Temperature in Medium Low-exchange Nocturnal Radiation Periods 2000
Due to the differences in available data, the climate parameters were calculated separately for West Berlin and East Berlin/surrounding countryside. However, the calculation procedures were largely identical. Since all calculation steps had to be conducted for East Berlin and the surrounding countryside, the procedure will be outlined briefly using the example of the parameter temperature.
East Berlin and the Surrounding Countryside
Of central importance for the different calculation steps is the assignment of individual measurement points to continuously measuring climate stations and/or to measurement points which were repeatedly visited during measurement trips. In addition, it was assumed that the temperature course at the climate station and/or the repeatedly visited measurement points, could be extrapolated to other measurement points.
Using this assignment, the various measurements from a trip could be synchronized, i.e. referenced to a given point in time (see Stülpnagel 1987). Subsequently, the mean of the results from the measurement trips was obtained for each measurement point. For the weighting of the individual trips, the weather statistics from May through September 1991 for Berlin-Dahlem were applied (Institute for Meteorology of the FU Berlin 1991): The individual measurements were weighted for wind direction, wind speed and degree of cloud cover at measurement time, and its proportion of overall weather conditions during all low-exchange nocturnal radiation periods in the period May through September.
To derive the mean conditions in low-exchange nocturnal radiation periods during the summer semester of 1991 from the results of the measurement trips, the results from the climate stations were again applied. The sorting of the measurement points from each of the measurement trips into the corresponding climate station structure was done step by step according to a procedure described in detail by Stülpnagel 1987. It can only be described briefly here.
First, the measurement points adjacent to a climate station were considered. Regression equations were developed empirically in order to derive the temperature of the climate station at the respective adjacent point. The data from each measurement trip was compared with the simultaneous data of the station, and as a linear function of the temperature difference between the station to the central station in the Great Tiergarten at the respective point in time. The adjacent measurement points for the period under examination could be projected using these equations.
Thus, a network of “fixed points” emerged which could be used for the projection of the remaining measurement points. In this way, measurement routes which passed several climate stations, for which several fixed points emerged, were broken down into segments extending from one fixed point to the next. The projection for the intermediate measurement points was calculated by extrapolating the measured temperature course between the fixed points and the measurement points to be calculated onto the projected course at the fixed points. That means it was assumed that in case of an expansion or compression set of temperatures at the fixed points, a corresponding expansion or compression set would be undertaken at the measurement points. This process was expanded gradually to all further measurement points, whereby common points on already adjusted routes were treated as new fixed points.
At the conclusion of the process, the extrapolated temperatures for each measurement point of each route had been calculated for the investigation period. The large-scale depiction was obtained by means of manual interpolation, taking into account land use (SenStadtUm 1993b, c).
The projections for relative humidity and vapor pressure, which were needed for the calculation of equivalence temperature, were generated analogously.
For the western part of the city, the temperature distribution under low-exchange weather conditions was essentially adopted from the first edition of the Environmental Atlas. However the temperature level was lowered by about 1 °C, on the basis of a comparison of the mean values for the summers of 1982 and 1991 at the climate station in Berlin-Dahlem, and the assumption that a general reduction by this amount for all measurement points would be justified. The only deviations from this procedure involved new measurement trips when they crossed into areas of West Berlin.
Update of Data Base in 2000
For the update of the climate maps of the Environmental Atlas, the temperature ranges were not newly calculated, but rather were entered into the maps of the Environmental Atlas. For this purpose, the temperature data from the measurement trips were scaled to and compared with the results of the 1993 version. The scaling permits the comparison of the cooling of different measurement routes and weather situations. A scaled temperature of 1 means that in comparison with a reference point, no cooling takes place in the overheated city center. The lower the scaled temperature, the stronger the cooling is. The scaled temperatures were then entered into the existing temperature classes. Fig. 3 shows the breakdown of scaled temperatures for a measurement route in northeastern Berlin. The deviations between the measurements of 1999 (blue curve) and the 1993 breakdown (green curve) can be clearly seen around the development areas of Buchholz and Karow. The methodology and the results are described in detail in Stoffregen, H. 2000.
The scaled temperature is calculated according to the following formula:
Ts: Scaled temperature of the measurement point [-];
TMessung: measured, time-corrected temperature of the measurement point [°C]; TMitte: mean temperature in the area Unter den Linden/ Friedrichstrasse (time-corrected) [°C;];
and DTMessnetz: Difference between daily minimum values of the TU measurement network [°C].
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Temperature and Moisture Conditions
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