Assessment of wind‐stress errors using bias corrected ocean data assimilation

Abstract

SUMMARYCurrent seasonal forecasting methods make extensive use of wind-stress products and ocean thermal profile observations to produce ocean analyses for retrospective forecasts. The combination of inaccurate wind-stress forcing and relatively accurate ocean thermal profile observations can have significant detrimental impacts on the analysis in equatorial regions as it leads to an imbalance between the zonal pressure gradient and wind stress. Model integrations have been performed to assess various wind-stress products using a Pacific region ocean general-circulation model in three assimilation modes. The assimilation of thermal profile data has been shown to impact negatively on the zonal and vertical current structure. A bias correction scheme has been used to illustrate how these errors can be mitigated. The method used to correct for these systematic errors allows for the errors to evolve in time and space. The strength of the equatorial undercurrent is brought to a realistic level, but the scheme does reduce its variability. The European Remote Sensing satellite scatterometer wind products have been used to illustrate the methodology and comparisons have been drawn with several other wind-stress products.

Impact of Data Assimilation on ECCO2 Equatorial Undercurrent and North Equatorial Countercurrent in the Pacific Ocean

“…In the eastern Pacific-for example, 1408 and 1108W-our result that data assimilation had no impact on the 5-yr mean EUC transport (Fig. 4) was not consistent with the results of Huddleston et al (2004), Hoteit et al (2010, Balmaseda et al (2013) and Karspeck et al (2013), which indicated that assimilation of data increased the EUC transport, and was not similar to the Hyder et al (2012) result that data assimilation reduced the EUC transport at 1408W. In the western Pacific-for example, 1658E and 1708W-we found data assimilation to have no impact in some years and it increased EUC transport in other years.…”

“…In the western Pacific-for example, 1658E and 1708W-we found data assimilation to have no impact in some years and it increased EUC transport in other years. Huddleston et al (2004), Hoteit et al (2010), and Balmaseda et al (2013) reported that data assimilation increased the EUC transport in the western Pacific, but Karspeck et al (2013) found that data assimilation reduced the EUC transport. Hoteit et al (2010 assimilated NOAA in situ moored current measurements recorded along the equator, unlike other studies.…”

Meteorological Research Institute multivariate ocean variational estimation (MOVE) system: Some early results

“…3. The same problem also occurs in other data assimilation systems (e.g., Huddleston et al, 2004). The correction of this defect is a part of future work.…”

Data assimilation in the FOAM operational short‐range ocean forecasting system: a description of the scheme and its impact

“…An example of this is in the tropical oceans, where the main large-scale dynamical balance is between the surface wind stress and the subsurface pressure gradients. When assimilating temperature, salinity and altimeter data, the subsurface pressure gradients are altered to be closer to the true state, but systematic errors in the wind forcing and the way in which it is input into the model can disrupt this balance (Huddleston et al, 2004). This causes spurious circulation cells to be set off by the assimilation; these tend to oppose the increments being put in by the assimilation.…”