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Intercomparison of Model Simulations of Mixed-phase Clouds Observed During the ARM Mixed-Phase Arctic Cloud Experiment. Part I

Intercomparison of Model Simulations of Mixed-phase Clouds Observed During the ARM Mixed-Phase Arctic Cloud Experiment. Part I PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 80

Book Description
Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed liquid water path of around 160 g m−2 was about two-thirds of the adiabatic value and much greater than the mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m−2. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics indicate that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is some evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics. This case study, which has been well observed from both aircraft and ground-based remote sensors, could be a benchmark for model simulations of mixed-phase clouds.

Intercomparison of Model Simulations of Mixed-phase Clouds Observed During the ARM Mixed-Phase Arctic Cloud Experiment. Part I

Intercomparison of Model Simulations of Mixed-phase Clouds Observed During the ARM Mixed-Phase Arctic Cloud Experiment. Part I PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 80

Book Description
Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed liquid water path of around 160 g m−2 was about two-thirds of the adiabatic value and much greater than the mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m−2. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics indicate that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is some evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics. This case study, which has been well observed from both aircraft and ground-based remote sensors, could be a benchmark for model simulations of mixed-phase clouds.

Intercomparison of Model Simulations of Mixed-phase Clouds Observed During the ARM Mixed-Phase Arctic Cloud Experiment. Part II

Intercomparison of Model Simulations of Mixed-phase Clouds Observed During the ARM Mixed-Phase Arctic Cloud Experiment. Part II PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 65

Book Description
Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a deep, multi-layered, mixed-phase cloud system observed during the ARM Mixed-Phase Arctic Cloud Experiment. This cloud system was associated with strong surface turbulent sensible and latent heat fluxes as cold air flowed over the open Arctic Ocean, combined with a low pressure system that supplied moisture at mid-level. The simulations, performed by 13 single-column and 4 cloud-resolving models, generally overestimate the liquid water path and strongly underestimate the ice water path, although there is a large spread among the models. This finding is in contrast with results for the single-layer, low-level mixed-phase stratocumulus case in Part I of this study, as well as previous studies of shallow mixed-phase Arctic clouds, that showed an underprediction of liquid water path. The overestimate of liquid water path and underestimate of ice water path occur primarily when deeper mixed-phase clouds extending into the mid-troposphere were observed. These results suggest important differences in the ability of models to simulate Arctic mixed-phase clouds that are deep and multi-layered versus shallow and single-layered. In general, models with a more sophisticated, two-moment treatment of the cloud microphysics produce a somewhat smaller liquid water path that is closer to observations. The cloud-resolving models tend to produce a larger cloud fraction than the single-column models. The liquid water path and especially the cloud fraction have a large impact on the cloud radiative forcing at the surface, which is dominated by the longwave flux for this case.

Mixed-Phase Clouds

Mixed-Phase Clouds PDF Author: Constantin Andronache
Publisher: Elsevier
ISBN: 012810550X
Category : Science
Languages : en
Pages : 302

Book Description
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

Thermodynamics, Kinetics and Microphysics of Clouds

Thermodynamics, Kinetics and Microphysics of Clouds PDF Author: Vitaly I. Khvorostyanov
Publisher: Cambridge University Press
ISBN: 1107016037
Category : Science
Languages : en
Pages : 801

Book Description
This book advances understanding of cloud microphysics and provides a unified theoretical foundation for modeling cloud processes, for researchers and advanced students.

Physical Processes in Clouds and Cloud Modeling

Physical Processes in Clouds and Cloud Modeling PDF Author: Alexander P. Khain
Publisher: Cambridge University Press
ISBN: 1108651550
Category : Science
Languages : en
Pages : 643

Book Description
This book presents the most comprehensive and systematic description currently available of both classical and novel theories of cloud processes, providing a much-needed link between cloud theory, observation, experimental results, and cloud modeling. This volume shows why and how modern models serve as a major tool of investigation of cloud processes responsible for atmospheric phenomena, including climate change. It systematically describes classical as well as recent advancements in cloud physics, including cloud-aerosol interaction; collisions of particles in turbulent clouds; and the formation of multiphase cloud particles. As the first of its kind to serve as a practical guide for using state-of-the-art numerical cloud models, major emphasis is placed on explaining how microphysical processes are treated in modern numerical cloud resolving models. The book will be a valuable resource for advanced students, researchers and numerical model designers in cloud physics, atmospheric science, meteorology, and environmental science.

Arctic mixed-phase clouds : Macro- and microphysical insights with a numerical model

Arctic mixed-phase clouds : Macro- and microphysical insights with a numerical model PDF Author: Loewe, Katharina
Publisher: KIT Scientific Publishing
ISBN: 3731506866
Category : Physics
Languages : en
Pages : 174

Book Description
This work provides new insights into macro- and microphysical properties of Arctic mixed-phase clouds: first, by comparing semi-idealized large eddy simulations with observations; second, by dissecting the influences of different surface types and boundary layer structures on Arctic mixed- phase clouds; third, by elucidating the dissipation process; and finally by analyzing the main microphysical processes inside Arctic mixed-phase clouds.

Fast Processes in Large-Scale Atmospheric Models

Fast Processes in Large-Scale Atmospheric Models PDF Author: Yangang Liu
Publisher: John Wiley & Sons
ISBN: 1119528992
Category : Science
Languages : en
Pages : 483

Book Description
Improving weather and climate prediction with better representation of fast processes in atmospheric models Many atmospheric processes that influence Earth’s weather and climate occur at spatiotemporal scales that are too small to be resolved in large scale models. They must be parameterized, which means approximately representing them by variables that can be resolved by model grids. Fast Processes in Large Scale Atmospheric Models: Progress, Challenges and Opportunities explores ways to better investigate and represent multiple parameterized processes in models and thus improve their ability to make accurate climate and weather predictions. Volume highlights include: Historical development of the parameterization of fast processes in numerical models Different types of major sub-grid processes and their parameterizations Efforts to unify the treatment of individual processes and their interactions Top-down versus bottom-up approaches across multiple scales Measurement techniques, observational studies, and frameworks for model evaluation Emerging challenges, new opportunities, and future research directions The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.

An Improved Understanding of the Lifecycle of Mixed-phase Stratiform Clouds Through Oberservations and Simulation

An Improved Understanding of the Lifecycle of Mixed-phase Stratiform Clouds Through Oberservations and Simulation PDF Author: Gijs De Boer
Publisher:
ISBN:
Category :
Languages : en
Pages : 168

Book Description


Simulations of Arctic Mixed-phase Clouds in Forecasts with CAM3 and AM2 for M-PACE.

Simulations of Arctic Mixed-phase Clouds in Forecasts with CAM3 and AM2 for M-PACE. PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 45

Book Description
[1] Simulations of mixed-phase clouds in forecasts with the NCAR Atmosphere Model version 3 (CAM3) and the GFDL Atmospheric Model version 2 (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed using analysis data from numerical weather prediction centers. CAM3 significantly underestimates the observed boundary layer mixed-phase cloud fraction and cannot realistically simulate the variations of liquid water fraction with temperature and cloud height due to its oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer cloud fraction while its clouds contain much less cloud condensate than CAM3 and the observations. The simulation of the boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used (CAM3LIU). The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes. Sensitivity tests show that these results are not sensitive to the analysis data used for model initialization. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. AM2 simulated cloud fraction and LWP are sensitive to the change in cloud ice number concentrations used in the Wegener-Bergeron-Findeisen process while CAM3LIU only shows moderate sensitivity in its cloud fields to this change. Furthermore, this paper shows that the Wegener-Bergeron-Findeisen process is important for these models to correctly simulate the observed features of mixed-phase clouds.

Current Trends in the Representation of Physical Processes in Weather and Climate Models

Current Trends in the Representation of Physical Processes in Weather and Climate Models PDF Author: David A. Randall
Publisher: Springer
ISBN: 9811333963
Category : Science
Languages : en
Pages : 372

Book Description
This book focuses on the development of physical parameterization over the last 2 to 3 decades and provides a roadmap for its future development. It covers important physical processes: convection, clouds, radiation, land-surface, and the orographic effect. The improvement of numerical models for predicting weather and climate at a variety of places and times has progressed globally. However, there are still several challenging areas, which need to be addressed with a better understanding of physical processes based on observations, and to subsequently be taken into account by means of improved parameterization. And this is all the more important since models are increasingly being used at higher horizontal and vertical resolutions. Encouraging debate on the cloud-resolving approach or the hybrid approach with parameterized convection and grid-scale cloud microphysics and its impact on models’ intrinsic predictability, the book offers a motivating reference guide for all researchers whose work involves physical parameterization problems and numerical models.