Works on altimetry in the Solomon Sea (start:29/06/2007)


   Lien sur les sites d'Angélique

  
   Lien sur les sites de Billy:
              Plots from ERS winds
              Plots from XBT track

   Bathymetric maps from Maxsea, details on the Solomon Sea:
                         Woodlark Island.jpeg
                         SE_PNG.jpeg
                         Vitiaz.jpeg
Solomon strait.jpeg
North Solomon Islands.jpeg
Central_Solomon_Islands.jpeg
Guadalcanal.jpeg
SanCristobal-Makira.jpeg


A. Mean Dynamic Topography
B.  Mapped Sea Level Anomalies
C. Processing of along track data
D. Some plots illustrating observations in-around the Solomon Sea
E. What to tell
F. EKE
G. EOF Analysis
H. Harmonic Analysis (Annual cycle)
I. Climatologic year
J. Transport
K. Low Frequency
L. Ideas for a discussion based on the Low frequency signature in the Solomon Sea


A. Mean Dynamic Topography
    1. "Bingham" solution (0.5°x0.5° grid)
          a. unfiltered solution:  Pacific (30n-30s)  ;   South Pacific
          b. Filtered solution following Thierry's processing
                1. same filtering than for Grace02 (Castruccio) (x=5°, y=1°)
                                              Pacific (30n-30s) ;     South Pacific
                2. fltx5y1  (x=2.5°,y=.5°):  Pacific (30s-30n)  ;  South Pacific

      2. "Maximenko" solution
(0.5°x0.5° grid)
 
a. unfiltered solution:
               i. MDT Pacific (30n-30s)  ;   South Pacific

                  ii. Geostrophic Current
                               a.  Zonal component (Pacific)
                               b.  Circulation in the South West Pacific


           b. Filtered solution following Thierry's processing
               1. same filtering than for Grace02 (Castruccio) (x=5°, y=1°)

                      i. MDT:   Pacific (30n-30s)  ;  South Pacific
                          ii. Geostrophic Current
                                  a.  Zonal component (Pacific)
                                  b.  Circulation in the South West Pacific

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B.  Mapped Sea Level Anomalies
 
               time sampling: 7 days

    1. unfiltered data:  RMS South West Pacific   ;  RMS Salomon Sea
            a. Seasonal cycle:   RMS Salomon Sea

    2. Filtered data (SBX:5):   RMS Salomon Sea  ;  RMS residual
            a. Seasonal cycle:     RMS Salomon Sea 
            b. Interannual:          RMS Salomon Sea

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C. Processing of along track data

C.1 Traitment of altimetric data

Topex/Poseidon along track dataset has been treated by the CTOH team of Toulouse, with special algorithms whose aim is to recover good data in the open ocean that would have been juged erroneous, and to recover data near the coasts.
A post-processing treatment has been applied to flag erroneous left data. A 4 sigma filter is first applied. Then, data are filtered with a 2 sigma cycle to cycle difference filter. Afterward, data are "replaced" on a reference track, which is the barycentre of the track for every cycle.
Another filter is used : the difference of rms between the first point after or before land and his neighbour is not allowed to rise above 2 cm. This filter is applied several times.
Finally, a point must have a minimum of 200 valid cycles to be valid. Otherwise, this point can't be used.

            Tracks of interest and bathymetry

Example of the number of valid cycles and sla variance for a track of the new product :   Track 251

C.2 Comparison of the new product with Aviso and the MSLA gridded data

          -   Track 23 ;
zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ;  Aviso


          -  Track 73  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ;  Aviso

          -  Track 10  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 112  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 149  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ;  Aviso

          -  Track 162  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 199  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 238  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 86  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 99  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 251  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO  ;  Aviso

          -  Track 175  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO

          -  Track 188  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO

          -  Track 225  ;  zoom Salomon
                   a. RMS  ;  RMS Salomon
                   b. Hovmuller:  MSLA  ;  DEGEO


          -  Track 36
                   a. RMS  ; 
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 123
                   a. RMS  ; 
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 47
                   a. RMS  ; 
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

          -  Track 60
                   a. RMS  ; 
                   b. Hovmuller:  MSLA  ;  DEGEO  ; 

C.3 Variance along the tracks
        
Sla rms map after filtering, using all TP tracks
        
Sla seasonal cycle rms map after filtering, using all TP tracks
        
Sla interannual variability rms map after filtering plus 3 months filtering, using all TP tracks
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D. Some plots illustrating observations in-around the Solomon Sea
       (Most from Billy's website)
       NICU.pngPNGzoom_vectors.pngvitiaz_sect.png

       Boug_Kiri_map_with_adcp.gifBoug_Kiri_ug_1000m.gifwepocs2_solomon_sea_adcp_ony.gif

       poi1map.pdfpoi1sol.pdf

       poi2map.pdfpoi2wsol.pdf

       mw9304_adcp_vectors3.gif

       Alex's page

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E. What to tell

The Solomon sea is characterized by a complex bathymetry and ocean dynamic as illustrated on:
          
Fig.E1. 

How altimetry can help to describe the variability of such dynamics?

       - This area exhibits the strongest variability over the Pacific ocean between 10°N-19°S as shown from the gridded altimetric product:
            Fig.E2: RMS.gif

      
- The gridded product, which merged TOPEX/POSEIDON and ERS, has a  1/3° horizontal resolution, and a 5 day temporal resolution. As shown on the figure above, the gridded data don't take account of the complex bathymetry of the Solomon Sea. Therefore, this product could be irrelevant for our study.

       - We decide to use a new processing for alond track altimetric data. Compared to the classical product, data are gained near the coast, and more cycles are available. Details on the processing can be found on the Angelique'web site. Here are the tracks that have been used:
      
Fig. E3:  tracks of interest and bathymetry

Only 10 tracks span the Solomon Sea.

The benefit from this new processing can be illustrated by comparing the
Old (Fig.E4a) with the New (Fig.E4b) Sla along track 251.
This new Sla data have been validated against tide gauge data available in our region (look at "
Tracks of interest and bathymetry" for the location of the tide gauge). We present the time series of the tide gauge, and of the nearest altimetric point for the Lombrum, Madang, Rabaul, Townsville, Honiara sites (faire plots)

      
- Here is the rms variability along the tracks: 
along track sla rms  (Fig.E5)
The highest variability (15 cm rms) is centered along 8°S and extends between 11°S-5°S in latitude, and between 150°E-170°E in longitude.

In the Solomon Sea, the eastern part of the basin, along the Solomon Islands, exhibits  higher variability than the western part, alonb the Papua New Guinea Coast.
Is this difference of variability representative of different dynamics between the west and the east into the Solomon Sea?

The western part of the basin is characterized by Western Boundary Currents, the NGCUC flowing northward below the NGCC; whereas  the eastern part is characterized by complex recirculation.

East of the Solomon Islands, the highest variability are not against the coast but a few degrees to the east. Qiu and Chen (2004) have studied the seasonal cycle in this area, and have found that at seasonal time scale, this high variability is explained from barotropic instability associated with the horizontal shear of the SECC-SEC system.

North (the Bismark Sea) and south of the Solomon Sea (11°S) the variability falls from 15 cm to 10 cm.

In conclusion, the highest variability are concentrated in the Solomon Sea, and just to the east of the Solomon Islands. The explanation of Qiu and Chen (2004) for the seasonal variability east of the Solomon Islands doesn't seem a good one for the Solomon Sea where neither the SECC nor the SEC can easily flow into the Solomon Sea

Some questions:
- From which temporal frequencies is this variability representative?
- How is different the variability inside and outside the Solomon Sea?
- Can the variability of the WBC be observed from altimetry?


Filtering of the data

    - The SLA are filtered with a 1-month triangle filter:
                 Fig.E6a: rms of along track filtered sea level.gif
                
Fig.E6b: rms of the sla annual cycle.gif
                
Fig.E6c: rms of sea level once the seasonal cycle is removed.gif
                
Fig.E6d: rms of the interannual sla signal.gif

    A 3 cm rms noise is filtered from the raw data. The description of the variability of the filtered sla is the same than above (check the track 188). The spatial distributions of the variability of the annual and interannual sla signals are similar, but east of the Solomon Islands, the highest annual variability is centered at 6°S whereas it is at 8°S  for interannual variability. The interannual sla signal exhibits higher variability than the annual cycle, 13 cm rms against 8 cm rms respectively. The comparison between the interannual variability and the sla variability free from the annual cycle shows that other time frequencies could exist (bi annual?? noise? see spectrum)

       - Check of the track 188. All the data are plotted on:  track 188.gif (Fig. E7) ;  some data seems wrong. Sla greater than .45m are filtered.
                The other tracks are also checked

Spectra
    - Spectrum at some locations characteristic of different dynamics:
          - North of the Vitiaz strait:                 Track 23, 4°S  (Fig. E8a);  AvisoT023,4S
          - South of the Vitiaz strait:                  Track 112, 7°S
  (Fig. E8b); AvisoT112,7S
          - Solomon Sea, east part:                     Track 10, 8°S
  (Fig. E8c);   AvisoT010,8S
          - Milne Bay:                                         Track 188, 10°S
  (Fig. E8d);   AvisoT188,10S
          - 10°S, middle west of Solomon Sea     Track 073, 10°S
  (Fig. E8e);   AvisoT073,10S
          - 10°S, middle east of Solomon Sea:     Track 149, 10°S
  (Fig. E8f);   AvisoT149,10S
          -  Makira:                                             Track 225, 10.5°S
  (Fig. E8g);   AvisoT225,10.5S
          - East of Solomon Islands:                   Track 239, 8°S
  (Fig. E8h);   AvisoT238,8S
          - South of Solomon Sea:                       Track 086, 14°S
  (Fig. E8i);   AvisoT086,14S
          - West of the Coral Sea:                      Track099, 11°S
  (Fig. E8j);   AvisoT099,11S
         

    - Around the Solomon Sea
South of the Solomon Sea, at 14°S, interannual and annual frequencies are dominant with a 5 cm magnitude. More to the west, at 11°S, there is no dominant variability. High interannual signal is present east of the Solomon Island at 8°S with magnitude up to 11 cm. In addition, three peaks between 1 and 1.5 years (4-6 cm) exist (??). North of the Vitiaz strait, the dominant frequency is dominant with a 9 cm magnitude. There is also a clear annual signal (4 cm), and there are also some energy at  4-6 months.
    - Inside the Solomon Sea
We check the signal at 10°S from the east to the west between 152°E-162°E. The interannual signal is dominant (up to 10 cm) everywhere, except in the far west part of the section (down to 3 cm). The annual signal is always present but with different amplitude (>4 cm). The amplitude is maximum (up to 9 cm) on the central east part of the section. In the west part of the section, frequencies greater than the annual cycle are distinguishable, particularly a 60 days period. In the basin, there are more energy, at all frequencies, in the eastern part than in the western part. In the East, we retrieve both the 10 cm amplitude of the interannual signal, and the 9 cm amplitude of the annual signal. The 60 day peak is also high with a 3 cm amplitude. In the West, the annual cycle is dominant (6 cm), the interannual signal is only of 4 cm. The 60 day period is also present.
    - In conclusion, a 60 day period exists in the Solomon Sea and not outside. The annual cycle is relatively high in the Solomon Sea compared to the surrounding areas. In the Solomon Sea, the interannual variability is particularly located on the central-east part of the basin. Outside, the interannual signal is high everywhere north of 10°S


Difference Between the east-West sides of the Solomon Sea

For each tracks, the points inside the Solomon Sea are selected. Another selection consists to distinguish the west and east parts of the Solomon Sea based on the location of the tracks inside the basin, and a criterion in variability (rms < or > 11 cm, respectively West and East). The west part is the area where is the NGCC. This separation between the East and the West is critical. Noted that the area of the West part is smaller than the East one.

Both time serie are highly correlated (0.87):  Fig.E9:  West/east correlation

And present energy at the same frequencies, mostly at annual and interannual period: Fig.E10: West/east spectra
Logically, there are more energy in the West part than in the East. The interannual signal is dominant in the East part (11 cm),  whereas the annual and interannual signals have same magnitude in the west part (4 cm). A peak at 60 days is visible in the West, and a semi annual signal is visible in the East. We retrieve the conclusion from the spectra at individual locations.

We look at the correlation between the West and the East function of latitude:  Fig.E11: West/East correlation
The correlation is high, around .9 for the annual and interannual signals from 6°S to 9°S, and decrease to .7 at 10.8°S. South of 10.8°S, we are out of the Solomon Sea, and there is a break in the correlation. For the interannual signal, the correlation increases to .99 whereas it decreases for the annual signal

In conclusion, the solomon sea seems to invole in phase between the West and the East, particularly north of 9°S (north of Milne bay) for period higher or equal to the annual signal. South of 9°S, the West part is representative of Milne bay and there are just few points available in this area, therefore may be correlations are less robust. The break between 11°S and 10.5°S seems to delineate the south boundary of the Solomon Sea.

Solomon Sea: East side

Is the SLA correlated between the north and the south of the domain. We  look at the correlation at 7°S function of latitude: Fig.E12: Correlation function of latitude.
The correlation is very close to 1 for the annual and interannual signals. It begins to decrease south of 10°S, and north of 6°S which are the limits of the domain. for the high frequency signal, the correlation falls down to .8 in a  distance of 100° km (Decorrelation scale, rayon de rossby??)

Hovmuller:  Fig. E13 a)full signal    b)Annual   c)Interannual
Sea level anomalies may each 30-35 cm. The amplitude of the annual signal is of 10-15 cm. It is interesting to see that the maximum (in march) and the minimum (in september) have a 2° extension in latitude, and they are not centered at the same place, 8°S and 9°S respectively. It deseappears at 10.5°S (the south boundary would be Guadalcalnal and not Makira. May be a significant flow exist between the two islands), and it reappears more south with a 4 months lag. The amplitude of the interannual signal is of 15-20 cm, the positive anomalies being higher than the negative anomalies. There are 3 negative events: the 1993, and the 1997-1998 are the most significant. The third one is present during the second half of 1994. There are 3 positive events, Each one having a marked signature during the first half of a year. The 2000- 2001 are the stongest events. There is another one in 1996.
The anomalies in the full signal are clearly a combination of annual and interannual signals.
.
Solomon Sea: West side
Is the SLA correlated between the north and the south of the domain. We  look at the correlation at 7°S function of latitude: Fig.E14: Correlation function of latitude.
The correlation decreases slowly down to .9 at 10°S. South of 10°S, the annual and interannual signals behave differently. For the annual signal the correlation falls down quickly wheras for interannual signal the correlation decreases significantly south of 11°S and reachs .5 at 12°S. For the high frequency, the correlation decreases firstly drasticaly in less than 1°, before to decrease continuously with the latitude. Is the observed decrease of correlation with latitude for the different signals due to some propagation??

Hovmuller: Fig. E15 a)full signal    b)Annual   c)Interannual
There is a break at 10°5°S in the SLA signal which means that the SLA signature of the Solomon Sea is different from the surroundings. The annual signal has a 5 cm amplitude extending between 9.5°S and 7.5°S. The anomalies are maximum in march and minimun in September. There is a clear 4 months lag with the signal at 11°S (maximum in December). The interannual signal is relatively small with a maximum amplitude between 5-10 cm.

Relation between the Solomon Sea (east side) and the variability at the east of the Solomon Islands

Sal-eastof_ft.gif

Sal-eastof_spe.gif

East of Solomon Islands:
    Hovmuller:  full signal   Annual   Interannual  HF
    Correlation fonction of latitude


Relation between the Solomon Sea and the variability at the south of the Solomon Islands
Because the south west corner of the Solomon Sea is located more to the south than the south east corner, we look at the east side of the Solomon Sea with the south of the Solomon Sea between 10.5°S et 11.5°S, and we look at the west side of the Solomon Sea with the south of the Solomon Sea between 11.5°S and 13°S.

The two latitudinal bands don't have similar variability:  temporal series of SLA south of the Solomon Seacorresponding spectra

Relation between the east side of the Solomon sea and the [10.5°S-11.5°S] band: temporal seriesspectra

Relation between the west side of the Solomon sea and the [11.5°S-13°S] band: temporal seriesspectra

Relation between the west side of the Solomon sea and the south of PNG: temporal seriesspectra

North of New Britain
Relation with the west side of the Solomon Sea:
temporal seriesspectra
Relation with the ocean at the east of the Solomon Islands: temporal seriesspectra



First summary:

What is the role of the Solomon Sea to exchange anomalies between the subtropics and the western equatorial Pacific? What do we learn from altimetry??
The Solomon Sea is a pathway for the western boundary current and this boundary current connects both regions. Therefore the WBC may play a significant role in ENSO variability. It is a question to know the exact role of the WBC.
The solomon Sea is divided is two areas: a West side characteristic of the WBC (SalW) and a East Side (SalE).
The Solomon Sea is located inside an area of high sea level anomalies. It means that this high variability at the east of the Solomon Islands (EastOf) is at the latitude of the Solomon Sea, and could be due to barotropic instability (Qiu and Chen, 2004) at seasonnal time scale and also to propagating Rossby waves.
A crucial question is to know the story of these anomalies once they meet the Solomon Islands.
May be, there are some similitude with Hawaii.


Spectra of sla provide some insights:

    - First, SalE and EastOf have similar spectra:   
SalE-eastof_spe.gif
Ce qui veut dire que les îles Salomons ne sont pas un obstacle à la propagation du signal. Le signal qui arrive à la côte est des iles Salomons va se propager le long des îles et va pouvoir penetrer par les extremites nord (Solomon strait) et sud (Guadalcanal-Makira). En effet, la région au sud de Guadalcanal (
SudOf, 10.5°S-11°S) montre une variabilité interannuelle proche de celle observée sur EastOf:  SalE-Sudof_spe.gif

             - Time series SalE/EastOf:   Climatology
  ; low frequency; residual
Pour les 3 signaux (Clim, interannual, haute fréquence), SalE et Eastof ont la même variabilité. Si l'on regarde le signal haute fréquence, il est en retard (1mois) dans SalE par rapport à EastOf

             - Time series SalE/SudOf :  Climatologylow frequency;   residual
  Si la variabilité climatologique est nettement differente entre SalE et SudOf, la variabilité haute et basse fréquence est relativement concordante.

    - Second, the variability north of New Britain (NorthOf) is more related to EastOf than to SalW:
         
NorthOf-EastOf_spectra.gif;    NorthOf-SalW_spectra.gif
Ce qui voudrait dire que la variabilité au nord ouest de la mer des Salomons est directement associée à celle qui de trouve à l'est des iles Salomons et cette relation ne se fait pas forcemment par la mer des Salomons. Le signal arrivant de l'est va donc contourner la Nouvelle Irlande et se propager vers l'Ouest.

          - Time series NorthOf/EastOf: Climatologylow frequencyresidual
Pour les 3 signaux (Clim, interannual, haute fréquence), SalE et Eastof ont la même variabilité.

          - Time series NorthOf/SalW: Climatologylow frequencyresidual
NorthOf a clairement un signal semi annuel visible aussi dans EastOf mais qui n'existe pas dans SalW. La variabilité interannuelle est moins prononcée dans SalW que NorthOf mais les deux signaux sont en phase.

    - Third, SalW exibits a lower variability than SalE that seems to be a combination of Signals from SalE, SudOf (11°S-13°S), and from the WBC south of PNG (SouthPNG)

   
SalW/SalE spectra.gif
    Time series SalW/SalE:  Climatologylow frequencyresidual
La différence des spectres suggèrent que la partie ouest et est de la mer des Salomons ont des régimes dynamiques différents.  La variabilité basse fréquence est en phase entre les deux séries.

   
SalW/SouthPNG_spectra.gif
    Time series SalW/SalE:  Climatologylow frequencyresidual
SouthPNG montre une faible variabilité interannuelle ce qui suggère que la variabilité interannuelle observée en mer des Salomon (SalW) ne provient pas de façon majoritaire de cette région. La ressemblance des spectres pour les fréquences à 60 jours et annuelle indique bien que le WBC au sud de la PNG contourne l'extremité sud est de la png et longe la cote est de la png. La variabilité "climatologique" est similaire entre les deux séries avec un retard de 2 mois pour SalW

   
SalW/SouthOf_spectra.gif
    Time series SalW/SalE:  Climatologylow frequencyresidual
Les spectres sont similaires surtout pour les fréquences annuelles et interannuelles. Les series climatologiques SouthPNG, SouthOf, SalW sont trés ressemblantes avec des déphasages. Il n'est pas facile de voir si SouthOf est capable d'influencer SalW. On peut penser que si c'est le cas l'effet de SouthOf se fait au détriment de SouthPNG

Il est clair que SalW est associé à SouthPNG et à SalE, le role de Southof est moins évident. Cela voudrait dire que SouthOf se propage vers l'ouest avant de rejoindre SouthPNG.

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F. EKE
Use of gridded SLA from AVISO
Qiu and Chen (2004) have focussed on the Seasonal cycle of the EKE in the SECC box (150°E-170°W; 15°S-5°S).
First, we do similar plots than in their paper.
We retrieve the results from the figures 4a and 5a of Chen and Qiu (2004)
    - F.1:  EKE averaged over the SECC box.gif
    - F.2: EKE as a function of calendar month in the SECC box.gif

But when looking at the spatial distribution of the mean EKE, we see strong heterogeneous areas. High EKE is cencentrated in the Solomon Sea:
    - Fig.3: Spatial distribution of mean eke.gif

The SECC box is divided in two parts: 150°E-160°E and 160°E-170°W
    - Fig. 4: EKE averaged over the differents boxes.gif
Mean EKE in the box included the Solomon Sea: 341 cm2/s2 against 174 cm2/s2 for the other part. Results from Qiu and Chen (2004) are relative to the area at the east of the Solomon Sea.

EKE in the Solomon Sea:
     - Fig. 5: EKE averaged in the Solomon Sea.gif;   150°E-155°E: 9°S-5°S; Mean EKE: 679 cm2/s2
     - Fig.6:  EKE as a function of calendar month in the Solomon box compared to the east part.gif

       Contribution of the U component (y derivative):
                    Fig.7:
EKE averaged in the Solomon Sea.gif
                    Fig.8:
EKE as a function of calendar month in the Solomon box
       Spatial Distribution of mean EKE: U2;    V2

    - EKE has a dominant interannual signal
             - Fig.9: Low frequency
             - Fig. 10: High frequency
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G. EOF Analysis
Use of the gridded SLA from AVISO: 1992-2004

EOF analysis are performed both on a climatological series and on a series where the climatological signal has been removed.

First, we consider the domaine 142°E-170°E; 13°S-12°S

    - Climatological series: Mode 1Mode 2Mode 3Mode 4Mode 5
The mode 1 explains 74% of the variance; and the first 3 modes 92%

    - "Inter-intraannual" series: Mode 1Mode 2Mode 3Mode 4Mode 5Mode 6
The mode 1 explains 71% of the variance

EOF performed on the Solomon Sea only:
    - raw data:
Mode 1  The mode 1 explains 81% of the variance (Variance=9.8E-3 m2)

    - Climatological series: Mode 1Mode 2Mode 3
The mode 1 explains 88% of the variance

    - "Inter-intraannual" series: Mode 1Mode 2Mode 3
The mode 1 explains 81% of the variance
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H. Harmonic Analysis (Annual cycle)
       - Amplitude and Phase
       - Velocity anomalies in March and September

        - Amplitude and phase curl tau
TOP

I. Climatologic year

    - Hovmuller at different latitute: msla_hov.html

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J. Transport
L'approche de Ridgway (1993) est utilisée ici pour estimer la variabilité des transports entrant et sortant de la mer des Salomon à partir de l'altimétrie. La SLA est censée représenter la variabilité des 150 premières mètres sus la surface. On utilise les sorties du modèle ORCA05 pour confirmer cette approche.

          1. Rms de SLA sur le domaine: ModèleAltimétrie

Le transport est  estimé soit par différence de sla aux extrémités de la section en utilsant l'altimétrie ou la SSH du modèle, soit directement avec le courant méridien du modèle.

        
         2. Flux entrant en mer des Salomons (entre la pointe sud est de la PNG et Makira)
                a. Courant méridien du modèle le long de la section: Mean;   RMS
                b. Spectres des transports
                c. transports fonction du temps: Non filtrésbasse fréquenceclimatologiques

         3. Flux sortant par Vitiaz (trace 99)
                a. Courant méridien du modèle le long de la section:
Mean;   RMS
                b. Spectres des transports
                c. transports fonction du temps: Non filtrésbasse fréquenceclimatologiques

         4. Flux sortant par Solomon strait
                a. Courant méridien du modèle le long de la section:
Mean;   RMS
                b. Spectres des transports
                c. transports fonction du temps: Non filtrés (0-150) (0-bottom)basse fréquenceclimatologiques

         5. Flux sortant à travers la section allant de Makira  l'ouest du détroit des Salomon
                a. Spectres des transports
                b. transports fonction du temps: Non filtrés (0-150) (HF filtrée)basse fréquenceclimatologiques


         6. Flux sortant à travers la section allant du sud est de la PNG à l'est de Vitiaz
                a. Spectres des transports
                b. transports fonction du temps: Non filtrés (0-150),  basse fréquenceclimatologiques

         7. Comparaison du flux entrant avec la somme des flux sortants
                   AltimetrieModèle
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K. Low Frequency

Les données sont filtrées à 7 mois (spz41, dt=10 jours)
Les sea level sont soit des données along track, soit des données AVISO grillées
Le signal EKE est issu de AVISO grillé

   
    1. Along track sea level anomalies averaged over the Solomon box
                a. Sla/SOI.gif
                b: Sla/EKE

    2. SLA Aviso averaged over the Solomon box:

                a. SLA calculé partir d'un masque sur la mer des Solomon: Slab/SOI.gif

    3. L'activité turbulente (EKE) sur la mer des Salomon est liée à la variabilité interannuelle de type ENSO (représentée par la SOI):
                 a. EKE/SOI.gif
                 b. EKE calculé sur la mer des Salomon: EKEb/SOI.gif

    4.Relation entre l'activité turbulente (EKE) et la variabilité des transports mesurée dans les détroits.
          Inflow: ce qui rentre par le sud et l'est
          Outflow: ce qui sort par Vitiaz et Solomon straits

                A. transports calculés à partir des données along track.
                       1. Correspondance entre Inflow et Outflow: In/out flow.gif
                       2. Correspondance entre EKE et Outflow (variables normalisées): EKE/outflow.gif
                       3. transports at Vitiaz and Solomon strait: Vitiaz/Solomon.gif

                B. transports calculés à partir de Aviso (résultats similaires avec le produit along track):

                       1. Correspondance entre Inflow et Outflow: In/out flow Aviso.gif
                       2. Correspondance entre EKE et Outflow (variables normalisées): EKE/outflow.gif

    5. Relation avec le Warm Water Volume de Meinen (ouest)
             1. en terme de niveau de la mer sur les Salomon: SLA/wwva.gif
             2. en terme de transport à travers Vitiaz et Solomon strait: Outflow/d(wwv)/dt.gif

    6. EOFs
                1. SLA Pacifique (14s-14n)/SOI:    Mode1/WWV West.gif;   Mode2/WWV Pac.gif
                2. SLA Pacifique Sud (14s-5s)/SOI:    Mode1/WWV West.gif;   Mode2/WWV Pac.gif
             3. SLA Salomon/SOI/WWVaWest:  Mode 1.gif;   Mode 2.gif

    7. Wind Curl from ERS
             1. Pacifique (14s-14n)/SOI:  Mode1/WWV Pac.gif;   Mode2/WWV West.gif
             2. Pacifique Sud Ouest/SLA_Sal/SOI: Evolution temporelle.gif
             3. Pacifique sud Ouest/Sv: Temporal Evolution.gif

    8. TAO
              1. 5S156E, Heat Content/SLA_Sal/SOI: Temporal evolution.gif
              2. 5S156E/Sv: Temporal Evolution.gif

    9. SST
          1. Anomalies over the Solomon Sea/SLA_Sal/SOI: Temporal Evolution.gif

    10. Relation between SLA and transports in the Solomon Sea: Temporal Evolution,.gif
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L. Ideas for a discussion on Low frequency variability in the Solomon Sea

On the specific role of the Solomon sea to fill/empty the equatorial band in the western Pacific


The importance of the South West Pacific Ocean, and of the Solomon Sea, to connect the subtropical region to the Western equatotrial region is largely discussed in the SPICE programm.
This study is based on altimetric data and focusses on the interannual variability in the Solomon Sea. The Sla are analyzed with regard to the WWV anomalies provided by C. Meinen. Results are supported by model analysis. This study emphasizes that most of the water necessary to balance the discharge/recharge of the equatorial Pacific transit through the Solomon Sea. They point out the importance of the South hemisphere and of the western boundary current in ENSO dynamics.

The results presented below is a synthesis of the work
Data are filtered with a triangle filter and a 7-months cutoff

1.  Maxima of high variability are located in the western Pacific ocean of each hemisphere around 8°. The western end of the ocean is characterized by the recirculation of zonal currents crossing the Pacific basin into western boundary currents. In the South hemisphere,
the high SLA variability between 5S-10S and 140E-170 encompasses the Solomon Sea. We will try to characterize the specific role of the Solomon Sea at ENSO time scale.
          FigA:  RMS LF 92-07.gif

2. An EOF analysis over the tropical Pacific (14S-14N) shows two dominant modes explaining
respectively 54% et 23% of the variance. These two modes are discussed a lot in the literature. The mode 1 represents a tilting mode and the mode 2 a discharge and recharge of WWV. Mode 1 is in phase with the SOI whereas mode 2 is negatively correlated with the SOI. (Fig.B)
          Fig.B: a) Mode1/WWV West.gif;  b)  Mode2/WWV Pac.gif


3. Altimetry is a good way to track changes in WWV (already shown by Meinen, 2005). It is worth noting that the WWVa for the western region lags the mode 1 in SLA (and the SOI) by 5-7 months, and the WWVa for the equatorial band is in phase with the mode 2 in SLA. (Fig. B).
The Mode 1 is correlated with the western WWV by about 0.58, and leads the western WWV by about 5 months with a 0.83 correlation.

4. A zoom in the Solomon shows that the first EOF mode explains up to 95% of the interannual variance.
In a statistical point of view, the Solomon Sea exhibits a relatively simple variability. This mode is highly correlated to the SOI and leads the western WWVa by few months (Fig.C). The temporal function of this mode is very closed to that one of the mode 1 over the tropical Pacific (Fig. Cb), and their spatial structure over the Solomon Sea are similar with maxima of varialility along the western coast of the Solomon Islands. The correlation between the two EOF temporal function is high 0.82. The Solomon Mode is correlated with the western WWV by about 0.87, and 0.89 considering a two months lag.
          Fig.Ca: Mode_Sal 1.gif
          Fig.Cb: Mode1: Sal/Pac.gif

5.  For the spatial EOF 1 mode, looking at zonal sections in the latitudinal range spanning the Solomon sea from 5S to 10S, we clearly see that inside the Solomon Sea, the slope of SLA variability is inverse of the slope outside the Solomon Sea (Fig.D). The crosses in Fig.Db delineate the location of the Solomon Islands. It means that the corresponding meridional flow is in phase opposition inside and outside the Solomon Sea. When the interior ocean discharges (recharges), it recharges (discharges) through the Solomon Sea. Looking at a similar figure for the northern hemisphere, we don't see a so strong signature. This result argues for the predominance of the Solomon Sea to fill or deplete the Western Equatorial Pacific.
          Fig.D: a) EOF1 South.gifb) EOF1 South West.gif (the Solomon Islands are located by crosses);  c) EOF1 North.gif

6. To illustrate the discussion above, the velocity field corresponding to the spatial EOF1 mode is plotted (Fig.E). When there is a meridional divergence in the equatorial band, a westward surface geostrophic flow
south of 10°S enters the Solomon Sea, and goes north. It bifurcates at the New Britain coast before to escape throuh Vitiaz and Solomon straits. Just a smal part of this westward flow continues  to the Australian coast decreasing the NQC. It seems that a part of the interannual variability of the Australian WBCs is in fact controlled by the SEC inflow. Similar conclusion have been done By Kessler and Gourdeau (2007) when looking at the annual cycle
          Fig.E:  EOF1_vector.gif

7. It is an uneasy task to physically interpret the statistical EOF modes. Because there is only one dominant mode in the Solomon Sea, there is no particular interest any more to use EOFs to analyse interannual varaibility inside the Solomon Sea. We retrieve the same relations between the western WWVa, the SOI and the EOF mode than using directly the high-pass filtered SLA time series. Compare Fig.F with Fig.C
          Fig.F: Solomon Sea: relation between SLA, SOI and western WWVA.gif

8. We use a numerical simulation: the one used in Kessler and Gourdeau (2007) to check the interannual variability of the model with regard to the results above. We performed similar EOF analysis (Fig.Ga), and in the Solomon Sea we look at the ssh variability (Fig.Gb) and the relations between the SSH signal averaged in the Salomon Sea, the SOI and the western WWV (Fig.Gc). Model analysis are very close to the altimetric analysis giving confidence both in the model and in the data analysis.
       ORCA05:
                       Fig.Ga: EOF1.gif;   EOF2.gif
                       Fig.Gb: RMS.gif
                       Fig.Gc: Relation between SSHa averaged over the Solomon Sea, the SOI and the western WWVa.gif

9. Once the relations between the SLA in the Solomon Sea and the SOI and the Western WWVA are established, we try to provide an estimation of the transports crossing the Solomon Sea. We use the same idea already developped in Ridgway et al (1993) with tide gauges. The geostrophic mass transport is estimated from the expression gdHD/f where dH is the sea level difference between each side of the straits, and D=150 is representaive of the depth of the upper thermocline. It is a crude estimation of the transport because D is fixed and transports at deeper levels may exist, particularly in the WBC. These estimations are assessed with the use of the numerical simulation.

10.  Transports are estimated at the south entrance of the Solomon Sea between the south east extremity of the PNG coast and the southern islands of the Solomon Islands (y=10.5°S) for the inflow and at the Vitiaz  and Solomon straits for the outflow (y=-6.41°S, and x=151°E is the longitude which divide th eoutflow into the straits). We need only two SLA measurements (one at each extremity of the sections) to estimate the transports.
    We check that the inflow balances the outflow (Fig.H). The inflow is defined by the addition of the flow at the souterhn entrance of the Solomon Sea and of the flow crossing the Solomon Islands. except some differences existing at the peaks of transports anomalies, both curves are greatly similar.  Transports anomalies may reach 10 Sv during the 1997-1998 ENSO event
       Fig.H: Inflow/outflow transports from Aviso.gif

11. The model is used to verify the estimation  from
altimetrie (old plots). We remember that the bathymetry of the model is not very good in this area, very poor representation of the Solomon Islands. transports from the model are estimated in differents ways: by using the same method used for altimetry (using modeled SSH), ans directly by using the velocity fields (0/150m and 0/bottom transports are estimated) (Fig.I)
             - Inflow at the south entrance: Fig.Ia Comparison Model/altimetry ;   Spectra

             - Outflow at Vitiaz straits: Fig.Ib Comparison Model/altimetry  ;  Spectra
             - Outflow at Solomon straits: Fig.Ic  comparison Model/altimetry  ;   Spectra
Altimetry and model provide similar estimation with similar amplitude and a good phasing. Therefore the crude astimation of transports from altimetry is not so bad. Discrepancies exist for the Solomon strait. It is not surprizing because of an unrealistic bathymetry in the model.

12. The model has the advantage to provide the vertical structure of the currents (Fig.J)
            
- Inflow at the south entrance: Fig.Ja Mean;   RMS
             - Outflow at Vitiaz straits: Fig.Jb Mean;   RMS
             - Outflow at Solomon straits: Fig.Jc   Mean;   RMS

13. Relation between the flux in the Solomon Sea (through Vitiaz and Solomon straits) and the flux from the recharge/discharge of the Western WWVa (dWWVa/dt) (Fig.K).
Both time series are out of phase and their magnitude are similar.
         Fig.K      Outflow/d(wwv)/dt.gif    It is the most important plot!

14. We can separate the contribution of Vitiaz and Soloon straits (Fig. L.)
       Fig.L:  Vitiaz/Solomon straits.gif


Reste à developper tout ceci avec la biblio qui va bien, le message étant 1. que la mer des Salomon est un endroit majeur pour "équilibrer" les recharges/décharges qui ont lieu en plein océan. 2. que l'altimetrie avec juste quelques points de part et d'autres des détroits donne des informations assez fiables sur la variabilité basse fréquence" de la circulaiton à travers la mer des Salomon.


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