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Another reason why the FillValues give me a headache: Most users place point sources at locations where the u- or v-mask is zero (i.e. land). During the simulation the model will actually compute a source value at that 'land' location and those transports are used in the simulation. However, when writing history or other output files, the u- or v-values at the ppoint source locations will be replaced with FillValues.

This does not allow the user to check if the correct transport is being introduced into the model. Please negate the FillValue at locations of the point sources. Suggested fix: make up a temporary u/vmask that does not mask the point sources in wrt_his.F send that temporary mask to nf_fwite3d instead of GRID(ng)%umask.

A new C-preprocessing option FLOAT_STICKY was added to reflect floats that hit the surface and stick floats that hit the bottom. This is needed to avoid overshoots and spurious unmixing near the boundary when vertical random walk (FLOAT_VWALK) is activated.

Alternate options may be needed in the floats with biological behavior.

Many thanks to Mark Hadfield for contributing this option.

A new C-preprocessing option was added MINRES to accelerate the convergence of the dual formulation data assimilation algorithms (R4D-Var and 4D-PSAS) using the Minimal Residual Method (MinRes) proposed by El Akkraoui and Gauthier (2010, QJRMS, 136, 107-115). This method is described by Paige and Saunders (Sparse Indefinite Systems of Linear Equations, 1975, SIAM Journal on Numerical Analysis, 617-619). Specifically we use equations 6.10 and 6.11 of this paper.

This is a remarkable algorithm and makes R4D-Var and 4D-PSAS practical in strong- and weak-constraint applications. The convergence rate is similar to that of the primal form I4D-Var. This is illustrated in the following plot:

This algorithm also works for the associated observation sensitivity and observation impact. We still need to work on the posterior analysis routines posterior.F and posterior_var.F. These routines will be updated to MINRES later.

Many thanks to Andy Moore for his help in coding and testing this new algorithm. Also many thanks to Amal El Akkraoui for bringing this minimization algorithm to our attention at the last International Adjoint Workshop.