Comparison of Two Kinds of Momentum Control Variables in 3DVAR During Assimilating Low-resolution Observations in a Convective-scale Model: a Case Study of Torrential Rainfall in North China

The x and y components of wind (U and V, respectively) are widely used as control variables in radar assimilation; therefore, it is common to choose (U, V) as the control variables for multi-scale data assimilation (DA) in convective-scale. When the model resolution reaches the convective scale, whether (U, V), as the momentum control variables, are still more suitable than the stream function (ψ) and unbalanced velocity potential (χ_u), it needs to be studied further examination. This study uses 3-km resolution forecast samples to calculate the background error covariance (B) with two different pairs of momentum control variables ((ψ, χ_u) and (U, V)) by the National Meteorology Center (NMC) method. In single-observation experiments, the analysis wind field is most sensitive to the two pairs of B, and the temperature is insensitive. When using (U, V) as the control variables, the local characteristic is more evident according to vertical and horizontal wind increments. The study assimilates low- resolution conventional observations to compare different momentum control variables, (ψ, χ_u) and (U, V), in numerical simulation experiments of the torrential rainfall in North China. In addition, the impacts of the two control variables options are also compared in terms of the 15 continuous days of cases in flood season. The main results are as follows: (1) the wind field is the critical difference between the two assimilation experiments at the analysis time. Using (U, V) as the control variables, the analysis field of wind from both the surface and different vertical levels is superior. The analysis field closer fits the wind observation; (2) the use of (U, V) control variables improves the short term (0 ~ 3-h) in surface wind prediction; and (3) the use of (U, V) control variables enhances the 24-h TS (threat score) in moderate rain and heavy rain.