Study of Ice Cloud Properties from Synergetic Use of Satellite Observations and Modeling Capabilities PDF Download

Author: Yu Xie
Publisher:
ISBN:
Category :
Languages : en
Pages :

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The dissertation first investigates the single-scattering properties of inhomogeneous ice crystals containing air bubbles. Specifically, a combination of the ray-tracing technique and the Monte Carlo method is used to simulate the scattering of light by randomly oriented large hexagonal ice crystals containing spherical or spheroidal air bubbles. The effect of the air bubbles within ice crystals is to smooth the phase functions, diminish the 22° and 46° halo peaks, and reduce the backscatter in comparison with the case of bubble-free ice crystals. Cloud reflectance look-up tables were generated at the wavelengths of 0.65 um and 2.13 um to examine the impact of accounting for air bubbles in ice crystal morphology on the retrieval of ice cloud optical thickness and effective particle size. To investigate the effect of the representation of aggregates on electromagnetic scattering calculations, an algorithm is developed to efficiently specify the geometries of aggregates and to compute some of their geometric parameters such as the projected area. Based on in situ observations, aggregates are defined as clusters of hexagonal plates with a chain-like overall shape. An aggregate model is developed with 10 ensemble members, each consisting of between 4-12 hexagonal plates. The scattering properties of an individual aggregate ice particle are computed using the discrete dipole approximation or an Improved Geometric Optics Method, depending upon the size parameter. The aggregate model provides an accurate and computationally efficient way to represent all aggregates occurring within ice clouds. We developed an algorithm to determine an appropriate ice cloud model for application to satellite-based retrieval of ice cloud properties. Collocated Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging SpectroRadiometer (MISR) data are used to retrieve the optical thicknesses of ice clouds as a function of scattering angle in the nine MISR viewing directions. The difference between cloud optical thickness and its averaged value over the nine viewing angles can be used to validate the ice cloud models. Using the data obtained on 2 July 2009, an appropriate ice cloud model is determined. With the presence of all the uncertainties in the current operational satellite-based retrievals of ice cloud properties, this ice cloud model has excellent performance in terms of consistency in cloud property retrievals with the nine MISR viewing angles.

Author: Benjamin Cole
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ISBN:
Category :
Languages : en
Pages :

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Uncertainties associated with the microphysical and radiative properties of ice clouds remain an active research area because of the importance these clouds have in atmospheric radiative transfer problems and the energy balance of the Earth. In this study, an adding/doubling model is used to simulate the top of atmosphere (TOA) radiance and full Stokes vector from an ice cloud at the wavelength lambda = 865 nm with many different combinations of assumed ice habits (shapes) and different degrees of ice surface roughness, and the polarized radiance at a wide range of scattering angles is derived. Simulated results are compared with polarized radiance data from the POLDER (POLarization and Directionality of the Earth's Reflectances) instrument on board the PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) satellite. Bulk ice scattering properties are obtained by using five different size distributions collected during field campaigns ranging in effective diameter from 10 micrometers to 90 micrometers. Bulk scattering properties for the MODIS Collection 5 ice cloud product are used in this study, along with properties for two mid-latitude ice cloud models, a polar/mid-latitude ice model, and a model built for ice clouds over deep convection. Solid columns and hollow columns are used as well. The polarized radiance simulation results for the moderate surface roughness level best fit the satellite measurements for all ice models, though severely roughened ice crystals do fare well in a few cases. Hollow columns are the best fit to the satellite polarization measurements, but of the ensemble ice models, the polar/mid-latitude model at an effective diameter of 90 micrometers best fits the polarized radiance measurements for the one day of PARASOL data considered. This model should be the best to simulate ice cloud properties on a global scale.

Author: Kerry Glynne Meyer
Publisher:
ISBN:
Category :
Languages : en
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Ice clouds occur quite frequently, yet so much about these clouds is unknown. In recent years, numerous investigations and field campaigns have been focused on the study of ice clouds, all with the ultimate goal of gaining a better understanding of microphysical and optical properties, as well as determining the radiative impact. Perhaps one of the most recognized instruments used for such research is the Moderate-resolution Imaging Spectroradiometer (MODIS), carried aboard the NASA EOS satellites Terra and Aqua. The present research aims to support ongoing efforts in the field of ice cloud research by use of observations obtained from Terra and Aqua MODIS. First, a technique is developed to infer ice cloud optical depth from the MODIS cirrus reflectance parameter. This technique is based on a previous method developed by Meyer et al. (2004). The applicability of the algorithm is demonstrated with retrievals from level-2 and -3 MODIS data. The technique is also evaluated with the operational MODIS cloud retrieval product and a method based on airborne ice cloud observations. From this technique, an archive of daily optical depth retrievals is constructed. Using simple statistics, the global spatial and temporal distributions of ice clouds are determined. Research has found that Aqua MODIS observes more frequent ice clouds and larger optical depths and ice water paths than does Terra MODIS. Finally, an analysis of the time series of daily optical depth values revealed that ice clouds at high latitudes, which are most likely associated with synoptic scale weather sytems, persist long enough to move with the upper level winds. Tropical ice clouds, however, dissipate more rapidly, and are in all likelihood associated with deep convective cells.

Author: Joannès Berque
Publisher:
ISBN:
Category : Atmosphere
Languages : en
Pages : 436

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A radiative transfer model of the Antarctic snow-atmosphere system was developed, as radiometric contrast between clouds and the snow hinders remote sensing of clouds and surface properties over the high ice sheets. The radiative effect of clouds at the top of the atmosphere was evaluated over the South Pole with ground-based lidar observations and data from NASA's Terra satellite.

Author: Katherine Loraine Pitts
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Clouds continue to be a large source of uncertainty within global climate models. While satellites provide the only global datasets for comparison with these models, satellite retrievals provide inferences of cloud properties, rather than direct measurements. Therefore, comparisons between climate model simulations and satellite retrievals require careful construction of globally-gridded and time-averaged (Level 3) satellite datasets. For some types of comparisons, existing Level 3 datasets may not be sufficient, necessitating the generation of gridded datasets directly from Level 2 products. The current study uses a filtering and gridding algorithm to create a customized globally-gridded (i.e., Level 3) dataset based on Aqua MODIS Level 2 cloud top pressure and cloud optical property retrievals. With the recent release of MODIS Collection 6, we utilize this algorithm to examine the differences between cloud parameters in the MODIS Collection 5 and Collection 6 datasets, and then compare these satellite measurements to the GISS-E2-H model-simulated cloud parameters that were provided for the Coupled Model Intercomparison Project - Phase 5 (CMIP5). This comparison study focuses on the vertical distribution of cloud liquid water and ice, especially in the mid-troposphere where mixed-phase clouds are most likely to occur. Results show that the cloud retrieval algorithm improvements with MODIS Collection 6 lead to an overall decrease in uncertainty in cloud water path retrievals, as well as a change in the vertical distribution of clouds (high clouds higher, low clouds lower) and the resulting vertical distribution of cloud water path (increased mid-level cloud water path). When MODIS Collection 6 data are compared with GISS-E2-H climate model simulations, it is clear that the model greatly overestimates ice water path within a double ITCZ (intertropical convergence zone) in the high cloud height regime, but underestimates ice water path in higher latitudes. The model also overestimates low level liquid water path over land, especially over mountainous regions. The filtering and gridding algorithm used in this study is a convenient tool for building custom gridded datasets to address research questions that the official Level 3 datasets were not designed for. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155013

Author: Constantin Andronache
Publisher: Elsevier
ISBN: 012810550X
Category : Science
Languages : en
Pages : 302

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Mixed-Phase Clouds: Observations and Modeling presents advanced research topics on mixed-phase clouds. As the societal impacts of extreme weather and its forecasting grow, there is a continuous need to refine atmospheric observations, techniques and numerical models. Understanding the role of clouds in the atmosphere is increasingly vital for current applications, such as prediction and prevention of aircraft icing, weather modification, and the assessment of the effects of cloud phase partition in climate models. This book provides the essential information needed to address these problems with a focus on current observations, simulations and applications. Provides in-depth knowledge and simulation of mixed-phase clouds over many regions of Earth, explaining their role in weather and climate Features current research examples and case studies, including those on advanced research methods from authors with experience in both academia and the industry Discusses the latest advances in this subject area, providing the reader with access to best practices for remote sensing and numerical modeling

Author: Benjamin H. Cole
Publisher:
ISBN:
Category :
Languages : en
Pages : 112

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The energy balance of the Earth is regulated in part by ice clouds, which both reflect shortwave solar radiation and absorb infrared radiation from the Earth. These clouds appear frequently worldwide, with up to 70% coverage in tropical regions. The microphysics of ice clouds determines their radiative properties, and is important for accurately predicting the role of ice clouds in Earth's energy balance. However, describing the microphysics of ice clouds remains a challenging problem, especially with regard to the shape of ice particles and the degree of ice particle surface roughening. In-situ studies have found evidence for ice surface roughness and have found many complex ice geometries; however, these studies are limited spatially and temporally. An approach which allows large-scale analysis is to retrieve these properties via theoretical modeling using satellite observations of polarized reflectance from ice clouds, since polarized reflectance is sensitive to the shape and roughness of ice particles. The theoretical model requires the scattering properties of simulated ice particles. These properties are obtained for 10 different ice shapes and 17 different levels of surface roughness. Simulations are performed for 3 different effective ice particle diameters: 30, 60 and 90 [mu]m. Overall, the retrieved shape is dominated by the compact aggregate of columns. Although the exact composition of shapes varies from month to month, the compact aggregate of columns remains the most commonly retrieved shape. The retrieved roughness varies from moderately rough at [delta] = 0.1 to severely rough at [delta] = 0.5. Retrieved roughness varies more than shape, and smooth surfaced ice is most prominent in January. Tropical regions tend to have ice particles that are more roughened, while the midlatitudes and polar regions tend to have more smooth ice. In almost all cases, roughened ice represents > 60% of the total retrievals. The asymmetry parameter inferred from the retrieval of ice particle shape and roughness has a mean value near 0.77, with only small differences based on assumed ice effective diameter. The median value of the asymmetry parameter has a nearly constant value of approximately 0.75. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151196

Author: Christopher James Nankervis
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Loknath Adhikari
Publisher:
ISBN: 9781267820068
Category : Antarctica
Languages : en
Pages : 146

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Clouds in the polar regions play an important roles in the hydrologic cycle, the local radiative balance, and polar sea ice. However, harsh climatic conditions and perennial snow and ice cover limits the collection of cloud data from the surface as well as the effectiveness of cloud detection with satellite passive sensors. Therefore, there is a lack of reliable data on polar clouds and their properties. This study combines active and passive measurements from the NASA A-Train satellites to overcome these shortcomings and to provide a novel approach to study on polar clouds. Multi-year CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to investigate the characteristics of tropospheric clouds and precipitation systems, and their effect on the occurrence and microphysical properties of polar stratospheric clouds in the Antarctic region, south of 60 °S. The lidar and radar data are collocated to derive a combined cloud mask to improve detection of cloud vertical structure. Polar stratospheric clouds were detected using CALIPSO attenuated lidar scattering ratios (ALSR) at a horizontal resolution of 20 km to achieve good signal-to-noise ratios to allow the detection of tenuous PSCs. Clouds in the Antarctic region exhibit distinct land-sea and seasonal variabilities. The mean annual cloud occurrence is ~ 50 % over the continent and ~ 85 % over the ocean. Over the ocean the mean occurrence is higher in summer (90 %) than in winter (70 %). Low-level clouds contribute to more than 60 % of the total clouds. However, due to the extensive snow cover and cold surfaces in winter these low-level cloud occurrences are smaller in winter (50 %) than in summer (65 %). For ice clouds, both the effective radius and ice water content are larger in summer than in winter. High-level and deep tropospheric clouds strongly affect polar stratospheric cloud (PSC) occurrence and their microphysical properties by providing additional cooling of the lower stratosphere, especially during late winter and early spring. 70 % of all PSCs and 80 % of ice PSCs are formed in connection with tropospheric cloud systems during September and October. Similarly, PSCs associated with tropospheric cloud systems have higher particle number concentration than PSCs not associated with tropospheric cloud systems. A novel stratiform mixed-phase cloud retrieval algorithm has been developed by combining CloudSat, CALIPSO and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements to address the large positive biases of the MODIS operational algorithm, which assumes a single liquid- or ice-phase in its retrieval for mixed-phase clouds. The algorithm is validated using collocated MODIS and ground-based measurements at the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) North Slope Alaska (NSA) site. Results indicate that the new mixed-phase algorithm reduces the positive LWP biases of the operational MODIS algorithm from 35 % and 68 % to 10 % and 22 % over the temperature ranges of -5 to -10 °C and -10 to -20 °C, respectively.

Author: Vinay Kumar Kayetha
Publisher:
ISBN:
Category : Ice clouds
Languages : en
Pages : 328

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In this research we investigate the global occurrence and properties of optically thin midlevel ice clouds. These clouds are difficult to detect with passive radiometric techniques and are under-represented in current studies. We use the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data set to identify thin midlevel ice clouds and determine their global occurrence and distribution. For the first time, we find that the global mean occurrence of these clouds is at least 4.5%, being at least 7.3% of all the tropospheric clouds detected at a horizontal scale of 10 km. Seasonally, these clouds are found most commonly in the polar regions. These clouds occur most commonly in the Arctic in winter and least commonly in the summer. In winter these clouds can occur up to 19% of the time. The occurrence of these clouds decreases with increasing spatial scale and are most commonly found at spatial scales of 25 km or less. We found five large distinct clouds over the Arctic and investigated them for their meteorological conditions and radiative effects. These thin midlevel ice clouds are formed along the frontal zones in weakly ascending air masses. Our model simulations show that thin midlevel ice clouds have a net warming effect on the surface of 23-48 W/m2. We conclude that these clouds have a significant impact on the radiation budget in Arctic winters. Our study highlights the importance of active satellite-based remote sensing in globally detecting and characterizing optically thin clouds. Our estimates of occurrence and fraction of clouds represents a lower bound, as these clouds can be obscured by optically thicker clouds. The volume of measurements provided by the satellite allowed us to identify a small but consistent set of large clouds with which we could conduct a contemporary radiative analysis. These findings can be used to improve the representation of clouds and their impacts in regional and global climate models.