Why Gliders Appreciate Good Company: Glider Assimilation in the Oregon‐Washington Coastal Ocean 4DVAR System With and Without Surface Observations

Abstract

Gliders are low-power autonomous underwater vehicles used to obtain oceanic measurements in vertical sections. Assimilation of glider temperature and salinity into coastal ocean circulation models holds the potential to improve the ocean subsurface structure estimate. In this study, the impact of assimilation of glider observations is studied using a four-dimensional variational (4DVAR) data assimilation and forecast system set offshore of Oregon and Washington on the U.S. West Coast. Four test cases are compared: (1) no assimilation, (2) assimilation of glider temperature and salinity data alone, (3) assimilation of the glider data in combination with the surface observations including satellite sea surface temperature, sea surface height, and high-frequency radar surface velocities, and (4) assimilation of the surface data alone. It is found that the assimilation of glider observations alone creates unphysical eddies in the vicinity of the glider transect. As a consequence, the forecast errors in the surface velocity and temperature increase compared to the case without data assimilation. Assimilation of surface and subsurface observations in combination prevents these features from forming and reduces the errors in the forecasts for the subsurface fields compared to the other three experiments. These improvements persisted in 21-day forecasts run after the last data assimilation cycle.Plain Language Summary Ocean forecast systems, like our system for the ocean offshore Oregon-Washington, USA, use numerical models to predict future temperature, currents, sea surface height, and salt concentration. Eventually, these predictions are corrected using observations in a process called data assimilation (DA) in order to better approximate the true state of the ocean. Assimilation of subsurface observations made by autonomous underwater vehicles called gliders can potentially improve the predictions of the ocean state below the surface. In this study, we have assimilated glider observations together with, and in absence of, surface observations. We found that assimilation of glider observations alone creates predictions that are less accurate than those obtained from a model without DA as the DA creates unphysical features. Assimilating the glider observations in tandem with surface observations prevents these features from forming and realizes local improvements to the subsurface ocean predictions that last for 21 days after the last DA correction. These results show that one has to be careful with using glider observations in DA and should always assimilate glider observations in combination with observations that cover large swaths of the ocean surface.

Assessing the Impact of Nontraditional Ocean Observations for Prediction of the East Australian Current

“…The work by Pasmans et al. (2019), in which the reanalysis using the combination of surface and glider observations was skillful in estimating and forecasting the subsurface ocean features, has demonstrated that assimilating glider observations without the surface observations can create erroneous eddy variability that will deteriorate forecast performance.…”

“…It is also noteworthy that the glider observations should be used with caution. The work by Pasmans et al (2019), in which the reanalysis using the combination of surface and glider observations was skillful in estimating and forecasting the subsurface ocean features, has demonstrated that assimilating glider observations without the surface observations can create erroneous eddy variability that will deteriorate forecast performance. shows that the sharper across-current vorticity gradient within the EAC leads in turn to more intense submesoscale features growing on its inshore side.…”

Action Progress Report #2

“…A final way to compare the system is to give more weight on some specific physical structures, for example the formation of an eddy between August-December 2017 in the Balearic Sea (Aguiar et al, 2019). This is a good testbed to assess the gain from glider observations which are prone to generate eddy-like structures in the analysis (Pasmans et al, 2019). In these experiments, the initial condition (IC) used for the forecast, which is normally the best estimate available (i.e., analysis state), is perturbed by using analysis fields from the preceding 10-days.…”

Accurate pH and O2 Measurements from Spray Underwater Gliders

“…For example, Spray gliders operating in the California Underwater Glider Network (CUGN) have made sustained observations along three lines in the CCS since 2007 (Rudnick et al 2017) and have been used to study the impacts of the 2014-15 marine heat wave (Zaba and Rudnick 2016) and the El Niño of 2015-16 (Jacox et al 2016). Glider observations are also particularly useful for constraining data assimilating models, and it has been demonstrated that assimilating glider data can significantly improve model forecasting capabilities (Pasmans et al 2019). Biogeochemical sensors have been equipped onto gliders to measure parameters such as O 2 (Pierce et al 2012), nitrate (Evans et al 2013;Vincent et al 2018), bio-optics (Briggs et al 2011), and zooplankton (Ohman et al 2019).…”