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An anomaly correlation skill score for the evaluation of the performance of Hyperspectral Infrared Sounders

Show simple item record Aumann, Hartmut H. Manning, Evan Barnet, Chris Maddy, Eric Blackwell, William 2014-09-03T17:44:05Z 2014-09-03T17:44:05Z 2009-08-02
dc.identifier.citation SPIE Optical Engineering and Applications, San Diego, California, August 2-6, 2009 en_US
dc.identifier.clearanceno 09-2191
dc.description.abstract With the availability of very accurate forecasts, the metric of accuracy alone for the evaluation of the performance of a retrieval system can produce misleading results. A useful characterization of the quality of a retrieval system and its potential to contribute to an improved weather forecast is its skill, which we define as the ability to make retrievals of geophysical parameters which are closer to the truth than the six hour forecast, when the truth differs significantly from the forecast. We illustrate retrieval skill using one day of AMSU and AIRS data with three different retrieval algorithms, which result in retrievals for more than 90% of the potential retrievals under clear and cloudy conditions. Two of the three algorithms have better than 1 K rms “RAOB quality” accuracy on the troposphere, but only one has skill between 900 and 100 mb. AIRS was launched on the EOS Aqua spacecraft in May 2002 into a 705 km polar sun-synchronous orbit with accurately maintained 1:30 PM ascending node. Essentially uninterrupted data are freely available since September 2002. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2009 en_US
dc.subject Atmospheric Infrared Sounder (AIRS) en_US
dc.subject Temperature en_US
dc.subject retrieval en_US
dc.subject humidity en_US
dc.subject cloud clearing en_US
dc.title An anomaly correlation skill score for the evaluation of the performance of Hyperspectral Infrared Sounders en_US
dc.type Presentation en_US

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