Impacts of high-resolution Himawari-8 AMVs on TC forecast in HWRF

Masahiro Sawada
  14 August, Noon, in 2155


To investigate the impact of the assimilation of high spatial and temporal resolution atmospheric motion vectors (AMVs) derived from the full disk scan of the new generation geostationary satellite Himawari-8 on tropical cyclone (TC) forecasts in a western North Pacific basin, forecast experiments for three TCs in 2016 are performed using the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting Model (HWRF). Two different data assimilation (DA) configurations (three-dimensional variational DA and ensemble-variational hybrid DA), based on the Grid-point Statistical Interpolation (GSI), are used for the sensitivity experiments.

The results show the inclusion of high-resolution Himawari-8 AMVs (H8AMV) can benefit the track forecast skill, especially for longer-range lead times. The diagnosis of optimal steering flow indicates that the improved track forecast is attributed to the improvement of steering flow surrounding the TC itself, but not in the representation of TC structure. However, the assimilation of H8AMV increases the negative intensity bias and error, especially for short-range lead times. The investigation of the structural change from the assimilation of H8AMV revealed that an increase of inertial stability outside the radius of maximum wind (RMW) which weakens the boundary layer inflow, enhancement of asymmetric component around the RMW, and drying of the inner core region are three factors related to the negative intensity bias. An experiment using ensemble-variational hybrid assimilation demonstrates that combining H8AMV with the hybrid assimilation contributes to a significant reduction in negative intensity bias and error, while retaining the improvement in track forecast.