NUMERICAL EXPERIMENTS AND ANALYSIS OF DIGITAL FILTER INITIALIZATION FOR WRF MODEL

Initialization and initial imbalance problem were discussed in the context of a three-dimensional variational data assimilation system of the new generation “Weather Research and Forecasting Model”. Several options of digital filter initialization have been tested with a rain storm case. It is shown that digital filter initialization, especially diabatic digital filter initialization and twice digital filter initialization, have effectively removed spurious high frequency noise from initial data for numerical weather prediction and produced balanced initial conditions. For six consecutive intermittent data assimilation cycles covering a 3-day period, mean initialization increments and impact on forecast variables are studied. DFI has been demonstrated to provide better adjustment of the hydrometeors and vertical velocity, reduced spin-up time, and improved forecast variables quantity.

NUMERICAL EXPERIMENTS AND ANALYSIS OF DIGITAL FILTER INITIALIZATION FOR WRF MODEL

Initialization and initial imbalance problem were discussed in the context of a three-dimensional variational data assimilation system of the new generation "Weather Research and Forecasting Model". Severaloptions of digital filter initialization have been tested with a rain storm case. It is shown that digital filter initialization, especially diabatic digital filter initialization and twice digital filter initialization, have effectively removed spurious high frequency noise from initial data for numerical weather prediction and produced balanced initial conditions. For six consecutive intermittent data assimilation cycles covering a 3-day period, mean initialization increments and impact on forecast variables are studied. DFI has been demonstrated to provide better adjustment of the hydrometeors and vertical velocity, reduced spin-up time, and improved forecast variables quantity.