  A simplified model of natural convection, similar to the Lorenz (1963)
system, is compared to computational fluid dynamics simulations in order to
test data assimilation methods and better understand the dynamics of
convection. The thermosyphon is represented by a long time flow simulation,
which serves as a reference "truth". Forecasts are then made using the
Lorenz-like model and synchronized to noisy and limited observations of the
truth using data assimilation. The resulting analysis is observed to infer
dynamics absent from the model when using short assimilation windows.
  Furthermore, chaotic flow reversal occurrence and residency times in each
rotational state are forecast using analysis data. Flow reversals have been
successfully forecast in the related Lorenz system, as part of a perfect model
experiment, but never in the presence of significant model error or unobserved
variables. Finally, we provide new details concerning the fluid dynamical
processes present in the thermosyphon during these flow reversals.
