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Theoretical research on the microphysics of polar stratospheric clouds (PSCs) is reviewed. Problems discussed include microphysical features of PSCs, the Antarctic ozone depletion, and a comparison of PSC microphysical characteristics with those of low-level polar stratus clouds over the Antarctic coast.
Cloud microphysical properties are an important component in climate model parameterizations of water transport, cloud radiative exchange, and latent heat processes. Estimation of effective cloud particle size, liquid or ice water content, and optical depth from satellite-based instrumentation is needed to develop a climatology of cloud microphysical properties and to better understand and model cloud processes in atmospheric circulation. These parameters are estimated from two different surface data sets taken at Coffeyville, Kansas, during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (November 13 - December 7, 1991). Satellite data can also provide information about optical depth and effective particle size. This paper explores the combination of the FIRE-2 surface and satellite data to determine each of the cloud microphysical properties.
We have used a one-dimensional model of cirrus formation to study the development of cirrus clouds during the 1986 First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) intensive field observations (IFO). The cirrus model includes microphysical, dynamical, and radiative processes. Sulfate aerosols, solution drops, ice crystals, and water vapor are all treated as interactive elements in the model. Ice crystal size distributions are fully resolved based on calculations of homogeneous freezing nucleation, growth by water vapor deposition, evaporation, coagulation, and vertical transport. We have focused on the cirrus observed on November 1, 1986. Vertical wind speed for the one-dimensional simulation is taken from a mesoscale model simulation for the appropriate time period. The mesoscale model simulation suggested that strong upward motions over Wyoming and subsequent horizontal transport of upper level moisture were responsible for the cirrus observed over Wisconsin on this date. We assumed that our one-dimensional model could be used to represent a vertical column moving from Wyoming to Wisconsin over a period of several hours. Ice crystal nucleation occurs in our model in the 8 to 10-km region as a result of the strong updrafts (and cooling) early in the simulation. Growth, coagulation, and sedimentation of these ice crystals result in a broad cloud region (5-10 km thick) with an optical depth of 1-2 after a few hours, in agreement with the FIRE measurements. Comparison with aircraft microphysical measurements made over Wisconsin indicates that the simulation generated reasonable ice water content, but the predicted ice number densities are too low, especially for radii less than about 50 microns. Sensitivity tests suggest that better agreement between simulated and observed microphysical properties is achieved if the nucleation rate is higher or stronger vertical mixing (perhaps associated with multidimensional motions) is present.
The one-dimensional cirrus model described in part 1 of this issue has been used to study the sensitivity of simulated cirrus microphysical and radiative properties to poorly known model parameters, poorly understood physical processes, and environmental conditions. Model parameters and physical processes investigated include nucleation rate, mode of nucleation (e.g., homogeneous freezing of aerosols and liquid droplets or heterogeneous deposition), ice crystal shape, and coagulation. These studies suggest that the leading sources of uncertainty in the model are the phase change (liquid-solid) energy barrier and the ice-water surface energy which dominate the homogeneous freezing nucleation rate and the coagulation sticking efficiency at low temperatures which controls the production of large ice crystals (radii greater than 100 mcirons). Environmental conditions considered in sensitivity tests were CN size distribution, vertical wind speed, and cloud height. We found that (unlike stratus clouds) variations in the total number of condensation nuclei (NC) have little effect on cirrus microphysical and radiative properties, since nucleation occurs only on the largest CN at the tail of the size distribution. The total number of ice crystals which nucleate has little or no relationship to the number of CN present and depends primarily on the temperature and the cooling rate. Stronger updrafts (more rapid cooling) generate higher ice number densities, ice water content, cloud optical depth, and net radiative forcing. Increasing the height of the clouds in the model leads to an increase in ice number density, a decrease in effective radius, and a decrease in ice water content. The most prominent effect of increasing cloud height was a rapid increase in the net cloud radiative forcing which can be attributed to the change in cloud temperature as well as change in cloud ice size distributions. It has long been recognized that changes in cloud height or cloud area have the greatest potential for causing feedbacks on climate change. Our results suggest that variations in vertical velocity or cloud microphysical changes associatd with cloud height changes may also be important.
The objective of this work is to explore relationships between the microphysical properties of precipitation and optimal polarizations. The dependence of three optimal polarization parameters (asymmetry ratio A, optimal tilt tau(sub op), and optimal ellipticity epsilon(sub op) on the reflectivity-weighted mean drop shape, mean canting angle, and standard deviation of a Gaussian canting angle distribution is studied. This is accomplished by using computer simulations that provide the rms scattering matrix for an ensemble of canted drops with a prescribed two-parameter canting angle distribution. Also examined are the effects of propagation on the polarization parameters for nonattenuating wavelengths. The asymmetry ratio A is simply the ratio of the maximal to minimal total backscattered energy (ratio of the largest and smallest eigenvalue of the Graves power matrix G is identically equal to S dagger S). Similar to Z(sub DR), this ratio decreases with increasing mean axial ratio, but unlike Z(sub DR), it is not affected by canting (for a single drop). The dependence of A on the reflectivity-weighted mean drop shape is examined, and a power-law relationship similar to that which exists for Z(sub DR) is established. The asymmetry ratio A can be regarded as a generalization of Z(sub DR) because it requires only a measurement of linear depolarization ratio (in addition to Z(sub DR)), is independent of the propagation phase, and is less sensitive to canting. In a similar manner, the dependence of optimal ellipticity and tilt on the microphysical parameters is studied. In particular, it appears that the rms tilt of the optimal polarization ellipse is proportional to the variance of the canting angle distribution. Several other promising relationships between optimal polarizations and the microphysical variables of an ensemble of hydrometeors are also discussed.
The importance of understanding the radiative and microphysical properties of cirrus clouds in weather and climate research has been articulated by Liou (1986). This importance has also been recognized in view of the intensive field observations that have been conducted as a major component of the First ISCCP Regional Experiment (FIRE) in October-November 1986 (Starr 1987) and more recently in November-December 1991 (FIRE-II) as well as the European experiments on cirrus (ICE/EUCREX) that has been carried out in 1989. One of the fundamental objectives of the FIRE program has been and is to apply the field campaign and theoretical results to develop and verify improved techniques for the inference of cloud radiative and microphysical properties from satellite and surface-based data. A program is designed for the validation of the satellite retrived optical depth and mean effective ice crystal size utilizing in situ replicator observations for ice crystal size distributions and shapes. To minimize the effect of the horizontal size variability of the microphysical structure and the problem associated with collocation and coincidence, an averaging procedures was developed for both the satellite retrieved cloud parameters and the measured ice crystal data.
A prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) was developed with the aim of improving cloud-microphysics, and cloud-radiation interactions in GCMs. McRAS distinguishes convective, stratiform, and boundary-layer clouds. The convective clouds merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds do so instantly. The cloud condensate transforms into precipitation following the auto-conversion relations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, and diffuse both horizontally and vertically with a fully active cloud-microphysics throughout its life-cycle, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III data has shown that McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. An evaluation with the ARM-CART SCM data in a cloud model intercomparison exercise shows reasonable but not an outstanding accurate simulation. Such a discrepancy is common to almost all models and is related, in part, to the input data quality. McRAS was implemented in the GEOS II GCM. A 50 month integration that was initialized with the ECMWF analysis of observations for January 1, 1987 and forced with the observed sea-surface temperatures and sea-ice distribution and vegetation properties (biomes, and soils), with prognostic soil moisture, snow-cover, and hydrology showed a very realistic simulation of cloud process, incloud water and ice, and cloud-radiative forcing (CRF). The simulated ITCZ showed a realistic time-mean structure and seasonal cycle, while the simulated CRF showed sensitivity to vertical distribution of cloud water which can be easily altered by the choice of time constant and incloud critical cloud water amount regulators for auto-conversion. The CRF and its feedbacks also have a profound effect on the ITCZ. Even though somewhat weaker than observed, the McRAS-GCM simulation produces robust 30-60 day oscillations in the 200 hPa velocity potential. Two ensembles of 4-summer (July, August, September) simulations, one each for 1987 and 1988 show that the McRAS-GCM simulates realistic and statistically significant precipitation differences over India, Central America, and tropical Africa. Several seasonal simulations were performed with McRAS-GEOS II GCM for the summer (June-July- August) and winter (December-January-February) periods to determine how the simulated clouds and CRFs would be affected by: i) advection of clouds; ii) cloud top entrainment instability, iii) cloud water inhomogeneity correction, and (iv) cloud production and dissipation in different cloud-processes. The results show that each of these processes contributes to the simulated cloud-fraction and CRF.
The First International Satellite Cloud Climatology Regional Experiment (FIRE) program has the goal of improving our capabilities to understand, model and detect the properties of climatically-important clouds. This is being undertaken through a three-pronged effort of modeling, long-term observations and short-term intensive field studies. Through examination of satellite and other data it is apparent that stratus and cirrus cloud types have the greatest impact on climate due to their radiative effects and ubiquitous nature. As a result, the FIRE program has developed two paths of investigation, each having its own subset of research objectives and measurement programs. The work conducted under this grant was directed toward furthering our understanding of cirrus cloud systems. While it is known that cirrus are climatically important, the magnitude and even sign of the impact is unclear. Cirrus clouds affect the transfer of radiation according to their physical depth and location in the atmosphere and their microphysical composition. However, significant uncertainties still exist in how cirrus clouds form and how they are maintained, what their physical properties are and how they can be parameterized in numerical models. Better remote sensing techniques for monitoring cirrus cloud systems and improved modeling of radiative transfer through ice particles are also needed. A critical element in resolving these issues is a better understanding of cirrus cloud microphysical properties and how they vary. The focus of the research to be conducted under this grant was th data collected in situ by the University of North Dakota Citation aircraft. The goals of this research were to add to the body of knowledge of cirrus cloud microphysics, particularly at the small end of the size spectrum; and analyze the spatial variation of cirrus clouds.
The 3D Goddard Cumulus Ensemble (GCE) model was utilized to examine the behavior and response of simulated deep tropical cloud systems that occurred over the west Pacific warm pool region, the Atlantic ocean and the central United States. The periods chosen for simulation were convectively active periods during TOGA-COARE (February 22 1993, December 11-17, 1992; December 19-28, February 9-13, 1993), GATE (September 4, 1974), LBA (January 26 and February 23, 1998), ARM (1997 IOP) and PRESTORM (June 11, 1985). We will examine differences in the microphysics for both warm rain and ice processes (evaporation /sublimation and condensation/ deposition), Q1 (Temperature), Q2 (Water vapor) and Q3 (momentum both U and V) budgets for these three convective events from different large-scale environments. The contribution of stratiform precipitation and its relationship to the vertical shear of the large-scale horizontal wind will also be examined. New improvements to the GCE model (i.e., microphysics: 4ICE two moments and 3ICE one moment; advection schemes) as well as their sensitivity to the model results will be discussed. Preliminary results indicated that various microphysical schemes could have a major impact on stratiform formation as well as the size of convective systems. However, they do not change the major characteristics of the convective systems, such as: arc shape, strong rotational circulation on both ends of system, heavy precipitation along the leading edge of systems.
The microphysical parameterization of clouds and rain-cells plays a central role in atmospheric forward radiative transfer models used in calculating passive microwave brightness temperatures. The absorption and scattering properties of a hydrometeor-laden atmosphere are governed by particle phase, size distribution, aggregate density., shape, and dielectric constant. This study identifies the sensitivity of brightness temperatures with respect to the microphysical cloud parameterization. Cloud parameterizations for wideband (6-410 GHz observations of baseline brightness temperatures were studied for four evolutionary stages of an oceanic convective storm using a five-phase hydrometeor model in a planar-stratified scattering-based radiative transfer model. Five other microphysical cloud parameterizations were compared to the baseline calculations to evaluate brightness temperature sensitivity to gross changes in the hydrometeor size distributions and the ice-air-water ratios in the frozen or partly frozen phase. The comparison shows that, enlarging the rain drop size or adding water to the partly Frozen hydrometeor mix warms brightness temperatures by up to .55 K at 6 GHz. The cooling signature caused by ice scattering intensifies with increasing ice concentrations and at higher frequencies. An additional comparison to measured Convection and Moisture LA Experiment (CAMEX 3) brightness temperatures shows that in general all but, two parameterizations produce calculated T(sub B)'s that fall within the observed clear-air minima and maxima. The exceptions are for parameterizations that, enhance the scattering characteristics of frozen hydrometeors.
A retrieval algorithm has been developed for the microphysical analysis of polar stratospheric cloud (PSC) optical data obtained using lidar instrumentation. The parameterization scheme of the PSC microphysical properties allows for coexistence of up to three different particle types with size-dependent shapes. The finite difference time domain (FDTD) method has been used to calculate optical properties of particles with maximum dimensions equal to or less than 2 mu m and with shapes that can be considered more representative of PSCs on the scale of individual crystals than the commonly assumed spheroids. Specifically. these are irregular and hexagonal crystals. Selection of the optical parameters that are input to the inversion algorithm is based on a potential data set such as that gathered by two of the lidars on board the NASA DC-8 during the Stratospheric Aerosol and Gas Experiment 0 p (SAGE) Ozone Loss Validation experiment (SOLVE) campaign in winter 1999/2000: the Airborne Raman Ozone and Temperature Lidar (AROTEL) and the NASA Langley Differential Absorption Lidar (DIAL). The 0 microphysical retrieval algorithm has been applied to study how particle shape assumptions affect the inversion of lidar data measured in leewave PSCs. The model simulations show that under the assumption of spheroidal particle shapes, PSC surface and volume density are systematically smaller than the FDTD-based values by, respectively, approximately 10-30% and approximately 5-23%.
Knowledge of particle sizes and number densities of polar stratospheric clouds (PSCs) is highly important, because they are critical parameters for the modeling of the ozone chemistry of the stratosphere. In situ measurements of PSC particles are rare. the main instrument for the accumulation of PSC data are lidar systems. Therefore the derivation of some microphysical properties of PSCS from the optical parameters measured by lidars would be highly beneficial for ozone research. Inversion of lidar data obtained in the presence of PSCs formed from crystalline particles type 11 and the various nitric acid tri Ydrrate (NAT) types cannot be easily accomplished, because a suitable scattering theory for small faceted crystals has not been readily available tip to now. As a consequence, the T-matrix method is commonly used for the interpretation of these PSC lidar data. Here the assumption is made that the optical properties of an ensemble of spheroids resemble those of crystalline PSCs, and microphysical properties of the PSC are inferred from the optical signatures of the PSC at two or more wavelengths. The problem with the T-matrix approach is that the assumption of spheroidal instead of faceted particles can lead to dramatically wrong results: Usually cloud particle properties are deduced from analysis of lidar profiles of backscatter ratio and depolarization ratio. The particle contribution to the backscatter ratio is given by the product of the particle number density and the backscattering cross section. The latter is proportional to the value of the particle's scattering phase function at 180 degrees scattering angle. At 180 degrees however, the phase functions of rough, faceted crystals and of spheroids with same maximum dimension differ by a factor of 6. From this it follows that for a PSC consisting of faceted crystals, the particle number density is underestimated by roughly the same factor if spheroidal particles are unrealistically assumed. We are currently developing a retrieval technique for determining the microphysical parameters of crystalline PSCs that takes into account the faceted shape of the PSC particles. This approach utilizes finite-difference time-domain (FDTD) calculations of particle optical properties. The accuracy and the free choice of the shape of the scattering particle make the FDTD technique a promising tool for the inversion of PSC lidar data. A first comparison of FDTD and T-matrix calculations will be presented.
The Goddard Cumulus Ensemble (GCE) model is used to examine the impact of various microphysical schemes, and vertical and horizontal resolution on the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing ratios of all water phases (vapor, liquid, and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes, and with surface processes. For idealized hurricane, an axisymmetric version of the GCE model was developed and used successfully to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was used to simulate squall lines that developed in the western Pacific, eastern Atlantic and central US. For the cloud ensemble, the GCE model was integrated for several days in order to have good sampling of cloud statistics. In this paper, the sensitivities of hurricane intensity to various microphysical processes and model grid resolution will be examined.
One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.
Fine-resolution simulations of Hurricane Erin 2001 are conducted using the Penn State University/National Center for Atmospheric Research mesoscale model version 3.5 to investigate the role of thermodynamic, boundary layer and microphysical processes in Erin's growth and maintenance, and their effects on the horizontal and vertical distributions of hydrometeors. Through comparison against radar, radiometer, and dropsonde data collected during the Convection and Moisture Experiment 4, it is seen that realistic simulations of Erin are obtained provided that fine resolution simulations with detailed representations of physical processes are conducted. The principle findings of the study are as follows: 1) a new iterative condensation scheme, which limits the unphysical increase of equivalent potential temperature associated with most condensation schemes, increases the horizontal size of the hurricane, decreases its maximum rainfall rate, reduces its intensity, and makes its eye more moist; 2) in general, microphysical parameterization schemes with more categories of hydrometeors produce more intense hurricanes, larger hydrometeor mixing ratios, and more intense updrafts and downdrafts; 3) the choice of coefficients describing hydrometeor fall velocities has as big of an impact on the hurricane simulations as does choice of microphysical parameterization scheme with no clear relationship between fall velocity and hurricane intensity; and 4) in order for a tropical cyclone to adequately intensify, an advanced boundary layer scheme (e.g., Burk-Thompson scheme) must be used to represent boundary layer processes. The impacts of varying simulations on the horizontal and vertical distributions of different categories of hydrometeor species, on equivalent potential temperature, and on storm updrafts and downdrafts are examined to determine how the release of latent heat feedbacks upon the structure of Erin. In general, all simulations tend to overpredict precipitation rate and hydrometeor mixing ratios. The ramifications of these findings for quantitative precipitation forecasts (QPFs) of tropical cyclones are discussed.
An algorithm to retrieve optically thick ice cloud microphysical property profiles is developed by using the GSFC 9.6 GHz ER-2 Doppler Radar (EDOP) and the 94 GHz Cloud Radar System (CRS) measurements aboard the high-altitude ER-2 aircraft. In situ size distribution and total water content data from the CRYSTAL-FACE field campaign are used for the algorithm development. To reduce uncertainty in calculated radar reflectivity factors (Ze) at these wavelengths, coincident radar measurements and size distribution data are used to guide the selection of mass-length relationships and to deal with the density and non-spherical effects of ice crystals on the Ze calculations. The algorithm is able to retrieve microphysical property profiles of optically thick ice clouds, such as, deep convective and anvil clouds, which are very challenging for single frequency radar and lidar. Examples of retrieved microphysical properties for a deep convective clouds are presented, which show that EDOP and CRS measurements provide rich information to study cloud structure and evolution. Good agreement between IWPs derived from an independent submillimeter-wave radiometer, CoSSIR, and dual-wavelength radar measurements indicates accuracy of the IWC retrieved from the two-frequency radar algorithm.
A cloud rift is characterized as a large-scale, persistent area of broken, low reflectivity stratocumulus clouds usually surrounded by a solid deck of stratocumulus. A rift observed off the coast of Monterey Bay, California on 16 July 1999 was studied to compare the aerosol and cloud microphysical properties in the rift with those of the surrounding solid stratus deck. Variables measured from an instrumented aircraft included temperature, water vapor, and cloud liquid water. These measurements characterized the thermodynamic properties of the solid deck and rift areas. Microphysical measurements made included aerosol, cloud drop and drizzle drop concentrations and cloud condensation nuclei (CCN) concentrations. The microphysical characteristics in a solid stratus deck differ substantially from those of a broken, cellular rift where cloud droplet concentrations are a factor of 2 lower than those in the solid cloud. Further, CCN concentrations were found to be about 3 times greater in the solid cloud area compared with those in the rift and aerosol concentrations showed a similar difference as well. Although drizzle was observed near cloud top in parts of the solid stratus cloud, the largest drizzle rates were associated with the broken clouds within the rift area. In addition to marked differences in particle concentrations, evidence of a mesoscale circulation near the solid cloud rift boundary is presented. This mesoscale circulation provides a mechanism for maintaining a rift, but further study is required to understand the initiation of a rift and the conditions that may cause it to fill.
Forecast precipitation and radar characteristics are used by operational centers to guide the issuance of advisory products. As operational numerical weather prediction is performed at increasingly finer spatial resolution, convective precipitation traditionally represented by sub-grid scale parameterization schemes is now being determined explicitly through single- or multi-moment bulk water microphysics routines. Gains in forecasting skill are expected through improved simulation of clouds and their microphysical processes. High resolution model grids and advanced parameterizations are now available through steady increases in computer resources. As with any parameterization, their reliability must be measured through performance metrics, with errors noted and targeted for improvement. Furthermore, the use of these schemes within an operational framework requires an understanding of limitations and an estimate of biases so that forecasters and model development teams can be aware of potential errors. The National Severe Storms Laboratory (NSSL) Spring Experiments have produced daily, high resolution forecasts used to evaluate forecast skill among an ensemble with varied physical parameterizations and data assimilation techniques. In this research, high resolution forecasts of the 5-6 February 2008 Super Tuesday Outbreak are replicated using the NSSL configuration in order to evaluate two components of simulated convection on a large domain: sensitivities of quantitative precipitation forecasts to assumptions within a single-moment bulk water microphysics scheme, and to determine if these schemes accurately depict the reflectivity characteristics of well-simulated, organized, cold frontal convection. As radar returns are sensitive to the amount of hydrometeor mass and the distribution of mass among variably sized targets, radar comparisons may guide potential improvements to a single-moment scheme. In addition, object-based verification metrics are evaluated for their utility in gauging model performance and QPF variability.