Impacts of high-resolution Himawari-8 AMVs on TC forecast in HWRF
Masahiro Sawada
EMC/JMA
14 August, Noon, in 2155
Abstract:
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.