Tremendous advances in oceanographic observing and modelling systems over the last decade have led to unprecedented developments in the nature of information available to marine science. While improvements in observational technologies and networks have garnered much attention, remarkable developments in forecasting the ocean have received much less focus. Exploiting this new predictive skill to improve scientific understanding, generate advice and aid in the management of marine resources, is emerging as one of the new challenges of marine science.
The potential for predicting the ocean far exceeds that of the atmosphere. The slow-dynamics (and therefore “long-memory”) of the ocean mean that anomalies can persist for months or longer, and can thus be used as the basis for simple persistence forecasts. State of the art global climate prediction systems can increase forecast skill above persistence, adding further value and allowing for higher forecast skill at longer lead times. Moreover, in some areas (e.g. NE Atlantic) statistically meaningful predictive skill of variables such as sea-surface temperature has been demonstrated out to five years or more.
Translating these predictions of the physical environment into biological outcomes, on the other hand, is not straightforward. Fisheries scientists, for example, have been trying to understand the links between physics and biology, and generate predictions of variables such as recruitment, for close to a century, with limited success. Nevertheless, spatial distributions and the timing of key events, which have received less focus, are often tightly linked to the physical environment and may have management-relevant applications.
This research topic aims to provide an overview of marine forecasting at seasonal-to-decadal scales, a scientific field that is still in its infancy, and allow researchers to share their experiences of developing prediction systems for marine resource management. We welcome contributions that address all aspects of prediction in marine ecosystems, including, but not limited to:
• What aspects of the marine physical (and chemical) environment can be predicted? For what variables and over what time and space scales does predictability exist? How does the predictability arise?
• What aspects of the marine biological environment can be predicted? What biological responses are the most predictable and why?
• Do we need to have mechanistic understanding or can useful predictions be predicated on the basis of correlative relationships?
• How do we assess the quality (skill) of a prediction?
• What can be learned from biological predictions already being made on the climatic (centennial) time-scales? Where are there similarities and where are there differences?
• How do we use predictions of biological outcomes in pre-existing advice and management structures? What structures are required to take advantage of this new knowledge? How can these estimates be incorporated into management strategy evaluations?
• How do we make predictions with a frequency and timeliness that is appropriate for end-users?
• Does predictive knowledge have a value in the management of marine systems? How can we quantify the value of such knowledge?
• Case studies of existing and proposed predictive systems
• Needs for future research, advisory and management structures
Tremendous advances in oceanographic observing and modelling systems over the last decade have led to unprecedented developments in the nature of information available to marine science. While improvements in observational technologies and networks have garnered much attention, remarkable developments in forecasting the ocean have received much less focus. Exploiting this new predictive skill to improve scientific understanding, generate advice and aid in the management of marine resources, is emerging as one of the new challenges of marine science.
The potential for predicting the ocean far exceeds that of the atmosphere. The slow-dynamics (and therefore “long-memory”) of the ocean mean that anomalies can persist for months or longer, and can thus be used as the basis for simple persistence forecasts. State of the art global climate prediction systems can increase forecast skill above persistence, adding further value and allowing for higher forecast skill at longer lead times. Moreover, in some areas (e.g. NE Atlantic) statistically meaningful predictive skill of variables such as sea-surface temperature has been demonstrated out to five years or more.
Translating these predictions of the physical environment into biological outcomes, on the other hand, is not straightforward. Fisheries scientists, for example, have been trying to understand the links between physics and biology, and generate predictions of variables such as recruitment, for close to a century, with limited success. Nevertheless, spatial distributions and the timing of key events, which have received less focus, are often tightly linked to the physical environment and may have management-relevant applications.
This research topic aims to provide an overview of marine forecasting at seasonal-to-decadal scales, a scientific field that is still in its infancy, and allow researchers to share their experiences of developing prediction systems for marine resource management. We welcome contributions that address all aspects of prediction in marine ecosystems, including, but not limited to:
• What aspects of the marine physical (and chemical) environment can be predicted? For what variables and over what time and space scales does predictability exist? How does the predictability arise?
• What aspects of the marine biological environment can be predicted? What biological responses are the most predictable and why?
• Do we need to have mechanistic understanding or can useful predictions be predicated on the basis of correlative relationships?
• How do we assess the quality (skill) of a prediction?
• What can be learned from biological predictions already being made on the climatic (centennial) time-scales? Where are there similarities and where are there differences?
• How do we use predictions of biological outcomes in pre-existing advice and management structures? What structures are required to take advantage of this new knowledge? How can these estimates be incorporated into management strategy evaluations?
• How do we make predictions with a frequency and timeliness that is appropriate for end-users?
• Does predictive knowledge have a value in the management of marine systems? How can we quantify the value of such knowledge?
• Case studies of existing and proposed predictive systems
• Needs for future research, advisory and management structures
