2015
DOI: 10.3390/cli3030542
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Lattice Wind Description and Characterization of Mexico City Local Wind Events in the 2001–2006 Period

Abstract: Urban transformation and expansion in Mexico City continuously affect its urban morphology, and therefore the modes of wind circulation inside it and their occurrence probabilities. Knowledge on these topics is an important issue for urban planning and for other urban studies, such as air quality assessment. In this paper, using a lattice wind model at a meso-β scale, we develop a simple description and characterization of Mexico City local wind events that occurred during the period 2001-2006, including an es… Show more

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Cited by 4 publications
(7 citation statements)
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“…The set of the couples (U(s,h), V(s,h)) will be denoted by H*; (2) A 9 × 9 calculation grid G was defined over the spatial domain, and a Kriging technique of vector interpolation (boundary-constrained) was applied to H* to estimate the wind velocity components u(i,j,h) and v(i,j,h) at the nodes (i,j) of G for each h; (3) These estimations were used to calculate the wind velocity components (u, v), the wind divergence γ, and the wind vorticity ω at the cells of the 8 × 8 lattice, L, associated to the calculation grid G. At each cell (p,q) of L, the estimation of the parameters u(p,q), v(p,q), γ(p,q) and ω(p,q) was carried out using the values of (u,v) at the four nodes located at the cell vertexes. Here, the 2D numerical definitions [25,28] of divergence and vorticity were used. The set {(u(p,q,h), v(p,q,h), γ(p,q,h), ω(p,q,h)) | (p,q) ∈ L } will be denoted by W(h).…”
Section: The Mexico City Model Wind Eventsmentioning
confidence: 99%
See 2 more Smart Citations
“…The set of the couples (U(s,h), V(s,h)) will be denoted by H*; (2) A 9 × 9 calculation grid G was defined over the spatial domain, and a Kriging technique of vector interpolation (boundary-constrained) was applied to H* to estimate the wind velocity components u(i,j,h) and v(i,j,h) at the nodes (i,j) of G for each h; (3) These estimations were used to calculate the wind velocity components (u, v), the wind divergence γ, and the wind vorticity ω at the cells of the 8 × 8 lattice, L, associated to the calculation grid G. At each cell (p,q) of L, the estimation of the parameters u(p,q), v(p,q), γ(p,q) and ω(p,q) was carried out using the values of (u,v) at the four nodes located at the cell vertexes. Here, the 2D numerical definitions [25,28] of divergence and vorticity were used. The set {(u(p,q,h), v(p,q,h), γ(p,q,h), ω(p,q,h)) | (p,q) ∈ L } will be denoted by W(h).…”
Section: The Mexico City Model Wind Eventsmentioning
confidence: 99%
“…Positions of the REDMET stations are shown in Figure 2 as small solid squares. TLA 68 97 96 95 92 97 91 XAL 95 91 95 96 96 82 93 MER 92 94 90 92 95 96 93 PED 92 93 96 96 95 94 95 CES 81 92 92 93 91 92 90 PLA 87 95 95 94 94 94 93 HAN 92 85 92 93 96 18 79 VIF 68 89 94 96 95 96 90 CUA 84 86 97 99 96 75 89 TPN 63 76 43 0 34 55 45 CHA 85 87 86 89 93 91 89 TAH 94 91 93 98 97 31 84 A simple illustration of wind circulation in a given region is supplied by the Wind Direction State (WDS) concept [3,12,13,25] as long as the 4-cell lattice wind model is used. In this case, Mexico City is modeled as a rectangular 2 × 2 lattice domain, where each cell represents a quadrant of the city.…”
Section: The Mexico City Model Wind Eventsmentioning
confidence: 99%
See 1 more Smart Citation
“…In a first step, we represented the study domain (D) as a square grid G with 289 nodes Grs, where the subscripts r = 1, 2, …, 17 and s = 1, 2, …, 17 vary along with the West-East (WE) and South-North (SN) directions, respectively. Using the wind speed and wind direction data supplied by the REDMET stations, and the NO2, O3, PM10, and SO2 concentration data supplied by the RAMA stations, we estimated (using Kriging interpolation) the horizontal components of the flow vector field at each grid node Grs and time t, ( , , ) ( , , ) ( , , ) The estimations, for each pollutant, of the flow vector components at the grid nodes Grs, allow calculating (numerically) the spatial averages of the components of the pollutant-flow vector and its gradients at the cells Cij of the lattice L using their 2D discrete definitions in terms of centered finite differences [24,30]. For a given pollutant, we will denote the flow vector components at Cij by ( , , )…”
Section: Study Databasementioning
confidence: 99%
“…However, most of the studies have been performed on an episode-by-episode basis and using small data sets obtained from short-term experimental campaigns with different approaches [14][15][16][17][18][19][20][21]. Some of the main exceptions are the first long-term micrometeorological campaign carried out by Salcido et al [11] in this region during 2001, and the studies of Klaus et al [22], de Foy et al [23], Salcido et al [24], and Carreón-Sierra et al [25], which were carried out using data provided by the atmospheric monitoring network of Mexico City (SIMAT: Figures 2 and Figure 3 illustrate the study domain and the spatial distributions of the stations of the monitoring networks of SIMAT for wind, nitrogen dioxide, ozone, PM10, and sulfur dioxide. These monitoring networks provided the 1-hour average values of the meteorological and air quality variables systematically and made them publicly available through its web site [26].…”
Section: Introductionmentioning
confidence: 99%