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Luc Fillion and Stéphane Bélair

Abstract

Advanced operational four-dimensional variational data assimilation (4DVAR) schemes include a linearized version of moist convective parameterization and its adjoint. At the Meteorological Service of Canada, work is underway to implement 4DVAR for both global and regional operational data assimilation. Moreover, the Kain– Fritsch moist convective parameterization scheme is currently under operational testing for global and regional weather forecasting. Consequently, tangent linear and adjoint versions of this convective scheme have been developed. Sources of nonlinearities and accuracy of the tangent linear approximation of the convective scheme itself were examined. The procedure to test this latter aspect uses Monte Carlo simulations based on background error covariances from the operational three-dimensional variational data assimilation (3DVAR) system at the Canadian Meteorological Centre. It is shown that for a critical level of amplitudes of vertical perturbations of temperature or moisture greater than typically 0.1 K or 0.1 g kg−1, the tangent linear approximation becomes inaccurate (e.g., typical perturbation response having the wrong sign and amplitude errors larger than 100%). For such perturbation amplitudes, there is a rapid increase of convective points where the tangent linear convective approximation is very strongly in error. Deactivation of the Kain–Fritsch scheme becomes frequent and a significant source of invalid tangent linear approximation for input perturbations exceeding typically 0.3 K or 0.3 g kg−1. Potential implications of this study for linearized moist convection in the context of 4DVAR and moist singular vector computation are discussed.

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Stéphane Bélair and Jocelyn Mailhot

Abstract

The relative roles of implicit and explicit condensation schemes in the numerical representation of a squall line that occurred on 7–8 May 1995 over the southern Great Plains are examined in this study using Mesoscale Compressible Community model integrations at 2-, 6-, 18-, and 50-km resolution. Results from the 2-km model in which condensation is explicitly represented agree best with observations and are used as “synthetic” data to evaluate the performance of lower-resolution configurations.

It is found that the representation of the squall system greatly deteriorates as resolution is decreased and that the relative roles of the implicit and explicit condensation schemes change dramatically. At 6-km resolution, the leading convective band is barely resolved by the model, and the implicit–explicit partition of precipitation is ambiguous because both implicit and explicit schemes are active simultaneously at the leading edge of the system. In spite of this ambiguity, it is found that use of a deep convection scheme is still beneficial to the squall-line simulation. At 18 km, the convective line is not resolved by the model, and its effect is completely due to the implicit scheme. The mesoscale circulations in the trailing anvil region of the squall system are generated at the small end of the model resolvable scales and are exaggeratedly intense. There is no ambiguity concerning the partition of condensation into implicit and explicit components at this resolution, but the relative intensity of precipitation produced by the two cloud schemes is opposite to what is observed, considering that the implicit scheme is supposed to represent subgrid-scale convection at the leading edge of the system, and the explicit scheme the grid-scale condensation in the trailing anvil. At 50 km, both the leading convection and the mesoscale circulations in the trailing anvil have to be parameterized because they are not resolved at the model grid scale. The precipitation and internal structures associated with the squall line are thus not well represented at this resolution.

The results also show that all the configurations produce precipitation accumulations that are much larger than observations. This problem is most important at 18-km resolution. Grid-scale condensation is mostly responsible for this rainfall overestimation. It is suggested that this problem is linked to a misrepresentation of convective-scale processes.

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Stéphane Bélair and Da-Lin Zhang

Abstract

Despite considerable progress in the understanding of two-dimensional structures of squall lines, little attention has been paid to the along-line variability of these convective systems. In this study, the roles of meso- and larger-scale circulations in the generation of along-line variability of squall lines are investigated, using an 18-h prediction of a frontal squall line that occurred on 26–27 June 1985 during PRE-STORM (Preliminary Regional Experiment for Stormscale Operational Research Meteorology). It is shown that the Canadian regional finite-element (RFE) model reproduces reasonably well a number of surface and vertical circulation structures of the squall system, as verified against available network observations. These include the initiation, propagation, and dissipation of the squall system, surface pressure perturbations, and cold outflow boundaries; a midlevel mesolow and an upper-level mesohigh; a front-to-rear (FTR) ascending flow overlying an intense rear-to-front (RTF) flow; and a leading convective line followed by stratiform precipitation regions.

It is found that across-line circulations at the northern segment of the squall line differ significantly from those at its southern segment, including the different types of precipitation, the absence of the RTF flow and midlevel mesolow, and the early dissipation of organized convection in the northern part. The along-line variability of the squall’s circulations results primarily from the interaction of convectively generated perturbations with a midlevel baroclinic trough. The large-scale trough provides an extensive RTF flow component in the southern portion of the squall system and an FTR flow component in the north, whereas the midlevel mesolow tends to enhance the RTF flow to the south and the FTR flow to the north of the mesolow during the mature to decaying stages. The along-line variability of the squall’s circulations appears to be partly responsible for the generation of different weather conditions along the line, such as the development of an upper-level stratiform region in the southern segment and a midlevel cloud region in the northern portion of the squall line.

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Natacha B. Bernier and Stéphane Bélair

Abstract

As harvesting of wind energy grows, so does the need for improved forecasts from the surface to the top of wind turbines. To improve mesoscale forecasts of wind, temperature, and dewpoint temperature in this layer, two different approaches are examined. In the first experiment, the vertical resolution of a limited-area model with 2.5-km grid spacing (LAM-2.5 km) is significantly increased near the surface to better represent profiles in that layer. In the second experiment, prognostic variables for land and ocean surfaces are initialized using results from an external land surface model system [the Global Environmental Multiscale Surface system (GEM-Surf)] and from a regional ocean model. Results show that increasing the vertical resolution near the surface leads to improved temperature and dewpoint temperature forecasts at the surface and in the wind turbine layer. For winds, improvements are more modest, because they are limited to the gradient measured across the span of the vertical wind turbine blades. On the other hand, the replacement of operational surface analyses with high-resolution analyses obtained from GEM-Surf is found to improve summer dewpoint temperature forecasts. It is shown that changes in soil moisture analyses explain the bulk of the improved dewpoint forecasts.

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Marco L. Carrera, Stéphane Bélair, and Bernard Bilodeau

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The Canadian Land Data Assimilation System (CaLDAS) has been developed at the Meteorological Research Division of Environment Canada (EC) to better represent the land surface initial states in environmental prediction and assimilation systems. CaLDAS is built around an external land surface modeling system and uses the ensemble Kalman filter (EnKF) methodology. A unique feature of CaLDAS is the use of improved precipitation forcing through the assimilation of precipitation observations. An ensemble of precipitation analyses is generated by combining numerical weather prediction (NWP) model precipitation forecasts with precipitation observations. Spatial phasing errors to the NWP first-guess precipitation forecasts are more effective than perturbations to the precipitation observations in decreasing (increasing) the exceedance ratio (uncertainty ratio) scores and generating flatter, more reliable ranked histograms. CaLDAS has been configured to assimilate L-band microwave brightness temperature TB by coupling the land surface model with a microwave radiative transfer model. A continental-scale synthetic experiment assimilating passive L-band TBs for an entire warm season is performed over North America. Ensemble metric scores are used to quantify the impact of different atmospheric forcing uncertainties on soil moisture and TB ensemble spread. The use of an ensemble of precipitation analyses, generated by assimilating precipitation observations, as forcing combined with the assimilation of L-band TBs gave rise to the largest improvements in superficial soil moisture scores and to a more rapid reduction of the root-zone soil moisture errors. Innovation diagnostics show that the EnKF is able to maintain a sufficient forecast error spread through time, while soil moisture estimation error improvements with increasing ensemble size were limited.

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Stéphane Bélair, Da-Lin Zhang, and Jocelyn Mailhot

Abstract

In an effort to improve operational forecasts of mesoscale convective systems (MCSs), a mesoscale version of the operational Canadian Regional Finite-Element (RFE) Model with a grid size of 25 km is used to predict an intense MCS that occurred during 10–11 June 1985. The mesoscale version of the RFE model contains the Fritsch–Chappell scheme for the treatment of subgrid-scale convective processes and an explicit scheme for the treatment of grid-scale cloud water (ice) and rainwater (snow).

With higher resolution and improved condensation physics, the RFE model reproduces many detailed structures of the MCS, as compared with all available observations. In particular, the model predicts well the timing and location of the leading convective line followed by stratiform precipitation; the distribution of surface temperature and pressure perturbations (e.g., cold outflow boundaries, mesolows, mesohighs, and wake lows); and the circulation of front-to-rear flows at both upper and lower levels separated by a rear-to-front flow at midlevels.

Several sensitivity experiments are performed to examine the effects of varying initial conditions and model physics on the prediction of the squall system. It is found that both the moist convective adjustment and the Kuo schemes can reproduce the line structure of convective precipitation. However, these two schemes are unable to reproduce the internal flow structure of the squall system and the pertinent surface pressure and thermal perturbations. It is emphasized that as the grid resolution increases, reasonable treatments of both parameterized and grid-scale condensation processes are essential in obtaining realistic predictions of MCSs and associated quantitative precipitation.

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Lily Ioannidou, Wei Yu, and Stéphane Bélair

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The capability of the Canadian land surface external modeling system known as the Global Environmental Multiscale Surface (GEM-SURF) system with respect to surface wind predictions is evaluated. Based on the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface scheme, and an exponential power law adjusted to the local stability conditions for the prediction of surface winds, the system allows decoupling of surface processes from those of the free atmosphere and enables high resolutions at the surface as dictated by the small-scale heterogeneities of the surface boundary. The simulations are driven by downscaled forecasts from the Regional Deterministic Prediction System, the 15-km Canadian regional operational modeling system. High-resolution, satellite-derived datasets of orography, vegetation, and soil cover are used to depict the surface boundary. The integration domains cover Canada’s eastern provinces at resolutions ranging from that of the driving model to resolutions similar to those of the geophysical datasets. The GEM-SURF predictions outperform those of the driving operational model. Reduction of the standard error and improvement of the model skill is seen as resolution increases, for all wind speeds. Further, the bias error is reduced in association with a rise in the corresponding value of the roughness length. For all examined resolutions GEM-SURF’s predictions are shown to be superior to those obtained through a simple statistical downscaling. In the prospect of the future development of a multicomponent system that provides wind forecasts at levels of wind energy generation, GEM-SURF’s potential for improved scores at the surface and its limited requirements in computer resources make it a suitable surface component of such a system.

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Yi-Ching Chung, Stéphane Bélair, and Jocelyn Mailhot

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A one-dimensional (1D) version of a blowing snow model, called PIEKTUK-D, has been incorporated into a snow–sea ice coupled system. Blowing snow results in sublimation of approximately 12 mm of snow water equivalent (SWE), which is equal to approximately 6% of the annual precipitation over 324 days from 1997 to 1998. This effect leads to an average decrease of 9 cm in snow depth for an 11-month simulation of the Surface Heat Budget of the Arctic Ocean (SHEBA) dataset (from 31 October 1997 to 1 October 1998). Inclusion of blowing snow has a significant impact on snow evolution between February and June, during which it is responsible for a decrease in snow depth error by about 30%. Between November and January, however, other factors such as regional surface topography or horizontal wind transport may have had a greater influence on the evolution of the snowpack and sea ice. During these few months the new system does not perform as well, with a snow depth percentage error of 39%—much larger than the 12% error found between February and June. The results also indicate a slight increase of 4 cm on average for ice thickness, and a decrease of 0.4 K for the temperature at the snow–ice interface. One of the main effects of blowing snow is to shorten the duration of snow cover above sea ice by approximately 4 days and to lead to earlier ice melt by approximately 6 days. Blowing snow also has a very small impact on internal characteristics of the snowpack, such as grain size and density, leading to a weaker snowpack.

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Yi-Ching Chung, Stéphane Bélair, and Jocelyn Mailhot

Abstract

The new Recherche Prévision Numérique (NEW-RPN) model, a coupled system including a multilayer snow thermal model (SNTHERM) and the sea ice model currently used in the Meteorological Service of Canada (MSC) operational forecasting system, was evaluated in a one-dimensional mode using meteorological observations from the Surface Heat Budget of the Arctic Ocean (SHEBA)’s Pittsburgh site in the Arctic Ocean collected during 1997/98. Two parameters simulated by NEW-RPN (i.e., snow depth and ice thickness) are compared with SHEBA’s observations and with simulations from RPN, MSC’s current coupled system (the same sea ice model and a single-layer snow model). Results show that NEW-RPN exhibits better agreement for the timing of snow depletion and for ice thickness. The profiles of snow thermal conductivity in NEW-RPN show considerable variability across the snow layers, but the mean value (0.39 W m−1 K−1) is within the range of reported observations for SHEBA. This value is larger than 0.31 W m−1 K−1, which is commonly used in single-layer snow models. Of particular interest in NEW-RPN’s simulation is the strong temperature stratification of the snowpack, which indicates that a multilayer snow model is needed in the SHEBA scenario. A sensitivity analysis indicates that snow compaction is also a crucial process for a realistic representation of the snowpack within the snow/sea ice system. NEW-RPN’s overestimation of snow depth may be related to other processes not included in the study, such as small-scale horizontal variability of snow depth and blowing snow processes.

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Syed Zahid Husain, Stéphane Bélair, and Sylvie Leroyer

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The influence of soil moisture on the surface-layer atmosphere is examined in this paper by analyzing the outputs of model simulations for different initial soil moisture configurations, with particular emphasis on urban microclimate. In addition to a control case, four different soil moisture distributions within the urban and surrounding rural areas are considered in this study. Outputs from the Global Environmental Multiscale atmospheric model simulations are compared with observations from the Joint Urban 2003 experiment held in Oklahoma City, Oklahoma, and the relevant conclusions drawn in this paper are therefore valid for similar medium-size cities. In general, high soil moisture is found to be associated with colder near-surface temperature and lower near-surface wind speed, whereas drier soil resulted in warmer temperatures and enhanced low-level wind. Relative to urban soil moisture content, rural soil conditions are predicted to have larger impacts on both rural and urban surface-layer meteorological conditions. Dry rural and wet urban soil configurations are shown to have a strong influence on the urban–rural temperature contrast and resulted in city-induced secondary circulations that considerably affect the near-surface wind speed. Dry rural soil in particular is found to intensify the nocturnal low-level jet and significantly affect the thermal stability of nocturnal near-neutral urban surface layer by altering both thermal and mechanical generation of turbulence.

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