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Generation and Initial Evolution of a Mode Water -S Anomaly Gregory Johnson NOAA/Pacific Marine Environmental Laboratory Introduction & Motivation Variations.

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Presentation on theme: "Generation and Initial Evolution of a Mode Water -S Anomaly Gregory Johnson NOAA/Pacific Marine Environmental Laboratory Introduction & Motivation Variations."— Presentation transcript:

1 Generation and Initial Evolution of a Mode Water -S Anomaly Gregory Johnson NOAA/Pacific Marine Environmental Laboratory Introduction & Motivation Variations in the S Pacific Salinity Maximum The South Pacific Eastern Subtropical Mode Water Modeling Study Seasonal Mode Water Evolution Potential Vorticity -S Anomaly Turner Angle Double-Diffusion Microstructure Mixing Parameterization Salinity Flux Estimates 1-D Model Conclusions Simple 1-D Model Goes Some Way in Matching -S Anomaly Evolution However, Advection Must Play a Part

2 SE Pacific Salinity Max Variations Figures after Kessler (1999) S max Subducted in SE Pacific S max Advected Towards Equator Significant -S Variation along 165 E Salinity Changes of Order 0.4 Few Locations so Well Measured Variations Related to Advection Difficult to Find Cause at Source Next cut along 103 W...

3 South Pacific Eastern Subtropical Mode Water After Wong & Johnson (2003) WOCE P18 Section Data –Along 103 W in 1994 Region of Small d /dz 25.6 < < 24.8 kg m -3 Region Sits Below S Maximum Formed in High E-P Region –Winter Evaporation & Cooling dS/dz Also Reduced Here Note dS/dz Destabilizing –Warm Salty Over Cold Fresh

4 SPESTMW (Continued) After Wong & Johnson (2003) Potential Vorticity Minimum –Capped Over in Austral Fall –Spreads Equatorward of Formation Region –Wide -S Property Range High Turner Angle –Winter Evaporation & Cooling –Warm Salty Over Cold Fresh –(Tu > 77 = Density Ratio < 1.6) –Potential for Double Diffusion –Just Austral Fall Data –Well After Subduction

5 Modeled -S Variability Figures of Yeager & Large (2004) –Look on = 25.5 kg m -3 –RMS S (10 -2 PSS-78) –Strong Signal In SPESTMW –Propagates Equatorward –Linked to Spiciness Follow Anomaly Equatorward –Subducted Around –On Equator 6-7 Years Later –Reduced in Magnitude Appropriate Diffusivity ? –Numerical & Parameterized –Double Diffusion not Enabled...

6 Floats as a Time-Series After Johnson (in press) Just Downstream of High Turner Angle (Spicy) SPESTMW Formation Region Winter Surface Waters Contoured as 1.0 < R < 2.0 at 0.2 Intervals WMO IDs (cyan) & (magenta) -Deployed January 2004 & Analyzed into July Profiles Every 10 days -71 Data Points 100-dbar Spacing at 2000 dbar Reduces to 8-dbar Spacing by 160-dbar

7 A Condensed Preview of the Time-Series Mar 2004 (Black os) –Typical of Central Waters –Salinity Destabilizing –Anomaly Near 24.8 kg m -3 ? Oct 2004 (Magenta +s) –Maximum Ventilation –Mixed Layer to 25.0 kg m -3 –Temp Cold But... – Upper -S Pulled Salty < 25.2 kg m -3 Cooling with Evaporation Mar 2005 (Cyan s) –Austral Fall Stratification –Strong Anomaly Near 25.0 kg m -3 –Anomaly Also Denser > 25.2 kg m -3 –Double Diffusion? Downward S Flux Rotated -S Curve

8 Potential Vorticity Time-Series Seasonal Mixed Layer Evolution –Deeper & Denser Mar-Oct –Abrupt Spring Restratification –Gradually Lighter Until Fall Maximum Spring Ventilation –Pr > 150 dbar – 25.0 kg m -3 Late Spring PV Reset –Low PV Replenished 2004 Ventilation vs –PV Min Lower –PV Min Thicker –Stronger Ventilation?

9 Salinity Anomaly Time-Series Pick Reference -S Curves –(Blue Vertical Lines) S Anomalies Relative to Curves S Anomaly Around 0.3 PSS-78 Salty & Warm Water Subducted Subsequent Evolution –Max Anomaly Reduces –Anomaly Also Moves Denser Result of Salt-Fingering? –Patchiness Mesoscale? Advection? Winter 2004 Stronger Than 2003?

10 Turner Angle Time-Series Contours: R 2.0 at 0.1 intervals Wintertime –Latent Cooling with... –Strong Evaporation Salinity Anomaly Favors –Large Turner Angle –Double Diffusion Seasonal Anomaly Evolution –Again Tu Maximum Eroded –Migrates Downward –Similar to the S Anomaly Interannual Variations –2004 Exceeds 2003

11 Parameterize Salt Fingering Mixing Use an Ad-Hoc Parameterization Decreased Stability ->Increased Mixing After Yeager & Large (2004, Eq. B1) St. Laurent & Schmitt (1999) Data Assume That For 1 < R < 2.05 (90 < Tu < 71): K s (R ) = F m 2 s -1 With F = [1 - (R - 1)/( )] 3 And Elsewhere: K s = m 2 s -1

12 Diapycnal Salinity Flux Time-Series Seasonal Anomaly Evolution –Flux Decays with Time –Zero-Crossing Denser with Time –Similar to Other Fields Interannual Variations... –2004 Stronger than 2003 Next: Follow = kg m -3 Use Previous Parameterization Admittedly Ad-Hoc & Uncertain Salinity Flux Below S Anomaly Large Diapyncal Flux Downward Significant Fraction of Anomaly Size Over a Year

13 Model S Anomaly on = kg m -3 Find Diapycnal Salt Flux on Isopycnal Integrate with Time (1-D) Compare Mapped Salinities Pick Best Agreement Integration Constant Seasonal Anomaly Evolution –Anomaly Ramps up in Spring –Decays slowly thereafter –Delayed for Weaker Northern Winter Ventilation

14 What about Advection? 1-D Model is Surprisingly Good However, Advection is Present –Short-term Variations (Eddies) –Mean Circulation –Mixed Layer Slumping? In January 2004 Data Were Few –Difficult Even to Map Anomaly –More Difficult to Trace Anomaly In January 2006 Data Are Many –Anomaly Mapping & Tracing Almost Possible?

15 Conclusions Observational and Modeling Studies Reveal SE Pacific -S Variations Warm Salty Water Subducted in SE Subtropical Pacific Spiciness Enables Large -S Variation in Eastern STMW Anomalies May Even Reach the Equator, Upwell, and Influence SST Argo Floats Allow Local Studies of Seasonal Mode Water Evolution Potential Vorticity -S Anomaly Turner Angle Double-Diffusion May Be Important Microstructure Mixing Parameterization Salinity Flux Estimates from 1-D Model Match Observations Pretty Well Advection Must Play a Role Over Longer Time-Scales Next Steps: Mapping Anomalies & Tracing Their Evolution Growth of Array Begins to Make this Realistic Requires Data From a Continuous Argo Float Array Must Maintain Array over Several Years For Mapping Anomalies & Tracing Them Equatorward For Analyzing Interannual Variations


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