Synergistic Use of Visible Stereoscopy and Thermal Infrared Techniques for Estimating Global Two-layered Cloud Properties from Terra

Cloud-top height (CTH) is an Essential Climate Variable, with our longest and most stable single-platform satellite record provided by Terra's Multi-angle Imaging Spectroradiometer (MISR), which employs stereoscopy on visible radiation, and the Moderate Resolution Imaging Spectroradiometer (MODIS), which employs either a CO2-slicing or an 11 μm-brightness temperature technique, in the infrared, depending on the estimated pressure at cloud-top. While operational passive sensors retrieve a single CTH for a given field-of-view, having two separate sensors with varying capabilities on the same platform has been utilized to retrieve discrete cloud layer heights (and the optical properties of these layers), in the crucially important case of a thin cirrus overlying a thick low water cloud. Our new algorithm makes use of the sensitivity of the CO2 slicing channels from MODIS to thin cirrus and the sensitivity of MISR's stereoscopic retrieval to the lower, more textured clouds to retrieve the CTH of both cloud layers.

Upon validation of the new dataset against space-borne lidar, we find ~75% increase in CTH accuracy for high cloud heights over MODIS CTH. This improvement leads to lidar-like distribution of high cloud amounts from passive sensors. Furthermore, improved cloud macrophysical retrievals propagate to ~75% increase in accuracy in both infrared emissivity and visible optical depth for the new dataset over MODIS. 87% of residuals from our method fall within 95% CI of modeled errors, achieving reasonable error closure. Our improved 2-layer retrievals are also found to improve simulated longwave radiative fluxes by 5-45 W m-2 over 1-layered retrievals.

Our novel technique is easy to operationalize over the 20-year Terra record, which can lead to a unique 2-layered cloud climatology from a morning orbit and refined estimates of CTH variability in recent decades. Accurate estimates of CTH variation are relevant for understanding how clouds have responded to climate change and in applying empirical constraints to climate modeling uncertainties. While a space-based lidar is more suited to detect such trends, existing lidar records are shorter than required for the task, and also lack swath coverage. These reasons, coupled with its remarkable orbital stability makes Terra uniquely suited to the task.