frequency of aerosol layers 2–3 km thick is about 4–5% in the tropical belts during overlap events. Over the regions where high aerosol loadings are present, the overlap frequency can be up to 50% higher when quality criteria on aerosol/cloud feature detection are relaxed. Over the polar regions, more than 50% of the overlapping aerosol layers have optical thickness less than 0.02, but the contribution from the relatively optically thicker aerosol layers increases towards the equatorial regions in both hemispheres. The results suggest that the frequency of occurrence of overlap events is far from being negligible globally.
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Burley, Jarred L., Steven T. Fiorino, Brannon J. Elmore, and Jaclyn E. Schmidt. "A Remote Sensing and Atmospheric Correction Method for Assessing Multispectral Radiative Transfer through Realistic Atmospheres and Clouds." Journal of Atmospheric and Oceanic Technology 36, no. 2 (February 1, 2019): 203–16. http://dx.doi.org/10.1175/jtech-d-18-0078.1.
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Abstract The ability to quickly and accurately model actual atmospheric conditions is essential to remote sensing analyses. Clouds present a particularly complex challenge, as they cover up to 70% of Earth’s surface, and their highly variable and diverse nature necessitates physics-based modeling. The Laser Environmental Effects Definition and Reference (LEEDR) is a verified and validated atmospheric propagation and radiative transfer code that creates physically realizable vertical and horizontal profiles of meteorological data. Coupled with numerical weather prediction (NWP) model output, LEEDR enables analysis, nowcasts, and forecasts for radiative effects expected for real-world scenarios. A recent development is the inclusion of the U.S. Air Force’s World-Wide Merged Cloud Analysis (WWMCA) cloud data in a new tool set that enables radiance calculations through clouds from UV to radio frequency (RF) wavelengths. This effort details the creation of near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest. Calendar year 2015 data are analyzed to establish climatological limits for diffuse transmission in the 300–1300-nm band, and the impacts of various geometry, cloud microphysical, and atmospheric conditions are examined. The results show that 80% of diffuse band transmissions are estimated to fall between 0.248 and 0.889 under the assumptions of cloud homogeneity and maximum overlap and are sufficient for establishing diffuse transmission percentiles. The demonstrated capability provides an efficient way to extend optical wavelength cloud parameters across the spectrum for physics-based multiple-scattering effects modeling through cloudy and clear atmospheres, providing an improvement to atmospheric correction for remote sensing and cloud effects on system performance metrics.
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Heiblum, Reuven H., Lital Pinto, Orit Altaratz, Guy Dagan, and Ilan Koren. "Core and margin in warm convective clouds – Part 1: Core types and evolution during a cloud's lifetime." Atmospheric Chemistry and Physics 19, no. 16 (August 26, 2019): 10717–38. http://dx.doi.org/10.5194/acp-19-10717-2019.
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Abstract. The properties of a warm convective cloud are determined by the competition between the growth and dissipation processes occurring within it. One way to observe and follow this competition is by partitioning the cloud to core and margin regions. Here we look at three core definitions, namely positive vertical velocity (Wcore), supersaturation (RHcore), and positive buoyancy (Bcore), and follow their evolution throughout the lifetime of warm convective clouds. Using single cloud and cloud field simulations with bin-microphysics schemes, we show that the different core types tend to be subsets of one another in the following order: Bcore⊆RHcore⊆Wcore. This property is seen for several different thermodynamic profile initializations and is generally maintained during the growing and mature stages of a cloud's lifetime. This finding is in line with previous works and theoretical predictions showing that cumulus clouds may be dominated by negative buoyancy at certain stages of their lifetime. The RHcore–Wcore pair is most interchangeable, especially during the growing stages of the cloud. For all three definitions, the core–shell model of a core (positive values) at the center of the cloud surrounded by a shell (negative values) at the cloud periphery applies to over 80 % of a typical cloud's lifetime. The core–shell model is less appropriate in larger clouds with multiple cores displaced from the cloud center. Larger clouds may also exhibit buoyancy cores centered near the cloud edge. During dissipation the cores show less overlap, reduce in size, and may migrate from the cloud center.
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Pincus, Robert, Richard Hemler, and Stephen A. Klein. "Using Stochastically Generated Subcolumns to Represent Cloud Structure in a Large-Scale Model." Monthly Weather Review 134, no. 12 (December 1, 2006): 3644–56. http://dx.doi.org/10.1175/mwr3257.1.
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Abstract A new method for representing subgrid-scale cloud structure in which each model column is decomposed into a set of subcolumns has been introduced into the Geophysical Fluid Dynamics Laboratory’s global atmospheric model AM2. Each subcolumn in the decomposition is homogeneous, but the ensemble reproduces the initial profiles of cloud properties including cloud fraction, internal variability (if any) in cloud condensate, and arbitrary overlap assumptions that describe vertical correlations. These subcolumns are used in radiation and diagnostic calculations and have allowed the introduction of more realistic overlap assumptions. This paper describes the impact of these new methods for representing cloud structure in instantaneous calculations and long-term integrations. Shortwave radiation computed using subcolumns and the random overlap assumption differs in the global annual average by more than 4 W m−2 from the operational radiation scheme in instantaneous calculations; much of this difference is counteracted by a change in the overlap assumption to one in which overlap varies continuously with the separation distance between layers. Internal variability in cloud condensate, diagnosed from the mean condensate amount and cloud fraction, has about the same effect on radiative fluxes as does the ad hoc tuning accounting for this effect in the operational radiation scheme. Long simulations with the new model configuration show little difference from the operational model configuration, while statistical tests indicate that the model does not respond systematically to the sampling noise introduced by the approximate radiative transfer techniques introduced to work with the subcolumns.
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Chang, Fu-Lung, and Zhanqing Li. "A Near-Global Climatology of Single-Layer and Overlapped Clouds and Their Optical Properties Retrieved from Terra/MODIS Data Using a New Algorithm." Journal of Climate 18, no. 22 (November 15, 2005): 4752–71. http://dx.doi.org/10.1175/jcli3553.1.
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Abstract Cloud overlapping has been a major issue in climate studies owing to a lack of reliable information available over both oceans and land. This study presents the first near-global retrieval and analysis of single-layer and overlapped cloud vertical structures and their optical properties retrieved by applying a new method to the Moderate Resolution Imaging Spectroradiometer (MODIS) data. Taking full advantage of the MODIS multiple channels, the method can differentiate cirrus overlapping lower water clouds from single-layer clouds. Based on newly retrieved cloud products using daytime Terra/MODIS 5-km overcast measurements sampled in January, April, July, and October 2001, global statistics of the frequency of occurrence, cloud-top pressure/temperature (Pc/Tc), visible optical depth (τVIS), and infrared emissivity (ɛ) are presented and discussed. Of all overcast scenes identified over land (ocean), the MODIS data show 61% (52%) high clouds (Pc < 500 hPa), 39% (48%) lower clouds (Pc > 500 hPa), and an extremely low occurrence (<4%) of Pc between 500 and 600 hPa. A distinct bimodal distribution of Pc is found and peaks at ∼275 and ∼725 hPa for high and low clouds, thus leaving a minimum in cloud in the middle troposphere. Out of the 61% (52%) of high clouds identified by MODIS, retrievals reveal that 41% (35%) are thin cirrus clouds (ɛ < 0.85 and Pc < 500 hPa) and the remaining 20% (17%) are thick high clouds (ɛ ≥ 0.85). Out of the 41% (35%) of thin cirrus, 29% (27%) are found to overlap with lower water clouds and 12% (8%) are single-layer cirrus. Total low-cloud amount (single-layer plus overlapped) out of all overcast scenes is thus 68% (39% + 29%) over land and 75% (48% + 27%) over ocean, which is greater than the cloud amounts reported by the MODIS and the International Satellite Cloud Climatology Project (ISCCP). Both retrieved overlapping and nonoverlapping cirrus clouds show similar mean τVIS of ∼1.5 and mean ɛ of ∼0.5. The optical properties of single-layer cirrus and single-layer water clouds agree well with the MODIS standard retrievals. Because the MODIS retrievals do not differentiate between cirrus and lower water clouds in overlap situations, large discrepancies are found for emissivity, cloud-top height, and optical depth for high cirrus overlapping lower water clouds.
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Zhang, H., X. Jing, and J. Li. "Application and evaluation of McICA scheme with new radiation code in BCC_AGCM2.0.1." Geoscientific Model Development Discussions 6, no. 3 (September 16, 2013): 4933–82. http://dx.doi.org/10.5194/gmdd-6-4933-2013.
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Abstract. This research incorporates the Monte Carlo Independent Column Approximation (McICA) scheme with the correlated k-distribution BCC-RAD radiation model into the climate model BCC_AGCM2.0.1 and examines the impacts on modeled climate through several simulations with variations in cloud structures. Results from experiments with consistent sub-grid cloud structures show that both clear-sky radiation fluxes and cloud radiative forcings (CRFs) calculated by the new scheme are mostly improved relative to those calculated from the original one. The modeled atmospheric temperature and specific humidity are also improved due to changes in the radiative heating rates. The vertical overlap of fractional clouds and horizontal distribution of cloud condensation are important for computing CRFs. The maximum changes in seasonal CRF using the general overlap assumption (GenO) with different decorrelation depths (Lcf) are larger than 10 and 20 Wm2 for longwave (LW) CRF and shortwave (SW) CRF, respectively, mostly located in the Tropics and mid-latitude storm tracks. Larger (smaller) Lcf in the Tropics (mid-latitude storm tracks) yield better cloud fraction and CRF compared with observations. The inclusion of an observation-based horizontal inhomogeneity of cloud condensation has a distinct impact on LW CRF and SW CRF, with global means of ∼1.2 Wm−2 and ∼3.7 Wm−2 at the top of atmosphere, respectively, making these much closer to observations. These results prove the reliability of the new model configuration to be used in BCC_AGCM2.0.1 for climate simulations, and also indicate that more detailed real-world information on cloud structures should be obtained to constrain cloud settings in McICA in the future.
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Fujiwara, Masatomo, Takuji Sugidachi, Toru Arai, Kensaku Shimizu, Mayumi Hayashi, Yasuhisa Noma, Hideaki Kawagita, et al. "Development of a cloud particle sensor for radiosonde sounding." Atmospheric Measurement Techniques 9, no. 12 (December 9, 2016): 5911–31. http://dx.doi.org/10.5194/amt-9-5911-2016.
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Abstract. A meteorological balloon-borne cloud sensor called the cloud particle sensor (CPS) has been developed. The CPS is equipped with a diode laser at ∼ 790 nm and two photodetectors, with a polarization plate in front of one of the detectors, to count the number of particles per second and to obtain the cloud-phase information (i.e. liquid, ice, or mixed). The lower detection limit for particle size was evaluated in laboratory experiments as ∼ 2 µm diameter for water droplets. For the current model the output voltage often saturates for water droplets with diameter equal to or greater than ∼ 80 µm. The upper limit of the directly measured particle number concentration is ∼ 2 cm−3 (2 × 103 L−1), which is determined by the volume of the detection area of the instrument. In a cloud layer with a number concentration higher than this value, particle signal overlap and multiple scattering of light occur within the detection area, resulting in a counting loss, though a partial correction may be possible using the particle signal width data. The CPS is currently interfaced with either a Meisei RS-06G radiosonde or a Meisei RS-11G radiosonde that measures vertical profiles of temperature, relative humidity, height, pressure, and horizontal winds. Twenty-five test flights have been made between 2012 and 2015 at midlatitude and tropical sites. In this paper, results from four flights are discussed in detail. A simultaneous flight of two CPSs with different instrumental configurations confirmed the robustness of the technique. At a midlatitude site, a profile containing, from low to high altitude, water clouds, mixed-phase clouds, and ice clouds was successfully obtained. In the tropics, vertically thick cloud layers in the middle to upper troposphere and vertically thin cirrus layers in the upper troposphere were successfully detected in two separate flights. The data quality is much better at night, dusk, and dawn than during the daytime because strong sunlight affects the measurements of scattered light.
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Pan, Honglin, Minzhong Wang, Kanike Raghavendra Kumar, Jiantao Zhang, and Lu Meng. "A Decadal Global Climatology of Ice Cloud Fraction with Their Microphysical and Optical Properties Inferred from the CALIPSO and Reanalysis Data." Remote Sensing 12, no. 22 (November 19, 2020): 3795. http://dx.doi.org/10.3390/rs12223795.
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In the present study, the spatiotemporal and vertical distributions of ice cloud properties and their association with meteorological variables are analyzed for the period 2007–2016 using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Modern Era Retrospective-Analysis for Research (MERRA-2) reanalysis observations. The distribution of ice cloud fraction (ICF) with its peak does not overlap with that of the ice water content (IWC) peak during daytime and nighttime due to the sampling bias. Moreover, the vertical distributions of mean IWC exhibited a vaguely “sharp thorn” at an altitude of ~4 km in all seasons at the location of about ±40°, which can be caused by the artifacts. Furthermore, it is noted that different ice cloud optical depth (ICOD) presents significant changes observed in their diurnal variations in the heights of peaks. The maximum diurnal difference of ice cloud properties occurs in the tropical regions of the North Hemisphere (NH) during summer. We also investigated the relation between ICOD and the meteorological variables and found that the ICOD values are dependent on the meteorological parameters.
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Neggers, R. A. J., and A. P. Siebesma. "Constraining a System of Interacting Parameterizations through Multiple-Parameter Evaluation: Tracing a Compensating Error between Cloud Vertical Structure and Cloud Overlap." Journal of Climate 26, no. 17 (August 23, 2013): 6698–715. http://dx.doi.org/10.1175/jcli-d-12-00779.1.
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Abstract This study explores the opportunities created by subjecting a system of interacting fast-acting parameterizations to long-term single-column model evaluation against multiple independent measurements at a permanent meteorological site. It is argued that constraining the system at multiple key points facilitates the tracing and identification of compensating errors between individual parametric components. The extended time range of the evaluation helps to enhance the statistical significance and representativeness of the single-column model result, which facilitates the attribution of model behavior as diagnosed in a general circulation model to its subgrid parameterizations. At the same time, the high model transparency and computational efficiency typical of single-column modeling is preserved. The method is illustrated by investigating the impact of a model change in the Regional Atmospheric Climate Model (RACMO) on the representation of the coupled boundary layer–soil system at the Cabauw meteorological site in the Netherlands. A set of 12 relevant variables is defined that covers all involved processes, including cloud structure and amplitude, radiative transfer, the surface energy budget, and the thermodynamic state of the soil and various heights of the lower atmosphere. These variables are either routinely measured at the Cabauw site or are obtained from continuous large-eddy simulation at that site. This 12-point check proves effective in revealing the existence of a compensating error between cloud structure and radiative transfer, residing in the cloud overlap assumption. In this exercise, the application of conditional sampling proves a valuable tool in establishing which cloud regime exhibits the biggest impact.
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Shonk, Jonathan K. P., and Robin J. Hogan. "Tripleclouds: An Efficient Method for Representing Horizontal Cloud Inhomogeneity in 1D Radiation Schemes by Using Three Regions at Each Height." Journal of Climate 21, no. 11 (June 1, 2008): 2352–70. http://dx.doi.org/10.1175/2007jcli1940.1.
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Abstract Radiation schemes in general circulation models currently make a number of simplifications when accounting for clouds, one of the most important being the removal of horizontal inhomogeneity. A new scheme is presented that attempts to account for the neglected inhomogeneity by using two regions of cloud in each vertical level of the model as opposed to one. One of these regions is used to represent the optically thinner cloud in the level, and the other represents the optically thicker cloud. So, along with the clear-sky region, the scheme has three regions in each model level and is referred to as “Tripleclouds.” In addition, the scheme has the capability to represent arbitrary vertical overlap between the three regions in pairs of adjacent levels. This scheme is implemented in the Edwards–Slingo radiation code and tested on 250 h of data from 12 different days. The data are derived from cloud retrievals using radar, lidar, and a microwave radiometer at Chilbolton, southern United Kingdom. When the data are grouped into periods equivalent in size to general circulation model grid boxes, the shortwave plane-parallel albedo bias is found to be 8%, while the corresponding bias is found to be less than 1% using Tripleclouds. Similar results are found for the longwave biases. Tripleclouds is then compared to a more conventional method of accounting for inhomogeneity that multiplies optical depths by a constant scaling factor, and Tripleclouds is seen to improve on this method both in terms of top-of-atmosphere radiative flux biases and internal heating rates.
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Persad, R. A., and C. Armenakis. "ALIGNMENT OF POINT CLOUD DSMs FROM TLS AND UAV PLATFORMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W4 (August 27, 2015): 369–73. http://dx.doi.org/10.5194/isprsarchives-xl-1-w4-369-2015.
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The co-registration of 3D point clouds has received considerable attention from various communities, particularly those in photogrammetry, computer graphics and computer vision. Although significant progress has been made, various challenges such as coarse alignment using multi-sensory data with different point densities and minimal overlap still exist. There is a need to address such data integration issues, particularly with the advent of new data collection platforms such as the unmanned aerial vehicles (UAVs). In this study, we propose an approach to align 3D point clouds derived photogrammetrically from UAV approximately vertical images with point clouds measured by terrestrial laser scanners (TLS). The method begins by automatically extracting 3D surface keypoints on both point cloud datasets. Afterwards, regions of interest around each keypoint are established to facilitate the establishment of scale-invariant descriptors for each of them. We use the popular SURF descriptor for matching the keypoints. In our experiments, we report the accuracies of the automatically derived transformation parameters in comparison to manually-derived reference parameter data.
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Stephens, Graeme L., Norman B. Wood, and Philip M. Gabriel. "An Assessment of the Parameterization of Subgrid-Scale Cloud Effects on Radiative Transfer. Part I: Vertical Overlap." Journal of the Atmospheric Sciences 61, no. 6 (March 2004): 715–32. http://dx.doi.org/10.1175/1520-0469(2004)061<0715:aaotpo>2.0.co;2.
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Li, Jiming, Bida Jian, Chuanfeng Zhao, Yuxin Zhao, Jing Wang, and Jianping Huang. "Atmospheric Instability Dominates the Long‐Term Variation of Cloud Vertical Overlap Over the Southern Great Plains Site." Journal of Geophysical Research: Atmospheres 124, no. 16 (August 27, 2019): 9691–701. http://dx.doi.org/10.1029/2019jd030954.
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McCoy, Daniel T., Dennis L. Hartmann, and Daniel P. Grosvenor. "Observed Southern Ocean Cloud Properties and Shortwave Reflection. Part I: Calculation of SW Flux from Observed Cloud Properties*." Journal of Climate 27, no. 23 (December 1, 2014): 8836–57. http://dx.doi.org/10.1175/jcli-d-14-00287.1.
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Abstract The sensitivity of the reflection of shortwave radiation over the Southern Ocean to the cloud properties there is estimated using observations from a suite of passive and active satellite instruments in combination with radiative transfer modeling. A composite cloud property observational data description is constructed that consistently incorporates mean cloud liquid water content, ice water content, liquid and ice particle radius information, vertical structure, vertical overlap, and spatial aggregation of cloud water as measured by optical depth versus cloud-top pressure histograms. The observational datasets used are Moderate Resolution Imaging Spectroradiometer (MODIS) effective radius filtered to mitigate solar zenith angle bias, the Multiangle Imaging Spectroradiometer (MISR) cloud-top height–optical depth (CTH–OD) histogram, the liquid water path from the University of Wisconsin dataset, and ice cloud properties from CloudSat. This cloud database is used to compute reflected shortwave radiation as a function of month and location over the ocean from 40° to 60°S, which compares well with observations of reflected shortwave radiation. This calculation is then used to test the sensitivity of the seasonal variation of shortwave reflection to the observed seasonal variation of cloud properties. Effective radius decreases during the summer season, which results in an increase in reflected solar radiation of 4–8 W m−2 during summer compared to what would be reflected if the effective radius remained constant at its annual-mean value. Summertime increases in low cloud fraction similarly increase the summertime reflection of solar radiation by 9–11 W m−2. In-cloud liquid water path is less in summertime, causing the reflected solar radiation to be 1–4 W m−2 less.
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Keshtgar, Behrooz, Aiko Voigt, Bernhard Mayer, and Corinna Hoose. "Uncertainties in cloud-radiative heating within an idealized extratropical cyclone." Atmospheric Chemistry and Physics 24, no. 8 (April 22, 2024): 4751–69. http://dx.doi.org/10.5194/acp-24-4751-2024.
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Abstract. Cloud-radiative heating (CRH) within the atmosphere affects the dynamics and predictability of extratropical cyclones. However, CRH is uncertain in numerical weather prediction and climate models, and this could affect model predictions of extratropical cyclones. In this paper, we present a systematic quantification of CRH uncertainties. To this end, we study an idealized extratropical cyclone simulated at a convection-permitting resolution of 2.5 km and combine large-eddy-model simulations at a 300 m resolution with offline radiative transfer calculations. We quantify four factors contributing to the CRH uncertainty in different regions of the cyclone: 3D cloud-radiative effects, parameterization of ice optical properties, cloud horizontal heterogeneity, and cloud vertical overlap. The last two factors can be considered essentially resolved at 300 m but need to be parameterized at a 2.5 km resolution. Our results indicate that parameterization of ice optical properties and cloud horizontal heterogeneity are the two factors contributing most to the mean uncertainty in CRH at larger spatial scales and can be more relevant for the large-scale dynamics of the cyclone. On the other hand, 3D cloud-radiative effects are much smaller on average, especially for stratiform clouds within the warm conveyor belt of the cyclone. Our analysis in particular highlights the potential to improve the simulation of CRH by better representing ice optical properties. Future work should, in particular, address how uncertainty in ice optical properties affects the dynamics and predictability of extratropical cyclones.
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Willén, Ulrika, Susanne Crewell, Henk Klein Baltink, and Oliver Sievers. "Assessing model predicted vertical cloud structure and cloud overlap with radar and lidar ceilometer observations for the Baltex Bridge Campaign of CLIWA-NET." Atmospheric Research 75, no. 3 (May 2005): 227–55. http://dx.doi.org/10.1016/j.atmosres.2004.12.008.
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Kim, Minsu, Seonkyung Park, Jeffrey Irwin, Collin McCormick, Jeffrey Danielson, Gregory Stensaas, Aparajithan Sampath, Mark Bauer, and Matthew Burgess. "Positional Accuracy Assessment of Lidar Point Cloud from NAIP/3DEP Pilot Project." Remote Sensing 12, no. 12 (June 19, 2020): 1974. http://dx.doi.org/10.3390/rs12121974.
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The Leica Geosystems CountryMapper hybrid system has the potential to collect data that satisfy the U.S. Geological Survey (USGS) National Geospatial Program (NGP) and 3D Elevation Program (3DEP) and the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) requirements in a single collection. This research will help 3DEP determine if this sensor has the potential to meet current and future 3DEP topographic lidar collection requirements. We performed an accuracy analysis and assessment on the lidar point cloud produced from CountryMapper. The boresighting calibration and co-registration by georeferencing correction based on ground control points are assumed to be performed by the data provider. The scope of the accuracy assessment is to apply the following variety of ways to measure the accuracy of the delivered point cloud to obtain the error statistics. Intraswath uncertainty from a flat surface was computed to evaluate the point cloud precision. Intraswath difference between opposite scan directions and the interswath overlap difference were evaluated to find boresighting or any systematic errors. Absolute vertical accuracy over vegetated and non-vegetated areas were also assessed. Both horizontal and vertical absolute errors were assessed using the 3D absolute error analysis methodology of comparing conjugate points derived from geometric features. A three-plane feature makes a single unique intersection point. Intersection points were computed from ground-based lidar and airborne lidar point clouds for comparison. The difference between two intersection points form one error vector. The geometric feature-based error analysis was applied to intraswath, interswath, and absolute error analysis. The CountryMapper pilot data appear to satisfy the accuracy requirements suggested by the USGS lidar specification, based upon the error analysis results. The focus of this research was to demonstrate various conventional accuracy measures and novel 3D accuracy techniques using two different error computation methods on the CountryMapper airborne lidar point cloud.
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Črnivec, Nina, and Bernhard Mayer. "Quantifying the bias of radiative heating rates in numerical weather prediction models for shallow cumulus clouds." Atmospheric Chemistry and Physics 19, no. 12 (June 20, 2019): 8083–100. http://dx.doi.org/10.5194/acp-19-8083-2019.
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Abstract. The interaction between radiation and clouds represents a source of uncertainty in numerical weather prediction (NWP) due to both intrinsic problems of one-dimensional radiation schemes and poor representation of clouds. The underlying question addressed in this study is how large the NWP radiative bias is for shallow cumulus clouds and how it scales with various input parameters of radiation schemes, such as solar zenith angle, surface albedo, cloud cover and liquid water path. A set of radiative transfer calculations was carried out for a realistically evolving shallow cumulus cloud field stemming from a large-eddy simulation (LES). The benchmark experiments were performed on the highly resolved LES cloud scenes (25 m grid spacing) using a three-dimensional Monte Carlo radiation model. An absence of middle and high clouds is assumed above the shallow cumulus cloud layer. In order to imitate the poor representation of shallow cumulus in NWP models, cloud optical properties were horizontally averaged over the cloudy part of the boxes with dimensions comparable to NWP horizontal grid spacing (several kilometers), and the common δ-Eddington two-stream method with maximum-random overlap assumption for partial cloudiness was applied (denoted as the “1-D” experiment). The bias of the 1-D experiment relative to the benchmark was investigated in the solar and thermal parts of the spectrum, examining the vertical profile of heating rate within the cloud layer and the net surface flux. It is found that, during daytime and nighttime, the destabilization of the cloud layer in the benchmark experiment is artificially enhanced by an overestimation of the cooling at cloud top and an overestimation of the warming at cloud bottom in the 1-D experiment (a bias of about −15 K d−1 is observed locally for stratocumulus scenarios). This destabilization, driven by the thermal radiation, is maximized during nighttime, since during daytime the solar radiation has a stabilizing tendency. The daytime bias at the surface is governed by the solar fluxes, where the 1-D solar net flux overestimates (underestimates) the corresponding benchmark at low (high) Sun. The overestimation at low Sun (bias up to 80 % over land and ocean) is largest at intermediate cloud cover, while the underestimation at high Sun (bias up to −40 % over land and ocean) peaks at larger cloud cover (80 % and beyond). At nighttime, the 1-D experiment overestimates the amount of benchmark surface cooling with the maximal bias of about 50 % peaked at intermediate cloud cover. Moreover, an additional experiment was carried out by running the Monte Carlo radiation model in the independent column mode on cloud scenes preserving their LES structure (denoted as the “ICA” experiment). The ICA is clearly more accurate than the 1-D experiment (with respect to the same benchmark). This highlights the importance of an improved representation of clouds even at the resolution of today's regional (limited-area) numerical models, which needs to be considered if NWP radiative biases are to be efficiently reduced. All in all, this paper provides a systematic documentation of NWP radiative biases, which is a necessary first step towards an improved treatment of radiation–cloud interaction in atmospheric models.
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Williams, Christopher R. "Vertical Air Motion Retrieved from Dual-Frequency Profiler Observations." Journal of Atmospheric and Oceanic Technology 29, no. 10 (October 1, 2012): 1471–80. http://dx.doi.org/10.1175/jtech-d-11-00176.1.
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Abstract The 50-MHz profiler operating near Darwin, Northwest Territory, Australia, is sensitive to both turbulent clear-air (Bragg) and hydrometeor (Rayleigh) scattering processes. Below the radar bright band, the two scattering peaks are observed as two well-separated peaks in the Doppler velocity spectra. The Bragg scattering peak corresponds to the vertical air motion and the Rayleigh scattering peak corresponds to the hydrometeor motion. Within the radar bright band, the Rayleigh scattering peak intensity increases and the downward velocity decreases causing the hydrometeor peak to overlap or merge with the air motion peak. If the overlap of the two peaks is not taken into account, then the vertical air motion estimate will be biased downward. This study describes a filtering procedure that identifies and removes the downward bias in vertical air motions caused by hydrometeor contamination. This procedure uses a second collocated profiler sensitive to hydrometeor motion to identify contamination in the 50-MHz profiler spectra. When applied to four rain events during the Tropical Warm Pool-International Cloud Experiment (TPW-ICE), this dual-frequency filtering method showed that approximately 50% of the single-frequency method vertical air motion estimates within the radar bright band were biased downward due to hydrometeor contamination.
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Zhang, H., X. Jing, and J. Li. "Application and evaluation of a new radiation code under McICA scheme in BCC_AGCM2.0.1." Geoscientific Model Development 7, no. 3 (May 6, 2014): 737–54. http://dx.doi.org/10.5194/gmd-7-737-2014.
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Abstract. This research incorporates the correlated k distribution BCC-RAD radiation model into the climate model BCC_AGCM2.0.1 and examines the change in climate simulation by implementation of the new radiation algorithm. It is shown that both clear-sky radiation fluxes and cloud radiative forcings (CRFs) are improved. The modeled atmospheric temperature and specific humidity are also improved due to changes in radiative heating rates, which most likely stem from the revised treatment of gaseous absorption. Subgrid cloud variability, including vertical overlap of fractional clouds and horizontal inhomogeneity in cloud condensate, is addressed by using the Monte Carlo Independent Column Approximation (McICA) method. In McICA, a cloud-type-dependent function for cloud fraction decorrelation length, which gives zonal mean results very close to the observations of CloudSat/CALIPSO, is developed. Compared to utilizing a globally constant decorrelation length, the maximum changes in seasonal CRFs by the new scheme can be as large as 10 and 20 W m−2 for longwave (LW) and shortwave (SW) CRFs, respectively, mostly located in the tropics. The inclusion of an observation-based horizontal inhomogeneity of cloud condensate has also a significant impact on CRFs, with global means of ~ 1.5 W m−2 and ~ 3.7 Wm−2 for LW and SW CRFs at the top of atmosphere (TOA), respectively. Generally, incorporating McICA and horizontal inhomogeneity of cloud condensate in the BCC-RAD model reduces global mean TOA and surface SW and LW flux biases in BCC_AGCM2.0.1. These results demonstrate the feasibility of the new model configuration to be used in BCC_AGCM2.0.1 for climate simulations, and also indicate that more detailed real-world information on cloud structures should be obtained to constrain cloud settings in McICA in the future.
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Luo, Yali, Steven K. Krueger, and Kuan-Man Xu. "Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-Phase Microphysics Using a Cloud-Resolving Model." Journal of the Atmospheric Sciences 63, no. 11 (November 1, 2006): 2831–47. http://dx.doi.org/10.1175/jas3785.1.
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Abstract This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement Program and output from the University of California, Los Angeles/Colorado State University cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties analyzed by applying the SCM’s assumptions about cloud vertical overlap and horizontal homogeneity to its profiles of cloud water/ice mixing ratio, cloud fraction, and snow flux differed from the cloud radar observations while the CRM simulation reproduced most of the observed cirrus properties. The present study evaluates, through a comparison with the CRM, the SCM’s representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. This study finds that, although the SCM’s detrainment rate profile averaged over the entire simulation period is comparable to the CRM’s, detrainment in the SCM is comparatively sporadic and vertically localized. Too much detrained ice is sublimated when first detrained. Snow formed from detrained cloud ice falls through too deep of a layer. These aspects of the SCM’s parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM), and suggest several possible improvements for the SCM: 1) allowing multiple coexisting cumulus cloud types as in the original Arakawa–Schubert scheme, 2) prognostically determining the stratiform cloud fraction, and 3) explicitly predicting the snow mixing ratio. These would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow flux.
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Perfetti, L., G. P. M. Vassena, F. Fassi, and M. Sgrenzaroli. "TARGETLESS REGISTRATION METHODS BETWEEN UAV LIDAR AND WEARABLE MMS POINT CLOUDS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W1-2023 (May 25, 2023): 395–402. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w1-2023-395-2023.
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Abstract. Fixed-wing Unmanned Aerial Vehicles (UAV) and wearable or portable Mobile Mapping Systems (MMS) are two widely used platforms for point cloud acquisition with Light Detection And Ranging (LiDAR) sensors. The two platforms acquire from distant viewpoints and produce complementary point clouds, one describing predominantly horizontal surfaces and the other primarily vertical. Thus, the registration of the two data is not straightforward. This paper presents a test of targetless registration between a UAV LiDAR point cloud and terrestrial MMS surveys. The case study is a vegetated hilly landscape characterized by the presence of a structure of interest; the UAV acquisition allows the entire area to be acquired from above, while the terrestrial MMS acquisitions will enable the construction of interest to be detailed. The paper describes the survey phase with both techniques. It focuses on processing and registration strategies to fuse the two data together.Our approach is based on the ICP (Iterative Closest Point) method by exploiting the data processing algorithms available in the Heron Desktop post-processing software for handling data acquired with the Heron Backpack MMS instrument. Two co-registration methods are compared. Both ways use the UAV point cloud as a reference and derive the registration of the terrestrial MMS data by finding ICP matches between the ground acquisition and the reference cloud exploiting only a few areas of overlap. The two methods are detailed in the paper, and both allow us to complete the co-registration task.
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Neu, J. L., and M. J. Prather. "Toward a more physical representation of precipitation scavenging in global chemistry models: cloud overlap and ice physics and their impact on tropospheric ozone." Atmospheric Chemistry and Physics Discussions 11, no. 8 (August 31, 2011): 24413–66. http://dx.doi.org/10.5194/acpd-11-24413-2011.
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Abstract. Uptake and removal of soluble trace gases and aerosols by precipitation represents a major uncertainty in the processes that control the vertical distribution of atmospheric trace species. Model representations of precipitation scavenging vary greatly in their complexity, and most are divorced from the physics of precipitation formation and transformation. Here, we describe a new large-scale precipitation scavenging algorithm, developed for the UCI chemistry-transport model (UCI-CTM), that represents a step toward a more physical treatment of scavenging through improvements in the formulation of the removal in sub-gridscale cloudy and ambient environments and their overlap within the column as well as ice phase uptake of soluble species. The UCI algorithm doubles the lifetime of HNO3 in the upper troposphere relative to a scheme with commonly made assumptions about cloud overlap and ice uptake, and provides better agreement with HNO3 observations. We find that the process of ice phase scavenging of HNO3 is a critical component of the tropospheric O3 budget, but that differences in the formulation of ice phase removal, while generating large relative differences in HNO3 abundance, have little impact on NOx and O3. The O3 budget is much more sensitive to the lifetime of HNO4, highlighting the need for better understanding of its interactions with ice and for additional observational constraints.
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Dodson, Dillon S., and Jennifer D. Small Griswold. "Turbulent and boundary layer characteristics during VOCALS-REx." Atmospheric Chemistry and Physics 21, no. 3 (February 10, 2021): 1937–61. http://dx.doi.org/10.5194/acp-21-1937-2021.
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Abstract. Boundary layer and turbulent characteristics (surface fluxes, turbulent kinetic energy – TKE, turbulent kinetic energy dissipation rate – ϵ), along with synoptic-scale changes in these properties over time, are examined using data collected from 18 research flights made with the CIRPAS Twin Otter Aircraft. Data were collected during the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) at Point Alpha (20∘ S, 72∘ W) in October and November 2008 off the coast of South America. The average boundary layer depth is found to be 1148 m, with 28 % of the boundary layer profiles analyzed displaying decoupling. Analysis of correlation coefficients indicates that as atmospheric pressure decreases, the boundary layer height (zi) increases. As has been shown previously, the increase in zi is accompanied by a decrease in turbulence within the boundary layer. As zi increases, cooling near cloud top cannot sustain mixing over the entire depth of the boundary layer, resulting in less turbulence and boundary layer decoupling. As the latent heat flux (LHF) and sensible heat flux (SHF) increase, zi increases, along with the cloud thickness decreasing with increasing LHF. This suggests that an enhanced LHF results in enhanced entrainment, which acts to thin the cloud layer while deepening the boundary layer. A maximum in TKE on 1 November (both overall average and largest single value measured) is due to sub-cloud precipitation acting to destabilize the sub-cloud layer while acting to stabilize the cloud layer (through evaporation occurring away from the surface, primarily confined between a normalized boundary layer height, z/zi, of 0.40 to 0.60). Enhanced moisture above cloud top from a passing synoptic system also acts to reduce cloud-top cooling, reducing the potential for mixing of the cloud layer. This is observed in both the vertical profiles of the TKE and ϵ, in which it is found that the distributions of turbulence for the sub-cloud and in-cloud layer are completely offset from one another (i.e., the range of turbulent values measured have slight or no overlap for the in-cloud and sub-cloud regions), with the TKE in the sub-cloud layer maximizing for the analysis period, while the TKE in the in-cloud layer is below the average in-cloud value for the analysis period. Measures of vertical velocity variance, TKE, and the buoyancy flux averaged over all 18 flights display a maximum near cloud middle (between normalized in-cloud height, Z*, values of 0.25 and 0.75). A total of 10 of the 18 flights display two peaks in TKE within the cloud layer, one near cloud base and another near cloud top, signifying evaporative and radiational cooling near cloud top and latent heating near cloud base. Decoupled boundary layers tend to have a maximum in turbulence in the sub-cloud layer, with only a single peak in turbulence within the cloud layer.
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Neu, J. L., and M. J. Prather. "Toward a more physical representation of precipitation scavenging in global chemistry models: cloud overlap and ice physics and their impact on tropospheric ozone." Atmospheric Chemistry and Physics 12, no. 7 (April 5, 2012): 3289–310. http://dx.doi.org/10.5194/acp-12-3289-2012.
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Abstract. Uptake and removal of soluble trace gases and aerosols by precipitation represents a major uncertainty in the processes that control the vertical distribution of atmospheric trace species. Model representations of precipitation scavenging vary greatly in their complexity, and most are divorced from the physics of precipitation formation and transformation. Here, we describe a new large-scale precipitation scavenging algorithm, developed for the UCI chemistry-transport model (UCI-CTM), that represents a step toward a more physical treatment of scavenging through improvements in the formulation of the removal in sub-gridscale cloudy and ambient environments and their overlap within the column as well as ice phase uptake of soluble species. The UCI algorithm doubles the lifetime of HNO3 in the upper troposphere relative to a scheme with commonly used fractional cloud cover assumptions and ice uptake determined by Henry's Law and provides better agreement with HNO3 observations. We find that the process of ice phase scavenging of HNO3 is a critical component of the tropospheric O3 budget, but that NOx and O3 mixing ratios are relatively insensitive to large differences in the removal rate. Ozone abundances are much more sensitive to the lifetime of HNO4, highlighting the need for better understanding of its interactions with ice and for additional observational constraints.
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Mellado, Juan Pedro, Bjorn Stevens, and Heiko Schmidt. "Wind Shear and Buoyancy Reversal at the Top of Stratocumulus." Journal of the Atmospheric Sciences 71, no. 3 (February 27, 2014): 1040–57. http://dx.doi.org/10.1175/jas-d-13-0189.1.
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Abstract A numerical experiment is designed to study the interaction at the stratocumulus top between a mean vertical shear and the buoyancy reversal due to evaporative cooling, without radiative cooling. Direct numerical simulation is used to eliminate the uncertainty introduced by turbulence models. It is found that the enhancement by shear-induced mixing of the turbulence caused by buoyancy reversal can render buoyancy reversal comparable to other forcing mechanisms. However, it is also found that (i) the velocity jump across the capping inversion Δu needs to be relatively large and values of about 1 m s−1 that are typically associated with the convective motions inside the boundary layer are generally too small and (ii) there is no indication of cloud-top entrainment instability. To obtain these results, parameterizations of the mean entrainment velocity and the relevant time scales are derived from the study of the cloud-top vertical structure. Two overlapping layers can be identified: a background shear layer with a thickness (⅓)(Δu)2/Δb, where Δb is the buoyancy increment across the capping inversion and a turbulence layer dominated by free convection inside the cloud and by shear production inside the relatively thin overlap region. As turbulence intensifies, the turbulence layer encroaches into the background shear layer and defines thereby the entrainment velocity. Particularized to the first research flight of the Second Dynamics and Chemistry of the Marine Stratocumulus (DYCOMS II) field campaign, the analysis predicts an entrainment velocity of about 3 mm s−1 after 5–10 min—a velocity comparable to the measurements and thus indicative of the relevance of mean shear in that case.
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Barrera-Verdejo, M., S. Crewell, U. Löhnert, E. Orlandi, and P. Di Girolamo. "Ground based lidar and microwave radiometry synergy for high vertically resolved thermodynamic profiling." Atmospheric Measurement Techniques Discussions 8, no. 5 (May 29, 2015): 5467–509. http://dx.doi.org/10.5194/amtd-8-5467-2015.
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Abstract. Continuous monitoring of atmospheric humidity and temperature profiles is important for many applications, e.g. assessment of atmospheric stability and cloud formation. While lidar measurements can provide high vertical resolution albeit with limited coverage, microwave radiometers receive information throughout the troposphere though their vertical resolution is poor. In order to overcome these specific limitations the synergy of a Microwave Radiometer (MWR) and a Raman Lidar (RL) system is presented in this work. The retrieval algorithm that combines these two instruments is an Optimal Estimation Method (OEM) that allows for a uncertainty analysis of the retrieved profiles. The OEM combines measurements and a priori information taking the uncertainty of both into account. The measurement vector consists of a set of MWR brightness temperatures and RL water vapor profiles. The method is applied for a two month field campaign around Jülich, Germany for clear sky periods. Different experiments are performed to analyse the improvements achieved via the synergy compared to the individual retrievals. When applying the combined retrieval, on average the theoretically determined absolute humidity error can be reduced by 59.8% (37.9%) with respect to the retrieval using only-MWR (only-RL) data. The analysis in terms of degrees of freedom for signal reveals that most information is gained above the usable lidar range. The retrieved profiles are further evaluated using radiosounding and GPS water vapor measurements. Within a single case study we also explore the potential of the OEM for deriving the relative humidity profile, which is especially interesting to study cloud formation in the vicinity of cloud edges. To do so temperature information is added both from RL and MWR. For temperature, it is shown that the error is reduced by 47.1% (24.6%) with respect to the only-MWR (only-RL) profile. Due to the use of MWR brightness temperatures at multiple elevation angles, the MWR provides significant information below the lidar overlap region as shown by the degrees of freedom for signal. Therefore it might be sufficient to combine RL water vapor with multi-angle, multi-wavelength MWR for the retrieval of relative humidity, however, long-term studies are necessary in the future. In general, the benefit of the sensor combination is especially strong in regions where Raman Lidar data is not available (i.e. overlap region, poor signal to noise ratio), whereas if both instruments are available, RL dominates the retrieval.