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Retrieving Cloud Properties for Multilayered Clouds Using Simulated GOES-R Data

Retrieving Cloud Properties for Multilayered Clouds Using Simulated GOES-R Data. Fu-Lung Chang 1 , Patrick Minnis 2 , Bing Lin 2 , Rabindra Palikonda 3 , Mandana Khaiyer 3 , Sunny Sun-Mack 3 , Ping Yang 4

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Retrieving Cloud Properties for Multilayered Clouds Using Simulated GOES-R Data

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  1. Retrieving Cloud Properties for Multilayered Clouds Using Simulated GOES-R Data Fu-Lung Chang1, Patrick Minnis2, Bing Lin2, Rabindra Palikonda3, Mandana Khaiyer3, Sunny Sun-Mack3, Ping Yang4 1) National Institute of Aerospace, Virginia, USA, 2) NASA Langley Research Center, 3) Science System Applications Inc., 4) Texas A&M University GOES-12 (U.S. EAST) Starting with the U.S. GOES-12 (GOES-EAST) in a series of new GOES imagery satellites, a 13.3-µm CO2-absorption channel has been added to replace the original 12-µm channel. Meteosat-8 SEVIRI (Europe) The European new geostationary satellites, starting with Meteosat-8, Meteosat Second Generation (MSG) SEVIRI, also add a 13.4-µm CO2 absorbing channel. Introduction This study presents a multi-spectral satellite retrieval algorithm for retrieving the multi-layered cloud properties. The retrievals are presented by applying to current satellite data available from GOES-12, -13, Meteosat-8, -9, and MODIS. The GOES-R and new series of satellite imagers have all added at least one (13.3-µm) CO2-absorbing channel to allow for an enhanced CO2-multilayered cloud retrieval algorithm. Case Study: 2007/04/04 GOES-12 (UTC 1745) & MODIS (UTC 1750) Case Study: 2007/04/04 Meteosat-8 SEVIRI (UTC 1300) & MODIS (UTC 1250) GOES12 visible image GOES12 infrared image SEVIRI visible image SEVIRI infrared image • Outline • Introduce an enhanced CO2-multilayer cloud retrieval algorithm. • Apply the enhanced algorithm to the GOES-12 imagery data. • Apply the enhanced algorithm to the Meteosat-8 SEVIRI imagery data. • Apply the algorithm and compare to the MODIS data. GOES12 cloud top Zc MYD06 cloud top Zc SEVIRI cloud top Zc MYD06 cloud top Zc Algorithm A brief description of the enhanced CO2-VISST-Multilayer algorithm: An enhanced 11µm/13.3µm CO2-cloud retrieval technique that corrects for the underlying lower clouds in the multi-layer cloud situation. An iteration is applied: The MODIS 11/13.3-µm-only retrieved cloud top Zc The MODIS 11/13.3-µm-only retrieved cloud top Zc GOES12 multilayer ID SEVIRI multilayer ID The MODIS 11/13.3-µm-only retrieved multilayer ID The MODIS 11/13.3-µm-only retrieved multilayer ID Lower cloud top Zc Lower cloud top Zc Summary • The 11/13.3-µm-CO2 absorbing technique improves the geostationary satellite retrieval for uppermost cloud top height. • The integrated CO2-VISST-Multilayer algorithm enhanced the retrievals of multi-layered cloud properties. • The algorithm is applicable to the geostationary satellites like GOES-12, GOES-13, MSG-SEVIRI, MTG-SEVIRI, and future GOES-R, and to polar-orbiting MODIS instruments as well. • Future work includes the algorithm refinements and retrieval validations. REFERENCES: Chang, F.-L., and Z. Li, 2005: A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J. Atmos. Sci., 62, 3993–4009. Minnis et al., 1995: CERES Algorithm Theoretical Basis Document; Minnis, P., and Co-Authors, 1998: Parameterization of reflectance and effective emittance for satellite remote sensing of cloud properties. J. Atmos. Sci., 55, 3313-3339.

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