Monitoring of climate change in Germany – data, products and services of Germany's National Climate Data Centre

Kaspar, Frank; Müller‐Westermeier, G.; Penda, E.; Mächel, H.; Zimmermann, K.; Kaiser-Weiss, Andrea; Deutschländer, Thomas

doi:10.5194/asr-10-99-2013

Cited by 90 publications

(85 citation statements)

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“…For this purpose, we use data from German climate stations (Kaspar et al, 2013) provided by the DWD (Deutscher Wetterdienst), which report the classical weather parameters, e.g., air temperature, air pressure, and humidity, three times a day. These data are aggregated to monthly resolution.…”

Section: The Observations and The Methods To Build Pairsmentioning

confidence: 99%

The joint influence of break and noise variance on the break detection capability in time series homogenization

Lindau

Venema

2018

Adv. Stat. Clim. Meteorol. Oceanogr.

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Abstract. Instrumental climate records of the last centuries suffer from multiple breaks due to relocations and changes in measurement techniques. These breaks are detected by relative homogenization algorithms using the difference time series between a candidate and a reference. Modern multiple changepoint methods use a decomposition approach where the segmentation explaining most variance defines the breakpoints, while a stop criterion restricts the number of breaks. In this study a pairwise multiple breakpoint algorithm consisting of these two components is tested with simulated data for a range of signal-to-noise ratios (SNRs) found in monthly temperature station datasets. The results for low SNRs obtained by this algorithm do not differ much from random segmentations; simply increasing the stop criterion to reduce the number of breaks is shown to not be helpful. This can be understood by considering that, in case of multiple breakpoints, even a random segmentation can explain about half of the break variance. We derive analytical equations for the explained noise and break variance for random and optimal segmentations. From these we conclude that reliable break detection at low but realistic SNRs needs a new approach. The problem is relevant because the uncertainty of the trends of individual stations is shown to be climatologically significant also for these small SNRs. An important side result is a new method to determine the break variance and the number of breaks in a difference time series by studying the explained variance for random break positions. We further discuss the changes from monthly to annual scale which increase the SNR by more than a factor of 3.

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Section: The Observations and The Methods To Build Pairsmentioning

confidence: 99%

The joint influence of break and noise variance on the break detection capability in time series homogenization

Lindau

Venema

2018

Adv. Stat. Clim. Meteorol. Oceanogr.

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“…dwd.de/pub/CDC/observations_germany/climate/ (Kaspar et al, 2013). Available are the station data and associated metadata describing the particularities of the station instrumentation and measurement time series.…”

Section: Datamentioning

confidence: 99%

Comparison of regional and global reanalysis near-surface winds with station observations over Germany

et al. 2015

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Abstract. Reanalysis near-surface wind fields from multiple reanalyses are potentially an important information source for wind energy applications. Inter-comparing reanalyses via employing independent observations can help to guide users to useful spatio-temporal scales. Here we compare the statistical properties of wind speeds observed at 210 traditional meteorological stations over Germany with the reanalyses' near-surface fields, confining the analysis to the recent years (2007 to 2010). In this period, the station time series in Germany can be expected to be mostly homogeneous. We compare with a regional reanalysis (COSMO-REA6) and two global reanalyses, ERA-Interim and ERA-20C. We show that for the majority of the stations, the Weibull parameters of the daily mean wind speed frequency distribution match remarkably well with the ones derived from the reanalysis fields. High correlations (larger than 0.9) can be found between stations and reanalysis monthly mean wind speeds all over Germany. Generally, the correlation between the higher resolved COSMO-REA6 wind fields and station observations is highest, for both assimilated and non-assimilated (i.e., independent) observations. As expected from the lower spatial resolution and reduced amount of data assimilated into ERA-20C, the correlation of monthly means decreases somewhat relative to the other reanalyses (in our investigated period of 2007 to 2010). Still, the inter-annual variability connected to the North Atlantic Oscillation (NAO) found in the reanalysis surface wind anomalies is in accordance with the anomalies recorded by the stations.We discuss some typical examples where differences are found, e.g., where the mean wind distributions differ (probably related to either height or model topography differences) and where the correlations break down (because of unresolved local topography) which applies to a minority of stations. We also identified stations with homogeneity problems in the reported station values, demonstrating how reanalyses can be applied to support quality control for the observed station data.Finally, as a demonstration of concept, we discuss how comparing feedback files of the different reanalyses can guide users to useful scales of variability.Published by Copernicus Publications.

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“…HKB zugrunde. Die Auswertungen wurden durch Beobachtungsdaten des DWD (Kaspar et al 2013), weiteren räum-lich interpolierten Beobachtungsdaten und regiona len Reanalysen für den Zeitraum 1981-2010 aktualisiert. Die Ergebnisse werden mit den Auswertungen im Norddeutschen Klimamonitor (Stand Oktober 2015) verglichen.…”

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Klima der Region – Zustand, bisherige Entwicklung und mögliche Änderungen bis 2100

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et al. 2018

Hamburger Klimabericht – Wissen Über Klima, Klimawandel Und Auswirkungen in Hamburg Und Norddeutschland

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Monitoring of climate change in Germany – data, products and services of Germany's National Climate Data Centre

Cited by 90 publications

References 1 publication

The joint influence of break and noise variance on the break detection capability in time series homogenization

The joint influence of break and noise variance on the break detection capability in time series homogenization

Comparison of regional and global reanalysis near-surface winds with station observations over Germany

Klima der Region – Zustand, bisherige Entwicklung und mögliche Änderungen bis 2100

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