Regional analyses of atmospheric conditions that may cause flooding of important transport infrastructure (railway tracks, highways/roads, rivers/channels) and subsequent adaptation measures are part of topic 1 of the network of experts initiated by the German Federal Ministry of Transport and Digital Infrastructure (BMVI). As an example case study, the December 2014 flood in Schleswig-Holstein, Germany, was investigated. Atmospheric conditions at the onset of the flood event are described and evaluated with respect to the general weather circulation, initial wetness, and event precipitation. Persistent, predominantly westerly general weather circulations (GWCs) directed several low-pressure systems over the North Sea to Schleswig-Holstein during December 2014, accompanied by prolonged rainfall and finally a strong precipitation event in southern Schleswig-Holstein, causing several inland gauges to exceed their, by then maximum, water levels. Results show that the antecedent precipitation index (API) is able to reflect the soil moisture conditions and, in combination with the maximum 3-day precipitation sum (R3d), to capture the two main drivers finally leading to the flood: (1) the initial wetness of north-western Schleswig-Holstein and (2) strong event precipitation in southern and eastern Schleswig-Holstein from 21 to 23 December; at the same time, both indices exceeded their respective 5-year return periods. Further, trend analyses show that both API and R3d have been increasing during recent years, while regional patterns match the north-eastward shift of cyclone pathways, leading to a higher risk of flooding in Schleswig-Holstein. Within the network of experts, investigations of these and further indices/drivers for earth system changes (e.g. wind surge and sea level rise) derived from observations, reanalyses, and regional climate model data are planned for all German coastal areas. Results can be expected to lead to improved adaptation measures to floods under climate change conditions wherever catchments have to be drained and infrastructures and ecosystems may be harmed.
In December 2014, predominant westerly general weather circulations (GWCs)
caused a major Baltic inflow (MIB) event (see, e.g., Lehmann et al., 2016; Post
and Lehmann, 2016). At the same time, persistent rainfall in combination with
an extreme precipitation event from 21 to 23 December led to the flooding of
several catchment areas in Schleswig-Holstein, Germany, located between the
North and Baltic seas. Both events mark independent atmospheric and hydrologic
responses to the GWC, illustrating the importance of interdisciplinary
research in this area. In this regard, the region Schleswig-Holstein is a
potent “blue spot” dealing with multiple drivers for earth system changes
in the North and Baltic seas region. It is affected in many ways by extremes,
especially under climate change conditions: (1) considerable areas in the
southern parts lie beneath sea level and have to be drained artificially; (2)
long-lasting and heavy rainfall events lead to increased flooding possibility
in economically relevant parts of the country. The North and Baltic seas
Canal (NOK;
The physical conditions of the North Sea control both meteorology and hydrology in northern European coastal regions (see, e.g., Attema and Lenderink, 2014): dominant factors are the actual wind and water levels – including future sea level rise – and the predominant GWC. According to Randall et al. (2007), large-scale and prolonged extreme events result from a persistent GWC in conjunction with air–sea interactions (and air and soil). These interactions are of particular importance for coastal areas. Hydrological extremes, like flooding events, are thus caused rather by unusual and unfavourable combinations of different influencing factors than by extremes of these factors themselves (Klemes, 1993). For instance, storm surges in combination with heavy but not extreme rain fall may lead to problematic drainage situations due to high seaward water levels (see, e.g., Wahl et al., 2015). According to investigations by Kew et al. (2013) conducted in the Rhine delta, the probability of extreme surge conditions following extreme 20-day precipitation sums is even 3 times higher than estimated from treating extreme surge and discharge probabilities independently. Also, a combination of initial catchment wetness and a single heavy yet not extreme precipitation event alone may lead to flooding. Berthet et al. (2009) and Pathiraja et al. (2012) show that catchment wetness is actually a crucial parameter in flood forecasting. Given the difficulties in estimating the catchment wetness, arising from inadequate records of soil moisture conditions (e.g. Albergel et al., 2013), Woldemeskel and Sharma (2016) point out the role of antecedent precipitation as a surrogate variable for any flood assessment under global warming conditions.
In the following, the observed situation, predominant GWC, and precipitation
indices describing soil moisture condition and event precipitation are
investigated for the December 2014 flood in Schleswig-Holstein, Germany. An
extensive evaluation concerning the hydrology based on catchment gauge data
has already been undertaken by the Landesbetrieb für Küstenschutz,
Nationalpark und Meeresschutz Schleswig-Holstein (LKN–SH) and the Landesamt
für Landwirtschaft, Umwelt und ländliche Räume
Schleswig-Holstein (LLUR–SH) in a separate report (LKN–SH and LLUR–SH,
2015). Therefore, the focus of this paper lies on the atmospheric conditions
leading to the flood. The aim is to show that (1) the method of Schröter
et al. (2015) to classify nationwide flood events can be applied on a
regional scale and that (2) the indices used, namely the antecedent
precipitation index (API) and 3-day precipitation sum (R3d), can add useful
information about changing local flood regimes in a warming climate. Evidence
is presented by investigating the significant trends in recent
years. Within topic 1 of the network of experts of the German Federal
Ministry of Transport and Digital Infrastructure (BMVI,
The remainder of this paper is structured as follows: first, data and methods (Sect. 2) are described. An evaluation of the atmospheric drivers leading to the December 2014 flood and a discussion of the findings are offered in Sect. 3. Finally, concluding remarks are given in Sect. 4 and an outlook in Sect. 5.
Two different objective GWC classification
methods were compared to describe the situation in Schleswig-Holstein (SH) during December 2014:
(1) the modified Lamb weather types (LWTs; Jenkinson and Collison, 1977) used
at the Federal Maritime and Hydrographic Agency (BSH; Löwe, 2005)
with a model centre over the central North Sea, and (2) the objective
classification (OWTC; Dittmann et al., 1995; Bissolli and Dittmann, 2001) of
the German Meteorological Service (DWD) with a model centre over central
Germany. Further differences are the input parameters: while LWT is based
solely on sea level pressure data, here the NCEP/NCAR Reanalysis 1 (Kalnay et
al., 1996), at 16 grid points over northern Europe, OWTC input data include
air pressure, temperature, wind, and water vapour content on different height
levels derived from the current operational GME (Global Model Extended) of
DWD (
Schröter et al. (2015) have investigated 76 nationwide flood
events that affected at least 10 % of the German
river catchments over a period from 1960 to 2009 and ranked them concerning their severity. Further included were the
floods from 1954 and 2013 (Blöschl et al., 2013). The investigations
are based on the data set from Uhlemann et al. (2010) using time series of daily
mean discharge records at 162 gauge stations of the German Water and Shipment
Administration (WSV) and the German Federal Institute of Hydrology (BfG).
Additionally, Schröter et al. (2015) used daily precipitation sums from
the REGNIE data set (see, e.g., Rauthe et al., 2013) provided by DWD with a
spatial resolution of 1
Both indices were calculated using REGNIE's daily precipitation sums for the
December 2014 flood. The constant
Furthermore, the Matlab toolbox WAFO (WAFO-group, 2000) was used for the statistical evaluation: according to Schröter et al. (2015), the yearly maximum 3-day precipitation sums and the respective 30-day antecedent precipitation were calculated at each REGNIE grid point. Then, 5 to 100-year return periods (5–100yRPs) were derived at each grid point using the Gumbel distribution over the base period 1960–2009.
Mean trends above the 95 % significance level for the five highest R3d (R3dfivemax) and API (APIfivemax) values per year were calculated over 30-year running intervals from 1960–1989 to 1985–2014 for the Kiel Canal catchment (EZG NOK), SH, and all of Germany (D). Instead of the yearly maximum alone, the five highest events per year were chosen so as to obtain more reliable and robust statistics. A modified version of the Mann–Kendall test (see Hamed and Rao, 1998) was used to determine significant trends, avoiding misleading results due to autocorrelation (in case autocorrelation is greater than 0). All trends were calculated at each grid point separately. Then, area means were derived.
Results from gauge data from the LKN–SH and LLUR–SH (2015) report will also be presented to investigate the applicability of the chosen precipitation indices. A map showing maximum water levels at all catchment gauges in Schleswig-Holstein during the December 2014 flood is kindly provided by Thomas Hirschhäuser (LLUR–SH). Furthermore, in-depth analyses of the hydrological situation including discharges and statistical evaluations can be found in the LKN–SH and LLUR–SH (2015) report. The most relevant results are presented in Sect. 3.6.
The December 2014 was dominated by westerly GWCs lasting for several
weeks. Therefore, a number of low-pressure systems were led from the North
Atlantic over northern Europe in quick succession. As an example, the systems
Alexandra and Billie (11/12/2014), both characterized by wet maritime air and
stormy conditions with gusts from 17 to 28 m s
Sea level pressure prediction for Thursday, 11 December 2014, showing the low-pressure systems Alexandra and Billie in quick succession.
Image credit: FU Berlin,
Modified Lamb weather types (LWT; BSH) and objective classification (OWTC; DWD), December 2014. Letters in the LWT column indicate the following from left to right: the classified weather type, cyclonality index (A or C), predominant wind direction at ground level, and gale index. Characters in the OWTC column indicate the following from left to right: weather type number, predominant wind direction at 700 hPa, cyclonality (A or Z) at 950 and 500 hPa, and humidity index (T or F). LWT gale indices are printed in italic (gale) and bold and italic (severe gale) letters; OWTC wet weather types are given in bold letters. “NUL” indicates no gale.
In general, both classification methods show predominant westerly GWCs from 5 December onwards with north-westerly (NW) situations during the heavy precipitation event from 21 to 23 December (Table 1): OWTC shows humid conditions; LWT shows “gale”. However, differences are apparent during the first precipitation event: the cores of the low-pressure systems are centred far north, categorized by LWT as severe gale (Alexandra) and gale (Billie) with south-westerly (SW) cyclonic flow (Fig. 2a, b). OWTC on the other hand categorized a NW anticyclonic flow and dry conditions. An explanation provides the relevant model centre; OWTC is focused over central Germany, while LWT is ideally centred in the North Sea. Since most of southern and central Germany was unaffected by this precipitation event, most of the model domain was indeed dry.
Classification of the general weather circulation (GWC) after the
modified Lamb weather types used at BSH for
It becomes obvious that the use of the classification method is subject to several factors. One of these specifies that the method should be suitable to the region of interest and capture its unique features. In this case, LWT provides slightly better results due to its focus on the North Sea and the fact that OWTC misses wet days during the first precipitation event. Nevertheless, both GWC analyses clearly show that not only one specific weather type but the succession of similar (westerly) types was important to the overall high soil moisture conditions, i.e. in generating prolonged rainfall, especially in northern Schleswig-Holstein. Additionally, the extreme precipitation event in southern Schleswig-Holstein was caused by a succession of NW types from 19 to 23 December (5 days; LWT) and 17 to 23 December (7 days; OWTC). Considering the mean life time of the NW type of 1.82 days (base period 1971–2000; Löwe et al., 2013, their Table 2-10), the event was extraordinary for this region.
Above-average monthly precipitation amounts between 80 and 160 mm were recorded at the German coasts during December 2014; local monthly means were exceeded by more than double that value and old records were broken. In SH, values of 175 mm up to 225 mm were reached (Fig. 3a), which corresponds to about 225–300 % of the long-term means (Fig. 3b). All over the rest of Germany, December 2014 was unremarkable, with maximum mean values around or clearly below those of the reference period (1961–1990).
Looking at daily precipitation sums from the REGNIE data set, two main rainfall periods can be distinguished: one from 10 to 12 December, more pronounced in northern SH, and one from 18 to 24 December (Fig. 4). Maximum daily precipitation was detected from 22 to 23 December in southern SH and HH, with local values exceeding 50 mm corresponding to the standard monthly mean values.
Daily sums of REGNIE precipitation data in millimetres for the first
event, 10–12 December 2014
As seen in Fig. 4a–c, the first rainfall period begins in far north-eastern (NE) SH on 10 December slowly progressing to the south. It further shows that not only SH was affected during this event: pronounced rainfall was detected north of the Eifel region on 12 December. Figure 4d–f display the main precipitation event from 21 to 23 December. Now mainly northern Germany is affected, especially southern SH on 22 December. Values are comparable to daily precipitation sums from selected DWD stations presented in Fig. 5 showing that REGNIE (solid black lines) fits the station data (bar plots) well. Only the highest maximum values are slightly underestimated: highest values are found at Wittenborn, north of Hamburg, with over 50 mm on 22 December (see Fig. 4e), about 30 mm at Schleswig in central SH, and over 20 mm at Leck in northern SH on 22 December (see Fig. 4f). The first rainfall period is captured as well, with maximum values on 11 and 12 December (see Fig. 4b, c).
Daily precipitation sums at DWD stations in northern (Leck), central (Schleswig), and southern (Wittenborn) Schleswig-Holstein, December 2014. Black lines indicate REGNIE daily precipitation sums at the closest respective grid points.
Additional investigations using modelled soil moisture data from DWD's Agrometeorological Research Centre (ZAMF) for sandy loam soil and cultivation with sugar beets show highest values in the SH region, with up to 139 % nFK (effective field moisture capacity) in the north for 21 December 2014 (start date of the corresponding event precipitation). Values decrease southward but never below 100 % nFK except in the south of SH (Fig. 6a). The unit % nFK describes the saturation in percent of effective field capacity of the upper 60 cm of soil. If soil moisture exceeds 100 % nFK, the actual water content is higher than is usable for plants (DWD, 2016), i.e. as in most of northern and central SH at the onset of the main precipitation event. The south to north gradient is in accordance with precipitation data, showing a slow progression of rainfall events from north to south (see Sect. 3.2).
ZAMF also provides soil moisture data for loamy sand soil and cultivation with winter grain. Using this data, values in northern and central SH are between 105 and 110 % nFK for the same date (Fig. 6b). It should be noted that neither the actual soil differentiation nor the degree of sealing is part of the model chain, and locally, this might be of importance (see, e.g., Apel et al., 2016). Nevertheless, both soil types show the same oversaturated regions in SH with some minor differences in the Fehmarn area (eastern SH).
Figure 7 shows the 3-day precipitation sum R3d for the December 2014 flood in Schleswig-Holstein (Fig. 7a) and its corresponding ratio to the 5-year return period (5yRP, Fig. 7b). The scaling for R3d is set according to Schröter et al. (2015). Clearly, the main contiguous part of the event precipitation is restricted to northern Germany, with some spots in central and southern Germany. R3d shows rather moderate maximum values of 109 mm north of Hamburg compared to the flood in 2013 with maximum values up to 300 mm (see Schröter et al., 2015, their Fig. 5, left). These differences can be explained mainly with the origin of both events: the flood 2013 was triggered by a quasi-stationary trough over central Europe in May and June leading low-pressure systems with hot and humid air masses at their flanks from SE Europe northwards. Additional orographic effects caused by the mountain ridges in central Europe, large-scale uplifting downstream from the low-pressure systems, and embedded convective processes finally led to prolonged and extended rainfall (e.g. Belz et al., 2013, 2014; Stein and Malitz, 2013). The December 2014 flood was triggered by low-pressure systems with North Atlantic air masses exclusively and appeared in winter when relatively cold air cannot hold as much water.
Areas with R3d exceeding the 5yRP are centred north of Hamburg, the eastern NOK region, the catchments Stör and Krückau, and at the coasts of Mecklenburg-Vorpommern (Fig. 7b). Higher return periods can be found north of Hamburg in the area of Wittenborn (see Fig. 4). Here, values even exceed 100yRPs locally, but due to the fact that the base period only spans 50 years, return periods over 100 years are becoming increasingly uncertain (rule of thumb: 2 times the observational time span gives the maximum return period to be statistically sound). Therefore, the cut has been made at 100 years. Nevertheless, this shows how extraordinary this event was for this region.
As in Fig. 7, but for the API.
Figure 8 shows the corresponding values for the API, again, scaled according to Schröter et al. (2015). Maximum API values of 41.5 mm (Fig. 8a) are well below those of the flood 2013 (see Schröter et al., 2015, their Fig. 7, left) and can be found in NW SH, which is in fair agreement with the soil moisture data (see Fig. 6a). In contrast to R3d, the 5yRPs for API are exceeded only in NW SH (Fig. 8b), with maximum values corresponding to 20yRP.
It is obvious that antecedent precipitation in combination with the maximum precipitation event led to SH-wide flooding in 2014 (Figs. 7, 8): areas that were struck by heavy rainfall did not need additional initial wetness to be flooded; areas with high antecedent precipitation were saturated already and needed only small amounts of additional event precipitation. In this regard, the importance of both indices to describe this flood accurately is illustrated. Furthermore, ongoing investigations in the NOK catchment area suggest that R3d and API are promising indicators or predictors to describe problematic situations in the canal's operational routine. However, since many other influencing factors like wind surge, locking of ships, dewatering, ferry traffic, etc. are involved, pinpointing the respective factors to one single event is difficult, and therefore, accurate estimations of the consistency for regional investigations cannot be given at this point yet.
The LKN–SH and LLUR–SH (2015) report points out that more than a third (66 out of 184) of inland gauges in SH exceeded the, thus far, highest high-water level (HHW) during the December 2014 flood (Fig. 9). Almost all of these gauges are located in areas affected by high R3d values in southern and north-eastern SH or high API values in north-western SH (see Figs. 7, 8).
Gauge data in Schleswig-Holstein, showing exceedance of highest high-water levels (mauve), medium high-water levels (yellow to red), medium water levels (green to yellow), medium low-water levels (dark blue), and lower levels (light blue) during the December 2014 flood. This map from the LKN–SH and LLUR–SH (2005) report was kindly provided by Thomas Hirschhäuser (LLUR–SH).
Furthermore, 14 gauges exceeded high waters with low probability, i.e. 200 yr return periods (HW200; according to HWRM-RL, 2007). Two more gauges exceeded their 100 yr return periods (HW100) and eight gauges their 10 yr return periods (HW10; LKN–SH and LLUR–SH, 2015, their Fig. 46). Regarding discharges, three gauges exceeded their respective 200 yr return periods, four more their 100 yr return periods, and five more their 50 yr return periods (LKN–SH and LLUR–SH, 2015, their Fig. 80). All of these gauges are located in areas affected by R3d or API.
More than 80 % exceeded the mean high-water level (MHW), while gauges not reaching the MHW were mainly sea gauges located in the North Sea. Return periods of half a year were hardly exceeded here (Jens Möller, BSH, personal communication, 2015). Therefore, the December 2014 flood could have been much worse if an additional storm surge had hindered the drainage of the SH catchments into the North Sea.
Mean significant trends (above 95 % significance level) over
30-year running intervals from 1960–1989 to 1985–2014 in millimetres per year for
the five highest
Figure 10 shows significant mean 30-year running trends for the North and Baltic seas Canal catchment area (EZG NOK), SH, and D for the five highest R3d and API events per year. Obviously, trends are not only highly dependent on the respective base period, showing considerable interannual variation, but on the area under investigation as well: while trends for R3d are positive in SH (with one exception) and the EZG NOK during the whole period, they become negative during recent years looking at Germany as a whole. Keeping in mind that cyclone pathways and connected extreme precipitation events are shifting north-eastwards (e.g. Stendel et al., 2016), SH and the EZG NOK will probably experience more and heavier extreme situations in the future. Furthermore, a clear separation of NE and SW Germany regarding significant R3d trends is evident in recent years, exemplarily shown for the period 1983–2012 (Fig. 11a): trends are positive in NE Germany and negative in SW Germany with only some local spots (e.g. mountainous areas) showing opposing trends. This separation also is in accordance with the shifting cyclone pathways.
Significant trends (above 95 % significance level) in millimetres per year for the five highest
API trends (Fig. 11b) are negative for all areas in the beginning, change to high positive values during the 1980, and have settled at lower values since. Again, D shows the smallest values since the NE–SW separation is also evident but not as articulated as for R3d. Nevertheless, API can also be expected to increase more strongly in the north-east under climate change conditions, leading to wetter soil and an increased risk of flooding in these areas. Combined with the higher probability of extreme precipitation events, especially for northern Germany (SH, EZG NOK), the risk increases even further.
In the end, the December 2014 flood in Schleswig-Holstein did not turn out to be as dramatic as it could have been: the flood management worked well and the infrastructure withstood the water masses for the most part (only a few dyke breaks and a slope slide of about 1.5 km on the motorway A1 were reported). An additional simultaneous storm surge, however, could have caused severe problems, e.g. by cutting off the possibilities for drainage due to high low-water levels. The relevant meteorological situation did indeed exist: persistent westerly weather circulations with frequent low-pressure systems partly classified as gales or even severe gales. The fact that all catchments could be drained at all tides and retention areas were utilized to a greater extent (see LKN–SH and LLUR–SH, 2015) may have prevented greater damage.
The indices R3d and API used nationwide by Schröter et al. (2015) can be applied on the regional scale as well and give an accurate evaluation of the initial wetness and the heavy rainfall event that led to the flood in December 2014. Almost all inland gauges exceeding their highest high-water values, return periods (HW200, HW100, HW10), and discharges (HQ200, HQ100, HQ50) during this flood are located in areas influenced by R3d and API. API, especially, captures the highest soil moisture conditions modelled by ZAMF at the onset of the R3d event quite well. This is of particular interest for future evaluation of reanalyses and climate models because this method only needs precipitation data as input, which makes it a cost-effective estimation of the soil moisture without running additional soil models. Since catchment wetness prior to extreme precipitation events is of high importance for flood forecasts (see Berthet et al., 2009; Pathiraja et al., 2012), API seems to be a promising surrogate, especially in the case of poor observational soil moisture data (see Woldemeskel and Sharma, 2016). Nevertheless, additional high-resolution information about the actual soil type, i.e. in calculating the respective depletion constant, could be an advantage. Other influencing factors and drivers like snowmelt, frost, droughts, etc. could be taken into consideration as well since each catchment exhibits its own system of dependencies (see, e.g., Valiuškevičius et al., 2016).
Trend analyses indicate an increasing risk of flood-prone situations in Schleswig-Holstein due to increasing R3d and API values over the last decades. Taking sea level rise into account (e.g. Quante et al., 2016; Wahl et al., 2013), leading to increased ground water levels and, therefore, higher initial soil moisture, flood protection and improved drainage of the affected catchments becomes even more relevant.
Future work within topic 1 of the network of experts will include amongst other things the evaluation of long-term changes at gauge stations in the North and Baltic seas (Möller and Heinrich, 2016) and applying the above-described precipitation indices to reanalyses and regional climate models (RCMs). Since precipitation extremes are expected to increase in the future (e.g. Nikulin et al., 2010; Kharin et al., 2013; Scoccimarro et al., 2013), the number of potentially harmful situations can be expected to increase accordingly. In fact, the trend analyses presented above show that R3d and API are already increasing. How big the impact will be compared to other potent drivers for coastal changes (e.g. wind surge and sea level rise) is one major aspect of this ongoing research.
In addition, several other impact studies and pilot projects will investigate
future planning and management of transportation under climate change
scenarios, e.g. the NOK, Fehmarnsund, and coastal infrastructure. The latter
may be harmed by increasing wind-induced water levels in the North Sea as
well (Gaslikova et al., 2012). New high-resolution reanalyses like
COSMO–REA6 (Bollmeyer et al., 2015) by the Hans-Ertel-Zentrum
(HErZ), based on DWD's operational forecast model COnsortium for
Small-Scale MOdelling limited-area model (COSMO–LAM; Schättler et
al., 2011), will improve the hindcast evaluations and serve as input for RCM
runs. In a first comparison, Kaiser-Weiss et al. (2015) have already shown
advantages over global reanalyses for ground level wind data, especially in
coastal and mountainous regions due to the improved spatial (
Further investigations could include extending R3d and API to extreme and abnormal events (see Müller and Kaspar, 2014; Müller et al., 2015) via seasonality and a varying size of the catchment areas, which is of particular interest for regional investigations. Also, the use of the extreme climate indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI; see, e.g., Sillmann et al., 2013a, b) might prove relevant.
DWD daily REGNIE data are freely available for download at
DWD daily station data are freely available for download at
DWD daily OWTC data are freely available for download at
The author declares that he has no conflict of interest.
The research leading to this paper was conducted as part of topic 1 of
the network of experts initiated by the German Federal Ministry of Transport
and Digital Infrastructure (BMVI). REGNIE, OWTC, and station data have been provided by
the German Meteorological Service (DWD), soil moisture data by DWD's
Agrometeorological Research Centre (ZAMF). NCEP/NCAR R1 has been provided by
the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at