Pathways to Better Prediction of the MJO: 2. Impacts of Atmosphere-Ocean Coupling on the Upper Ocean and MJO Propagation.

This study investigates effects of atmosphere-ocean coupling on MJO precipitation and eastward propagation, and upper ocean conditions during and after MJO passage. To explore pathways for improving MJO prediction, three model experiments are conducted using the Unified Wave Interface-Coupled Model at convection-permitting (4 km) resolution: (a) uncoupled atmosphere-only, (b) coupled atmosphere-ocean, and (c) coupled atmosphere-ocean with improved air-sea flux algorithm simulations. The model simulations are compared with observations from the DYNAMO field campaign in 2011. Both coupled atmosphere-ocean simulations produced eastward propagation of the MJO where the uncoupled, atmosphere-only simulation did not. The uncoupled model overestimates both precipitation and surface winds associated with the MJO, while coupled model simulations substantially reduce model bias. Improved air-sea fluxes lead to systematic improvements in precipitation, winds, sea surface temperature, and the ocean mixed layer when compared to the original coupled simulation. This leads to further improvement of the MJO's eastward propagation speed compared with observations. Despite these improvements, the regional coupled simulations still have difficulty representing the extent of convectively suppressed conditions in the Indian Ocean after MJO passage, which indicates the importance of the large-scale environment from lateral boundary conditions. Coupled model simulations also reveal some issues in the representation of upper ocean stratification in the ocean model, especially errors in salinity, which result in overestimation of the mixed layer depth after MJO passage.

Towards integrated modeling of the long-term impacts of oil spills.

Although great progress has been made to advance the scientific understanding of oil spills, tools for integrated assessment modeling of the long-term impacts on ecosystems, socioeconomics and human health are lacking. The objective of this study was to develop a conceptual framework that could be used to answer stakeholder questions about oil spill impacts and to identify knowledge gaps and future integration priorities. The framework was initially separated into four knowledge domains (ocean environment, biological ecosystems, socioeconomics, and human health) whose interactions were explored by gathering stakeholder questions through public engagement, assimilating expert input about existing models, and consolidating information through a system dynamics approach. This synthesis resulted in a causal loop diagram from which the interconnectivity of the system could be visualized. Results of this analysis indicate that the system naturally separates into two tiers, ocean environment and biological ecosystems versus socioeconomics and human health. As a result, ocean environment and ecosystem models could be used to provide input to explore human health and socioeconomic variables in hypothetical scenarios. At decadal-plus time scales, the analysis emphasized that human domains influence the natural domains through changes in oil-spill related laws and regulations. Although data gaps were identified in all four model domains, the socioeconomics and human health domains are the least established. Considerable future work is needed to address research gaps and to create fully coupled quantitative integrative assessment models that can be used in strategic decision-making that will optimize recoveries from future large oil spills.

Submesoscale dispersion in the vicinity of the Deepwater Horizon spill.

Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society, and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity field at the submesoscales (100 m to tens of kilometers, hours to days) remain unresolved due to a lack of synoptic measurements at these scales. Using high-frequency position data provided by the near-simultaneous release of hundreds of accurately tracked surface drifters, we study the structure of submesoscale surface velocity fluctuations in the Northern Gulf of Mexico. Observed two-point statistics confirm the accuracy of classic turbulence scaling laws at 200-m to 50-km scales and clearly indicate that dispersion at the submesoscales is local, driven predominantly by energetic submesoscale fluctuations. The results demonstrate the feasibility and utility of deploying large clusters of drifting instruments to provide synoptic observations of spatial variability of the ocean surface velocity field. Our findings allow quantification of the submesoscale-driven dispersion missing in current operational circulation models and satellite altimeter-derived velocity fields.

Hurricane intensity and eyewall replacement.

Observations made during the historic 2005 hurricane season document a case of "eyewall replacement." Clouds outside the hurricane eyewall coalesce to form a new eyewall at a greater radius from the storm center, and the old eyewall dies. The winds in the new eyewall are initially weaker than those in the original eyewall, but as the new eyewall contracts, the storm reintensifies. Understanding this replacement mechanism is vital to forecasting variations in hurricane intensity. Processes in the "moat" region between the new and old eyewall have been particularly unclear. Aircraft data now show that the moat becomes dynamically similar to the eye and thus is converted into a region inimical to survival of the inner eyewall. We suggest that targeting aircraft to key parts of the storm to gain crucial input to high-resolution numerical models can lead to improvements in forecasting hurricane intensity.