Transcript 投影片 1 - World Weather

Sixth International Workshop on
Tropical Cyclones
Topic 3.3: Targeted observations and
data assimilation in track prediction
Rapporteur:
Chun-Chieh Wu
PSA
Working Group: Sim Aberson, Brian Etherton,
Sharanya J. Majumdar, Seon Park, Melinda S. Peng,
Zhaoxia Pu, Michael Morgan, Steve Tracton, Samuel
Westrelin, and Munehiko Yamaguchi
Outline
Introduction
 Surveillance programs using the
dropwindsondes
 Targeted observations for tropical cyclones
 Comparison of targeted observing methods
 Other data to be targeted and assimilated
 Issues and concerns
 Recommendations

Improving the understanding
and forecasting of TCs
Dynamics of the
typhoon system
Cost effective?
Initial condition
Dynamics of
the model
New
Observation
Multi-scale interaction
Data assimilation
and/or Initialization
Air-sea interaction
Terrain/PBL effect
Introduction
• Accurate forecast of tropical cyclones
– Realistic numerical models
– Accurate representation of meteorological fields
• Observation data
– Surface observations, soundings, and ships
– Dropwindsonde data
– Satellite data
– Radar data
• Data assimilation
Surveillance programs using
the Dropwindsondes
• The impact of dropwindsonde data
– Between 1982 and 1996, the HRD conducted 20
“synoptic flow” experiments.
• Burpee et al. (1996)
– The average error reductions in the consensus
forecasts from three dynamical models varied from
16% to 30%.
Dropwindsondes
• In 1997, the HRD began operational synoptic
surveillance mission with the G-IV jet aircraft.
• Aberson and Franklin
(1999)
– The dropwindsonde
observations
improved the mean
track forecasts of the
GFDL model by as
much as 32%.
No drop
with drop
Dropwindsondes
• Aberson (2002)
– The additional dropwindsonde data from the
synoptic surveillance missions provided
statistically significant improvements in the GFDL
forecast only at 12 h.
• TC vortex initialization schemes
• The amount of data coverage
• Aberson (2003) and ongoing…
– The improvement through targeted observations
DOTSTAR (Dropwindsonde Observations of
Typhoon Surveillance near the Taiwan Region)
6
9
69
Astra jet of AIDC
(Wu et al. 2005a, BAMS)
JMA,
UKMO,
….
DOTSTAR observations
Up to 2006, 24 missions have been
conducted in DOTSTAR for 20 typhoons,
with 386 dropsondes deployed during
the 129 flight hours.
18 typhoons affecting Taiwan
8 typhoons affecting mainland China
4 typhoons affecting Japan
2 typhoons affecting Korea
5 typhoons affecting Philippines
20. Bilis
21. Kaemi
22. Bopha
23. Saomai
24. Shanshan
The impact of DOTSTAR data on global
models in 2004
Melinda
Peng
Sim
Aberson
NCEP GFS : 14%
NOGAPS : 14%
JMA GSM : 19%
ENSEMBLE : 22%
Tetsuo
Nakazawa
(Wu et al. 2006a, WF)
Background on targeted
observations
• Adaptive observations : observations targeted in
sensitive regions can reduce the initial condition’s
uncertainties, and thus decrease forecast error.
• Targeted observation is an active research topic in NWP,
with plans for field programs, tests of new observing
systems, and application of new concepts in predictability
and data assimilation. (Langland 2005)
• Factors associated with adaptive observations
- Observation density, variables and errors
- Magnitude of uncertainty
- Data assimilation system
- Growth of uncertainty
Adaptive observation strategies
• Dynamics-based strategy
SV, adjoint sensitivity, and PV.
• Uncertainty-based strategy.
Ensemble variance
• Joint dynamics-uncertainty based strategy.
The ideal one would be the strategy that use
both of dynamics and uncertainty information
(e.g., ETKF, VARSV).
(Since 1997, developed for mid-lat, FASTEX)
• Since 2003, several objective methods, have been
proposed and tested for operational surveillance
missions in the environment of Atlantic hurricanes
conducted by HRD/NOAA (Aberson 2003) and NW
Pacific typhoons by DOTSTAR (Wu et al. 2005).
(Aberson 2003, MWR)
– NCEP/GFS ensemble variance
(collaborating with Aberson)
(Majumdar et al. 2006, MWR)
– ETKF
(collaborating with Majumdar)
– NOGAPS Singular Vector (Peng and Reynolds 2006, JAS)
(collaborating with Reynolds and Peng)
– Adjoint-Derived Sensitivity Steering Vector (ADSSV)
– JMA moist Singular Vector
(Wu et al. 2006b, JAS)
(collaborating with Yamaguchi)
Comparison of targeted observations in DOTSTAR
Ensemble Variances,
Toth and Kalnay (1993)
FNMOC SV, Palmer et al. (1998)
ETKF, Bishop and
Majumdar (2001)
ADSSV, Wu et al. (2006)
• DOTSTAR
(Wu et al. 2006b)
•G-IV surveillance
Comparison of
targeted techniques
(Etherton et al. 2006)
Maumdar et al. 2006
Reynolds et al. 2006 More comprehensive comparisons are ongoing.
How the dropsonde data improve the forecast?
Typhoon Conson (2004) as an example
(Nakazawa 2004, THORPEX meting)
JMA-GSM
Typhoon Conson (2004)
8 June 1200UTC
Evaluate a SV method as a strategy for Targeting Observation
JMA has executed Observing System Experiments (OSEs) to investigate the usefulness of the
singular vector method as a strategy for sensitive analysis.
For the initial time of 12UTC 08 June 2004 when totally 16 dropsondes were dropped into
typhoon CONSON by the DOTSTAR (Dropsonde Observation for Typhoon Surveillance
near the Taiwan Region) project, 4 predictions with JMA Global Spectral Model
(TL319L40) about the use of the dropsondes in the global 4D-Var analysis are executed.
(I)
all dropsonde observations are used for making the initial condition
(II) dropsondes are not used at all
(From Yamaguchi)
(III) only 3 data within a sensitive region are used (4, 9, 12)
(IV) only data outside of a sensitive region are used (6, 8, 10, 13, 15, 16)
Sensitive analysis result
The distribution means
vertically accumulated total
energy by the 1st moist
singular vector.
Targeted area for the SV
calculation is N25-N30,
E120-E130.
x
CONSON’s center position
Optimization time
interval is 24 hours.
OSEs result on CONSON’s track forecast
Red: (I) all dropsonde observations are used for
making the initial condition
Blue: (II) dropsondes are not used at all
Green: (III) only 3 data within a sensitive region are
used (4, 9, 12)
Water: (IV) only data outside of a sensitive region are
used (6, 8, 10, 13, 15, 16)
(From Yamaguchi)
(III)
(I)
similar
(IV)
(II) is almost same with (IV)
Other data to be targeted
and assimilated
• Observations for data assimilation
– To date, “Targeted” observations for TCs are mainly
dropwindsondes deployed from the aircraft.
– There is considerable scope for extending targeted
observing strategies to include other types of data,
most prominently from satellites.
• GOES (Zou et al. 2001) and TRMM (Pu et al. 2004)
• Microwave radiances (Bauer et al. 2006a, b).
– The collection of satellite and in-situ data from field
programs (e.g. CAMEX-4, Kamineni et al. 2006) with
different spatial and temporal resolutions and error
characteristics (Fisher 2003; Berre et al 2006, Westrelin et al
2006) will continue to play a very important role in
improving tropical cyclone track forecasts.
Other data o be targeted
and assimialted
– Questions more specific to targeted observations can
be addressed over the next decade:
• Given the abundance of satellite data that will be
available for assimilation, what subsets of the data
are the most necessary for assimilation to improve
the tropical cyclone forecast? (satellite data
thinning)
• What are the optimal variables, three-dimensional
structures, and spatial and temporal density that are
necessary for observation?
Issues of concerns (Langland 2005 and THORPEX)
• Although the impact of observations is greater when
selected in a sensitive area, the few observations
deployed may not make a substantial impact on the
forecasts.
• The statistical evaluation of the significance of the
measured impact requires a large number of cases.
• Current diagnostics used to evaluate forecasts provides
a good assessment of the validity of forecasts (skill), but
it may not be sufficient to reveal whether these
improvements are relevant to applications (value).
• The use of climatological sensitivities may lead to
improvements on average and be more cost effective
than targeted observations on demand.
• Overall, there was a considerable question as to the
value of targeting, especially when isolated from the
more general issues of observing system sensitivities in
design of an “optimal” mix of available observing
platforms.
Recommendation
•
•
•
•
•
•
•
Need to assess the influence of the data assimilation scheme
on the effectiveness of targeted observations.
More studies of varying definitions, interpretations, and
significance of sensitive regions (e.g., different methods,
metrics)
More work on sampling strategies in sensitive areas, e.g.,
immediate storm environment for shorter range prediction
versus remote areas relevant to longer range forecasts –
including the impact of large scales in meso-scales models.
More work on metrics to assess the impact of targeting – or
more generally on any changes in the observation network.
Emphasis of the potential value of OSEs and OSSEs in
assessing potential observing system impacts prior to actual
field programs.
Stronger efforts to develop alternative observing platforms
(other than the dropwindsondes) for targeting, especially
adaptively selecting satellite observations by revising the data
thinning algorithms currently used.
Improvement and continuous refinement of targeted
observing strategies.
THORPEX-PARC Experiments and Collaborating Efforts
(from Dave Parsons)
Upgraded Russian
Radiosonde Network for IPY
Winter storms
reconnaissance
and driftsonde
NRL P-3 and
HIAPER with the
DLR Wind Lidar
JAMSTEC/IORG
G