GOES and Tropical Systems

Meteo 415

Fall 2007

92 landfalls since 1950: Cat 1: 37 Cat 2: 19

Cat 3: 27 Cat 4: 7 Cat 5: 2

Added Dennis, Emily, Katrina, Rita, Wilma from 2005

Much, much more than just pretty pictures …

Tropical Applications

Satellite-derived winds and analyses

Indispensable for tropical forecasters

• Dvorak Method

• Sea-Surface temperatures

• El Nino Monitoring

• Sounder data

Low-mid level infrared winds

Mid-upper level water vapor and infrared winds

Low-level visible winds

Improvements in tropical cyclone track forecasts due to inclusion of satellite-derived winds (Soden et.al. 2001).

Root mean square error between GOES winds and radiosonde winds (Rao et.al. 2002.

Impact of GOES-derived winds

“Satellite Winds” keyword search of AMS journals: (30+ hits)

Qingnong Xiao, X. Zou, M. Pondeca, M. A. Shapiro and C. Velden. 2002: Impact of GMS-5 and GOES-9 Satellite-Derived Winds on the Prediction of a NORPEX Extratropical Cyclone.

Jason P. Dunion, Samuel H. Houston, Christopher S. Velden and Mark D. Powell. 2002: Application of Surface-Adjusted GOES Low-Level Cloud-Drift Winds in the Environment of Atlantic Tropical Cyclones. Part II: Integration into Surface Wind Analyses.

P. Anil Rao, Christopher S. Velden and Scott A. Braun. 2002: The Vertical Error Characteristics of GOES-Derived Winds: Description and Experiments with Numerical Weather Prediction.

Brian J. Soden, Christopher S. Velden and Robert E. Tuleya. 2001: The Impact of Satellite Winds on Experimental GFDL Hurricane Model Forecasts.

M. Tomassini, G. Kelly and R. Saunders. 1999: Use and Impact of Satellite Atmospheric Motion Winds on ECMWF Analyses and Forecasts.

Christopher S. Velden, Christopher M. Hayden, Steven J. Nieman, W. Paul Menzel, Steven Wanzong and James S. Goerss. 1997: Upper-Tropospheric Winds Derived from Geostationary Satellite Water Vapor Observations

Suzanne Dickinson and Robeitt A. Brown. 1996: A Study of Near-Surface Winds in Marine Cyclones Using Multiple Satellite Sensors.

C.M. Kishtawal, Sujit Basu and F.C. Pandey. 1996: An Algorithm for Retrieving Vertical Wind Profiles from Satellite-Observed Winds over the Indian Ocean Using Complex EOF Analysis.

Christopher S. Velden, Christopher M. Hayden, W. Paul Menzel, James L. Franklin and James S. Lynch. 1992: The Impact of Satellite-derived Winds on Numerical Hurricane Track Forecasting.

Robert A. Brown and Gad Levy. 1986: Ocean Surface Pressure Fields from Satellite-Sensed Winds.

Upper-level convergence

Low-level divergence (tendency of air to come together or spread apart)

Wind shear

Wind shear tendency

Low-level vorticity (spin)

The seeds of tropical

cyclones

2004 Hurricane season

Imagery and satellite winds/analyses also available for Pacific and Indian Oceans

Hurricane “Catarina”

Pinwheel structure of the eye

Isabel 2003

Wilma

HURRICANE IVAN DISCUSSION NUMBER 12NWS TPC/NATIONAL HURRICANE CENTER MIAMI FL11 AM EDT SUN SEP 05 2004

IVAN IS STRENGTHENING RATHER RAPIDLY AT THIS TIME. THE EYE IS BECOMING BETTER DEFINED ON THE VISIBLE IMAGERY AND DVORAK INTENSITY ESTIMATES SUPPORT AT LEAST 75 KT FOR THE CURRENT INTENSITY. THIS MAKES IVAN THE STRONGEST TROPICAL CYCLONE FOR SUCH A LOW LATITUDE IN THE ATLANTIC BASIN RECORDS … ALL PARAMETERS SEEM TO BE IN PLACE FOR IVAN TO CONTINUE STRENGTHENING...AND THERE IS A HIGH LIKELIHOOD THAT THIS WILL BECOME THE SEASON'S FOURTH MAJOR HURRICANE.

Dvorak Method – a statistical system using observed satellite cloud patterns (both visible and infrared) to estimate a tropical cyclone's strength.

Main tool for determining tropical cyclone strength when out of range of reconnaissance aircraft.

Dvorak Method

Sea-Surface temperatures

14th Conference on Satellite Meteorology and Oceanography (Feb 1, 2006)

Geostationary Sea Surface Temperature Products (Current and Future): Eileen Maturi, NOAA/NESDIS, Camp Springs, MD; and A. Harris, C. J. Merchant, X. Li

The NOAA Office of Satellite Data Processing and Distribution is generating operational sea surface temperature (SST) retrievals from GOES-9/10 and 12 satellite imagers … allowing the acquisition of high temporal SST retrievals from 110 E to 30 W. Combined with data from the European Meteosat series of satellites, Japanese MTSAT-1R and the Chinese FY2C, we can now determine the diurnal cycle of SST throughout most of the world's oceans. This is an important capability for the generation of a new global high resolution SST analysis …

The GOES-SST products generated from these algorithms include hourly regional sectors and 3-hourly hemispheric imagery, 24 hour merged composites and the new combined POES/GOES 10-km resolution SST analysis. Other GOES-SST related activities that are ongoing include … risk reduction studies for the upcoming GOES-R program.

data / data / data

El Nino / La Nina monitoring

Memorable tropical systems affecting Delaware Valley

Ocean City, NJ August 1933

Tem

ple

Uni

vers

ity U

rban

Arc

hive

s

“Chesapeake-Potomac” hurricane, 4th Street approach to boardwalk

Margate City September 1944

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ple

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rban

Arc

hive

s

Hurricane Hazel October 1954

Tem

ple

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ity U

rban

Arc

hive

s N

atio

nal

Wea

the

r S

ervi

ce

Hurricane Connie August 1955

Tem

ple

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rban

Arc

hive

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Hurricane Diane August 1955

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ple

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rban

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hive

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Hurricane Agnes

June 1972 Tem

ple

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rban

Arc

hive

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Hurricane Edouard

August 1996

8-31-96, 21Z: Hurricane Watch from Cape Lookout, NC to

Plymouth, MA

Actual vs. Forecasted Track (as of 8/31/96)

over Labor Day weekend

12Z August 31, 1996

References

GOES Project Science: http://rsd.gsfc.nasa.gov/goes/

14th Conference on Satellite Meteorology and Oceanography (Feb 1, 2006)Geostationary Sea Surface Temperature Products (Current and Future): Eileen Maturi, NOAA/NESDIS, Camp Springs, MD; and A. Harris, C. J. Merchant, X. Li

Space Science and Engineering Center, Univ. Wisconsin

J. Nese and G. Schwartz, The Philadelphia Area Weather Book, Temple University Press, 2002.

Urban Archives, Temple University Library

Brian J. Soden, Christopher S. Velden and Robert E. Tuleya. 2001: The Impact of Satellite Winds on Experimental GFDL Hurricane Model Forecasts, Mon. Wea. Rev. 129.

P. Anil Rao, Christopher S. Velden and Scott A. Braun. 2002: The Vertical Error Characteristics of GOES-Derived Winds: Description and Experiments with Numerical Weather Prediction, J. Applied Meteorology, 41.