Marina Tonani

Assessing the impact of observations on ocean forecasts and reanalyses: Part 2, Regional applications

The value of global (e.g. altimetry, satellite sea-surface temperature, Argo) and regional (e.g. radars, gliders, instrumented mammals, airborne profiles and biogeochemical) observation-types for monitoring the mesoscale ocean circulation and biogeochemistry is demonstrated using a suite of global and regional prediction systems and remotely-sensed data. A range of techniques is used to demonstrate the value of different observation-types to regional systems and the benefit of high-resolution and adaptive sampling for monitoring the mesoscale circulation. The techniques include Observing System Experiments, Observing System Simulation Experiments, adjoint sensitivities, representer matrix spectrum, observation footprints and spectral analysis. It is shown that local errors in global and basin-scale systems can be significantly reduced when assimilating observations from regional observing systems.

Toward Marine Environmental Predictions in the Mediterranean Sea Coastal Areas: A Monitoring Approach

Marine environmental predictions involve the observation and modeling of physical, biogeochemical processes and parameters, fused by advanced data assimilation schemes that optimally merge the observational and numerical modeling information in order to produce forecasts. The result of such system should be interfaced with socio-economic models of sustainable development and management of marine resources. Fusing the deterministic dynamical information about the marine ecosystem with the socio-economic and political knowledge of the marine environment has not been tried yet but it is one of the outstanding challenges in integrated coastal management studies. This paper tries to show a scientific strategy to predict the physical and biochemical components toward marine environmental predictions, being aware that some considerations could be changed in view of the integration with socio-economic models and issues. Here we use prediction in total analogy with forecasting and thus as synonymous of deterministic prognosis of dynamical variables from a pre-defined initial state of the system.

The diurnal cycle of sea-surface temperature and estimation of the heat budget of the Mediterranean Sea

The diurnal cycle in sea-surface temperature (SST) is reconstructed for the year 2013 by combining numerical model analyses and satellite measurements using Optimal Interpolation (OI). The method is applied to derive hourly Mediterranean SST fields using Spinning Enhanced Visible and Infrared Imager (SEVIRI) data and Mediterranean Forecasting System analyses (Copernicus Marine Environment Monitoring Service - Analysis and Forecast product). The evaluation of the Diurnal OI SST (DOISST) values against drifter measurements results in a mean bias of −0.1°C and a RMS of 0.4°C. The DOISST fields reproduce well the diurnal cycle in SST including extreme Diurnal Warming events as measured by drifting buoys. We evaluate the impact of resolving the SST diurnal cycle, including extreme events, on estimates of the heat budget of the Mediterranean Sea over an entire annual cycle. It results in the mean annual difference in the heat loss derived using SSTs with and without diurnal variations of 4 Wm−2 with a peak of 9 Wm−2 in July. This value is comparable to several other sources of uncertainty in the calculation of the heat and water budgets of the Mediterranean Sea. The results are an important step toward reducing uncertainties in the “Mediterranean Sea Heat Budget Closure Problem”.

Mediterranean ocean forecasting system: First phase of implementation

Abstract The Mediterranean Forecasting System Pilot Project (1998-2001) has been completed and every week a ten days forecast is released on the Web ( http://www.cineca.it/mfspp ). This is realised with a networking of Near Real Time observing and modelling centres started within the project and working operationally from January 2000. The network consists of: 1) three data centres that provide in situ and satellite data for initialisation of model forecasts. The observations are released with a time delay of one to three days through the internet; 2) a meteorological data centre for the collection and transmission of atmospheric forcing fields; 3) a central modelling and data assimilation centre which executes the forecasts. The satellite data consist of sea level anomalies and sea surface temperatures (SST) while the in situ data are temperature profiles acquired on Voluntary Observing ship tracks at biweekly frequency. All these data are assimilated to produce an initial condition for the forecast that is coupled asynchronously to atmospheric forecast surface fields. Skill scores indicate that RMS forecast error is lower than RMS persistence error after the first day in all Mediterranean regions.