The “teapot in a city”: A paradigm shift in urban climate modeling

Science advances - Tập 8 Số 27 - 2022
Najda Villefranque1,2,3, F. Hourdin2, Louis d’Alençon2, Stéphane Blanco3, Oliviér Boucher2, Cyril Caliot4, Christophe Coustet5, Jérémi Dauchet6, Mouna El-Hafi7, Vincent Eymet5, Olivier Farges8, Vincent Forest5, Richard Fournier3, Jacques Gautrais9, Valéry Masson1, Benjamin Piaud5, Robert Schoetter1
1CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
2LMD/IPSL/SU, CNRS, Paris 75005, France.
3Laplace, INP/Université de Toulouse/CNRS, Toulouse, France.
4LMAP, CNRS, UPPA, E25, Anglet, France.
5Méso-Star, Longages, France.
6Institut Pascal, Université Clermont Auvergne, Clermont Auvergne INP, CNRS, Clermont-Ferrand, France.
7Centre RAPSODEE, Université de Toulouse, Mines Albi, UMR CNRS 5302, Campus Jarlard, Albi, France.
8LEMTA, Université de Lorraine, CNRS, Nancy, France
9CRCA, CBI, Université de Toulouse, CNRS, Toulouse, France.

Tóm tắt

Urban areas are a high-stake target of climate change mitigation and adaptation measures. To understand, predict, and improve the energy performance of cities, the scientific community develops numerical models that describe how they interact with the atmosphere through heat and moisture exchanges at all scales. In this review, we present recent advances that are at the origin of last decade’s revolution in computer graphics, and recent breakthroughs in statistical physics that extend well-established path-integral formulations to nonlinear coupled models. We argue that this rare conjunction of scientific advances in mathematics, physics, computer, and engineering sciences opens promising avenues for urban climate modeling and illustrate this with coupled heat transfer simulations in complex urban geometries under complex atmospheric conditions. We highlight the potential of these approaches beyond urban climate modeling for the necessary appropriation of the issues at the heart of the energy transition by societies.

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Tài liệu tham khảo

10.1016/0004-6981(73)90140-6

10.1002/joc.859

10.1007/s10584-008-9441-x

10.1016/j.envpol.2011.01.016

10.1111/j.1475-4959.2007.232_3.x

10.1002/joc.3415

UN World urbanization prospects—the 2018 revision (Technical Report ST/ESA/SER.A/420 Department of Economic and Social Affairs 2019).

10.1016/j.uclim.2020.100623

10.1016/j.uclim.2017.05.004

10.1016/j.enbuild.2016.09.067

10.1016/j.solener.2016.12.006

10.1016/j.scitotenv.2017.01.158

10.1146/annurev-environ-012320-083623

T. R. Oke G. Mills A. Christen J. A. Voogt Urban Climates (Cambridge Univ. Press 2017).

10.1007/s10113-013-0499-2

10.1023/A:1016099921195

10.1023/A:1002463829265

10.1016/S0306-2619(03)00009-6

10.1007/s00704-009-0142-9

10.5194/gmd-5-433-2012

10.1016/j.uclim.2017.10.006

10.1016/S1364-8152(98)00042-5

10.5194/gmd-13-1335-2020

10.1016/S0378-7788(00)00114-6

E. Vorger “Étude de l’influence du comportement des occupants sur la performance énergétique des bâtiments ” thesis École nationale supérieure des mines de Paris (2014).

D. Robinson F. Haldi P. Leroux D. Perez A. Rasheed U. Wilke CITYSIM: Comprehensive Micro-Simulation of Resource Flows for Sustainable Urban Planning Building Simulation 2009: Proceedings of the Eleventh International IBPSA Conference (Glasgow Scotland 2009) (Glasgow 2009) pp. 1083–1090.

J. Vinet “Contribution à la modélisation thermo-aéraulique du microclimat urbain. Caractérisation de l’impact de l’eau et de la végétation sur les conditions de confort en espaces extérieurs ” thesis Université de Nantes (2000).

10.1016/S0360-1323(02)00049-5

10.1016/j.envsoft.2017.09.020

E. Haines Spline surface rendering and what’s wrong with octrees Ray Tracing News 1 article 4 (1988); https://graphics.stanford.edu/pub/Graphics/RTNews/html/rtnews1b.html#art4.

10.1145/2601097.2601199

R. P. Feynman Feynman’s Thesis—A New Approach To Quantum Theory (World Scientific 2005) pp. 71–109.

M. Kac On some connections between probability theory and differential and integral equations in Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability J. Neyman Ed. (University of California Press 1951) pp. 189–215.

K. K. Sabelfeld Monte Carlo Methods in Boundary Value Problems (Springer-Verlag 1991).

10.1080/01621459.1949.10483310

I. Lux L. Koblinger Monte Carlo Particle Transport Methods: Neutron and Photon Calculations (CRC Press 1991).

R. Farnoosh, M. Ebrahimi, Monte Carlo method for solving Fredholm integral equations of the second kind. Appl. Math Comput. 195, 309–315 (2008).

A. Doucet, A. M. Johansen, V. B. Tadić, On solving integral equations using Markov chain Monte Carlo methods. Appl. Math Comput. 216, 2869–2880 (2010).

P. Del Moral F.-K. Formulae S. Asmussen J. Gani P. Jagers T. Kurtz Probability and Its Applications (Springer 2004) pp. 47–93.

K. Itô H. McKean Diffusion Processes and Their Sample Paths: Reprint of the 1974 Edition (Springer 1996).

10.1080/00029890.1947.11990189

B. Lapeyre É. Pardoux E. Pardoux R. Sentis Introduction to Monte Carlo Methods for Transport and Diffusion Equations Vol. 6 (Oxford University Press on Demand 2003).

10.1214/aoms/1177728169

10.1115/1.3614330

10.1515/mcma-2019-2032

10.1145/15886.15902

10.1145/964965.808590

E. Veach “Robust Monte Carlo methods for light transport simulation ” thesis Stanford University Stanford CA (1998).

M. Pharr G. Humphreys Physically Based Rendering Third Edition: From Theory To Implementation (Morgan Kaufmann ed. 3 2018).

10.1145/360349.360354

10.1145/15886.15916

A. S. Glassner An Introduction to Ray Tracing (Academic Press Ltd. 1989).

M. Raab D. Seibert A. Keller in Monte Carlo and Quasi-Monte Carlo Methods 2006 A. Keller S. Heinrich H. Niederreiter Eds. (Springer 2006) pp. 591–605.

10.1016/j.jqsrt.2013.04.001

10.1016/j.jqsrt.2013.06.004

10.1016/j.jqsrt.2015.10.016

10.1016/j.jqsrt.2017.03.026

10.1016/j.jqsrt.2021.107725

10.1111/cgf.13383

10.1145/3306346.3323025

10.1145/3355089.3356559

10.1029/2018MS001602

R. Fournier, S. Blanco, V. Eymet, E. Mouna, C. Spiesser, Radiative, conductive and convective heat-transfers in a single Monte Carlo algorithm. J. Phys. 676, 012007 (2016).

V. Gattepaille “Modèles multi-échelles de photobioréacteurs solaires et méthode de Monte Carlo ” thesis Université Clermont Auvergne (2020).

10.1063/1.1710976

10.1016/j.jqsrt.2020.107402

10.1038/s41598-018-31574-4

10.1103/PhysRevE.105.025305

J.-M. Tregan “Thermique non-linéaire et Monte-Carlo ” thesis Université Toulouse 3 Paul Sabatier (2020).

10.1016/j.solener.2014.12.027

10.1038/s41467-021-26370-0

10.1029/2020MS002217

10.1029/2020MS002225

W. C. Skamarock J. B. Klemp J. Dudhia D. O. Gill D. Barker M. G. Duda J. G. Powers A description of the Advanced Research WRF version 3 (NCAR/TN-475+STR University Corporation for Atmospheric 2008).

10.5194/gmd-11-1929-2018

10.1016/j.jclepro.2018.10.086

10.1016/j.isprsjprs.2014.05.005

10.1007/s00585-997-0090-6

10.1256/003590002320373210

10.1029/2019MS002010