Status and future of the operational oceanography in Denmarkgodae-data/OP19/1.1.5-Ocean... ·...
Transcript of Status and future of the operational oceanography in Denmarkgodae-data/OP19/1.1.5-Ocean... ·...
Status and future of the operational oceanography in Denmark
Vasily Korabel, Jens Murawski, Kristine Skovgaad Madsen, Jun
She, Vibeke Huess, Jacob Woge Nielsen, Till Rassmusen, Jacob Hoyer,
and the rest of the R&D team at DMI
OceanPredict19 , Halifax, 6-th May 2019
Denmark’s place in the oceanographic world
Denmark is a leading oceanographic center providing operational products for BS/North Sea• Storm surges• Wave forecasts• Ice forecasts for Greenland• Oil spill
DMI (Denmark) 2015-2016:WAM: local implementation to handle unresolved islandsonline-coupled bio model ERGOM HBM: code optimization for performance improvements (DMI)HBM+ERGOM: implemented improved river run-off and nutrients data (DMI)HBM: simple ice dynamic model + fast ice module implemented (DMI) SMHI (Sweden) 2017:Reanalysis system: NEMO + SCOBI + Ensemble 3dVarMSI (Estonia) 2015-2017CalVal system and dissemination unitBSH (Germany) 2017:ERGOM: improved chl calculations + light routine (Kd) FMI (Finland) 2017:WAM: local implementation to handle partly covered ice grids HBM: tuning ice-thermodynamic & heat exchange routines for improved sea ice product (DMI)
Copernicus Marine Environmental Monitoring Service (CMEMS): Consortium Service developments with DMI contribution
Existing ocean forecasting systems in Baltic Sea
ProductionUnit
Basin system Local system
Models Resolution Model Resolution Area
BAL MFC HBM 1.85km
BSH (GE) HBM 1.85km HBM 0.93km Transition waters
DMI (DK) HBM 5.55km HBM 0.40km Limfjoden
HBM 0.93km Transition waters
FMI (FI) OAAS (2D) 3.7km HELMI(sea ice)
1.85km Northern Baltic Sea
HBM 5.55km
MSI (EE) HBM 0.93km Gulf of Finland, Gulf of Riga
SMHI (SE) NEMO-Nordic
1.85km NEMO 0.36km Lake Vänern
NEMO 0.06km Brofjorden
UL (LV) HBM 102m -1.85km
Eastern Baltic Sea, lakes
Forecasting: Baltic-North Sea cooperation based on: Multiple forecastsReal-time data exchange (obs. & forecast) (Golbeck etal
2015)
≈1nm
≈0.5nm (1’x1.66’) ≈185m (6’’x10’’)
≈0.5nm (30’’x50’’)
2-way nesting:• to model Danish
territorial watersin high resolution
• to resolve narrowstraits
Dynamical nesting:Mass and momentum are exchanged on time step level during the update of the hydrodynamic equations.
Current operational CMEMS Model Setup
Fig. 1. Impact of model resolution on the Baltic inflow - bottom salinity difference (a) before and after the Major Inflow Event 2014/15 HBM0.9; (b) same as in (a) but for HBM1.8 (c) between HBM0.9 and HBM1.8 after the major inflow event (31-th May 2015).
HBM0.9 HBM0.9 –HBM1.8
May 2015minus Nov. 2014 May 2015
Bottom Salinity HBM1.8
HBM1.8
May 2015minus Nov. 2014
Bottom Salinity HBM0.9 Bottom Salinity HBM0.9-1.8
Inter-basin water exchange
1. Waves generate additional
drift currents of locally up
to 1 cm/s in the Gulf of
Finland (2 cm/s during
storms).
2. Wave induced oil drift
increases onshore oil
advection:
J. Murawski, J. Woge Nielsen, (2013) “Applications of an Oil Drift
and Fate Model for Fairway Design”, Chapter 11 of the book
“Preventive Methods for Coastal Protection – Towards the
Use of Ocean Dynamics for Pollution Control” (Editors
Tarmo Soomere, Ewald Quak), Springer 2013
T. Soomere, K. Döös, A. Lehmann, H.E. Markus Meier, J.
Murawski, K. Myrberg, E. Stanev (2014), “The Potential of
Current-and Wind-Driven Transport for Environmental
Management of the Baltic Sea”, 2014, AMBIO
Xi Lu, T. Soomere, E. Stanev, J. Murawski (2011), “Identification
of the environmentally safe fairway in the south-western
Baltic Sea and Kattegat using the Lagrangian trajectories”,
2012, Ocean Dynamics
landing probability20%
10%
-10%
-20%
0%
Coupled ocean-wave modelling
DMI, Research Evaluation , Copenhagen, 28-th Aug 2018
Shear Stress at
the sea bed
Fine Sediment
concentration in
the sea bed
SPM concentration
at the surface
Re-Suspension
Erosion
Sedimentation
Transport, sinking and upwards mixing of SPM
Processes:
•Sinking versus mixing
•Advection
•Sedimentation
•Re-suspension
•Erosion
•Consumption
•Bioturbation
3 SPM fractions:
wsink(f1)=0.0001 m/s
wsink(f2)=0.00002 m/s
wsink(f3)=0.001 m/s
EOOS, YEOS,
BALTADAPT:→ CLAIM
Improved shear stress
formulation, dependent
on the wave spectra.
Phenomenological model that describes theformation, consolidation and disintegration of fast ice, and the advance and retreat of its front.
Coastal Fastice Model
Ice growth
Damaging,Deformation
Sea ice thickness
Hirlam SKA
Requirement: high quality weather forcing for the entire domain
Storm surge prediction servicedevelopment, examples
Geographical representation: bathymetry, model tuning: bed friction, CD
100 years event inthe southern BS
Silent Storm SurgeJanuary 2017
November 2011
Multi-model ensemble and satellite observations. The Bodil storm surge example
DMI operational storm surge model overlaid with Cryosat satellite observations
BOOS ensemble of Baltic Sea models + observations
Future of the operational oceanagraphy in Denmark
Future activities focus on 3 issues: > filling observation gaps> improve forecast > modelling and provide better data and product service.
Ongoing : Development of a new operational NEMO-ERGOM-WAM-PDAF coupled system
i) being able to fully exploit benefits from future observationsii) generate meaningful products in finer scales e.g., sub-mesoscale and in estuary-coast-sea
continuum iii) efficient parallel computing and model grid structureiv) provide high quality forecasts as forcing to NWP and coastal climate modelsv) resolving correctly inter-basin and inter-sub-basin water exchange,vi) resolving synoptic variability and predictability in marine ecosystems, e.g., for algae bloom, vii) being able to address critical and relevant issues in coastal applications, e.g., marine spatial
planning, maritime safety, marine pollution protection, disaster prevention, offshore wind energy, climate change adaptation and mitigation
HBM v4
New pre-operational Model Setup
Nemo-Nordic
● Horizontal resolution of 1 nm
● 56 z* vertical layers
● GLS turbulence scheme
● OBCs from FOAM system
(T,S,U,V,SSH including tides)
● ATM forcing: mix of ECMWF 9km
and Arome 2.5km
● EHYPE hydrology
● 4 two-way nested subdomains with
horizontal resolution of 1-0.5 nm
● 21-122 z vertical layers
● k-e turbulence scheme
● Tides forced at open boundaries
● Climatological T/S OBCs
● ATM forcing: HIRLAM/HARMONY
2.3 km
● EHYPE hydrology
Water level validation
Intercomparison of HBM-NEMO water level
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
Aar
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Bal
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Deg
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RM
SD (
m)
RMSD of water level: 2011-2015
HBM-NoDA
NEMO-NoDA
NEMO-DA
Summary on water level comparison
• Validation shows lower quality of NEMO-Nordic water levelproducts at all 62 Baltic Sea stations in comparing with CMEMS HBM V4
• MME results show that NEMO’s water level forecast at SE and FI coast are in reasonable quality but has significantly lowquality at Jutland E. coast, Belt Sea and German coast.
• For a 50yr event at Slipshavn in 20171029, NEMO underpredicted sea level peak by ~50cm.
Objective evaluation scheme
• Estimate error statisticsin 4 zones for SST/SSH/ ice, T/S and currents
• Bias, RMSD and correlation
• Product type: • 2016/05/03-11/02
– NEMO: without DA– HBM: without DA
• Best estimate: 2011 to 2015
Zone 1
Zone 4
Zone 3Zone 2
Quantitative evaluationperformance scores
Definition of
category &
scores
Significantly
worse (SW)
Worse
(W)
Slightly
worse (SLW)
Similar
(S)
Slightly
better (SLB)
Better
(B)
Significantly
better (SB)
Category order 1 2 3 4 5 6 7
|Bias(HBM) |-
|Bias(NEMO) |
<-0.5 -0.5 – -0.2 -0.2- -0.1 ±0.1 0.1-0.2 0.2-0.5 >0.5
RMSD(HBM) –
RMSD(NEMO)
<-0.5 -0.5 – -0.2 -0.2- -0.1 ±0.1 0.1-0.2 0.2-0.5 >0.5
Score of HBM 0.1 0.25 0.4 0.5 0.6 0.75 0.9
Score of NEMO 0.9 0.75 0.6 0.5 0.4 0.25 0.1
T/S evaluation by zone
Water temperature: results show that HBM performs better in all 4 zones for bias and
Zones 1 and 4 for RMSD. NEMO is better in Zones 2 and 3 for RMSD.
Water salinity: results show that NEMO performs better in all 4 zones for bias while HBM
performs better for RMSD.
Summary on T/S validation• HBM has significant bottom salinity bias in open Baltic Sea,
NEMO has not. (better representation of slop flow)• In transition waters, HBM has significantly smaller T bias and
salinity RSMD than NEMO• There are no big differences in RMSD in T and S in open Baltic
Sea, except for – In Zone 3 deep layer, NEMO has significantly smaller T
RMSD than HBM– HBM has smaller RMSD in 15-50m depth
• Inflow: – HBM does not give inflow signal in the central Baltic
Proper; – Inflow into Bothnian Bay are not simulated in both HBM
and NEMO.
Inflow assessment
• For inflow in Danish straits and W. Baltic, HBM gives much more accurate signals in terms of salinity peak with -3% bias while NEMO-DA has a clearly overestimation by 18% for depth-mean max salinity at Arkona.
• For inflow in Baltic Proper, HBM and NEMO-DA both show inflow signals in H2 and K2 in 2011/12. HBM does not show salinity increase in J1 (C. Baltic) bottom layer in the 2014/15 event, as existed both in observations and NEMO-DA
• For inflow in GoF, both HBM and NEMO-DA are able to model a salinity increaseevent in early 2013
• For inflow in Bothnian Bay, both HBM and NEMO-DA are not able to catch a salinityevent in early 2013.
Development of assimilation scheme
• Observations: DMI SST,
L3S multisensor merged
0.02 deg daily
Method: PDAF ( LETKF)
Ensemble-based inhomogeneous /
anistropic background error covariances
based on 10-year hindcast run
+ FMI daily ice
charts
Improvements in SST: v3 REF, V4 REF and DA
Improvements in ice cover representation
Prototype of a next generation reanalysis system Testing Agrif capabilities with tides
At DMI Nemo-Nordic code was upgraded to Nemo v4.0
● Horizontal resolution of 1 nm with added Agrif 0,5 nm nest
in the transition zone
● 56 z* vertical layers
● GLS turbulence scheme
● OBCs from the global reanalysis system + tides TPXO 7.2
● ATM forcing: 11km UERRA
● EHYPE hydrology
Summary and future directions
THANK YOU !