An Overview of the Urban Boundary Layer Atmosphere Network in Helsinki

Wood, Curtis W.; Järvi, Leena; Kouznetsov, Rostislav; Nordbo, Annika; Joffre, Sylvain M.; Drebs, Achim; Vihma, Timo; Hirsikko, Anne; Suomi, Irene; Fortelius, Carl; O’Connor, Ewan; Моисеев, Д. В.; Haapanala, Sami; Moilanen, J.; Kangas, Markku; Karppinen, Ari; Vesala, Timo; Kukkonen, Jaakko

doi:10.1175/bams-d-12-00146.1

Cited by 34 publications

(23 citation statements)

References 56 publications

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“…This becomes a simple one-dimensional optimization problem in which the objective is to minimize J = β f i,j,k dx , where β represents the far-field domain, by the means of controlling c i,j,k . Thus, this technique bears resemblance to a planar fit method (Wilczak et al, 2001). Because the control variable here is a single scalar, a rudimentary implementation of an iterative gradient decent search algorithm suffices (see, for instance, Nocedal and Wright, 2006).…”

Section: Coordinate Rotation Via Far-field Correctionmentioning

confidence: 99%

Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

et al. 2017

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Abstract. Conventional footprint models cannot account for the heterogeneity of the urban landscape imposing a pronounced uncertainty on the spatial interpretation of eddycovariance (EC) flux measurements in urban studies. This work introduces a computational methodology that enables the generation of detailed footprints in arbitrarily complex urban flux measurements sites. The methodology is based on conducting high-resolution large-eddy simulation (LES) and Lagrangian stochastic (LS) particle analysis on a model that features a detailed topographic description of a real urban environment. The approach utilizes an arbitrarily sized target volume set around the sensor in the LES domain, to collect a dataset of LS particles which are seeded from the potential source area of the measurement and captured at the sensor site. The urban footprint is generated from this dataset through a piecewise postprocessing procedure, which divides the footprint evaluation into multiple independent processes that each yield an intermediate result. These results are ultimately selectively combined to produce the final footprint. The strategy reduces the computational cost of the LES-LS simulation and incorporates techniques to account for the complications that arise when the EC sensor is mounted on a building instead of a conventional flux tower. The presented computational framework also introduces a result assessment strategy which utilizes the obtained urban footprint together with a detailed land cover type dataset to estimate the potential error that may arise if analytically derived footprint models were employed instead. The methodology is demonstrated with a case study that concentrates on generating the footprint for a building-mounted EC measurement station in downtown Helsinki, Finland, under the neutrally stratified atmospheric boundary layer.

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Section: Coordinate Rotation Via Far-field Correctionmentioning

confidence: 99%

Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

et al. 2017

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“…According to Ahokas and Kaartinen (2013), the ALS accuracy obtained in all various sur- (Koskinen et al, 2011). Recently, the Helsinki UrBAN (Urban Boundary-layer Atmosphere Network, http://urban.fmi.fi) project has started a long-term intensive observational network to study physical processes in the atmosphere above the city (Wood et al, 2013). The network's key purpose is the understanding of the physical processes in the urban boundary layer such as fluxes of heat, momentum and exchanges of water vapor.…”

Section: Methodsmentioning

confidence: 99%

Airborne laser scan data: a valuable tool with which to infer weather radar partial beam blockage in urban environments

2016

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Abstract. High-spatial-resolution weather radar observations are of primary relevance for hydrological applications in urban areas. However, when weather radars are located within metropolitan areas, partial beam blockages and clutter by buildings can seriously affect the observations. Standard simulations with simple beam propagation models and digital elevation models (DEMs) are usually not able to evaluate buildings' contribution to partial beam blockages. In recent years airborne laser scanners (ALSs) have evolved to the state-of-the-art technique for topographic data acquisition. Providing small footprint diameters (10-30 cm), ALS data allow accurate reconstruction of buildings and forest canopy heights. Analyzing the three weather C-band radars located in the metropolitan area of Helsinki, Finland, the present study investigates the benefits of using ALS data for quantitative estimations of partial beam blockages. The results obtained applying beam standard propagation models are compared with stratiform 24 h rainfall accumulation to evaluate the effects of partial beam blockages due to constructions and trees. To provide a physical interpretation of the results, the detailed analysis of beam occultations is achieved by open spatial data sets and open-source geographic information systems.

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“…The terms that comprise Eq. (1) are not commonly available from measurements (although there are measurements of eddy covariance at some research sites; Wood et al, 2013) and are therefore estimated by the meteorological preprocessor. A comprehensive description of MPP-FMI is already available in the literature (Karppinen et al, 1997).…”

Section: The Meteorological Preprocessor Mpp-fmimentioning

confidence: 99%

Sensitivity analysis of the meteorological preprocessor MPP-FMI 3.0 using algorithmic differentiation

et al. 2017

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Abstract. The meteorological input parameters for urbanand local-scale dispersion models can be evaluated by preprocessing meteorological observations, using a boundarylayer parameterisation model. This study presents a sensitivity analysis of a meteorological preprocessor model (MPP-FMI) that utilises readily available meteorological data as input. The sensitivity of the preprocessor to meteorological input was analysed using algorithmic differentiation (AD). The AD tool used was TAPENADE. The AD method numerically evaluates the partial derivatives of functions that are implemented in a computer program. In this study, we focus on the evaluation of vertical fluxes in the atmosphere and in particular on the sensitivity of the predicted inverse Obukhov length and friction velocity on the model input parameters. The study shows that the estimated inverse Obukhov length and friction velocity are most sensitive to wind speed and second most sensitive to solar irradiation. The dependency on wind speed is most pronounced at low wind speeds. The presented results have implications for improving the meteorological preprocessing models. AD is shown to be an efficient tool for studying the ranges of sensitivities of the predicted parameters on the model input values quantitatively. A wider use of such advanced sensitivity analysis methods could potentially be very useful in analysing and improving the models used in atmospheric sciences.

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An Overview of the Urban Boundary Layer Atmosphere Network in Helsinki

Cited by 34 publications

References 56 publications

Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

Airborne laser scan data: a valuable tool with which to infer weather radar partial beam blockage in urban environments

Sensitivity analysis of the meteorological preprocessor MPP-FMI 3.0 using algorithmic differentiation

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