Relevance of long term observatories such as the tide gauge in Świnoujście

1. 18 Nov. 2011 Scientific Symposium: 200 years of tide-gauge measurements in Świnoujście Relevanceoflongtermobservatoriessuch asthetidegauge in Świnoujście Hans von Storch and Birgit Hünicke Institute ofCoastal ResearchHelmholtz Zentrum GeesthachtGermany

4. First EOF of annual sea level data after subtracting the linear trend, 1890 - 2008 The change due to vertical crustal movement and other long-term changes is presumably taken out by subtracting a linear trend. The remaining signals contains effects of - changing ocean volume (e.g., due to global warming) - changing weather related effects (wind, freshwater flux)

5. Assessing climate change • Climate = statistics of weather, as given by distributions or parameters thereof, such as means, percentiles etc. • First task: Describing change • Second task: “Detection” - Assessing change if consistent with natural variability • Third task: “Attribution” – Determining which mix of causes describes the present change best

6. Describing climate change Observational data – thus local data, and not analysis which suffer from changing procedures and data density Stationary data with respect to informational value (data must not become better in the course of time) – Homogeneity / see below Representative data for more than just the specific location

7. The increase in damages related to extreme weather conditions is massive – but is it because the weather is getting worse? Losses from Atlantic Hurricanes Hardly “Great Miami”, 1926, Florida, Alamaba – damages of 2005 usage - in 2005 money: 139 b$ Katrina, 2005: 81 b$ Pielke, Jr., R.A., Gratz, J., Landsea, C.W., Collins, D., Saunders, M., and Musulin, R., 2008. Normalized Hurricane Damages in the United States: 1900-2005. Natural Hazards Review

8. Representativityofnearsurface wind speedmeasurements • Wind speed measurements • SYNOP Measuring net (DWD) • Coastal stations at the German Bight • Observation period: 1953-2005 This and the next 3 transparencies: Janna Lindenberg, GKSS

9. Representativityofnearsurface wind speedmeasurements • Causesofinhomogenities: • Changes in • Instruments • Sampling frequencies • Measuringunits • Environments (e.g. trees, buildings) • Station relocations(Dottedlines)

10. Representativityofnearsurface wind speedmeasurements 1.25 m/s

11. Representativityofnearsurface wind speedmeasurements Map based on: www.openstreetmap.org, License: Creative Commons Attribution-Share Alike 2.0 Openstreetmap

12. Max: 52 m/s Counting storms in weather maps – steady increase of NE Atlantic storms since the 1930s …. Max: 20 m/s

13. Storm surge heights in Hamburg Differenz Scheitelhöhen Hamburg - Cuxhaven Stormsurgesintensified after 1962 event due toimprovingcoastaldefenseanddeepningshippingchannel in theriver.

14. Inhomogeneity Observed values depend on the immediate environment of the location where the observation is made. This environment is subject to gradual and abrupt changes. Therefore such data often do not only reflect changes of the wind statistics but also other factors, such as observation method, practice, location, analysis method … Inhomogeneity is a key constraint, which is usually overseen by non-experts. Improved instruments and analysis introduces into data records such inhomogeneities (and thus, false signals); therefore satellite data as well as re-analyses are in most cases unsuitable for the assessment multi-decadal change

15. Detection climate change … needs knowledge about the undisturbed level of natural variability. This means having access either to reliable model simulations or homogeneous time series covering a sufficiently long period, when no external influences are present. What “sufficiently long” means is a subjective decision.

16. 2 1 0 -1 1880 1900 1920 1940 1960 1980 2000 North Sea: Changingintensityof regional storminess Alexandersson, SMHI, 2003

17. Temporal development of Ti(m,L) = Ti(m) – Ti-L(m) divided by the standard deviation of the m-year mean reconstructed temp record for m=5 and L=20 (top), andfor m=30 and L=100 years. The thresholds R = 2, 2.5 and 3σ are given as dashed lines. Rybski et al., 2006

18. Attribution? The issue is deconstructing a given record with the intention to identify „predictable“ components. „Predictable“ -- either natural processes, which are known of having limited life times, -- or man-made processes, which are subject to decisions (e.g., GHG, urban effect) For global and regional temperatures, this has been done, and the ongoing warming can not be explaining without considering elevated levels of GHG concentrations as a key cause.

19. First EOF of annual sea level data after subtracting the linear trend, 1890 - 2008 • Change of pc#1: 1970-2010 •  2 • Times EOF#1 at Helsinki (65 mm) • or Swinoujscie (38 mm) • 13 cm in 40 years ( 3 mm/a) • 8 cm in 40 years ( 2 mm/a) • Plausibly related to global warming, • But no separation into wind and/or freshwater flux signals; • No separation between GHG and aerosol effects.

20. Conclusion • Climate change studies need as a methodical basis a reliable description of ongoing change, an assessment of this change is plausible in the context of natural variable, and, if not, which of a series of possible causes are best in describing the ongoing change. • For doing so, we need long time series of (ideally) unchanging quality (no improvement across time!) • Thus, time series such as that one collected by Swinoujscie tide gauge are of utmost importance. • Formal detection and attribution studies are needed to assess the present change of Baltic Sea level. • Efforts are needed to construct more long time series from data of written records, in particular for gauges, which have been operated by different national authorities in the course of history.