Changes of temperature and humidity in areas of city sprawl under climate change conditions

D. Argüeso, J.P. Evans and A. Di Luca ARC Centre of Excellence for Climate System Science & Climate Change Research Centre

University of New South Wales, UNSW, Sydney Australia

Email: d.argueso@unsw.edu.au

9th International Conference on Urban Climate (ICUC9) – Toulouse 20 July 2015

Motivation

Urban population

growth (urbanization)

Climate in cities is distinct

Anthropogenic climate change

FACTORS

? What will be the

combined effect of CC and urban expansion?

QUESTION

Future climate at urban scales

Sydney

GCM (150-200km) RCM (10km)

No cities at all Only urban land use

•  GCM primary source of Climate Change information

•  But too coarse to represent cities

•  RCMs at 10k capture some features of the city, but urban areas are represented only as different land use

•  Need for explicit representation of cities!

Future climate at urban scales

Sydney

GCM (150-200km) RCM (10km)

No cities at all Only urban land use Urban canopy model

RCM (2km)

Experiment design

•  Weather Research and Forecasting (WRF) system •  2-km spatial resolution (nested in 10k and 50k)

–  CSIRO-MK3.5 •  No cumulus parameterization in inner domain (explicit) •  Using Urban Canopy Model (SLUCM)1

276 F. CHEN et al.

HeatTurbulenceMomentum

Drag Wake diffusion Radiation

Lowest model level

BEPSLUCM

Urban canopy layer

Roughness sublayer

ZSun Z

Lowest model level

Urban canopy layer

Roughness sublayer

Sun

Wind profile RadiationFluxes

Figure 2. A schematic of the SLUCM (on the left-hand side) and the multi-layer BEP models (on the right-hand side).

and road layers (calculated from the thermal conductionequation). Surface-sensible heat fluxes from each facetare calculated using Monin–Obukhov similarity theoryand the Jurges formula (Figure 2). The total sensibleheat flux from roof, wall, roads, and the urban canyon ispassed to the WRF–Noah model as QHurb (Section 2.1).The total momentum flux is passed back in a similarway. SLUCM calculates canyon drag coefficient andfriction velocity using a similarity stability function formomentum. The total friction velocity is then aggregatedfrom urban and non-urban surfaces and passed to WRFboundary-layer schemes. AH and its diurnal variation areconsidered by adding them to the sensible heat flux fromthe urban canopy layer. SLUCM has about 20 parameters,as listed in Table I.

2.4. Multi-layer urban canopy (BEP) andindoor–outdoor exchange (BEM) modelsUnlike the SLUCM (embedded within the first modellayer), the multi-layer UCM developed by Martilli et al.(2002), called BEP for building effect parameterization,represents the most sophisticated urban modelling inWRF, and it allows a direct interaction with the PBL(Figure 2). BEP recognizes the three-dimensional natureof urban surfaces and the fact that buildings vertically dis-tribute sources and sinks of heat, moisture, and momen-tum through the whole urban canopy layer, which sub-stantially impacts the thermodynamic structure of theurban roughness sub-layer and hence the lower part ofthe urban boundary layer. It takes into account effects ofvertical (walls) and horizontal (streets and roofs) surfaceson momentum (drag force approach), turbulent kineticenergy (TKE), and potential temperature (Figure 2). Theradiation at walls and roads considers shadowing, reflec-tions, and trapping of shortwave and longwave radi-ation in street canyons. The Noah–BEP model hasbeen coupled with two turbulence schemes: Bougeaultand Lacarrere (1989) and Mellor–Yamada–Janjic (Jan-jic, 1994) in WRF by introducing a source term in theTKE equation within the urban canopy and by modify-ing turbulent length scales to account for the presenceof buildings. As illustrated in Figure 3, BEP is able tosimulate some of the most observed features of the urbanatmosphere, such as the nocturnal urban heat island (UHI)and the elevated inversion layer above the city.

To take full advantage of BEP, it is necessary tohave high vertical resolution close to the ground (tohave more than one model level within the urbancanopy). Consequently, this approach is more appropriatefor research (when computational demands are not aconstraint) than for real-time weather forecasts.

In the standard version of BEP (Martilli et al., 2002),the internal temperature of the buildings is kept con-stant. To improve the estimation of exchanges of energybetween the interior of buildings and the outdoor atmo-sphere, which can be an important component of theurban energy budget, a simple building energy model(BEM; Salamanca and Martilli, 2010) has been developedand linked to BEP. BEM accounts for the (1) diffusionof heat through the walls, roofs, and floors; (2) radiationexchanged through windows; (3) longwave radiationexchanged between indoor surfaces; (4) generation ofheat due to occupants and equipment; and (5) air con-ditioning, ventilation, and heating. Buildings of severalfloors can be considered, and the evolution of indoorair temperature and moisture can be estimated for eachfloor. This allows the impact of energy consumption dueto air conditioning to be estimated. The coupled BEP+ BEM has been tested offline using the Basel UrBanBoundary-Layer Experiment (Rotach et al., 2005) data.Incorporating building energy in BEP + BEM signifi-cantly improves sensible heat-flux calculations over usingBEP alone (Figure 4). The combined BEP + BEM hasbeen recently implemented in WRF and is currently beingtested before its public release in WRF V3.2 in Spring2010.

2.5. Coupling to fine-scale T&D models

Because WRF can parameterize only aggregated effectsof urban processes, it is necessary to couple it withfiner-scale models for applications down to building-scaleproblems. One key requirement for fine-scale T&D mod-elling is to obtain accurate, high-resolution meteorolog-ical conditions to drive T&D models. These are oftenincomplete and inconsistent due to limited and irreg-ular coverage of meteorological stations within urbanareas. To address this limitation, fine-scale building-resolving models, e.g. Eulerian/semi-Lagrangian fluidsolver (EULAG) and CFD–urban, are coupled to WRF

Copyright © 2010 Royal Meteorological Society Int. J. Climatol. 31: 273–288 (2011)

Source: (2) Chen et al. (2011)

(1) Kusaka et al. (2001) Boundary-Layer Meteorology

Experiment design

•  Three 20-y simulations: –  1990-2009: Present climate, present LU (CO) –  2040-2059: Future climate, present LU (CC) –  2040-2059: Future climate, future LU (CC + URB)

•  Climate change (A2) + Urban expansion (red)

Temperature and humidity climatology Day Night

Temperature

Vapor Pressure

Elevation

Land use

(3) Argüeso et al. (2015) PLoS ONE

CC

CC + URB

Changes in temperature

Day Night

(2) Argüeso et al. (2014) Clim Dyn

CC only •  Tmax changes:~ 1.0 to 1.5°C •  Tmin changes: ~ 1.5 to over

2.0°C CC + URB: •  Tmax changes: similar to CC only •  Tmin changes: ~ 3.0 to over

4.0°C (LU change)

•  Almost no footprint of urban expansion in Tmax

•  Clear impact of urban expansion on Tmin

CC

CC + URB

Changes in humidity (vapor pressure) Day Night

(3) Argüeso et al. (2015) PLoS ONE

Overall increase in VP due to global warming But substantially smaller increases in new urban areas, particularly during the day

CC

CC + URB

Changes in heat stress Day Night

(3) Argüeso et al. (2015) PLoS ONE

•  Heat stress: simplified wet-bulb globe temperature

•  W = 0.567*T+0.393e+3.94

Conclusions

•  Urban expansion + Climate change using RCMs: –  City growth effect on local Tmin ~ climate change signal (A2) –  No perceptible impact on Tmax changes –  Reduced diurnal cycle

•  Smaller increases in humidity (vapor pressure) –  Less than half of the CC-only increase during the day

•  Implications for heat stress: compensating factors –  Day: cities reduce CC-induced heat-stress increase (humidity

driven) –  Night: cities enhance CC-induced heat-stress increase (temp.

driven) •  Highlights the need to include other variables to assess human

vulnerability in future cities

References

•  (1) Kusaka H, Kondo H, Kikegawa Y, Kimura F (2001) A simple single-layer urban canopy model for atmospheric models: Comparison with multi-layer and slab models. Boundary-Layer Meteorology 101:329–358.

•  (2) 1. Chen F, Kusaka H, Bornstein RD, et al. The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems. Roth M, Emmanuel R, Ichinose T, Salmond J, eds. Int J Climatol. 2011;31(2):273–288. doi:10.1002/joc.2158.

•  (3) Argüeso D, Evans JP, Pitman AJ, Di Luca A (2015) Effects of City Expansion on Heat Stress under Climate Change Conditions. PLoS ONE 10:e0117066–19. doi: 10.1371/journal.pone.0117066

•  (4) Argüeso D, Evans JP, Fita L, Bormann KJ (2014) Temperature response to future urbanization and climate change. Clim Dyn 42:2183–2199. doi: 10.1007/s00382-013-1789-6

Thanks! Questions and comments?

Seasonal changes in daily heat stress

Contribution to heat stress changes in urban expansion areas

Day Night