Observing System Simulation Experiments

for NPOESS

Stephen J. Lord (PI), Michiko Masutani, John C. Woollen, John C. Derber

NOAA/NWS/NCEP/EMC, Camp Springs, MD

Robert Atlas, Joseph Terry

NASA/GSFC/DAO, Greenbelt, MD

G. David Emmitt, Sidney A. Wood, Steven Greco

Simpson Weather Associates, Charlottesville, VA

Thomas J. Kleespies, Vaishali Kapoor

NOAA/NESDIS, Camp Springs, MD

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

Participating Institutes:

NOAA/NWS/NCEP/EMC, /NASA/GSFC/DAO, SWA, NOAA/NESDIS

Sponsored by:

Dr. Stephen Mango ( NPOESS/IPO), NOAA/OAR, NOAA/NESDIS

OSSE: Observing System Simulation Experiments

NPOESS: National Polar-orbiting Operational Environmental Satellites

NPP: NPOESS Preparatory Project

(OSSEs are a major component of the NOAA/NASA Joint Center for Satellite Data Assimilation - JCSDA)

Schematic diagram for OSSE

Objective:

• Test the impact of new NPP instruments using OSSEs in a state of the science numerical forecast system.



• Evaluate and recommend configurations

Instruments to be tested

• Doppler Wind Lidar (DWL)
• Atmospheric infrared sounder (AIRS)
• Cross track infrared sounder (CrIS)
• Conically scanning Microwave Imager/Sounder (CMIS)
• Advanced Technology Microwave Sounder (ATMS)

The NCEP OSSE data assimilation system

Operational data assimilation system-March 99 version.

Spectral Statistical Interpolation (SSI)

Parrish and Derber (1992)

T62/ 28 level

Real Observations (1993 distribution)

RAOB and other conventional data

ACAR (1993 distribution)

HIRS and MSU level 1B data from NOAA-11, NOAA-12

Satellite wind

Nature Run

ECMWF reanalysis model

Resolution T213 (about 60 km), 31 levels

06Z 5 February 1993 to 00Z 7 March 1993

The nature run available from NCEP ftp site

Major accomplishments (2000)

• Nature Run processed and made available to the U.S. OSSE community.

• Nature Run evaluation and adjustment of cloudiness for realistic sampling.



• Upgraded data base for LOS winds.

• Upgraded NCEP data assimilation (SSI) to use LOS winds. .



• Simulated observations.

• Existing instruments (Conventional data and TOVS 1B)
• Future Instruments (DWL)

• Sensitivity tests performed for real observations (Observing System Experiments). 3 Months.



• Repeat sensitivity tests on simulated data set for existing instruments (OSSE) for calibration. The nature run period.

Calibration Experiments

EXPID	TOVS 1B	RAOB Temp	RAOB Wind	All other conventional data ACAR, SATWIND, SFCdata
Control	Y	Y	Y	Y
1	Y	N	Y	Y
2	Y	Y	N	Y
3	Y	N	N	Y
4	N	Y	Y	Y
5	N	N	Y	Y
6	N	Y	N	Y
7	N	N	N	Y

Procedures

• Spin up of assimilation is from 06Z 5^th February with all conventional data.



• Add or deny starting from 00Z 13th February



• So far, four days of data assimilation completed; total 24 days.



• Compare RMS difference between control and experiments for 6 hour forecast field.

Comparison of impact in real and simulated analysis

Results

In general, there is satisfactory consistency between real and simulated data impacts.

• RAOB winds have more impact on forecast winds compared to RAOB temperatures globally in both simulation and real.

• The exception:

In NH, the impact of RAOB temperatures on temperature fields is slightly stronger in the simulation compare to real data.

• In tropics, simulations show bias related to temperature and moisture data.



• In NH, 1B has little impact over Europe - Asia. But shows small impact over Pacific. The magnitudes are similar between simulation and real.



• In SH, 1B dominates. However, with 1B data, RAOB data do show some impact and their impacts are similar between simulation and real.



• In SH, RAOB winds have more impact than RAOB temperatures for both wind and temperature fields and for both simulation and real.

Planned Evaluation Metrics for OSSE results

• Standard anomaly correlation by scale and wave number
• Diagnostics of cyclone and jets. (Strength and position)
• Compare extreme events.
• Data rejection statistics
• Cost benefit in aviation application (flight planning)

Plan for 2001

A. Complete calibration experiments

For longer time period.

Forecast skill comprison

B. OSSE for future instruments

DWL, AIRS, and others

C. Impact tests for :

• Data density
• Data distribution and processing

(Averaging, Super observation, etc.)

• Error assignment. Test systematic errors.
• Adaptive observing strategies

Simulation of DWL wind

TRV: Targeted Resolution Volume 200kmx200kmxT

T: Thickness of the TRV

0.25km if z<2km, 1km if z>2km

0.25km for cloud return

Swath width: 2000 km except for EXP4 (non-scanning)

Clustered:Data product is based upon averaging the observations of shots clustered within a very small area compared to the base area of the TRV.

Distributed: Data product is based upon averaging the observations of shots distributed throughout the TRV as would result from continuous conical scanning

Data products based upon clustered and distributed shots are generated for each experiment except for the reference experiment.

No measurement error is assigned.

EXP 1(Best): Ultimate DWL that provides full tropospheric LOS soundings, clouds permitting.

EXP 2 (PBL+cloud): An instrument that provides only wind observations from clouds and the PBL.

EXP 3 (Upper): An instrument that provides mid and upper tropospheric winds only down to the levels of significant cloud coverage.

Exp 4 (Non-Scan): A non-scanning instrument that provides full tropospheric LOS soundings, clouds permitting, along a single line that parallels the ground track.

Reference: Perfect u,v observations from an orbiting instrument at single points within the TRV. No cloud or sub-grid wind variability effects accounted for.

(Clustered shots only)

Acknowledgment

Wei -You Yang, Russ Treadon, Ken Campana, S.-K. Yang, Wan Shu Wu, Yuejian Zhu, , Bert Katz, Jim Purser, Dave Parrish, Bill Collins, Mark Iredell, Dennis Keyser, Zoltan Toth, Song- You Hong, Bob Kistler ,Wesley Ebisuzaki, George Vendenberg, Steve Tracton (NCEP)

Genia Brin,Stephen C. Bloom, Dick P. Dee, and N. Wolfson (DAO)

,

Lin Wood (SWA)

Larry Stowe, Andrew Heidinger , Po Li (NESDIS)

Christian Jakob, Roger Saunders, Keith Felding, Tony Hollingsworth (ECMWF)

Advised by:

Drs. W. Baker, James Yoe, R. Daley, E. Kalnay,

and Members of the review panel

Supported by:

Dr. Steven Mango ( NPOESS/IPO)

NOAA/OAR, NOAA/NESDIS

Documentation

More details may be found on Web site

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

- Evaluation of Nature run

(NASA/DAO, NCEP, SWA)

- Simulation of conventional data

Terry and Atlas (NASA/DAO)

- Simulation of DWL data

Emmitt, Wood, Greco (SWA)

- A set of requirements for global atmospheric wind observations Emmitt (SWA)

- Systematic errors in simulated Doppler wind lidar observations Emmitt (SWA)

- Simulation of TOVS radiance

Kleespies, Kapoor (NESDIS)

- Data withdrawal experiments

Masutani, Lord, Woollen, et al. (NCEP)

- Observation error assignment

Woollen et al. (NCEP)