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Observing System Simulation Experiments for COSMIC-II. UCAR COSMIC Team. FORMOSAT-3/COSMIC Follow-on Mission Planning. NSC/NSPO and NOAA are discussing a possible collaboration on the FORMOSAT-3 Follow-On Mission, which is called “COSMIC-II.”

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formosat 3 cosmic follow on mission planning
FORMOSAT-3/COSMIC Follow-on Mission Planning
  • NSC/NSPO and NOAA are discussing a possible collaboration on the FORMOSAT-3 Follow-On Mission, which is called “COSMIC-II.”
  • Preliminary design calls for 12 low-Earth orbiting satellites, each carrying an advanced receiver to track thee navigation systems, including GPS, GALILEO, and GLONASS.
  • Observing system simulation experiments (OSSE) are useful to assess the potential impacts of the COSMIC-II mission, and to assist in constellation design.
three key questions
Three Key Questions:
  • What are the potential impacts of FORMOSAT-3 Follow-on on the prediction of typhoons in the vicinity of Taiwan?
  • What is the optimal design of the Follow-on Mission? [This needs to be looked at from global, regional weather prediction, climate, and space weather perspectives.]
  • What are the relative performance of FORMOSAT-3 Follow-on compared with the existing FORMOSAT-3 mission?
two possible configurations
Two Possible Configurations
  • Option A:
    • 8 satellites placed at 72 degree inclination angle
    • 4 satellites placed at 24 degree inclination angle
  • Option B:
    • 12 satellites placed at 72 degree inclination angle
distribution of ro soundings in a day
Distribution of RO soundings in a day

G

A

B

FORMOSAT-3/COSMIC

COSMIC-IIA

COSMIC-IIB

Different color shows availability of RO soundings at different hours of the day.

data density for formosat 3 cosmic iia cosmic iib
Data Density for FORMOSAT-3, COSMIC-IIA, COSMIC-IIB

COSMIC

- 6 x 72o

COSMIC-IIA

- 8 x 72o + 4 x 24o

COSMIC-IIB

- 12 x 72o

COSMIC-IIA Provides a much more even data density around the globe.

Enhanced data density over the tropics is important for typhoon prediction.

selected case typhoon shanshan 2006
Selected Case: Typhoon Shanshan (2006)
  • Min. pressure of 920 hPa on Sep 15, 2006
nature run from mm5 with ecmwf initial condition
Nature Run from MM5 with ECMWF Initial condition
  • Typhoon track recurvature was reproduced
  • The track is close to the best track
  • Note that no official intensity observation is available
forecast experiment design
Forecast Experiment Design
  • WRF-Var (3D-Var) /WRF with GFS IC and LBC
    • B.E.: generated from one month forecast of September, 2006 (NMC)
    • 169 x 157 x 38, ptop = 10 hPa
    • Assimilation performed on 36-km grid, 1hr update cycle, over two-day period.
convention data are assimilated as well
Convention Data Are Assimilated As Well

Synop

SOUND upper air

Satellite wind (SATOB)

  • Upper Air sounding (SOUND)
  • Observation (SYNOP)
  • Satellite Cloud track Wind (SATOB)
  • The horizontal and temporal distribution of these data are consistent with actual observations (location/time, and with realistic errors )
simulated ro refractivity data

Equator

Height

pole

Percentage of GPS Ref observations

Simulated RO Refractivity Data
  • For GPSRO refractivity, the observation errors vary with height and latitude (Chen and Kuo, 2005).
  • RO soundings are simulated from the nature run as local value, no ray tracing simulation.
intensity forecast
Intensity Forecast

C

  • Intensity Forecast Performance: C+A > C+B > C+G > C

C+G

C+B

C+A

Nature

intensity forecast improvement against control conventional data forecast
Intensity Forecast Improvement against control (conventional data) forecast

Percentage of improvement of intensity forecast

  • FORMOSAT-3 only shows modest improvement over Control.
  • COSMIC-IIA shows significant improvements over control.
  • COSMIC-IIA is superior to COSMIC-IIB

Percent Improvement relative to the control:

P.I. = (Error of Exp. C minus Error of Exp. X)/Error of Exp. C

track forecast errors
Track Forecast Errors
  • Performance: C+A > C+B > C+G > C

C

C+G

C+B

C+A

track forecast errors improvement against control conventional data forecast
Track Forecast ErrorsImprovement against control (conventional data) forecast

Percentage of improvement of track forecast

  • FORMOSAT-3 only shows visible improvement over Control.
  • COSMIC-IIA shows significant improvements over control.
  • COSMIC-IIA is superior to COSMIC-IIB
6 hour integrated precipitation forecast
6 hour Integrated Precipitation Forecast

N

C

C+G

C+A

C+B

No precipitation system was developed in C, C+G, and C+B, only C+A

6 hour integrated precipitation cont d
6 hour Integrated Precipitation (cont’d)

N

C

C+G

C+A

C+B

  • Precipitation in C+A is much closer to that in nature run
6 hour integrated precipitation cont d1
6 hour Integrated Precipitation (cont’d)
  • Late development of precipitation in C, C+G, and C+B, but in wrong locations

N

C

C+G

C+A

C+B

6 hour integrated precipitation cont d2
6 hour Integrated Precipitation (cont’d)
  • All precipitation is stronger, but C+A still show better location

N

C

C+G

C+A

C+B

summary and conclusions
Summary and Conclusions
  • COSMIC-IIA gives a much more uniform data distribution globally, compared with COSMIC-IIB.
  • Data density is important for typhoon prediction:
    • FORMOSAT-3: < 1 over 500 km x 500 km
    • COSMIC-IIA: > 8 over 500 km x 500 km
    • COSMIC-IIB: < 4 over 500 km x 500 km
typhoon forecast improvements
Typhoon Forecast Improvements
  • We perform two-day data assimilation, followed with three-day forecast for FORMOSAT-3, COSMIC-IIA, and COSMIC-IIB.
  • Compared with the Control (without RO data) COSMIC-II gives far superior results.
summary and conclusions1
Summary and Conclusions
  • COSMIC-IIA also gives significantly better precipitation forecasts, in terms of rainfall intensity and distribution.
  • The Option A design will greatly benefit the prediction of severe weather events over the Taiwan area, including typhoon, Mei-Yu, and mesoscale convective systems.
data density for cosmic and cosmic ii options a b c and d
Data Density for COSMIC and COSMIC-II Options: A, B, C, and D

COSMIC

- 6 x 72o

COSMIC-IIA

- 8 x 72o + 4 x 24o

COSMIC-IIB

- 12 x 72o

COSMIC-IIC

- 6 x 72o + 6 x 24o

COSMIC-IIB

- 4 x 72o + 8 x 24o

intensity forecast improvement against control conventional data forecast1
Intensity Forecast Improvement against control (conventional data) forecast
  • Intensity: C+D ~ C+C ~ C+A > C+B > C+G > (C) in evident

Percentage of improvement of intensity forecast

track forecast errors improvement against control conventional data forecast1
Track Forecast ErrorsImprovement against control (conventional data) forecast
  • Track forecast: C+A ~ C+D > C+C > C+B > C+G > (C) in evident

Percentage of improvement of track forecast

6 hour integrated precipitation
6 hour Integrated Precipitation

N

C+G

C+A

C+B

C+C

C+D

2A: 8x72 + 4x24, 2B: 12x72 + 0x24, 2C: 6x72 + 6x24, 2D: 4x72 + 8x24

future work
Future Work
  • Additional cases that affect Taiwan area:
    • Sinlaku (2008), Jangmi (2008), and other T-PARC and U.S. cases
    • Mei-Yu convective systems and heavy rainfall events
  • More realistic simulation of observations:
    • Ray tracing simulation of RO observations
    • Take into account available ground stations, and data latency
  • Use different data assimilation systems:
    • Global and Regional NCEP GSI system
    • WRF/DART ensemble data assimilation system
  • Collaborate with NCEP and ECMWF on global OSSEs and observing system experiments (OSE).
the cosmic team
The COSMIC Team

Bill Kuo: P.I. on OSSE Study

Ted Iwabuchi: WRF-3D-Var and Forecast

Bill Schreiner: Mission simulation

Zaizhong Ma: Observation simulations

Tae-Kwon Wee: Nature run

Yong-Run Guo: WRF-Var and Obs. Simulation

This work is funded by Dr. Jay Fein at NSF.