the impact of gps radio occultation data on the analysis and prediction of tropical cyclones
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The Impact of GPS Radio Occultation Data on the Analysis and Prediction of Tropical Cyclones. Bill Kuo UCAR. GPS RO observations advantages for tropical cyclone prediction. - PowerPoint PPT PresentationTRANSCRIPT
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The Impact of GPS Radio Occultation Data on the Analysis and Prediction of Tropical
Cyclones
Bill KuoUCAR
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GPS RO observations advantages for tropical cyclone prediction
• There are considerable uncertainties in global analyses over data void regions (e.g., where there are few or no radiosondes), despite the fact that most global analyses now make use of satellite observations.
• GPS RO missions (such as COSMIC) can be designed to have globally uniform distribution (not limited by oceans, or high topography).
• The accuracy of GPS RO is compatible or better than radiosonde, and can be used to calibrate other observing systems.
• GPS RO observations are of high vertical resolution and high accuracy. • GPS RO is an active sensor, and provides information that other satellite
observing systems could not provide• GSP RO provide valuable information on the 3D distribution of moisture
over the tropics, which is important for typhoon prediction.
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Challenges for Tropical Cyclone Prediction
• Some of the operational GPS RO missions (e.g., METOP/GRAS) do not provide much data in the lower troposphere.
• There are still significant uncertainties and challenges for GPS RO to provide accurate measurement in the lowest 2 km of the tropical troposphere.
• How would this impact tropical cyclone prediction?
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COSMIC and Metop/GRAS ComparisonsWith ECMWF
Tropics Jul-Dec 2009
MetopCOSMIC
- Tropics, Jul-Dec 2009
- Metop/GRAS processed down to first data gap
- Metop/GRAS profiles have worse penetration than COSMIC
- Metop/GRAS BA’s negatively biased by several percent in lower troposphere
Metop/COSMIC Bending Angles
Courtesy of Bill Schreiner
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Hurrican Ernesto:
Formed: 25 August 2006
Reached Hurricane strength: 27 August
Dissipated: 1 September 2006
15:50 UTC 27 August 2006
Picture taken by MODIS, 250 m resolution
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4-Day Ernesto Forecasts with WRF-ARWForecast with GPS Forecast without GPSThe Actual Storm
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WRF/DART ensemble assimilation of COSMIC GPSRO soundings
• WRF/DART ensemble Kalman filter data assimilation system• 36-km, 32-members, 5-day assimilation• Assimilation of 178 COSMIC GPSRO soundings (with nonlocal obs
operator, Sokolovskiey et al) plus satellite cloud-drift winds• Independent verification by ~100 dropsondes.
178 COSMIC GPSRO soundings during 21-26 August 2006
From Liu et al. (2011)
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Verification of WRF/DART analysis by about 100 dropsondes during the Ernesto genesis stage.
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2-hour Forecast Difference of GPSonly-NODA (700 hPa)
00Z 24 August
Water vapor 06Z 23 August Wind
00Z 25 August Ernesto’s genesis time
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2-hour Water Vapor Differences (700 hPa)Only - NODA 06Z 23 August Only6km - NODA
00Z 24 August
00Z 25 August Ernesto’s genesis time
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48h-forecast of SLP (starting at 00UTC 25 August)
August 2006
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Summary of Ernesto Study
• Assimilation of GPS RO data adds moisture in the lower troposphere, and produces noticeable wind increments, consistent with the convective environment.
• GPS RO data in the lower troposphere is crucial for creating a favorable environment for hurricane genesis. If we miss the bottom 6km, we will fail to capture hurricane genesis. The bottom 2km is also important.
• Assimilation of GPS RO data produced improved analysis and subsequent forecasts both in terms of track and intensity.
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COSMIC-2 vs. COSMIC-1• 10,000 vs 2,000 soundings
per day• Better and phase-steerable
antenna• Advanced receiver (Tri-G) Will
track all GNSS and additional radiometric signals (GPS, GLONASS, Galileo, Compass, and DORIS)
• Improved retrieval and data assimilation algorithms
All of this implies much greater impact on science andoperational forecasting, Including tropical cyclones andheavy rainfall
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From August 6 to 10, 2009, extraordinary rainfall was brought over Taiwan by Typhoon Morakot, breaking 50 year’s precipitation record, causing a loss of more than 700 people and estimated property damage exceeding US$3.3 billion
Observed Rainfall of Typhoon Morakot (2009)
Typhoon Morakot (2009)Max. 24-h gauge 1504 mmMax. 96-h gauge 2874mm
at Chiayi County (windward slope of CMR)
Accumulated rainfall:(a) 96-h on August 6-10(b) 24-h on August 8-9
* Objective analysis ~450 automatic stations
24-h rain world record 1825 mm
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WRF/DART Analyses and Forecasts for Morakot (2009)
• Experiments performed using CWB operational configuration• Control (with GPS RO):
CWB operational observations including TC BOGUS data, 6-hourly analysis cycle
• NOGPS:Remove the GPS RO data from the control run.
• Continuous assimilations from 12UTC Aug. 3, 2009 through 00UTC 6 August on the CWB 45-km grid, based on NCEP GFS analysis.
• Subsequent 16 member ensemble forecast using CWB 45/15/5 km operational configuration
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12 UTC 6 August (12hr Fcst)
GPS
GPS – No GPS EC
No GPS
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Forecast initialized at 00 UTC 6 August
With GPS NO GPS
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Forecast initialized at 00 UTC 6 August
With GPS NO GPS
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48hr Rain Forecast (August 7-8 00Z)
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72hr Rain Forecast (August 8-9 00Z)
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96hr Rain Forecast (August 9-10 00Z)
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00 UTC 6 August (Analysis)
GPS No GPS
ECGPS – No GPS
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12 UTC 7 August (36hr Fcst)
GPS No GPS
ECGPS – No GPS
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12 UTC 8 August (60hr Fcst)
GPS No GPS
ECGPS – No GPS
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FORMOSAT-7/COSMIC-2 SoundingsGPS and GLONASS
(6@72°, 6@24°)
1 hour
6 hour
3 hour
24 hour
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Typhoon Forecast Improvements• We perform two-day data assimilation, followed with
three-day forecast for COSMIC-1 and COSMIC-2.• Compared with the Control (without RO data)
COSMIC-2 gives far superior results.
Intensity forecast Track forecast
COSMIC-1 8.1 25.0
COSMIC-2 45.4 65.4