Transcript DAOS report to WWRP/JSC 21-25 Feb 2011 Roger Saunders and Pierre Gauthier.

DAOS report to WWRP/JSC
21-25 Feb 2011
Roger Saunders and Pierre Gauthier
Overview of DAOS report to JSC
Roger Saunders and Pierre Gauthier
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WG Activities
Update on observations for global NWP
Update on developments in DA
Results from THORPEX campaigns
Paper on targeted observations
Mission statement
The DAOS-WG was established to ensure that THORPEX
contributes to the international efforts to optimise the use of
the current Global Observing System and to the development
of well-founded strategies for the evolution of the GOS to
support NWP primarily for 1 to 14 day weather forecasting.
To achieve its mission the DAOS WG, in collaboration with the
CBS OPAG-IOS:
• Addresses Data Assimilation issues including the development of
improved understanding of the sources and growth of errors in
analyses and forecasts
• Promotes research activities that lead to a better use of observations
and the understanding of their value
• Provides input and guidance for THORPEX regional campaigns for
the deployment of observations to achieve scientific objectives.
Current membership
Pierre Gauthier,
Co-chair
UQAM, Canada
Roger Saunders,
Co-chair
Met Office, UK
Carla Cardinali
ECMWF
Ron Gelaro,
NASA, USA
Tom Hamill
NOAA, USA
Tom Keenan
Rolf Langland
CAWCR, Australia
NRL, USA
Bertrand Calpini
MeteoSwiss, Switzerland
Andrew Lorenc
MetOffice, UK
Florence Rabier
Météo-France
Prof. Bin Wang, Chinese
Academy of Sciences,
China
Michael Tsyroulnikov
HydroMet Centre,
Russia
Chris Velden
Univ WisconsinCIMSS, USA
3rd THORPEX DAOS Working
Group meeting
Université du Québec à Montréal
8-9 July 2010
Montréal (Québec) CANADA
*http://web.sca.uqam.ca/~wgne/DAOS/DAOS3_meeting/
Update on Observations
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E-AMDAR coverage expanding and now water vapour
Use of IASI radiances over cloud shown to be beneficial
Chinese FY-3A MW sounder radiances proven for NWP
Reduced thinning of AMSU-A radiances at ECMWF
Use of Hi-RES AMVs for improved TC forecasts
Continuity of scatterometer (Oceansat-2?) and GPS-RO
data (COSMIC-2) looks hopeful
Polar Communications and Weather Mission in a Molniya
orbit for improved coverage of the northern polar latitudes.
Raman lidar shows vertical profiles of water vapour at very
high time and vertical resolution and can be available 24
hrs a day for high resolution mesoscale models.
Common data format for radar backscatter measurements
E-AMDAR: Network Performance 1.
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E-AMDAR: Network Performance 2.
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E-AMDAR: Network Developments 1.
• 1st Nov 2010 - EZY fleets providing data over UK domain and
selected European airports.
• Software installed on BAW A319 (LCY – SNN – JFK).
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E-AMDAR: WVSS Programme 1.
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US (NOAA): WVSS Programme 1.
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PCW
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AMVs for Sinlaku in NCEP data file for assimilation
(CTL)
Enhanced AMVs from CIMSS
CTL: NCEP cloud winds
CIMSS-6h: CIMSS 6-hourly wind
Track and Intensity Analyses for Sinlaku (32 members)
Enhanced AMVs: Significant improvement in
analyzed position, track and intensity in first 3 days
AMSU-A thinning experiments
This plot shows the density of AMSU-A
channel 9 data for the case of
2008/12/14@00UTC for the different
experiments:
• EXP-HI: global thinning to 0.625o
• EXP: global thinning to 1.25o (i.e. ope)
• EXP-SV: EXP but with SV thinning 0.625o
• EXP-CLI:EXP but with SVcli thinning
0.625o
• EXP-RND: EXP but with random thinning
0.625o
• Target areas occupy same fraction (15%)
of the Southern hemisphere. The SV-based
climatology was derived from the mean
2007 SV-areas
Experiments have been run for JAS08 and
D08JF09 Forecasts from these experiments
have been verified against EXP-HI analyses
EXP-HI
EXP
EXP-SV
EXP-CLI
EXP-RND
Update on Data Assimilation
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Higher resolution
reduced thinning
Observability of structure functions
Move to hybrid 4D-Var systems
EnKF systems also being trialled
Improved background error statistics are key
to make better use of humidity observations
• Adjoint sensitivity tools now implemented at
most global NWP centres. What about
regional/mesoscale?
Campaigns sponsored by
THORPEX
Concordiasi: an international project
Participating Institutes:
CNES, CNRS/INSU (LMD, LGGE, LA), Météo-France, NSF, Alfred
Wegener Institute, Met Office, Purdue University, UCAR,
University of Colorado, University of Wyoming, BSRN
Polar institutes: IPEV, PNRA, USAP, BAS, ECMWF
Collaborating institutes:
NWP centres (Australia…), NASA/GMAO, UCLA, ….
Part of the THORPEX-cluster
Overview of Concordiasi: “The Concordiasi project in Antarctica”
Rabier et al, Bulletin of the American Meteorological Society, January 2010.
Website: www.cnrm.meteo.fr/concordiasi/
CONCORDIASI
• In September and October 2010, 19
balloons were deployed from McMurdo, 6
with a scientific payload sounding the
stratosphere, and 13 of the driftsonde
type. From the 13 driftsondes, around 640
dropsondes were dropped over Antarctica
and the surrounding seas. Most of these
were transmitted in real-time on the Global
Telecommunication System, for use by the
Numerical Weather Prediction centres.
Balloon tracks
Dropsonde coverage
Concordiasi: Sep 2010 Dropsonde
Data
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39 reports up to
21Z 30/9/2010
37 assimilated.
Wind: Similar
bias/rms to
Antarctic sondes.
Temp: ~+0.5 K
bias above
600hPa. ~-1.0K
bias near surface
(few reports
rejected).
Humidity: 11/37
reports rejected.
Not RS92 so data
<-40C not used.
Assimilation of surface sensitive observations from AMSU over land:
Impact on humidity analyses
Impact studies with 2 versions of ARPEGE: CY32 and CY33 during summer 2006. CY33 introduces
important changes in the physics. Data assimilation is identical between the two versions and takes
advantage of better description of the land surface emissivity to assimilate the observations near the
surface (Karbou et al. 2006-2010ab).
TCWV (EXP-CTL), CY32,
August 2006
TCWV (EXP-CTL), CY33,
August 2006
Similar humidity bias features
were noticed with the assimilation
of MERIS observations over land
(Bauer, 2009) and AMSU
observations in IFS
More moisture in EXP
F. Karbou
HyMeX: 2 types of balloons will be used in 2012-2013
BAMED project (CNES)
Alex Doerenbecher, Clement Fesquet, Claude Basdevant
The intercomparison experiment on the impact
of observations
 A goal of THORPEX is to improve our understanding of the
‘value’ of observations provided by the current global network
• optimize the use of current observations
• inform the design/deployment of new obs systems
 In 2007, DAOS-WG proposed a comparison of observation
impacts in several forecast systems, facilitated by the
emergence of new (adjoint-based) techniques
 Experiments for a baseline observation set were designed by
DAOS members from NRL, GMAO, EC, ECMWF, Météo-France
…so far, results obtained for 3 systems: NRL, EC, GMAO
Daily average observation impacts
Global domain: 00+06 UTC assimilations Jan 2007
NRL NOGAPS
GMAO GEOS-5
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EC GDPS
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AMSU-A, Raob, Satwind
and Aircraft have largest
impact in all systems
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24h Observation Impacts in GEOS-5
Average values at 00z for the period 01 Sep – 31 Dec 2010
Global
Southern
Hemisphere
Northern
Hemisphere
Tropics
JANUARY 2009
Petropavlosk
Circled stations provided
ten or more profiles
1x10-3 J kg-1 (Moist Total Energy Norm)
Error Reduction
Error Increase
Total # of targeted radiosonde data = 27,508 (06UTC and 18UTC)
Number of targeted radiosonde profiles = 247 (33 stations provided at least one profile)
Total targeted radiosonde impact = -0.4322 J kg-1
For comparison: 00UTC and 12UTC observations from these same stations: -4.24 J kg-1 and 2,154 profiles
during all of January 2009
FEBRUARY 2009
TARGETED DROPSONDE IMPACT ON 24H FORECAST ERROR IN NOGAPS/NAVDAS
Impact summed in 2x2 lat/lon boxes
1x10-3 J kg-1 (Moist Total Energy Norm)
Error Reduction
Error Increase
Total # of assimilated dropsonde data = 32,172 (T, q, u, v at all levels)
Number of dropsonde profiles = 355
Total dropsonde impact = -0.7176 J kg-1
Average impact per dropsonde observation = -2.23x10-5 J kg-1
ALL Lufthansa AMDAR
January 2009 – all analysis times
Impact summed in 2x2 lat/lon boxes
1x10-3 J kg-1 (Moist Total Energy Norm)
Error Reduction
EAMDAR Summary
Impact
Error Increase
#of observations
Level Flight
- 3.618 J kg-1
337,506
+ 3% from Dec 2008
Ascent Profiles
- 1.891 J kg-1
79,850
+ 19% from Dec 2008
Descent Profiles
-1.003 J kg-1
33,301
+ 64% from Dec 2008
Summary of intercomparison
 Comparison experiments for GMAO, NRL and EC systems completed for
baseline set of observations and now UKMO added
 Despite differences in assimilation methodologies, overall quantitative
results similar for all systems; but details of impact differ (e.g., impact-perob, channels)
 Largest impacts provided by AMSU-A and raobs (GMAO, UKMO), AMSU-A
and satwinds (NRL, EC); aircraft also has large impact in all systems
 Common problem areas with AMSU-A noted; handling of surface properties
a likely cause
 First paper of adjoint impact intercomparison facilitated by DAOS WG has
been published (Gelaro et al. 2010)
DAOS-WG draft statement on need
for additional in-situ observations
There is increasing evidence based upon results from ATREC, TPARC, AMMA (in the form of OSEs, adjointbased observation impact studies, and analysis
uncertainty estimates) to recommend, if feasible,
increases in observations from:
• Commercial aircraft over the N. Pacific, N. Atlantic, and
the S. Hemisphere in general.
• Additional soundings from certain coastal radiosondes,
including those in eastern Siberia, and perhaps selected
stations in polar regions, Africa, and South America.
to improve NWP forecasts in the 2-5 day timeframe.
Review of the impact of targeted data
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Community paper being written
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Lead author is Sharan Majumdar with contributions from the
DAOS-WG and scientists involved in targeting campaigns
(including Y. Song and Z. Toth)
Reconcile seemingly opposing views on the impact
of targeted data
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Summary of results obtained so far
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Identify issues that need to be addressed to improve the use
of observations that impact weather forecasts (e.g., metrics,
assimilation methods, sampling of precursors to dynamic
instability)
The
targeting
procedure
A. Doerenbecher,
Météo France
Field Campaigns: pre-THORPEX /
independent campaigns
• 1982-96: NOAA Hurricane
Synoptic Flow
• 1997-present: NOAA Hurricane
Synoptic Surveillance
• 2003-present: DOTSTAR Typhoon
Surveillance
• 1997: FASTEX
• 1998: NORPEX
• 1999-present: NOAA
Winter Storm
Reconnaissance
(WSR)
Field Campaigns: THORPEX era
• 2003: A-TReC. Atlantic, minimal impact.
(Forecasts very good without targeted obs)
• 2006-9: European Experiments with a small
targeting component: AMMA-THORPEX, COPS/ETReC, GFDex, DTS-MEDEX, THORPEX-IPY
• 2008: Summer T-PARC
• 2009: Winter T-PARC
• 2010 and future: Concordiasi, HYMEX, TNAWDEX (THORPEX PDP)
EURORISK PREVIEW helped facilitate coordination
Winter T-PARC case
Y. Song, NOAA/NCEP
Summer T-PARC: effectiveness of targeted
obs depends on model/DA
GFS typhoon forecasts, lead time: 24-120 h
JMA, lead time: 0-84 h
800
300
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250
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150
15
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10
20
500
400
15
300
10
200
100
mean track forecast error (km)
JMA GSM
600
0
30
NCEP GFS
700
mean track forecast error (km)
30
5
50
0
120
0
5
no mean improvement?
JMA NoDrop
GFS NoDrop
GFS Drop
24
36
48
60
72
84
forecast lead time (h)
96
108
JMA Drop
track error reduced by up to 200km!
0
12
24
36
48
forecast lead time (h)
60
0
84
72
ECMWF and GFS typhoon forecasts, lead time: 24-120 h
700
30
WRF, lead time: 0-72 h
ECMWF
450
600
mean track forecast error (km)
KMA WRF
400
mean track forecast error (km)
350
300
250
200
150
100
500
20
400
15
300
10
200
improvement after 72 h
5
100
WRF NoDrop
WRF Drop
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0
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0
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24
36
48
forecast lead time (h)
60
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EC NoDrop
EC Drop
24
36
72
Period: 2008090900-2008091812 and 2008092412-2008092900
48
60
72
84
forecast lead time (h)
96
108
0
120
M. Weissmann, DLR
Conclusions 1
• Extratropical: average value of targeted data (mostly
from aircraft) is positive but small.
– Still a lack of strong consensus, limited evaluations
– Results may depend on choice of verification metric
• Tropical cyclones: significant benefits sampling
around the storm; results depend on model.
• Most evaluations for short-range (1-3 day) forecasts.
Smaller sample for medium-range; results promising
in some cases, neutral in others.
Conclusions 2
• Targeting techniques that identify ‘sensitive’ areas
sometimes agree, sometimes disagree, but are not
thought to be the first-order problem.
– Targeting in sensitive areas is better than at random
– Target areas are often in cloudy areas and/or baroclinic
zones
• Results from the adjoint-based observation impact
calculations can be used to explain why we cannot
consistently get large impacts from a few targeted
observations.
– Benefit of aircraft data per observation is large, but
cumulative benefit is small.
Recommendations
• Seek to further optimize existing resources:
commercial aircraft, rawinsonde network, satellite
radiances, atmospheric motion vectors
• Account for data assimilation scheme in targeting
strategy; quantitatively predict effects of obs
• Further evaluations with common cases and multiple
models/DA would strengthen conclusions
• Targeting for longer-range f/casts is interesting topic,
but results are not mature enough to make an
authoritative statement. Broader-scale regime-based
targeting seems the most promising approach.
Targeted Observations for
Improving Numerical Weather
Prediction: An Overview
S. J. Majumdar (RSMAS/U. Miami)
R. Saunders, P. Gauthier (DAOS WG Co-Chairs)
S. Aberson, C. Bishop, C. Cardinali, J. Caughey, A.
Doerenbecher, R. Gelaro, T. Hamill, R. Langland, A. Lorenc,
T. Nakazawa, F. Rabier, C. Reynolds, Y. Song, Z. Toth, C.
Velden, M. Weissmann, C.-C. Wu plus contributions from
past and present DAOS WG members
Manuscript in preparation for WMO Report and BAMS