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QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETYQ. J.R. Meteorol. Soc.00: 1–?? (2012)Published online in Wiley InterScience(www.interscience.wiley.com) DOI: 10.1002/qj.000

Impact of anthropogenic heat emissions on London’stemperatures

S.I. Bohnenstengela, I. Hamiltonb∗ M. Daviesc∗ and S.E. Belchera,d∗

aDepartment of Meteorology, University of Reading, UKbEnergy Institute, University College London, UKcBartlett School of Graduate Studies, University College

Abstract: We investigate the role of the anthropogenic heat flux on the urban heat island of London. To do this the time-varyinganthropogenic heat flux was added to the urban surface energybalance parameterisation, MORUSES, implemented into a 1kmresolution version of the UK Met Office Unified Model. The anthropogenic heat flux is derived from energy demand data forLondon and is specified on the models 1km grid, and includes variations on diurnal and seasonal time-scales. We contrast aspringwith a winter case, which illustrates the effects of the larger anthropogenic heat flux in winter and the different thermodynamicsroles played in the different seasons. The surface energy balance channels the anthropogenic heat into heating the urban surface,which warms slowly because of the large heat capacity of the urban surface. About one third of this additional warming goes intoincreasing the outgoing long-wave radiation and only abouttwo thirds goes into increasing the sensible heat flux that warms theatmosphere. The anthropogenic heat flux has a larger effect on screen level temperatures in the winter case, partly because theanthropogenic flux is larger then, and partly because the boundary layer is shallower in the winter. For the specific winter casestudied here the anthropogenic heat flux maintains a well-mixed boundary layer through the whole night over London, whereasthe surrounding rural boundary layer becomes strongly stably stratified. This finding is likely to have important implications for airquality in winter. On the whole the inclusion of the anthropogenic heat flux improves slightly the comparison between themodelsimulations and measurements of screen level temperature,and indicates that the anthropogenic heat flux is beginning to be animportant factor in the London urban heat island.Copyright information: This is a preprint of an article published as early view online in the Quarterly Journal of the RoyalMeteorological Society Copyright c 2013 Royal Meteorological Society as SI Bohnenstengel, I Hamilton, M Davies, SE Belcher:Impact of anthropogenic heat emissions on London’s temperatures, DOI: 10.1002/qj.2144 , article first published online 22ndMay 2013. The published version of this article can be found under http://onlinelibrary.wiley.com/doi/10.1002/qj.2144/abstractCopyright c© 2012 Royal Meteorological Society

KEY WORDS Anthropogenic emissions, urban heat island, surface energy balance, diurnal cycle, London

Received October 2012; Revised ; Accepted

1 Introduction

Anthropogenic heat emissions in cities due to humanactivities are likely to increase the urban heat island,whereby urban areas are warmer than rural areas. Thispotentially increases heat related mortality rates, espe-cially during hot summer periods (Milojevic et al., 2011),but can also offset cold night-time temperatures in winter.The present study aims to understand the role of anthro-pogenic emissions for the urban heat island (UHI). Weillustrate the processes for spring and winter conditions inLondon. To do this, the UK Met Office Unified Model isapplied to London using the urban surface energy balanceparameterisation MORUSES (Porson et al. 2010a), whichwas specifically configured for London (Bohnenstengel etal., 2011) and is extended here to include a representationof anthropogenic heat fluxes. Understanding the influenceof anthropogenic emission on the urban surface energybalance then helps to inform how energy might be used inurban areas to minimise its impact on urban temperatures.

∗Correspondence to: Sylvia I. Bohnenstengel, Department ofMeteor-ology, University of Reading, PO Box 243, Earley Gate, Reading, RG66BB, UK. E-mail: [email protected]

Anthropogenic heat and moisture sources includeemissions from buildings and transportation. They appearin the surface energy balance as further terms in the formof additional anthropogenic latent and sensible heat fluxes.Often these terms do not consider a diurnal cycle eitherbecause they are thought to be small, or because they aredifficult to estimate. The anthropogenic emissions in Lon-don, which experiences a temperate climate, have beenassumed to be small, the current version of the UK MetOffice Unified Model uses values of the order of up to20Wm−2 in urban areas that slightly vary with seasonbut not on a diurnal cycle. These values compare wellwith total anthropogenic emissions for the Greater Londonarea derived by Iamarino et al. (2011). However, Iamarinoet al. (2011) and Hamilton et al. (2009) also show thelarge variability of anthropogenic emissions at the kilo-metre scale with values of the order of200Wm−2 incentral London and emissions of the order of10Wm−2

at the fringes of Greater London. We know that anthro-pogenic emissions vary spatially and diurnally in London,however we do not know their impact on urban tempera-tures. These measured anthropogenic heat flux values are

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2 S.I. BOHNENSTENGEL, I. HAMILTON, M. DAVIES, S.E. BELCHER

very large compared to the net incoming radiation, par-ticularly in winter. However, such large values are con-strained to very small areas in the city centre. Neverthe-less, their influence on the urban atmosphere deserves tobe investigated in more detail with a view to improvethe representation of the diurnal and seasonal cycle ofanthropogenic emissions in the UK Met Office UnifiedModel. The first question this paper addresses is how thediurnal cycle of anthropogenic emissions alters the indi-vidual terms of the surface energy balance during win-ter and spring/summer conditions, since Bohnenstengel etal. (2011) demonstrated that London’s urban heat islanddepends considerably on the surface sensible heat flux. Weinvestigate a second question of more generic character,namely, can anthropogenic emissions change the timingand strength of the urban heat island.

Sailor (2011) summarises three approaches to esti-mate anthropogenic emissions in urban areas. These are(i) an inventory approach, (ii) an estimate using theenergy budget closure and (iii) using building energymodels. The inventory approach gathers energy consump-tion data. Most of these inventory approaches make theassumption that the energy consumed is similar to theanthropogenic sensible heat released (Sailor, 2011), whichneglects a time-lag between consumption and heat releasedue to conduction through building walls for instance.Most of these approaches also neglect the latent heatreleased, which is a valid assumption for London, wherelatent anthropogenic emissions are estimated below 7.3%(Iamarino et al., 2011). Allen et al. (2010) developed theLUCY model, that provides global anthropogenic emis-sions at 2.5 x 2.5 arc-minute resolution. Their anthro-pogenic estimates for London compared well with themore detailed emissions for London by Hamilton et al.(2009) which are used in the present study.

The energy budget closure approach uses direct mea-surements of the terms in the surface energy balance fora control volume. The residual of the net terms in and outof the control volume is then assumed to be the anthro-pogenic heat generated within the volume. The downsidesare that this approach does not distinguish between thedifferent anthropogenic sources and data generated by thisapproach are sparse. Also, the errors in each term accumu-late into the anthropogenic term (Sailor, 2011).

The third approach then uses building energy models,which calculate the energy consumption within buildings.Of these models, EnergyPlus is probably the most wellknown (Bueno et al. 2011). This method characterisesthe physical properties of the building and simulatesthe energy demand for services using assumptions ofoccupancy and service patterns. It attempts to combinethe estimated sensible and latent emissions from building-scale models with the urban canopy over a geographicarea. Dynamic simulation models such as EnergyPlus arevery commonly used.

Urban surface energy balance parameterisationsstarted to include anthropogenic terms in the urban sur-face energy balance during the last decade. Masson etal. (2002) include anthropogenic heating into their TEB

parameterisation as an additional term in the surfaceenergy balance. They account for the building inducedanthropogenic emissions by assuming an annual cycle forthe building temperature. They further add a prescribedtraffic induced anthropogenic heat source term to the sen-sible heat flux term in the canyon. Salamanca et al. (2010)take a more complex approach to account for buildinginduced anthropogenic emissions by including the build-ing energy model (BEM) into their urban canopy param-eterisation (UCP). BEM takes into account several build-ing energy sources such as generation of heat by build-ing occupants, radiation from the windows, heat exchangedue to building ventilation and heat diffusion through thewalls. Presently, this is the most complex approach toaccount for anthropogenic emissions in weather forecastmodels, however, it has the disadvantage that it needs verydetailed high-resolution input data. In the present study,we follow the simpler approach of Masson et al. (2002)by including an anthropogenic heat source term into theurban surface energy balance.

In the present study we include, for the first time,detailed anthropogenic emissions in the UK Met OfficeUnified Model generated for London. An inventoryapproach to estimate anthropogenic emissions (Hamiltonet al., 2009) allows us to feed high-resolution spatiallyand temporally varying emissions into the urban surfaceenergy balance. To answer the questions raised earlier wesimulate two case studies. One in May 2008 that is anal-ysed by Bohnenstengel et al. (2011) which is characterisedby a strong urban heat island and moderate advection. Thesecond one simulates the London UHI on 10/11 December2009, when a strong UHI occurred during a very locallydriven meteorological situation. The comparison of casestudies allows us to compare the impact of anthropogenicemissions in spring/summer and winter as well as duringadvectively driven and locally driven meteorological situ-ations.

2 Anthropogenic emissions

2.1 Anthropogenic emissions in London

The anthropogenic energy use (domestic, non-domestic,metabolic emissions and transport) is derived from energydemand statistics for London and is then converted intohourly anthropogenic heat fluxes for each1km2 UK Uni-fied Model grid box using a standardised emission profile.The total annual, domestic, non-domestic, and transportanthropogenic energy data is provided at a census outputlevel (i.e. Middle Layer Super Output Area) inKWh−1.A method of accounting for these emissions is detailedin Davies et al. (2008a), which uses national statisticsof domestic and non-domestic energy demand (includ-ing: gas, electricity, oil and solid fuels), transport fueldemand and flows in London, and the metabolic releaseof heat of the resident and workplace population (Davieset al. 2008b). Individual daily and hourly emission pro-files for each energy sector are developed using avail-able daily demand profiles for a whole year, updated to

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IMPACT OF ANTHROPOGENIC HEAT EMISSIONS ON LONDON’S TEMPERATURES 3

the selected periods in May 2008 and December 2009.Hourly anthropogenic releases for each Unified Modelgrid box are made using estimates of diurnal profiles foreach energy sector (Davies et al. 2008b and Hamilton etal. 2009). The sum of the anthropogenic energy from allmentioned energy sectors is apportioned to each grid boxof the Unified Model domain by overlaying the grid onthe MLSOA boundaries and apportioning the total to eachgrid box within the boundary. The emission profiles areconverted into a heat emission flux using the technique setout in Hamilton et al. (2009). They use the national dailyenergy demand profiles and transport movement profileto estimate the total daily energy expenditure within eachoutput area. These daily total emissions profiles are thenconverted into an hourly emission by applying the hourlydemand profiles for each energy source. Finally, the totalanthropogenic emissionsEtotal are divided by the totalsub-grid scale urban land-use areaAi within each Uni-fied Model grid boxi to define an hourly average anthro-pogenic heat fluxQA,i in Wm−2.

The anthropogenic heat fluxQA,i(t) for a grid boxiat a timet is then given by the following set of equations:

QA,i(t) = Etotal,i(t)/Ai (1)

Etotal,i(t) = Ed,i ∗ fd(t) + End,i ∗ fnd(t)

+Etr,i ∗ ftr(t) + Em,i ∗ fm(t) (2)

with the functionsfd,fnd,ftr,fm being the hourly emis-sion profiles for domestic (d), non-domestic (nd), trans-port (tr) and metabolic (m) emissions. For all functionsfS it is assumed that

∑8760

t=1fS(t) = 1, where S stands for

each sector, i.e. d (domestic), nd (non-domestic), tr (trans-port) and m (metabolic), respectively.Ed, End, Etr, Em

are the annual demand for each energy sector inkWh.

2.2 Implementation of anthropogenic emissions inMORUSES

The surface energy balance provides the forcing to theatmosphere. MORUSES calculates the thermodynamicurban surface energy balance separately for roof and streetcanyon tiles (Porson et al. 2010a,b) in the UK Met OfficeUnified Model. There are a range of approaches suchas using fixed internal building temperatures to simulatethe impact of domestic heating contributions i.e. Masson(2000). However, MORUSES is developed for use in aNWP model and we are only interested in the overallsurface fluxes from the street canyon and the roof thatprovide the forcing to the lowest atmospheric model levelat 5m and how anthropogenic emissions alter this surfaceenergy balance. Therefore, we assume in MORUSESthat the anthropogenic heat from buildings is mostlyreleased via ventilation into the street canyon. Therefore,the anthropogenic heating termQA is added to the surfaceenergy balance of the canyon tile as follows:

CdTc

dt= RN − QH − QE + QA − G (3)

Here C is the areal heat capacity of the canopy(JK−1m−2), Tc is the surface temperature. Their prod-uct represents the thermal inertia of the urban canopy.RN

is the net radiation inWm−2, QH represents the sensibleheat flux (Wm−2), QE the latent heat flux,QA is the addi-tional anthropogenic emissions term (Wm−2) andG is theheat flux into the underlying ground (Wm−2). A detaileddescription of the individual terms of the surface energybalance is provided in Porson et al. (2010a).

Figure 1 shows the urban land-use distribution forthe model domain which is100kmx100km large. Figure2(a) shows the corresponding spatial pattern of the anthro-pogenic heat fluxQA at morning peak on 10 December2009 and Figure2(b) shows the corresponding diurnalcycle of the anthropogenic emissions at the city centreand the fringes of London for the May and the Decem-ber case study. In both cases the anthropogenic emissionspeak in the city centre and decrease in roughly concen-tric circles towards the fringes of London. Values in thecity centre exceed400Wm−2 (Figure2a) and values at thefringes of London are of the order of60Wm−2 in Decem-ber. As can be seen from Figure2(a) anthropogenic heatemissions correlate loosely with London’s urban land-use fraction. The correlation factor is around 0.44 dueto some smaller urban land-use fractions being associ-ated with higher anthropogenic heat fluxes towards thefringes of London, where light industrial land-use leadsto higher anthropogenic emissions.The urban parameter-isation varies the building morphology at the grid scaleat 1km and therefore accounts for different urban land-use types such as industrial or residential areas via thebuilding morphology. London’s subgrid-scale urban land-use fractions and the planar and the frontal area indexthat describe the density and height of buildings for Lon-don are correlated with a factor of 0.98. However, theanthropogenic emissions show a correlation factor of 0.44with the building morphology parameters. Therefore, thebuilding morphology and urban land-use fraction onlypartly explain anthropogenic emission values. However,higher urbanisation mostly leads to higher anthropogenicheat fluxes in most parts of London with the highestanthropogenic heat fluxes associated with central London.They are slightly lower in May at the fringes and sim-ilar to December in the city centre according to Figure2(b). However, the spatial pattern is similar to the one inDecember. Anthropogenic emissions depend not only onthe degree of urbanisation but also on the urban land-usetype such as residentially or commercially used districts.A similar dependence on urban land-use type was foundfor Singapore by Quah and Roth (2012). The timing of thediurnal cycle (Figure2b) of anthropogenic heat fluxes isthe same in these scenarios, however the amplitude variesbetween May and December.

As shown in Figure2(b), the anthropogenic forcingterm shows a pronounced diurnal cycle with two peaksin both periods. In May the anthropogenic heat fluxstarts to increase at sunrise around 5am and peaks afirst time around 9am, about 2.5 hours after sunrise. Theanthropogenic heat flux then drops until noon to a value




of just under100Wm−2 in the city centre. It then reachesa second peak about half an hour after sunset around9pm. The evening heat flux is slightly lower than themorning emissions. During peak hours the anthropogenicheat flux reaches values of over400Wm−2 (Figure2(a)).This equals about half of the net solar radiation flux inMay. Outside the city centre the diurnal cycle follows thesame pattern as in, although the emissions are only abouta third of those in the centre.

In December the timing of the diurnal cycle of theanthropogenic heat flux is similar to May, although, theamplitude is higher near the fringes. The timing of thepeak heat flux is however different compared to sunriseand sunset in December: The sun rises around 8am andsets around 4pm in December. Hence, the first peak ofthe anthropogenic heat flux in the morning nearly coin-cides with sunrise, while the evening peak is delayed by 5hours compared to sunset. In contrast, in May the anthro-pogenic heat flux peaks in the morning after sunrise; in theevening at sunset. Diurnally, through the year, the patternand timing of anthropogenic release is dependent on themagnitude of the source. In the summertime, the transportemissions dominate while in the winter time the heatingemissions dominate. The seasonal trend is primarily alsodriven by the summer/winter balance of urban heating, asit will be highest in the winter and lowest in the sum-mer in London. These differences provide an interestingexperiment into the mechanism of anthropogenic heatingon urban boundary layer.

3 Selection of the case studies

Two cases were selected, one in spring, one in winter.Both case studies were selected for conditions with littlecloud and with weak synoptic forcing, and so both caseshave pronounced urban heat islands. The UK Met OfficeUnified Model was run with the urban surface energybalance scheme MORUSES that was configured for Lon-don with a horizontal resolution of 1km for a domainof 100km2 (Figure 1) with London in the centre of thedomain (Bohnenstengel et al., 2011). For each case studytwo simulations were set up: anurban and arural simu-lation. The urban simulation uses realistic land-use infor-mation including urban areas and information about thebuilding morphology, while the rural simulation replacesthe urban land-use in each grid box with the remainingsub-grid scale land-use classes in this grid box by scalingthem up. Alternatively, if a grid box is covered by 100%urban land-use urban areas are replaced by grass. Com-paring the urban with the rural simulation determines theurban increment in the surface energy balance or temper-atures caused by London.

The spring case study is centred on the 7/8 May 2008.This case was analysed in detail in Bohnenstengel et al.(2011): A strong urban heat island occurred during thenight 7/8 May 2008 while a high pressure system wasdominating the weather over the UK with clear skies atnight. Moderate winds lead to a well-mixed boundary

layer and an urban heat island pattern that was shiftedslightly downwind from the urban land-use in London.

The winter case study is centred on the urban heatisland observed during the night from 10/11 December2009 and has not been analysed before. During this periodthe UK was under the influence of a high pressure sys-tem with about1030hPa sitting over the UK and verylow wind conditions. The UK experienced cold temper-atures around freezing point during the simulated period.These conditions led to the formation of some fog and lowclouds in and around London in the early morning hoursof the 11 December 2009. It is particularly difficult to dis-tinguish low clouds from fog in satellite images. The scat-tered fog or low clouds peaked around 6am and clearedup around noon on 11 December according to satelliteimages (personal communication with Aurore Porson andAdrian Lock, UK Met Office). This makes a comparisonwith observations difficult. The low level fog affects thesurface energy balance via the long wave radiation term.Therefore, it is expected that the simulated screen leveltemperatures will differ from the measured ones if fogwas simulated but not observed in some locations or viceversa, because the Unified Model simulates fog over Lon-don around the same time with a peak around 8am. Unfor-tunately, there are no fog measurements in central Londonand we can therefore only speculate that fog might haveaffected the comparison between the simulation and theobservations. The wind direction during these two daysshifted from north-westerlies to northerly winds and windspeeds were very low with about1ms−1. Under such con-ditions a strong local urban heat island signal developedin the screen level temperatures at night.

4 Impact of anthropogenic emissions on the urbansurface energy balance

In order to understand the physical mechanisms that giverise to the urban and anthropogenic increment we analysethe energy balance for the city centre of London, whereanthropogenic emissions are very high. Consider first thebalance of terms during the May case in the absenceof the anthropogenic heat flux. As shown in Figure3(a)the dominant balance during the night, at the beginningof the period, is between loss of energy at the surfacefrom out-going long wave radiation and cooling of theurban fabric. During the morning transition the incomingsolar flux is largely balanced by an increased storage inthe urban fabric. Over time this warms the urban fabric.The time scale is determined by the heat capacity ofthe urban fabric. Once the urban fabric is warmer thanthe overlying air, this drives a positive heat flux into theatmosphere. In the rural simulation the heat capacity ofthe vegetated land is considerably lower than in the urbanenvironment. As a consequence, the rural surface warmsup faster and drives a positive sensible heat earlier than inthe urban simulations. In contrast to the urban areas therural surface energy balance shows a positive latent heatflux during the day, while the latent heat flux is suppressedin the urban simulation in central London. Through the




afternoon, as the incoming solar drops, the loss of heatfrom the urban fabric by out-going long wave radiationand sensible heat flux is balanced by cooling of the urbanfabric. Again the large heat capacity of the urban fabricmeans that it is some time beyond sunset before the urbanfabric temperature drops below the air temperature, andthe sensible heat flux drops to zero. In contrast, the smallrural heat capacity causes the sensible heat flux to drop tozero about an hour before sunset. The large heat capacityof the urban fabric therefore acts like a thermal flywheelwhich reduces and delays the diurnal variations in sensibleheat flux. This pattern of variation is seen in idealisedmodelling (e.g. Harman & Belcher 2006) and in other data(e.g. Porson et al 2010 a, b).

The dashed lines shown in Figure3(a) show that theanthropogenic heat flux is not transferred directly intothe atmosphere. Instead it is channelled by the surfaceenergy balance into the storage term, which then warmsthe urban fabric. The temperature of the urban fabric thenrises driving an increased loss of energy as out-going longwave radiation and as a heat flux into the atmosphere.Hence again there is a time lag in the response of thesensible heat flux to variations in anthropogenic heatfluxes which is determined by the heat capacity of theurban fabric. During daytime the sensible heat flux isincreased by about60Wm−2, and the outgoing long waveradiation is increased by about 10Wm−2. The inclusionof anthropogenic emissions also leads to a longer-termeffect by storing more energy in the urban fabric duringthe morning, which in turn leads to the positive sensibleheat flux being sustained later into the night.

Figure3(b) shows the results for the December case.All the natural terms in the energy balance are smaller,because of the smaller net drive from the incomingsolar (note the different scales on Figures3(a) and (b)).The dominant balance is similar to the May case study,although the daytime sensible heat flux remains negativethroughout the day. The anthropogenic heat flux has alarger proportional effect in December because the nat-ural terms are all smaller than in May. The basic patternof effects of the anthropogenic heat flux is similar to theMay case, although there are interesting differences dueto the different magnitude of the anthropogenic heat fluxrelative to the other terms, and the different phasing ofthe peak in anthropogenic heat flux relative to sunrise andsunset. The morning peak in anthropogenic heat fluxesagain drives higher storage terms over the whole morn-ing. This drives up the temperature of the urban fabric,which drives greater out-going long wave radiation, byup to about25Wm−2, and changes the sensible heat fluxfrom negative to positive. Although it peaks at only about50Wm−2, as we shall see, this difference leads to substan-tial changes to the urban heat island intensity.

5 Atmospheric response to the anthropogenic heatflux

5.1 Screen level temperature and boundary layer depth

The simulated screen level temperatures are plottedagainst measurements for a rural simulation, a simula-tion with London’s urban land-use and a simulation withurban land-use and anthropogenic emissions.We make theassumption that the mixing is sufficient that temperaturedifferences between surface level and above roof levelare small (Oke, 2006) in order to compare the measure-ments with simulated temperatures. Figure4 shows theMay case and Figure5 the December case. This allowsus to determine an urban increment as well as an anthro-pogenic increment in the screen level temperatures.

MORUSES calculates temperatures at10m height,which are then interpolated down to1.5m height assumingMonin-Obukhov theory. The temperature at1.5m heightthen represents the fraction-weighted average of the sub-grid scale land-use tile temperatures at screen level.

Figure 4 compares simulated screen level tempera-tures with observations made with the University CollegeLondon (UCL) temperature sensor network at 7 locations(given in TableI and in Figure1) for the May case. Asdescribed in Bohnenstengel et al. (2011) including theurban land use leads to good agreement between sim-ulated and measured screen level temperatures, with atemperature increment of up to5K during the night. Day-time values show almost no difference between rural andurban areas. The reason is that the night-time boundarylayer is shallow and so increases to the sensible heat fluxassociated with the urban land use warm less air by ahigher temperature; by day the boundary layer is deep andthe increases to the sensible heat flux associated with theurban land use warm more air by a lower temperature.

The anthropogenic temperature increment, forcedby the anthropogenic heat flux, is much smaller thanthe urban temperature increment. The night-time tem-peratures are warmed by a further0.5K to 1K, whichimproves the agreement between the model and the obser-vations, although this improvement lies within the uncer-tainty range of both MORUSES and the measurements.Day-time temperatures are hardly affected. There is adifference between the observed and modelled tempera-tures during the morning transition (Bohnenstengel et al.2011). The addition of the anthropogenic heat flux doesnot explain this difference.

The simulated temperatures for both cases are eval-uated against measurements at screen level height at sev-eral locations in and around London. Both case studieswere evaluated against UCL temperature measurementsassuming an uncertainty of 1K for the measurements anda model uncertainty of 1.3K and 1.5K after 6h and 36hsimulations time, respectively (Jorge Bornemann,UK MetOffice, personal communication) with a spin-up time of24 hours. Locations for all stations can be found in Table Iand in Figure1. A detailed description of the UCL temper-ature sensors can be found in Bohnenstengel et al. (2011).




Figure 5 shows the comparison of the screen leveltemperatures from midnight on 10 until 6pm on 11December. In general, Figures5(b), 5(d) and5(e) showa reasonable agreement, within an uncertainty of0.5K to1K, between the measurements and the model. The tem-peratures measured and simulated in Figure5(a), Figure5(c) and Figure5(f) do not agree well, especially dur-ing the cooling phase at night. In general then the agree-ment between MORUSES and UCL is not as good asfor the May case. Two reasons for this are as follows.Firstly, the measurements are much noisier than for theMay case. This noisy behaviour is not reflected in thesimulations. The fog or low clouds that developed isvery patchy and, although the model did produce fog forthis case, it is unlikely that it is in exactly the correctlocations. Since fog alters the net long wave radiationand therefore screen level temperatures this is likely tocompromise the comparisons. It is difficult to determineexactly when and where the fog formed: satellite imagesshow patchy fog during the early morning hours of the11 December. Secondly, the meteorological situation inDecember was extremely locally driven with wind speedsaround1ms−1. It is therefore likely that the UCL sensorsreflect a more local temperature within the street canyon,while MORUSES simulates a temperature above the streetcanyon. In this case the assumption that there is suffi-cient mixing that temperature differences between surfacelevel and above roof level are small might be violated.With only a very small positive sensible heat flux duringthe night the urban canopy is likely to be stably strati-fied, suppressing mixing and leading to a very small foot-print of the measurements. MORUSES, however, reflectsa temperature averaged over a1km2 region. Given thesecaveats, the comparison between measurements and sim-ulations looks sufficiently promising to use this case tostudy the generation of an urban heat island and the roleof the anthropogenic heat flux in a winter setting.

The anthropogenic heat flux has a negligible effectat sites with low urban fraction, such as Figures5(a)and 5(b), but a more pronounced effect for sites witha high urban fraction, such as Figures5(d), 5(e) and5(f), where the anthropogenic increment reaches1.5K,which is probably just above the uncertainty range ofthe measurements. It seems anthropogenic emissions tendto have a measurable impact on temperatures in locallydriven situations.

The spatial pattern of the anthropogenic increment inscreen level temperatures for the May case is shown inFigure6. Screen shots of the anthropogenic temperatureincrement are shown for 7 May 2008 at 6am and 10pmlocal time. The spatial pattern of the anthropogenic incre-ment follows the pattern of the night-time UHI (Bohnen-stengel et al., 2011, their figure 3 and figure 9b), althoughits maximum values are restricted to the small area wherethe anthropogenic heat flux peaks (cf. Figure2a). Duringthe morning the anthropogenic increment reaches nearly2K in the city centre, decreasing to0.8K for the sur-rounding areas of the city and0.4K in the suburbs. At

10pm the overall pattern remains the same but the temper-ature increment only reaches1.8K to the west of the citycentre and the overall impact is slightly smaller. At bothtimes a plume forms with higher temperatures also founddownwind of London. The differences between 6am and10pm can be explained partly by the larger emissions dur-ing the morning compared to the evening, and by the lowerboundary layer depth in the early morning.

The anthropogenic increment in screen level temper-ature in the December case is generally larger than in theMay case, especially in the evening (Figure7). The urbantemperature increment reaches up to4K in the evening forthe urban simulation including anthropogenic heat fluxes.In contrast to May, the atmospheric response to emissionsis largest in the evening. The reason is that in the winterthe boundary layer is shallow and so the anthropogenicheat flux through the day is restricted to warming a shal-low layer of air near the surface. In the December casethe daytime boundary layer is up to400m deep and thenight-time boundary layer roughly100m for the urbansimulation with anthropogenic heat flux (Figure8). Whilethe temperature profiles from the rural simulation indicatea well mixed boundary layer of up to400m around noononly and otherwise a stable stratified boundary layer, theurban simulation has a slightly deeper daytime bound-ary layer of up to500m depth and is otherwise lessstably stratified (Figure8a). However, with the anthro-pogenic emissions, a well mixed shallow boundary layereven exists during the night and is of the order of200mdeep. Hence, in this December case study the anthro-pogenic emissions not only increase the urban heat islandbut also change the mixing properties of the urban bound-ary layer. For comparison, the boundary layer in May ismuch deeper with nearly2000m during day-time and awell mixed layer of the order of up to300m during thenight (Figure8b). Hence, the anthropogenic emissions aremixed over a much smaller volume in December. This isan important outcome with regards to air quality forecaststhat depend on accurately predicted mixing properties ofthe boundary layer.

The December case also shows very detailed struc-tures on very short length-scales. The low wind speedsin December, however, allow for a very local response toanthropogenic emissions. This is in contrast to the spatialstructure in May (Figure6), when temperatures are moreblurred through the mixing associated with advection.

5.2 Frequency distribution of urban and rural tempera-tures

Figure 9(a) summarises the frequency distribution ofscreen level temperatures for the inner10km2 area aroundthe London city centre for the rural, the urban and theurban plus anthropogenic simulations from 6am on 7 until6am on 8 May 2008 concentrating on a complete night.All three simulations show the same peak in the frequencydistribution for high temperatures around295K. These areday-time temperatures. The occurrence of these tempera-tures does not change between the three simulations. This




underlines the findings from analysing the diurnal cycleof the screen level temperatures that daytime tempera-tures hardly differ between urban and rural areas, becausethe boundary layer is deep. At night, however, when theboundary layer is shallow, larger differences appear in thefrequency distribution. The urban simulation shows thattemperatures are likely to be about4K warmer than in therural simulation; the lowest temperatures are shifted by3K for the urban and 4K for the anthropogenic simulationcompared to the rural simulation. And the urban simula-tion including anthropogenic emissions shows that night-time temperatures are likely to be5.5K higher than in therural simulation and1.5K higher than in the urban simula-tion for the most likely night-time temperatures indicatedby the night-time peaks. Hence, the anthropogenic emis-sions increase screen level temperatures just beyond theuncertainty range of the model when analysing the wholeinner10x10km2 London domain.

In December a similar pattern is found in the fre-quency distribution for 10 and 11 December 2009 (Figure9(b)) for the rural simulation. The peak around282.5Kindicates that daytime temperatures hardly differ betweenrural, urban and urban plus anthropogenic simulations. Atnight the urban simulation gives temperatures1K warmerfor the most likely night time temperatures than for therural temperatures. This is much smaller than for the Maycase. However, we observe a4K shift for the lowest tem-peratures at night for the urban simulation. This shift ofnight-time temperatures is of the same order of magnitudeas in May. The anthropogenic heat flux yields a furtherwarming of about1K. From Figure7 it was shown thatthe anthropogenic temperature increment can exceed 3Kin places in December. While the rural simulation showsa distribution with two peaks like in May, both urban sim-ulations show a distribution with only a single peak. Areason for this shift is the smaller diurnal temperaturerange in December than in May due to the lower heatfluxes. The additional heat flux from the urban area andthe anthropogenic heat is large enough to shift the two-peak rural distribution into a single peak distribution forthe urban and the anthropogenic simulations in December.

5.3 Urban heat island

Figure 10a and10b show the evolution of the canopy-layer urban heat island at a city centre location for theMay and December cases, respectively. In both cases theUHI grows sharply from noon and levels out at sunset.Following sunset, the UHI calculated with the urbansimulation (without the anthropogenic heat flux) dropsslightly until sunrise, when it drops sharply. Hence theUHI persists over a longer period in the winter case. Thesimulation with the anthropogenic heat flux remains morenearly constant through the night. At this location theanthropogenic heat flux increases the UHI by1K in Mayand1.5K in December.Similar values were found by Ruyand Baik (2012) for an idealised study quantifying thecontributing factors to the UHI.

6 Conclusions

In this study diurnally varying anthropogenic emissionswere included into the Met Office Unified Model for thefirst time based on realistic emissions data sets for Lon-don. Anthropogenic heat emissions are locally consid-erable larger than assumed, however, these large valuesof the order of several hundredWm−2 are restricted tosmall areas in London. We then evaluated the improvedMORUSES set-up against screen level temperatures mea-sured in London to test the impact of the heat emis-sions of urban temperatures. Therefore, two case studieswere chosen to compare winter and springtime impactsof anthropogenic emissions on the urban heat island inLondon. Including anthropogenic emissions improves thesimulation of screen level temperatures just beyond theuncertainty range. The impact of the anthropogenic heatsource is more pronounced in December than in May,when anthropogenic emissions are large compared to thesensible heat flux caused by storage of heat in the urbancanopy.

We then determined how anthropogenic emissionschange the diurnal cycle of the urban heat island inLondon. The anthropogenic emissions have a more pro-nounced impact on temperatures in December than inMay. The reason is that the anthropogenic emissionsaccount for a relatively larger proportion of heat avail-able in urban areas in December than in May due to thelower incoming energy in December. Further, the bound-ary layer is shallower in December and the anthropogenicemissions are mixed over a much smaller volume. Theyincrease temperatures beyond the uncertainty range ofmeasurements by up to1.5K in central parts of Londonin December on a calm cloud-free day. However, in Maytheir impact is smaller compared to the incoming solarenergy. The anthropogenic emissions increase the ampli-tude of the UHI and slightly extend the period of the UHIin December. The reason is that they only partly affecttemperatures directly in the form of an anthropogenic sen-sible heat flux but also indirectly by altering storage andconsequently the outgoing long wave and sensible heatflux terms. Due to the buffer effect of the storage term inthe surface energy balance the anthropogenic emissionshave a delayed effect on screen level temperatures thatmaintains higher night-time temperatures in London. Withanthropogenic heat fluxes likely to increase in the futureit seems that the London UHI is likely to be increasinglyaffected by anthropogenic heat fluxes.

7 Acknowledgement

This work was undertaken within the LUCID projectand ClearfLo project and was funded by EPSRC grantEP/E016448/1 and NERC grant NE/H00324X/1. Buildinginput parameters were provided from CASA (UCL Centrefor Advance Spatial Analysis) using the GLUD database.We are grateful to the Met Office for making the MetUMavailable and to the National Centre of Atmospheric Sci-ence (NCAS) Computational Modelling Support (CMS)




for providing technical support. We are grateful to Dr.Aurore Porson and Dr. Adrian Lock from the UK MetOffice for providing information on fog during December2009. Thanks go to Jorge Bornemann (UK Met Office)for advise on model uncertainty. We wish to thank the twoanonymous reviewers for their helpful comments.

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Harman IN and Belcher SE 2006. The surface energy balance andboundary layer over urban street canyons, Q.J.R. Meteorol.Soc., 132,2749-2768.

Iamarino M, Beevers S and Grimmond CSB, 2011. High-resolution(space, time) anthropogenic emissions: London 1970-2025.Int. J.Climatol. 32:1754-1767.

Masson V 2000. A physically-based scheme for the urban surfaceenergy budget in atmospheric models, Boundary-Layer Meteorol. 94:357-397.

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Table I. Longitude and latitude of the UCL temperature sensors.

Location Longitude Latitude Height [m]

SE1 -0.0814 51.5044 16

NW1 -0.1418 51.5292 12

EE3 -0.0556 51.5189 25

SW4 -0.1911 51.4780 8

NE5 -0.0266 51.5803 4

WW7 -0.3580 51.5189 5

WW11 -0.5440 51.5190 0




Figure 1. Model domain showing the sub-grid scale urban land-use fractions for London and the surrounding within each grid box and thelocations of UCL temperature sensors listed in TableI




(a) (b)

(c)

Figure 2. (a) Spatial pattern of anthropogenic heat emissions. Colours indicate anthropogenic emissions inWm−2 on the Unified Model

grid on 10 December 2009 at 9am local time and on 7 May 2006 at 9am local time. Blue isolines indicate urban land-use fractions forLondon. (c) Corresponding diurnal cycle of anthropogenic heat emissions for the city centre (black lines) and the fringes (grey lines) of

London for the 7/8 May 2008 and 10/11 December 2009. Thick lines depict May and thin lines December.




0 3 6 9 12 15 18 21−400

−200

0

200

400

600

800

Hour[UTC]

flux

[Wm

−2 ]

(a)

0 3 6 9 12 15 18 21−150

−100

−50

0

50

100

150

200

250

Hour[UTC]

flux

[Wm

−2 ]

(b)

Figure 3. Surface energy balance for simulations with and without anthropogenic heat emissions for the city centre for (a) 7 May 2008 and(b) 10 December 2009. Black solid lines depict the anthropogenic heat emissions, solid coloured lines refer to the simulations includinganthropogenic heat emissions and dashed coloured lines refer to simulations without the anthropogenic heat emissions, dotted lines referto the rural simulation. Green lines depict net short wave radiation fluxes, magenta lines depict net long wave radiativefluxes, red linesdepict latent heat fluxes, blue lines depict sensible heat fluxes and yellow lines depict the sum of storage of heat into theurban slab and

ground heat flux term.




(a) (b) (c)

(d) (e) (f)

(g)

Figure 4. Diurnal cycle of screen level temperature at sevenUCL locations from 1800 on 7 May to 1800 on 8 May 2008. Dashed-dottedlines refer to rural simulation, dotted lines refer to urbansimulation, dashed lines refer to urban simulation including anthropogenic

emissions and solid lines refer to the UCL measurements. Vertical lines indicate measurement and model uncertainty.The latitude and longitude coordinates of each station is listed in Table I.




(a) (b) (c)

(d) (e) (f)

Figure 5. Diurnal cycle of screen level temperature at 6 UCL locations from 00 on 10 December 2009 to 18 hours on 11 December2009. Dashed-dotted lines refer to rural simulation, dotted lines refer to urban simulation, dashed lines refer to urban simulation including

anthropogenic emissions and solid lines refer to the UCL measurements. Vertical lines indicate measurement and model uncertainty.




(a)

(b)

Figure 6. Anthropogenic increment in screen level temperatures for(a) 6am local time on 7 May 2008 and (b) 10pm local time on 7 May

2008.

(a)

(b)

Figure 7. Anthropogenic increment in screen level temperatures for(a) 6am local time on 10 December 2009 and (b) 10pm local time

on 10 December 2009.




(a)

(b)

Figure 8. Vertical potential temperature profiles over the city centre of London for (a) December and (b) May. Dark grey lines depictprofiles at noon, light grey lines depict profiles at 21UTC andblack lines depict profiles 3UTC. Solid lines refer to the rural simulation,dashed lines refer to the urban simulations and dash-dottedlines refer to the urban simulations with anthropogenic heat fluxes included.




(a)

(b)

Figure 9. Frequency distribution of screen level temperatures for the inner10x10km2 area of London for the rural simulation, the urban

simulation and the urban simulation with anthropogenic emissions based on temperature data on (a) 6am on 7 May until 6am on 8 Mayand (b) 6am on 10 until 6am on 11 December 2009.




(a)

(b)

Figure 10. Diurnal cycle of the urban heat island at a city centre location for the urban simulation (solid line) and the urban simulationincluding anthropogenic emissions (dashed line) for (a) 7/8 May 2009 and (b) 10/11 December 2009. Vertical black lines indicate sunrise

and sunset.



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