Syed Zahid Husain

Subkilometer Numerical Weather Prediction in an Urban Coastal Area: A Case Study over the Vancouver Metropolitan Area

AbstractNumerical weather prediction is moving toward the representation of finescale processes such as the interactions between the sea-breeze flow and urban processes. This study investigates the ability and necessity of using kilometer- to subkilometer-scale numerical simulations with the Canadian urban modeling system over the complex urban coastal area of Vancouver, British Columbia, Canada, during a sea-breeze event. Observations over the densely urbanized areas, collected from the Environmental Prediction in Canadian Cities (EPiCC) network and from satellite imagery, are used to evaluate several aspects of the urban boundary layer features simulated in three model configurations with different grid spacings (2.5 km, 1 km, and 250 m). In agreement with the observations, results from the numerical experiments with 1-km and 250-m grid spacings suggest that two sea-breeze flows converge over the residential areas of Vancouver. The resulting convergence line oscillates around the hill ridge, depending o...

Influence of Soil Moisture on Urban Microclimate and Surface-Layer Meteorology in Oklahoma City

AbstractThe 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 ...

Warm Season Evaluation of Soil Moisture Prediction in the Soil, Vegetation, and Snow (SVS) Scheme

AbstractA new land surface scheme has been developed at Environment and Climate Change Canada (ECCC) to provide surface fluxes of momentum, heat, and moisture for the Global Environmental Multiscale (GEM) atmospheric model. In this study, the performance of the Soil, Vegetation, and Snow (SVS) scheme in estimating the surface and root-zone soil moisture is evaluated against the Interactions between Soil, Biosphere, and Atmosphere (ISBA) scheme currently used operationally at ECCC within GEM for numerical weather prediction. In addition, the sensitivity of SVS soil moisture results to soil texture and vegetation data sources (type and fractional coverage) has been explored. The performance of SVS and ISBA was assessed against a large set of in situ observations as well as the brightness temperature data from the Soil Moisture Ocean Salinity (SMOS) satellite over North America. The results indicate that SVS estimates the time evolution of soil moisture more accurately, and compared to ISBA, results in highe...

The Multibudget Soil, Vegetation, and Snow (SVS) Scheme for Land Surface Parameterization: Offline Warm Season Evaluation

AbstractA new land surface parameterization scheme, named the Soil, Vegetation, and Snow (SVS) scheme, was recently developed at Environment and Climate Change Canada to replace the operationally used Interactions between Soil, Biosphere, and Atmosphere (ISBA) scheme. The new scheme is designed to address a number of weaknesses and limitations of ISBA that have been identified over the last decade. Unlike ISBA, which calculates a single energy budget for the different land surface components, SVS introduces a new tiling approach that includes separate energy budgets for bare ground, vegetation, and two different snowpacks (over bare ground and low vegetation and under high vegetation). The inclusion of a photosynthesis module as an option to determine the surface stomatal resistance is another significant addition in SVS. The representation of vertical water transport through soil has also been substantially improved in SVS with the introduction of multiple soil layers. Overall, offline simulations conduc...

High‐resolution surface analysis for extended‐range downscaling with limited‐area atmospheric models

High-resolution limited-area model (LAM) simulations are frequently employed to downscale coarse-resolution objective analyses over a specified area of the globe using high-resolution computational grids. When LAMs are integrated over extended time frames, from months to years, they are prone to deviations in land surface variables that can be harmful to the quality of the simulated near-surface fields. Nudging of the prognostic surface fields toward a reference-gridded data set is therefore devised in order to prevent the atmospheric model from diverging from the expected values. This paper presents a method to generate high-resolution analyses of land-surface variables, such as surface canopy temperature, soil moisture, and snow conditions, to be used for the relaxation of lower boundary conditions in extended-range LAM simulations. The proposed method is based on performing offline simulations with an external surface model, forced with the near-surface meteorological fields derived from short-range forecast, operational analyses, and observed temperatures and humidity. Results show that the outputs of the surface model obtained in the present study have potential to improve the near-surface atmospheric fields in extended-range LAM integrations.

Improving the Representation of the Nocturnal Near-Neutral Surface Layer in the Urban Environment with a Mesoscale Atmospheric Model

A new approach to improve the representation of surface processes in the Global Environmental Multiscale (GEM) atmospheric model associated with the exchanges between the urban canopy and the atmosphere is presented. Effects of the urban canopy on the evolution of surface-layer wind, temperature, moisture, and turbulence are directly parametrized in order to allow realistic interactions between the canopy elements (i.e., roofs, roads, and walls) and the atmosphere at GEM’s multiple vertical levels that are positioned inside the canopy. Surface energy budgets as implemented in the Town Energy Balance (TEB) scheme have been used to determine temperatures of the urban canopy elements for the proposed multilayer scheme. Performance of the multilayer scheme is compared against standard implementations of the TEB scheme for one nighttime intensive observation period of the Joint Urban 2003 experiment held in Oklahoma City, USA. Although the new approach is found to have a negligible impact on urban surface-layer wind profiles, it improves the prediction of near-neutral nocturnal profiles of potential temperature close to the surface. The urban heat island effect is simulated with a better accuracy by the multilayer approach. The horizontal temperature gradient across the central business district of the city along the direction of flow is also reasonably well captured by the proposed scheme.

Extended‐range high‐resolution dynamical downscaling over a continental‐scale spatial domain with atmospheric and surface nudging

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.

Internal variability of fine‐scale components of meteorological fields in extended‐range limited‐area model simulations with atmospheric and surface nudging

Internal variability (IV) in dynamical downscaling with limited-area models (LAM) represents a source of error inherent to the downscaled fields, which originates from the sensitive dependence of the models to arbitrarily small modifications. If IV is large it may impose the need for probabilistic verification of the downscaled information. Atmospheric spectral nudging (ASN) can reduce IV in LAMs as it constrains the large-scale components of LAM fields in the interior of the computational domain and thus prevents any considerable penetration of sensitively dependent deviations into the range of large scales. Using initial condition ensembles, the present study quantifies the impact of ASN on IV in LAM simulations in the range of fine scales that are not controlled by spectral nudging. Four simulation configurations that all include strong ASN but differ in the nudging settings are considered. In the fifth configuration, grid nudging of land surface variables towards high-resolution surface analyses is applied. The results show that the IV at scales larger than 300 km can be suppressed by selecting an appropriate ASN setup. At scales between 300 and 30 km, however, in all configurations, the hourly near-surface temperature, humidity and winds are only partly reproducible. Nudging the land surface variables is found to have the potential to significantly reduce IV, particularly for fine-scale temperature and humidity. On the other hand, hourly precipitation accumulations at these scales are generally irreproducible in all configurations and probabilistic approach to downscaling is therefore recommended.