Response of the Adriatic Sea to the atmospheric anomaly in 2003

Unusual weather conditions over the southern Europe and the Mediterranean area in 2003 significantly impacted the oceanographic properties of the Adriatic Sea. To document these changes, both in the atmosphere and the sea, anomalies from the normal climate were calculated. The winter 2003 was extremely cold, whereas the spring/summer period was extremely warm. The air temperature in June was more than 3 standard deviations above the average. On the other hand, precipitation and river runoff were extremely low between February and August. The response of the sea was remarkable, especially in surface salinity during spring and summer, with values at least one standard deviation above the average. Analysis of thermohaline properties in the middle Adriatic showed the importance of two phenomena responsible for the occurrence of exceptionally high salinity: (1) enhanced inflow of saline Levantine Intermediate Water (LIW) in the Adriatic, and (2) extremely low precipitation and river runoff, accompanied with strong evaporation. Two large-scale atmospheric indices: NAOI (North Atlantic Oscillation Index) and MOI (Mediterranean Oscillation Index), although generally correlated to the Adriatic climate, failed to describe anomalies in 2003. The air pressure gradients used for the definition of both indices significantly decreased in 2003 due to the presence of the high pressure areas over most of Europe and the northern Atlantic, and were actually responsible for the observed anomalies above and in the Adriatic

A 55-Year Time Series Station for Primary Production in the Adriatic Sea: Data Correction, Extraction of Photosynthesis Parameters and Regime Shifts

In 1962, a series of in situ primary production measurements began in the Adriatic Sea, at a station near the island of Vis. To this day, over 55 years of monthly measurements through the photic zone have been accumulated, including close to 3000 production measurements at different depths. The measurements are conducted over a six-hour period around noon, and the average production rate extrapolated linearly over day length to calculate daily production. Here, a non-linear primary production model is used to correct these estimates for potential overestimation of daily production due to linear extrapolation. The assimilation numbers are recovered from the measured production profiles and subsequently used to model production at depth. Using the recovered parameters, the model explained 87% of variability in measured normalized production at depth. The model is then used to calculate daily production at depth, and it is observed to give on average 20% lower daily production at depth than the estimates based on linear extrapolation. Subsequently, water column production is calculated, and here, the model predicted on average 26% lower water column production. With the recovered parameters and the known magnitude of the overestimation, the time-series of water column production is then re-established with the non-linearly-corrected data. During this 55-year period, distinct regimes were observed, which were classified with a regime shift detection method. It is then demonstrated how the recovered parameters can be used in a remote sensing application. A seasonal cycle of the recovered assimilation number is constructed along with the seasonal cycle of remotely-sensed chlorophyll. The two are then used to model the seasonal cycle of water column production. An upper and a lower bound on the seasonal cycle of water column production based on remotely-sensed chlorophyll data are then presented. Measured water column production was found to be well within the range of remotely-sensed estimates. With this work, the utility of in situ measurements as a means of providing information on the assimilation number is presented and its application as a reference for remote sensing models highlighted

Recovery of photosynthesis parameters fromin situprofiles of phytoplankton production

We examine a model of the rate of phytoplankton production in the ocean and its dependence on depth. The model is analysed as a function of photosynthesis parameters and it is shown that: (i) production profiles with depth are determined uniquely by the parameter values; (ii) daily water column production is not uniquely determined by the parameter values; (iii) a unique combination of parameters exists for which the model best fits a measured production profile. An inverse procedure is developed to recover photosynthesis parameters from measured profiles of primary production, and its performance tested by application to profiles of primary production collected at the Hawaii Ocean Time Series. For each profile tested, the method is successful in recovery of the photosynthesis parameters. The method can be applied to the estimation of photosynthesis parameters from data on in situ production profiles, which have been collected globally for more than half a century, thereby augmenting the world archive of these parameters for application in ecosystem modelling and estimation of primary production from remotely sensed data