Davidson, F., Alvera-Azcárate, A., Barth, A., Brassington, G. B., Chassignet, E. P., Clementi, E., et al. (2019). Synergies in Operational Oceanography: The Intrinsic Need for Sustained Ocean Observations.
Front. Mar. Sci., 6.
Abstract: Operational oceanography can be described as the provision of routine oceanographic information needed for decision-making purposes. It is dependent upon sustained research and development through the end-to-end framework of an operational service, from observation collection to delivery mechanisms. The core components of operational oceanographic systems are a multi-platform observation network, a data management system, a data assimilative prediction system, and a dissemination/accessibility system. These are interdependent, necessitating communication and exchange between them, and together provide the mechanism through which a clear picture of ocean conditions, in the past, present, and future, can be seen. Ocean observations play a critical role in all aspects of operational oceanography, not only for assimilation but as part of the research cycle, and for verification and validation of products. Data assimilative prediction systems are advancing at a fast pace, in tandem with improved science and the growth in computing power. To make best use of the system capability these advances would be matched by equivalent advances in operational observation coverage. This synergy between the prediction and observation systems underpins the quality of products available to stakeholders, and justifies the need for sustained ocean observations. In this white paper, the components of an operational oceanographic system are described, highlighting the critical role of ocean observations, and how the operational systems will evolve over the next decade to improve the characterization of ocean conditions, including at finer spatial and temporal scales.
Hu, X., Cai, M., Yang, S., & Wu, Z. (2018). Delineation of thermodynamic and dynamic responses to sea surface temperature forcing associated with El Niño.
Clim Dyn, 51(11-12), 4329–4344.
Abstract: A new framework is proposed to gain a better understanding of the response of the atmosphere over the tropical Pacific to the radiative heating anomaly associated with the sea surface temperature (SST) anomaly in canonical El Niño winters. The new framework is based on the equilibrium balance between thermal radiative cooling anomalies associated with air temperature response to SST anomalies and other thermodynamic and dynamic processes. The air temperature anomalies in the lower troposphere are mainly in response to radiative heating anomalies associated with SST, atmospheric water vapor, and cloud anomalies that all exhibit similar spatial patterns. As a result, air temperature induced thermal radiative cooling anomalies would balance out most of the radiative heating anomalies in the lower troposphere. The remaining part of the radiative heating anomalies is then taken away by an enhancement (a reduction) of upward energy transport in the central-eastern (western) Pacific basin, a secondary contribution to the air temperature anomalies in the lower troposphere. Above the middle troposphere, radiative effect due to water vapor feedback is weak. Thermal radiative cooling anomalies are mainly in balance with the sum of latent heating anomalies, vertical and horizontal energy transport anomalies associated with atmospheric dynamic response and the radiative heating anomalies due to changes in cloud. The pattern of Gill-type response is attributed mainly to the non-radiative heating anomalies associated with convective and large-scale energy transport. The radiative heating anomalies associated with the anomalies of high clouds also contribute positively to the Gill-type response. This sheds some light on why the Gill-type atmospheric response can be easily identifiable in the upper atmosphere.
Dukhovskoy, D. S., Myers, P. G., Platov, G., Timmermans, M. - L., Curry, B., Proshutinsky, A., et al. (2016). Greenland freshwater pathways in the sub-Arctic Seas from model experiments with passive tracers.
J. Geophys. Res. Oceans, 121(1), 877–907.