Senate Department for Urban Development,
Environment and Technology
04.09 Bioclimate - Day and Night
(Edition 1998)
Overview
Environmental Atlas studies of the Berlin urban climate resulted in comprehensive descriptions (Maps
04.02-04.06, SenStadtUm 1993b-e,1994a, 1996b-f). These studies document changes in climate
conditions typical for city centers. The Climate Function Map 04.07 (SenStadtUm 1993f, 1996g) gives
information for planning for the city and its nearer surroundings from a climate perspective. The
Climate Function Map gives statements on areas where
 potential exists for the relief of adjoining or more distant spaces (relief areas),
 the strongest additional stresses are to be expected (stress areas) 
The Thermic Effects Complex
Human biometeorology is increasingly significant in applied urban climatology. Human
biometeorology analyses of cause and effect relationships between the atmospheric environment and
the health and quality of life of humans in cities mainly consider air quality and the thermic effects
complex. The thermic effects complex has special significance in prevention measures and it can be
influenced by planning measures. (cf. VDI 1998).
Healthy human beings possess extraordinarily great abilities to adapt to atmospheric conditions
(acclimatization). Healthy organisms adapt autonomously without noticing it. The adaptive abilities of
some persons can be overtaxed, depending on sensitivity, age (young children, the aged), illness,
pregnancy, etc. An indicator for the level of general health are certain discomforts. A predisposition for
certain illnesses may cause these illnesses to appear or to worsen, particularly in the cardio-circulatory
and upper respiratory systems. Epidemiological studies demonstrate the effects exerted on illness and
mortality rates by extreme conditions such as cold, heat, air pollution, and weather changes.
A good example is illustrated in Fig. 1. This figure depicts thermal stress on humans in their
meteorological surroundings in relation to the mean mortality rate. It is based on data from the state of
Baden-Württemberg. Both heat and cold are stress factors. Comparable results are found in other
countries, too.
Fig. 1: Relative Deviation of the Average Daily Mortality Rate (with 95 % Confidence Interval) from the
Mean (= Thermically Comfortable Range) in Baden-Württemberg (1968-1993) (DWD 1996)
It must be assumed that less extreme climate conditions also clearly influence the quality of life. This
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must particularly be true for anthropogenic, small-area, highly variable climate conditions in human
urban habitats.
Atmospheric effects on humans never proceed from a single meteorlogical element. The climate
influences organisms through a combination of numerous individual factors. The biological answer
to various parameters can range from no effects at all, or even positive effects in healthy persons, up
to minor annoyances, impairments, sub-clinical modifications, clinical damages and a rise in mortality
rates.
Humans posess the ability to maintain their body temperature within a certain range, independent of
changing surrounding conditions. This is achieved by a number of autonomous (involuntary) physical
and chemical regulatory mechanisms. These systems balance heat loss and heat generation between
each other and environmental conditions. Minimal activity of the thermal regulatory system is
experienced as comfortable. The more demands made on this system, the more the surroundings are
experienced as burdening, as stress.
Certain factors influence thermal regulation; clothing, activity, air conditioning, seeking relief in shadow,
or shelter from the wind (Jendritzky et al. 1990, Fig. 2).
Fig. 2: Factors of Tthermal Effects Complex (Jendritzky et al. 1990)
Energy exchange takes place by way of convection (air temperature, air movement); evaporation
(humidity, air movement); radiation (radiation balance in shortwave and longwave spectrum); and
breathing (air temperature, humidity). The meteorlogical parameters in parentheses are critical in
each transport process. Clothing type is also a factor in heat exchange.
The difference in atmospheric conditions between the city and its surrounding areas include a lower
average wind velocity (cf. Map 04.03, SenStadtUm 1994a, 1996c) and higher temperatures; this can be
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described as a heat island (cf. Map 04.02, SenStadtUm 1993b, 1996b). Humans adjust to the demands
of these conditions by way of the thermal regulatory system. This system balances heat production and
loss. The thermal regulatory system is minimally active when thermal conditions do not differ. The
greater the difference in thermal conditions, the more is demanded of the system.
Cold stress can be generally be reduced by wearing appropriate clothing or finding shelter in windprotected areas. Heat stress is more problematic because the direct physiological possibilities for
adjustment are limited. Heat stress is thus the main focus of scientific studies on the effects the climate
of dense urban areas has on human health and well-being.
The UBIKLIM Model
Research can help space planners to evaluate facts relevant both to the environment and to
intervention measures related to planning procedures. The procedural processes are often so complex
that it is greatly advantageous to have methods based on existing legal specifications, binding
threshold values, and the recommendations of recognized scientific bodies. Such methods make the
evaluation of individual projects easier to understand, as well as enabling comparisons to be made with
other regions or planning intentions. VDI Guideline 3787 Page 2 `Methods for the human
biometeorlogical evaluation of climate and air quality for urban and regional planning´ is an
excellent instrument. VDI 3787 reflects current scientific knowledge and recommends defined
regulatory applications for its implementation (VDI 1998).
Evaluations of the Berlin bioclimate use these recommended regulatory applications in the modeling
process `Urban Climate Model - UBIKLIM (Urbanes Klimamodell). A scaled evaluation parameter
derived from UBIKLIM is Predicted Mean Vote - PMV. PMV is a predicted average value for
estimated thermal conditions (cf. Methodology and Tab. 1).
Tab. 1: Evaluation Parameter PMV, Thermal Sensitivity, and Physiological Stress Levels (Tab. 1 is
Based on ´Relaxed Walking') (after VDI Guideline 3787 Bl. 2, VDI 1998)
Statistical Base
The total approach of the UBIKLIM climate model assumes that meteorlogical conditions in a given
climate area depend primarily on the following climate factors:

type of land use and settlement structure,

settlement density (building density of built-over area, population),

interactions between neighboring structures,

topography (altitude, location, exposure).
The starting parameters required for characterizing the initial meteorlogical data for Berlin, such as
degree of cloud cover, seasonal angle of the sun, and wind speed, were taken from observation
material of the German Weather Service (Deutscher Wetterdienst).
All basic parameters on land use and topographic altitudes were supplied from the data of the
Environmental Information System - EIS Berlin. The entire city was divided into grids of 50 x 50 m,
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except for the area within the inner City Rail Circle (S-Bahn), which was divided into a grid of 10 x 10
m.
The parameters used included:
 mean degree of sealing in % (cf. Map 01.02, SenStadtUm 1993a, 1996a),
 mean built-over share, in %,
 land use / urban structure types in 61 classes (cf. Map 06.07, SenStadtUm 1994b, 1996h),
 mean topographic altitude above sea level in meters (cf. Map 01.08, SenStadtUmTech 1998).
Building and vegetation heights were related to urban structure types by means of a reference file (FPK
1993).
Other information sources were descriptions of structure types; maps of Berlin at a scale of 1 : 5,000;
and aerial photography of the city.
This basic data had to be prepared and fitted to the input requirements of the model. Statements about
green areas were derived from descriptions in structure types. These areas were classified into not
greened (n), moderately greened (m) and parklike greened (p). The determination of the internal model
parameter for built-over areas, the `Number of Buildings per Grid´, used the exact property lot map of
Berlin in a scale of 1 : 5,000, as well as values derived from experience. The exact allocation of
individual mean built-over area parameters for urban structure types of the EIS Berlin are given in
Table 2.
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Tab. 2: Allocation of Mean Built-over Area Parameters into the Urban Structure Types of the EIS
Berlin
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Methodology
Basics of the UBIKLIM Procedure
An evaluation of climate in relation to humans can be based on the adaptative demands placed on the
organism by given climate conditions. Recommended for this analysis and evaluation is the human
energy balance model given in VDI Guideline, Bl. 2 3787 (mentioned above), the extended "Michael
Climate Model" (Klima-Michel-Modell) (Jendritzky et al. 1990). The PMV value of the model gives a
measure for thermal (heat and cold) stress on organisms in defined surroundings. "Michael" is the
name of a fictional average person, here assumed to be male, 35 years old, 175 cm tall, and to weigh
75 kg. The procedure calculates heat production caused by activity-dependent energy turnovers and
takes into consideration the heat insulation of clothing. The procedure then connects this with the
meteorlogical conditions responsible for heat loss. These conditions include air temperature,
humidity, wind speed, and short and longwave radiation fluxes.
PMV = f (H, Icl, tl, v, e, tmrt)
H
metabolic rate; 60 bis 300 W/m², e. g. a range from sitting still to walking quickly
(approx. 7 km/h)
Icl
heat insulation of clothing (0.5 to 1.5 clo, e. g. light summer clothing up to a suit and
jacket; 1 clo = 0,155 (m²  K)/W
Meteorological Parameters:
tl
air temperature
v
typical wind speed
e
water vapor pressure
tmrt
mean radiation temperature
The mean radiation temperature includes direct sunlight, diffuse radiation reflected by the sky,
shortwave reflection, the reflected radiation of the atmosphere, and the infra-red radiation of
surrounding surfaces.
The biometerological evaluation of urban climate used calculations of parameters important in the
human heat balance, including air temperature (tl), humidity (water vapor pressure) (e), wind
speed (v) and shortwave and longwave radiation fluxes (sr, lr) at a height of 1 meter above the
ground.
The UBIKLIM model initially produces an all-area model of the meteorological parameters mentioned
above, and it then conducts an evaluation analysis with the Michael Climate Model. The resolution of
the result fields is basically dependent on the type and resolution of the starting data. The ideal is 10 m.
This resolution enables maps to be produced up to a scale of 1: 10,000.
The comparison of statements was enabled by assuming a constant value for human clothing and
activity. The constant was defined as walking with an energy turnover of 116 W/m² in a light street suit
with a heat insulation of 0.9 clo.
There is a primary problem in the implementation of these model approaches. The problem is to obtain
suitable resolution (during the preparation) of the physiologically relevant meteorlogical fields at 1
meter above the ground. Measurement models or high-resolution numeric models usually require too
much effort and they are thus impractical for application to larger urban areas and to whole cities. They
require too much data collection and calculation time.
The UBIKLIM model is an expert system that manages with relatively little effort on data collection and
calculation time. A certain degree of detail precision is lost, but statements relevant to planning are
indeed made possible in regard to bioclimate quality and stress upon individual blocks and block
segments.
Respective to the input parameter land use it is assumed that the entire study area may be divided
into a clear number of areas with similar physical behavior. These areas are then classified; among
other things they include bodies of water, forests, parks, sealed and unsealed open areas, residential
areas and commercial/industrial areas. Built-up areas are further subdivided and clear characterized
according to their built-over area parameters (cf. Tab. 2). Differences between individual urban
structures can be worked out well with it, whereas an interpretation of the exact single grid is not
sensible. Questions of small-scale structures are better answered with other, more suitable, models,
such as MUKLIMO_3 (Sievers 1995) and MISKAM (Schädler et al. 1996).
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UBIKLIM Sequence Diagramm
The UBIKLIM Sequence Diagramm is portrayed in Fig. 3. First, the meteorlogical parameters are
calculated for each individual urban structure, independent of topography. These parameters include
air temperature, wind speed, humidity, and short and longwave radiation fluxes. This is done indirectly,
by way of the one-dimensional Microscale Urban Climate Model MUKLIMO_1 (Mikroskaliges
Urbanes Klimamodell) (Sievers et al. 1986). Indirectly, because more than 3,000 MUKLIMO_1
simulations regression equations are prepared on the basis of built-over area parameters. These are
then used in MUKLIMO to calculate the meteorlogical parameters.
Fig. 3: Sequence Diagram of the UBIKLIM Evaluation Procedure
The fundamental idea for the model treatment of constructions used in MUKLIMO_1, and thus in
UBIKLIM, is found in Gross, 1989. The concept uses the similarity of current flows between individual
buildings with the current flows of a gas, or fluid flows in a porous medium. It is not expedient to
describe such current flows in detail; it is described by mean values of variables with a sufficiently large
number of pores. The medium itself is described by average properties, such as porosity and flow
resistance.
MUKLIMO_1 considers built-over areas to be a porous medium that can be described by a few
mean parameters, and these parameters can be derived from the built-over area parameters of urban
structures.
Following this mean point of view, it is apparent that the buildings in the model concept are distributed
evenly throughout the area. They have a square ground form and the same building height. An
illustration is presented by this sketch:


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






The image of distribution changes according to differing built-over area parameters of individual areas,
if, for example, buildings are closer together, or if individual building lots are larger. The characteristics
of the spaces between the buildings is varied by means of the degree of sealing.
The use of regression equations gives a field for each meteorological parameter. Each area has a
uniform value determined only from the land use type, and not from the topography of the study area,
nor from the relationship of the individual areas to each other.
A reference is made to the respective topography in a second step by modifying these fields with
various methods. Altitude, exposure, and orography are taken into consideration.
The relationship of individual areas to each other is produced by a sliding mean that simulates the
balance flow from cold to warm. Experience is useful here, for it shows that the influence of
neighboring structures dissipates after 50 to 150 meters under weather conditions of slight winds. This
procedure is conducted for temperature, humidity, and wind distribution. This results in the initial
meteorlogical fields. These fields are then analyzed pixel for pixel with the Michael Climate Model.
This human biometeorlogical evaluation of the thermal environment is based on the heat balance of
the human body. The evaluation conducts a coupling of the comfort balance according to Fanger
(1972) with short and longwave radiation flux densities.
Validation of Model Results
As in all model applications, a verification of results given by the UBIKLIM model is necessary for the
portrayals in this report. This is possible with the following preconditions:
1. Several meteorlogical stations are maintained in Berlin. Their observations enable random
comparisons with model results.
2. The final results are expressed as PMV values and are not directly comparable because they are
derived from different parameters.
3. An intermediate product of the UBIKLIM application are the air temperature and wind speed
fields. These could be included for comparison with the observations of the Berlin stations.
The juxtaposition of temperature data from the model and from observations resulted in an initial
meteorlogical situation for the model. The starting point is a strongly radiant summer day with
maximum temperatures between 25 and 25.9 °C at the stations. Table 3 shows this comparison.
Tab. 3: Comparison of Hourly Values of Air Temperature from Measurements and Model
(Measurement Values for Radiant Energy Days with Maximum Temperatures between 25.0 and
25.9 °C) (DWD 1996)
The relatively small deviation between measurements and model in the 02:00 p.m. values is
conspicuous. It often amounts to only ± 0.5 K. The model has lower values of 1 to 2 K at 02:00 p.m.
only at the edge of the city, and in surrounding areas at the Berlin Buch and Schönefeld stations. The
04:00 a.m. model values are clearly below measurement values. That might be related to the greater
variability of daytime minimum temperatures. The model also tends to depict large not-built-up areas
as too cold; such as the Tempelhof and Schönefeld airports.
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On the whole, good agreement between calculation and measurements can be assumed. It must be
remembered in making comparisons that the UBIKLIM model is not entirely a mathematical model. It is
an expert model that includes the current knowledge of biometeorlogical analysis and evaluation, and it
uses these to good results.
The successful comparison with measurement results on summer days makes it possible to give
probabilities for the appearance of such situations during the summer half-year, as well as for
individual summer months, in a differentiated area-related portrayal.
The longterm average number of summer days in the center of Berlin is 35 to 45 (cf. Tab. 4). In most
of the city, including outer districts, 32 to 35 summer days are average.
The number of summer days can be considerably greater in some years. The hot summer of 1992 had
60 to 75 summer days.
Tab. 4: Number of Summer Days (Summer Days are Defined as Having Daytime Maximum Air
Temperatures of  25 °C; Normal Values for 1961-1990) (DWD 1996)
An allocation of these days into PMV classes, as depicted in the map, was made for the summer days
in Table 4. The heat stress depicted in the maps is thus the lower threshold. Heat stress on some days
(such as hot days, with temperatures  30 °C) may be considerably greater, depending on the
temperature.
Map Description
The maps depict the spatial distribution of heat stress intensities in Berlin during a late summer
weather situation of high radiant energy, expressed in PMV gradations. The depicted value gradations
are valid only for the evaluation of the fundamental meteorlogical conditions of summer days with
maximum temperatures of 25 °C. The color scale is arranged so that the intensity increases from
green to yellow to red. The intensity of each color gradation is 0.2 PMV.
Topography has little influence in Berlin because differences in altitude are minimal. The depicted
distributions are mainly marked by the arrangement of land use in the urban area, and the interactions
between various adjacent use types.
Interactions cause clear modifications, especially where many relatively small areas are differentiated.
It is to be basically assumed that a horizontal advection occurs from cold to warm, in the sense of an
equilibrium flow, and that the air streaming upwards above warm areas is replaced by cooler air. The
influence of neighboring structures dissipates at about 100 meters according to the model (cf.
Methodology). Even if the interactions are limited to a narrow boundary area, they prove to be very
effective as bioclimatic effects on well-being where numerous green areas are interlaced through builtup areas.
The heat island effect works spatially more comprehensively. In the model, it modifies the bioclimatic
conditions through the distribution of air temperature.
Bioclimate in the Daytime
The depicted distribution of thermal conditions for 02:00 p.m. is for daytime on a cloudless summer day
with weak winds.
The lowest PMV values are in forests, and in the direct vicinity of bodies of water. The factors for this
in forests are low radiation fluxes because of tree shelter, in conjunction with the relatively low air
temperature at the height of the tree trunks. Factors for low PMV by bodies of water are higher wind
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speeds over the flat surfaces of water, and cool air above the evaporating water surface.
A balancing effect in built-up areas, even if only in small parts, can be recognized where a body of
water directly borders an area, such as along the Spree river.
The relative stress intensity in park facilities is also small, even though the PMV values are about 0.4
higher than in forests. The effects correspond to those in forests, in weaker form.
Unsealed open areas can be assumed to have higher PMV values than parklike areas because solar
radiation has unlimited access. Only the relatively greater wind speed hinders an even greater increase
of thermal stress.
In contrast, the air over sealed open areas, such as squares and streets (e.g. the Avus motorway), is
clearly more heated. But here the wind finds less surfaces to work upon than in meadows and fields.
The wind blows completely unhindered and is, finally, responsible for the fact that only a minimally
higher stress level is found here than in unsealed open areas.
Similar conditions prevail around railway tracks, although the wind does not quite reach the same
speed as over asphalt. But the wind over these areas compensates to a certain degree for the stress
effects of high air and radiation temperatures. The heat stress intensity is at a medium level, slightly
above sealed open areas.
Built-up areas have the greatest stresses. In general, loads increase with building density because
air in the spaces between buildings is more strongly heated and the average wind is weak. Shortwave
radiation influences are decreased at the same time, but they are almost completely compensated for
by increased longwave radiation fluxes.
Greening measures with trees sink thermal stress in built-up areas. The relief is effected by the
reduction of radiation fluxes, particularly the shielding of direct solar radiation. This effect overweights
the reduction of wind speed by the trees which, by itself, would effect an increase of thermal stress.
The best conditions are found in loosely built-up residential areas with parklike greening.
Industry and commercial areas are marked in many cases by a few large buildings and large sealed
surfaces. The result is good, rather unhindered ventilation which keeps stress values from increasing,
in spite of high degress of sealing, as much as in residential built-over areas that are highly sealed.
Parks, forests, and water are structures that contribute to a favorable bioclimate. These structures
are effective, even when they are narrowly limited in the surrounding built-up area. Noteworthy is the
occasional small-area behavior of transitional zones between land uses of differing thermal behavior,
such as between open areas of medium thermal stress, and forests with lesser heat stress. Stress
increases directly at the forest edge, on open areas, because the radiation fluxes are high there, but
wind has been reduced by the `raw´ forest. The wind, even if weakened, which enters the forest edge
from the open areas provides for minimal heat stress where the shadows greatly reduce radiation
fluxes.
Transitions between water and forest in Berlin are particularly frequent and conspicuous. The thermal
situation is most favorable at forest edges for the reasons given.
This leads to the statements:
The Bioclimate map shows an increase in thermal stress from the slightly stressed edge of the city
towards the city center, where the highest heat stress intensities are concentrated. This means that, on
a summer day, the outer districts average a moderate stress, and the city center area is uniformly
highly stressed.
A comparison with land use shows that the city periphery is dominated by water, forests, open areas,
and loose, greened built-up areas. These have an equalizing effect. In the direction of the city center,
green areas become fewer and building density increases. This is clearly depicted in the map of urban
structure parameters (cf. Map 06.07, SenStadtUm 1994b, 1996h).
The 100 km² area of the city center has a very high degree of sealing, approximately 80 to 100 %.
The outer districts have a 30 to 40 % degree of sealing. The built-up area of the city center is also high,
at 40 to 70 %, compared to the outer districts at 20 %. The consequence is a large stress complex
broken by single, smaller, and scattered green areas, such as cemeteries and parks; and broken by
the larger Spree river, the Landwehrkanal navigation canal, the Große Tiergarten park, and the
Tempelhof airport with the adjoining Hasenheide park. There is a compact area of 12 km² in the
boroughs of Charlottenberg and Wilmersdorf that has calculated PMV values up to 3.0. That means a
strong thermal stress on a summer day. The minimum values for a summer day are depicted; that
means an extreme stress must often be counted on at that location. Alternatives for relief are seldom
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or do not exist at all. These districts are to judged as especially problematic from a bioclimatic
perspective.
Thermal stress highpoints are also concentrated in the districts of Kreuzberg, Moabit, Prenzlauer Berg,
and Mitte. Areas with more favorable bioclimate are easier to find here in these districts.
Emphasis must be given to the manner that various green areas are integrated into built-up areas in
the northeast of the city, from the districts Weißensee to Mitte to Prenzlauer Berg. These green areas
are parks, cemeteries and sport facilities. This interlocking juxtaposition effects a continuous change of
bioclimates. Even though very high stress intensities do occur, the bioclimate is to be regarded as
positive because of the vicinity to relief areas.
It can generally be said that a multiplicity of smaller park facilities integrated scattered through builtup areas have advantages compared with larger parks, from a bioclimate viewpoint. The smaller
facilities, relative to their size, present more boundary surface to built-up areas. This enables more
effective relief through interactions.
A similar favorable effect is provided by the flowing waters of the Spree river and Landwehrkanal
navigation canal. They interrupt the stress complex straight through the entire city center. The bank
areas are relieved by interaction.
The Große Tiergarten park has a size of 220 hectares and is the most significant large open space in
the Berlin urban area. It is of great importance for bioclimate conditions in Berlin. Firstly, the thermal
surrounding conditions are more than 1 PMV better than in the surrounding built-up areas. Secondly, it
breaks up the stress complex of the city center and hinders the complete conglomeration of the city
center into a single stress complex. It also hinders the formation of a unified heat island in conjunction
with the bordering areas of the former diplomatic quarter, the Gleisdreieck railway area, and the
Suedgelande area. Thirdly, its central location makes it easy to reach from all city center districts. The
populations of these districts can use it as a valuable alternative for a thermally pleasant surrounding.
Thermal conditions improve markedly towards the edge of the city. There is a noticible decrease in
the degree of sealing and built-up areas. Parklike or at least partially greened built-up areas dominate
in the outer districts. The heat stress intensities are often around 0.8 PMV lower than in the city center.
Some parklike, greened residential areas have more favorable bioclimate conditions than are found in
open fields. Large areas of such locations are in the Lichterfelde and Pankow districts. There are also
good bioclimates in settlements at the edge of the city in Gatow, Kladow, Müggelheim, and Rahnsdorf.
Very high heat stress intensities can occur in the outer districts, but peak stresses are reached only
at small local points. Some old city cores (locations of the original settlements that later became
Berlin's boroughs) stand out against their surroundings, such as in Tegel and Spandau; or in other city
quarters like Tempelhof and Lichtenberg. Their greater degrees of sealing and built-up areas are also
conspicuous.
High-rise residential settlements, such as in Hellersdorf and Marzahn, and the large settlement
complexes in West Berlin, the Gropiusstadt and Märkisches Viertel, are also sites of relatively high
stress intensities.
Industrial areas are found in the entire urban area but are more concentrated along the Spree river
and in the Tempelhof and Lichtenberg/Marzahn districts. They show no uniform situation, it depends
on their degree of sealing and built-up area levels. The mean thermal stress is less than in dense
residential built-over areas of the city centers, but higher than in the loose residential building density of
the outer districts.
The distribution of heat stress in Berlin is primarily influenced by built-over areas, but the large water
and forest areas in the west and southeast are important factors in the total situation. These wide
areas have 1 to 1.5 lesser PMV values on a cloudless summer day. Their positive effect remains
primarily limited to narrow boundary zones, effecting interaction with adjoining areas.
In the southeast, on both sides of the Spree river, there are smaller forest areas that reach into the city
up to the Rummelsberger Bucht. These forests touch built-up areas again and again. There are highly
variable and positive bioclimate conditions in these areas.
Bioclimate at Night
The map for 04:00 a.m. depicts distribution of the relative heat stress intensities expected in a
cloudless summer night with weak winds.
The differences in air temperature are greater than during the day, but stress intensities have smaller
ranges. This is because shortwave radiation fluxes, which are strongly modified by settlement
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structures, are lacking, and because average winds at night are considerably weaker.
Lesser stress intensities are to be expected over unsealed open areas like lawns, meadows, and
fields. Causes are the completely unhindered emissive radiation accompanied by the cooling air.
Sealed open areas like streets and squares have slightly higher mean PMV values.
Stress intensities over water are about 0.6 PMV higher than over fields. This is caused by the
negligible cooling of the water surface, which dampens the daytime amplitudes of air temperature and
longwave radiation. Relatively high air and radiation temperatures thus compensate for the cooling
effect of the relatively high wind speeds over water.
The highest thermal stresses occur in densely built-up areas with very high degrees of sealing. The
high stresses are caused by the relatively slight cooling of air in the spaces between buildings, and the
high radiation temperatures - and that with large building volume and limited horizon. Thermal stress
sinks with decreasing building volume. But fairly high heat stresses can form even in relatively slightly
built-up areas; when numerous trees hinder radiation emission and hinder wind between the buildings.
Commercial and industrial areas often have large open spaces which promote radiation emission.
These area have relatively low PMV values.
Stress levels are high in park facilities where trees hinder radiation emission, similar to the mean in
commercial areas. Forests can even be expected to have values of 0.2 PMV higher, even though the
air temperature is sometimes clearly lower than in the city center.
Here a more detailed description:
The city center area within the City Rail Circle (S-Bahn) also has the highest thermal stress during the
night. The unfavorable conditions are concentrated in the boroughs of Wilmersdorf/Charlottenburg,
Prenzlauer Berg, and Kreuzberg/Neukölln. The stress complex is loosened by the Große Tiergarten
park, smaller green facilities, and some not so densely built-up areas, such as around the
Alexanderplatz square. The thermal situation here shows medium stress. Particularly striking are the
low PMV values at the airports. This is to be expected because of the unhindered radiation emission.
The outer districts present a different picture by night than by day. Basically they are marked by three
heat stress classes. The forests, mainly in the west and southeast of the city, cause comparatively high
values. The open areas have the lowest PMV values. The difference is 1 PMV. The stress intensity of
other areas ranges between these two values.
Only the open areas in the northeast, and west of Gatow have a larger size. Open areas are otherwise
found in smaller sizes, such as sports fields, scattered throughout the outer urban districts, and here
these open areas cause minimal stress intensities.
Stress intensities in built-up areas vary up to 0.5 PMV, according to building type, as in Lichtenrade
compared to single areas in Spandau or Friedrichsfelde. Heat stress intensities remain relatively high,
about that typical for forests, only in individual densely built-up areas. About the same is to be expected
in loose, parklike, greened residential areas, such as in Lichterfelde-West, where trees hinder
nocturnal upgoing radiation.
Values in the high-rise residential settlements are around 0.2 to 0.3 PMV lower. Good upward radiation
is enabled by a negligible tree population and open spaces of 70 to 80 %.
Loosely built-up areas with moderately dense tree growth have the least nocturnal stress, as in
Lichtenrade.
The old city cores are prominent on the bioclimate map during the day, whereas at night they are only
faintly discernible. This is caused by the relatively large size of non-built-up areas, which favor upward
radiation.
Water has a high heat storage capacity, so the diurnal (day/night) temperature differences are slight.
There is a continuous reduction of perceivable heat because these sites are open to the wind (at least
the larger bodies of water) and there is regular evapotranspiration. Bodies of water thus show similar
conditions at night as in the day, with PMV values in the "slight heat stress" range of 1.3.
Industrial and commercial areas are distributed throughout the entire city. Their thermal values are
usually moderate or even low, and not conspicuous at night. Only where building density is very high,
as in Lichtenberg, must high thermal stress be assumed at night too.
According to Givoni, 1989, human thermal stress at night is important because good, recuperative
sleep is only possible under favorable thermic conditions. Such a sleep enables thermic stress to be
12
better dealt with on the following day. This means that strong stress during the day must be regarded
as amplified to the degree that nocturnal cooling is prevented. An interpretation of the 04:00 a.m. map
always must be viewed in the context of the distribution of heat stress during the day.
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Bahr, R.-M. 1959:
Geschichte der meteorologischen Beobachtungen der Stadt Berlin, Dissertation am Institut für
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Urban Design in Different Climates, WMO/TD-No 349, WCAP-10, Geneva
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13
[16] Sievers, U.; Zdunkowski, W. 1986:
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Umweltatlas Berlin, aktualisierte und erweiterte Ausgabe, Bd. 1, Karte 01.02 Versiegelung,
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Umweltatlas Berlin, aktualisierte und erweiterte Ausgabe, Bd. 2, Karte 04.02 Langjähriges Mittel
der Lufttemperatur 1961-1990, 1 : 50 000, Berlin.
[21] SenStadtUm (Senatsverwaltung für Stadtentwicklung und Umweltschutz Berlin) (Hrsg.)
1993c:
Umweltatlas Berlin, aktualisierte und erweiterte Ausgabe, Bd. 2, Karte 04.04 Temperatur- und
Feuchteverhältnisse in mäßig austauscharmen Strahlungsnächten, 1 : 50 000, Berlin.
[22] SenStadtUm (Senatsverwaltung für Stadtentwicklung und Umweltschutz Berlin) (Hrsg.)
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Umweltatlas Berlin, aktualisierte und erweiterte Ausgabe, Bd. 2, Karte 04.05 Klimazonen,
1 : 50 000, Berlin.
[23] SenStadtUm (Senatsverwaltung für Stadtentwicklung und Umweltschutz Berlin) (Hrsg.)
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Umweltatlas Berlin, aktualisierte und erweiterte Ausgabe, Bd. 2, Karte 04.06
Oberflächentemperaturen bei Tag und Nacht, Berlin.
[24] SenStadtUm (Senatsverwaltung für Stadtentwicklung und Umweltschutz Berlin) (Hrsg.)
1993f:
Umweltatlas Berlin, aktualisierte und erweiterte Ausgabe, Bd. 2, Karte 04.07 Klimafunktionen,
1 : 50 000, Berlin.
[25] SenStadtUm (Senatsverwaltung für Stadtentwicklung und Umweltschutz Berlin) (Hrsg.)
1994a:
Umweltatlas Berlin, aktualisierte und erweiterte Ausgabe, Bd. 2, Karte 04.03 Bodennahe
Windverhältnisse, Berlin.
[26] SenStadtUm (Senatsverwaltung für Stadtentwicklung und Umweltschutz Berlin) (Hrsg.)
1994b:
Umweltatlas Berlin, Bd. 3, Karte 06.07 Stadtstruktur, 1 : 50 000, Berlin.
Digital Maps
[27] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1996a:
Umweltatlas Berlin, digitale Ausgabe, Karte 01.02 Versiegelung, 1 : 50 000, Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei102.htm
[28] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1996b:
Umweltatlas Berlin, digitale Ausgabe, Karte 04.02 Langjähriges Mittel der Lufttemperatur 19611990, 1 : 50 000, Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei402.htm
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[29] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1996c:
Umweltatlas Berlin, digitale Ausgabe, Karte 04.03 Bodennahe Windverhältnisse, Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei403.htm
[30] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1996d:
Umweltatlas Berlin, digitale Ausgabe, Karte 04.04 Temperatur- und Feuchteverhältnisse in
mäßig austauscharmen Strahlungsnächten, 1 : 50 000, Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei404.htm
[31] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1996e:
Umweltatlas Berlin, digitale Ausgabe, Karte 04.05 Klimazonen, 1 : 50 000, Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei405.htm
[32] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1996f:
Umweltatlas Berlin, digitale Ausgabe, Karte 04.06 Oberflächentemperaturen bei Tag und Nacht,
Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei406.htm
[33] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1996g:
Umweltatlas Berlin, digitale Ausgabe, Karte 04.07 Klimafunktionen, 1 : 50 000, Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei407.htm
[34] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1996h:
Umweltatlas Berlin, digitale Ausgabe, Karte 06.07 Stadtstruktur, 1 : 50 000, Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei607.htm
[35] SenStadtUmTech (Senatsverwaltung für Stadtentwicklung, Umweltschutz und
Technologie Berlin) (Hrsg.) 1998:
Umweltatlas Berlin, digitale Ausgabe, Karte 01.08 Geländehöhen, 1 : 50 000, Berlin.
Internet: http://www.stadtentwicklung.berlin.de/umwelt/umweltatlas/ei108.htm
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