Traditionally, the diffusional growth of a cloud droplet population is calculated using values of the environmental conditions that represent averages over large volumes, the so called macroscopic conditions (Srivastava 1989). However, it is apparent that the growth rate of an individual droplet is a function of the temperature and the vapor pressure in its immediate environment. These quantities vary from droplet to droplet and with time in a turbulent medium such as a cumulus cloud. In most theoretical and numerical studies of clouds, the hypothesis is made that these variations are unimportant when calculating the growth of an ensemble of droplets. The objective of this work is to determine the validity of this hypothesis. In order to do so we use a 3D turbulence model coupled with a cloud droplet growth model which solves for the trajectories and growth of several tens of thousands of individual droplets as a function of their local conditions (microscopic approach). / A series of experiments with various initial size distributions were conducted using no turbulent flow conditions or one of three turbulent flows with increasing eddy dissipation rate. The results show that in the absence of any turbulent flow or sedimentation of droplets, the non-uniform distribution of cloud droplets in space results in significant variance of the distribution of the supersaturation perturbation over all droplets (DSP) and the distribution of the degree of growth (DDG), defined as the Lagrangian integral of the supersaturation perturbation along each droplet's trajectory. The variance of the DDG is directly responsible for the broadening of the microscopic size distribution relative to the macroscopic size distribution. However, in the presence of turbulence and sedimentation of droplets, the variance of the DSP is significantly reduced. Furthermore, the average, over all droplets, of the decorrelation time of the supersaturation perturbation decreases as a function of increasing level of turbulence. Consequently, the variance of the DDG is significantly reduced compared to the no turbulence and no sedimentation experiments and furthermore, it decreases as a function of increasing level of turbulence. / We have found that for the typical levels of turbulence found in adiabatic cloud cores, the spatial distribution of the larger cloud droplets can significantly deviate from a Poisson distribution. The increasing preferential concentration as a function of increasing level of turbulence does contribute to an increase in the DSP as a function of increasing level of turbulence. However, the DDG decreases as a function of increasing level of turbulence. / These results are at odds with those in the idealized studies of Pinsky et al. (1996) and Shaw et al. (1998). These authors specified and maintained very significant preferential concentration artificially rather than obtaining it by solving explicitly the trajectories of the droplets. / Comparison of our results with the observations of Brenguier and Chaumat (096) made in adiabatic cloud cores lead us to the conclusion that the microscopic approach, even under the most favorable condition of no turbulence, produces too little broadening to explain the observations.

A four dimensional variational (4D-Var) formulation is developed for the assimilation of radar reflectivity, Doppler velocities, and near-surface refractivity index data into a non-hydrostatic fully compressible limited-area atmospheric model coupled with a simplified warm microphysics scheme. The cloud-model is used as a weak constraint so the model error is explicit in the 4D-Var formulation. The ultimate goal is to provide initial conditions to a high-resolution numerical weather prediction model. The environmental flow around storms is modelled by a linear wind in a moving frame using Doppler velocity measurements over a given assimilation window. A three-stage procedure is established to solve the assimilation problem. The background-, observationand model-error statistics are adaptively estimated by comparison with a posteriori residuals and they converge after only a few minimizations. During the adaptive procedure, a smoothing constraint is applied to the analysis variables. The smoothing constraint diminishes towards zero for the last minimization while still leading to a smooth analysis. / Experiments with synthetic data from model outputs at 1 km horizontal resolution show that the method is able to retrieve unobserved variables. An assimilation period of 10 minutes is shown to be optimal for the analysis of clouds. All the other variables of the model are rather insensitive to the assimilation period. Here the model time step has been varied from 1 to 5 minutes. Most of the a posteriori residual distributions have a high kurtosis while the velocity and the near-surface refractivity index residual distributions are nearly Gaussian. The data assimilation for the case of a shallow hailstorm suggests that the model used for the assimilation is able to forecast the system for 30 minutes within the estimated observational errors. Application of the method to the initialization of the MC2 model leads to a better forecast of a convective system over 40 minutes than the nowcasting technique based on Lagrangian persistence.

The purpose of this thesis is to evaluate the downscaling ability of one-way nesting regional climate models (RCM). To do this, a rigorous and well-defined experiment for assessing the reliability of the one-way nesting approach is developed. This experiment, baptised the Big-Brother Experiment (BBE), is used for addressing some important one-way nesting issues. / The first part of this work is dedicated to the development of a scale decomposition tool employed for the BBE. This tool involves a new spectral analysing technique suitable for two-dimensional fields on limited-area domains, and is based on the discrete cosine transform (DCT). It is used for degrading the spatial resolution of the lateral boundary conditions (LBC) used to drive the Canadian RCM (CRCM), for extracting mesoscale features from the atmospheric fields, and for regional validation, and producing power spectra. / The second part of the thesis describes the BBE framework and its first results. The BBE consists in first establishing a reference virtual-reality climate from an RCM simulation using a large and high-resolution domain. This simulation is called the "Big Brother". This big-brother simulation is then degraded toward the resolution of today's global objective analyses (OA) and/or global climate models (GCM) by removing the short scales. The resulting fields are then used as nesting data to drive an RCM (called the "Little Brother") which is integrated at the same high-resolution as the Big Brother, but over a sub-area of the big-brother domain. The climate statistics of the Little Brother are then compared with those of the big-brother simulation over the little-brother domain. Differences between the two climates can thus be unambiguously attributed to errors associated with the dynamical downscaling technique, and not to model errors nor to observation limitations. The results for a February simulation shows that the Canadian RCM, using a factor of 6 between the model and the LBC spatial resolution, and an update interval of 3 hours, is capable to pass the BBE test; thus showing the reliability of the one-way nesting approach. / In the third and last part of the thesis, the BBE is used to investigate the sensitivity of an RCM to the spatial resolution and temporal update frequency of the LBC. It is shown that spatial resolution jumps of 12, and an update frequency between twice a day (every 12 hours) and four times a day (every 6 hours), are the limits for which a 45-km RCM yields acceptable results.

Despite being ubiquitous in the Mackenzie River Basin (MRB) of Canada, the role of snow in its energy and water budgets are still open to much speculation. This thesis presents a multi-scale analysis of the contribution of blowing snow to the hydrometeorology of the MRB. A climatology of adverse wintertime weather events is first presented and demonstrates that blowing snow events are rare within the forested sections of the MRB but become more frequent in the northern parts of the basin covered by Arctic tundra. It is these areas which experience the largest impacts of blowing snow transport and sublimation due to large-scale processes. To further assess the mesoscale and microscale effects of blowing snow to the northern regions of the MRB, the development of a bulk blowing snow model is then described. The single- and double-moment versions of the PIEKTUK blowing snow model are shown to produce equivalent results as a previous spectral version of the numerical model while operating about 100 times faster. The application of the double-moment PIEKTUK model (PIEKTUK-D) to a Canadian Arctic tundra site near the northern tip of the MRB reveals that blowing snow sublimation depletes ≈3 mm snow water equivalent (swe) from the snowpack over a period of 210 days during the winter of 1996/1997 at Trail Valley Creek, Northwest Territories. Various assumptions on the state of the background thermodynamic profiles and their evolution during blowing snow, however, can yield significantly higher (>300%) rates of sublimation over the same period. PIEKTUK-D is then coupled to the Mesoscale Compressible Community (MC2) model for an interactive simulation of a ground blizzard at Trail Valley Creek. This coupled mesoscale simulation reveals that moistening and cooling of near-surface air associated with blowing snow sublimation is observed but mitigated in part by advective and entrainment processes. Combined, blowing snow sublimation and mass divergence are then shown to rem

The atmospheric fluctuations associated with sea surface temperature (SST) anomalies in the northern North Atlantic and their subsequent effects on river runoff variations over Siberia are studied in this thesis. A data analysis is performed in Part I of the thesis using 50 years (1930-79) of records of SST sea level pressure, precipitation and runoff. It is found from this analysis that the winter SST anomalies in the northern North Atlantic are significantly correlated with the winter and the following summer runoff fluctuations of the Ob and Yenisey rivers in western Siberia. / A modelling study is conducted in Part II of the thesis to investigate the variability of winter atmospheric responses to the SST anomalies in the northwest Atlantic. Experiments are performed with an atmospheric global spectral model using both November and January conditions. The atmospheric responses to the prescribed positive SST anomalies obtained are found to be completely different in the November and January simulations. Over the Atlantic, a positive (negative) geopotential height anomaly center is observed downstream of the warm SST area in the November (January) case. A comprehensive diagnostic analysis of the heat advection in the experiments is carried out to obtain a deeper understanding of the physical maintenance of the two responses.

The nature of balance schemes and the concept of the slow manifold are discussed using Lorenz's (1980) model. It has been found that the Bear-Tribbia's (1977) scheme leads to a divergent series in locating the slow manifold of the model. The optimal asymptotic approximation and Pade approximant are use to "sum" the divergent series. / The optimal asymptotic approximation gives reasonable approximation to the full solutions of the model and provides the optimal balance relations which are quite accurate when the forcing is small. The accuracy seems to degrade rather quickly as the forcing increases. The "imbalance", which is the difference between the actual flow and the optimal balance state, is found to consist of nearly monochromatic inertial-gravity waves. It is shown that the optimal asymptotic approximation fails to give a reasonable estimate of the level of inertial-gravity wave activity from the Rossby modes. / For the case considered in this thesis, the Pade approximant does not seem to work well and hence offers no significant advantage over the optimal asymptotic approximation. The slow manifold, fuzzy slow manifold and effects of the scaling on the balance are also discussed in this thesis.

Early scaling stochastic models of cloud and rain fields were designed to obey the simple scale invariance symmetry. The linear nature of these additive processes is intrinsically related to their single fractal dimension which is in sharp contrast with the non-linear nature of the dynamical processes within the atmosphere and with the observed multiple scaling of rain and cloud fields. We consider stochastic models corresponding to coupled cascade processes, non linearly conserving the fluxes of energy and concentration variance. Multiplicative processes, previously based on discrete cascade procedures, are generalized to their continuous limit using a dynamical generator of the cascade characterized by only two parameters which determine the full multifractal spectrum of dimensions. We show how to numerically simulate such multifractal processes with both gaussian and Levy generators, and how to perform a scale invariant "zooming" procedure in the case of clouds passively advected by a turbulent velocity field.

This study investigates the potential usefulness of a commercial laser ceilometer, an instrument used operationally at most airports for monitoring cloud base, for providing an inexpensive, continuous indication of air quality. Using lidar principles, a method is presented in which the ceilometer can provide information on the aerosol optical properties of the atmosphere. Further insight into the ceilometer measurements is obtained by comparing observations with aircraft, lidar, and a RASS-equipped profiler. The results of this work show that the ceilometer can provide estimates of aerosol extinction in the lower troposphere under sufficiently hazy conditions.

In this thesis, a series of (48-60 h) numerical simulations of a family of frontal cyclogenesis events that occurred over western Atlantic Ocean during 13-15 March 1992 are conducted using a nested-grid version of the PSU/NCAR mesoscale model (MM4) with a fine-mesh grid size of 30 km. It is shown that MM4 captures very well the genesis, track and intensity of three secondary cyclones, their associated thermal structure and precipitation pattern as well as their surface circulations. / It is found that an upper-level potential vorticity (PV) ring plays an important role in determining the initiation and track of the frontal cyclones. The cyclones appear to form as a consequence of the superposition of upper-level PV anomalies on the low-level intense baroclinicity in the cold sector behind the slow moving primary cold front, and then they propagate into colder air towards the parent cyclone's center. It is also found that as the MFC intensifies, a mesoscale trough is induced in the low-to-middle troposphere, creating a favorable phase lag between the new pressure trough and a slow moving thermal wave. This phase lag provides a baroclinic conversion mechanism by which the system's kinetic energy could increase rapidly at the expense of available potential energy. / Diagnosis of sensitivity experiments reveals (i) dry dynamics determines the initiation and track of the frontal cyclones, accounting for about 59% of the final intensity of the MFC; (ii) the low-level baroclinicity and the upper-level PV anomalies are near-equally important in the genesis of the dry systems; (iii) the Ekman spin-down tends to slow substantially the development of the frontal cyclones; and (iv) surface heat and moisture fluxes could produce a significant impact (i.e., 59%) on the final intensity of the cyclones in the presence of latent heat release, but its impact is small in the dry dynamical framework. (Abstract shortened by UMI.)

A variational semi-Lagrangian wind retrieval algorithm from single-Doppler radar data is studied both analytically and numerically, in order to understand its responses as well as limitations. The theoretical background on which the algorithm is based, is described in detail. A new approximation of the conservation equation of reflectivity for wind retrieval purposes is derived. It is shown that, in general, a unique wind field may not be available for the entire domain. However, some ways of minimizing this inconvenience are presented. The existence of a spurious solution when the conservation equation of a tracer is discretized is found analytically. A real case (a storm characterized by a mesocyclonic circulation) is used in order to illustrate the problem of the non-uniqueness of the solution. This is carried out through the study of the sensitivity of the algorithm to the moving frame and the initial guess. In addition, the influence of each one of the constraints used (conservation of reflectivity, continuity equation, smoothness constraint) in the retrieved wind field are analyzed. It is concluded that in spite of the sources of error described, the results may be meaningful.