Correction of Thin Cirrus Absorption Effects in Landsat 8 Thermal Infrared Sensor Images Using the Operational Land Imager Cirrus Band on the Same Satellite Platform.

Data from the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) instruments onboard the Landsat 8 and Landsat 9 satellite platforms are subject to contamination by cloud cover, with cirrus contributions being the most difficult to detect and mask. To help address this issue, a cirrus detection channel (Band 9) centered within the 1.375-µm water vapor absorption region was implemented on OLI, with a spatial resolution of 30 m. However, this band has not yet been fully utilized in the Collection 2 Landsat 8/9 Level 2 surface temperature data products that are publicly released by U.S. Geological Survey (USGS). The temperature products are generated with a single-channel algorithm. During the surface temperature retrievals, the effects of absorption of infrared radiation originating from the warmer earth's surfaces by ice clouds, typically located in the upper portion of the troposphere and re-emitting at much lower temperatures (approximately 220 K), are not taken into consideration. Through an analysis of sample Level 1 TOA and Level 2 surface data products, we have found that thin cirrus cloud features present in the Level 1 1.375-µm band images are directly propagated down to the Level 2 surface data products. The surface temperature errors resulting from thin cirrus contamination can be 10 K or larger. Previously, we reported an empirical and effective technique for removing thin cirrus scattering effects in OLI images, making use of the correlations between the 1.375-µm band image and images of any other OLI bands located in the 0.4-2.5 µm solar spectral region. In this article, we describe a variation of this technique that can be applied to the thermal bands, using the correlations between the Level 1 1.375-µm band image and the 11-µm BT image for the effective removal of thin cirrus absorption effects. Our results from three data sets acquired over spatially uniform water surfaces and over non-uniform land/water boundary areas suggest that if the cirrus-removed TOA 11-µm band BT images are used for the retrieval of the Level 2 surface temperature (ST) data products, the errors resulting from thin cirrus contaminations in the products can be reduced to about 1 K for spatially diffused cirrus scenes.

The VIIRS Cirrus Reflectance Algorithm.

The VIIRS instrument (Visible Infrared Imaging Radiometer Suite) on board the SNPP (Suomi National Polar-orbiting Partnership) satellite contains 11 narrow channels (M1-M11) in the 0.4-2.5 µm solar spectral region. The M9 channel is specifically designed for detecting thin cirrus clouds. It is centered at 1.378 µm with a width of 15 nm, which is located within a strong atmospheric water vapor band absorption region. In comparison with the corresponding MODIS Channel 26, the VIIRS M9 channel is narrower and more sensitive for cirrus detections. Because the radiances of the M9 channel over cirrus pixels are subjected to absorption by atmospheric water vapor molecules above and within the cirrus clouds, the water vapor absorption effect needs to be properly taken into consideration when using the M9 channel for quantitative removal of cirrus effects in other VIIRS channels in the 0.4-2.5 µm spectral range. In this article, we describe in detail an empirical technique for the retrieval of cirrus reflectances in the visible and near-IR (VNIR, 0.4-1.0 µm), where ice particles within cirrus clouds have negligible absorption effects, and in shortwave IR (SWIR, 1.0-2.5 µm) where ice particles' absorption effects are observed. The descriptions include all elements leading to the development of the operational VIIRS cirrus reflectance algorithm, the journal literature backing up the approach, theoretical descriptions of the algorithm's physics and mathematical background, and sample retrieval results from the VIIRS data. The SNPP VIIRS cirrus reflectance data products from 1 March 2012 to the present are available from a NASA data center.

Laboratory measurements of HDO/H2O isotopic fractionation during ice deposition in simulated cirrus clouds.

The stable isotopologues of water have been used in atmospheric and climate studies for over 50 years, because their strong temperature-dependent preferential condensation makes them useful diagnostics of the hydrological cycle. However, the degree of preferential condensation between vapor and ice has never been directly measured at temperatures below 233 K (-40 °C), conditions necessary to form cirrus clouds in the Earth's atmosphere, routinely observed in polar regions, and typical for the near-surface atmospheric layers of Mars. Models generally assume an extrapolation from the warmer experiments of Merlivat and Nief [Merlivat L, Nief G (1967) Tellus 19:122-127]. Nonequilibrium kinetic effects that should alter preferential partitioning have also not been well characterized experimentally. We present here direct measurements of HDO/H2O equilibrium fractionation between vapor and ice ([Formula: see text]) at cirrus-relevant temperatures, using in situ spectroscopic measurements of the evolving isotopic composition of water vapor during cirrus formation experiments in a cloud chamber. We rule out the recent proposed upward modification of [Formula: see text], and find values slightly lower than Merlivat and Nief. These experiments also allow us to make a quantitative validation of the kinetic modification expected to occur in supersaturated conditions in the ice-vapor system. In a subset of diffusion-limited experiments, we show that kinetic isotope effects are indeed consistent with published models, including allowing for small surface effects. These results are fundamental for inferring processes on Earth and other planets from water isotopic measurements. They also demonstrate the utility of dynamic in situ experiments for studying fractionation in geochemical systems.

Using Active Remote Sensing to Evaluate Cloud-Climate Feedbacks: a Review and a Look to the Future.

Uncertainty in the equilibrium climate sensitivity (ECS) of the Earth continues to be large. Aspects of the cloud feedback problem have been identified as fundamental to the uncertainty in ECS. Recent analyses have shown that changes to cloud forcing with climate change can be decomposed into contributions from changes in cloud occurrence that are proportional to globally averaged temperature change and changes associated with rapid adjustments in the system that are independent of changes to globally averaged surface temperature. Together these responses enhance warming due to (1) cloud feedback from increasing cloud altitude by upper tropospheric clouds and (2) decreases in cloud coverage by marine boundary layer clouds. We argue that active remote sensing from space can play a unique and crucial role in constraining our understanding of these separate phenomena. For 1, the feedback associated with changing tropical cirrus is predicted to emerge from the statistical noise of the climate system within the next one to two decades. However, active remote sensing will need to continue for that signal to be observed since accurate placement of these clouds in the vertical dimension is necessary. For 2, the processes associated with changes to marine boundary layer clouds have been linked to the coupling between cloud and precipitation microphysics and air motions over remote ocean basins where precipitation formation in shallow convection is modulated by changes to aerosols and thermodynamics. Exploiting the synergy in combined active and passive remote sensing is likely one of the only ways of constraining our evolving theoretical understanding of low-level cloud processes as represented in cloud-resolving models and for validating global-scale models.