Relevance of long term observatories

such as the tide gauge in Świnoujście

Hans von Storch and Birgit HünickeInstitute of Coastal Research

Helmholtz Zentrum GeesthachtGermany

18 Nov. 2011 Scientific Symposium: 200 years of tide-gauge measurements in Świnoujście

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)

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

Describing climate change

1. Observational data – thus local data, and not analysis which suffer from changing procedures and data density

2. Stationary data with respect to informational value (data must not become better in the course of time) – Homogeneity / see below

3. Representative data for more than just the specific location

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“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

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

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• Wind speed measurements

SYNOP Measuring net (DWD)

Coastal stations at the German Bight

Observation period: 1953-2005

Representativity of near surface wind speed measurements

This and the next 3 transparencies: Janna Lindenberg, GKSS

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• Causes of inhomogenities:

• Changes in– Instruments– Sampling

frequencies – Measuring units– Environments (e.g.

trees, buildings)– Station relocations

(Dotted lines)

Representativity of near surface wind speed measurements

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1.25 m/s

Representativity of near surface wind speed measurements

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Representativity of near surface wind speed measurements

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

Counting storms in weather maps – steady increase of NE Atlantic storms since the 1930s ….

Max: 52 m/s

Max: 20 m/s

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Differenz Scheitelhöhen Hamburg - Cuxhaven

Stormsurges intensified after 1962 event due to improv ing coastal defense and deepning shipping channel in the river.

Storm surge heights in Hamburg

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

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.

North Sea: Changing intensity of regional storminess

1880 194019201900 200019801960

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Alexandersson, SMHI, 2003

Temporal development of Ti(m,L) = Ti(m) – Ti-L(m) divided by the standard deviation of the m-year mean reconstructed temp recordfor 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.

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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.

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.

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.