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Progreee in Evaluation of Space Based DWL in Joint OSSEs

http://www.emc.ncep.noaa.gov/research/JointOSSEs

February 2009

Michiko Masutani(EMC,JCSDA), G. David Emmitt (SWA), Steven Greco(SWA), Sidney Wood(SWA)

Ad Stoffelen(KNMI), Gert-Jan Marseille(KNMI)Jack Woollen(EMC)

Lars Peter Riishojgaard Joint Center for Satellite Data Assimilation

(Director)

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A Nature Run (NR, proxy true atmosphere) is produced from a free forecast run using the highest resolution operational model which is significantly different from NWP model used in DAS.

For a “Full OSSE”, all major existing observations have to be simulated with both random and systematic observational errors.

Calibrations of the simulated observations must be performed to provide quantitative data impact assessment.

Full OSSEsThere are several types of Observing System Simulation Experiments. We refer to the “Joint OSSE” as a ‘Full OSSE’ to avoid confusion.

In OSSE calibrations, real and simulated data impacts are compared. The results are used to evaluate data impacts in simulation experiments.

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While “Rapid Response OSSEs” or “QuickOSSEs” may provide less expensive yet important and reliable insights to potential data impacts from proposed new observing systems, full OSSEs offer a more realistic and quantitative representation of those data impacts on analyses and forecasts.

A Full OSSE can use the full extent of an existing operational forecast system and provide input to the preparation of that system for the ingestion of the new data set(s) in an operational setting (e.g. ADM).

Advantages of Full OSSEs

Existing Data Assimilation System and verification methods are used for Full OSSEs. This will help in the development of DASs and verification tools.

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Why an International Joint OSSE capability

• Full OSSEs are expensive– Nature Run, entire reference observing system, additional

observations must be simulated. Sharing one Nature Run saves $$.

– Calibration experiments, perturbation experiments must be assessed according to standard operational practices and using operational metrics and tools

• OSSE-based decisions have international stakeholders– Decisions on major space systems have important scientific,

technical, financial and political ramifications– Community ownership and oversight of OSSE capability is

important for maintaining credibility• Independent but related data assimilation systems allow us to test

robustness of answers

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.

New Nature Run by ECMWFProduced by Erik Andersson(ECMWF)

Based on discussion with JCSDA, NCEP, GMAO, GLA, SIVO, SWA, NESDIS, ESRL, and ECMWF

Low Resolution Nature Run Spectral resolution : T511 , Vertical levels: L91, 3 hourly dumpInitial conditions: 12Z May 1st, 2005 , Ends at: 0Z Jun 1,2006

Daily SST and ICE: provided by NCEPModel: Version cy31r1

Two High Resolution Nature Runs35 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 dumpGet initial conditions from T511 NR

Not recommended for OSSE. Better version will be provided when JOSSE is ready

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Comparison between the ECMWF T511 Nature Run against

climatology20050601-20060531, exp=eskb,

cycle=31r1Adrian Tompkins, ECMWF

NR

MODIS

NR-MODIS

Utilize Goddard’s cyclone tracking software. - By J. Terry(NASA/GSFC)

Evaluation of the Nature run

Vertical structure of a HL vortex shows, even at the degraded resolution of 1 deg, a distinct eye-like feature and a very prominent warm core. Structure even more impressive than the system observed in August. Low-level wind speed exceeds 55 m/s.

Tropics by Oreste Reale (NASA/GSFC/GLA)

Seasonal mean zonal mean zonal wind jet maximum strength and latitude of the jet maxima for the ECMWF reanalysis (1989-2001, blue circles) and the Nature Run (), northern hemisphere. (N. Prive.)

Time series showing the night intensification of the LLJ at the lee of the Andes in the simulation.Gridpoint at 18 S / 63 W

THE SOUTH AMERICAN LOW LEVEL JET

Juan Carlos Jusem (NASA/GSFC)

M.Masutani (NOAA/NCEP)

-90 -60 -30 0 30 60 90L a titu d e

0

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Total

Clo

ud C

over

(%)

Total C lou d C ove r (Land and O cean)

- NR- ISC CP- W W M CA-- H IR S

Evaluation of T511(1°) clouds

by SWA

OSSE Calibration● In order to conduct calibration all major existing observation have to be simulated.

● The calibration includes adjusting observational error.

● If the difference is explained, we will be able to interpret the OSSE results as to real data impact.

● The results from calibration experiments provide guidelines for interpreting OSSE results on data impact in the real world.

● Without calibration, quantitative evaluation data impact using OSSE could mislead the meteorological community. In this OSSE, calibration was performed and presented.

Simulation of control data for calibration

● Simulation of control data should be funded for OSSEs● GMAO and NCEP are simulating control data

Data Simulation strategies at NCEP-NESDIS

► Ozone data from SBUV► Conventional data based on NCEP reanalysis quality controlled distribution. (More complete data set compared to operational data)► Satellite radiance data in 2005 distribution. AMSUA, AMSUB, GOES, HIRS2, HIRS3, AIRS,MSU are being generated at foot print used by NCEP operational analysis. ► Observational error is random error based on error table.► Limited calibration and validation will be conducted by NCEP and NESDIS for their own use. However, users are expected to perform their own calibrations and validation.

Progress and current plan :

Future plan:

► Observational error based on correlated noise► Simulation and assimilation of of cloudy radiance and let sampling done by assimilation. Cloudy radiance is still under development.

Template dataObserved radiance with horizontal thinning

Simulation of HIRS3 radiance from NOAA16Latest version of CRTM (1.2.2) is used for simulationDBL 91 was generated at foot print used by NCEP GDASAll information in GDAS bufr files are copied to simulated radiance file.Channel which are not used by GDAS was marked in diag file. Masked out to generate masked radiance data.

Horizontal thinning

Horizontal and vertical thinning

HIRS3 NOAA 16 Ch=4 May 2nd 00z (f12)

Progress in Calibration at ESRL- NCEP

ESRL and NCEP are working on calibration using data denial method and fits to observation.

Using simulated data by GMAO and additional data from NCEP-NESDIS.Focused on July-August 2005.GSI version May 2007.

NCEP is working on upgrading OSSE system to newer GSI to accommodate DWL and flow dependent error covariances. Some calibrations will be repeated.

• Data denial tests are run for synthetic obs subsets of similar data types

• Analysis impact (global RMS difference in control and data denial analysis) is calculated for synthetic obs and compared to analysis impact for data denial with real archived data from July 2005

• Standard deviation of synthetic errors are adjusted, errors are regenerated

• New data denial case is run and compared to real data, errors adjusted, etc

• Repeat until analysis impact matches real data analysis impact, or until satisfied that calibration is not possible

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Concept for a U.S. Space-Based Wind Lidar

Global Wind Observing Sounder (GWOS)

Dual Technology Sampling• The coherent subsystem provides very accurate (<

1.5m/s) observations when sufficient aerosols (and clouds) exist.

• The direct detection (molecular) subsystem provides observations meeting the threshold requirements above 2km, clouds permitting.

• When both sample the same volume, the most accurate observation is chosen for assimilation.

• The combination of direct and coherent detection yields higher data utility than either system alone. Note that in the background aerosol mode, the combination of the coherent and direct provide ~ 20 % more coverage near 3 -5 km than could either technology by itself.

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Hybrid Doppler Wind LidarHybrid Doppler Wind LidarMeasurement Geometry: 400 kmMeasurement Geometry: 400 km

350 km/217 mi53 secAlong-Track Repeat“Horiz. Resolution” 586 km/363 mi

GWOS Sampling

1) Acquired the ECMWF T511 Nature Run (NR) model level data in GRIB format

2) Developed software to read and unpack the T511 NR model level GRIB data

3) Unpacked the T511 NR model level GRIB data for July 1 - Aug 10, 2005

4) Created global atmospheric data sets for July 1 - Aug 10, 2005 to be used by

the Doppler Lidar Simulation Model (DLSM)

5) Modified the LSM to work with the variables, levels and resolutions/grids of

the T511 NR model level data

6) Conducted a test run of a GWOS DWL simulation using the T511 NR

7) Will continue the GWOS DWL simulations for July 1 - August 10, 2005 upon

final quality check

Progress in GWOS DWL Simulations (SWA)

Simulation of GWOS dataSimpson Weather Associates

Simmulation of ESA DWLKNMI

• Spring 2008: ADM Mission Advisory Group (ADMAG) advises ESA to participate in Joint OSSE

• KNMI submits TOGETHER proposal to ESA

TOGETHER

Towards a Global observing systemthrough

collaborative simulation experiments

ADM simulation

• ADM OSSE heritage, for details see Stoffelen et al., 2006 http://www.knmi.nl/~marseill/publications/fulltexts/osse.pdf• Tools for retrieving nature run fields from ECMWF archive• Orbit simulator• Interpolation of model fields to ADM location

“True” (HLOS) wind• Instrument error: LIPAS (Lidar Performance Analysis Simulator)

− For details see Marseille and Stoffelen, 2003http://www.knmi.nl/~marseill/publications/fulltexts/dwlsimul.pdf

− LIPAS is updated and compatible with L2B processor performance

DWL OSSE Progress and Plans at NCEP

NCEP data assimilation system (GSI) has been upgraded to handle DWL data more efficiently. The code was successfully tested for idealized data. The system is being upgraded for 2010 operational version.

Extensive calibration experiments have been conducted by ESRL for July-August 2005 using control data produced by GMAO with 2007 GSI system. NCEP will repeat calibration experiment for selected wind data (RAOB wind) with new GSI system.

GWOS DWL data provided by SWA will be tested for July-August 2005.

NCEP will produce further control data.

GWOS OSSE will be extended to hurricane period and winter storm period.

Data impact of SWA and KNMI product for ADM will be compared.

Coordinate with GMAO OSSE to gain the confidence in results.

Data Sharing in Joint OSSEs

NASA/NCCS provided dis space for Joint OSSE data sharingThere is a entry created for Joint OSSEhttp://portal.nccs.nasa.gov/josse/index.pl

Make entry to each data set and generating institute, and contact person.

People use these data must contact generating institutes.

Simulated observation and other useful data will be shared among Joint OSSE teams.

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• OSSEs are a cost-effective way to optimize the investment in future observing systems such as the proposed space-based Doppler wind lidar (GWOS)

• OSSE capability should be broadly based (multi-agency)– Credibility– Cost savings– Simulation of basic control data should be conducted by instrument teams

• Exploratory or “Quick” OSSEs serve as a less expensive way to down-select observing system configurations as candidates for “full OSSEs”.– However, the interaction of the full and exploratory OSSE efforts is critical

to the proper interpretation and representation of the simulated impact results

Summary

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End

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• OSSEs are a cost-effective way to optimize investment in future observing systems

• OSSE capability should be broadly based (multi-agency)– Credibility– Cost savings

• TimingAll OSSEs are funded unrialistic time scale. People are forced to do shortcut.Simulation of basic data will should be funded for OSSEs.

If we do not assist other OSSEs they will produce damaging results

Summary

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In Spring, 2008 Simpson Weather Associates, Inc. established the Doppler Lidar Simulation Model version 4.2 on an Apple dual quad processor computer for the SensorWeb project. SSH, the network protocol that allows data to be exchanged over a secure channel between two computers, was installed and tested. SWA and SIVO were able to test the push/pull and communications functionality successfully. SIVO was able to push DLSM inputs to SWA and request model simulations. The DLSM was successfully executed and SIVO was able to retrieve DWL coverage and DWL line-of-sight wind products for a six hour simulation in less than 2 minutes.

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Doppler Wind Lidar Simulation ModelSimpson Weather Associates