Process-based evaluation of green roof models for assessment of heat mitigation efficacy in WRF (v4.3.1) and EnergyPlus (v8.6.0)
- 1Western University (London, Canada)
Abstract
Green roofs mitigate urban heat, but to fully assess their impact, green roof models must be integrated into urban climate models, where they provide critical surface boundary conditions. Ensuring their reliability requires evaluation, yet such efforts remain limited in the literature. This study addresses that gap by evaluating two configurations of EcoRoof, the green roof module from EnergyPlus (ER o for the original version of the model, and ER m for a modified version), and a multilayer green roof parametrization for WRF (WRF-MLGR) (Heusinger et al., 2018; Sailor, 2008; Zonato et al., 2021). These models were tested against field observations from a monitored green roof in London, Ontario, focusing on latent heat flux ( Q e ), surface temperature ( T surf ), soil heat flux ( Q g ) and substrate water content (SWC). Model performance varied by variable. The two EcoRoof versions showed similar performance, with mean RMSE across study periods of approximately 56–60 W m ⁻² for Q e , 3–4 °C for T surf , 22 W m ⁻² for Q g , and 0.03 m ³ m ⁻³ for SWC. Performance for Q e was comparable across models; however, WRF-MLGR exhibited much larger errors for Q g (with mean RMSE exceeding 100 W m ⁻² ) and SWC (0.06 m ³ m ⁻³ ), along with higher T surf deviations (∼5 °C). Overall, EcoRoof provided a more consistent representation of the daytime energy balance, whereas WRF-MLGR showed structural biases in surface heating. These findings highlight the importance of process-level evaluation for urban climate applications and underscore the need for continued model development to address the structural limitations in green roof parametrizations.
Versions
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BibTeX
@article{mendoza2026processbased,
title = {{Process-based evaluation of green roof models for assessment of heat mitigation efficacy in WRF (v4.3.1) and EnergyPlus (v8.6.0)}},
author = {Maria Martinez Mendoza and Alireza Saeedi and James A. Voogt and E. Scott Krayenhoff},
journal = {Geoscientific Model Development},
year = {2026},
month = oct,
doi = {10.5194/gmd-19-9729-2026},
url = {https://gmd.copernicus.org/articles/19/9729/2026/},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Process-based evaluation of green roof models for assessment of heat mitigation efficacy in WRF (v4.3.1) and EnergyPlus (v8.6.0)
AU - Maria Martinez Mendoza
AU - Alireza Saeedi
AU - James A. Voogt
AU - E. Scott Krayenhoff
PY - 2026
DA - 2026/10/12
JO - Geoscientific Model Development
DO - 10.5194/gmd-19-9729-2026
UR - https://gmd.copernicus.org/articles/19/9729/2026/
AB - Green roofs mitigate urban heat, but to fully assess their impact, green roof models must be integrated into urban climate models, where they provide critical surface boundary conditions. Ensuring their reliability requires evaluation, yet such efforts remain limited in the literature. This study addresses that gap by evaluating two configurations of EcoRoof, the green roof module from EnergyPlus (ER o for the original version of the model, and ER m for a modified version), and a multilayer green roof parametrization for WRF (WRF-MLGR) (Heusinger et al., 2018; Sailor, 2008; Zonato et al., 2021). These models were tested against field observations from a monitored green roof in London, Ontario, focusing on latent heat flux ( Q e ), surface temperature ( T surf ), soil heat flux ( Q g ) and substrate water content (SWC). Model performance varied by variable. The two EcoRoof versions showed similar performance, with mean RMSE across study periods of approximately 56–60 W m ⁻² for Q e , 3–4 °C for T surf , 22 W m ⁻² for Q g , and 0.03 m ³ m ⁻³ for SWC. Performance for Q e was comparable across models; however, WRF-MLGR exhibited much larger errors for Q g (with mean RMSE exceeding 100 W m ⁻² ) and SWC (0.06 m ³ m ⁻³ ), along with higher T surf deviations (∼5 °C). Overall, EcoRoof provided a more consistent representation of the daytime energy balance, whereas WRF-MLGR showed structural biases in surface heating. These findings highlight the importance of process-level evaluation for urban climate applications and underscore the need for continued model development to address the structural limitations in green roof parametrizations.
SN - 1991-9603
ER -