Statistics Of Arctic Cloud Downwelling Infrared Emissivity

Time series of optical depth of Arctic stratus clouds are investigated for scaling properties and biases with respect to a plane-parallel model. The study is based on 3 years of infrared spectrometer and microwave radiometer measurements made at the Atmospheric Radiation Measurement North Slope of Alaska site. Power spectra of radiance and radiance emissivity are found to indicate scaling with a spectral coefficient on the order of 5/3 over 0.5-10 hours, consistent with the Kolmogorov-Obukhov prediction [Kolmogorov, 1941] for three-dimensional turbulence. Irradiance emissivities inferred from the data set, using an independent column approximation and 6-hour time intervals, are further analyzed to find reduction factors for the same mean optical depth in a plane-parallel representation. These factors are estimated to average 0.82 in March and 0.48 in September but with a high degree of variability: The most inhomogeneous quarters of these data sets exhibit reduction factors of 0.57 (March) and 0.20 (September). Observed reduction factors for radiance and irradiance are found to depend primarily on the ratio of mean optical depth to variance, a result consistent with exact results for a gamma distribution of cloud thickness

Responsivity-based Criterion For Accurate Calibration Of Ftir Emission Spectra: Theoretical Development And Bandwidth Estimation

An analytical expression for the variance of the radiance measured by Fourier-transform infrared (FTIR) emission spectrometers exists only in the limit of low noise. Outside this limit, the variance needs to be calculated numerically. In addition, a criterion for low noise is needed to identify properly calibrated radiances and optimize the instrument bandwidth. In this work, the variance and the magnitude of a noise-dependent spectral bias are calculated as a function of the system responsivity (r) and the noise level in its estimate (sigma(r)). The criterion sigma(r)/r \u3c 0.3, applied to downwelling and upwelling FTIR emission spectra, shows that the instrument bandwidth is specified properly for one instrument but needs to be restricted for another

A responsitivity-based criterion for accurate calibration of FTIR spectra: theoretical development and bandwidth estimation

An analytical expression for the variance of the radiance measured by Fourier-transform infrared (FTIR) emission spectrometers exists only in the limit of low noise. Outside this limit, the variance needs to be calculated numerically. In addition, a criterion for low noise is needed to identify properly calibrated radiances and optimize the instrument bandwidth. In this work, the variance and the magnitude of a noise-dependent spectral bias are calculated as a function of the system responsivity (r) and the noise level in its estimate (? r ). The criterion ? r /

Representation Of A Nonspherical Ice Particle By A Collection Of Independent Spheres For Scattering And Absorption Of Radiation: 3. Hollow Columns And Plates

The ability of an assembly of spheres to represent scattering and absorption by a nonspherical ice crystal of the same volume-to-area (V/A) ratio was previously evaluated for convex shapes (circular cylinders and hexagonal prisms). Here we extend the comparison to indented and hollow prisms, which are common in ice clouds. In the equivalent-sphere representation, the crystal mass and surface area are both conserved. Internal surfaces as well as external surfaces contribute to the total surface area; in the model representation both become external surfaces of spheres. The optical depth tau of the model cloud is thus greater than that of the real cloud by the ratio A/4P, where A is the total area of the nonspherical particle and P is the orientation-averaged projected area. This ratio, which we call fluffiness,\u27\u27 is unity for convex shapes but may exceed 2 for clusters of hollow bullets. In effect, the scattering at interior surfaces of a hollow crystal becomes classified as multiple scattering in the model of ice spheres. Therefore, rather than directly comparing the asymmetry factor (g) and single-scattering albedo (omega(o)) of the hollow crystal to those of the equal-V/A sphere, it is more appropriate to compare the product tau(1 - g)omega(o), because this quantity largely determines the bulk radiative properties of the cloud. Errors in albedo, absorptance, and transmittance of ice clouds, caused by the equal-V/A representation, are presented for a range of aspect ratios, indentation depths, and ice-water paths at visible and near-infrared wavelengths

Representation Of A Nonspherical Ice Particle By A Collection Of Independent Spheres For Scattering And Absorption Of Radiation: 2. Hexagonal Columns And Plates

[1] A cloud of nonspherical ice particles may be represented in radiation models by a collection of spheres, in which the model cloud contains the same total volume of ice and the same total surface area as the real cloud but not the same number of particles. The spheres then have the same volume-to-area (V/A) ratio as the nonspherical particle. In previous work this approach was shown to work well to represent randomly oriented infinitely long circular cylinders for computation of hemispherical reflectance, transmittance, and absorptance. In this paper the results have been extended to hexagonal columns and plates using a geometric optics technique for large particles and finite-difference-time-domain theory (FDTD) for small particles. The extinction efficiency and single-scattering coalbedo for these prisms are closely approximated by the values for equal-V/A spheres across the ultraviolet, visible, and infrared from 0.2 to 25 mum wavelength. Errors in the asymmetry factor can be significant where ice absorptance is weak, at visible wavelengths for example. These errors are greatest for prisms with aspect ratios close to 1. Errors in hemispheric reflectance, absorptance, and transmittance are calculated for horizontally homogeneous clouds with ice water paths from 0.4 to 200,000 g m(-2) and crystal thicknesses of 1 to 400 mum, to cover the range of crystal sizes and optical depths from polar stratospheric clouds (PSCs) through cirrus clouds to surface snow. The errors are less than 0.05 over most of these ranges at all wavelengths but can be larger at visible wavelengths because of the ideal shapes of the prisms. The method was not tested for, and is not expected to be accurate for, angle-dependent radiances

Evaluation of Temperature-Dependent Complex Refractive Indices of Supercooled Liquid Water Using Downwelling Radiance and In-Situ Cloud Measurements at South Pole

Clouds have a large effect on the radiation budget and represent a major source of uncertainty in climate models. Supercooled liquid clouds can exist at temperatures as low as 235 K, and the radiative effect of these clouds depends on the complex refractive index (CRI) of liquid water. Laboratory measurements have demonstrated that the liquid-water CRI is temperature-dependent, but corroboration with field measurements is difficult. Here we present measurements of the downwelling infrared radiance and in-situ measurements of supercooled liquid water in a cloud at temperatures as low as 240 K, made at South Pole Station in 2001. These results demonstrate that including the temperature dependence of the liquid-water CRI is essential for accurate calculations of radiative transfer through supercooled liquid clouds. Furthermore, we show that when cloud properties are retrieved from infrared radiances (using the spectral range 500–1,200 cm−1) spurious ice may be retrieved if the 300 K CRI is used for cold liquid clouds (∼240 K). These results have implications for radiative transfer in climate models as well as for retrievals of cloud properties from infrared radiance spectra.publishedVersio

Radiative consequences of low-temperature infrared refractive indices for supercooled water clouds

Simulations of cloud radiative properties for climate modeling and remote sensing rely on accurate knowledge of the complex refractive index (CRI) of water. Although conventional algorithms employ a temperature independent assumption (TIA), recent infrared measurements of supercooled water have demonstrated that the CRI becomes increasingly ice-like at lower temperatures. Here, we assess biases that result from ignoring this temperature dependence. We show that TIA-based cloud retrievals introduce spurious ice into pure, supercooled clouds, or underestimate cloud thickness and droplet size. TIA-based downwelling radiative fluxes are lower than those for the temperature-dependent CRI by as much as 1.7 W m?2 (in cold regions), while top-of-atmosphere fluxes are higher by as much as 3.4 W m?2 (in warm regions). Proper accounting of the temperature dependence of the CRI, therefore, leads to significantly greater local greenhouse warming due to supercooled clouds than previously predicted. The current experimental uncertainty in the CRI at low temperatures must be reduced to properly account for supercooled clouds in both climate models and cloud property retrievals