A vision for the
development and implementation of the Warn on Forecast concept
Huiling Yuan
Nanjing University
23 Jan, Noon, in 2155
Abstract:
In this study, a convective-scale ensemble prediction system (EPS) has
been established over the Yangtze-Huaihe river basin, China. The EPS
was implemented at a horizontal grid spacing of 3 km based on the WRF
model (version 3.9), which was initialized daily at 00 UTC and ran out
to 36 h during June 2015. First, using the NCEP global forecast system
(GFS) analysis as the background, radar and in-situ observations were
assimilated to ARPS data assimilation system (ADAS) with cloud
analysis, which was applied to produce the diabatic initial condition
for the convective-scale EPS. Satellite-gauge precipitation analysis at
0.1 degree resolution was used to verify precipitation forecasts.
Compared with the direct downscaling from the GFS initialization, the
forecasts with cloud analysis greatly reduced the spin-up time in the
WRF model, through the adjustment of hydrometeors and vertical
velocity. Multiple combinations of physical parameterization schemes,
including microphysics, planetary boundary layer and land surface
parameterizations, were used in ensemble members to account for model
uncertainties. However, the experiment of a heavy rainfall event
indicated that the spread of multiple physics ensembles alone was
insufficient and ensemble mean forecasts by the convective-scale EPS
did not improve the forecast errors in the GFS forecasts. Therefore,
the perturbations derived from the initial conditions (ICs) of the
global ensemble forecast system (GEFS) were added to the cloud analysis
(with two microphysical schemes) in the convective-scale EPS. One
control run and 14 perturbed members were generated by the EPS, forced
by randomly selected 14 GEFS members as lateral boundary conditions
(BCs). Short-range (3 h or 24 h) ensemble precipitation forecasts were
evaluated for one month, including several heavy precipitation events.
In general, the convective-scale EPS provides skillful precipitation
forecasts over the Yangtze-Huaihe river basin, in terms of rainfall
location and intensity. Cloud analysis is a critical factor to improve
0-12 h forecasts, especially for strong convective events. Combination
of IC perturbations from the large-scale EPS and multiple physical
schemes improves the spread-skill relationship of ensemble
precipitation forecasts, by mitigating the underdispersion and forecast
errors in the convective-scale EPS. The improvements of cloud analysis
(such as assimilation of satellite information) and convective-scale
IC/BC perturbations need further investigations.