Climate Control Scenarios [1971 – 2000]

A number of strategies to analyse climate data series have been outlined in the methodology (3.4). For the analysis of the control scenario data series referred to the observed data series of the same time period from 1971 to 2000, two approaches have been applied. First a comparison of average climate data series (temperature, precipitation, potential evaporation) of hydrological year periods has been performed, and secondly a comparison of probability distributions of extreme rainfall events has been worked out.

5.3.1.1 Average Climate Data Results

For the comparison of computed temperature time series with observed data series, the average temperature of the yearly, summer and winter sequences are calculated.

For the comparison of the difference in precipitation and potential evaporation, the average sums have been computed. The results of the differences are summarized in Table 5. 2 in [°C] and [%]¹ respectively.

Table 5. 2 Results of the comparison between observed and REMO control scenario data series.

Average over time

observed data series 13.9°C 440.9mm 437.4mm control scenario (C20) 13.8°C 565.5mm 464.8mm Difference (%) - 0.4% + 22.0% + 6.3%

winter

observed data series 5.4°C 372.6mm 178.4mm control scenario (C20) 4.5°C 443.3mm 144.8mm

Difference (%) - 16.7% + 16.0% -18.8%

yearly

observed data series 9.7°C 813.5mm 615.7mm control scenario (C20) 9.2°C 1008.8mm 609.5mm Difference (%) - 5.0% + 19.4% -1.0%

Temperature:

The average observed temperature of the summer period is 13.9°C between 1971 and 2000, which is 0.1°C higher than the average computed summer temperature (13.8°C). The average observed temperature of the winter period is 5.4°C and the computed REMO data display an average temperature of 4.5 °C, the difference between the data sets is 0.9°C. The yearly average temperature measured at the

1 The percentage rates are calculated in relation to the results of the observed data series.

gauging stations is 9.7°C. This is 0.5°C higher than the yearly average temperature computed by the climate model REMO (9.2°C).

Precipitation:

An average precipitation of 440.9mm has been observed during the summer periods between 1971 and 2000, whereas the average precipitation computed with the climate model is 565.5mm and therewith 22% larger. The difference of the average winter precipitation between the observed (372.6mm) and computed data series (443.3mm) is less significant with 16%. The observed average yearly precipitation is 813.5mm, and the computed average yearly precipitation of the climate model REMO is 1008.8mm, which is 195.3mm (19.4%) higher than the observed data.

Potential Evaporation:

A difference of 6.3% has been calculated between the average summer evaporation of the observed data series (437.4mm) and the control scenario data (464.8mm). This difference is reasonable due to the displayed positive difference in precipitation rate (22%) and the low positive difference in temperature (0.4%), whereas the evaporation rate depends to a larger degree on the temperature. It can be assumed that the generation of runoff and drainage simulated with the control scenario data series will be higher than with the observed data series in the summer periods.

Although the computed average precipitation in the hydrological winter sequence is larger (16%) the computed average evaporation is lower by about 18.8%.

This is derived by the computed lower temperature (16.7%) in the winter period, which has a high effect on the evaporation. It can be assumed as well that the computed runoff and drainage with the REMO control scenario data will be higher referred to the use of observed data series. The average yearly observed evaporation is 615.7mm which is 1.0% higher than the control scenario C20 evaporation (=609.5mm).

It is expected that the overall runoff and drainage volume simulated with the model Kalypso Hydrology will be higher with the REMO control scenario data than with the observed data series for the time period 1971 to 2000.

5.3.1.2 Statistical Evaluations of Rainfall Events

It is required to calculate probability distribution curves of extreme rainfall events with observed as well as computed climate model data series. The results are post-processed later on to compute the magnitude of climate change impacts, CCFs as well as design rainfall events.

The analysis of probability distributions of extreme rainfall events have been done with hourly and daily data series. The statistical evaluations are worked out according to the approach defined in 3.4. After testing the independency of the rainfall events, a trend adjustment of the data series from 1971 to 2000 (M = 30) has

been done for each hydrological year period (yearly, summer, winter) with a partial series of a number of N = e*M ≈ 82 rainfall events.

In attachment 8 the results of the trend adjustments are illustrated according to the hydrological year sequences. In the summer periods no significant trend is displayed in the data series of the observed rainfall events, but in the REMO data series a significant decreasing trend towards the year 2000 is illustrated. This decreasing trend is distinguished for the first realisation of the REMO model run and has been detected as well in the UFOPLAN report (Jacob et al., 2008). The winter sequences of the observed and the REMO C20 data series of rainfall events illustrate an increasing trend towards the year 2000. The yearly series mainly comprise larger summer rainfall events. Therefore a similar decreasing trend in the REMO C20 data series and no trend in the observed data series are displayed.

With the trend adjusted data series, the statistical evaluations according to the approach described in the attachment 3 have been worked out. The applied correction factor for the observed data series is 1.03, due to a temporal aggregation of 4 intervals (each 15minutes) for hourly data series. For climate model data series a correction factor of 1.14 has to be defined. After the first statistical evaluations of the observed and computed REMO C20 data series, three outliers have been identified in the hourly and four outliers in the daily data series. The results of the Grubbs Tests are illustrated in Table 5. 3.

Table 5. 3 Results of the Grubbs Test with the observed and REMO control scenario data series of extreme rainfall events.

In the hourly data series, computed with the climate model, the rainfall event with an intensity of 33.37mm/h on the 11^th September 1975 is not adequately displayed in the statistical evaluation; therefore it had to be neglected. The defined outlier on the

5^th September 1973 (29.55mm/h) with a lower difference between the acceptable value according to DIN 53 804 of ΔG = 0.49 is adequately displayed in the statistical evaluation with a return period of about once in 50 years (T = 50a). In the observed hourly data series an outlier has been defined as well with the Grubbs Test, but it is adequately represented in the statistical evaluation with a return period of about once in 100 years (T=100a).

In the daily data series an outlier in each of the winter and summer sequences have been defined. Both outliers defined in the computed control scenario data series with REMO are not displayed adequately in the statistical evaluation. In contrast to this, the outliers defined in the observed data series are represented with an adequate higher probability of occurrence. The rainfall events in the summer period (76.63mm/d) and in the winter period (49.34mm/d) are both displayed with a return period of once in 125 years.

After the Grubbs Tests, the trend adjustment has been repeated and the final results are displayed in the attachment 8 according to the period of the hydrological season (summer, winter, yearly) and the duration of the rainfall (daily, hourly). With these data series the final probability distribution curves have been calculated which are transferred to graphs, which illustrate directly the return period T in years. The rainfall intensities with a specific return period are displayed in tables for each hydrological season and duration (daily, hourly) respectively in the attachment 8.

The difference in percentage is referred to the observed data series.

For the short term hourly rainfall intensities the differences are higher than the differences in daily rainfall intensities. The differences cover a range of about 3%

(T=1a) to about 40% (T=100a) in the summer and yearly rainfall intensities (Fig. 5. 3 and Fig. 5. 4). The differences in the winter rainfall intensities increases from about 3% for higher probabilities of occurrence (T =1a) to a difference of about 20% for

100year events (T=100a). _{[ ]}

0 5 10 15 20 25 30 35 40

0 50 100 150 200 250

Return Period T [a]

REMO C20 Data Series Observed Data Series REMO C20 Hourly

Data Series

Observed Hourly Data Series

Rainfall Intensity [mm/h]

Empirical Distribution

Fig. 5. 3 Probability distribution curves of hourly extreme rainfall events [mm/h] in the summer periods.

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