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Abstract: In this study, the performance of an irrigation-integrated green roof (GR) system is analyzed through numerical simulations using the vertically-resolved Princeton ROof Model (PROM). The simulations are driven by a 63-day series of summertime meteorological forcing measured at a GR site in Beijing, China. Due to the importance of the medium layer depth of GR systems, its effect on the dynamics of heat and moisture transports and consequently on the thermal performance is first examined under a no-irrigation scenario. The results confirm that the medium layer depth affects heat and moisture transports significantly, but non-monotonic trends emerge. A deeper layer is found to redistribute more water into the bottom section, thus limiting surface evaporation, while a thin layer does not store enough water, dries up fast, and decreases performance too. This indicates that an optimal layer thickness exists somewhere in the middle. Given a fixed medium layer depth, different irrigation scenarios are then investigated. Higher irrigation control limits (i.e. the soil moisture at which irrigation is initiated) enhance the thermal performance of the GR, but this enhancement plateaus at high limits. Based on these findings, a GR (constructed over an un-insulated concrete slab roof in Beijing) is simulated and a simplified operational cost-benefit analysis is performed by comparing the cost of irrigation to that of the energy saved due to lower air-conditioning (AC) requirement when the GR is wetted. The analysis indicates that the irrigated GR system costs are lower than the AC costs for an unirrigated GR. For instance, an irrigated GR system with an area of 100 m2 under an irrigation control limit of 0.3 m3 m−3 will save ￥110 (18 USD) for the chosen 63-day simulation period in Beijing. Therefore, irrigation-integrated GR systems emerge as potentially viable solutions for improving building energy efficiency in a temperate climate. [Copyright &y& Elsevier]

Numerical weather and climate prediction systems necessitate accurate land surface-atmosphere fluxes, whose determination typically replies on a suite of parameterization schemes. The authors present a field investigation over tall grass in a Beijing suburb, where the aerodynamic roughness length ( z0) and zero-plane displacement height ( d) are found to be 0.02 and 0.44 m, respectively (the value of d is close to two-thirds the average grass height during this field experiment). Both z0 and d values are then used as input parameters of an analytic model of flux footprint; the footprint model reveals that eddy-covariance flux measurements are mainly representative of the tall grass surface concerned herein, potential influences from anthropogenic sources in this suburban area notwithstanding. Based on the 'fair weather' data (with an energy balance ratio of 0.89), the authors evaluate four parameterizations of turbulent surface fluxes, namely, a total of three traditional 'iterative' schemes and one 'noniterative' scheme developed recently to reduce computational time. Their performances are intercompared in terms of the estimations of the sensible heat flux and two turbulence components (the friction velocity and temperature scale). In weakly stable to unstable conditions, two schemes are recommended here for their good performance overall; the first scheme stems jointly from the work of Högström and Beljaars and Holtslag, and the second stems from that of Li et al.. For this tall grass surface, the choice of z0/ z0 h = 100 ( z0 h is the thermal roughness length) is more appropriate than another choice of 10, because the former produces comparatively accurate sensible heat flux estimations. [ABSTRACT FROM AUTHOR]