Publications by authors named "Andrea Storto"

Long-term changes in ocean heat content (OHC) represent a fundamental global warming indicator and are mostly caused by anthropogenic climate-altering gas emissions. OHC increases heavily threaten the marine environment, therefore, reconstructing OHC before the well-instrumented period (i.e.

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Four different Marine Rapid Environmental Assessment (MREA) procedures are compared with a focus on underwater acoustic performance. Co-located oceanographic-acoustic data were collected during the summer of 2015 in the Northwestern Mediterranean in the framework of a sea trial led by the NATO Centre for Maritime Research and Experimentation. The data were used to link MREA procedures and ocean-acoustic validation in a seamless framework.

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Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged to make better use of observations that are already available, for example, taking advantage of strongly coupled DA so that ocean observations can be used to improve atmospheric analyses and vice versa.

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There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability.

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Predicting North Atlantic hurricane activity months in advance is of great potential societal significance. The ocean temperature, both in terms of North Atlantic/tropical averages and upper ocean heat content, is demonstrated to be a significant predictor. To investigate the relationship between the thermal state of the Atlantic Ocean and the tropical cyclone (TC) activity in terms of accumulated cyclone energy (ACE), we use observed 1980-2015 TC records and a 1/4° resolution global ocean reanalysis.

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Decadal climate predictability in the South Atlantic is explored by performing reforecast experiments using a coupled general circulation model with two initialization schemes; one is assimilated with observed sea surface temperature (SST) only, and the other is additionally assimilated with observed subsurface ocean temperature and salinity. The South Atlantic is known to undergo decadal variability exhibiting a meridional dipole of SST anomalies through variations in the subtropical high and ocean heat transport. Decadal reforecast experiments in which only the model SST is initialized with the observation do not predict well the observed decadal SST variability in the South Atlantic, while the other experiments in which the model SST and subsurface ocean are initialized with the observation skillfully predict the observed decadal SST variability, particularly in the Southeast Atlantic.

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Article Synopsis
  • - Protecting marine biodiversity hotspots, like the Northern Line Islands (NLIs), is crucial for maintaining ecosystem services and enhancing the growth of marine life in both protected areas and surrounding habitats.
  • - The study examines larval connectivity in the NLIs, revealing that the islands often function as "sinks" for larvae rather than "sources," and this connectivity varies seasonally and annually, particularly affected by climate phenomena like El Niño.
  • - Understanding the patterns of larval connectivity over time is essential for creating effective marine protection strategies that can adapt to environmental changes and help preserve marine ecosystems in the face of global warming.
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Various observation- and reanalysis-based estimates of sea ice mass and ocean heat content trends imply that the energy imbalance of the Arctic climate system was similar [1.0 (0.9,1.

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