Development of adjoint-based ocean state estimation for the Amundsen and Bellingshausen seas and ice shelf cavities using MITgcm–ECCO (66j)

Abstract. The Antarctic coastal ocean impacts sea level rise, deep-ocean circulation, marine ecosystems, and the global carbon cycle. To better describe understand these processes their variability, it is necessary to combine sparse available observations with best-possible numerical descriptions of circulation. In particular, high ice shelf melting rates in Amundsen Sea have attracted many observational campaigns, we now some limited oceanographic data that capture seasonal interannual variability during past decade. One method models can maximize information extracted from adjoint method, a.k.a. 4D-Var (4-dimensional variational assimilation), as developed implemented for state estimation by Estimating Circulation Climate Ocean (ECCO) project. Here, first time, apply adjoint-model a regional configuration Bellingshausen seas, Antarctica, including explicit representation sub-ice-shelf cavities. We utilize 2010–2014, ship-based seal-tagged CTD measurements, moorings, satellite sea-ice concentration estimates. After 20 iterations adjoint-method minimization algorithm, cost function, here defined sum weighted model–data difference, reduced 65 % relative baseline simulation adjusting initial conditions, atmospheric forcing, vertical diffusivity. components function are 59 70 %, respectively. Major improvements include representations (1) Winter Water (WW) characteristics (2) intrusions modified Circumpolar Deep (mCDW) towards Pine Island Glacier. Sensitivity experiments show ∼40 ∼10 state, respectively, be attributed adjustment air temperature wind. This study preliminary demonstration optimization cavity Despite reduction, substantial discrepancies remain, particular annual observed moorings front Ice Shelf. list series possible causes residuals, limitations model, methodology, sampling. hypothesize residuals could further if model more accurately represent polynyas.