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André Tremblay

Abstract

The structure and development of idealized short mesoscale baroclinic waves are investigated within the framework of several numerical simulations. The numerical model used in this study is a mesoscale version of Clark's nonhydrostatic cloud model generalized to allow horizontally varying basic states. It is shown that short mesoscale disturbances can grow quickly when superimposed on a narrow and intense baroclinic zone having strong potential vorticity anomalies. Simulations with a weaker baroclinic zone yield a significantly weaker development. Results from dry runs with different wavelengths have shown that a natural scale-selection mechanism exists in the numerical model for a given basic state. For the initial data considered in this work, we found a maximum development for a disturbance wavelength of 1200 km.

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André Tremblay

Abstract

One year of precipitation records taken from a subset of the World Meteorological Organization (WMO) global rain gauge network has been analyzed. This analysis has shown that the distribution of accumulation of precipitation with the rainfall rate is characterized by an exponential law. This relationship seems to be universal and is present regardless of the averaging interval considered. The data structure suggests that this exponential distribution can be used as a basic state to partition surface precipitation into stratiform and convective components. The physical basis of this approach is investigated and discussed using Monte Carlo simulations based on a simple cloud model. The methodology is validated using a Fourier analysis in time, and average global monthly maps of convective and stratiform precipitation are presented to illustrate the feasibility of the technique.

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Andre Tremblay and Henry Leighton

Abstract

A cloud chemistry model is formulated in term of continuity equations for chemical species in the aqueous and aqueous phases within the cloud. The model includes scavenging of SO2, HNO3, HN3, H2O3, and sulphate aerosol particles. Calculations have been performed within the framework of a three-dimensional convective cloud model. The results are compared with aircraft measurements of cloud water chemistry.

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André Tremblay and Anna Glazer

Abstract

To improve forecasts of various weather elements (snow, rain, and freezing precipitation) in numerical weather prediction models, a new mixed-phase cloud scheme has been developed. The scheme is based on a single prognostic equation for total water content and includes parameterization of key cloud microphysical processes. The three-dimensional forecasts of solid particles, liquid, and supercooled cloud droplets and different precipitation types are typical outputs of the cloud scheme. It is shown that the scheme compares reasonably well with available meteorological observations. A novel aspect embodied in the scheme is the explicit inclusion of physical processes for the formation of supercooled liquid water. Thus, it is possible to model freezing precipitation and supercooled cloud droplets in the absence of the melting ice mechanism. The inclusion of the supercooled liquid water mechanism increased significantly the probability of detection of freezing precipitation and improved the bias score over the melting ice algorithm alone.

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André Tremblay, Anna Glazer, and Louis Garand

Abstract

To improve cloud and precipitation forecasts in the Canadian numerical weather prediction system, three cloud schemes with various degrees of complexity are evaluated. Several winter cases are simulated and mesoscale forecasts are compared with satellite, radiosonde, and surface observations. In particular, the distribution of cloud-top pressure is studied in detail using Geostationary Operational Environmental Satellite-8 (GOES-8) data. The three-dimensional structure of temperature and moisture is compared with upper-air data and forecasts of surface precipitation are scored against synoptic observations. This study demonstrates that the operational Canadian cloud scheme has problems that can be partially addressed by the inclusion of more realistic cloud microphysics in the forecast system.

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Stewart G. Cober, Andre Tremblay, and George A. Isaac

Abstract

Comparisons have been made between in situ aircraft measurements of integrated liquid water and retrievals of integrated liquid water path (LWP) from algorithms using SSM/I brightness temperatures. The aircraft measurements were made over the North Atlantic Ocean during the winter of 1992. Six case studies are presented from which trends in the LWP algorithms are discussed. SSM/I liquid water path validation has previously only been performed through comparisons with measurements from upward-looking radiometers or with calculations from radiative transfer models. The case studies presented here reflect an alternative technique for validation.

Aircraft-derived liquid water paths ranged from 0.01 to 0.09 kg m−2 for the six cases presented. The SSM/I algorithms investigated predicted LWP to within ±0.02–0.03 kg m−2, provided one accounted for systematic biases in the retrievals. These biases were systematic in the range ±0.06 kg m−2 and were presumably caused by latitudinal and seasonal influences inherent in the algorithms. Algorithms based on radiative transfer models appeared to perform better than the statistically based algorithms.

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André Tremblay, Anna Glazer, Wanda Szyrmer, George Isaac, and Isztar Zawadzki

Abstract

Using parameterizations of cloud microphysics, a technique to forecast supercooled cloud events is suggested. This technique can be coupled on the mesoscale with a prognostic equation for cloud water to improve aircraft icing forecasts. The procedure is validated using comparisons with airborne measurements from the Canadian Atlantic Storms Program. As an illustration of the application of this forecast technique, constant-pressure maps showing regions of cloud ice, supercooled cloud water, and cloud liquid water are presented for two particular cases.

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Hong Guan, Stewart G. Cober, George A. Isaac, André Tremblay, and André Méthot

Abstract

In situ aircraft measurements, collected during three research projects, are used to compare forecasts from three explicit cloud schemes. These schemes include the Canadian operational Sundqvist (SUND) scheme, the Tremblay mixed-phase (MIX) cloud scheme, and the Kong and Yau (KY) cloud scheme. The supercooled liquid water forecast accuracy is also determined for the MIX and KY schemes. For the entire in situ dataset, the three cloud forecast schemes show a similar skill in detecting the presence of clouds, with a true skill statistic ranging between 0.27 and 0.34. Quantitative comparisons of total cloud water content (TWC), supercooled liquid water content (SLWC), and ice water content (IWC) suggest that adjustments for autoconversion thresholds for precipitation formation within the different cloud microphysical schemes would improve forecasts of SLWC, IWC, and TWC.

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André Tremblay, Paul A. Vaillancourt, Stewart G. Cober, Anna Glazer, and George A. Isaac

Abstract

To improve the quality of forecasts of mixed-phase clouds in winter storms, some aspects of a cloud scheme are examined in detail. Modifications to the basic formalism and specification of selected parameters of the cloud model are studied, and simulation results are compared with aircraft observations and satellite data. In particular, a sensitivity study to the parameterization of the ice particle size distribution is presented. A special technique allowing the reconstruction of any model variable along a virtual aircraft trajectory is used to compare model results with aircraft observations. It has been possible from these comparisons to optimize the scheme and improve the quality of forecasts.

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Paul A. Vaillancourt, André Tremblay, Stewart G. Cober, and George A. Isaac

Abstract

In order to provide guidance for the further improvement of a mixed-phase cloud scheme being developed for use in an NWP model, comparisons of dynamical, thermodynamical, and microphysical variables between in situ aircraft data and model data were made. A total of 21 flights (∼88 h of data) from the First and Third Canadian Freezing Drizzle Experiments were selected and simulated. The basis of the evaluation of the model performance is a point-by-point comparison of each pertinent variable along the real and “virtual” aircraft trajectories. The virtual aircraft trajectory is constructed by choosing, for every observed data point, the closest available model data point in terms of time, pressure level, and latitude–longitude position. Observed and model data were used to calculate simple descriptive statistics to evaluate the ability of the forecast system to predict the presence of clouds, their phase, and water content.

Even though a point-by-point comparison of the aircraft and model data is a very severe test given the errors in the initial conditions and the disparity in temporal and spatial resolution, the results were encouraging for about half the flights simulated. It was found that, in general, the model predicts ice clouds better than water clouds. The model generally overpredicts (underpredicts) both the presence and the quantities of ice water content (supercooled liquid water content). Furthermore, where mixed-phase clouds are present in the model, the ice phase represents a large fraction of the total water content, contrary to the observations. These conclusions suggest that the parameterization of the ice particle size distribution is an important aspect of the mixed-phase cloud scheme that should be optimized.

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