City-descriptive input data for urban climate models: Model requirements, data sources and challenges

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Valéry Masson
  • Wieke Heldens
  • Erwan Bocher
  • Marion Bonhomme
  • Bénédicte Bucher
  • Cornelia Burmeister
  • Cécile de Munck
  • Thomas Esch
  • Julia Hidalgo
  • Farah Kanani-Sühring
  • Yu Ting Kwok
  • Aude Lemonsu
  • Jean Pierre Lévy
  • Björn Maronga
  • Dirk Pavlik
  • Gwendall Petit
  • Linda See
  • Robert Schoetter
  • Nathalie Tornay
  • Athanasios Votsis
  • Julian Zeidler

Externe Organisationen

  • Université de Toulouse
  • Centre national de la recherche scientifique (CNRS)
  • Université Paris-Est Créteil Val-de-Marne (UPEC)
  • The Chinese University of Hong Kong
  • École des Ponts ParisTech
  • International Institute for Applied Systems Analysis, Laxenburg
  • Finnish Meteorological Institute
  • Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) Standort Oberpfaffenhofen
  • Architectural Research Laboratory (LRA)
  • GEO-NET Umweltconsulting GmbH
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Aufsatznummer100536
FachzeitschriftUrban Climate
Jahrgang31
Frühes Online-Datum19 Nov. 2019
PublikationsstatusVeröffentlicht - März 2020

Abstract

Cities are particularly vulnerable to meteorological hazards because of the concentration of population, goods, capital stock and infrastructure. Urban climate services require multi-disciplinary and multi-sectorial approaches and new paradigms in urban climate modelling. This paper classifies the required urban input data for both mesoscale state-of-the-art Urban Canopy Models (UCMs) and microscale Obstacle Resolving Models (ORM) into five categories and reviews the ways in which they can be obtained. The first two categories are (1) land cover, and (2) building morphology. These govern the main interactions between the city and the urban climate and the Urban Heat Island. Interdependence between morphological parameters and UCM geometric hypotheses are discussed. Building height, plan and wall area densities are recommended as the main input variables for UCMs, whereas ORMs require 3D building data. Recently, three other categories of urban data became relevant for finer urban studies and adaptation to climate change: (3) building design and architecture, (4) building use, anthropogenic heat and socio-economic data, and (5) urban vegetation data. Several methods for acquiring spatial information are reviewed, including remote sensing, geographic information system (GIS) processing from administrative cadasters, expert knowledge and crowdsourcing. Data availability, data harmonization, costs/efficiency trade-offs and future challenges are then discussed.

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City-descriptive input data for urban climate models: Model requirements, data sources and challenges. / Masson, Valéry; Heldens, Wieke; Bocher, Erwan et al.
in: Urban Climate, Jahrgang 31, 100536, 03.2020.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Masson, V, Heldens, W, Bocher, E, Bonhomme, M, Bucher, B, Burmeister, C, de Munck, C, Esch, T, Hidalgo, J, Kanani-Sühring, F, Kwok, YT, Lemonsu, A, Lévy, JP, Maronga, B, Pavlik, D, Petit, G, See, L, Schoetter, R, Tornay, N, Votsis, A & Zeidler, J 2020, 'City-descriptive input data for urban climate models: Model requirements, data sources and challenges', Urban Climate, Jg. 31, 100536. https://doi.org/10.1016/j.uclim.2019.100536
Masson, V., Heldens, W., Bocher, E., Bonhomme, M., Bucher, B., Burmeister, C., de Munck, C., Esch, T., Hidalgo, J., Kanani-Sühring, F., Kwok, Y. T., Lemonsu, A., Lévy, J. P., Maronga, B., Pavlik, D., Petit, G., See, L., Schoetter, R., Tornay, N., ... Zeidler, J. (2020). City-descriptive input data for urban climate models: Model requirements, data sources and challenges. Urban Climate, 31, Artikel 100536. https://doi.org/10.1016/j.uclim.2019.100536
Masson V, Heldens W, Bocher E, Bonhomme M, Bucher B, Burmeister C et al. City-descriptive input data for urban climate models: Model requirements, data sources and challenges. Urban Climate. 2020 Mär;31:100536. Epub 2019 Nov 19. doi: 10.1016/j.uclim.2019.100536
Masson, Valéry ; Heldens, Wieke ; Bocher, Erwan et al. / City-descriptive input data for urban climate models : Model requirements, data sources and challenges. in: Urban Climate. 2020 ; Jahrgang 31.
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title = "City-descriptive input data for urban climate models: Model requirements, data sources and challenges",
abstract = "Cities are particularly vulnerable to meteorological hazards because of the concentration of population, goods, capital stock and infrastructure. Urban climate services require multi-disciplinary and multi-sectorial approaches and new paradigms in urban climate modelling. This paper classifies the required urban input data for both mesoscale state-of-the-art Urban Canopy Models (UCMs) and microscale Obstacle Resolving Models (ORM) into five categories and reviews the ways in which they can be obtained. The first two categories are (1) land cover, and (2) building morphology. These govern the main interactions between the city and the urban climate and the Urban Heat Island. Interdependence between morphological parameters and UCM geometric hypotheses are discussed. Building height, plan and wall area densities are recommended as the main input variables for UCMs, whereas ORMs require 3D building data. Recently, three other categories of urban data became relevant for finer urban studies and adaptation to climate change: (3) building design and architecture, (4) building use, anthropogenic heat and socio-economic data, and (5) urban vegetation data. Several methods for acquiring spatial information are reviewed, including remote sensing, geographic information system (GIS) processing from administrative cadasters, expert knowledge and crowdsourcing. Data availability, data harmonization, costs/efficiency trade-offs and future challenges are then discussed.",
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note = "Funding Information: Coauthors Burmeister, Esch, Heldens, Kanani-S{\"u}hring, Maronga, Pavlik and Zeidler express their gratitude to the German Federal Ministry of Education and Research (BMBF) for funding grant 01LP1601 within the framework of Research for Sustainable Development (FONA; www.fona.de ). Coauthor See would like to acknowledge the support of the FP7-funded ERC project CrowdLand (Grant n° 617754 ). Coauthors Masson, Bocher, de Munck, Lemonsu, L{\'e}vy, Schoetter, Tornay, Bonhomme thank the French National Agency of Research for their support through the project applied Modelling and urbAn Planning laws: Urban Climate and Energy (MApUCE) with reference ANR-13-VBDU-0004 . Coauthors Masson, Bocher, de Munck, Lemonsu, Schoetter, Votsis and Bucher express their gratitude to ERA4CS, an ERA-NET initiated by JPI Climate with co-funding from the European Union (Grant n° 690462 ) for the URCLIM project ( www.urclim.eu ).",
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Download

TY - JOUR

T1 - City-descriptive input data for urban climate models

T2 - Model requirements, data sources and challenges

AU - Masson, Valéry

AU - Heldens, Wieke

AU - Bocher, Erwan

AU - Bonhomme, Marion

AU - Bucher, Bénédicte

AU - Burmeister, Cornelia

AU - de Munck, Cécile

AU - Esch, Thomas

AU - Hidalgo, Julia

AU - Kanani-Sühring, Farah

AU - Kwok, Yu Ting

AU - Lemonsu, Aude

AU - Lévy, Jean Pierre

AU - Maronga, Björn

AU - Pavlik, Dirk

AU - Petit, Gwendall

AU - See, Linda

AU - Schoetter, Robert

AU - Tornay, Nathalie

AU - Votsis, Athanasios

AU - Zeidler, Julian

N1 - Funding Information: Coauthors Burmeister, Esch, Heldens, Kanani-Sühring, Maronga, Pavlik and Zeidler express their gratitude to the German Federal Ministry of Education and Research (BMBF) for funding grant 01LP1601 within the framework of Research for Sustainable Development (FONA; www.fona.de ). Coauthor See would like to acknowledge the support of the FP7-funded ERC project CrowdLand (Grant n° 617754 ). Coauthors Masson, Bocher, de Munck, Lemonsu, Lévy, Schoetter, Tornay, Bonhomme thank the French National Agency of Research for their support through the project applied Modelling and urbAn Planning laws: Urban Climate and Energy (MApUCE) with reference ANR-13-VBDU-0004 . Coauthors Masson, Bocher, de Munck, Lemonsu, Schoetter, Votsis and Bucher express their gratitude to ERA4CS, an ERA-NET initiated by JPI Climate with co-funding from the European Union (Grant n° 690462 ) for the URCLIM project ( www.urclim.eu ).

PY - 2020/3

Y1 - 2020/3

N2 - Cities are particularly vulnerable to meteorological hazards because of the concentration of population, goods, capital stock and infrastructure. Urban climate services require multi-disciplinary and multi-sectorial approaches and new paradigms in urban climate modelling. This paper classifies the required urban input data for both mesoscale state-of-the-art Urban Canopy Models (UCMs) and microscale Obstacle Resolving Models (ORM) into five categories and reviews the ways in which they can be obtained. The first two categories are (1) land cover, and (2) building morphology. These govern the main interactions between the city and the urban climate and the Urban Heat Island. Interdependence between morphological parameters and UCM geometric hypotheses are discussed. Building height, plan and wall area densities are recommended as the main input variables for UCMs, whereas ORMs require 3D building data. Recently, three other categories of urban data became relevant for finer urban studies and adaptation to climate change: (3) building design and architecture, (4) building use, anthropogenic heat and socio-economic data, and (5) urban vegetation data. Several methods for acquiring spatial information are reviewed, including remote sensing, geographic information system (GIS) processing from administrative cadasters, expert knowledge and crowdsourcing. Data availability, data harmonization, costs/efficiency trade-offs and future challenges are then discussed.

AB - Cities are particularly vulnerable to meteorological hazards because of the concentration of population, goods, capital stock and infrastructure. Urban climate services require multi-disciplinary and multi-sectorial approaches and new paradigms in urban climate modelling. This paper classifies the required urban input data for both mesoscale state-of-the-art Urban Canopy Models (UCMs) and microscale Obstacle Resolving Models (ORM) into five categories and reviews the ways in which they can be obtained. The first two categories are (1) land cover, and (2) building morphology. These govern the main interactions between the city and the urban climate and the Urban Heat Island. Interdependence between morphological parameters and UCM geometric hypotheses are discussed. Building height, plan and wall area densities are recommended as the main input variables for UCMs, whereas ORMs require 3D building data. Recently, three other categories of urban data became relevant for finer urban studies and adaptation to climate change: (3) building design and architecture, (4) building use, anthropogenic heat and socio-economic data, and (5) urban vegetation data. Several methods for acquiring spatial information are reviewed, including remote sensing, geographic information system (GIS) processing from administrative cadasters, expert knowledge and crowdsourcing. Data availability, data harmonization, costs/efficiency trade-offs and future challenges are then discussed.

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