Transcript Intercomparison of sensitivity to observations in the context of THORPEX and the THORPEX Pacific-Asia regional campaign (T-PARC) Pierre Gauthier Department of Earth and Atmospheric Sciences Université.

Intercomparison of sensitivity to
observations in the context of THORPEX
and the THORPEX Pacific-Asia regional
campaign (T-PARC)
Pierre Gauthier
Department of Earth and Atmospheric Sciences
Université du Québec à Montréal
Contributions from Carla Cardinali (ECMWF), Ron Gelaro (GMAO),
Rolf Langland (NRL), Pat Harr (NPS),
Florence Rabier and Gérald Desroziers (Météo-France)
Stéphane Laroche and Simon Pellerin (Environment Canada)
Observation Impact Workshop, Geneva, 19-21 May 2008
Introduction
• The THORPEX data assimilation and observation
strategies working group (DAOS-WG)
• Intercomparison experiment on observation impact
• The Pacific-Asia Regional Campaign (T-PARC)
• Evaluating the impact of observations collected
during the T-PARC
– The value of targeted data
• Perspectives
Observation Impact Workshop, Geneva, 19-21 May 2008
Objectives of THORPEX DAOS-WG
• Impact of observations
– Guidance for observation campaigns and the
configuration of the Global Observing system
– Evaluation of observation impact with different
systems
– Assessment of the value of targeted observations
– Intercomparison experiment in the context of the TPARC campaign
• Improving the use of satellite data
– Use of sensitivity information to do adaptive data
thinning
– Related to the use of flow dependent background
error covariances
– OSSEs
Observation Impact Workshop, Geneva, 19-21 May 2008
The observation impact
intercomparison experiment
• Baseline experiment
– Common set of observations assimilated by all centres
– Assimilation and model configurations
– Metrics to measure the impact of observations
• Selection of period
– Winter phase of the T-PARC: December 2008 to
February 2009
– Period selected: January 2007
• observations available were closer to what would be available
during T-PARC
Observation Impact Workshop, Geneva, 19-21 May 2008
Observations assimilated by NRL, GMAO
and ECMWF
(also at Météo-France and Environment Canada)
• Radiosondes
• Dropsondes
• Land surface stations (all data except winds and
humidity)
• Ship surface (winds and ps)
• Aircraft (all data except humidity)
• AMV from geostationary satellites (no rapid-scan winds)
• MODIS winds
• AMSU-A radiances
• QuikScat
Observation Impact Workshop, Geneva, 19-21 May 2008
Comparison of the characteristics of
the systems
Analysis
NRL
T239L30
3D-Var
GMAO
0.5ºx0.67ºL72
3D-Var
ECMWF
T255L60
12-h 4D-Var
0.5ºx0.67º L72
Forecasts
T239L30
(Finite Volume model)
Observation Impact Workshop, Geneva, 19-21 May 2008
T255L60
Adjoint of Assimilation Equation
Baker and Daley 2000 (QJRMS)
7
Sensitivity to Observations:
J
J
T
1
 [HPb H  R ] HPb
y
xa
KT
Adjoint of forecast
model produces
sensitivity to x
a
Sensitivity to Background:
J
J
T J

H
x b xa
y
Observation Impact Workshop, Geneva, 19-21 May 2008
Observation Impact Methodology
(Langland and Baker, 2004)
OBSERVATIONS
ASSIMILATED
e30
e24
e24  e30
00UTC
8
+ 24h
Observations move the model state from the “background” trajectory
to the new “analysis” trajectory
The difference in forecast error norms, e24  e30 , is due to the
combined impact of all observations assimilated at 00UTC
Observation Impact Workshop, Geneva, 19-21 May 2008
Evaluation of the impact of
observations
• Measure of the reduction in forecast error
eab  J a t   J b t 
1
1
 x a  x t , x a  x t t  t T  x b  x t , x b  x t
0
2
2
J a J b
1

x a  xb ,

2
x a x b t t T
0
• Evaluation at the initial time
eab
T T
x b ,K  L a
 y  H


J a
T J b 

 Lb
x a
x b 
Observation Impact Workshop, Geneva, 19-21 May 2008
t  t 0 T
Sensitivity with respect to analysis
• Configuration of the measure of forecast
error
– Departure with respect to a verifying analysis (each
centre uses its own)
– Dry adjoint model
– 24h (third order) sensitivity gradient (LB04), dry
forecast error norm, from surface to 150hPa
• Forecast Sensitivity to Observation
– impact at 0,6,12,18 (3D-Var or 4D-Var 6h) or 00, 12
(4D-Var 12 h)
Observation Impact Workshop, Geneva, 19-21 May 2008
Total observation impact at 00 UTC
ECMWF 24h Obs Impact Jan2007 00UTC
Ships
SatWind
RaobDsnd
Qscat
MODIS
LandSfc
Aircraft
AMSU-A
-300
-250
-200
-150
-100
-50
0
50
100
Total observation impact at 12 UTC
ECMWF 24h Obs Impact Jan2007 12UTC
Ships
SatWind
RaobDsnd
Qscat
MODIS
LandSfc
Aircraft
AMSU-A
-300
-250
-200
-150
-100
-50
0
50
100
Observation count
ECMWF 24 h Obs Number Jan2007 12 UTC
ECMWF 24 h Obs Number Jan2007 00UTC
Ships
Ships
SatWind
SatWind
RaobDsnd
RaobDsnd
Qscat
Qscat
MODIS
MODIS
LandSfc
LandSfc
Aircraft
Aircraft
AMSU-A
AMSU-A
0
0.2
0.4
0.6
0.8
x107
1
1.2
1.4
0
0.2
0.4
0.6
0.8
x107
1
1.2
1.4
Impact per observation
ECMWF
ECMWF24
24hhImpact
Impactper
perobs
ObsJan2007
Jan200712
00UTC
UTC
Ships
Ships
SatWind
SatWind
RaobDsnd
RaobDsnd
Qscat
Qscat
MODIS
MODIS
LandSfc
LandSfc
Aircraft
Aircraft
AMSU-A
AMSU-A
-550
-550
-450
-450
-350
-350
-250
-250
-150
-150
Observation Impact Workshop, Geneva, 19-21 May 2008
-50
-50
50
50
X10-6
NAVDAS-NOGAPS
Percent of observations that produce forecast error
reduction (e24 – e30 < 0)
Other approaches to evaluate the
impact of observations
• OSEs
• Information content and the degrees of
freedom per signal (DFS)
– DFS = tr (AB-1)
– Reduction of analysis error
Observation Impact Workshop, Geneva, 19-21 May 2008
Observation Forecast Sensitivity Intercomparison
(J/kg Dry norm - LB4 SG 0-150 hPa)
and Observation Analysis Sensitivity
(10-6)
ECMWF 24 h Impact per Obs Jan2007 00 UTC
Relative Mean Influence %
Ships
Ships
SatWind
SatWind
RaobDsnd
RaobDsnd
Qscat
Qscat
MODIS
MODIS
LandSfc
LandSfc
Aircraft
Aircraft
AMSU-A
AMSU-A
0
5
10
15
20
25
30
-550
-450
-350
-250
-150
-50
DFS %
Ships
SatWind
RaobDsnd
Qscat
MODIS
LandSfc
Aircraft
AMSU-A
0
5
10
15
20
25
WMO Observation Impact Geneva May 2008
30
slide 17
ECMWF
50
Preliminary conclusions
• Numerous differences between the systems remain
– Baseline experiment provided a common context against which
three different systems evaluated the impact of observations with
the same method
– Differences persist in terms of assimilation methodologies and
models (e.g., 3D-Var and 4D-Var)
– The impact of observations differs from one system to another
– For each system, the total impact of observations evaluated with
the LB04 method is consistent with results from OSEs.
• Further experimentation with different approaches
– Ensemble methods (Météo-France)
– Encourage other centres to participate
Observation Impact Workshop, Geneva, 19-21 May 2008
THORPEX Pacific Asian Regional
Campaign (T-PARC)
David Parsons
Co-chair ,North American THORPEX Regional Committee
Contributions from Tetsuo Nakazawa, Dehui Chen, Pat Harr,
Istvan Szunyogh, Anna Agusti-Panareda, Sarah Jones, Martin
Weismann, Carla Cardinali, etc…
North American Region
What is
happening
in this region?
BC’s flood of the
Century (18.5”)
Western WA
Flood (Seattle
1-day record)
CA Wild Fires
(downslope winds)
North American Region
Major scientific issues for T-PARC
• Tropical cyclogenesis
– Better understand the large-scale influences on cyclogenesis
and their relation to cyclone structure
– To examine the predictability of cyclogenesis and develop
strategies to improve forecast skill
– To examine the evolution and the role of convection during
cyclogenesis
• Recurvature
– To understand dynamic/thermodynamic environmental fields
which affect TC recurvature
– To better understand ensemble spread and improve the
utilization of ensemble information in disaster mitigation
– To develop, refine typhoon targeting capabilities with the goal of
improving regional and downstream predictions
Major scientific issues for T-PARC
• Extra-Tropical transition
– Factors limiting the regional and global predictability of the
interaction between the tropical cyclone and the mid-latitude flow
– Structural changes in the tropical cyclone core during the ET
process and how these changes are related to the evolution of the
distribution of precipitation
– to develop and test observational, assimilation and modeling
strategies to improve local and downstream predictive skill for ET
events
• Winter storms
– to develop and test new adaptive observation strategies for winter
systems that overcome the current limitations of aircraft targeting
– to better understand and predict Rossby wave triggering and
enhancement in the Pacific wave guides
– to extend the adaptive use of in-situ and satellite observations to
medium range prediction
Proposing Institutions
• North America
– US Academic Community: SUNY at Stony Brook, U. of Hawaii, Naval Post
Graduate School, U. of North Carolina Charlotte, Pen. State, U. of Washington, U
of Maryland, SUNY Albany, U of Miami, U of Wisconsin, Florida State U
– US Research Institutions: NCAR, NOAA/NCEP, NOAA/NWS, Naval Research
Lab, NASA/Goddard
– Canada: Environment Canada
• Asia
– China: Chinese Academy of Meteorological Sciences, Chinese Meteorological
Administration plus members of the Academic Community in China
– Japan: Japan Meteorological Agency, Japan Marine Science and Technology Center
(JAMSTEC), Kyoto U, Nagoya U, Tohoku U, Tsukuba U, U of Tokyo
– Korea: Korean Meteorological Administration, Cheju National U, Ehwa Womans
U, Kongju National U, Kyungpook National U, Seoul National U,Yonsei
– Collaboration with an expanded DOTSTAR program
• Europe
– Germany: U of Karlrsuhe, Institut für Physik der Atmosphäre, DLR,
– Others (ECMWF and National Met Centers)
T-PARC and Observing
System/Observing Strategies Research
• Typhoon genesis
– Relevant science
• Impact of assimilating new type of measurements on typhoon
genesis (radar reflectivity, winds in clear air and clouds,
synoptic style in-situ obs vs dropsondes, rapid scan satellite
obs)
• Evaluation of initial condition and model error in genesis
regions
• Advancing knowledge of the genesis process and the factors
limiting predictive skill
– Instruments
• NRL P-3 with ELDORA Doppler radar, dropsondes, ocean
SST and (perhaps) a Doppler lidar for mesoscale (US)
• Driftsonde and tropical island radiosonde sites for large-scale
for 2007 and 2008 (proposed China, France, and US)
T-PARC and Observing
System/Observing Strategies Research
• Typhoon landfall and recurvature
– Instruments
• NRL P-3 with ELDORA Doppler radar, dropsondes, ocean
SST and (perhaps) a Doppler lidar for mesoscale (US)
• DLR Falcon with Doppler lidar, water vapor lidar and
dropsondes
• Dropsonde aircraft (China, DOTSTAR, Japan, Korea?)
• Driftsonde for 2007 and 2008 (proposed China, France, US)
• Coordination of Chinese IOPs over land: SCHeREX-“973”
basic research project; Tibet-Est surrounding Exp., 4 MeTebs
of LaSW (Guangzhou, Wuhan, Anhui and Shanghai)
• Rapid scan MTSAT satellite observations
• Collaboration with extended DOTSTAR program (dropsonde
aircraft and driftsonde)
T-PARC and Observing
System/Observing Strategies Research
• Extra-Tropical transition
– Relevant science
• Advance understanding and test the regional and
downstream impacts of targeted measurements
(typhoon vs middle latitude) by in-situ and satellite
measurements
• Impacts of future remote sensing strategies from
space (winds, water vapor, radars with frequent
updates)
• Understanding the factors that limit predictability
General Decrease in Forecast Skill for ET Storms
Forecast Skill Bifurcation
ET Tracks
From Jones et al., 2003: Wea. And Forecasting
T-PARC and Observing
System/Observing Strategies Research
• Winter phase
– Instruments
• Upgraded and enhanced Russian radiosonde network and
continuation of some Chinese land-based sounding
enhancements (Tibetan Plateau)
• US NOAA G-IV with dropsondes (western Pacific)
• Air Force C-130’s with dropsondes (central Pacific)
• NOAA P-3 or other assets in the eastern Pacific
• NOAA and NASA satellites
• Relevant science
• Value of sensitivity information for targeting and adaptive
data selection strategies
• Led by Zoltan Toth
Summary and conclusion (1)
• New approaches are being investigated to evaluate the
impact of observations on the quality of forecasts
– Forecast sensitivity to observations
• Adjoint based approaches
• Ensemble methods (e.g., ETKF)
• DFS and information content
– Objective is to obtain robust and reliable methods to evaluate the
impact of observations on the quality of weather forecasts
• Intercomparison experiment
– Numerous components are involved associated with model,
observations, assimilation methods and flow regimes
– Intercomparison experiment has value in that it reduces several
of the differences to bring the systems on a common ground
(e.g., observations used, flow regimes, resolution)
– Calibration of assimilation systems raises some questions about
the value of ‘degrading’ a system in that context
Summary and conclusion (2)
• Value of data deployed during T-PARC
– Experiment aims at capturing the different stages of Tropical
cyclones from their genesis to their migration into northern
latitudes
– Value of data over the Pacific for the short to medium-range
forecasts over Asia and North America
– Meteorological high-impact events in Asia and North America
• Data assimilation objectives
– Assess the impact of observations on deterministic and
probabilistic forecasts
– Targeting techniques and adaptive satellite data assimilation
– Large sets of data will be made available that could be used to
better use satellite data in those situations
Thank you
Other objectives
• Research on model error modeling and estimation
– Considered to be a necessity for model of increasing resolution,
convection, cloud representation
• ECMWF: weak-constraint 4D-Var with long assimilation windows
– Biases need to be addressed too
– Explore possibilities of using TIGGE framework to estimate model and
background error characteristics
• Observation error correlation
– Design of observation campaign to estimate observation error statistics
– Identify existing Cal/Val campaigns with similar objectives (in
collaboration with the Obs WG)
– Make it known what exactly the assimilation needs in terms of
observation error characteristization
• Data assimilation in the Tropics
– THORPEX and AMMA
Observation Impact Workshop, Geneva, 19-21 May 2008