| 10 Mar 2026
Process-based upgrades to the WRF multi-layer green-roof scheme (WRF-MLGR v2.0) and evaluation against field observations
Abstract. Green roofs can moderate urban heat by increasing latent heat flux and reducing sensible heat flux. However, capturing these effects in models depends on accurate representation of key green-roof processes, including substrate heat and moisture transport, soil-vegetation-atmosphere energy and moisture exchanges, interactions with the underlying roof, and drainage. Here we introduce targeted, process-based updates to the green-roof scheme (hereafter, MLGR) within the multi-layer urban canopy model (BEP-BEM) in the WRF mesoscale model to address key limitations in the original formulation. The updates include a non-linear dependence of soil thermal conductivity on moisture, vegetation-modulated surface thermal conductivity, explicit soil-surface evaporation, multi-layer root water uptake for transpiration, and canopy interception with evaporation and dew formation. We evaluate the original and modified MLGR schemes using hourly observations from an extensive sedum roof in London, Canada, for ‘summer’ (1 July–31 August 2014) and ‘fall’ (1 September–31 October 2014) periods. We also analyze 11–18 October 2025, when green roof modules were placed directly on the roof deck – which corresponds to the model’s lower boundary assumption. Following implementation of the process-based improvements, model–measurement agreement for the conductive heat flux is markedly improved: RMSE is reduced from 105.9 to 24.0 W m⁻² in summer and from 94.2 to 24.0 W m⁻² in fall and the model produces more realistic overall green roof energy partitioning. The modified model better captures post-rain increases in latent heat flux (QE) and improves the timing and magnitude of daytime turbulent latent and sensible heat flux peaks (QE and QH). Drainage is reduced relative to the original scheme; however, it remains slightly underestimated during summer and slightly overestimated during fall, and biases persist in surface temperature (warm during the day and cool at night) and in the magnitude and variability of QE. Overall, the revised MLGR physics improves surface-flux realism, and future development should focus on developing a more realistic vegetation canopy submodule.
This study improves a multi-layer green roof scheme coupled to the BEM+BEP urban canopy model within the WRF framework. The model development is clearly described, the validation is robust, and the authors clearly identify the contributions of individual modifications. The work would make a valuable contribution to the urban-climate and building-energy modeling community. I have several comments and suggestions below.
1. The green‑roof soil depth is only 0.03 m per layer. Please discuss potential numerical stability issues under extreme conditions (e.g., prolonged heat waves) when soil moisture may dry out and temperatures may rise rapidly. Have you tested model behavior under such extremes, and are any timestep or scheme adjustments needed?
2. Section 2.2 describes the original model in text. Consider adding a schematic or flow diagram that contrasts the original scheme and the modified scheme to make the differences clearer (e.g., layer structure, heat flux pathways, and where parameter changes are applied).
3. In Sections 2.3.1 and 2.3.2, please quantify how much the soil and vegetation thermal conductivities were changed relative to the original model. Are the modified values still within physically reasonable/observed ranges? If possible, include a table or figure showing the original vs. modified conductivity values and their sources or justification.
4. Table 1 and Fig. 1 show degraded performance in Ts prediction across all cases. Please discuss possible causes. Clarify which surface temperature is reported (soil surface, vegetation canopy surface, or some aggregated surface skin temperature). You mention two thermal conductivity calculations—how do those relate to the reported Ts, and might they explain the degradation? Consider adding separate diagnostics for soil-surface and vegetation-surface temperatures if available.
5. The resolution of all figures is quite low. Please replace figures with higher-resolution versions and ensure axes, legends, and labels are clearly legible.