1

Climate change and sediment budgets?

Jaak Monbaliu

Albin Ullmann

2

Content

• sediment budget – relevant parameters

• climate and climate change

• downscaling: link climate model parameter(s) to impact variables

• conclusion & further work

3

Sediment budget

• Natural variability

• Anthropogenic influence– Coastal safety -> beach nourishment– Aggregate extraction– Dredging / dumping– Construction– ....

4

Parameters affectingsediment budgets

imposed by nature:– tidal currents– storms -> waves and surges– water depth– sediment composition– ....

anthropogenic:– tidal currents– nourishment– D/D– extraction– water depth– ...

5

SLR SWH WDIR ??

nourishment H H L ?

extraction H H L ?

D/D L L L ?

.... .... ..... .... ....

Parameters affectingsediment budgets (*)

(*) as indication onlyH : high impact

L : low impact

6

Climate Change

Scenario A2 :

Min. : + 1.5 mm/an

Max. : + 7.5 mm/an

Scenario B2 :

Min. : + 1 mm/an

Max. : + 6.5 mm/an

Scenario A1b :

Min. : + 1.2 mm/an

Max. : + 7.0 mm/an

IPCC. http://www.ipcc.ch

21st century mean sea-level rise

7

Climate

climate = statistics of weather

weather = state of the atmosphere at a particular time

“Climate is what you expect,

weather is what you get.”quoted from Andreas Sterl, SEAMOCS meeting Malta 2009

8

Climate: downscaling

linking weather regimes to events

downscaling: statistical model(s)

using the downscale model(s) for future predictions

9

Climate: weather regimes

5 weather regimes can summarize the atmospheric circulation over the Northern Atlantic and Europe

ZO: « zonal » EA: « East Atlantic » GA: « Greenland Above » BL: « Blocking » AR: « Atlantic Ridge »

Mean SLP for each weather regime for the period 1925-2000.

10

Mean SLP for daily surge at Oostende > 50 cm (1925-2000)

Mean SLP for daily maximum wave height at Westhinder > 2.5 m (1994-2001)

deep low pressure system over the Baltic Sea +

reinforced Azores high ▼

highest surges and highest waves Belgian coast

weather regimes ↕

surges & waves

11

Correlation between daily surge height at Oostende and daily SLP field (1925-2000)

Correlation between daily maximum wave height at Westhinder and daily SLP field (1994-2001)

At daily time scale, surge and wave height along the Belgian coast are both correlated with sea-level pressure over the Baltic Sea

surges and waves: daily variability

12

statistical model

surge height =

Function_1 (Patm, Baltic , ΔPatm, Baltic-Azores)

wave height =

Function_2 (Patm, Baltic , ΔPatm, Baltic-Azores)

13

statistical model• regression model + correlation coefficient

including gradient information does not improve correlation but ...

Observed Vs simulated daily surge height. (a) Regression with the daily SLP averaged over the Baltic Sea as predictor. (b) Regression with both daily SLP averaged over the Baltic Sea and the daily value of the pressure gardient between the Baltic and the Azores as predictors

R = 0.61

R = 0.61

14

R = 0.76

σobs = 14.2 cm

σsim = 14.8 cm

R = 0.72

σobs = 50.0 cm

σsim = 47.3 cm

Monthly 90th percentile of daily wave-height anomaly observed at Westhinder (blue line) and hindcast with the linear statistical model (red line) for the period 1994-2001.

Monthly 90th percentile of daily surge observed at Oostende (blue line) and hindcast with the linear statistical model (red line) for the period 1950-2000.

15

Increase in wintertime P99 of daily maximum sea-level = + 3 mm/yr

Increase in wintertime P99 of daily surge = + 1 mm/yr

Increase in MSL = + 2 mm/yr (Van den Eynde et al., 2007, CLIMAR annual scientific report)

+

trend in sea-level and surge

16

MSL rise= mostly link with thermal expension of Seas and Oceans…

Wintertime SLP rise over Azores

=Increase in the

wintertime Northeast-Southwest pressure

gradient

increase in sea-level and surge

…and increase in surge height

17

prediction for the future

• Essence ensemble dataset: A1B scenario

• Meteo-France dataset: A2 and B2 scenario

18

yearly 90th percentile of sea surge for the period 2000-2100 for ESSENCE dataset A1b SRES scenario (thin line: mean of ensemble ; full line: 30-year low pass filtered ; grey shading: yearly mean variability in ensemble +/- σ

surge-height variability 21st century

19

yearly 90th percentile of sea surges for the period 2000-2100 for A2 (full line) and B2 (dashed line) SRES scenario.

surge-height variability 21st century

20

Conclusion

• downscaling possible for (some) driving parameters sediment budget

• from this dataset and climate models !!– no significant changes in surge and wave

heights– natural variability within the system is

substantial– SLR will be dominant natural factor for

changes in the sediment budget

21

Further work

• link surge / wave /.... to sediment budgets in a robust way for long term and natural variability estimates