1. Modes of the Adriatic long-term variability as seen on half-centurial Palagruža Sill series Ivica Vilibić, Hrvoje Mihanović, Jadranka Šepić, Natalija Dunić Institute of Oceanography and Fisheries, Split, Croatia, vilibic@izor.hr

2. Papers: Vilibić, I., Matijević, S., Šepić, J., Kušpilić, G., 2012. Changes in the Adriatic oceanographic properties induced by the Eastern Mediterranean Transient. Biogeosciences, 9, 2085-2097. Vilibić, I., Šepić, J., Proust, N., 2013. Weakening of thermohaline circulation in the Adriatic Sea. Climate Research, 55, 217–225. Vilibić, I., Pištalo, D., Šepić, J., 2015. Long-term variability and trends of relative geostrophic currents in the middle Adriatic. Continental Shelf Research, 93, 70-80. Vilibić, I., Čikeš Keč, V., Zorica, B., Šepić, J., Matijević, S., Džoić, T., 2015. Hydrographic conditions driving sardine and anchovy populations in a land-locked sea. Marine Mediterranean Science, in press, doi: 10.12681/mms.1120. Vilibić, I., Mihanović, H., Ivčević, A., Kušpilić, G., Milun, V., 2015. Mapping of oceanographic properties along a middle Adriatic transect by using Self- Organising Maps. Estuarine Coastal and Shelf Science, 163, 84-92. Mihanović, H., Vilibić, I., Dunić, N., Šepić, J., 2015. Mapping of decadal middle Adriatic oceanographic variability and its relation to the BiOS regime. Journal of Geophysical Research, 120, doi: 10.1002/2015JC010725..

3. Palagruža Sill Data: - Palagruža transect - Stations P1 (528), P2 (529), P3 (216), P4 (206), P5 (199) – number of vertical profiles in brackets - 1952-2010 - temperature, salinity, DO, TIN, HPO 4 2-

4. Vilibić et al. (BG, 2012): variabilityEMT  A strong footprint of EMT in all physical and chemical parameters

5. Vilibić et al. (BG, 2012): variability  Different TIN/HPO4 ratio during the EMT period indicate different origin of the intermediate water masses in the Adriatic Sea

6.  Heating of the Adriatic surface layer  Salinity increase, especially close to coasts  Weakening of dense water formation (northern Adriatic)  Weakening of the Adriatic THC!!!  Lower LIW transport to the Adriatic Vilibić et al., CR, 2013 Vilibić et al. (Cli. Res., 2013): trends

7. Vilibić et al. (CSR, 2015): model NEMOMED8 RegCM trends  RegCMs do not reproduce weakening of the Adriatic THC

8. Vilibić et al. (MMS, 2015): fisheries  Fluctuations of sardine and anchovy parameters are dependant on fluctuations of the Adriatic hydrography.

9. Mihanović et al. (JGR, 2015): BiOS patterns Application of a novel method, Self-Organizing Maps (SOM), to the Adriatic long-term thermohaline series. Motivation: To objectively map the characteristic thermohaline patterns over the Palagruža Sill. What is the SOM method: -Objective mapping method based on neural networks -Performs a nonlinear smooth mapping of high-dimensional input data into the elements of a regular, low-dimensional (usually 2D) array. -This procedure enables that similar patterns are mapped onto neighboring regions on the map.

10. Mihanović et al. (JGR, 2015) SOM setup: batch training algorithm (efficient training)batch training algorithm (efficient training) a 2x3 SOM grid (good compromise between details and graphic presentation)a 2x3 SOM grid (good compromise between details and graphic presentation) rectangular lattice structure (preferable for small size SOMs)rectangular lattice structure (preferable for small size SOMs) linear initialization of unit weights (EOF decomposition and linear interpolation of the first two leading EOFs – saves time with complex data sets)linear initialization of unit weights (EOF decomposition and linear interpolation of the first two leading EOFs – saves time with complex data sets) “ep” neighborhood function (gives the least smoothing to the SOM units)“ep” neighborhood function (gives the least smoothing to the SOM units) The data: T, S, DO at the Palagruža Sill, 1952-2010 T, S, DO at the Palagruža Sill, 1952-2010

11. Mihanović et al. (JGR, 2015)  Objectively extracted patterns at the transect  SOM patterns (BMUs) stand for different circulation modes of the Adriatic, reflecting in water mass and primary production dynamics

12. Mihanović et al. (JGR, 2015)  Changing the length of the dataset and the number of stations used does not largely change SOM patterns All data, gaps 1975-2010, without P4 1994-2010, no gaps

13. Mihanović et al. (JGR, 2015)  BiOS is the dominant generator of the Adriatic variability  SOM patterns of the Absolute Dynamic Topography (ADT) in the northern Ionian Sea show a strong resemblance with T-S changes along the Palagruža Sill  Assymetric ADT patterns in the northern Ionian Sea  BiOS reversals may be rapid (within a year) or slow (2-3 years), resulting in a rapid or a slow changes in the Adriatic properties

14. Conclusions, thoughts, perspectives...  Palagruža Sill is a key and last standing place in the middle and southern Adriatic where basin-wide permanent monitoring of long-term Adriatic changes has been conducted (since 1952).  Other places (Jabuka Pit, Southern Adriatic Pit) have been strongly undersampled in the last two decades  there is no plan B option for the Adriatic ocean climate monitoring, so the monitoring should be maintained in the future!!!  this data is still scientifically underexploited – an opportunity for the future, also through THEMES collaboration JP IOF long-term monitored stations and transects (1952-2015)