Articles | Volume 17, issue 12
https://doi.org/10.5194/gmd-17-5023-2024
https://doi.org/10.5194/gmd-17-5023-2024
Model description paper
 | 
27 Jun 2024
Model description paper |  | 27 Jun 2024

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago

Related authors

A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024,https://doi.org/10.5194/gmd-17-2525-2024, 2024
Short summary
A global map of local climate zones to support earth system modelling and urban-scale environmental science
Matthias Demuzere, Jonas Kittner, Alberto Martilli, Gerald Mills, Christian Moede, Iain D. Stewart, Jasper van Vliet, and Benjamin Bechtel
Earth Syst. Sci. Data, 14, 3835–3873, https://doi.org/10.5194/essd-14-3835-2022,https://doi.org/10.5194/essd-14-3835-2022, 2022
Short summary
A one-dimensional model of turbulent flow through “urban” canopies (MLUCM v2.0): updates based on large-eddy simulation
Negin Nazarian, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 13, 937–953, https://doi.org/10.5194/gmd-13-937-2020,https://doi.org/10.5194/gmd-13-937-2020, 2020
Short summary
CFD modeling of reactive pollutant dispersion in simplified urban configurations with different chemical mechanisms
Beatriz Sanchez, Jose-Luis Santiago, Alberto Martilli, Magdalena Palacios, and Frank Kirchner
Atmos. Chem. Phys., 16, 12143–12157, https://doi.org/10.5194/acp-16-12143-2016,https://doi.org/10.5194/acp-16-12143-2016, 2016
Short summary

Related subject area

Atmospheric sciences
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024,https://doi.org/10.5194/gmd-17-6571-2024, 2024
Short summary
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024,https://doi.org/10.5194/gmd-17-6489-2024, 2024
Short summary
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024,https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024,https://doi.org/10.5194/gmd-17-6379-2024, 2024
Short summary
Impact of ITCZ width on global climate: ITCZ-MIP
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024,https://doi.org/10.5194/gmd-17-6365-2024, 2024
Short summary

Cited articles

Borge, R., Santiago, J. L., de la Paz, D., Martín, F., Domingo, J., Valdés, C., Sánchez B., Rivas, E., Rozas, M. T., Lázaro, S., Pérez, J., and Fernández, A.: Application of a short term air quality action plan in Madrid (Spain) under a high-pollution episode-Part II: Assessment from multi-scale modelling, Sci. Total Environ., 635, 1574–1584, https://doi.org/10.1016/j.scitotenv.2018.04.323, 2018. 
Bougeault, P. and Lacarrere, P.: Parameterization of Orography-Induced Turbulence in a Mesobeta–Scale Model, Mon. Weather Rev., 117, 1872–1890, https://doi.org/10.1175/1520-0493(1989)117<1872:POOITI>2.0.CO;2, 1989. 
Broadbent, A. M., Krayenhoff, E. S., and Georgescu, M.: The motley drivers of heat and cold exposure in 21st century US cities, P. Natl. Acad. Sci. USA, 117, 21108–21117, https://doi.org/10.1073/pnas.2005492117, 2020. 
Brousse, O., Martilli, A., Foley, M., Mills, G., and Bechtel, B.: WUDAPT, an efficient land use producing data tool for mesoscale models? Integration of urban LCZ in WRF over Madrid, Urban Clim., 17, 116–134, https://doi.org/10.1016/j.uclim.2016.04.001, 2016. 
Brown, M. J., Lawson, R. E., DeCroix, D. S., and Lee, R. L.: Comparison of centerline velocity measurements obtained around 2D and 3D building arrays in a wind tunnel, Int. 40 Soc. Environ. Hydraulics, Tempe, AZ, 5, 495, OSTI ID: 783425, https://digital.library.unt.edu/ark:/67531/metadc716934/m2/1/high_res_d/783425.pdf (last access: 25 June 2024), 2001 
Download
Short summary
Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.