Retrieval of Cloud Phase Using the Moderate Resolution Imaging Spectroradiometer Data During the Mixed-Phase Arctic Cloud Experiment PDF Download

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Languages : en
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Improving climate model predictions over Earth's polar regions requires a comprehensive knowledge of polar cloud microphysics. Over the Arctic, there is minimal contrast between the clouds and background snow surface, making it difficult to detect clouds and retrieve their phase from space. Snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds make it even more difficult to determine cloud phase. Also, since determining cloud phase is the first step toward analyzing cloud optical depth, particle size, and water content, it is vital that the phase be correct in order to obtain accurate microphysical and bulk properties. Changes in these cloud properties will, in turn, affect the Arctic climate since clouds are expected to play a critical role in the sea ice albedo feedback. In this paper, the IR trispectral technique (IRTST) is used as a starting point for a WV and 11-[micro]m brightness temperature (T11) parameterization (WVT11P) of cloud phase using MODIS data. In addition to its ability to detect mixed-phase clouds, the WVT11P also has the capability to identify thin cirrus clouds overlying mixed or liquid phase clouds (multiphase ice). Results from the Atmospheric Radiation Measurement (ARM) MODIS phase model (AMPHM) are compared to the surface-based cloud phase retrievals over the ARM North Slope of Alaska (NSA) Barrow site and to in-situ data taken from University of North Dakota Citation (CIT) aircraft which flew during the Mixed-Phase Arctic Cloud Experiment (MPACE). It will be shown that the IRTST and WVT11P combined to form the AMPHM can achieve a relative high accuracy of phase discrimination compared to the surface-based retrievals. Since it only uses MODIS WV and IR channels, the AMPHM is robust in the sense that it can be applied to daytime, twilight, and nighttime scenes with no discontinuities in the output phase.

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: Intergovernmental Panel on Climate Change (IPCC)
Publisher: Cambridge University Press
ISBN: 1139917196
Category : Science
Languages : en
Pages : 1554

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This Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) will again form the standard scientific reference for all those concerned with climate change and its consequences, including students and researchers in environmental science, meteorology, climatology, biology, ecology and atmospheric chemistry. It provides invaluable material for decision makers and stakeholders at international, national and local level, in government, businesses, and NGOs. This volume provides: • An authoritative and unbiased overview of the physical science basis of climate change • A more extensive assessment of changes observed throughout the climate system than ever before • New dedicated chapters on sea-level change, biogeochemical cycles, clouds and aerosols, and regional climate phenomena • Extensive coverage of model projections, both near-term and long-term climate projections • A detailed assessment of climate change observations, modelling, and attribution for every continent • A new comprehensive atlas of global and regional climate projections for 35 regions of the world

Author: M. Shupe
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Languages : en
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Recent in situ observations in stratiform clouds suggest that mixed phase regimes, here defined as limited cloud volumes containing both liquid and solid water, are constrained to narrow layers (order 100 m) separating all-liquid and fully glaciated volumes (Hallett and Viddaurre, 2005). The Department of Energy Atmospheric Radiation Measurement Program's (DOE-ARM, Ackerman and Stokes, 2003) North Slope of Alaska (NSA) ARM Climate Research Facility (ACRF) recently started collecting routine measurement of radar Doppler velocity power spectra from the Millimeter Cloud Radar (MMCR). Shupe et al. (2004) showed that Doppler spectra has potential to separate the contributions to the total reflectivity of the liquid and solid water in the radar volume, and thus to investigate further Hallett and Viddaurre's findings. The Mixed-Phase Arctic Cloud Experiment (MPACE) was conducted along the NSA to investigate the properties of Arctic mixed phase clouds (Verlinde et al., 2006). We present surface based remote sensing data from MPACE to discuss the fine-scale structure of the mixed-phase clouds observed during this experiment.

Author: Intergouvernemental panel on climate change. Working group 1
Publisher: Cambridge University Press
ISBN: 110705799X
Category : Climatic changes
Languages : en
Pages : 1553

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The report also provides a comprehensive assessment of past and future sea level change in a dedicated chapter.

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ISBN:
Category :
Languages : en
Pages : 183

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A novel new approach to retrieve cloud microphysical properties from mixed-phase clouds is presented. This algorithm retrieves cloud optical depth, ice fraction, and the effective size of the water and ice particles from ground-based, high-resolution infrared radiance observations. The theoretical basis is that the absorption coefficient of ice is stronger than that of liquid water from 10-13 mm, whereas liquid water is more absorbing than ice from 16-25 um. However, due to strong absorption in the rotational water vapor absorption band, the 16-25 um spectral region becomes opaque for significant water vapor burdens (id est, for precipitable water vapor amounts over approximately 1 cm). The Arctic is characterized by its dry and cold atmosphere, as well as a preponderance of mixed-phase clouds, and thus this approach is applicable to Arctic clouds. Since this approach uses infrared observations, cloud properties are retrieved at night and during the long polar wintertime period. The analysis of the cloud properties retrieved during a 7 month period during the Surface Heat Budget of the Arctic (SHEBA) experiment demonstrates many interesting features. These results show a dependence of the optical depth on cloud phase, differences in the mode radius of the water droplets in liquid-only and mid-phase clouds, a lack of temperature dependence in the ice fraction for temperatures above 240 K, seasonal trends in the optical depth with the clouds being thinner in winter and becoming more optically thick in the late spring, and a seasonal trend in the effective size of the water droplets in liquid-only and mixed-phase clouds that is most likely related to aerosol concentration.

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Languages : en
Pages :

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By making use of the in-situ data collected from the recent Atmospheric Radiation Measurement Mixed-Phase Arctic Cloud Experiment, we have tested the mixed-phase cloud parameterizations used in the two major U.S. climate models, the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) and the Geophysical Fluid Dynamics Laboratory climate model (AM2), under both the single-column modeling framework and the U.S. Department of Energy Climate Change Prediction Program-Atmospheric Radiation Measurement Parameterization Testbed. An improved and more physically based cloud microphysical scheme for CAM3 has been also tested. The single-column modeling tests were summarized in the second quarter 2007 Atmospheric Radiation Measurement metric report. In the current report, we document the performance of these microphysical schemes in short-range weather forecasts using the Climate Chagne Prediction Program Atmospheric Radiation Measurement Parameterizaiton Testbest strategy, in which we initialize CAM3 and AM2 with realistic atmospheric states from numerical weather prediction analyses for the period when Mixed-Phase Arctic Cloud Experiment was conducted.

Author: Alexander A. Kokhanovsky
Publisher: Springer Science & Business Media
ISBN: 3642155316
Category : Science
Languages : en
Pages : 353

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This is the next volume in series of Light Scattering Reviews. Volumes 1-5 have already been printed by Springer. The volume is composed of several papers ( usually, 10) of leading researchers in the respective field. The main focus of this book is light scattering, radiative transfer and optics of snow.

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Languages : en
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The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during October 9th-10th, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-hour simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation due to freezing of supercooled water in both saturated and subsaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.

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Languages : en
Pages : 33

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We proposed to analyze in-situ cloud data collected during ARM/ASR field campaigns to create databases of cloud microphysical properties and their uncertainties as needed for the development of improved cloud parameterizations for models and remote sensing retrievals, and for evaluation of model simulations and retrievals. In particular, we proposed to analyze data collected over the Southern Great Plains (SGP) during the Mid-latitude Continental Convective Clouds Experiment (MC3E), the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX), the Small Particles in Cirrus (SPARTICUS) Experiment and the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign, over the North Slope of Alaska during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) and the Mixed-Phase Arctic Cloud Experiment (M-PACE), and over the Tropical Western Pacific (TWP) during The Tropical Warm Pool International Cloud Experiment (TWP-ICE), to meet the following 3 objectives; derive statistical databases of single ice particle properties (aspect ratio AR, dominant habit, mass, projected area) and distributions of ice crystals (size distributions SDs, mass-dimension m-D, area-dimension A-D relations, mass-weighted fall speeds, single-scattering properties, total concentrations N, ice mass contents IWC), complete with uncertainty estimates; assess processes by which aerosols modulate cloud properties in arctic stratus and mid-latitude cumuli, and quantify aerosol's influence in context of varying meteorological and surface conditions; and determine how ice cloud microphysical, single-scattering and fall-out properties and contributions of small ice crystals to such properties vary according to location, environment, surface, meteorological and aerosol conditions, and develop parameterizations of such effects. In this report we describe the accomplishments that we made on all 3 research objectives.