EGU2008-A-10290

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EGU2008-A-10290
Progress in Joint OSSEs - Evaluation of the New
Nature runs. Progress in Simulation of
Observation- http//www.emc.ncep.noaa.gov/research
/JointOSSEs EGU April 2008
NCEP Michiko Masutani, John S. Woollen, Yucheng
Song, Stephen J. Lord, Zoltan Toth ECMWF Erik
Andersson KNMI Ad Stoffelen, Gert-Jan
Marseille JCSDA Lars Peter Riishojgaard
(NASA/GFSC), NESDIS Fuzhong Weng, Tong Zhu
Haibing Sun, SWA G. David Emmitt, Sidney A.
Wood, Steven Greco NASA/GFSC Ron Errico, Oreste
Reale, Runhua Yang, Emily Liu, Joanna Joiner,
Harpar Pryor, Alindo Da Silva, Matt McGill,
NOAA/ESRLTom Schlatter, Yuanfu Xie, Nikki
Prive, Dezso Devenyi, Steve Weygandt MSU/GRI
Valentine Anantharaj, Chris Hill, Pat
Fitzpatrick, JMA Takemasa Miyoshi , Munehiko.
Yamaguchi JAMSTEC Takeshi Enomoto So far most
of the work is done by volunteers.
People who helped or advised Joint OSSEs. Joe
Terry (NASA), K. Fielding (ECMWF), S. Worley
(NCAR), C.-F., Shih (NCAR), Y. Sato (NCEP,JMA),
Lee Cohen(ESRL), David Groff(NCEP), Daryl
Kleist(NCEP), J Purser(NCEP), Bob
Atlas(NOAA/AOML), C. Sun (BOM), M. Hart(NCEP), G.
Gayno(NCEP), W. Ebisuzaki (NCEP), A. Thompkins
(ECMWF), S. Boukabara(NESDIS), John Derber(NCEP),
X. Su (NCEP), R. Treadon(NCEP), P. VanDelst
(NCEP), M Liu(NESDIS), Y Han(NESDIS),
H.Liu(NCEP),M. Hu (ESRL), Chris Velden (SSEC),
George Ohring(JCSDA), Many more people from
NCEP,NESDIS, NASA, ESRL
More people are working on proposal, getting
involved or considering participation. Z.
Pu(Univ. Utah), Lidia Cucil (EMC, JCSDA), G.
Compo(ESRL), Prashant D Sardeshmukh(ESRL), M.-J.
Kim(NESDIS), Jean Pailleux(Meteo France), Roger
Saunders(Met Office), C. OHandley(SWA), E
Kalnay(U.MD), A.Huang (U. Wisc), Craig
Bishop(NRL), Hans Huang(NCAR),
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Need for OSSEs
Benefit of OSSEs

• ? OSSEs help in understanding and formulating
  observational errors
• ? DA (Data Assimilation) system will be prepared
  for the new data
• ? Enable data formatting and handling in advance
  of live instrument
• ? OSSE results also showed that theoretical
  explanations will not be satisfactory when
  designing future observing systems.

?Quantitativelybased decisions on the design and
implementation of future observing systems ?
Evaluate possible future instruments without the
costs of developing, maintaining using
observing systems.
If we cannot simulate observations, how could we
assimilate observations?
Need for collaboration

• Need one good new Nature Run which will be used
  by many OSSEs, including regional data
  assimilation.
• Share the simulated data to compare the OSSE
  results from various DA systems to gain
  confidence in results.
• OSSEs require many experts and require a wide
  range of resources.

Extensive international collaboration within the
Meteorological community is essential for timely
and reliable OSSEs to influence decisions.
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Archive and Distribution
New Nature Run by ECMWF Based on discussion
with JCSDA, NCEP, GMAO, GLA, SIVO, SWA, NESDIS,
ESRL, and ECMWF
To be archived in the MARS system on the THORPEX
server at ECMWF Accessed by external users.
Currently available internally as expveretwu
Copies for US are available to designated users
for research purpose users known to ECMWF
Saved at NCEP, ESRL, and NASA/GSFC Complete data
available from portal at NASA/GSFC ConctactMichik
o Masutani (michiko.masutani_at_noaa.gov),
Harper.Pryor_at_nasa.gov
Low Resolution Nature Run Spectral resolution
T511 Vertical levels L91 3 hourly dump Initial
conditions 12Z May 1st, 2005 Ends at 0Z
Jun 1,2006 Daily SST and ICE provided by
NCEP Model Version cy31r1
Supplemental low resolution regular lat lon data
1degx1deg for T511 NR, 0.5degx0.5deg for T799 NR
Pressure level data 31 levels, Potential
temperature level data 315,330,350,370,530K Selec
ted surface data for T511 NR Convective precip,
Large scale precip,

MSLP,T2m,TD2m, U10,V10, HCC, LCC, MCC, TCC, Sfc
Skin Temp Complete surface data for T799 NR T511
verification data is posted from NCAR CISL
Research Data Archive. Data set ID ds621.0.
Currently NCAR account is required for access.
T799 verification data are available from
NASA/GSFC portal (Contact Harper.Pryor_at_nasa.gov)
(Also available from NCEP hpss, ESRL, NCAR/MMM,
NRL/MRY, Univ. of Utah, JMA,Mississippi State
Univ.)
Two High Resolution Nature Runs 35 days
long Hurricane season Starting at 12z September
27,2005, Convective precipitation over US
starting at 12Z April 10, 2006 T799 resolution,
91 levels, one hourly dump Get initial conditions
from T511 NR
Note This data must not be used for commercial
purposes and re-distribution rights are not
given. User lists are maintained by Michiko
Masutani and ECMWF
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Comparison between the ECMWF T511 Nature Run
against climatology 20050601-20060531, expeskb,
cycle31r1 Adrian Tompkins, ECMWF
NR
TechMemo 452 Tompkins et al. (2004)
ftp//ftp.emc.ncep.noaa.gov/exper/mmasutani/ECMWF
_NR_Diag/Tompkins_ECMWF_T511_diag/tm452.pdf Jung
et al.  (2005) TechMemo 471 http//www.emc.ncep.no
aa.gov/research/osse/NR/ECMWF_T511_diag/tm471.pdf
Plot files are also posted at ftp//ftp.emc.ncep.n
oaa.gov/exper/mmasutani/ECMWF_NR_Diag/Tompkins_ECM
WF_T511_diag The description of the
data ftp//ftp.emc.ncep.noaa.gov/exper/mmasutani/E
CMWF_NR_Diag/Tompkins_ECMWF_T511_diag/climplot_REA
DME.html
Xie Arkin
NR-Xie_Arkin
Cloud Cover
Red NR BlackXie Arkin
NR
- These comparisons confirm the lack of rainfall
over the tropical land masses. - We have an
overestimation of precip over the high-SST
regions in the tropics. - There is a tendency
for deep convection to become locked in with the
highest SSTs, which in the east Pacific results
in a narrow ITCZ. - The TRMM NASDA-3b43
algorithm is presumed to be the most accurate of
the two TRMM retrieval products.
MODIS
NR-MODIS
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Evaluation of the European Centre for
Medium-Range Weather Forecasts (ECMWF) Nature
Run midlatitude cyclone activity tropical
Atlantic and African MonsoonOreste Reale
NASA/GSFC/GLAJoe Terry NASA/GSFC/SIVO
Midlatitude Cyclone Diagnostics

• Diagnostics produced
• Tracks
• Lifespan
• Distribution by central pressure
• Deepening rate
• Mean direction and speed (total, zonal and
  meridional speed)
• Cyclone, genesis and lysis density

• Statistical properties of the atmospheric flow,
  particularly midlatitude cyclone activity, are
  investigated
• In the tropics however, it is crucial the assess
  the presence of fundamental features of tropical
  weather systems
• Until few years ago, to search for evidence of
  tropical weather in a global model was not
  possible and only large-scale, diluted
  large-scale features could be detected

• Goals
• Identify any trends or biases
• Identify any conspicuous anomalies and
  determine source
• Assess realism

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• Utilize Goddards cyclone tracking software
  (Terry and Atlas, AMS conf, Aug 1996)
• Identifies and tracks mostly extratropical
  cyclones (cutoff at 20 deg N/S latitude)
• Interfaces with GrADS contouring algorithm
• Uses SLP field at 4hPa contour interval
• Finds centroid of inner-most closed isobar
• Tracks the centers using extrapolation and
  500hPa steering

• Cyclone tracks generated
• Nature run at one degree for Jun 2005 to May
  2006 (each month and season)
• NCEP operational analysis at one degree for
  2000 to 2006 (each month, 68 of 84 months were
  available)

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Cyclogenesis density from NCEP reanalysis over
Southern Hemisphere. (Simmonds and Keay, Journal
of Climate, March 2000)
Nature Run diagnostics (J. Terry, NASA/GSFC/SIVO)

• Statistical properties of midlatitude cyclone
  activity have been proved very satisfactory

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Nature Run Atlantic tropical cyclone
seasonOreste Reale NASA/GSFC/GLA

• Fundamental dynamical features associated to the
  climate-weather interface generally present in
  the tropical atmosphere, are searched in the
  Nature Run. Focus is the AMMA region and the
  tropical Atlantic
• African Easterly Jet, African Waves, Tropical
  Cyclones track (and their complexity), Tropical
  Cyclone structure are investigated
• Reale, O., J. Terry, M. Masutani, E. Andersson,
  L. P. Riishojgaard, J. C. Jusem, 2007
  Preliminary evaluation of the European Centre for
  Medium-Range Weather Forecasts (ECMWF) Nature Run
  over the Tropical Atlantic and African Monsoon
  region. Geophysical Research Letters, 34, L22810,
  doi10.1029/2007GL31640.

• First Nature Run to simulate one entire season
• Twelve tropical cyclones develop
• Realistic variability of tracks
• Most intense reaches 957 hPa
• Binary vortices, looping and singularities are
  observed (good from OSSE perspective)

FiveEarly recurvers appear in the season. Three
central-Atlantic TCs with convincing
Extra-tropical transitions, and 3 systems of the
Gulf. Overall, very realistic track variability.
Early recurvers are more than climatology but not
unseen. Four early recurving systems in an
active season, 2004 (NHC).
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Realistic Variability of TCL system tracks in the
Atlantic
Wind speed (m/s) Temp (oC) Vort (s-1)
Looping and Binary vortex interaction
Vertical structure of a TC 2 vortex shows, even
at the degraded resolution of 1 deg, a distinct
eye-like feature and a very prominent warm core.
4 systems Looping, Binary vortex
Interaction, Extratropical Transitions and
Extra-tropical Re-intensification
Singuarities, binary vortex Interactions,
Intensity fluctuations Due to large-scale forcing
fluctuations
Vertical structure of TC11 shows another example
of eye-like feature and a very prominent warm
core. Structure even more impressive than the
TC2. Low-level wind speed exceeds 55 m/s
vorticity max In the lower levels.
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The African Easterly Jet (AEJ)
September
Jul-Aug
MJJA

• The AEJ appears at the perfect climatological
  elevation (650hPa) but is slightly more to the
  north with respect to climatology and analyses
• Intensity (11m/s) compares well with observed
  climatology (e.g Burpee 1972 and operational
  analyses for the period)
• Realistic clear separation between AEJ and
  low-level Harmatthan flow at 20E
• Weaker than climatology low-level westerly
  monsoonal flow
• Reduced vertical easterly shear due to reduction
  of the TEJ at 150 hPa with respect to Jul-Aug
• Strong horizontal cyclonic shear on the southern
  flank of the AEJ, leads to condition much more
  favorable to tropical development

• July and August means show a northward
  displacement of the AEJ, gradual intensifcation
  of the Harmatthan flow and of the low-level
  monsoonal flow.
• Realistically well-defined low level westerly
  monsoonal flow in agreement with obs (e.g. Asnani
  2005)
• Realistically intense horizontal cyclonic shear
  on the southern flank of the AEJ in July and Aug
• Tropical Easterly Jet at 200-150 hPa is stronger
  than climatology, thus creating
  higher-than-observed vertical easterly shear,
  which appears to inhibit the early development of
  AEWs attempting to become vortices

• Intensity (11m/s) compares well with observed
  climatology (e.g Burpee 1972 and operational
  analyses for the period)
• Realistic clear separation between AEJ and
  low-level Harmattan flow
• Realistically well-defined low level westerly
  flow
• Moderate horizontal cyclonic shear on the
  southern flank of the AEJ, increasing towards the
  end of the analyzed period

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October
Comparison with NCEP op. Analyses for Sep 2005
January
The AEJ has a realistic maximum of 11 m/s at 600
hPa but wind speed are too low at 750 and 700
hPa consistently with the altitude bias.
Meridional shear of zonal wind is realistic and
supportive of barotropic instability.

• October shows a realistic receding of the African
  monsoon
• A realistic weakening of the AEJ, but also of the
  easterly vertical shear is evident
• Tropical Easterly Jet at 200-150 hPa follows
  climatology, reducing vertical shear and allowing
  several AEWs to become vortices in spite of
  reduced horizontal shear in the southern flank of
  the AEJ

September
Nature Run
October
The AEJ has a perfectly realistic maximum of 11
m/s at 600 hPa in September and gradually
weakens in October following climatology.
NCEP operational analyses
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Example of nondev. AEW due to Easterly Shear
Tropical Easterly Jet (TEJ) at 150hPa

• The TEJ controls the easterly vertical shear that
  may inhibit early stages of development.
• It is a planetary scale feature connected with
  the Asian Monsoon
• Fluctuations on interannual scale are known (Chen
  and van Loon, 1987) but intraseasonal variations,
  despite their importance, are still little known
• Eastward retreat of strong easterly speed (40
  m/s or higher) throughout the monsoon season,
  produces decreased vertical easterly shear over
  the Atlantic and an increasingly favorable
  environment for development
• The NR shows a stronger than climatology TEJ, but
  a very credible and realistic decrease of
  easterly speed with the progress of the monsoon
  season. As a consequence, the environment becomes
  conducive to more development

850hpa Vort (sh)
650 hPa flow
In the early stages, 850 hPa vort. increases and
vort max becomes aligned with 650hPa circulation
center. Eventually upper-level easterly shear
suppresses development.
The potentially favorable situation induced by a
vertically aligned structure between 800 and 500
hPa at 12-14N is counteracted by easterly
vertical shear of the order of 20 m/s.
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Concluding remarks on the African Monson region
and tropical Atlantic
African Easterly Waves (AEWs)

• A synoptic assessment of the NR over the AM
  region and the tropical Atlantic shows an overall
  very realistic African Monsoon, AEJ and wave
  activity
• Several weak tropical and sub-tropical systems
  are present, together with major tropical
  cyclones
• In spite of a tendency of creating several early
  recurvers, it can be stated that the NR, given
  the resolution limitation, does have a very good
  representativeness of tropical cyclone track
  variability in the Atlantic, as it would occur in
  an active season
• This Nature Run represents a very promising tool
  to perform OSSEs over the tropical Atlantic

CURRENT and FUTURE WORK at NASA GSFC (GLA, GMAO,
JCSDA and SIVO) on the NR validation

• Comprehensive statistics on midlatitude cyclone
  activity have been performed
• Analysis of tropical weather over Indian Ocean
  and Asian Monsoon regions with emphasis on the
  Somali Jet, monsoon onset and breaks, tropical
  depressions, together with an assessment of the
  Eastern Pacific tropical cyclone, Southern
  Hemisphere and WPacific seasons is being
  completed
• Results from this comprehensive assessment to be
  submitted as a journal article during 2008

AEWs show a realistic propagation speed of about
5-9 deg/day, comparable to analyses. Moreover,
there is a period of about six weeks in which the
majority of waves present signs of development.
This is similar to what happens in very active
seasons. The disappearance from the Hovm relates
to changes in latitude.
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Case Events Identified from ECMWF T799NR
Christopher M. Hill, Patrick J. Fitzpatrick,
Valentine G. Anantharaj Mississippi State
University (Plotted from 1x1 data)
Comparison of zonal mean zonal wind jet maxima,
NR and ECMWF analysis, Northern Hemisphere By
Nikki Prive, ESRL
blue ECMWF green star Nature Run
Evaluation of Cloud Simpson weather associates
Nikki Prive also presented realistic Rossby wave
and many good storms to test T-PARC experiments
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Quick look of T799 NR period T511 vs T799 in
1deg Michiko Masutan (NOAA/NCEP/EMC)
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Simulation of Observation
OBS91L Nature Run Model level profiles for
simulating radiance obs Jack Woollen (EMC)
Simulation of Conventional ObservationsJack
Woollen (NCEP/EMC)
Sat wind was included to provide reasonable
fields for SH Radiation data are not included.
Initial data will have no error added and
quality control is not necessary.
For development purposes, 91-level ML variables
are processed at NCEP and interpolated to
observational locations with all the information
need to simulate radiance data (OBS91L).
OBS91L made for all foot prints of HIRS, AMSU,
GOES are produced for a few weeks of the T799
period in October 2005 As well as for the month
of May 2005. OBS91L are produced for all
radiance foot prints assimilated in operational
GDAS as recorded in the archived radstat
files. The OBS91L are also available for
development of a Radiative Transfer Model (RTM)
for development of other forward model.
Considerations Data distribution depends on
atmospheric conditions Cloud and Jet location,
Surface orography, RAOB drift
Simulation of Observaional Error Ron Errico
NASA/GSFC/GMAO
Precursor run with Conventional DataYuanfu Xie
(NOAA/ESRL), Jack Woollen (EMC), Michiko
Masutani(EMC), Yucheng Song(EMC)

• T62L64 or T126 L64 is used in the experiment for
  entire period for T511 NR using perfect
  observation without quality control.
• This will to test the OSSE system and provide
  initial condition for other OSSEs.

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Radiance Simulation System for OSSEGMAO, NESDIS,
NCEPRon Errico, Runhua Yang, Emily Liu, Lars
Peter Riishojgaard, Ravi Govindaraju
(NASA/GSFC/GMAO)Tong Zhu, Fuzhong Weng, Haibing
Sun(NOAA/NESDIS)Jack Woollen(NOAA/NCEP)
Other possible resources and/or advisors David
Groff , Paul Van Delst (NCEP) Yong Han, Walter
Wolf, Cris Bernet,, Mark Liu, M.-J. Kim, Tom
Kleespies, (NESDIS) Erik Andersson (ECMWF) Roger
Saunders (Met Office)
NASA/GMAO is developing best strategies to
simulate and work on more complete foot prints.
This include development of cloud clearing
algorithm. NESDIS and NCEP are working on
thinned data to perform precursor run for entire
period. (seeking for resources) Sample full
resolution data for GOES for cloudy radiance are
also produced by Tong Zhu.
Existing instruments experiments must be
simulated for control and calibration and
development of DAS and RTM and to test
GOESR,NPOESS, and other future satellite data
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Simulation of GOES-R ABI radiances for OSSE Tong
Zhu et al. 5GOESR P1.31 at AMS annual
meeting http//www.emc.ncep.noaa.gov/research/Join
tOSSEs/publications/AMS_Jan2008/Poster-88thAMS2008
-P1.31-OSSEABI.ppt
Simulated from T511 NR. GOES data will be
simulated to investigate its data impact
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More Simulation of Observations This list show
the capabilities. Not all the activities are
funded.
Simulation of DWLKNMI, SWA, NASA/GSFC, Ball(?)
Simulation Radiance data to be evaluated by
OSSEsGMAO,NESDIS,MSU,JCSDA, UW/SSEC and more
Unmanned Air Craft System (UAS) NOAA/ESRL
Cloud Motion Vectors SWA - Advised by Chris
Velden -
Uniform Raob for testing DAS EMC
Scatterometer KNMI
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OSSEs planned Funded or seeking funding but
starting with volunteers
OSSEs to investigate data impact of GOES and
preparation for GOES-R NESDIS, EMC
OSSE to evaluate DWL KNMI,SWA,EMC, GMAO,
NOAA/ESRL, and more
OSSE to evaluate UAS ESRL and NCEP
OSSEs for THORPEX T-PARC EMC, FSU, ESRL
Regional OSSEs to Evaluate ATMS and CrIS
Observations GRI/Mississippi State Univ (MSU),
JCSDA
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Various planned OSSE-related activities
Visualization of the Nature run Jibo Sanyal
(MSS), O. Reale (NASA/GSFC/GLA), H.
Mitchell(NASA/GSFC/SIVO)
Sensor Web NASA/GSFC/SIVO, SWA
Assimilation with LETKF possibly by 4D-var T.
Miyoshi(JMA) and T. Enomoto(JEMSTEC)
Analysis with surface pressure Gil Compo, P. D.
Sardeshmukh (ESRL)
Identical twin experiments It is worthwhile to
try identical twin experiments to understand
model error. Identical twin OSSEs can be only
used for illustration only . ECMWF offered to
perform identical twin OSSEs if there is specific
goals. (Erik Andersson)
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Projects being considered or seeking funding and
various possibilities
Regional OSSEs to evaluate DWL Zhaoxia Pu,Univ of
Utah
OSSE to design configuration of GPS Lidia
Cucurull,JCSDA,EMC
Evaluation data assimilation system Ron Errico,
GMAO
Simulation of ASCAT QuickScat XOVMM Scatterometer
Ad Stoffelen, KNMI
Evaluation of RAOB Drift Erik Andersson,EMCWF
Evaluation of Drift Buoy Jean Pailleux, Meteo
France
More possibilities Evaluation of retrieval
program Simulating Gestational DWL, Ball Use
OSSEs for training and education.
Targeted Observation using LETKF Eugenia Kalnay,
UMCP
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Getting ready for OSSEs
? Produce perfect data and run calibration
experiments ? Design representativeness error and
observational error and redo calibration ?
Development of standard verification package ?
Clarify potential and limitations of OSSE and
educate community ? Meso/Regional OSSEs Joint
OSSE team agreed we have to concentrate on OSSEs
with existing NRs to study superobbed data impact
of high resolution data. However, there are
strong demands for mesoscale OSSEs. Joint OSSE
team is working on integrating mesoscale OSSE
interest. ? Coordination of work - Uniform
representation of observational data and
results - Keep track who actually did the work
and various contributions - Organizing
publication OSSE Chapter in Data Assimilation
book from Springer Introductory article in BAMS
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Requirements for a future Nature Run - Some
suggestions -
We need to avoid many poorly planned and assessed
nature run
? The NWP model must have good forecast skill.
Great visualization does not guarantee good
forecast skill. ? At least a 3 month lower
resolution run with the same model is required to
provide a spin-up period for bias correction. ?
Must have a good TC or a severe storm in the
Nature Run period. ? Sufficient number of
vertical levels Minimum 91 levels ? Some degree
of coupling with the ocean and land surface ? If
it is regional, the effect of the lateral
boundary must be evaluated. ? A list of
verification methods must be produced by Joint
OSSE. ? Need NR to be shared within Joint OSSE ?
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