Rainwater Mixing Ratio Research Articles

Structure of Mesoscale Convective Systems during the Late Baiu Season in the Global Warming Climate Simulated by a Non-Hydrostatic Regional Model

Mesoscale convective systems (MCSs) that bring rainfall in the vicinity of Kyushu Island, Japan during the late Baiu season in the present and global warming climates are examined by a non-hydrostatic regional climate model (NHM) with the horizontal grid of 5 km.In the global warming climate, two types of MCSs appear in the vicinity of Kyushu Island. One travels from the Chinese Continent and the other from the southern part of the East China Sea to Kyushu Island. These two MCSs often merge over the sea southwest of Kyushu Island, and they rapidly develop to bring heavy precipitation to the vicinity of Kyushu Island. Among the latter, MCSs with low cloud-tops below 4 km MSL (Mean Sea Level) are found.In the comparison with the present climate, the averaged cloud and rain water mixing ratios in the vicinity of Kyushu Island become much larger, and the peak altitude of the mixing ratios are about 0.5-1.0 km higher in the global warming climate. The cloud water mixing ratio between 2-4 km MSL increases in the global warming climate, corresponding to MCSs with low cloud-tops.These results suggest one of the processes to produce heavy rainfall in the vicinity of Kyushu Island in July in the global warming climate.

On the sensitivity of cloud microphysics under influence of cloud drop size distribution

The unique Khrgian–Mazin size distribution is suggested as an alternative approximation of the entire drop spectra besides the conventional approximation in which the monodisperse and the Marshall–Palmer size distributions for cloud droplets and raindrops are used, respectively. This approach is employed in bulk microphysics. It is shown that the effects of the changed drop size distribution are particularly pronounced in the case of the microphysical production terms with rain. This is a consequence of the fact that the Khrgian–Mazin size distribution produces more small raindrops and less large ones compared to the Marshall–Palmer one, where both have the same rain water mixing ratio. The new production terms with cloud water do not differ from those with the monodisperse size distribution used. In order to show the sensitivity of cloud microphysics with respect to the change of drop size distribution function, the experiments are perform with the two versions of a forced 1-D time-dependent model. The first one involves the microphysical production terms with the Khrgian–Mazin size distribution, while the other one uses the conventional approach. Experiments clearly show that cloud microphysics essentially depends on cloud drop size distribution. Some microphysical aspects of a model cloud with the new drop size distribution are in fair agreement with observations.

Dynamical and Microphysical Retrieval from Doppler Radar Observations Using a Cloud Model and Its Adjoint. Part II: Retrieval Experiments of an Observed Florida Convective Storm

Abstract The variational Doppler radar analysis system developed in part I of this study is tested on a Florida airmass storm observed during the Convection and Precipitation/ Electrification Experiment. The 3D wind, temperature, and microphysical structure of this storm are obtained by minimizing the difference between the radar-observed radial velocities and rainwater mixing ratios (derived from reflectivity) and their model predictions. Retrieval experiments are carried out to assimilate information from one or two radars. The retrieved fields are compared with measurements of two aircraft penetrating the storm at different heights. The retrieved wind, thermodynamical, and microphysical fields indicate that the minimization converges to a solution consistent with the input velocity and rainwater fields. The primary difference between using single-Doppler and dual-Doppler information is the reduction of the peak strength of the storm on the order of 10% when information from only one radar is provided. ...

An explicit approach to microphysics in MC2

An explicit microphysics scheme, including warm rain and ice‐phase processes, has been incorporated into the Canadian Mesoscale Compressible Community Model (MC2). Three equations for cloud water mixing ratio, rain water mixing ratio, and ice or snow mixing ratio are solved explicitly. The hydrometeor mass loading term is also included. For the single ice category, a generalized gamma size distribution is assumed and a new formulation by Meyers et al. (1992) is used to predict the ice concentration. A numerical simulation of the ERICA IOP2 cyclone shows that the scheme is efficient. Despite running at a relatively large time step, the scheme succeeded in capturing the deepening rates and the mesoscale features of the cyclone. The distribution of cloud and precipitation is in good agreement with satellite observations. Comparison with other implicit schemes available in MC2 show comparable performance in terms of deepening rate and precipitation rate. However, the explicit scheme generates mesoscale features in better agreement with observations.

Dynamical and Microphysical Retrieval from Doppler Radar Observations Using a Cloud Model and Its Adjoint. Part I: Model Development and Simulated Data Experiments

Abstract The purpose of the research reported in this paper is to develop a variational data analysis system that can be used to assimilate data from one or more Doppler radars. In the first part of this two-part study, the technique used in this analysis system is described and tested using data from a simulated warm rain convective storm. The analysis system applies the 4D variational data assimilation technique to a cloud-scale model with a warm rain parameterization scheme. The 3D wind, thermodynamical, and microphysical fields are determined by minimizing a cost function, defined by the difference between both radar observed radial velocities and reflectivities (or rainwater mixing ratio) and their model predictions. The adjoint of the numerical model is used to provide the sensitivity of the cost function with respect to the control variables. Experiments using data from a simulated convective storm demonstrated that the variational analysis system is able to retrieve the detailed structure of wind,...

Comparison of microphysics parameterizations in a three-dimensional dynamic cloud model

Abstract A three-dimensional, time-dependent flow model developed to simulate dynamics and cloud microphysics for warm-cloud processes is used to compare the moisture fields simulated with different cloud microphysics parameterization. Our parameterizations are based on detailed simulations of the physics of aerosols, clouds, and precipitation. The moisture content in the system is differentiated into water vapor, cloud water, and rain water. Advection and diffusion terms for momentum, potential temperature, and mixing ratios of water vapaor and cloud water are calculated by using finite-volume methods, while rain water mixing ratio fields are calculated by a Lagrangian method. The model simulations are examined through sensitivity analysis, interpreted in terms of the physical processes occurring, and are compared with simulations using parameterizations from the literature. Calculated precipitation totals are shown to vary by 10–30% among simulations with alternate parameterization.

Retrieval of Thermodynamic Variables within Deep Convective Clouds: Experiments in Three Dimensions

A three-dimensional numerical cloud model has been used to test a method for retrieving temperature and pressure deviation fields from detailed wind and water fields in deep convective clouds. A comparison of the retrieved fields with the output from the numerical model was used to test the validity of the theoretical treatment and accuracy of the programming. The local time derivatives of each of the velocity components are known to be potential problem sources in using Doppler radar data, and a test was done with this derivative estimated over a 4 min time span rather than 30 s, resulting in excellent agreement with the original solution for this data set. When the local derivative was eliminated, the solution was judged useful for general temperature patterns. Errors due to the inability to measure cloudwater mixing ratio and inaccuracies in rainwater mixing ratio were found to be significant, but not so severe as in the turbulence and steady-state sensitivity tests.

The application of a 2-D convective cloud model to waste heat release from proposed nuclear energy centers

A two-dimensional time-dependent convective cloud model is applied to the problem of atmospheric effects from latent and sensible heat releases by nuclear energy centers. In the model applications the horizontal extent and strength of the source (perturbation) is consistent with those proposed for such centers. One case considers the effect of excess water vapor from such centers upon an existing squall line convective element which passes over the center. Other cases consider the initiation of convection by both latent and sensible heat consistent with that released by evaporative cooling towers in such a center. In the case of enhancement of existing convection the increases in maximum vertical wind speed and maximum rainwater mixing ratio within the storm are computed to be less than 10%. In the cloud initiation cases, sub-cloud layer stability variations in a Nashville, Tennessee sounding were considered with no variation in the environmental motion field. No deep convection occurred in a case where thermal stability was present between 0.4 and 1.6 km. In a case where the atmosphere was dry adiabatic in this layer, deep convection did occur. In another case where the same sounding included a nocturnal inversion, deep convection occurred but was delayed by 3–4 h. In a case utilizing a sounding characteristic of very hot conditions in the interior Pacific Northwest, no condensed cloud was produced. A brief discussion is presented concerning some of the serious problems involved in applying one-, two-and three-dimensional convective cloud models to the waste heat problem. Also, certain additional experiments are suggested for both the enhancement and the initiation cases.