An Assessment of the Moana Operational Forecast System Assimilating Innovative Mangōpare Fishing Vessel Observations in Aotearoa, New Zealand Journal Article uri icon

Overview

abstract

  • Coastal seas around Aotearoa, New Zealand, are among the least observed parts of the global ocean, limiting our ability to monitor and forecast marine conditions. The Moana Project addresses this gap with a new observing system that includes temperature sensors mounted on commercial fishing gear—the Mangōpare fishing vessel network. This study presents the first evaluation of New Zealand’s operational ocean 4D-Var data assimilation system that incorporates these fishing vessel (FV) observations into a regional ROMS model. Using just over one year of operational forecasts, we show that FV temperature profiles significantly improve subsurface temperature representation, especially in coastal regions where satellite products have warm biases or miss key features such as upwelling and mesoscale variability. Assimilation of FV data reduces background temperature biases throughout the upper ocean and enhances forecast skill in areas influenced by major currents and dynamic coastal processes. We also identify sensitivity to periods of missing satellite sea surface temperature, which can lead to overfitting of the available observations. Overall, the results demonstrate that FV observations provide essential subsurface information and can substantially strengthen operational coastal ocean forecasting systems.

publication date

  • March 24, 2026

Date in CU Experts

  • March 31, 2026 2:01 AM

Full Author List

  • Azevedo Correia de Souza JM; de Godoi Rezende Costa C

author count

  • 2

Other Profiles

Electronic International Standard Serial Number (EISSN)

  • 2077-1312

Additional Document Info

start page

  • 591

end page

  • 591

volume

  • 14

issue

  • 7