A new methodology to propagate uncertainties from regional climate models to urban impact model : feasibility study
- Author
- François Duchêne, Bert Van Schaeybroeck (UGent) , Steven Caluwaerts (UGent) , Andy Delcloo (UGent) , Rozemien De Troch (UGent) , Rafiq Hamdi (UGent) and Piet Termonia (UGent)
- Organization
- Abstract
- The demand from the city planners and stakeholders concerning climate change impact on cities is increasing. Due to the global warming, cities, which are already more vulnerable, will experience an increasing number of extreme events such as heat waves. However, the information about long-term climate projections are extracted from global or regional climate models that are not conducted at city-scale resolutions. Additional simulations are therefore required. The computational cost of running a high-resolution regional climate model (RCM) coupled with a land surface model (LSM) to get the full atmospheric feedback from cities is extremely high. Moreover, an ensemble of simulations is required in order to estimate the uncertainties in part related to urban projections. Using a LSM in standalone mode is a cheaper solution. However, to downscale climate simulations from a RCM without urban parameterisation to a LSM, an extra step is required in order to present accurate results to compensate for the lack of atmosphere-land feedback. A simple and relatively fast statistical–dynamical downscaling approach is developed to fulfil this step and correct the LSM forcing. In this study, a description and a validation of the methodology is presented. The RCM used is ALARO, and the LSM is SURFEX. They are run over the Brussels Capital Region and forced with ERA-Interim reanalysis during the summers of 1981–2010. The validation is performed for the urban heat island.
Downloads
-
(...).pdf
- full text (Published version)
- |
- UGent only
- |
- |
- 138.02 KB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8740467
- MLA
- Duchêne, François, et al. “A New Methodology to Propagate Uncertainties from Regional Climate Models to Urban Impact Model : Feasibility Study.” ITM 2019: Air Pollution Modeling and Its Application XXVII, edited by Clemens Mensink and Volker Matthias, Springer, 2021, pp. 325–29, doi:10.1007/978-3-662-63760-9_47.
- APA
- Duchêne, F., Van Schaeybroeck, B., Caluwaerts, S., Delcloo, A., De Troch, R., Hamdi, R., & Termonia, P. (2021). A new methodology to propagate uncertainties from regional climate models to urban impact model : feasibility study. In C. Mensink & V. Matthias (Eds.), ITM 2019: Air Pollution Modeling and its Application XXVII (pp. 325–329). https://doi.org/10.1007/978-3-662-63760-9_47
- Chicago author-date
- Duchêne, François, Bert Van Schaeybroeck, Steven Caluwaerts, Andy Delcloo, Rozemien De Troch, Rafiq Hamdi, and Piet Termonia. 2021. “A New Methodology to Propagate Uncertainties from Regional Climate Models to Urban Impact Model : Feasibility Study.” In ITM 2019: Air Pollution Modeling and Its Application XXVII, edited by Clemens Mensink and Volker Matthias, 325–29. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-662-63760-9_47.
- Chicago author-date (all authors)
- Duchêne, François, Bert Van Schaeybroeck, Steven Caluwaerts, Andy Delcloo, Rozemien De Troch, Rafiq Hamdi, and Piet Termonia. 2021. “A New Methodology to Propagate Uncertainties from Regional Climate Models to Urban Impact Model : Feasibility Study.” In ITM 2019: Air Pollution Modeling and Its Application XXVII, ed by. Clemens Mensink and Volker Matthias, 325–329. Berlin, Heidelberg: Springer. doi:10.1007/978-3-662-63760-9_47.
- Vancouver
- 1.Duchêne F, Van Schaeybroeck B, Caluwaerts S, Delcloo A, De Troch R, Hamdi R, et al. A new methodology to propagate uncertainties from regional climate models to urban impact model : feasibility study. In: Mensink C, Matthias V, editors. ITM 2019: Air Pollution Modeling and its Application XXVII. Berlin, Heidelberg: Springer; 2021. p. 325–9.
- IEEE
- [1]F. Duchêne et al., “A new methodology to propagate uncertainties from regional climate models to urban impact model : feasibility study,” in ITM 2019: Air Pollution Modeling and its Application XXVII, Hamburg, Germany, 2021, pp. 325–329.
@inproceedings{8740467,
abstract = {{The demand from the city planners and stakeholders concerning climate change impact on cities is increasing. Due to the global warming, cities, which are already more vulnerable, will experience an increasing number of extreme events such as heat waves. However, the information about long-term climate projections are extracted from global or regional climate models that are not conducted at city-scale resolutions. Additional simulations are therefore required. The computational cost of running a high-resolution regional climate model (RCM) coupled with a land surface model (LSM) to get the full atmospheric feedback from cities is extremely high. Moreover, an ensemble of simulations is required in order to estimate the uncertainties in part related to urban projections. Using a LSM in standalone mode is a cheaper solution. However, to downscale climate simulations from a RCM without urban parameterisation to a LSM, an extra step is required in order to present accurate results to compensate for the lack of atmosphere-land feedback. A simple and relatively fast statistical–dynamical downscaling approach is developed to fulfil this step and correct the LSM forcing. In this study, a description and a validation of the methodology is presented. The RCM used is ALARO, and the LSM is SURFEX. They are run over the Brussels Capital Region and forced with ERA-Interim reanalysis during the summers of 1981–2010. The validation is performed for the urban heat island.}},
author = {{Duchêne, François and Van Schaeybroeck, Bert and Caluwaerts, Steven and Delcloo, Andy and De Troch, Rozemien and Hamdi, Rafiq and Termonia, Piet}},
booktitle = {{ITM 2019: Air Pollution Modeling and its Application XXVII}},
editor = {{Mensink, Clemens and Matthias, Volker}},
isbn = {{9783662637593}},
issn = {{2213-8684}},
language = {{eng}},
location = {{Hamburg, Germany}},
pages = {{325--329}},
publisher = {{Springer}},
title = {{A new methodology to propagate uncertainties from regional climate models to urban impact model : feasibility study}},
url = {{http://doi.org/10.1007/978-3-662-63760-9_47}},
year = {{2021}},
}
- Altmetric
- View in Altmetric