Understanding and PreDiction of Rainfall Associated with … · A Proposal for WWRP/WMO Research...
Transcript of Understanding and PreDiction of Rainfall Associated with … · A Proposal for WWRP/WMO Research...
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Workshop on WMO/WWRP Research and Development Project High Resolution Prediction of Landfalling Typhoon, 16‐18 May 2014,Nanjing, China
Participants: Prof. Johnny Chan Dr. Noel Davidson Dr. Yihong Duan Ms. Nanette Lomarda Dr. Robert Rogers Dr. Yong Wang Prof. Yuan Wang Prof. Yuqing Wang Dr. Hui Yu
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A Proposal for WWRP/WMO Research and Development Project
(RDP)
Understanding and PreDiction of Rainfall Associated with landFalling Tropical
cyclones
(UPDRAFT)
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Aim & Purpose
• Improving the understanding and forecasting on the landfalling typhoon rainfall
– UNDERSTANDING: Basic research
– FORECASTING: Application research
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Objective I
• To identify the deficiencies of state-of-the-art operational numerical models in forecasting landfalling typhoon rainfall
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• Truth sets: Conventional and unconventional observational data of 12 landfalling typhoons from the outcome of the National Basic Research Program of China
• Objective methods: Object-oriented verification techniques, e.g. Method for Diagnostic Evaluation (MODE), Contiguous Rain Area (CRA), etc.
• Quantitative estimations: Errors in rainfall size, location, intensity, distribution pattern, orientation angle, etc.
• Diagnostic verifications: Storm location, interaction with underlying surface, large-scale environment, vortex structure, microphysical processes, etc. (possible sources of rainfall forecasting error)
• Potential results: What is the main weakness in forecasting landfalling typhoon rainfall? How do other factors influence the rainfall prediction?
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Objective II
• To improve the understanding of key physical processes governing landfalling typhoon rainfall – To quantitatively estimate the individual contributions of
potential sources of error
– To investigate how physical processes influence the landfalling typhoon rainfall
– To improve representations of surface forcing, boundary layer, microphysical and radiative processes
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• Strom track – To evaluate the effect of track forecast uncertainty on rainfall
prediction
• Interaction with underlying surface and PBL – To identify suitable drag parameter, flux and turbulence transfer
coefficients used in PBL schemes
– To evaluate the effect of topography
– To test the potential value of LES
• Interaction with environmental features – To evaluate the impact of monsoon flow, vertical wind shear,
midlatitude circulations, etc.
• Vortex structure • To investigate the impact of initial vortex structure on eyewall,
rainbands, convective bursts, etc.
• Convective and microphysical processes – To recommend one or more parameterization schemes capable of
representing the convective and microphysical processes
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Objective III
• To develop an optimum forecasting system for predicting landfalling typhoon rainfall – To improve deterministic and probabilistic forecast
techniques
– To develop new consensus and ensemble forecasts
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Innovation
• 1 Radar net-work + aircraft obs.
• 2 vortex initialization
• 3 vortex spin-down after landfall
• 4 better parameterization schemes
• 5 new consensus rainfall forecast system
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Kompasu (2010) & Lionrock (2010)
Fitow (2013)
Evaluation of tropical cyclone rainfall forecasts
from operational NWP models
(Two case studies)
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Kompasu
Lionrock
Case study - 1
Kompasu (2010) and Lionrock (2010)
Qi L.B. and Cao X.G., 2013
12UTC1Sep2010
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00-06UTC
Rainband in N-S direction
Interaction between
Kompasu and cold air
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06-12UTC
Rainband in W-E direction
Interaction between the northerly
wind of Kompasu and inverted
trough of Lionrock
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All the available operational models failed in predicting this heavy rain
process one day before.
(ECMWF, CMA, JMA, SMB-WARMS)
06-09UTC
09-12UTC
12-15UTC
ECMWF Ini: 12UTC 31 Aug.
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ECMWF Ini. 12UTC31 Aug
Fcst. 12UTC1 Sep 850hPa wind
Small track error (60-80km) leads to the
missing of the two flows
Red:warm and moist air
Blue:dry and cold air
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14-17时
17-20时
20-23时
Rainfall at
Shanghai
ECMWF Ini: 00UTC 1 Sep.
A patch of rainfall is forecast
over Shanghai, but too weak
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SMB-WARMS (WRF, 9km)
MODE products for 24h precipitation
initialized at 00 UTC August 31.
(a) forecast of SMB-WARMS; (b) Observation.
Forecast has a larger
precipitation (>10mm) area
than observation.
The area ratio of forecast
and observation is 1.49.
The distance between the
centroids of forecast and
observed objects is ~70 km
and angle difference of the
axis is only 5.7 degree.
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SMB-WARMS 9km Ini: 00UTC 1 Sep.
6h surface wind and 6-12h precipitation
~100km west to the
observation
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Rainband of
Kompasu
South-easterly
wind of the
inverted trough
Northerly wind
of Kompasu
SMB-WARMS 9km Ini: 00UTC 1 Sep.
12UTC 1 Sep. Surface wind
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Rainband of
Kompasu
SMB-WARMS 9km Ini: 00UTC 1 Sep.
14UTC 1 Sep. Surface wind
Northerly wind
of Kompasu
South-easterly
wind of the
inverted trough
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The predicted shear
line lasts ~ 4 hours.
SMB-WARMS 9km Ini: 00UTC 1 Sep.
15UTC 1 Sep. Surface wind
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SMB-WARMS 9km Ini: 00UTC 1 Sep.
16UTC 1 Sep. Surface wind
The predicted shear
line lasts ~ 4 hours.
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SMB-WARMS 9km Ini: 00UTC 1 Sep.
17UTC 1 Sep. Surface wind
The predicted shear
line lasts ~ 4 hours.
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SMB-WARMS 9km Ini: 00UTC 1 Sep.
18UTC 1 Sep. Surface wind
The predicted shear
line lasts ~ 4 hours.
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Predicted radar reflectivity
09UTC
Rainband related to
the shear line
12UTC
15UTC 18UTC 21UTC
TC position error - error in
‘meeting’ position (west)
and time (late) of the two
flows
Need to predict correctly
the position and intensity
of three TCs.
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Yuyao of Ningbo Shanghai
West Lake after Fitow
Case study - 2
Fitow (2013)
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Observed precipitation
1 Fitow’s rainband
2 Fitow & Danas & frontogenesis
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Courtesy to Mr. Chen Guomin
Regional models
Very good
track forecasts
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Track Error of ACCESS-TC for 1323 "FITOW"
Leading time
12h 24h 36h 48h 60h 72h
Tra
ck
err
or
(km
)
0
100
200
300
400
500Intensity Error of ACCESS-TC for 1323 "FITOW"
Leading time
12h 24h 36h 48h 60h 72h
Inte
nsity e
rro
r (m
/s)
-15
-10
-5
0
5
10
15
20
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ACCESS-TC Ini. 12UTC 5 Oct, 2013
24-48hr before the extreme rainfall event
Base time:
0512Z
Bao X.W., N. Davidson, Yu H., et al. 2014
Red: Forecast
Black: Observation
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18UTC 6
Fitow’s Rainband
Fitow & Danas &
Frontogenesis
18UTC 7
Track of Fitow: to the north of Obs.
Track of Danas: slower than Obs.
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Discussion
Extremely heavy rain events as a result of interactions among
multiple systems (two or three TCs + dry cold air intrusion)
are great challenges for NWP models.
(location & time)