A pre-operational variational data assimilation system for a non-hydrostatic model at the Japan Meteorological Agency: Formulation and preliminary results

A new variational data assimilation system for a non-hydrostatic model is being developed at the Japan Meteorological Agency (JMA) for operational use. Known as the JMA non-hydrostatic model variational data assimilation (JNoVA) system, it mainly functions as a four-dimensional variational data assimilation system, although it has an option to be used as a three-dimensional system. The set of control variables consists of initial conditions of unbalanced horizontal winds, large-scale components of potential temperature and surface pressure, unbalanced temperature and pseudo relative humidity. In the control variable transformation, hydrostatic balance and geostrophic balance are considered explicitly and the effect of the surface friction is also considered implicitly. When calculating the background-error covariances by the NMC method, a low-pass filter is introduced to remove noise in potential temperature and surface pressure that degrades the quality of the balanced winds. The cut-off wavelength of the low-pass filter is set to 300 km, which is the scale at which the model's kinetic energy spectrum transits to the shallower slope characterizing mesoscale motions. An adjoint model of the JMA non-hydrostatic model has been developed from scratch by hand for this system. Although some of the physics are simplified, all physical processes except the radiation are considered. A preliminary data assimilation experiment with the JNoVA has been done for a heavy rainfall event. The results show that the quantitative precipitation forecast (in terms of the intensity, timing and position of the event) from the analysis by the JNoVA is improved over the forecast from the analysis by a four-dimensional variational system that employs the JMA hydrostatic spectral model.