Analysis Of In Situ Observations Of Cloud Microphysics From M Pace Final Report Doe Grant Agreement No De Fg02 06er64168
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| Release | : 2009 |
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This report summarizes the findings and accomplishments of work performed under DOE Grant Agreement No. DE-FG02-06ER64168. The focus of the work was the analysis of in situ observations collected by the University of North Dakota Citation research aircraft during the Mixed-Phase Arctic Cloud Experiment (M-PACE). This project was conducted in 2004 along the North Slope of Alaska. The objectives of the research were: to characterize certain microphysical properties of clouds sampled during M-PACE, including spatial variability, precipitation formation, ice multiplication; to examine instrument performance and certain data processing algorithms; and to collaborate with other M-PACE investigators on case study analyses. A summary of the findings of the first two objectives is given here in parts 1 and 2; full results are contained in reports listed in part 3 of this report. The collaborative efforts are described in the publications listed in part 3.
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| Release | : 2003 |
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We were funded by ASR to use data collected during ISDAC and TWP-ICE to evaluate models with a variety of temporal and spatial scales, to evaluate ground-based remote sensing retrievals and to develop cloud parameterizations with the end goal of improving the modeling of cloud processes and properties and their impact on atmospheric radiation. In particular, we proposed to: 1) Calculate distributions of microphysical properties observed in arctic stratus during ISDAC for initializing and evaluating LES and GCMs, and for developing parameterizations of effective particle sizes, mean fall velocities, and mean single-scattering properties for such models; 2) Improve representations of particle sizes, fall velocities and scattering properties for tropical and arctic cirrus using TWP-ICE, ISDAC and M-PACE data, and to determine the contributions that small ice crystals, with maximum dimensions D less than 50 [mu]m, make to mass and radiative properties; 3) Study fundamental interactions between clouds and radiation by improving representations of small quasi-spherical particles and their scattering properties. We were additionally funded 1-year by ASR to use RACORO data to develop an integrated product of cloud microphysical properties. We accomplished all of our goals.
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| Release | : 2013 |
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This report briefly summaries the work performed at KNMI under DOE Grant DE-FG02-06ER64160 which, in turn was conducted in support of DOE Grant DE-FG02-90ER61071 lead by E. Clothieux of Penn. State U. The specific work at KNMI revolved around the development and application of the EarthCARE simulator to ground-based multi-sensor simulations.
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| Total Pages | : 48 |
| Release | : 2008 |
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The purpose of this proposal is to gain a better understanding of the space-time correlations of atmospheric fluctuations in clouds through application of methods from statistical physics to high resolution, continuous data sets of cloud observations available at the Department of Energy Atmospheric Radiation Measurement Program archive. In this report we present the accomplishments achieved during the four year period. Starting with the most recent one, we report on two break-throughs in our research that make the fourth year of the project exceptionally successful and markedly outperforming the objectives. The first break-through is on characterization of the structure of cirrus radiative properties at large, intermediate and small, generating cells scales by applying the Fokker-Planck equation method and other methods to ARM millimeter wavelength radar observations collected at the Southern Great Plains site. The second break-through is that we show that different characterizations of the cirrus radiative properties are obtained for different synoptic scale environments. We outline a stochastic approach to investigate the internal structure of radiative properties of cirrus clouds based on empirical modeling and draw conclusions about cirrus dynamical properties in the context of the synoptic environment. Results on the structure of cirrus dynamical properties are consistent with the structure of cirrus based on aircraft in situ measurements, with results from ground-based Raman lidar, and with results from model studies. These achievements would not have been possible without the accomplishments from the previous years on a number of problems that involve application of methods of analysis such as the Fokker-Planck equation approach, Tsallis nonextensive statistical mechanics, detrended fluctuation analysis, and others. These include stochastic analysis of neutrally stratified cirrus layers, internal variability and turbulence in cirrus, dynamical model and nonextensive statistical mechanics of liquid water path fluctuations, etc.
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| Release | : 2012 |
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In this project, we focused on applications of the new warm-rain and ice microphysics schemes to simulate various cloud systems. The overall goal was either to evaluate and improve specific aspects of the schemes (through comparisons with ARM/ASR observations) or to understand the coupling between aerosols, cloud microphysics and cloud dynamics in variety of situations. These studies are relevant to the indirect impact of atmospheric aerosols on climate. Below we report on selected key aspects of the research and then list all peer-reviewed papers that acknowledge support from this grant. Overall, studies partially supported by this grant resulted in 30 peer-reviewed publications (listed below), several dozens of conference presentations (including posters and oral presentations at the ASR Science Team Meetings), and two PhD dissertations. More detailed summaries of our accomplishments are included in yearly reports. Here we summarize only major efforts.
| Author | : Jerry M. Straka |
| Publisher | : Cambridge University Press |
| Total Pages | : 407 |
| Release | : 2009-06-11 |
| Genre | : Science |
| ISBN | : 1139478834 |
This book focuses specifically on bin and bulk parameterizations for the prediction of cloud and precipitation at various scales - the cloud scale, mesoscale, synoptic scale, and the global climate scale. It provides a background to the fundamental principles of parameterization physics, including processes involved in the production of clouds, ice particles, liquid water, snow aggregate, graupel and hail. It presents full derivations of the parameterizations, allowing readers to build parameterization packages, with varying levels of complexity based on information in the book. Architectures for a range of dynamical models are given, in which parameterizations form a significant tool for investigating large non-linear numerical systems. Model codes are available online at www.cambridge.org/9780521883382. Written for researchers and advanced students of cloud and precipitation microphysics, this book is also a valuable reference for all atmospheric scientists involved in models of numerical weather prediction.
| Author | : Meng Zhang |
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| Total Pages | : 52 |
| Release | : 2017 |
| Genre | : Arctic regions |
| ISBN | : 9780355325027 |
Mixed-phase clouds are persistently observed in the Arctic and the phase partition of cloud liquid and ice in mixed-phase clouds has important impacts on the surface energy budget and Arctic climate. In this study, we test the NCAR Community Atmosphere Model Version 5 (CAM5) in the single-column and weather forecast modes and evaluate the model performance against observation data obtained during the DOE Atmospheric Radiation Measurement (ARM) Program’s M-PACE field campaign in October 2004 and long-term ground-based multi-sensor measurements. We find that CAM5, like other global climate models, poorly simulates the phase partition in mixed-phase clouds by significantly underestimating the cloud liquid water content. An assumption of the pocket structure in the distribution of cloud liquid and ice based on in situ observations inside mixed-phase clouds has provided a possible solution to improve the model performance by reducing the Wegner-Bergeron-Findeisen (WBF) process rate. In this study, the modification of the WBF process in the CAM5 model has been achieved with applying a stochastic perturbation to the time scale of the WBF process relevant to both ice and snow to account for the heterogeneous mixture of cloud liquid and ice. Our results show that the modification of the WBF process improves the modeled phase partition in mixed-phase clouds. The seasonality of mixed-phase cloud properties is also better captured in the model compared with long-term ground-based remote sensing observations. Furthermore, the phase partitioning is insensitive to the reassignment time step of perturbations.
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| Release | : 2010 |
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Final Report for research grant DE-FG02-05ER63965.
| Author | : Steven A. Ackerman |
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| Total Pages | : 1 |
| Release | : 2002 |
| Genre | : Cloud physics |
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| Release | : 2007 |
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Mixed-phase clouds are composed of a mixture of cloud droplets and ice crystals. The cloud microphysics in mixed-phase clouds can significantly impact cloud optical depth, cloud radiative forcing, and cloud coverage. However, the treatment of mixed-phase clouds in most current climate models is crude and the partitioning of condensed water into liquid droplets and ice crystals is prescribed as temperature dependent functions. In our previous 2007 ARM metric reports a new mixed-phase cloud microphysics parameterization (for ice nucleation and water vapor deposition) was documented and implemented in the NCAR Community Atmospheric Model Version 3 (CAM3). The new scheme was tested against the Atmospheric Radiation Measurement (ARM) Mixed-phase Arctic Cloud Experiment (M-PACE) observations using the single column modeling and short-range weather forecast approaches. In this report this new parameterization is further tested with CAM3 in its climate simulations. It is shown that the predicted ice water content from CAM3 with the new parameterization is in better agreement with the ARM measurements at the Southern Great Plain (SGP) site for the mixed-phase clouds.
