Journal of Heat Island Institute International Vol. 9-2 (2014)

Academic Article

The role of soil water content for microclimatic effects of green
roofs and urban trees – a case study from Berlin, Germany
Robert Günther*1*1 Institute of Meteorology and Climatology, Leibniz University Hannover
Corresponding author: Robert Günther, guenther@muk.uni-hannover.de
ABSTRACT
Stormwater can have negative influences on receiving systems and could be used to transpire water in orderto improve urban climate and thermal comfort within an urban area. Especially during warm sunny days, people incities can suffer in certain areas under extreme temperatures and very strong heat stress. Green roofs and trees could
be measures to use the benefits from stormwater. In this study the three-dimensional distribution of wind andtemperature was simulated with a micro-scale model for a city quarter in Berlin to study the effects of those two
measures. Under optimal soil water conditions the green roof on a large low warehouse lowers the temperature in 2
m height at noon within 100 m downstream 0.5 – 3 K. The thermal comfort, here evaluated by the Universal
Thermal Climate Index (UTCI), is also improved by the same amount. The potential cooling effect of the trees isalmost limited to the area of their shadow. The air is at noon about 3-4 K cooler and the UTCI is 7 K lower. After
14 days without precipitation the soil water content is much lower and the green roof does not transpire soil water
anymore. This halves the effects of the green roof. They are now only caused by changes in the albedo and heat flux
into the underlying medium. The effects of the trees are almost the same for both soil water content situations, as it
relies mainly on the solar radiation shielding under their canopy.
Key Words : urban climate, thermal comfort, soil water content, green roof, stormwater(e.g., de-paving of impervious areas)(7). In the following the

1. Introduction

effects of two urban greenery measures on the urban climate andStormwater runoff from sealed surfaces and roof tops can havehuman thermal comfort are investigated during a heat wave. The

strong impacts on the sewer system and receiving lakes / rivers.

dependence of those effects on the availability of water for

It influences them regarding hydraulics(1), toxic impacts(2) andtranspiration is examined for two different soil water contents(3)water quality . The positive potential of rain water is(SWC).

traditionally not often used for building services(4) and
improving thermal comfort(5) in cities. Especially in larger urban

2. Methods

areas a heat island effect is observed and leads to higher
temperatures than in the surrounding rural area(6). This is caused

The wind and temperature distribution in a city district isby a reduced wind speed between buildings and other obstacles,

simulated with the micro-scale model ASMUS (Ausbreitungs-

changes in the radiation budget, heat storage in build-up

und Strömungs Modell für Urbane Strukturen). It is based uponmaterials and impervious surfaces that alter the water balance.

the Navier-Stokes equations, the continuity equation, the first

The

The

law of thermodynamics and an equation for specific humidity.

meteorological conditions of a typical summer day with low

Buildings and trees are represented by impermeable orwind speeds and no cloud cover can lead to heat stress and makesemipermeable grid volumes. Their surface temperatures are

it unpleasant for people to live there.

calculated depending on their specific orientation and physicalTo reduce the negative effect of sealed surfaces and improve theproperties by a surface energy budget(8). The model equations,urban climate, a number of measures can be applied at building

boundary conditions for ground and building surfaces, including

level (e.g., green roofs, rain water use) and city quarter levelgreen roofs and trees are described by Gross(9).

surfaceenergybudgetisoveralldifferent.

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The calculation of the latent heat flux is modified after Bruse(10)computing time for the micro-scale model the SWC is calculated

to take the SWC and solar radiation via stomata resistance into

separately for a longer time period starting before the main

account.
=L ρJf,trans ,simulation (here 2 months). It is simulated for a grass surface,(1)

for a grass surface with a nearby tree of 10 m height and a green

where Ls is the latent heat, ρ the air density and Jf,trans theroof.

transpiration part of water vapor fluxes. Evaporation is neglected

The different green surfaces of the micro scale model are

and rain fall only interacts with the SWC.

initialized with the resulting SWC of the hydrological model.

,

;
;

0

0
,
0

Hourly(2)observations,linearinterpolated,fromnearbymeteorological stations provide the necessary data (precipitation,with aerodynamic resistance ra, stomata resistance rs andair temperature in 2 m height, soil temperature, wind and cloud

difference between saturation humidity at leaf temperature andcover for the one-dimensional, the hydrological and the micro(11)

air humidity Δq. Stomata resistance can be calculated with=rs,minkw,max.03 kw,max +Rkw

+fwiltscale model).
(3)

3. Setup of the numerical experiments

and depends on the minimal stomata resistance rs,min (different
for each vegetation type, here: for grass 200, for deciduous trees

For the numerical experiments, GIS-data (Geographical400)(12), the possible daily maximum of shortwave radiation

Information System) of the city quarter Schöneberg in Berlin,

Rkw,max and the availability of water fwilt.

Germany and hourly data from the weather station of the german

wilt

wilt

weather service (DWD) at Berlin-Tempelhof is used from(4)

1.6.2003 to 14.8.2003. The whole time period was simulated

is the ratio between SWC at wilting point and the actual SWC in(11)

the root zone.

with the hydrology model and the last day was simulated withthe micro-scale model with two different SWC under the same
weather conditions. The simulation area has a size of 458 m x
458 m and is 1000 m high. The horizontal grid resolution inside

2.1 Hydrology model
ASMUS was extended by a hydrology model that is described(13)

by Chen and Dudhia

a square of 202 m x 202 m in the center of the domain is 2 m, on(14)

and verified against measurements. It

is used to simulate the changes in soil water under the groundsurface and within green roofs dependent on transpiration andprecipitation. Short vegetation on the ground and on green roofs
only interacts with the hydrology model at the top layer (here: 5cm depth) and directly under the greenery. Trees (here: only tilia
cordata / small-leaved lime) take water from deeper layers (here:
in depths up to 3 m) and from a larger horizontal area(15).
2.2 The superimposed forcing
The domain of the micro scale model is embedded in theatmospheric boundary layer. The time-dependent external
forcing above the domain has to be prescribed to study thediurnal variation of the effects of urban greenery measures. A
one-dimensional boundary layer model(16) simulates theatmosphere up to 2000 m height with 45 grid levels and gridlevels of 10 m near the ground and up to 100 m at the top of thedomain. The surface temperature at the lower boundary is
calculated by a surface energy budget for a green field. The
hourly results of the lowest 1000 m are used to force the microFig. 1 Simulation area in Berlin-Schöneberg (Google Earth,scale model. They are linear interpolated to match the time step2014). Inside the red square 2 m x 2m horizontal grid resolution

and vertical grid resolution of the mirco-scale model.

and outside 8 m x 8 m. The green area in the middle shows the

The reservoir capacities of the soil for water make it necessary

position of the green roof as measure number one and the yellow

to consider its long-term behavior. Because of the highdots the 13 trees as measure number two.

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the outside 8 m (Fig. 1). The vertical resolution is 2 m from the

3.3 Scenarios

ground up to 40 m height and then increases up to 150 m at the

In order to study the effects of measures for stormwater

top of the domain.

management on the urban climate and human thermal comfort
two measures are defined and simulated for one day under the

3.1 The synoptic situation

weather conditions described above (3.1). The first measure is a

From 1st of august until 14th of august 2003 the daily averagegreen roof (albedo 0.2)(17) on the central warehouse. It has antemperatures at the meteorological station were between 20 °C

assumed heat conductivity of 2.2 W/(m*K)(9) and a size of about

and 28 °C with daily maximum temperatures between 27 °C and

9600 m², is 4 m high and originally has a black mat surface

34 °C (Fig. 2). There were light winds with up to max. 2- 3 m/s(albedo 0.13)(17). The heat conductivity was set to 0.7 W/(min 10 m height from the east and during daytime strong solar

K)(18). The transpiration rate of the green roof depends on theradiation. The rain water total in June and July at Tempelhof was

SWC that is saved in the growing medium from previous rain

105 mm and almost no precipitation in the first two weeks offalls. The second measure are 13 trees of 10 m height and a ballAugust 2003 (Fig. 2).

shaped crown with a diameter of 8 m. They are located on theparking lot (that is now unsealed) in the south of the warehouse

3.2 Geographical data

(Fig. 1). They use the soil water in their environment for

The geographical data is from different databases and includes

transpiration.

high resolution information about building and vegetation

The SWC at the beginning of the simulation with the micro scaleheights, green roofs, degree of the sealing and tree positions. The

model takes two possible values: SWC at field capacity (“high”)

city quarter is in the southwest of Berlin and consists ofor as simulated with the hydrological model until 14th of August

perimeter development with inner yards and small public parks.

2003 (“low”) (see 4.1).

It has a less dense population than in the center of Berlin(Berlin-Mitte). The average building has a height of 20 m,

4. Results and discussion

except for the large warehouse in the center of the domain that is
4 m high (Fig. 1). Flat roofs are assumed for all buildings and

The effects on urban climate are described by changes in the

inclined or sloping surfaces were ignored. The averagesurface temperature and air temperature at 2 m height. The

vegetation / tree is about 10 m high and their overall coverage isUniversal Thermal Climate Index (UTCI) is used to characterize

about 30 % of the area. Short vegetation on the ground and on

the thermal comfort. The UTCI depends like the PMV

green roofs is assumed to be grass and covers about 15 % of the(Predicted Mean Vote) on several meteorological parameters

ground surface (excluding additional measures). Other ground(wind speed, mean radiation temperature, air temperature andsurfaces are assumed to be sealed. A sandy soil was assumed forhumidity), activity and clothing of people. There are some

all ground surfaces with a SWC at field capacity of 0.236 m³/m³,

differences between UTCI and PMV which lead to advantages

soil saturation at 0.339 m³/m³ and wilting point at 0.01 m³/m³.

and disadvantages, nevertheless is the correlation between both

For the green roofs a one-layer sandy loam soil with a higher

indices still very high(19). A comparison of the effects on thermal

SWC at field capacity (0.312 m³/m³), at soil saturation (0.476

comfort based upon PMV would also have been possible.

m³/m³) and at wilting point (0.084 m³/m³) was assumed.

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4.1 Soil water content
Fig. 3 shows the simulated SWC under a grass surface and agreen roof in a depth of 5 cm. The precipitation and evaporation
has a strong influence on the SWC in the top layers and isreduced in deeper layers. After rain fall the SWC at the top layer
reaches its maximum value and is limited to SWC at saturation.
Within one day the SWC at those layers is reduced to SWC atfield capacity. This matches the scenario with “high” SWC. At
mid-August 2003, during the heat wave with two weeks ofalmost no precipitation, the SWC reaches wilting point at the top
layers and minimum values in deeper layers under both types of
surfaces (“low” SWC scenario).
Fig. 4 Perspective view from southwest of surfaces temperatures
4.2 Diurnal variation of latent heat flux and waterin °C at noon with both measures and “high” SWC

consumption
The daily maximum latent heat flux over the grass covered green

orientated surfaces and the ground receive the largest values ofroof measure varies between 0 W/m² for “low” SWC and 270

solar radiation and temperatures of bare ground reachW/m² for “high” SWC (not shown here). Overall up to 4.0 l/m²

temperatures up to 36 °C. The temperature of other surfaces areof soil water are transpired per day under optimal conditions

much lower (≤ 24 °C) dependent on their orientation, presencewith high SWC.

of shadow, surrounding wind speeds and, as the case may be,

The trees of measure two have a mean maximum latent heat flux

transpiration.

of 105 W/m² for the “low” SWC and 180 W/m² for the “high”

The surface temperature of the warehouse roof is lower during

SWC (not shown here). Each tree has a surface of 194 m² anddaytime if it is covered with a green roof (not shown here). The

transpires between 300 l to 500 l soil water per day dependent on

maximum difference is at noon and depends on the SWC. It

the SWC scenario. Because of their size and shape the trees

ranges from -2 (“low” SWC) to -3 K (“high” SWC). This issimulated in this study consume about 2.7 l/m² to 4.4 l/m² per

caused by transpiration (for the “high” SWC scenario), aday. The water consumption of the two measures per squaredifferent albedo and heat flux through the underlying medium.

meter soil is similar, but trees also take soil water from deeper

In the early morning around 4 a. m. the green roof surface is 1.5

layers, access a greater water reservoir directly and are therefore

K warmer than the bare roof for both SWC scenarios, caused byless dependent on short-term rain events.

a stronger surface heat flux from the underlying medium.

The simulated latent heat flux depends strongly on the amount of

The surface temperature of the ground under the trees is at noon

solar radiation and is only sensitive to extremely low SWC. The

up to 4.5 K lower than without this measure (not shown here).

order of magnitude for the daily water consumption for bothThis is mainly caused by the shadow of the trees and does not(20)

measures is in the range of literature values.

significantly change with the SWC.
The maximum differences between the surfaces temperatures at

4.3 Temperatures and thermal comfort in the built-up area

daytime with and without green are much smaller than simulated

Fig. 4 shows a perspective view from south west of theby Gross(9) (10 - 15 K) or measured by Wong(21) (8 – 10 K).

simulated surface temperatures at noon for the inner domain

Reasons could be a different wind and temperature profile andwith both measures and “high” SWC. At this time south

lower solar radiation.

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In the following the focus of this study is on the evaluation ofhere). The effect of the tree measure on the UTCI is locallythe potential cooling effect of the two measures.

much stronger (up to -8 K) (Fig. 10). This measure lowers the

At noon the simulated air temperature in 2 m height ranges fromheat stress at noon by one category from strong to moderate heat

27 °C, in the shadow of buildings and vegetation to 36 °C, nearstress. The increased air humidity, caused by the transpiration ofsouth orientated walls and areas without vegetation and bare

two measures or between the “high” and “low” SWC scenarios,

surfaces for the reference situation with “low” SWC (Fig. 5).

do not decrease thermal comfort significantly.

The temperature distribution for the reference situation with“high” SWC is almost the same (not shown here), because of thesmall fraction of distributed short vegetation that transpire
significantly more water and have a different surface
temperature.
The green roof effects the air temperature in 2 m height in alarge area in wind direction, which covers almost the whole
inner domain, when there is “high” SWC. Near the warehousethe potential cooling can reach up to -3 K. In a distance of 100 m
the effect is much smaller (still more than -0.5 K) (Fig. 6).
Wong(22) measured a similar potential cooling effect 1 m aboveof a green roof (max. –4.2 K). The maximum potential cooling
effect of the green roof is much lower for the “low” SWC

Fig. 6 Effect on air temperature in 2 height of the green roof

scenario when the roof does not transpire water (max. -0.5 K)

measure in K with “high” SWC.

and diminishes within the inner domain (Fig. 7). The potential
cooling of the trees does not significantly depend on the SWC
and has its maximum within their shadows with -4 K but
vanishes within a distance of 20 m (Fig. 8). Shashua-Bar(23)calculated a similar potential cooling effect for this kind of tree
at noon, ranging from -1.2 to -3.4 K.
The UTCI is divided in heat and cold stress categories, e.g.:
26 °C - 32 °C = moderate heat stress and 32 °C - 38°C = strong
heat stress. It is very sensitive to the mean radiation temperature,
which is about 30 K cooler without direct solar radiation.
Because of this the heat stress is only moderate in the shadow oftrees and buildings within the inner domain. Near southorientated walls over bare ground with no shadow, strong heatstress is caused, e. g. in the south of the warehouse (Fig. 9).

Fig. 7 Effect on air temperature in 2 height of the green roof

The green roof on the warehouse changes the UTCI within themeasure in K with “low” SWC.

inner domain by up to -2 to -3 K (Fig. 10) because of the lower
air temperature dependent on the SWC scenario (not shown

Fig. 8 Effect on air temperature in 2 height of the tree measure in
Fig. 5 Simulated air temperature at noon in 2 m height in °C

K with “low” SWC.

without both measures and “low” SWC.

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Research (BMBF) in the framework of the FONA (Research for
Sustainable Development) initiative.
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(Received Nov. 30, 2014, Accepted Dec. 27, 2014)- 25 -