Igor N. Polonsky

Wide-Angle Imaging Lidar Deployment at the ARM Southern Great Plains Site: Intercomparison of Cloud Property Retrievals

Abstract The Wide-Angle Imaging Lidar (WAIL), a new instrument that measures cloud optical and geometrical properties by means of off-beam lidar returns, was deployed as part of a multi-instrument campaign to probe a cloud field at the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site on 25 March 2002. WAIL is designed to determine physical and geometrical characteristics using the off-beam component of the lidar return that can be adequately modeled within the diffusion approximation. Using WAIL data, the extinction coefficient and geometrical thickness of a dense cloud layer is estimated, from which optical thickness is inferred. Results from the new methodology agree well with counterparts obtained from other instruments located permanently at the SGP ARM site and from the WAIL-like airborne instrument that flew over the site during our observation period.

Space-time Green functions for diffusive radiation transport, in application to active and passive cloud probing

Clouds are a feast for the eye but, when contemplating their fluid beauty, it is important — at least for scientists — to bear in mind that they are also key elements of the Earth’s climate system. They are indeed the first-order regulators of the intake in solar energy: What portion goes back to space? What reaches the surface (then warms the ground, drives photosynthesis, etc.)? Clouds also contribute strongly to the vertical distribution of solar heating and, from there, the thermal balance of the atmosphere. These are well-known and relatively well-understood/modeled climate roles of clouds, as can be expected for such naturally occurring components of the atmosphere. We note that these roles involve radiative transfer across the electromagnetic spectrum. What is far less understood about clouds is how they interact microphysically, chemically and thermo-hydrodynamically, with other natural and anthropogenic constituents, especially aerosols. These are known as cloud feedback mechanisms in the parlance of climate science, and have been identified as the single most resilient roadblock in the way of reducing uncertainty in future climate prediction [1], an enterprise that relies heavily on models to explore various scenarios in global greenhouse gas emissions.

Identification and Correction of Residual Image in the

The detector used for the O2 A-band (0.76 μm) of the National Aeronautics and Space Administrations Orbiting Carbon Observatory (OCO) employed a HyViSI Hawaii-1RG sensor, operating at 180 K in a rolling read-out mode. During the thermal vacuum testing of the flight instrument, it was discovered that the detector exhibited residual images that lasted for many seconds and were of sufficient magnitude to compromise the mission objectives. Independent testing of flight-spare detectors revealed that the problem was common to all and was not simply a fault of the flight detector. The residual image was found to depend upon even-order derivatives of the spectrum, and its decay was a function of the number of frames rather than time. An empirical model was developed, which represented the measured spectrum in terms of the true spectrum and a history of all previous changes in the spectra. On the basis of the model, an algorithm was devised to correct spectra for the effects of residual image, using a time-marching analysis of a history of previous spectra. The algorithm was tested with spectra acquired during the second thermal vacuum test of OCO and was found to reduce the effect of residual image to almost the noise level of the detector. Numerical simulations indicate that residual image has a negligible impact on retrieved concentrations of O2 and CO2 once the spectra have been corrected.

\hbox{O}_{2}

Abstract High-resolution spectra of reflected sunlight in the 2-μm absorption band of CO2 are simulated at the top of the atmosphere using cloud profiles and particle sizes from CloudSat analyzed meteorology from ECMWF, surface bidirectional distribution functions over land derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), and a facet model of ocean reflectance. It is argued that in clear sky the photons will follow the direct path from sun to surface to satellite, because Rayleigh scattering is negligible at 2 μm, so the distribution of photon pathlengths will be a δ function. A proxy for the photon pathlength distribution under any sky condition is recovered from the high-resolution spectrum by representing the distribution as a weighted sum of δ functions. Scenes are classified as clear or cloudy according to how closely the distribution approximates the ideal single δ function for the direct path. The algorithm has an efficiency of approximately 75%, meaning that 25% of the clear...

A-Band of the Orbiting Carbon Observatory

Abstract Measurement of XCO2, the column-averaged mole fraction of CO2, using reflected sunlight in the near-infrared bands of CO2, is strongly influenced by photons that are scattered in the atmosphere because scattering can either decrease or increase the mean pathlength compared with the direct path from the sun to the surface to the satellite. A very simple algorithm that can be used to compensate for the errors introduced by scattering is presented. The algorithm is based on the observation that the apparent optical path differences in selected pairs of channels in the weak CO2 band at 1.6 μm and the O2 A band at 0.76 μm are tightly correlated for large ensembles of scattering atmospheres. The number of tightly correlated pairs of channels is many hundreds for the bands measured by NASA’s Orbiting Carbon Observatory (OCO). The physical reasons for the correlation are that the mean photon pathlengths are comparable for the members of each pair of channels, and that the extinction profiles vary similar...

Feasibility of Cloud Screening Using Proxy Photon Pathlength Distributions Derived from High-Resolution Spectra in the Near Infrared

The second NASA Earth Venture Mission, Geostationary Carbon Cycle Observatory (GeoCarb), will provide measurements of atmospheric carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and solar-induced fluorescence (SIF) from Geostationary Orbit (GEO). The GeoCarb mission will deliver daily maps of column concentrations of CO2, CH4, and CO over the observed landmasses in the Americas at a spatial resolution of roughly 10 x 10 km. Persistent measurements of CO2, CH4, CO, and SIF will contribute significantly to resolving carbon emissions and illuminating biotic processes at urban to continental scales, which will allow the improvement of modeled biogeochemical processes in Earth System Models as well as monitor the response of the biosphere to disturbance. This is essential to improve understanding of the Carbon-Climate connection. In this paper, we introduce the instrument and the GeoCarb Mission, and we demonstrate the potential scientific contribution of the mission through a series of CO2 and CH4 simulation experiments. We find that GeoCarb will be able to constrain emissions at urban to continental spatial scales on weekly to annual time scales. The GeoCarb mission particularly builds upon the Orbiting Carbon Obserevatory-2 (OCO-2), which is flying in Low Earth Orbit.