1. SEA SURFACE TEMPERATURE TRENDS IN THE MEDITERRANEAN SEA: FROM INTERANNUAL TO DECADAL VARIATIONSBy
S. Marullo1, R. Santoleri2, M. Guarracino1, B. Buongiorno Nardelli2, V. Artale1
1 Ente per le Nuove tecnologie l’Energia e l’Ambiente (ENEA) – Dipartimento Ambiente, Clima Globale e Sviluppo sostenibile – Roma (Italia)
2 Istituto di Scienze Atmosfera e Clima, CNR, Gruppo Oceanografia da Satellite (GOS) – Roma (Italia)
In the next few minutes I will try to give you and idea about our analysis of the trends and interannual to decadal variation of the SST field in the Mediterranean Sea
Tribute to Ümit Ünlüata - Session at the 38th CIESM Congress
Istanbul, Turkey, 9-13 April 2007

2. Objectives of the investigation
The Mediterranean high resolution SST datasets MFS_SST (OISST).
Verify the consistency of International Comprehensive Ocean-Atmosphere Data Set (ICOADS SST) and satellite SST during the last 22 years at regional scale.
Regional SST trends and variability over the satellite era and behind.
Forcing of the variability: open questions and some tentative answer.
Verify the consistency in order to satisfy the minimum request that ICOADS SST and MFS_SST are as close as possible during the satellite era to have some more confidence for the past

3. MFS_SST are daily optimally Interpolated Sea Surface Temperature (OISST) maps produced in near real time are for direct assimilation in MFS-OGCM model by CNR-GOS (Roma - Italia). The OISST products cover the Mediterranean and Eastern Atlantic areas at 1/16° resolution.
The same OI scheme has also been used to perform a Re-Analysis (RAv0) of AVHRR Pathfinder SST time series, from 1985 to 2005 by ENEA in collaboration with CNR-GOS. This products will be available at GHRSST very soon
Since July 2006, In the framework of MERSEA, CNR-GOS also produces multi-sensors OISST maps merging a variety of sensors (AVHRR, MODIS, SEVERI, TMI, ATSR) as contribution to the GODAE/GHRSST-PP
Every peope know ICOADS but…
Based on AVHRR only…. …once that minor format problems will be fixed

4. How much can we believe in these data?

5. Can MFS_SST (Optimally Interpolated Sea Surface Temperature) represent the sea-true for the other SST estimate?
Yearly behaviour of the bias between in situ measurements and Pathfinder OISST in the Mediterranean Sea (From Marullo et al. 2006)
Pathfinder MFS_SST (OISST) do not reveal any significant trend of the bias respect to in situ measurements derived from a variety of different sources (XBT, CTD, ARGOS, etc..)
Number of pairs

6. Comparison between data sets in the Mediterranean Sea
Bias
RMSE
Slope
Intercept
ICOADS 1deg - MFS-OISST
0.06
0.90
0.996
0.01
ICOADS 2deg - MFS-OISST
0.07
0.89
0.994
ICOADS 1deg -MFS_OISST
ICOADS 2deg - MFS_OISST
ICOADS are consistent with MFS_SST (OISST).
RMSE values are essentially due to SST variability within the 2x2 or 1x1 deg box

7. Data voids & basin scale SST yearly averages based on ICOADS
A. Since seasonal signal dominates the SST variability, annual average can be distorted where an incomplete time series is used.
B. The spatial distribution of the available data can affect the basin scale monthly SST mean.

8. The yearly average have been calculated only over those boxes where the 12 monthly values were available
Time series in the Mediterranean Sea: percent of grid points where the 12 monthly estimate were available to compute the year average

9. How to reduce the impact of data voids in the annual basin scale SST estimates?
Data voids are present in the yearly maps
A correction factor F have been applied to each basin scale spatial yearly mean to take into account the effect of those data voids:
Gmap: spatial mean of a reference climatic SST map deduced from 25 years of satellite POISST
Gmap(void): spatial mean of the same reference map obtained after flagging grid points that are not available for the ith year

10. Mean Absolute Difference
time series
Mean Absolute Difference
BASIC ICOADS - MFS_OISST
0.13 °C
Corrected ICOADS -MFS_OISST
0.10 °C
The application of the correction for data voids tends to slightly reduce the distance between satellite derived Mediterranean SST and ICOADS SST.

11. We can investigate the effect of the data voids correction over other regions at the same latitude60 40
ATL3
ATL2
ATL1
MED 20 -0
-60
-40
-20 20

12. Effect on Standard Deviation
Med
Standard deviation over 11 years time window
ATL1
After F-correction black line
Before F-correction red line
The impact of the data void correction is more evident where less data are available but, in general, always produce a reduction of the standard deviation over the moving 11 years time window.
ATL2
ATL3

13. Time series analysis: linear trends and variability during the satellite era

14. Yearly linear SST trends in the Mediterranean Sea during the Satellite era (1985-2006)
MFS_OISST trends
°C/year

15. Monthly Sea Surface temperature Trends in the Mediterranean Sea (1985-2006)
°C/y

16. The year 2003 SST anomaly
Probability Density Function (PDF) of the Mediterranean SST from 1985 to 2005 (excluding 2003) (black curves) and 2003 PDF (red curves) derived from POISST

17. Let we now compare the Mediterranean variability with other regions at the the same latitude for the longer ICOADS time series 60 40
ATL3
ATL2
ATL1
MED 20 -0
-60
-40
-20 20

18. SST anomalies respect to the 1961-1990 average
11 years moving average
Unfiltered time series
Min=-0.80 °C Max=+0.5°C
Min=-0.65 °C Max=+0.6°C
Min=-0.45 °C Max=+0.6°C
Min=-0.90 °C Max=+0.5°C
Mean SST

19. ICOADS time series
For the period 1880 to 2005 the slope is ± °C/year
-0.012±0.005 °C/Year
+0.025±0.004 °C/Year
-0.013±0.004 °C/Year
+0.026±0.005 °C/Year
Standard deviation of the slope

20. The 19° C isotherm moved from 35 °N to 39 °N in 90 years

21. Global scale radiative forcing
Radiative forcing figures from: Climate Change 2001: The Scientific Basis,

22. Winter atmospheric Sea Level Pressure along the Subtropical Gyre
Regional forcing

23. Winter (January, February, March) Sea Level Pressure field

24. Conclusions
ICOADS SSTs are consistent with the corresponding satellite estimate of the last two decades
SST increased of more than 1°C during the last century
Radiative forcing are important to explain the time variability of the SST
But local effect can modulate the trends