Parallel measurements at German climate reference stations: DWD s approach to compare manual vs. automatic observations

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1 Parallel measurements at German climate reference stations: DWD s approach to compare manual vs. automatic observations Frank Kaspar and Lisa Hannak Deutscher Wetterdienst, National Climate Monitoring, Frankfurter Str. 135, Offenbach, Germany Correspondence to: frank.kaspar@dwd.de Abstract. Germany's national meteorological service (Deutscher Wetterdienst, DWD) operates a network of socalled 'climate reference stations'. One specific task is the performance of parallel measurements in order to allow the comparison of manual and automatic observations. Later, also subsequent generations of automatic sensor will be operated in parallel over sufficiently long periods to allow an assessment of the effect of such changes. Here, we present the concept and configuration of DWD s climate reference stations, together with exemplary results for temperature and sunshine duration. 1 Introduction For reliable analysis of climate change atmospheric parameters have to be observed over sufficiently long time and non-climatic influences on time series of observations have to be understood. Over such periods observation networks and procedures are typically affected by various modifications. One important example is the transition from manual to automatic observation techniques. The GCOS Climate Monitoring Principles suggest that traditional and new sensors should be operated with a sufficiently long temporal overlap. To analyze the impacts of the transition from manual to automatic stations, DWD operates a network of socalled 'climate reference stations' (CRS). Currently manual and automatic observations are performed in parallel in order to allow understanding the impact of changes in the instrumentation in Germany. 2 History and status of the climate reference stations After Germany's reunification, the observation network was successively modernized and automatized. In a first step, seven 'reference stations' were introduced to allow the comparison of conventional and automatic measurements. Since 2008, 12 stations are operated as climate reference stations (Table 1). Parallel measurements at these stations officially started 1st of May At these stations observations are performed by observers and automatic instruments. The stations are located in different climatic regions of Germany. At these locations observations have already been performed since several decades, in most cases already since the end of the 19th century. 1

2 Table 1: DWD s climate reference stations: Length of time series, time range in which station has parallel measurements and geographic location. WMO-ID Station name Time series since Period with parallel Lat. Lon. measurements and AMDA Helgoland Schleswig 1947 from Hamburg-Fuhlsbüttel Potsdam 1893 from Lindenberg 1906 from Brocken 1881 from Görlitz Aachen / Aachen-Orsbach ~50.8 ~ Fichtelberg Frankfurt-Airport 1949 from Hohenpeißenberg 1781 from Currently 10 stations are operated as climate reference stations. In the current configuration, the CRSs are manned with observers around the clock. The automatic measurements are performed equivalently to other stations in DWD's main observing network. In addition, manual observations are performed in parallel at the three traditional observing times (so called 'Mannheimer Stunden'): 06:30 UTC, 13:30 UTC and 20:30 UTC (in the following: observing times I, II, III). These include readings of instantaneous and extreme values and the interpretation of recordings. Observed parameters are: air pressure, air temperature, humidity, precipitation, sunshine duration, snow height (Table 2) and soil temperatures at different depths. The instruments used at these stations are listed in Table 2. The time periods in Table 1 refer to the interval when so-called AMDA stations (=Automatische Meteorologische Datenerfassungs-Anlage) were used. For some stations also earlier parallel measurements exist, but were excluded from the comparisons shown in this paper. 2

3 Table 2: Conventional and automatic measurements taken at climate reference stations and instruments used for these measurements. Observation times for these parameters for traditional observations are: (I): 06:30 UTC, (II): 13:30 UTC and (III): 20:30 UTC. Parameter Instrument (traditional) Instrument (automatic) Air pressure Hg station barometer PTB 220, PTB 330, AIR-DB Dry temperature 2 m Mercury-in-glass thermometer (Hg) Pt 100 Wet temperature 2 m Mercury-in-glass thermometer (Hg) - Maximum temperature 2 m Mercury-in-glass thermometer (Hg) Pt 100 Minimum temperature 2 m Glass thermometer (alcohol) Pt 100 Minimum temperature 5 cm Glass thermometer (alcohol) Pt 100 Precipitation amount Hellmann, Pluviograph PLUVIO, NG200, Joss-Tognini Sunshine duration Campbell-Stokes SCAPP, SONIEe Relative humidity Thermo-hygrograph HMP45D, EE33, MP100, MP300 Temperature in 5, 10, 20, 50, 100 cm depth Mercury-in-glass thermometer (Hg) Pt 100 Snow depth (total and fresh) Yardstick SR50-G1, SHM30 Five CRSs will be operated in the current mode until 2018 (Schleswig, Lindenberg, Brocken, Frankfurt, Hohenpeißenberg). Ten years of parallel measurements will then be available for these stations ('type I' stations). After that period, they will be converted to automatic CRSs ('type II'). At these automatic stations no manual observations will be performed. When a new generation of automatic instruments is introduced into DWD's network, the previous and new instruments will be operated in parallel at the CRSs. The intended duration for such parallel measurements is 2 to 5 years. From 2019 onward, all CRSs will be of type II, i.e. automatic CRSs. A detailed systematic analysis for all parameters is currently ongoing. Preliminary results for several parameters are also presented in Hannak et al. (2017). 3 Example 1: Temperature The temperature measurements from DWD's station network are regularly used to provide information on climate change in Germany (see e.g. Kaspar et al., 2013 or Kaspar & Mächel, 2017). It is therefore important to understand if there are any artificial breaks in these time series, e.g. caused by changes in the observing technique. The parallel measurements from the CRSs have therefore been used to analyze the impacts of changes of the sensors, screen types and data processing. Detailed results, for temperature, including daily extremes are summarized in Kaspar et al. (2016). An important finding was that the introduction of automatic thermometers does not lead to systematic differences in the time series of state temperature. Figure 1 shows the frequency distribution of differences between automatic and manually observed temperatures. The mean value of these differences is close to zero. In Kaspar et al. (2016) it was also shown that the automatic 3

4 measurement of maximum temperature might in some situations be affected by radiation effects. The effect of the automatization on the daily extremes of temperature is also small on average, but a seasonal cycle for the daily maximum temperature was noted for stations where a lamellar shelter LAM 630 is used, with higher values for the electrical thermometer in summer. This effect can be avoided by optimizing the placement of the sensors within the screen. Figure 1: Histogram of the differences between automatically and manually observed temperature observations based on data from all climate reference stations. 4 Example 2: Sunshine duration Sunshine duration is an example for a parameter, for which an impact of the change of the observing technique is clearly visible. The traditional measurement technique ( Campbell Stokes ) is based on a burned trace in a paper card whereas the automatic observations are based on radiation measurements. Figure 2 shows the histogram of the differences based on the data from all CRSs. On average, the manually derived values are higher than the automatic ones. Figure 3 shows a time series of the differences for station Schleswig. A seasonal cycle is visible and differences are stronger during summer. Similar differences are also described by Legg (2014). A potential explanation is that observers might overestimate the length of the burned areas on the paper card when a frequent change between sunny and cloudy situation occurs. 4

5 Figure 2: Histogram of the differences between automatically and manually derived sunshine duration data based on observations from all climate reference stations. Figure 3: Time series of the differences between automatically and manually derived sunshine duration data for station Schleswig. 5

6 References Kaspar F, Müller-Westermeier G, Penda E, Mächel H, Zimmermann K, Kaiser-Weiss A, and Deutschländer T (2013) Monitoring of climate change in Germany data, products and services of Germany's National Climate Data Centre, Adv Sci Res 10:99-106, doi: /asr Kaspar, F., Hannak, L., and Schreiber, K.-J.: Climate reference stations in Germany: Status, parallel measurements and homogeneity of temperature time series, Adv. Sci. Res., 13, , Kaspar, F. and Mächel, H.: Beobachtung von Klima und Klimawandel in Mitteleuropa und Deutschland, in: Klimawandel in Deutschland Entwicklung, Folgen, Risiken und Perspektiven, edited by: Brasseur, G. P., Jacob, D., and Schuck- Zöller, S., 3, 17 26, doi: / _3, Springer, Berlin, Heidelberg, 2017 Hannak, L. Friedrich, K., Imbery, F., and Kaspar, F. (2017): Analysis of the impacts of the automatization of measurement systems using parallel measurements from German climate reference stations. Proceedings of the 9th Seminar for Homogenization and Quality Control in Climatological Databases (Budapest, Hungary), in press. Legg, T. (2014). Comparison of daily sunshine duration recorded by Campbell Stokes and Kipp-and-Zonen sensors. Weather, 69(10):