Objective Assessment of the Information Content of Visible and Infrared Radiance Measurements for Cloud Microphysical Property Retrievals over the Global Oceans. Part I: Liquid Clouds

• Published in: Journal of applied meteorology (1988) 2006-01, Vol.45 (1), p.20-41
• Main Authors: L’Ecuyer, Tristan S., Gabriel, Philip, Leesman, Kyle, Cooper, Steven J., Stephens, Graeme L.
• Format: Article
• Language: English
• Subjects: Algorithms; Climate change; Climate studies; Cloud physics; Clouds; Earth, ocean, space; Error rates; Exact sciences and technology; External geophysics; Geophysics. Techniques, methods, instrumentation and models; Information content; Information retrieval noise; Liquids; Measurement; Meteorology; Oceans; Physical properties; Radiance; Radiative transfer; Supernova remnants; Water vapor; Wavelengths
• ISSN: 1558-8424; 0894-8763; 1558-8432; 1520-0450
• DOI: 10.1175/JAM2326.1

The importance of accurately representing the role of clouds in climate change studies has become increasingly apparent in recent years, leading to a substantial increase in the number of satellite sensors and associated algorithms that are devoted to measuring the global distribution of cloud properties. The physics governing the radiative transfer through clouds is well understood, but the impact of uncertainties in algorithm assumptions and the true information content of the measurements in the inverse retrieval problem are generally not as clear, making it difficult to determine the best product to adopt for any particular application. This paper applies information theory to objectively analyze the problem of liquid cloud retrievals from an observing system modeled after the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument currently operating on theAquaandTerraplatforms. It is found that four diagnostics—the retrieval error covariance, the information content, the number of degrees of freedom for signal, and the effective rank of the problem—provide a rigorous test of an observing system. Based on these diagnostics, the combination of the 0.64- and 1.64-μm channels during the daytime and the 3.75- and 11.0-μm channels at night provides the most information for retrieving the properties of the wide variety of liquid clouds modeled. With an eye toward developing a coherent representation of the global distribution of cloud microphysical and radiative properties, these four channels may be integrated into a suitable multichannel inversion methodology such as the optimal estimation or Bayesian techniques to provide a common framework for cloud retrievals under varying conditions. The expected resolution of the observing system for such liquid cloud microphysical property retrievals over a wide variety of liquid cloud is also explored.