Effect of Doppler radial Velocity data assimilation on the simulation of a typhoon
approaching Taiwan
Hsin-Hung Lin, Pay-Liam LinNational Central University, Taiwan
Wu and Kuo (1999) pointed out that the major problems of typhoon prediction in Taiwan are caused by: 1) inadequate observations 2) insufficient model resolution 3) the complicated influence of the CMR on airflow
Mesoscale precipitation patterns induced by typhoon circulation over complicated terrain are difficult to predict. Radar wind data assimilations are used to study possible improvements to this problem.
In this study, the potential improvement of short-term typhoon predictions near Taiwan, particularly the related rainfall forecasts over the mountainous island, using Doppler radial wind observations is explored.
Typhoon Case• 2004/8/24-25 Typhoon Aere• 15-hr maximum accumulated rainfall is 760 mm
Experiment Design• MM5 and 3D-VAR• 3 Nesting Domain • model resolutions are 45, 15 and 5 km• Assimilate Doppler Radial Velocity and GTS data
Radar Data Number
First 2 cyclesLast 3 cycles
Radar Site at 766 meter height
5 assimilation cycles4 km radar data resolutionMax. 3000-3500 data points in each cycles
fewer data Below 3 km
Radar Data Number at each Height
Typhoon Track
CTL & GTS
DRV & GADCTL &
GTS
The typhoon movement was deflected toward the south during the second assimilation cycle
When Typhoon moved closer to Taiwan, the simulated typhoon positions closer to the observed track.
Typhoon Intensity
CTL & GTS
DRV , GAD, RV3
25.5 hPa
the DRV, GAD and RV3 produced relatively better minimum SLP, implying a positive influence of the radar data assimilation on typhoon intensity.
In comparison with the CTL, the error of the simulated central SLP was reduced by about 25%
Typhoon Aere
CTL
GTS
DRV
GAD
RV3
2004/08/25 0300 UTC
Doppler wind data assimilation made the better simulation results of eye wall and rainband structure
Typhoon Aere
Doppler wind data assimilation led the better rainfall simulation and improve the under-prediction above 5 mm threshold.
TS and BIAS for 3-hr Rainfall at the last assimilation cycle
Sensitivity Test
Case Assimilated data (typical number of data points in domain 3)
SEN-NON NoneSEN-SFC Surface station data (37)SEN-SND Upper air soundings (6)SEN-DRV Doppler radial velocity (3664)SEN-DUR Dual-Radar retrieval wind, resolution 2km(3593)
In order to clarify the individual impact of different observation.
Follow GAD, and assimilate single kind of observation at the last cycle.Dual-Radar retrieval wind was added in addition.
Sensitivity Test
3km radar coverage
Dual-radar wind coverage
Radar Data Number at each Height Doppler Wind
Dual-Radar wind 2km
Dual-Rada wind 4km
Dual-radar wind coverage is smaller than Doppler radial wind and lack data above 6 km
Sensitivity Test
SEN-SFC SEN-SND
SEN-DRV SEN-DUR
Increment of Horizontal Wind of Assimilation Analysis at 700 hPa
Red: positive incrementBlue: negative incrementSEN-DRV and SEN-DUR had stronger cyclonic positive increment
Sensitivity TestThe cross section of u-wind Increment of Analysis
at latitude 24.6SEN-SFC SEN-SND
SEN-DRV SEN-DUR
A
Red: positive incrementBlue: negative increment
Dual-Radar wind increase the low level wind, but decrease high level wind.
Sensitivity Test
SEN-SFC SEN-SND
SEN-DRV SEN-DUR
Red: positive incrementBlue: negative increment
C
The typhoon center cross section of u-wind IncrementSEN-DRV had more symmetric wind structure than SEN-DUR.
Sensitivity Test
SEN-DUR
SEN-DRV
SEN-SND
Compare with Sounding (46715) at the north Taiwan
Low Level Wind Speed
SEN-DUR had the best analysis wind speed
SEN-DRV is secondary
Sensitivity Test
SEN-DURSEN-DRV
SEN-SFCSEN-SND
Simulation Typhoon intensityMinimum Sea Level Pressure
Doppler wind data assimilation descended 3 hpaDual-Radar wind data assimilation descended 2 hPa
Summary• The model predicted fields including sea level pressure,
wind and precipitation were improved with the additional observed wind information through Doppler radial velocity assimilation.
• When the typhoon center moved closer to Taiwan and the whole circulation of the core region could be observed, the typhoon tracks were predicted more correctly with radar data assimilation
• The typhoon intensity also was increased and revised about 25 % errors from non-assimilation simulation.
• The effects of dual-radar retrieval wind leads the best low level wind speed of typhoon over the land by the analysis of data assimilation. The radar radial wind has the more symmetrical adjustment of wind structures than the dual-radar wind.
Thank You