Hans Hanson, Lund Universty Hans Hanson, Lund Universty Hans

Home , Flat coast

Hans Hanson, Lund Universty

International View - Hurricanes, Cyclones, Typhoons

Hans Hanson, Lund Universty

Hurricane

Damage

Hans Hanson, Lund Universty

1 Hurricane Flooding – Katrina in New Orleans 2005

050829

050826 Bah. 050823

Cuba

Jam. Haiti Dom.Rep. Category 5 => max wind 95 m/s

Hans Hanson, Lund Universty

Storm-Threats to Coastal Cities

Hans Hanson, Lund Universty

Flooding of Cities due to Rain, Rivers, and Tides

Hans Hanson, Lund Universty

2 GREEN HOUSE EFFECT

Hans Hanson, Lund Universty

GREEN HOUSE EFFECT

80 70 60 50 40 30 20 10 0 80 18 2

Hans Hanson, Lund Universty

GREEN HOUSE EFFECT

CO N2O CO2 2 CO2 CH4

CFC

Meat Prod.

N2O = laughing gas

CH4 = methane

CFC = freon

Hans Hanson, Lund Universty

3 GREEN HOUSE GASES

CO2 CH4 (methane)

19% 64% 10% 6%

CFC (freon)

N O (laughing gas) 1% 2 Other (Ozone, Halone,...)

Conc. (PPB) Life (yrs) Rel. Effect CO2 350,000 3-5 1 CH4 1,800 5-10 25 N2O 304 100-150 250 Ozone 40-80 0.1 2,000 CFC 0.6 100 20,000

Hans Hanson, Lund Universty Bogren et al. (2006)

PALEO CLIMATOLOGICAL RECONSTRUCTION

Nat’l Geogr., 193(5), 1998 Hans Hanson, Lund Universty

CORRELATION CO2 AND TEMPERATURE?

2008 = 385 ppm

Inter glacial periods

Methane (ppb)

IPCC Hans Hanson, Lund Universty

4 RECENT TEMP VARIATIONS

IPCC

the past 1200 years

Small climatic optimum Small ice age Nat’l Acad. Sci., 2006

Hans Hanson, Lund Universty

RECENT & PROJECTED CO2

Hans Hanson, Lund Universty IPCC

RECENT & PROJECTED TEMP

CO2

What is 5 deg temperature difference?

IPCC Hans Hanson, Lund Universty

5 5-DEG DIFFERENCE

30 Now Future 25 Cooler periods Warmer periods less common. more common. 20

15 Extremely warm periods much 10 more common.

Extremely cold New extreme 5 periods very temperatures rare. occur.

Relative frequency of (%) frequency occurrence Relative 0 -20-100 10203040 Temperature (oC)

Hans Hanson, Lund Universty

TEMPERATURE vs. SEA LEVEL

Temp (oC)

MSL (m)

Time (1,000 yrs)

Roper (2010) http://arts.bev.net/roperldavid Hans Hanson, Lund Universty

CONTRIBUTION TO SLR (%)

40 35 30 25 20 15 10 5 0

Hans Hanson, Lund Universty

6 GLACIAL RETREAT

2003

Glaciers Switzerland

Hans Hanson, Lund Universty

ANTICIPATED FUTURE SLR

SMHI estimation 2009 MSL = +100 cm 2100

Klimat- o Sårbarhetsutredningen estimation 2007 MSL = +80 cm 2100

~30 cm

Historic Trend MSL

IPCC

Hans Hanson, Lund Universty

Nat’l Geogr., 184(6), 1993 TIME AGAIN? Hans Hanson, Lund Universty

7 SUGGESTED CHAIN OF EVENTS

Increasing Concentrations of Green House Gases in the Atmosphere

Increasing Temperatures

Persistent Sea Level Rise

More and Worse Floodings Impact on Nature & Impact on Resources Human Society More and Worse Coastal Erosion

Hans Hanson, Lund Universty

Water level fluctuations in the S Baltic Sea 14,500 Baltic Ice Lake Yoldia Sea Ancylus Lake 11,600 11,200 10,500

11,500 20 H

Ö 0 * M

10,700

-20 * * 6,500 -40 *

10,000 Littorina Sea

12 10 8 6 4 2 0 14 12 101000-tals 8År Före Nutid 6 4 2 0 1,000 years1000-tals before år fpresentöre nutid

3,000 Hans Hanson, Lund Universty

Possible Threats

Overwash

Flooding

Erosion

Hans Hanson, Lund Universty

8 Consequences of Sea Level Rise

Shoreline Recession Shoreline Recession

Higher Sea Level Low, flat coast High, steep Lower Sea Level coast

Sea

Hans Hanson, Lund Universty

Erosion of Upper Profile/Dune

Hans Hanson, Lund Universty

SEA LEVEL RISE! WHAT HAPPENS TO THE BEACH?

R R1

FutureNew SL Sea Level Present Sea Level Rocky shore New bottom? Present Bottom Level

1 1

Hans Hanson, Lund Universty

9 SEA LEVEL RISE! WHAT HAPPENS TO THE BEACH?

New SL Present Sea Level Sandy shore New bottom? Present Bottom Level

1 1

Hans Hanson, Lund Universty

SEA LEVEL RISE! WHAT HAPPENS TO THE BEACH?

FutureNew SL Sea Level Present Sea Level Sandy shore NewFuture bottom? Bottom Level Present Bottom Level

1 1

Hans Hanson, Lund Universty

SEA LEVEL RISE! WHAT HAPPENS TO THE BEACH?

Eroded material Future Sea Level B Ackumulated material A Present Sea Level S Present beach profile Future beach profile R = S/bottom slope

Sandy shore

Bruun rule: An increase S of MSL => coastal erosion R = S/bottom slope.

If bottom slope = about 1/100 => A sea level rise of 1 m => erosion R = 100 m.

Hans Hanson, Lund Universty

10 MEASURES AGAINST RISING SEA LEVELS?

Groins? Detached Breakwaters?

Seawalls? Hans Hanson, Lund Universty

MEASURES AGAINST RISING SEA LEVELS?

L ~ 450 M S ~ 1 m yr 2100

Added volume V = S*L m3/m beach

V ~ 450 000 m3/km ~ 5 000 m3/km per yr ~ 500 000 SEK/km/yr over 90 yrs!

Hans Hanson, Lund Universty

BEACH WIDTH REDUCTION OF STORM DAMAGES

Dean, 1988 An investigation of 540 damaged structures after Hurricane Eloise (1975) along Florida Panhandle shows that an increase of beach width by 50 ft (15 m) reduces the damages significantly (Dean, 1988)

increase in beach width by 15 m reduces ~15 m structural damages down to ~ 1/2 - 1/3!

Hans Hanson, Lund Universty

11 ÅSAND FOR STORM PROTECTION?

ÅUS Army Corps nourished Åjust prior to Sandy

Å6 miles N, Brant Beach, NJ, Å“No overwash or wave damage”

ÅHolgate, NJ, “Complete destruction – it’s like a war zone”

ÅMayor Mancini estimated that if the entire Long Beach coast (30 km) had had the same beach as Brant Beach they would have saved ~$500M. Hans Hanson, Lund Universty ÅHouston (2013)

Study Site

SWEDEN

Lund Copenhagen Malmö

DENMARK Study site

GERMANY POLAND

Hans Hanson, Lund Universty

Study Site

Hans Hanson, Lund Universty

12 Water Levels in Falsterbokanalen

Sea level relative to Mean Sea Level (MSL) between 1942-1998

150 y = 0.0002x + 0.9159 Trend: 0.073 cm/yr (or 0,006cm/month)

100

50 ) cm . (

0 Sea level level Sea -50

-100

166 000 data points! -150 1942 1970 1998 Year Hans Hanson, Lund Universty

Annual High Water Levels (corrected for MSL change)

Water level above MSL (cm) 160

140 Trend = 0.45 cm/yr 120

100

60 Antal dagar/år > 21 m/s 35 1940 1950 1960 1970 1980 1990 2000 Year Uppmätta 30 Trend

15 r ar/å dag 0.32 10

Källa: SMHI (1989)

0 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 År Hans Hanson, Lund Universty

Distribution of ’Detrended’ NHW Levels

30 25 20 15 10 5 0 -5 -10 -15 -20 WaterLevel Rel Trend (cm) -25

-30 Meas - trend -35 Trend (MHV) -40 1946 1956 1966 1976 1986 1996 2050? Year 1.00

0.90 Conditions1996

0.80

0.70

0.60

MV = 0.09 0.50 SD = 16.68

0.40

0.30 P (Annual high > Level) > high (Annual P

0.20 Measurements 0.10 Normal distr.

0.00 -40 -35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 NHWHans Level Rel Trend Hanson, (cm) Lund Universty

13 FUTURE SEA LEVELS?

P (Annual high > level) 1.0

0.8

0.6

0.4

0.2

0.0 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 Level relative present MSL (m)

Present situation

Hans Hanson, Lund Universty

Normal distribution

1001.0 KumulativCumulative normalfördelning normal (inverterad)distribution (inverted)

800.8 40 NormalNormalfördelning distribution

600.6 20

10 P (Betyg1 < x < Betyg2) < x < (Betyg1 P P >(x Betyg) 400.4 0 -2-101234567 Betyg

200.2

0.00 Hans Hanson, Lund Universty-2-101234567 Betyg

Increase in SL 2000 - 2050 Trend in NHW in Trend Trend in MSL in Trend

Hans Hanson, Lund Universty

14 FUTURE SEA LEVELS?

P (Annual high > level) 1.0

0.8

0.6

0.4

0.2

0.0 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 Level relative present MSL (m)

Present situation 2050, 57-yr trend+ increased GHE 2100, SMHI

Hans Hanson, Lund Universty

Increasing SL – What is flooded?

Hans Hanson, Lund Universty

Digital Elevation Modell – Existing (x,y,z)

Hans Hanson, Lund Universty

15 Digital Elevation Model – New Data

Based on 18,000 known points (x, y, z).

Vertical scale exaggerated to enhance 3D-effekt.

Hans Hanson, Lund Universty

SKANÖR/FALSTERBO – FLOODED REAL ESTATE FOR DIFFERENT SEA LEVELS...

P(annual high level > level)

2010 2050 2100

Level relative present MSL (m)

18%

67% Hans Hanson, Lund Universty0%

IS IT ECONOMICALLY DEFENDABLE?

Cost dams/dunes (50 yr): about 0.6 MEuro/km = $M10 ~ $M0.2/yr $M0.5/yr Cost sand (~10 km): $M15 over 50 yrs = $M0.3/yr

Protected values (c:a) (2012): $B6

Cost ~ 0.4% ~ 0.008%/yr Total number of houses ~ 3,100

Home insurance premiums 2012 ~ $450/yr/house (avg SE) ~ $M1.5/yr Living expences 2011 (avg SE) ~ $12,000/month/house ~ $M37/yr

Commute cost (10 000 out, 3 000 in, 1.5 p/carl, 15 km*2) ~ $M0.1/day!

NL: Protective measures $M1,600/yr ~ 0.1%/yr

Hans Hanson, Lund Universty

16 ECONOMY BEACH NOURISHMENT YSTAD 2009

Total cost beach nourishment ~ 3 Mkr/yr 1 m2 7 m3 sand / m2 beach

3 2 1 m sand ~ 100 kr => 700 kr/m 7 m3

Beach tourism in Ystad total sale ~ 440 Mkr/yr

Total income (~12%) from beach tourism in Ystad ~55 Mkr/yr

Suppose 80% from 10 summer weeks => 4.5 Mkr/summer week (3Mkr in 4.6 days)

Suppose 80% Ystads Sandskog (1 km)  42 Mkr/yr = 42 000 kr/m/yr

Compensation for SLR = 500 000 kr/km/yr = 500 kr/m/yr! Hans Hanson, Lund Universty

Worst Case Scenario?

Hans Hanson, Lund Universty

17 THE END

L13-12 Hans Hanson, Lund Universty