ARTICLE INFORMATION
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A icle i le
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100m clima e and hea s ess da a up o 2100 o 142 ci ies a ound he globe
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Au ho s
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Niels Sou e ijnsa,*
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Di k Lauwae a
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Quen in Lejeuneb
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Chahan M. K op c,d
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Kam Lam Yeungc
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Sh u i Na he
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Ca l F. Schleussne
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A ilia ions
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a En i onmen al In elligence Uni , Flemish Ins i u e o Technological Resea ch (VITO), Mol, Belgium
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b V ije Uni e si ei B ussels (VUB), B ussels, Belgium
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c Ins i u e o En i onmen al Decisions, ETH Zu ich, Zu ich, Swi ze land
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d Fede al O ice o Me eo ology and Clima ology Me eoSwiss, Zu ich, Swi ze land
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e Depa men o Physics, Uni e si y o Ox o d, Ox o d, Uni ed Kingdom
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In eg a ed Clima e Impac s Resea ch G oup, In e na ional Ins i u e o Applied Sys ems Analysis
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(IIASA), Laxenbu g, Aus ia
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Co esponding au ho ’s email add ess and Twi e handle
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Niels.sou e ijns@ i o.be; h ps://x.com/nielssou e ijns
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Keywo ds
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U ban clima e; U ban hea ; P ojec ions; High- esolu ion
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Abs ac
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Ci ies wo ldwide a e inc easingly acing he challenges o hea s ess, a p oblem expec ed o wo sen
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wi h ongoing clima e change. The lack o de ailed, ci y-speci ic da a hinde s e ec i e esponse
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measu es and limi s he adap i e capaci y o u ban popula ions. In his da a desc ip o , we in oduce
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a comp ehensi e da abase p o iding clima e and hea s ess in o ma ion o 142 ci ies globally,
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co e ing he p esen and ex ending p ojec ions up o 2100 ac oss h ee dis inc clima e scena ios,
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including wo o e shoo scena ios. This da ase includes 34 hea s ess indica o s a a spa ial esolu ion
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o 100 me e s, o e ing a unique da abase o iden i y ulne able a eas and deepen he unde s anding
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o u ban hea isks. The da a is p esen ed h ough an accessible, use - iendly dashboa d, enabling
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policymake s, esea che s, and ci y planne s, as well as non-expe s, o easily isualise and in e p e
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he indings, suppo ing mo e in o med decision-making and u ban adap a ion s a egies.
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SPECIFICATIONS TABLE
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Subjec
Ea h & En i onmen al Sciences
Speci ic subjec
a ea
Mic oscale clima e in o ma ion o ci ies wo ldwide
Type o da a
Spa ially explici 100m clima e in o ma ion a decadal imes eps o he pe iod
2010-2100 in Ne CDF o ma
Da a collec ion
The U bClim u ban bounda y laye model is used o dynamically downscale la ge-
scale clima e in o ma ion o he ex en o indi idual ci ies and hei u al
su oundings a e y high esolu ion (100m). This hou ly in o ma ion is ansla ed
o decadal hea s ess indica o s o he pe iod 2010-2100. Impac indica o s a e
calcula ed using he CLIMADA model.
Da a sou ce
loca ion
142 ci ies a ound he wo ld
Da a accessibili y
Reposi o y name: Zenodo
Da a iden i ica ion numbe : h ps://doi.o g/10.5281/zenodo.13361538
Di ec URL o da a: h ps://zenodo.o g/ eco ds/13361538
Rela ed esea ch
a icle
None
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1. VALUE OF THE DATA
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• The da ase p esen ed in his pape p o ides a i s -o -i s kind a chi e o 142 ci ies co e ing all
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con inen s (excluding An a c ica) wi h de ailed clima e, hea s ess and impac in o ma ion o
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bo h p esen and u u e ime scales (un il 2100) a 100m spa ial esolu ion.
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• The 100m spa ial esolu ion allows o iden i y he mos ulne able a eas wi hin he ci y and
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he long- e m a ailabili y o he da a pe mi s o calcula e hea s ess impac s owa ds he end
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o he cen u y unde di e en emission pa hways, including o e shoo scena ios and hei
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unce ain y. This p o ides in aluable suppo o u ban planning, enhancing public heal h
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esponses, eme gency esponse planning and clima e impac and adap a ion s a egies.
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• The da a is p esen ed in an easy- o-access dashboa d (h ps://clima e- isk-
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dashboa d.iiasa.ac.a /impac s/explo e), allowing no only esea che s, bu also non-expe s
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and policy make s o easily access, isualise and in e p e he hea s ess da a. Las ly, a oolbox
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is p esen ed o ob ain simila da a o ci ies ha a e cu en ly no ep esen ed in his da ase .
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• The model ools (U bClim & CLIMADA) a e alida ed bo h on empe a u e and humidi y,
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impo an componen s o calcula ing hea s ess.
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2. BACKGROUND
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Hea s ess is a na u al disas e ha is esponsible o app oxima ely 500.000 excess dea hs pe yea
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wo ldwide (1). In u ban en i onmen s, empe a u es a e gene ally highe compa ed o u al
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en i onmen s caused by he lowe amoun o ege a ion and abundance o sealed su aces. Towa ds
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he u u e, one expec s an inc ease in he numbe o hea wa es in ci ies (2) and hei inhabi an s a e
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p ospec ed o expe ience wice as much hea s ess compa ed o u al popula ions (3). Taking in o
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accoun ha 68 % o he global popula ion is p ojec ed o li e in u ban a eas by 2050 (4), hea s ess
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in ci ies is a key p io i y o conside by policy make s, ci y planne s and au ho i ies. Despi e he
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acknowledgemen o he inc eased ulne abili y o ci y popula ions o hea s ess (5,6), cu en
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globally a ailable da ase s lack he spa ial and empo al esolu ion o ep esen his addi ional hea
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bu den (7,8). The da ase p esen ed he e p o ides a i s -o -i s kind a chi e o 142 ci ies co e ing all
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con inen s (excluding An a c ica) wi h de ailed clima e, hea s ess and impac in o ma ion o bo h
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p esen and u u e ime scales (un il 2100) a 100m spa ial esolu ion, building on he wo k ha was
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execu ed o e Eu ope by Lauwae e al. (2024) (9).
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3. DATA DESCRIPTION
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Indica o s o each decade a e a ailable o a selec ion o 142 ci ies o he pe iod 2010-2100 o
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di e en u u e clima e model scena ios and unce ain ies (Figu e 1; Supplemen a y Table 1). The
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da abase o indica o s is p o ided in bo h Geo i and Ne CDF o ma and is a ailable in a local
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p ojec ion (which can be e ie ed om he me ada a o he iles) and in EPSG:4326. Indi idual iles
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and quick isualisa ions o indica o maps can be e ie ed om he Clima e Risk Dashboa d
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((h ps://clima e- isk-dashboa d.iiasa.ac.a /impac s/explo e), which allows o download he Geo i s,
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Ne CDFs and isualisa ions in PNG o ma (Figu e 2). A bulk da a download op ion ha allows o
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download all indica o s, ime pe iods, scena ios a once is also p o ided ia
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h ps://doi.o g/10.5281/zenodo.13361538. As all da a is geo e e enced, use s can isualise, analyse
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and manipula e he maps in GIS so wa e ools and py hon.
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Figu e 1: O e iew map indica ing he 142 ci ies o which p esen and u u e clima e and hea s ess da a is made a ailable.
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Figu e 2: Snippe isualisa ions o he annual numbe o days wi h mode a e hea s ess (We Bulb Globe Tempe a u es abo e
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25°C) o e Be lin in he 2020 clima e policies scena io om a (le )) spa ial and ( igh ) empo al pe spec i e. Visualisa ions
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ob ained om he Clima e Risk Dashboa d.
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An o e iew o he lis o indica o s ha is calcula ed o each o he 142 ci ies is lis ed below.
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- Tempe a u e Indica o s
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o A e age daily maximum empe a u e: A e age daily maximum 2 me e empe a u e
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o e he ull decade
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o A e age daily minimum empe a u e: A e age daily minimum 2 me e empe a u e
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o e he ull decade
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o A e age daily empe a u e: A e age daily 2 me e empe a u e o he ull decade
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o Maximum empe a u e o he wa mes mon h (10): The a e age maximum mon hly
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empe a u e o he wa mes mon h h oughou he yea
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o Maximum empe a u e o he cooles mon h (10): The a e age minimum mon hly
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empe a u e o he cooles mon h h oughou he yea
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o Day ime U ban Hea Island: The a e age di e ence in daily maximum empe a u es
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be ween each pixel and he u al (non-wa e ) spa ial 10 h pe cen ile empe a u e
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alue. Tempe a u es a e heigh -co ec ed by escaling hem o he a e age ci y heigh ,
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applying a lapse a e o 6.5 K*km-1. I cap u es he di e ence in empe a u es due o
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human ac i i ies and he modi ica ion o land su aces.
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o Nigh ime U ban Hea Island: The a e age di e ence in daily minimum empe a u es
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be ween each pixel and he u al (non-wa e ) spa ial 10 h pe cen ile empe a u e
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alue. Tempe a u es a e heigh -co ec ed by escaling hem o he a e age ci y heigh ,
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applying a lapse a e o 6.5 K*km-1. I cap u es he di e ence in empe a u es due o
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human ac i i ies and he modi ica ion o land su aces.
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- Tempe a u e-based hea s ess indica o s
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o Annual hea wa e days: A hea wa e is de ined as a minimum o h ee days in which
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bo h he daily maximum and minimum empe a u e exceed he 90 h pe cen ile
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h eshold o a base pe iod ( aken as he pe iod 2011-2020). The 90 h pe cen ile
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h eshold is calcula ed o e he ull simula ion domain ( he ci y and i s u al
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su oundings) based on he de ini ion in Romanello e al. (2022) (11). The indica o is
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depic ed as he a e age numbe o hea wa e days pe yea .
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o Annual hea -wa e magni ude index daily (HWMId): The HWMId was de ined by Russo
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e al. (2015) (12) and allows quan i ying he magni ude o hea wa es by accoun ing
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o bo h hei se e i y and du a ion, which makes i mo e sui able o compa e ex eme
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empe a u e e en s ac oss he wo ld as well as pas , p esen and u u e hea wa es.
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o Annual numbe o days exceeding [25°C; 30°C; 35°C]: Annual numbe o days in which
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he maximum empe a u e exceeds [25°C; 30°C; 35°C].
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o Annual numbe o nigh s exceeding [20°C; 25°C; 28°C]: Annual numbe o nigh s in
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which he minimum empe a u e does no d op below [20°C; 25°C; 28°C]
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o Annual cooling deg ee hou s: Cooling deg ee hou s is an in e na ional s anda d o
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es ima e ene gy usage o cooling dwellings using ai condi ioning. I is calcula ed as
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he numbe o hou s du ing which he empe a u es ises o e 25°C, mul iplied by he
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numbe o deg ees he empe a u e ises abo e 25°C. The annual a e age alue o
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he decade is shown.
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- We Bulb Globe Tempe a u e based hea s ess indica o s
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o Annual numbe o days WBGT > [25°C; 28°C; 29.5°C; 31°C]: Annual numbe o days in
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which he WBGT exceeds [25°C; 28°C; 29.5°C; 31°C] o a leas one hou .
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o Annual numbe o nigh s WBGT > [25°C; 28°C]: Annual numbe o nigh s in which he
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WBGT does no d op below [25°C; 28°C]
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o Annual numbe o hou s WBGT > [25°C; 28°C; 29.5°C; 31°C]: Annual numbe o hou s
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in which he WBGT exceeds [25°C; 28°C; 29.5°C; 31°C].
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o Los wo king hou s (LWH) o in ense ac i i ies: Depending on he WBGT, wo ke s lose
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p oduc i i y o mus ake manda o y b eaks. Fo in ense ac i i ies (415W; see
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ISO:7243 o examples) he ollowing equa ion was cons uc ed o calcula e he los
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p oduc i i y in one hou (13):
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𝐿𝑊𝐻=1 − {1
−0.165∗𝑊𝐵𝐺𝑇+5.3982
0{𝑖𝑓 𝑊𝐵𝐺𝑇 < 26.55918
𝑖𝑓 26.55918 ≤ 𝑊𝐵𝐺𝑇 < 32.59783
𝑖𝑓 𝑊𝐵𝐺𝑇 ≥ 32.59783
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o LWH o mode a e ac i i ies: Depending on he WBGT, wo ke s lose p oduc i i y o
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mus ake manda o y b eaks. Fo mode a e ac i i ies (300W; see ISO:7243 o
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examples) he ollowing equa ion was cons uc ed o calcula e he los p oduc i i y in
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one hou (13):
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𝐿𝑊𝐻=1 − {1
−0.2195∗𝑊𝐵𝐺𝑇+7.2043
0{𝑖𝑓 𝑊𝐵𝐺𝑇 < 28.2656
𝑖𝑓 28.2656 ≤ 𝑊𝐵𝐺𝑇 < 32.82141
𝑖𝑓 𝑊𝐵𝐺𝑇 ≥ 32.82141
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o LWH o ligh ac i i ies: Depending on he WBGT, wo ke s lose p oduc i i y o mus
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ake manda o y b eaks. Fo ligh ac i i ies (180W; see ISO:7243 o examples) he
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ollowing equa ion was cons uc ed o calcula e he los p oduc i i y in one hou (13):
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𝐿𝑊𝐻=1 − {1
−0.5∗𝑊𝐵𝐺𝑇+16.5
0{𝑖𝑓 𝑊𝐵𝐺𝑇 < 31.0
𝑖𝑓 31.0 ≤ 𝑊𝐵𝐺𝑇 < 33.0
𝑖𝑓 𝑊𝐵𝐺𝑇 ≥ 33.0
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- Impac indica o s
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o Popula ion exposed o hea wa e wa ning days
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o Popula ion exposed o hea s ess days
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4. EXPERIMENTAL DESIGN, MATERIALS AND METHODS
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The U bClim model (14) is used o de i e he hou ly me eo ological ou pu o calcula e he indica o s.
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U bClim is an u ban bounda y laye clima e model, which is designed o dynamically downscale la ge-
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scale clima e in o ma ion o he ex en o indi idual ci ies and hei u al su oundings a e y high
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esolu ion (up o 100m). The U bClim model consis s o a land su ace scheme con aining simpli ied
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u ban physics, coupled o a 3-D a mosphe ic bounda y laye module, aking in o accoun he
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conse a ion equa ions o momen um, empe a u e, humidi y and mass, while also speci ically
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accoun ing o u bulen luxes and he mixing laye . The a mosphe ic bounda y laye is ied o
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synop ic-scale me eo ological ields h ough he la e al and op bounda y condi ions, o ensu e ha
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he synop ic o cing is p ope ly conside ed.
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The p esen -day simula ion pe iod spans a ime pe iod o 10 yea s om 2008-2017. Fo his pe iod,
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he U bClim model is o ced a i s op and la e al bounda ies by la ge-scale synop ic in o ma ion om
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he ERA-5 eanalysis p oduc (an o e iew o he a iables ha a e used can be ound in (14). Apa
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om me eo ological inpu da a, he main s eng h o he U bClim model lies in a de ailed
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ep esen a ion o he land su ace p ope ies. Depending on he egion, di e en da a sou ces ha e
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been used o cha ac e ise he u ban su oundings (Supplemen a y Table 2). These da a sou ces a e
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esampled o he ci y modelling domains a 100m spa ial esolu ion and allow o ob ain spa ial
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he e ogenei y wi hin he u ban canopy. De ails on he app oach can be ound in (9,14).
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The U bClim model p oduces hou ly ou pu o me eo ological a iables such as empe a u e,
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humidi y, wind speed, bu also soil p ope ies and ene gy luxes a 100m spa ial esolu ion. Nex o
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hese basic me eo ological a iables, hea s ess (We Bulb Globe Tempe a u e) is calcula ed based on
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he model o Liljeg en e al. (2008) (15). This me ic accoun s o empe a u e, humidi y and adia ion
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and se es as a p oxy o pe cei ed empe a u e. I is calcula ed ollowing ISO:7243 using he
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me eo ological ou pu o U bClim and sola adia ion in o ma ion om he eanalysis da ase ERA-5.
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To accu a ely downscale adia ion o 100m esolu ion, a de ailed ep esen a ion o he building
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oo p in s and ees wi hin he modelling domain is necessa y. Thei e ec is wo- old. On he one
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hand, hey cas shade, while on he o he hand, buildings also abso b and emi adia ion, adding an
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ex a sou ce o adia ion. De ailed building oo p in in o ma ion is ob ained om Open S ee Map,
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Google A ica Buildings and Mic oso Building Foo p in s, while he ac ion o ees in each 100m
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pixel is de ined depending on he land use.
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The u u e clima e o cing da a is ob ained om he MESMER-FaIR ensemble. Bo h FaIR and MESMER
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a e clima e model emula o s ha , wi h limi ed compu a ional e o , can p o ide a la ge ensemble o
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clima e model ealisa ions. The FaIR emula o (16) is used o ansla e g eenhouse gas emissions o
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he o al s eng h o he o cing imposed on he clima e sys em. This allows o calcula e he (change
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in) Global Mean Tempe a u e (GMT), cons ained by bo h his o ic wa ming and expec ed u u e
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changes se ou by he In e go e nmen al Panel on Clima e Change (IPCC). GMT is used by MESMER
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(17) o emula e he e olu ion o key clima e a iables o e land o each o he gi en Ea h empe a u e
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ajec o ies ob ained om FaIR. In his wo k, he mon hly downscaled module o MESMER is used,
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MESMER-M.
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Fo each o he 142 ci ies, he ollowing scena ios ha e been conside ed:
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- 2020 clima e policies (IPCC AR6 scena io): This scena io assumes ha no u he clima e ac ion
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is aken beyond he clima e policies ha we e in place in 2020. Global wa ming eaches 2.9°C
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in 2100 (bes es ima e), and would con inue climbing in o he new cen u y.
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- Delayed clima e ac ion (G adual s eng hening scena io in IPCC AR6): This scena io assumes
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ha deca bonisa ion is delayed o he 2030s, bu hen akes place in ea nes . Fossil uel use
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ne e ends bu is ins ead compensa ed o wi h high amoun s o ca bon dioxide emo al.
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Global wa ming in 2100 eaches 1.7°C (bes es ima e).
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- Shi ing pa hway (IMP-SP scena io in IPCC AR6): This scena io explo es how a b oade shi
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owa ds sus ainable de elopmen can be combined wi h s ingen clima e policies. Global
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wa ming peaks a 1.6°C in 2060 and goes back o 1.3°C in 2100 (bes es ima e).
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The low spa ial esolu ion and mon hly empo al esolu ion p e en s us om pe o ming accu a e
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u u e simula ions o U bClim dynamically d i en by he MESMER-M ensemble. Fo example, changes
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in mon hly a e age empe a u e migh unde es ima e changes in he highes empe a u e quan iles
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(i.e. ex eme empe a u es gene ally change wi h highe amoun s han a e age empe a u es, which
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a e o mos in e es in ou s udy. To add ess his, we apply he quan ile mapping bias algo i hm (18).
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A e age mon hly changes in empe a u e o each decade in he 2.5°x2.5° g id cell in which each ci y
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is loca ed a e ob ained om MESMER-M, while changes in di e en empe a u e quan iles (10 in o al)
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o di e en changes in mon hly empe a u e a e ob ained om he CMIP6 a chi e, which has a highe
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ime esolu ion (daily). I is used o calcula e changes in quan iles o daily empe a u e o di e en
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le els o mon hly empe a u e change wi hin he ci y. These pe u ba ions a e added o he his o ical
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da a simula ed by U bClim, leading o a ime se ies o he same leng h and ime scale as he his o ical
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ime se ies bu ep esen a i e o u u e clima e condi ions. The app oach abo e is applied o he h ee
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u u e clima e scena ios o cing i wi h da a om he mean, 5 h and 95 h pe cen iles o he ensemble
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o MESMER-M ealisa ions un il 2100. This p o ides an es ima e o he unce ain y a ound he mean
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changes in he calcula ed indica o s.
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Apa om me eo ological in o ma ion ha is di ec ly ob ained om he U bClim model, impac s a e
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compu ed using he open-sou ced and open-access na u al haza d isk model, CLIMADA (CLIMa e
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ADAp a ion) (19). The impac is calcula ed based on h ee componen s: haza d, exposu e, and
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ulne abili y. The haza d da a is ob ained om he ci y-scale me eo ological modelling wi h he
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U bClim model. The exposu e is de ined as he popula ion and is ob ained a 100m spa ial esolu ion
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om Wo ldPop o each o he 142 ci ies. The Wo ldPop Cons ained Indi idual coun ies 2020 UN
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adjus ed da a p o ides he op-down cons ained g idded popula ion da a which is adjus ed o ma ch
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he Uni ed Na ions na ional es ima e. Thus, he popula ion da a is alida ed o o icial e e ence. The
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o iginal Wo ldPop da ase is on a coun y scale. To ma ch he haza d da a on a ci y scale, he o iginal
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coun y-le el g idded popula ion da a is immed in o he speci ic ci y-le el g idded popula ion da a.
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Vulne abili y, such as age g oup, is no conside ed. Each pe son in he exposu e has an equal weigh ing
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o he haza d.
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LIMITATIONS
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An impo an limi a ion o he da ase is ha i assumes s a ic u ban mo phology. In eali y, ci ies will
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expand and ans o m in ways ha can in luence bo h local clima e esponses and he numbe o
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people. By design, hese ac o s a e held cons an o isola e he la ge-scale clima e change signal a
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high esolu ion o p esen -day ci ies. The da ase should he e o e be in e p e ed as a clima ological
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baseline o assessing po en ial clima e impac s, a he han as a p ojec ion o u u e u ban
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condi ions. Fu u e ex ensions could combine his amewo k wi h u ban g ow h scena ios and
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dynamic demog aphic p ojec ions o gene a e mo e applica ion-o ien ed es ima es o u u e u ban
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clima e isk.
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ETHICS STATEMENT
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The au ho s ha e ead and ollow he e hical equi emen s o publica ion in Da a B ie . We he eby
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con i m ha he cu en wo k does no in ol e human subjec s, animal expe imen s, o any da a
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collec ed om social media pla o ms.
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CRediT AUTHOR STATEMENT
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Niels Sou e ijns: Concep ualiza ion, Da a Cu a ion, Me hodology, Fo mal Analysis, W i ing. Di k
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Lauwae : Concep ualiza ion, Me hodology, Fo mal Analysis. Quen in Lejeune: Concep ualiza ion,
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Me hodology. Chahan M. K op : Da a Cu a ion, Fo mal Analysis. Kam Lam Yeung: Da a Cu a ion,
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Fo mal Analysis. Sh u i Na h: Da a Cu a ion, Fo mal Analysis. Ca l F. Schleussne : Concep ualiza ion,
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Funding acquisi ion. All au ho s e iewed he manusc ip .
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ACKNOWLEDGEMENTS
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This p ojec has ecei ed unding om he Eu opean Union’s Ho izon Eu ope esea ch and
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inno a ion p og amme unde g an ag eemen No 101003687.
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DECLARATION OF COMPETING INTERESTS
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The au ho s decla e ha hey ha e no known compe ing inancial in e es s o pe sonal ela ionships
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ha could ha e appea ed o in luence he wo k epo ed in his pape .
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