DMI forecasting system forBaltic-North Sea (DMI BSHcmod),

and also for Greenland,NW Shelf (Hycom)

Jens Murawski (DMI)

Agenda

• DMI BSHcmod: An operational

Baltic and North Sea model– History– Model features– Quality – Ongoing developments

• An introduction to– DMI drift model– N. Atlantic/Greenland model – HYCOM– Wave model - WAM

• 2000: BSH kindly provided its operational model BSHcmod

• 2000: BSHcmod run operationally in DMI with DMI forcing

• 2003: Information system – http://ocean.dmi.dk

• 2004: SST assimilation (ODON)

• 2005: MERSEA Baltic V1

• 2006: MERSEA Baltic V2

History of BSH/DMIcmod

1998: DMI operational oceanography section

2005: DMI Marine Forecasting Centre

2006: DMI Centre of Ocean and Ice

2006: Marine Ecological Modelling Centre (Jointly by DMI-NERI-DIFRES)

Organisation of the DMI

Current model features

Forcing

Open boundary:T/S: dynamic boundaryfrom POLCOMS Monthly climatologyWater level: Tides, surge,baroclinically correctedwater level

River runoff: realtime data from(SMHI, BSH) & adjusted climatology for the rest

Meteo. Forcing - DMI-Hirlam 15km/5km, 60/54 hours prognoses

Current DMI 3D ocean model: BSHcmod

• BSHcmod, provided by BSH 2000, developed by DMI

• 3 nested layers: 6-3-0.5nm

• Coupled ocean-ice

• two way nesting

• Flooding-drying

• 50 layers (8-2-2…-50)

• Twice daily, 54h forecast

• Daily river runoff + climatology NEA: 6 nm, NS/BS: 3 nm, IDW: 0.5 nm

DMI BSHcmod: new features

1.) Surface heat flux: Windspeed & Airtemp. dependent

2.) Including vertical Penetration of short wave radiation

3.) Vertikal mixing: K-epsilon, k-omega model adapted

4.) Horizontal mixing: a new term to control div/conv.

5.) Surface momentum flux: currents dependent

6.) Simplified & Full ensemble Kalman filter for SST assimilation

Surface heat flux (cont.): SSTChange heat flux coeffcient, Kara et al. (2000) CL= f (W,Ts–Ta)

Bias [Cº]

Comparisson withODON data for 2001

SST Bias improves ~ 0.1°C

Vertical mixing

Improving diffusivities of momentum, heat and salt

• k-ε turbulence modele.g. Axell, JGR (2002)

• stability functions in terms of shear and gradients of S and T

Canuto et al., JPO: Part I (2001) + Part II (2002)

k-ω based mixing scheme: salinity in Great Belt (preliminary)

Ref.

k-ω

DMI cmod validation

Days since 2000/07/15

Bottom temperature:FYN6700053 Old k-ω

New k-ω

spring summer autumn winter

Wind friction

Wind induced shearstress is currentvelocity dependend

k-ω surfaceboundary conditionsare z0 dependend

z0 is either const. orsig. wave heigth dep.

New: currents dependend wind friction and wave height dependend roughness length

Southern Baltic Sea

color: windspeedarrows: currents (magnitude and direction)

color: currents (magnitude)arrows: currents (direction)

Quality

Water level forecasts, peak error

DK stations, 2002-2004, 4 models

Cmod: <10% in 2004

MIKE 21: 2D FD; official storm surge model; ~18% 2002-2004

MOG2D: 2D FE, from 2003

Staumod: 2D version of Cmod, no stations in IDW

MO

G2D

200

4

MO

G2D

200

3

Stau

mod

200

3

Cm

od 2

003

Mik

e21

2003

Stau

mod

200

2

Cm

od 2

002

Mik

e21

2002

Mik

e21

2004

Cm

od 2

004

Stau

mod

200

4

Data assimilation, SST:

Larsen et al., JMS 2006

DA

model runs for 2001 by assimilating SST from different products (NOAA 12, 14, 16)

Control DA

Bias 0.78 0.07

RMSE 1.20 0.64

psukts

BSH/DMIcmod results

Surface currents Salinity

Comparison of satelite SST withsimulated temperature values

Model-data comparison: Drogden Buoy station, T/S at 3.6m (inflow signals)

Temperature, year 2004 Salinity, year 2004

Observation (red)Model data (blue)

Bias(z) = -0.7 ,..., -0.3Std(z) = 0.6 ,..., 1.1

Bias(z) = -0.03 ,..., 0.8Std(z) = 2.0 ,..., 2.6

Surface Temperature 1.0m

Bottom Temperature 36.6m

Bottom Salinity 36.6m

Surface Salinity 1.0m

NOVANAstation

VSJ 20925(southernKattegat)

North Atlantic/Greenland modelling

depth maps:Etopo2

0.5deg-10km res.22 layers

data assim.:sst

2x/day, 66h

ECMWF 6hly forcing

Outline

1) Ocean modelling:HYCOM setup for the Atlantic and Arctic Ocean (~50 km)Nested around Greenland (~10 km)

2) Drift modelling for 2005:Random walk diffusionNormal distributed in time (40 days window),1000 particles

2a) Drift as eggs:On top of the Irminger Water component (use fixed density), First feeding larvae after 300 degree-days

2b) Drift as pelagic larvae Surface: 20m, 40m, 60m (use fixed depth)Exponential temperature dependent increase in weight: Wi~Wi-1*exp(T)Settling when reaching 210 mg dry weight

SST monthly mean SSS monthly mean Profiles at Diskobay position

Operational forecast for Greenland

•Currents•Salinity•Temperature•Mixed layer deepness•Ice thickness and concentration

Drift model

Emergency module, used primarily for oil spill

Other apllications, floating object, dissolved substance, fish larvae drift, …

Circulation model add-on module (HYCOM or BSHcmod)

The Fu Shan Hai collision, May 2003

The vessel sank at 68m depth, and began to leak fuel oil

The oil rises as a plume from the sunken ship

10 day simulation of Fu Shan Hai accident

Wave model WAM Cycle4

depth maps:Etopo5

sea ice:NCEP

0.5deg-10km-2km resolution

4x/day, 60h

Ongoing developments

Wave-current interaction

• DMI BSHcmod-WAM coupling– Two-way interface ready– WAM with current refraction running pre-

oprational– More coupling mechanisms to be added:

(Wave induced mixing)

Wave-Current interaction,01.10.2007 12:00

Sign. wave height up to 7m Δ(sign. wave height) = 1m,…,1.5m

Windspeed up to 20m/s

Differences of about ± 1maround Greenland

SPM modelling

• GKSS SPM model is coupled with DMI BSHcmod• Wave influenced vertical exchange of SPM• Horizontal advection as passive tracer (Cmod)

Ecological modelling

• DMI BSHcmod-ERGOM coupling– Framework ready, in model calibration– Assimilating satellite chl-a – Operationalisation

Sediment dynamik influencesthe nutrients concentration inthe water column.

Sedimentconcentrationregulates thepenetration depthof light

ERGOM

HTTP://OCEAN.DMI.DK

Thank you!!