Using a three-dimensional cloud ensemble model, a systematic exploration is undertaken of radiative-convective equilibrium states as a function of the structure and magnitude of an imposed background flow with vertical shear. In such simulations, mesoscale organization appears naturally, independent of the particulars of the initial condition. As the magnitude of an imposed low-level shear increases, the convection becomes increasingly organized in lines or arcs, propagating broadly downshear, as predicted by earlier work. When the shear is very strong, the convection tends to organize into lines at an angle to the shear, such that the linenormal component is not far from its theoretical optimal value. Midlevel shear favors shear-parallel lines, but if it occurs in conjunction with sufficiently strong low-level shear, the convection can become very strongly organized into lines or arcs generally orthogonal to the low-level shear. Optimal organization occurs when the depth of the shear layer is comparable to that of the cold pools associated with the convective downdrafts. As the vertical shear is increased, the domain-averaged convective available potential energy (CAPE) at first increases but then decreases at stronger shear values. Associated with these changes, the lower to middle troposphere becomes drier at low shear values and more humid when the shear is strong. This relationship between humidity and CAPE is broadly consistent with recently developed CAPE theories. The authors also confirm previous work that shows that the transport of momentum by the simulated convection, though usually down the gradient of the background flow, is nonlocal in character. Finally, some simulations are performed with an imposed hodograph taken from a tropical cyclone. Convective arcs form with an orientation similar to observed outer spiral bands, but the simulated bands propagate more rapidly than observed, perhaps because of a dry middle troposphere in the simulations.
The performance of the Weather Research and Forecasting (WRF) Model is evaluated in predicting the meteorological conditions over a complex open-pit mining facility in northern Canada in support of more accurate operational reporting of area-fugitive greenhouse gas emission fluxes from such facilities. WRF is studied in a series of sensitivity tests by varying topography, land use, and horizontal and vertical grid spacings to arrive at optimum configurations for reducing modeling biases in comparison with field meteorological observations. Overall, WRF shows a better performance when accounting for the mine topography and modified land use. As a result, the model biases reduce from 1.10 to 0.08 m s−1, from 1.04 to 0.50 m s−1, from 0.98 to 0.32 K, and from 45.7 to 17.3 W m−2, for near-surface wind speed, boundary layer wind speed, near-surface potential temperature, and turbulent sensible heat flux, respectively. Refining the model horizontal and vertical grid spacings results in bias reductions from 3.31 to 0.08 and from 0.80 to −0.11 m s−1 for near-surface and boundary layer wind speeds, respectively. The simulation results also agree with previous observations of meteorological effects on enclosed Earth depressions, characterized by formation of a cool pool of air, reduced wind speeds, and horizontal wind circulations at the bottom of the depression under thermally stable conditions. The results suggest that such configurations for WRF are necessary to arrive at more accurate meteorological predictions over complex open-pit mining terrains with similar features.
Greenhouse Gas (GHG) emissions pose a global climate challenge and the mining sector is a large contributor. Diurnal and seasonal variations of area-fugitive methane advective flux, released from an open-pit mine and a tailings pond, from a facility in northern Canada, were simulated in spring 2018 and winter 2019, using the Weather Research and Forecasting (WRF) model. The methane mixing ratio boundary conditions for the WRF model were obtained from the in-situ field measurements, using Los Gatos Research Ultra-Portable Greenhouse Gas Analyzers (LGRs), placed in various locations surrounding the mine pit and a tailings pond. The simulated advective flux was influenced by local and synoptic weather conditions in spring and winter, respectively. Overall, the average total advective flux in the spring was greater than that in the winter by 36% and 75%, for the mine and pond, respectively. Diurnal variations of flux were notable in the spring, characterized by low flux during thermally stable (nighttime) and high flux during thermally unstable (daytime) conditions. The model predictions of the methane mixing ratio were in reasonable agreement with limited aircraft observations (R2=0.68). The findings shed new light in understanding the area-fugitive advective flux from complex terrains and call for more rigorous observations in support of the findings.
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