Impacts of ocean observations on ocean (re)analysis and ...
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© ECMWF November 26, 2020
Impacts of ocean observations on ocean (re)analysis and coupled forecasts
Hao Zuo, Magdalena Alonso Balmaseda, Beena Balan-Sarojini, Christopher Roberts, Michael Mayer, Steffen Tietsche, Patricia de Rosnay
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 2
ECMWF Ocean and sea-ice (re)analysis systemOverview of the OCEAN5 setup
Zuo et al., 2019
OCEAN5 is the 5th generation ofECMWF ocean and sea-ice ensemblereanalysis-analysis system (Zuo et al.,2018, 2019).
• Ocean: NEMOv3.4
• Sea-ice: LIM2
• Resolution: ¼ degree with 75 levels
• Assimilation: 3DVAR-FGAT
• 5 ensemble member
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 3
Ocean in-situ observations used by ECMWF
Ocean in-situ observations in 5-days (After QC, Feb 2019)
0 150 300 450 600
Atmosphere
Ocean
Obs used (M) Obs received (M)
Ocean observation is about 1/1000 to 1/10000 smaller than Atmospheric observation
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 4
~1e6 /day
Sea-Level Anomaly (Altimeter)Sea-ice thickness
Sea-ice concentration
Ocean model
Nudging
SST (IR, PMW)
Nudging3DVar
3DVar
Satellite sea surface observations
~1e6 /day
~1e5 /day
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 5
Ocean observations impact: ocean reanalysis
Temperature RMSE: 0-1000m
MRB: moored buoyOSD: CTD sondeXBT: Expendable bathythermographPFL: Argo float
~65% of the total RMSE reduction comes from assimilating in-situ data
Assimilation of ocean in-situ observations helps to constrain the 3D ocean, therefore providing better estimation of the ocean initial condition for the coupled forecasting system
Model free run
ORAS5With DA
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 6
2.8 33.5
3.8
4.5
S1 S2 S3 S4 S5
Lead
Tim
e (m
onth
s)
Forecast lead month for correlation above 0.9 in NINO3.4 SST anomalies
2.8 33.5 3.8
4.5
3.2
S1 S2 S3 S4 S5 S5-NoOobs
• Gain about 1.3 months in ENSO prediction
• Without Ocean observation and DA, we would lose about 15 years of progress.
1997 2002 2006 2011 2017
OCEAN5 provides ocean and sea-ice initial conditions for all ECMWF coupled forecasting system: (ENS, HRES, seasonal-S5).
Ocean observations impact: ENSO prediction
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 7
Impact on ocean data assimilation system
Maps of normalized RMSD of Temperature (upper 700m) in OSEs
Zuo et al., 2019, Ocean Science
Remove Moored buoys
Remove all in-situ
Remove CTD/XBT/MBT
Remove Argo Remove in-situ only in Atlantic
RMSD w.r.t a reference reanalysis, in which all in-situ data are assimilated.
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 8
Significant degradation in ocean surface and subsurface variables when removing observationsFrom week 1 to week 4
Ocean observations impact: Extended Range
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 9
SIC DA and impact on sea-ice reanalysis
L4 OSTIA Sea-Ice Concentration (SIC) is
assimilated through outer-loop coupling in
NEMO-LIM2, with a 3DVar-FGAT scheme.
This has a positive impact on both SIC and
SIT analysis states.
SIC bias (1980-2016)Ref data: OSI-SAF 430
With SIC DAWithout SIC DA
In percent
In m
SIT bias (2011-2016)Ref data: CS2SMOS merged data
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SIT DA and impact on sea-ice reanalysis
where 𝑆𝐼𝑇! is the nudged thickness, 𝑆𝐼𝑇" is the modelled thickness, 𝑆𝐼𝑇# is the observed thickness (CS2SMOS), tau is the nudging coefficient
No SIT nudging with SIT nudging
Balan Sarojini, et al. The Cryosphere, in review
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October 29, 2014WMO 7TH WORKSHOP ON THE IMPACT OF VARIOUS OBSERVING SYSTEMS ON NWP 11
SIT DA and impact on sea-ice forecasts
with SIT nudging – No SIT nudging
Spatially integrated SIC mean absolute error over lead month (72 forecasts each first of the month: 2011-2016, verified against OSI-401-b)
Difference in forecast Integrated Ice Edge Error (2011-2016, verified against OSI-401b)
Balan Sarojini, et al. The Cryosphere, in review
Mean absolute error in SIC forecasts
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Summary and conclusion
Assessments of ocean and sea-ice observation impacts on ocean reanalysis, and coupled reforecasts have also been carried out using the operational ECMWF system.
• Assimilation of ocean observations has a strong positive impact on the performance of ocean reanalysis, with almost 2/3 of the error reduction comes from in-situ data.
• Removal of all ocean observations leads to significant degradation in forecasted ocean states from week 1 to week 4, and has a negative impact (~2 month skill) on coupled forecasts of ENSO prediction.
• Adding sea-ice thickness constrain has reduced the biases in the sea-ice initial conditions, which then leads to improvement on predictive skill of pan-Arctic sea-ice for lead times of up to 7 months.
• Coordinated efforts on developing a experimental framework and analysis methodology for assessing observation impact in ODA and coupled forecasts are needed (see Fujii et al., 2019).
A consistent, homogenous and deep reaching global ocean observing network is absolutely essential for both operational NWP and climate monitoring services.