eSurgeCork2014 D1Lecture03 CurrentStormSurgeModelling AS€¦ · 24/02/2014 3 Cork eSurge Training,...

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24/02/2014 1 Cork eSurge Training 20-21 Feb 2014 Modelling Surges [email protected] Thanks to: Jan Kroos (SVSD) Hans de Vries (KNMI) Martin Verlaan (Deltares) Cork eSurge Training, 20-21 Feb 2014 Cork eSurge Training, 20-21 Feb 2014 1953 Total sea level animation 1953 The animation shows the mean sea level pressure (blue contour lines), the wind at 10 m above the mean sea level (brown flags) and the total sea level (coloured, blue is NAP -5 m, red is NAP +5 m), starting on Jan 31, 1953 10:00 GMT and ending on Feb 2, 1953 0:00 GMT.

Transcript of eSurgeCork2014 D1Lecture03 CurrentStormSurgeModelling AS€¦ · 24/02/2014 3 Cork eSurge Training,...

Page 1: eSurgeCork2014 D1Lecture03 CurrentStormSurgeModelling AS€¦ · 24/02/2014 3 Cork eSurge Training, 20-21 Feb 2014 Mean Dutch tidal levels 0:00 12:00Time Cork eSurge Training, 20-21

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Cork eSurge Training20-21 Feb 2014

Modelling Surges

[email protected]

Thanks to:Jan Kroos (SVSD)

Hans de Vries (KNMI)Martin Verlaan (Deltares)

Cork eSurge Training, 20-21 Feb 2014

Cork eSurge Training, 20-21 Feb 2014

1953Total sea level

animation 1953

The animation shows the mean sea level pressure (blue contour lines), the wind at 10 m above the mean sea level (brown flags) and the total sea level (coloured, blue is NAP -5 m, red is NAP +5 m), starting on Jan 31, 1953 10:00 GMT and ending on Feb 2, 1953 0:00 GMT.

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Overview

The need for surge modelling Forecasting in the Netherlands Tides Satellite data Tide and surge propagation on a shelf Surges Forecasting Ensembles

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NL The

Netherlands is very vulnerable with most people living below sea level

The Rotterdam harbour fuels the Dutch economy

Trade and safety interests need trade-off

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Mean Dutch tidal waves

South to North Largest amplitude in South and North

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Mean Dutch tidal levels

Time0:00 12:00

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Normative levels in cmSection Exceedance

Probability

Per year

Station

Surge category / Level

Highest known level

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Results from the past . . .

Commensurate exceedance probability

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Surges and the Maeslantkering

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Accuracy surge forecasts is part of the strategy to close it

The Maeslantkering is closed when:The expected water level in

Rotterdam > 300 cm or Dordrecht > 290 cm above NAP

This occurs once per 7 to 10 years

Surges and the Maeslantkering

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Surges and the Maeslantkering

In 1988 standard deviation surge forecasts σ = 25 cm

MHW Rotterdam 365 cm Safety margin = 95 cm Accuracy forecasts 3*σ = 3*25 = 75 cm Additional margin 20 cm

Water level Rotterdam closure 270 cm Closing frequenty 1 / 2 per 3 years Not tolerable for Rotterdam harbour Surge forecasts need improvement!

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Ship traffic

Rotterdam anchorage Closure of

Maeslantkering causes economic loss

Shipping lanes appear in wind climate too at low winds

As well as platforms

R&D needed

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When building Maeslantkering

Rotterdam harbour threshold requirement:frequenty of closing Maeslantkering max. 1/10 years

MHW Rotterdam 365 Closing water level 300 cm (0.1 y-1) Safety margin (365 - 300) = 65 cm Additional margin 20 cm 45 cm margin for accuracy surge forecast

(3* standard deviation)

Requirement: accuracy surge forecasts Hoek van Holland is < 15 cm

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Progress surge forecasts Developments: High resolution models (weather, surge)

Data assimilation water levels (Kalman filtering)

Improved interaction hydrologists and Meteorologists

Better information exchange hydro-meteo

In 2007 standard deviation (RMSE) surge forecasts reached σ < 15 cm

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Accuracy surge forecasts Hoek van Holland

0

5

10

15

20

25

30

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1965 1970 1975 1980 1985 1990 1995 2000 2005

RM

SE

in c

m

0

5

10

15

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25

30

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# st

orm

vlo

eden

Mens-machine mix SVSD Model DCSM8 # stormvloeden

RMSE computed over period of 10 year

Berekeningsperiode

# st

orm

sur

ges

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Maeslantkering and seiches Mechanical joints can only hold pressure towards land Seiches may lower the seaward water level below the

inland water level A difference of 140 cm is dangerous The closed barrier responds automatically to low sea

level by controlled drifting of the doors This lowers the outward pressure on the doors

Cork eSurge Training, 20-21 Feb 2014

Roles KNMI and RWS

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History of water level modelsLorentz (1920) Waddenzee, 1 dimensional

Schalkwijk (1947) Hoek van Holland, from wind in 2 sections

Weenink en Groen (1958) 5 sections

Timmerman (1969) 6 sections

Timmerman (1975) Numerical linear model

Flather, IOS (1976) Numerical non-linear model

GB, D, DK, NL (1981) Model comparison

KNMI/IOS (1986) Numerical non-lineair model

WAQUA/CSM-16 (1991) Numerical non-lineair model (16 km)

GB, B, F, GR, NL (1992) Model comparison

Data Assimilation (1992) Kalman Filter in WAQUA

WAQUA/CSM-8 (1999) 8 km

WAQUA/CSM-8 (2008) Probability forecasts upto 240 hours

WAQUA/DCSMv6 +ZuNo.v4

(2012) 1.6km (leads to DCSMv6)

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Must see

www.dropbox.com/s/odzgofwtp3gkypz/globerefined.avi

Startup of global surge model- Check your own region- Effects of coasts and shelfs - Harmonics

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SectionsSchalkwijk (1947)

Usefulness Large scale storms Investigate meteo error

sensitivity

Not anymore Absolute water levels Small scale systems Quite circumstances

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SectionsSchalkwijk (1947)

Wind effect

Pressure effect

External surge

Back propagation

Total

See next slide

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Surge back propagationExample: Surge along Dutch coast Wind ceases Surge reflects to English coast Surge reflects again and returns 0,5 to 1 day later in

reduced form along the Dutch coast (20 – 30 %) Losses depend on basin shape, bottom and depth

UK NL

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Surge back propagationExample: Surge along Dutch coast Wind ceases Surge reflects to English coast Surge reflects again and returns 0,5 to 1 day later in

reduced form along the Dutch coast (20 – 30 %) Losses depend on basin shape, bottom and depth

UK NLStorm surge

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Surge back propagationExample: Surge along Dutch coast Wind ceases Surge reflects to English coast Surge reflects again and returns 0,5 to 1 day later in

reduced form along the Dutch coast (20 – 30 %) Losses depend on basin shape, bottom and depth

UK NLStorm surge

ReflectionEnglish coast

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Surge back propagationExample: Surge along Dutch coast Wind ceases Surge reflects to Englisch coast Surge reflects again and returns 0,5 to 1 day later in

reduced form along the Dutch coast (20 – 30 %) Losses depend on basin shape, bottom and depth

UK NLStorm surge

ReflectionEnglisch coast

ReflectionDutch coast

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Model forecasts

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Dutch Continental Shelf Model

Implementations of WAQUA Sequence CSM-16 (16 km; 1988), CSM-8 (8 km;

1999), DCSMv5, DCSMv6 (1.6 km; 2012) Also versions for southern North Sea (ZuNo),

coast and main rivers

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Dutch Continental Shelf Model DCSMv6 Improved representation of physical phenomena

such as tide and surge propagation and generation and the role of non-linear interactions therein– Bed friction (tidal wave amplitude; = g |u| u / C(D)2)– Bathymetry (tidal wave phase; u D1/2)– Wind forcing

Increased resolution of 1,6 km (representation) Initially NOOS and ETOPO2 bathymetry, but

optimised for stability and tidal propagation by altimeters

Open boundary where the amplitudes and phases of 22 harmonic constituents are specified

Zijlstra et al., Ocean Dynamics (2013) 63:823–847

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Astronomical CorrectionI. Model tides are not representative of station tidesII. Station tides are estimated by harmonic analysis of past

data (i.e., at average surge level), TSIII. Predicted model tides at stations are obtained without

meteorological forcing, TMIV. Predicted model water levels at stations are obtained with

meteorological forcing, WMV. Estimated water levels are corrected for the tidal

component, W = WM – TM + TS

Astronomical correction improves predicted water levels II and III may have different mean non-linear surge-tide

interaction Applicable only at tide gauge stations

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Bathym.

DCSMv6

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Obs.

Tide gauges (10 min.)

Altimeters 1992-2009 Jason-1/Topex-Poseidon

(~10 days)

Improved amplitude and phase of the actual tidal propagation harmonics

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Altimeter quality

Most uncertainty on the shelf

RSS Altimeter - GOTO0.2 tides RMS Altimeter ascending-desc.

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Tidal input verification

Surge model is calibrated by altimeter analyses Not possible with in situ data in deep waters

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Altimeter data assimilation

Provides correct astronomical input to DCSMv6

Next step: Verify tidal propagation modes within model area

Zijlstra et al., Ocean Dynamics (2013) 63:823–847

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Effect depth and sea bed

DCSMv6 Selected Dutch

stations Sea bed and depth

also affect surge propagation

Better bed and depth representation affects non-linear tide-surge interaction

Default bathymetry Bed roughness 0.026 s/m1/3

Default bathymetry Bed roughness 0.027 s/m1/3

Bathymetry – 2 m Bed roughness 0.027 s/m1/3

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Adaptation sections

More observations than adjusted parameters 100 sections, 200 parameters Minimize SD of differences model-obs www.openda.org

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Non-linear effects

Bottom friction term 2x depth term Depth term 2x advection term

A surge increases water level and makes the tide run faster

Neap tide surge contribution is larger than high tide surge contribution

Synchronized surges and tides interact Large non-linear effects for large surges

(Tide) + (Surge) ≠ (Tide + Surge)

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DCSMv6 2008 validation

Generally satisfying Shallow areas with variable bathymetry and

geometry remain most challenging

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DCSMv6 example

Surge errors dominate over tidal errors

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Kalman filterWeighted mean

Kalman filter K

Used here for water level

221

2

21

2211

22

11 11

iix w

wwww

xwxwx

x

x

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121

1221

21 K

xxKx

xxww

wxx

x

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Kalman filter flow

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Need for QC

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Kalman filter validation

Clear advantage over first 0.5-1 day Apparent overfitting thereafter for low water levels

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RMS verification high tides

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Bias verification high tides

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Meteorological inputs

Short range, limited area (HiRLAM, ECMWF boundaries) Up to 48 hours forecast 4 times a day: 0, 6, 12, 18 UTC Ready at 3, 9, 15, 21 UTC

Medium range (ECMWF) 48 hours and longer range 2 times a day: 0 and 12 UTC Ready at 7:30 (deterministic) Ready at 9:00 (ensemble)

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Pressure surge

1 hPa PMSL decrease theoretically causes 1 cm surge

Practically ~50% is realized– 1 hPa PMSL decrease theoretically causes 0.5 cm surge

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Ensembles

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Wind surge ensemble

50 ECMWF members, DCSMv6; surge and water level

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From plume to probability

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St. Nicolas surge warning

Integrate the probability in each warning class

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Alarm level probability

Can be done for each vulnerable location

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Case verification

Very serious threat; forecast fine, but lagged

Cork eSurge Training, 20-21 Feb 2014

Case verification

Underforecast in the North however by 0.35 m

Cork eSurge Training, 20-21 Feb 2014

What’s next

Take away remaining uncertainties Mesoscale wind forcing Air-sea interaction (momentum flux) Improving water-level representation inside

estuaries and shallow seas (increased resolution) Data assimilation of heights and winds to

increase predictive quality for the shorter lead times (<12 h)

Steric effects (salinity, SST)

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Mesoscale meteo oscillations

Large-scale turbulence and convection– Periods from minutes to an hour– Additional surges of a few dm max.– Occurs typically within a day due to unsettled

atmospheric conditions

Cork eSurge Training, 20-21 Feb 2014

OSCAT

50 km

12.5 km

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Maeslantkering closure

Surface winds from HARMONIE model at 1.7 km grid

HARMONIE shows mesoscale structures

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Mesoscale meteo oscillations

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Mesoscale meteo oscillations

Convective cells

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Squall lines

Characteristic– Sudden surge wave along a line– Single wave (modest tsunami)

Squall line or organized convection Surge period 30 min to 3 hours Surge up to 70 cm

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Squall line

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Squall line

Squall line

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3 Januari 2012

Squall line in rain radar

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Another meter in IJmuiden, 50 cm Roompot Buiten

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1 nov 2006

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Underpredicted surge Delfzijl

31/10/’6 18Z 1/11/’06 4Z

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Storm and high water Delfzijl (NL)

1/11/’06 6:14

• 0.5 m underpredicted surge by HiRLAM (blue) and ECMWF winds (green)

• OSI SAF QuikScat winds (red) are stronger and/or more directed into the harbour

NRT constellation needed R&D on mesoscales needed Coastal zone winds Extreme winds

1/11/’06 4:03

• Delfzijl

Cork eSurge Training, 20-21 Feb 2014

Sharp trough results in +0.7mAllerheiligenvloed 1 nov 2006

Wind forecast Surge forecast

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Eems Dollard 1 nov 2006

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21 maart 2008 H. van Holland

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Polar Low 21 Mar 2008 12:00

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Polar Low

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Front passage 5/6 Dec 2013

Extra surge at front passage

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Harbour seiches Characteristic

– Sudden surge along the coast reinforces in a harbour

Cause– Atmospheric convective cells above North Sea with

associated wind fluctuations of periods of 1 to 2 hours

– (Long-range) swell

Surge period 1 to 2 hours Surge 0 – 150 cm Duration 1 day or a few days Resonance with harbour basin dimensions

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Harbour seiches

Harbour seiches

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Seiches 5/6 Dec 2013

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Seiche mechanism

Convective-clouds

Sea level30 – 100 km

2 –

4 km

Direction front (N)NW

Seiche at sea 10-20 cm

cold front

Vertical temperature gradiënt typically7-10 gr / km for convective cells

Convective cells

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Convective cells

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Better use of observations More capable computers Improved weather models

NH

ZH

Weather forecasts improve

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Improve meteorology?

Greg.J. Tripoli, Un. Wisconsin

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Bus?

planetary waveslow pressure systemsstorms, frontsorographic circulations

matu

re sy

stem

sd

evelo

pin

g sy

stem

sb

ou

nd

ary

layer

Temperatuur en druk bepalenweerevolutie

Fast

Slow

Temperature and pressure determineweather evolution

Mis

t

Clo

ud la

yer

R

ain

colu

mn

10

V [

m]

100

1

000

10.

000

10 100 1000 10.000 H [km]Shower Front Storm Climate zone World

Wind determinesweather evolution

Cork eSurge Training, 20-21 Feb 2014

Cork eSurge Training, 20-21 Feb 201490ERS-2 scatterometer wave train; missed by HiRLAM

Mesoscale waves

NWP models miss wave

Next day forecast bust in UK and NL

Clouds alone do not depict dynamics well

Rossby wave

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Scatterometers in operation

9:30 LST & 21:30 LST: Advanced Scatterometer ASCAT-A and ASCAT-B carried by the Metop-A and MetOp-B meteorological satellites operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT); operational

12:00 LST & 0:00 LST: OSCAT from the Indian OceanSat-2 scatterometer; operational

6:00 LST & 18:00 LST: HSCAT from the Chinese HY-2A scatterometer; experimental

These all have follow-on instruments

WMO requires 6-hourly OSVW coverage Surges, diurnal cycle, mesoscale convective systems, eddy-scale

ocean applications, air-sea interaction, coastal applications

Cork eSurge Training, 20-21 Feb 2014

ASCAT and QuikScat impactJapan Meteorological Agency

ASCAT has smaller rain effect; splash remains

Cork eSurge Training, 20-21 Feb 2014KNMI Scientific

Review, January 13-

93

Product quality varies in TCs

TC Katrina just before landfall

KNMI SDP25 NOAA DIRTH

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Thinned data at ECMWF Mainly larger scales are assimilated With good impact though

Cork eSurge Training, 20-21 Feb 201495ERS-2 scatterometer wave train; missed by HiRLAM

Mesoscale waves

NWP models miss wave

Next day forecast bust in UK and NL

Clouds alone do not depict dynamics well

Rossby wave

Cork eSurge Training, 20-21 Feb 2014

Extreme winds

capability

NOAA hurricane flights

Ike: highest ASCAT speed ever at the time (75 knots) and we were just there !

Lack of buoy data > 20 m/s

ASCAT lacks H pol and sensitivity

Tested VH for Post-EPS

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ASCAT Ultra High ResolutionArea of 2 by 2

Centered around

19N 129E

(NE of Philippines)

26-10-2010 00:36

12.5 km

Coastal ASCAT wind product available at KNMI

Cork eSurge Training, 20-21 Feb 2014

ASCAT Ultra High Resolution

6.25 km

Sharper shear lines, divergence patterns

Cork eSurge Training, 20-21 Feb 2014

• Noisy

• Needs improved QC on footprint level

• MSS ?

• Rough eye as also witnessed by SFMR

• Do you want such products ?

3.125 km

ASCAT Ultra High Resolution

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Spatial representation

We evaluate area-mean (WVC) winds in the empirical GMFs 25-km areal winds are less extreme than 10-minute sustained in situ

winds (e.g., from buoys) So, extreme buoy winds should be higher than extreme scatterometer

winds Extreme NWP winds are again lower due to lacking resolution (over

sea)

Wind scales

0

10

20

30

40

0 25 50 75 100 125 150 175 200

Distance (km)

Win

d s

peed

(m

/s)

BuoyASCATECMWF

Cork eSurge Training, 20-21 Feb 2014101

Standards in TC classification

Hurricane standards are based on 1 ormin mean winds, not on 25-km mean winds !

Need for unification in names ?! DTU Summerschool, 2011

Cork eSurge Training, 20-21 Feb 2014102

WVC size WVC size is

50/25/.. km Extreme winds are

smeared out How to translate

scatterometer winds to hurricane categories ?

Same guidance in tropics as extratropics ?

Typical factor of 1.5-2.0 between 10-min winds and scatterometer winds

WVC size

DTU Summerschool, 2011

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Data Assimilation Systems (DAS) are cycled at the cut-off time Observation timeliness is subtracted from the cut-off point (t) Only in initial part of the analysis window observations are used This corresponds to a “duty cycle” percentage

What is the duty cycle for current operational HiRLAM implementations ?

Data Assimilation System Cycling

Analysis Window

Cut-offL2B tUsed

indow

Cut-offt

Analysis W

L2B Used

Cork eSurge Training, 20-21 Feb 2014

QRT timeliness ≡ 30 minutes, NRT ≡ 120 minutes Earth rotates at 825 km/h east (true at 60 N), such that the number of

data assimilation cycles can be approximated from SizeX (Lon) NRT 50% or less, while QRT about 70-100% observation data use

Rapid cycles with short cut-off are most sensitive to timelinesshttps://hirlam.org/trac/wiki/HirlamInventory/Operational

Model DMIT15

DMIM09

FMIRCR

FMIMB71

AEMETONR

KNMID11

Met.ieI10

Met.no12

SMHI C22

EMHIETA

LHMS HL8

Dxy km 16.5 9.9 16.5 7.48 17.6 11 11 11.88 22 11 8.8

SizeX km 10065 7227 9603 3606 10243 8976 7194 10264 6732 4026 1637

SizeY km 9372 7385 7392 2693 7462 7150 4664 8292 6732 3080 1637

Cycle hr 6 6 6 6 6 3 6 6 6 6 6

Cut-off min 100 100 120 120 120 120 110 125 115 120 120

QRT/cycle min 250 250 270 270 270 180 260 275 265 270 270

NRT/cycle min 160 160 180 180 180 90 170 185 175 180 180

QRT/cycle % 69 69 75 75 75 100 72 76 74 75 75

NRT/cycle % 44 44 50 50 50 50 47 51 49 50 50

Need for Quasi Real Time

Cork eSurge Training, 20-21 Feb 2014

Prospect based on HiRLAM operations

~70-100% of scatterometer QRT L2B winds can be used in current HiRLAM implementations

< 50% of scatterometer NRT L2B winds can be used in HiRLAM These numbers vary for other NRT and QRT specs.

and other model cycles

There is a general tendency to 3-h cycling and fast cut-off in the coming years to better exploit fast observations (like EARS), increasing the need for QRT delivery in regional NWP

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ASCAT scatterometer

Europe’s contribution

Cork eSurge Training20-21 Feb 2014

ASCAT-A and ASCAT-B come together

Convectivedownbursts

Cork eSurge Training, 20-21 Feb 2014

Triple collocation result ASCAT winds are veryaccurate

ASCAT error SD is smallerthan representativenessvector error SD

Buoy errors appear large(current, wind variability)

ECMWF winds appear smooth and biased lowon average

In extreme weather muchlarger deviations will occur

See also Vogelzang et al., JGR, 2011

ECMWF ScaleError SD U m/s V m/s

Buoy 1.44±0.02 1.59±0.02

ASCAT 1.05±0.02 1.29±0.02

ECMWF 1.32±0.02 1.18±0.02

Scatterometer ScaleError SD U m/s V m/s

Buoy 1.21±0.02 1.23±0.02

ASCAT 0.69±0.02 0.82±0.02

ECMWF 1.54±0.02 1.55±0.02

Representativeness (r2) 0.78±0.02 1.00±0.02

Trend U m/s V m/s

ASCAT 0.99 0.99

ECMWF 0.97 0.96

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OceanSat-2 scatterometer

OSCAT

International collaboration and cal/val team

Cork eSurge Training, 20-21 Feb 2014

Independent verification

KNMI processing delivers best verifying OSCAT winds

More extended verification needed

Naoto Ebuchi, Tokai Un., Japancoaps.fsu.edu/scatterometry/

meeting/past.php#2013

Cork eSurge Training, 20-21 Feb 2014

Independent verification

Naoto Ebuchi, Tokai Un., Japan, coaps.fsu.edu/scatterometry/meeting/past.php#2013

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OSCAT Monitoring• KNMI OWDP speed bias against

the global UK MetOffice NWP model (background) in March 2012

• Uncorrected OWDP• NSCAT2 GMF

• OWDP version with orbit-height based backscatter bias correction in dB

• NSCAT3 GMF

www.nwpsaf.org

Cork eSurge Training, 20-21 Feb 2014

OSCAT impact in TC forecasts

• Mean position errors (of MSLP minimum) of the 2011/2012 Tropical Cyclones in the south-west Indian Ocean as forecast with the regional Aladin Réunion NWP model (Dominique Mékiès, 2013).

• ASCAT is used in both.

Cork eSurge Training, 20-21 Feb 2014

Impact of assimilated observations on Forecast Error Reduction

[C. Cardinali, ECMWF]

The forecast sensitivity to observations measures the impact of the observations on the short‐range forecast (24 hours). The forecast sensitivity tool developed at ECMWF computes the Forecast Error Contribution (FEC) that is a measure (%) of the variation of the forecast error (as defined through the dry energy norm) due to the assimilated observations. 

May 2013 versus  May 201212%  Smaller Global FcError2% FcError Reduction due to  GOS

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HY2A Scatterometer

[email protected]

Anton Verhoef

Same approach as for OSCAT Data exchange Offer expert and GS support

Cork eSurge Training, 20-21 Feb 2014

Collocation result - u (559551 wind vectors)

-20 -10 0 10 20Model u component (m/s)

-20

-10

0

10

20

Scattero

mete

r u c

om

ponent (m

/s)

-20 -10 0 10 20

-20

-10

0

10

20

Collocation result - v (559557 wind vectors)

-20 -10 0 10 20Model v component (m/s)

-20

-10

0

10

20

Scattero

mete

r v c

om

ponent (m

/s)

-20 -10 0 10 20

-20

-10

0

10

20

Collocation result - speed (559540 wind vectors)

0 5 10 15 20 25Model wind speed (m/s)

0

5

10

15

20

25

Scattero

mete

r w

ind s

peed (

m/s

)

0 5 10 15 20 250

5

10

15

20

25Collocation result - direction (518777 wind vectors)

0 90 180 270 360Model wind direction (deg)

0

90

180

270

360

Scattero

mete

r w

ind d

irection (

deg)

0 90 180 270 3600

90

180

270

360 KNMI L2B vs ECMWF

1.48 m/s

1.44 m/s 1.44 m/s

10.58 deg

OWDP as used for QSCAT and OSCAT

-1.7 dB 0 correction -0.0001 linear outer

beam correction No outer swath WVCs No low wind adaptation

Speed bias removed Low winds introduced Rain issue reduced Scores similar to

QuikScat and OSCAT

Cork eSurge Training, 20-21 Feb 2014

Case study: closure Maeslantkering

Part of the Dutch Delta Works plan (initiated after the 1953 flooding disaster) to protect the South-Western part of the Netherlands for high sea levels

Closed for the first time:– 9 November 2007

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surface wind speed

AN: 2007110900FC+6

VT: 2007110906

Note the maximumwind speed in

South-West Netherlands for

conv+scat experiment

121110987

654321

no assim

conv + ascat + qscat

ECMWF

verifying qscat

Closure Maeslantkering …zooming in to The Netherlands

Cork eSurge Training, 20-21 Feb 2014

Maeslantkering closure

Surface winds

Harmonie shows structures not observed by QuikSCAT

Note: QuikSCAT footprint is about 50 km2

Cork eSurge Training, 20-21 Feb 2014

OSCAT

50 km

12.5 km

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Hurricane winds Discussion on highest ever peak winds

from Haiyan in the media, but impossible to measure!

Maximum 1-minute sustained winds are also difficult to know

Scatterometer winds are mentioned in 20% of ALL NHC TC discussions; these are calibrated against NOAA hurricane-hunter winds (SFMR & dropsondes)

Scatterometers measure 25-km scale winds and are much less extreme than peak winds

Current scatterometers either capture rain and/or saturate at 40 m/s; ASCAT-SG will measure extremes (2022)

The impact of a hurricane surge is catastrophic and depends on wind speed, wind direction, wind duration and wind fetch as e.g. depicted by NWP wind forecasts

Forecast errors need to be monitored against observations for surge quality assurance TC Rita

Cork eSurge Training, 20-21 Feb 2014

Global constellation users

OSCAT Beta UsersCanada

China

Europe

Hong Kong

India

Japan

Russia

SH

USA

OSI SAF Message List South America

Oceania

Europe

Other

Canada

China

Hong Kong

India

Japan

Korea

Russia

Taiwan

USA

KNMI OSCAT experimental winds were already distributed all over the globe to beta users (left)

All EUMETSAT SAF wind product service messages are popular world wide (now include OSCAT; right)

Service messages also through EUMETCAST and JPL PODAAC China is using constellation data right now

Cork eSurge Training, 20-21 Feb 2014

NWP SAF software users

AfricaChinaEuropaIndiaOther AsiaRussiaSouth AmericaUSA

Concerns all versions of AWDP, SDP and OWDP (247 users) In addition to the wind products, also EUMETSAT SAF wind processing codes

are popular world wide Both Ku-band processing codes (31) and AWDP (26) are popular in China

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Training EUMETRAIN Marine Forecasters Course:

webcast on Measuring Winds from Space http://www.eumetcal.org/courses/course/view.php?id=112&section=1

Training Course Applications of Satellite Wind and Wave Products for Marine Forecasting http://vimeo.com/album/1783188 (video)

Forecasters forum http://training.eumetsat.int/mod/forum/view.php?f=264

Xynthia storm case http://www.eumetrain.org/data/2/xynthia/index.htm

EUMETrain ocean and sea week http://eumetrain.org/events/oceansea_week_2011.html (video)

NWP SAF scatterometer training workshop http://research.metoffice.gov.uk/research/interproj/nwpsaf/scatterometer/data_assimilation_workshop/

Use of Satellite Wind & Wave Products for Marine Forecasting http://classroom.oceanteacher.org/course/view.php?id=103

Satellite and ECMWF data vizualisation http://eumetrain.org/eport/smhi_12.php?

Cork eSurge Training, 20-21 Feb 2014

Summary

WMO expresses a global need for scatterometer winds every 6 hours

The CEOS OSVW virtual constellation contributes to resolve the earth’s surges

The constellation partners make an effort to exchange their public resources for their own and the global public good

Exchange with ISRO operational NSOAS exchange is starting up The constellation winds do indeed lead to global societal

and economic benefits in diverse application areas, including surges

L-band (extreme) winds are emerging as well as SAR winds which are clearly complementary

Needs are NRT, coastal, extremes, and mesoscale (seiches); any priority or other needs?

Cork eSurge Training, 20-21 Feb 2014

ASCAT-A ASCAT-B

t = 50 minutes

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OSCAT

That’s why we needed wellies in Venice !

Cork eSurge Training, 20-21 Feb 2014

Cork eSurge Training, 20-21 Feb 2014

All maps are at tf=60 [h]; which model surge plot 1-4 corresponds to which map A-D?

ModelObs. 1

3 4

2A

DC

B