Variability of urban surface temperatures and implications for aerodynamic energy exchange in unstable conditions

Abstract

Sensible heat flux (Q H ) is a critical driver of surface and boundary layer meteorological processes, especially in urban areas. Aerodynamic resistance methods (ARM) for modelling Q H are promising because, in principle, all that is needed is surface temperature (T 0 ), air temperature (T A ) and an aerodynamic resistance term (r H ). There are significant challenges in urban areas, however, due to uncertainties in satellite-derived land surface temperatures (LST), logistical challenges in obtaining high-resolution air temperatures, and a limited understanding of spatial and temporal variability of r H and associated variables (e.g. thermal roughness length). This work uses an extensive LST dataset covering 6 years (2011)(2012)(2013)(2014)(2015)(2016) in central London and a long-term in situ observation network to analyse the variability of LST and r H variables. Results show that LST is spatially correlated with building and vegetation land cover with coherent thermal structures at length scales less than 500-1,000 m. Additionally, satellite-observed LST varies with average building height (up to 10% cooler in areas with tall buildings). The r H term and associated variables are observed to vary on daily and seasonal cycles, and findings are used to model Q H using five variations of an ARM-based approach on a 100 m pixel basis. Modelled Q H is compared to observations from three scintillometer paths and an eddy covariance flux tower. We find generally good agreement between observations and models, although there is uncertainty in all methods (mean absolute error ranges from 58.1-129.3 W/m 2 ) due to the challenges involved in determining high-resolution meteorological and surface inputs, particularly LST and friction velocity (u * ). Additional complexity in evaluating modelled Q H arises from anthropogenic heat sources: long-term tower-based observations show that T A and the radiometer-derived T 0 are warmer during working weekdays than non-working days (up to 0.7 • C) and that there is an observed lag (2-3 hr) between energy consumption and the observed warming and modelled Q H .

Integrating Urban Form, Function, and Energy Fluxes in a Heat Exposure Indicator in View of Intra-Urban Heat Island Assessment and Climate Change Adaptation

“…Their impact in absolute terms is limited in the urban core, as QE was found to have low values (fewer than 30 W m −2 ); however, for the vegetated suburbs, the estimation sensitivity is expected to be higher. The sensitivity analysis findings are in agreement with those reported in [67,81] (in terms of percentage variations), where Ts was also considered to be the most important parameter in the resulting sensitivity of the fluxes. A more uniform spatial distribution than H/W and βm was found for the estimated ΔQsm ( Figure 6c).…”

“…In the literature, several studies have modeled the urban energy fluxes using a remotely-sensed approach [66][67][68][132][133][134][135][136][137][138]; however, only few of them made synchronous measurements of the turbulent fluxes available for validation purposes. Here, the obtained accuracy is considered to be consistent with the reported errors in recent studies of long-term, remotely-sensed turbulent fluxes [68,81,86].…”

“…Remote sensing methods have often been used in natural [63][64][65] and urban environments [66][67][68] for the estimation of the turbulent surface fluxes using the aerodynamic resistances for heat (rH) [s m −1 ] and moisture (rV) [s m −1 ] transfer:…”

“…Remote sensing methods have often been used in natural [63][64][65] and urban environments [66][67][68] for the estimation of the turbulent surface fluxes using the aerodynamic resistances for heat (r H ) [s m −1 ] and moisture (r V ) [s m −1 ] transfer: methodology that combines ridge regression with multiple predictor variables and a high-resolution emissivity map [55]. MODIS calibrated radiances product (MOD/MYD021KM) and precipitable water product (MOD/MYD05-L2) were accessed from the National Aeronautics and Space Administration's (NASA's) Level-1 and Atmosphere Archive and Distribution System (LAADS) Distributed Active Archive Center (DAAC).…”

COSMO-BEP-Tree v1.0: a coupled urban climate model with explicit representation of street trees

“…In order to improve the representation of the transpiration from street trees and therefore the modelling of the associated latent heat fluxes, a mechanistic stomata model (e.g. Damour et al, 2010) will have to be implemented. Furthermore, to properly represent soil water scarcity during extended drought periods, an urban hydrology module should be developed and coupled to COSMO-BEP-Tree (e.g.…”