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Louis-Philippe Crevier and Yves Delage

Abstract

A numerical model to forecast road conditions, Model of the Environment and Temperature of Roads (METRo), has been developed to run at Canadian weather centers. METRo uses roadside observations from road weather information systems stations as input, together with meteorological forecasts from the operational Global Environmental Multiscale (GEM) model of the Canadian Meteorological Centre; the meteorologist can modify this forecast using the “SCRIBE” interface. METRo solves the energy balance at the road surface and the heat conduction in the road material to calculate the temperature evolution; it also accounts for water accumulation on the road in liquid and solid form. Radiative fluxes reaching the surface are taken from the GEM model in automatic mode or are parameterized as a function of cloud cover and temperature when run in manual mode. The road-condition forecast is done in three stages: initialization of the road temperature profile using past observations, coupling of the forecast with observations during the overlap period when the meteorological forecast and the roadside observations are both available, and the forecast itself. The coupling stage allows for adjusting the radiative fluxes to local conditions. Results for road temperature are presented for three stations in Ontario for a period of 3 months. The 24-h forecasts are issued 2 times per day at 0300 and 1500 LT. Overall, about one-half of the time the error in surface road temperature (verified every 20 min) is within ±2 K, and the nighttime rms error is about 2 K. The impact of the coupling stage is large and allows METRo to produce automatic forecasts almost as good as the manual ones, especially for the first few hours. When METRo is run in manual mode, several nearby stations can use the same meteorological input, saving preparation time for the meteorologist. METRo also contains a mechanism for correcting systematic errors at each station, and it is hoped that this capability will permit its application to many new sites without major adjustments.

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Steven C. Smyth, Dazhong Yin, Helmut Roth, Weimin Jiang, Michael D. Moran, and Louis-Philippe Crevier

Abstract

The fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) is currently the meteorological model most widely used as input into the Community Multiscale Air Quality (CMAQ) modeling system. In this study, meteorological fields produced by the Global Environmental Multiscale (GEM) meteorological model were compared with those from MM5, and the impact of using the two different modeled datasets as inputs to CMAQ was investigated. Two CMAQ model runs, differing only in meteorological inputs and meteorologically influenced emissions, were conducted for a domain covering eastern Canada and the northeastern United States for a 9-day period in July 1999. Comparison of the two modeled meteorological datasets with surface measurements revealed that GEM and MM5 gave comparable results. For a direct comparison of the two meteorological datasets the differences were small for pressure and temperature but larger for wind speed and relative humidity (RH). The variations in meteorological fields affect emissions and air quality results in differing ways and to differing degrees. The most influential meteorological field on emissions was temperature, which had a minor impact on on-road mobile emissions and a larger impact on biogenic emissions. Performance statistics for O3 and for particulate matter less than 10 μm and less than 2.5 μm (PM10, and PM2.5, respectively) show that GEM-based and MM5-based CMAQ results compare similarly to hourly measurement data, with minor statistical differences. A direct comparison of O3, PM10, PM2.5, and speciated PM2.5 showed that the results correlate to varying degrees and that the differences in RH affect total particulate matter (PM) mass and aerosol species concentrations significantly. Relative humidity affects total particle mass and particle diameters, which in turn affect PM2.5 and PM10 concentrations.

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Stéphane Bélair, Ross Brown, Jocelyn Mailhot, Bernard Bilodeau, and Louis-Philippe Crevier

Abstract

The performance of a modified version of the snow scheme included in the Interactions between Surface–Biosphere–Atmosphere (ISBA) land surface scheme, which was operationally implemented into the regional weather forecast system at the Canadian Meteorological Centre, is examined in this study. Stand-alone verification tests conducted prior to the operational implementation showed that ISBA's new snow package was able to realistically reproduce the main characteristics of a snow cover, such as snow water equivalent and density, for five winter datasets taken at Col de Porte, France, and at Goose Bay, Newfoundland, Canada. A number of modifications to ISBA's snow model (i.e., new liquid water reservoir in the snowpack, new formulation of snow density, and melting effect of incident rainfall on the snowpack) were found to improve the numerical representation of snow characteristics.

Objective scores for the fully interactive preimplementation tests carried out with the Canadian regional weather forecast model indicated that ISBA's improved snow scheme only had a minor impact on the model's ability to predict atmospheric circulation. The objective scores revealed that only a thin atmospheric layer above snow-covered surfaces was influenced by the change of land surface scheme, and that over these regions the essential behavior of the atmospheric model was not significantly altered by improvements to the treatment of snow cover. It was shown that this lack of response was most likely related to the treatment of the snow cover fraction in each atmospheric model grid tile. The estimation of snow cover fraction relied on simple formulations that were dependent on poorly known parameters, such as the fractional coverage of vegetation. Results showed that uncertainties of only 15% in vegetation fractional coverage could be responsible for uncertainties of as much as 1–1.5 K in screen-level air temperature. This indicates that some care must be exercised in the specification of vegetation and snow cover fractional coverage.

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Stéphane Bélair, Louis-Philippe Crevier, Jocelyn Mailhot, Bernard Bilodeau, and Yves Delage

Abstract

The summertime improvement resulting from the operational implementation of a new surface modeling and assimilation strategy into the Canadian regional weather forecasting system is described in this study. The surface processes over land are represented in this system using the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface scheme. Surface variables, including soil moisture, are initialized using a sequential assimilation technique in which model errors of low-level air temperature and relative humidity are used to determine analysis increments of surface variables.

It was found that the magnitude and nature of the analysis increments applied to the surface variables depended on the surface and meteorological conditions observed in each region. In regions characterized by weak meteorological activity (i.e., no clouds or precipitation), model errors of low-level air characteristics are more likely to be related to an incorrect representation of surface processes due to either erroneous initial conditions or inaccurate parameterizations in the land surface scheme. In other regions characterized by more frequent and more intense precipitation events, surface corrections are mainly associated with inaccurate atmospheric forcing.

Objective evaluation against observations from radiosondes and surface stations showed that the amplitude of the diurnal cycle of near-surface air temperature and humidity is larger with the new surface system, in better agreement with observations. This type of improvement was found to extend higher up in the boundary layer (up to 700 hPa) where cold and humid biases were significantly reduced by introducing the new surface system. The model precipitation was also found to be significantly influenced by the new representation of surface fluxes. The problematic increase of a positive bias in precipitation with integration time was found to be significantly reduced with the new system, due to the warmer and drier boundary layer.

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