Calibration process and parametrization of tropical plants using ENVI-met V4 – Sao Paulo case study

ABSTRACT

This work aims to improve the process of calibration of ENVI-met model based on air temperature in both built-up and vegetated areas, considering various parameters and models of trees. Field measurements were carried out in the city of Sao Paulo to monitor representative hot weather conditions inside an urban park and in a non-vegetated area nearby. The leaf density was calculated using a non-destructive indirect method with hemispherical photographs analysed in Can-Eye 6.1 model. Based on LAI measurements and on the characteristics of tropical species, four typologies of trees were created with different leaf distribution inside the crown. After a calibration process in which modelling parameters were tested and several simulations were run, a high agreement between simulation results and on-site measurements with an RMSE of 0.7 K could be achieved.

KEYWORDS:

• Urban microclimate
• urban vegetation
• leaf area index
• calibration process
• tree parameters

Acknowledgements

The authors thank to Prof. Dr. Humberto R. da Rocha of the Institute of Astronomy, Geophysics and Atmospheric Sciences IAG of the University of São Paulo for the soil data and Prof. Dr. Amauri Pereira de Oliveira, from Micrometeorology Laboratory (LabMicro) at IAG USP, for providing climate data for full forcing simulation. We also thank LABAUT staff for assistance in field surveys; Municipal Secretariat for Environment (SVMA) for authorization and support in Trianon Park studies; and Tim Kropp from Environmental Modelling Group (EMG) at Johannes Gutenberg-Universität Mainz for the assistance in 3D modelling of Trianon area.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Data provided by LabMicro from the Institute of Astronomy, Geophysics and Atmospheric Sciences – IAG at University of Sao Paulo – USP.

2. Available at: http://weather.uwyo.edu/upperair/sounding.html. Accessed January 2018.

Additional information

Funding

This work was supported by the Sao Paulo Research Foundation (FAPESP) grants number [#2014/50978-0], [#2016/01204-7] and [#2016/02825-5]; National Council for Scientific and Technological Development CNPq, Productivity grant [309669/2015-4].