Download or read book Testing Mixed Phase Cloud Parametrizations Through Confronting Models with In situ Observations written by Robert Farrington and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mixed Phase Clouds written by Constantin Andronache and published by Elsevier. This book was released on 2017-09-28 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Testing Cloud Microphysics Parameterizations and Improving the Representation of the Wegner Bergeron Findeisen Process in Mixed phase Clouds in NCAR CAM5 written by Meng Zhang and published by . This book was released on 2017 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Improving Mixed phase Cloud Parameterization in Climate Model with the ACRF Measurements written by and published by . This book was released on 2016 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentration retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations of mixed-phase cloud simulations by CAM5 were performed. Measurement results indicate that ice concentrations control stratiform mixed-phase cloud properties. The improvement of ice concentration parameterization in the CAM5 was done in close collaboration with Dr. Xiaohong Liu, PNNL (now at University of Wyoming).
Download or read book Evaluation of Mixed Phase Cloud Parameterizations in Short Range Weather Forecasts with CAM3 and AM2 for Mixed Phase Arctic Cloud Experiment written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Evaluation of Mixed Phase Cloud Microphysics Parameterizations with the NCAR Single Column Climate Model SCAM and ARM Observations written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Mixed-phase stratus clouds are ubiquitous in the Arctic and play an important role in climate in this region. However, climate models have generally proven unsuccessful at simulating the partitioning of condensed water into liquid droplets and ice crystals in these Arctic clouds, which affect modeled cloud phase, cloud lifetime and radiative properties. An ice nucleation parameterization and a vapor deposition scheme were developed that together provide a physically-consistent treatment of mixed-phase clouds in global climate models. These schemes have been implemented in the National Center for Atmospheric Research (NCAR) Community Atmospheric Model Version 3 (CAM3). This report documents the performance of these schemes against ARM Mixed-phase Arctic Cloud Experiment (M-PACE) observations using the CAM single column model version (SCAM). SCAM with our new schemes has a more realistic simulation of the cloud phase structure and the partitioning of condensed water into liquid droplets against observations during the M-PACE than the standard CAM simulations.
Download or read book Development and Testing of a Life Cycle Model and a Parameterization of Thin Mid level Stratiform Clouds written by and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We used a cloud-resolving model (a detailed computer model of cloud systems) to evaluate and improve the representation of clouds in global atmospheric models used for numerical weather prediction and climate modeling. We also used observations of the atmospheric state, including clouds, made at DOE's Atmospheric Radiation Measurement (ARM) Program's Climate Research Facility located in the Southern Great Plains (Kansas and Oklahoma) during Intensive Observation Periods to evaluate our detailed computer model as well as a single-column version of a global atmospheric model used for numerical weather prediction (the Global Forecast System of the NOAA National Centers for Environmental Prediction). This so-called Single-Column Modeling approach has proved to be a very effective method for testing the representation of clouds in global atmospheric models. The method relies on detailed observations of the atmospheric state, including clouds, in an atmospheric column comparable in size to a grid column used in a global atmospheric model. The required observations are made by a combination of in situ and remote sensing instruments. One of the greatest problems facing mankind at the present is climate change. Part of the problem is our limited ability to predict the regional patterns of climate change. In order to increase this ability, uncertainties in climate models must be reduced. One of the greatest of these uncertainties is the representation of clouds and cloud processes. This project, and ARM taken as a whole, has helped to improve the representation of clouds in global atmospheric models.
Download or read book Arctic mixed phase clouds Macro and microphysical insights with a numerical model written by Loewe, Katharina and published by KIT Scientific Publishing. This book was released on 2017-09-15 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Physical Processes in Clouds and Cloud Modeling written by Alexander P. Khain and published by Cambridge University Press. This book was released on 2018-07-05 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a comprehensive analysis of modern theories of cloud microphysical processes and their representation in numerical cloud models.
Download or read book Intercomparison of Model Simulations of Mixed phase Clouds Observed During the ARM Mixed Phase Arctic Cloud Experiment Part I written by and published by . This book was released on 2008 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Mountain top In situ Observations of Mixed phase Clouds with a Digital Holographic Instrument written by Jan Friedrich-Wilhelm Henneberger and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Intercomparison of Model Simulations of Mixed phase Clouds Observed During the ARM Mixed Phase Arctic Cloud Experiment Part II written by and published by . This book was released on 2008 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Investigation of the Phase Distribution and Related Parameters in Mixed phase Clouds Using Satellite Observations and Model Simulations written by Olimpia Bruno and published by . This book was released on 2023* with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Simulations of Arctic Mixed phase Clouds in Forecasts with CAM3 and AM2 for M PACE written by and published by . This book was released on 2008 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: [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.
Download or read book Mixed phase Cloud Microphysics Over Mountainous Terrain Emphasizing Airborne Dual wavelength Retrieval Approach written by Coltin Dale Grasmick and published by . This book was released on 2021 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kelvin-Helmholtz (KH) waves are common in deep stratiform precipitation systems associated with frontal disturbances, especially in the vicinity of complex terrain, as is evident from transects of vertical velocity and 2D circulation, obtained from a 3-mm airborne Doppler radar, the Wyoming Cloud Radar. These waves are observed in a variety of wavelengths, depths, amplitudes, and turbulence intensities. Complex terrain may locally enhance wind shear which reduces the Richardson number and leads to KH instability. KH waves are frequently locked to the terrain, and occur at various heights, including within the free troposphere, at the boundary layer top, and close to the surface. They are observed not only upwind of terrain barriers, as has been documented before, but also in the wake of steep terrain, where the waves can be highly turbulent. KH waves are a source of turbulence in stratiform precipitation systems over mountainous terrain. They introduce large eddies into otherwise laminar flow, with updrafts and downdrafts breaking down into small-scale turbulence. When they occur in-cloud, such dynamics influence microphysical processes that impact precipitation growth and fallout. Measurements within KH wave updrafts reveal the production of liquid water in otherwise ice-dominated clouds, which can contribute to snow generation or enhancement via depositional and accretional growth. Fallstreaks beneath KH waves contain higher ice water content, composed of larger and more numerous ice particles, suggesting that KH waves and associated turbulence may also increase ice nucleation. A Large-Eddy Simulation (LES), designed to model the microphysical response to the KH wave eddies in mixed phase cloud, shows that depositional and accretional growth can be enhanced in KH waves, resulting in more precipitation when compared to a baseline simulation.Properties of frozen hydrometeors in clouds remain difficult to remotely sense. Estimates of number concentration, distribution shape, ice particle density, and ice water content are essential for connecting cloud processes to surface precipitation. Researching the microphysical effects of dynamic features like KH waves heavily relies on in situ measurements on an aircraft or at the surface but these observations substantially under-sample the cloud and miss the effects of the KH waves. Progress has been made with dual-frequency radars, but validation has been difficult because of a lack of cloud microphysical observations collocated with the radar measurements Here, data are used from two airborne profiling (up & down) radars, the W-band Wyoming Cloud Radar and the Ka-band Profiling Radar, allowing for Ka-W-band Dual-Wavelength Ratio (DWR) profiles. The aircraft (the University of Wyoming King Air) also carried a suite of in situ cloud and precipitation probes. This arrangement is optimal for relating the “flight-level” DWR (an average from radar gates below and above flight level) to ice particle size distributions measured by in situ optical array probes, as well as bulk properties such as minimum snow particle density and ice water content. This comparison reveals a strong relationship between DWR and the ice particle median volume diameter. The DWR-defined size distribution shape is used with a Mie scattering model and an experimental mass-diameter relationship to estimate ice particle concentration and ice water content. Comparison with flight-level cloud-probe data indicate good performance, allowing microphysical interpretations for vertical radar transects.
Download or read book Retrieval of Cloud Phase Using the Moderate Resolution Imaging Spectroradiometer Data During the Mixed Phase Arctic Cloud Experiment written by and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Investigation of Freezing Parameterizations for Mixed Phase Clouds with the ECHAM Climate Model written by Delia Maria Luisa Wolf and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
