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Analyzing Ocean Salinity Drift Trends: Insights from 2012 OTT Data

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camden
16 diapositives · 268 Views · Sep 18, 2014

This study examines salinity drifts identified in Ocean Temperature Trends (OTT) data collected in 2012. Through the analysis of salinity anomalies and their long-term trends, we explore the correlation between OTTs and solar declination while addressing biases observed in SMOS brightness temperatures. This comprehensive investigation includes the assessment of data quality, annual variations, and the impact of galactic noise, ultimately proposing a refined approach for managing drift trends in future models. Insights aim to enhance understanding of ocean salinity variability and its climatic implications.

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Analyzing Ocean Salinity Drift Trends: Insights from 2012 OTT Data
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  1. OTT/drift analysisLevel 2 Ocean Salinity 24 October 2012 ARGANS & L2OS ESL

  2. Retrieved salinity drift during 2012 SSS1 – same results with SSS2/3, same trend with ascending/descending, so not TEC or GN

  3. Retrieved salinity anomaly Why large drifts in anomalies: OTT are referenced to climatology?

  4. Retrieved salinity anomaly Anomalies not so bad in SSS anomalies for 2011 REPR, same period

  5. OTT evolution REPR from month 1 to 23; OPER after month 24 Are OPER OTT good quality? Do they show same trends as 2011?

  6. OTT evolution REPR from month 1 to 23; OPER after month 24 Are OPER OTT good quality? Do they show same trends as 2011?

  7. OTT evolution 9 day time series products blur transitions due to OTT Monthly OTT

  8. Are there any annual/long term drift trends in OTT? Ascending AFFOV median deltaTB Descending AFFOV median deltaTB

  9. OTT drift trends? Ascending drift HH + 0.021 K/month VV ~0 K/month Descending drift HH + 0.013 K/month VV ~0 K/month Ascending AFFOV median deltaTB Descending AFFOV median deltaTB

  10. OTT annual cycle? Descending cycle stronger then ascending – why? Individual OTT sometimes far from trends – why? Ascending AFFOV median deltaTB Descending AFFOV median deltaTB

  11. Annual variations Descending orbits (Tx+Ty)/2 OTT mean LOCEAN (XB) analysis: positive correlation between OTTs and Sun declination. (No correlation with galactic noise, emission from flat sea or roughness) with Sun in FOV with Sun in FOV Physical temperature of antenna patches

  12. Annual variations Ascending orbits (Tx+Ty)/2 OTT mean LOCEAN (XB) analysis: negative correlation between OTTs and Sun declination. (No correlation with galactic noise, emission from flat sea or roughness) with Sun in FOV with Sun in FOV Physical temperature of antenna patches

  13. OTT/drift conclusions • All 3 L2OS ESLs have identified biases in SMOS Tbs very well correlated with Tp7 (at least on descending orbits; R=0.9!); why? (the reprocessing was expected to correct for Tp7, but it does not). • These biases cannot be explained by galactic noise, although we know that our galactic noise correction is probably imperfect. Justification: • in OTT computations, we exclude Tbs affected by large scattered GN (>4K); • when looking at the across track temporal evolution of the biases and of GN averaged along dwell lines, the temporal evolution of the Tb biases is the same whatever the location across track contrary to the GN variations for which the phase of the temporal evolution depends on the across track location; • the evolution of large GN and Tb biases seen by Joe are not well phased. (JB email 17/10/2012)

  14. OTT/drift: the way forward? DPGS • Use a single MOTT for all orbits • made from all 2012 DPGS (or 2011 REPR) OTTs • either keep MOTT offset constant & see drift in retrieved salinity • or apply parametric best-fit polynomial drift to MOTT • Maintain running average OTT • either by regular execution of compareTBs on selected orbits (IDEAS) • or extend L2OS to write data for an OTT post-processor REPR • NIR centred OTT, parametric, or running average?