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David W. Martin, Richard A. Kohrs, Frederick R. Mosher, Carlo Maria Medaglia, and Claudia Adamo

Abstract

The global convective diagnostic (GCD) is a bispectral (infrared and water vapor), day–night scheme for operationally mapping deep convection by means of geostationary satellite images. This article describes a test of GCD performance over tropical and subtropical waters near North America. The test consists of six cases, each involving a convective cloud complex. A seventh case treats convection over land. For each case, a map of deep convection was constructed from image pairs from Geostationary Operational Environmental Satellite-12 (GOES-12). Case by case and for all maritime cases together, the GCD map was compared with a convective parameter derived from the radar on the Tropical Rainfall Measuring Mission (TRMM), a polar-orbiting satellite. In general, each GCD map showed a bloblike feature. In each case, the radar convective pixels typically fell within the GCD blob. However, (except for the land case) the GCD predicted far too many convective pixels. In the maritime cases overprediction was reduced (without correspondingly impairing other measures of performance) by lowering the nominal GCD threshold. With this adjustment in place, for the six maritime cases taken individually, the GCD tended to yield more consistent results than did a monospectral (infrared) convective scheme. With the cases combined, at the lower threshold the GCD performed somewhat better than one of the more stable versions of the infrared scheme. Comparison with lightning events (also observed by TRMM) suggests the possibility of future improvement to the GCD through the incorporation of geostationary satellite observations of lightning.

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Steven D. Miller, Timothy L. Schmit, Curtis J. Seaman, Daniel T. Lindsey, Mathew M. Gunshor, Richard A. Kohrs, Yasuhiko Sumida, and Donald Hillger

Abstract

In 1967, at the dawn of the satellite era, the Applications Technology Satellite 3 (ATS-3) provided the first full-disk “true color” images of Earth. With its depiction of blue oceans, golden deserts, and green forestlands beneath white clouds, the imagery captured the iconic Blue Marble in a way that resonates strongly with human perception. After ATS-3, the standard fare of geostationary satellites entailed a single visible band with additional infrared spectral channels. While single-band visible satisfied the basic user requirements of daytime imagery, the loss of true-color capability and its inherent capability to distinguish myriad atmospheric and surface features via coloration left a notable void. Nearly half a century later, with the launch of Japan’s Himawari-8 in October 2014, there is once again a geostationary sensor—the Advanced Himawari Imager (AHI)—containing the multispectral visible bands required notionally for true color. However, it soon became apparent that AHI’s “green” band, centered at 0.51 μm, was not aligned with the chlorophyll reflectance signature near 0.55 μm. As a result, vegetation appears browner and deserts appear redder than legacy true-color imagery. Here, we describe a technique that attempts to mitigate these issues by blending information from a ref lective-infrared band at 0.86 μm to form a “hybrid” green band. When combining this method with Rayleigh corrections, AHI’s true-color performance is found to be consistent with that of the optimal 0.55-μm band, offering a stopgap solution adaptable to future satellites of similar design.

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