Experiments with Monthly Satellite Ocean Color Fields in a NCEP Operational Ocean Forecast System...
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Transcript of Experiments with Monthly Satellite Ocean Color Fields in a NCEP Operational Ocean Forecast System...
Experiments withExperiments withMonthly Monthly Satellite Ocean Color FieldsSatellite Ocean Color Fields
in a NCEP Operational Ocean Forecast Systemin a NCEP Operational Ocean Forecast System
PI: Eric Bayler, NESDIS/STARPI: Eric Bayler, NESDIS/STAR
Co-I: David Behringer, NWS/NCEP/EMC/GCWMBCo-I: David Behringer, NWS/NCEP/EMC/GCWMB
Co-I: Avichal Mehra, NWS/NCEP/EMC/MMABCo-I: Avichal Mehra, NWS/NCEP/EMC/MMAB
Sudhir Nadiga, NWS/NCEP/EMC – IMSGSudhir Nadiga, NWS/NCEP/EMC – IMSG
BackgroundBackground
Penetration and absorption of solar insolation in the upper layers of the ocean is affected by the optical properties of the water column
The vertical distribution of heating due to the absorption of solar radiation affects near-surface heat content and vertical stability
• Affects surface heat flux
Chlorophyll concentration has been found to correlate to the optical properties of water column
NCEP operational models employ a limited climatology (1998-2001) of satellite (SeaWiFS) ocean color data for modeling this process
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SeaWiFS
MotivationMotivation
Improved ocean and coupled ocean-atmosphere forecasts
Better representation of vertical distribution of solar radiation over the water column by properly representing temporal changes
Reduce biases and need for constraining the model (relaxation to observed surface and subsurface fields)
Transition towards operational near-real-time use of VIIRS ocean color data in operational ocean modeling
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NPP/JPSS VIIRS
NCEP OPERATIONAL OCEAN NCEP OPERATIONAL OCEAN MODEL MODEL
NOAA/OAR/GFDL Modular Ocean Model (MOM4) Global Ocean Data Assimilation System (GODAS) / Coupled
Forecast System (CFS) Grid:
Tripolar 1/2°×1/2° equatorial region: 1/2°×1/4°
Relaxation: SST – 30-day to daily Reynolds ¼-degree optimally interpolated SST SSS – 30-day to WOA 2009 SSS annual mean
Reference: Behringer, D. W., The Global Ocean Data Assimilation System at NCEP, AMS 87th
Annual Meeting, 2007.
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InvestigationInvestigation Design Design Data gaps: Filled by linear spatial and temporal interpolation
Forcing: All runs atmospherically forced by daily Climate Forecast System Reanalysis (CFSR,
1979 – 2009) values. CFSR modified with NRL-added scatterometer data (wind stress, wind speed)
Control: SeaWiFS chlorophyll monthly-mean climatology (1998 – 2001); Note: extreme ENSO
event 1997-1998
Annual chlorophyll cycle, no subsurface data assimilation
12-year model run: cyclical chlorophyll, sequential atmospheric forcing (1998-2009)
Experiment 1 (Exp1): Extended SeaWiFS chlorophyll monthly-mean climatology (1998 – 2010)
Annual chlorophyll cycle, no subsurface data assimilation
12-year model run: cyclical chlorophyll, sequential atmospheric forcing (1998-2009)
Experiment 2 (Exp2): SeaWiFS monthly mean chlorophyll (1998 – 2010)
Sequential monthly-mean chlorophyll no subsurface data assimilation
12-year model run: sequential chlorophyll and atmospheric forcing (1998-2009)5
Environmental State ReferenceEnvironmental State Reference
Climate Forecast System Reanalysis (CFSR) Reanalysis defines the mean states of the atmosphere, ocean, land surface and
sea ice Global, high-resolution, coupled atmosphere-ocean-land surface-sea ice model
system provides the best estimate of the state of these coupled domains over the period 1979 – 2009
Continually assimilated the best possible observation data Hourly time resolution and 0.5° horizontal resolution
Produced using the MOM model, the same model used for the control and experiment cases
Employs control case chlorophyll climatology; however, the reanalysis continually assimilates the best available observations (vertical profiles of temperature, salinity, satellite altimeter data, etc.), largely correcting for the influences of chlorophyll
Saha, S., et al., 2010, “The NCEP Climate Forecast System Reanalysis,” Bull. Amer. Meteor. Soc., 91, 1015-1057.
CFSR atmosphere forcing used for the control case and both experiments
Results referenced to CFSR ocean state values
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Analysis DefinitionsAnalysis Definitions Anomaly:
Difference from designated reference (specified monthly-mean annual cycle) Index (i) represents month of data record, e.g. (i = 1) = Jan 1998
Root Mean Square Error (RMSE) RMSE includes:
Differences in monthly-mean annual cycles Differences in anomalies
Index (i) represents month of data record; e.g. (i = 1) = Jan 1998
Normalized RMSE difference RMSE comparison of specified cases with respect to a common reference Expressed in terms of percentage of the Control’s RMSE with respect to the common
reference
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Control Case: Limited Ocean Color Climatology
Upper-ocean temperature variability
Pacific “Cold Tongue”(2S – 2N, 120W)
Temperature (C)
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Control Case: Limited Ocean Color Climatology
Seasonal and interannual anomalies
Temperature (C)
* Anomalies with respect to Control case mean-monthly cycle 9
Pacific “Cold Tongue”(2S – 2N, 120W)
Control Case: Limited Ocean Color Climatology
Ocean Temperature RMSE (CFSR reference)
Temperature (C)
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Pacific “Cold Tongue”(2S – 2N, 120W)
Exp2: Sequential Monthly-mean Ocean ColorOcean Temperature RMSE (CFSR reference)
Temperature (C)
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Pacific “Cold Tongue”(2S – 2N, 120W)
Exp2 vs Control:Ocean Temperature RMSE (CFSR reference)
Pacific “Cold Tongue” (2S – 2N, 120W)
RMSE (°C)
Near-surface improvement of order 0.2C, ~ 10%
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Control Case: Limited Ocean Color Climatology
Upper-ocean temperature variability
Temperature (C)
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Pacific “Warm Pool” (2S – 2N, 165E)
Temperature (C)
Control Case: Limited Ocean Color Climatology
Seasonal and interannual anomalies
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Pacific “Warm Pool” (2S – 2N, 165E)
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Temperature (C)
Control Case: Limited Ocean Color Climatology
Ocean Temperature RMSE (CFSR reference)
Pacific “Warm Pool” (2S – 2N, 165E)
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Temperature (C)
Exp2: Sequential Monthly-mean Ocean ColorOcean Temperature (CFSR reference)
Pacific “Warm Pool” (2S – 2N, 165E)
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Exp2 vs Control:Ocean Temperature RMSE (CFSR reference)
Pacific “Warm Pool” (2S – 2N, 165E)
RMSE (°C)
Minor near-surface improvement
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Near-surface Temperature RMSEControl Case (CFSR reference)
Equatorial Zonal Cross-section (2S – 2N)
Temperature (C)
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Near-surface Temperature RMSEExp1 (CFSR reference)
Equatorial Zonal Cross-section (2S – 2N)
Temperature (C)
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Temperature (C)
Equatorial Zonal Cross-section (2S – 2N)
Near-surface Temperature RMSEExp2 (CFSR reference)
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Equatorial Zonal Cross-section (2S – 2N)
Temperature (C)
Near-surface Temperature RMSEExp1 – Control: Impact magnitude of extended ocean color
climatology
0.05
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Equatorial Zonal Cross-section (2S – 2N)
Temperature (C)
Near-surface Temperature RMSEExp2 – Exp1: Additional impact magnitude from sequential ocean
color data
0.05
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Equatorial Zonal Cross-section (2S – 2N)
Temperature (C)
Near-surface Temperature RMSEExp2 – Control: Net impact magnitude from sequential ocean
color data
0.05
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Equatorial Zonal Cross-section (2S – 2N)
Temperature (C)
Near-surface Temperature RMSE Differences:Extended Ocean Color Climatology
RMSE (Exp1) – RMSE (Control): CFSR reference
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Equatorial Zonal Cross-section (2S – 2N)
Temperature (C)
Near-surface Temperature RMSE Differences:Sequential Ocean Color Data
RMSE (Exp2) – RMSE (Exp1): CFSR reference
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Equatorial Zonal Cross-section (2S – 2N)
Temperature (C)
Near-surface Temperature RMSE Differences:Net = Extended Climatology “+” Sequential Data
RMSE (Exp2) – RMSE (Control): CFSR reference
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Equatorial Zonal Cross-section (2S – 2N)
Percent
Normalized Near-surface Temperature RMSE Differences Extended Ocean Color Climatology
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Equatorial Zonal Cross-section (2S – 2N)
Percent
Normalized Near-surface Temperature RMSE Differences
Sequential Ocean Color Data
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Equatorial Zonal Cross-section (2S – 2N)
Percent
Normalized Near-surface Temperature RMSE Differences
Net = Extended Climatology “+” Sequential Data
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Height Anomaly Difference (cm)
Equatorial Pacific Ocean
Sea-Surface Height (SSH) RMSE Differences:Net = Extended Climatology “+” Sequential
DataRMSE (Exp2) – RMSE (Control): CFSR reference
Generalized reduction of SSH errors
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Equatorial Pacific Ocean
Percent
Normalized Sea-Surface Height (SSH) RMSE Differences:
Net = Extended Climatology “+” Sequential DataRMSE (Exp2) – RMSE (Control): CFSR reference
Generalized reduction of SSH errors
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Equatorial Pacific Ocean
Heat Content (exp-6 J/m2)
Ocean Heat Content (OHC) RMSE Differences:Net = Extended Climatology “+” Sequential
DataRMSE (Exp2) – RMSE (Control): CFSR reference
Air-sea heat flux impact important to fully coupled modeling (GODAS/CFS)
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Equatorial Pacific Ocean
Percent
Normalized Ocean Heat Content (OHC) RMSE Differences:
Net = Extended Climatology “+” Sequential DataRMSE (Exp2) – RMSE (Control): CFSR reference
Air-sea heat flux impact important to fully coupled modeling (GODAS/CFS)
SummarySummary Chlorophyll:
Simulations with monthly SeaWiFS ocean chlorophyll data reduce subsurface temperature errors. Most changes in temperature are found just above the seasonal thermocline (20C isotherm)
Sea-Surface Height (SSH): Reductions of SSH errors in the equatorial cold tongue region and north of the
equator are in the 5-10% range
Ocean Heat Content (OHC): Reductions of ocean heat content errors south of the equator and in the cold tongue
region are in the 1-10% range
Currently constrained at surface. When fully coupled (GODAS/CFS), differences will influence air-sea heat fluxes.
NEXT: Comparisons of model output with real data for validation; (in situ vertical profiles of
temperature, salinity, velocity) from Pacific/Atlantic/Indian Ocean arrays and satellite altimetry
Near-real-time ocean color assimilation
Extend study to assess ocean color assimilation impact on the operational results for NOAA’s Real-Time Ocean Forecast System (RTOFS), based on the HYCOM model
Unify NOAA’s ocean color data assimilation methodology for the operational models (GODAS, RTOFS)
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