https://alex-matus.github.io/tags/a-train-constellation/A-Train ConstellationHugoBlox Kit (https://hugoblox.com)en-usFri, 31 May 2019 00:00:00 +0000https://alex-matus.github.io/media/icon_hu_da05098ef60dc2e7.pnghttps://alex-matus.github.io/tags/a-train-constellation/https://alex-matus.github.io/publications/kernels/Fri, 31 May 2019 00:00:00 +0000https://alex-matus.github.io/publications/kernels/<p>This research establishes a framework for evaluating global climate feedbacks by replacing standard model-derived radiative kernels with observational profiles constructed from the A-Train satellite track.</p> <h3 id="key-innovations--framework-updates">Key Innovations &amp; Framework Updates</h3> <ul> <li><strong>Elimination of GCM Base-State Bias:</strong> Traditional climate sensitivity diagnostics inherit systematic discrepancies from model assumptions. This tool uses empirical vertical measurements to ensure a neutral diagnostic base state.</li> <li><strong>Active Sensor Synergy:</strong> Built upon high vertical-resolution measurements from the 2B-FLXHR-LIDAR multi-sensor product, mapping distinct layers of the atmosphere simultaneously.</li> <li><strong>Cloud Masking Corrections:</strong> Clarifies longwave feedback mechanics by mapping exactly how cloud layers interact with, mask, and structurally alter the flux signals of non-cloud climate variables.</li> </ul>