Harumi Isaka

Neural network retrieval of cloud parameters of inhomogeneous and fractional clouds: Feasibility study

One of the major issues of cloud parameter retrieval is how to optimize the improved observational capability of new radiometers to retrieve additional information about cloud characteristics. To investigate this problem, we developed a neural network approach for simultaneous retrieval of cloud parameters of inhomogeneous clouds with fractional cloud cover. We defined a simple inverse inhomogeneous cloud model with four parameters: mean optical depth, effective radius, relative cloud inhomogeneity, and fractional cloud cover. The retrieval algorithm, based on the use of a mapping neural network (MNN) with two hidden layers, was implemented and tested with synthetic multispectral reflectance data prepared for 2D clouds generated with a modified bounded cascade cloud model. We found that these cloud parameters could be retrieved from the moderate-resolution multispectral reflectance data with reasonable accuracy: for example with our data base, optical depth has a root mean square error of 1.7 for an ensemble of 1000 samples with optical depth up to 30. However, this accuracy depends on measurements errors and noises. A comparison with plan-parallel hypothesis shows the expected improvement of such an inhomogeneous cloud model. We show that the relevance of these cloud parameters is a function of the horizontal scale of averaging due to the net horizontal photon transport to and from adjacent cloud pixels. We tested the inclusion of ancillary data (reflectance of the neighbouring pixels) into the retrieval algorithm, and showed that the use of these ancillary data could partially correct the modeling error and significantly improve the performance of cloud parameter retrieval.

Effective radiative properties of bounded cascade nonabsorbing clouds: Definition of the equivalent homogeneous cloud approximation

In the present study we investigated the radiative properties of inhomogeneous nonabsorbing clouds under the Equivalent plane-parallel Homogeneous Cloud Approximation (EHCA), by using the one-dimensional (1-D) bounded cascade inhomogeneous clouds. The effective optical depth was defined under the EHCA by requiring the identity of the radiant flux components of the radiation budget between the inhomogeneous clouds and their equivalent homogeneous counterparts. Such requirement provides a rational framework to define the effective optical depth of the inhomogeneous nonabsorbing clouds. We analyzed the dependency of the effective optical depth on the horizontal scale of averaging and solar incidence angle and specified the conditions under which an inhomogeneous cloud segment could be treated as a plane-parallel homogeneous cloud. A parameterization of the effective optical depth was proposed as a function of the mean optical depth and a relative cloud inhomogeneity parameter. Finally, we compared the EHCA with the effective thickness approximation, both based on the definition of the effective optical depth, and discussed the difference between their respective effective optical depths.

Assessment of cloud optical parameters in the solar region: Retrievals from airborne measurements of scattering phase functions

A data set of approximately 60,000 airborne measurements of angular scattering coefficients was used to reproduce a representative set of both microphysical parameters and single light-scattering characteristics (angular scattering coefficient, asymmetry parameter, single-scattering albedo, and extinction coefficient) for three types of clouds. The measurements were limited to a wavelength of 0.8 mm and to 28 scattering angles near uniformly positioned from 15° to 155°. Microphysical and optical characteristics were computed at wavelengths of 0.8, 1.6, and 3.7 mm, which are needed for the direct and inverse modeling of radiative transfer. The estimation of these characteristics is achieved through cloud microphysical parameter retrievals, taking into account the variation of water droplet and ice crystal size as well as cloud phase composition. We present both average values and possible variability of microphysical and single-scattering characteristics for three types of clouds with respect to their particle phase composition (i.e., water droplets, mixed phase, and ice crystals in cloud). The variations are presented separately due to both random instrumental errors of optical measurements and possible changes in the microphysical parameters within a separated specific cloud category. The microphysical parameter retrievals are validated by comparison with collocated direct particle size distribution measurements. Additionally, the estimated single light-scattering characteristics are in reasonable agreement with those available from the literature.

Effective radiative properties of bounded cascade absorbing clouds: Definition of an effective single-scattering albedo

We applied the equivalent homogeneous cloud approximation (EHCA) to the bounded cascade inhomogeneous absorbing clouds and defined their effective radiative properties. It is found that we have to introduce an effective single-scattering albedo in addition to an effective optical depth to treat the inhomogeneous absorbing clouds under the plane-parallel homogeneous cloud assumption. For an inhomogeneous absorbing cloud, a pair of the effective parameters can be estimated from each one of three possible pairs taken from the area-averaged reflectance, transmittance and absorptance. We found that the behavior of these effective properties was quite similar to those observed for the inhomogeneous non absorbing clouds except that two effective parameters were to be examined instead of only one effective parameter for the nonabsorbing clouds. Empirical relations for both the effective optical depth and the single-scattering albedo were given as a function of the local mean optical depth and relative local cloud inhomogeneity. We showed that the effective single-scattering albedo could not be properly introduced under the effective thickness approximation (ETA), which indicates an important conceptual difference between the EHCA and the ETA. Finally, we discussed possible consequences of the effective single-scattering albedo, defined in this study, with respect to the anomalous absorption phenomenon.

Radiative transfer in multifractal clouds

We studied effects of the cloud inhomogeneity in subcloud scale on the reflectance, transmittance, and absorptance of two-dimensional, inhomogeneous clouds. We generated the inhomogeneous clouds as multifractal clouds with a lognormal multiplicative process. For such clouds, the information codimension C 1 is a measure of the cloud inhomogeneity. Radiative transfer through the multifractal clouds was computed with a discrete angle radiative transfer model. The average reflectance, transmittance, and absorptance of multifractal clouds with a given codimension were estimated as averages of 200 realizations. They were computed for different sets of the C 1 parameter, cloud total optical thickness, and asymmetry factor of cloud scatterers. An effective optical thickness of inhomogeneous clouds was defined empirically in the framework of a homogeneous, plane parallel cloud model. Consequently, computation of radiative flux in an inhomogeneous cloud could be transformed into that of an equivalent homogeneous, plane parallel cloud. For a two-dimensional, inhomogeneous, absorbing cloud we found that an inhomogeneous cloud absorbs generally less energy than its homogeneous counterpart. An exception was found for inhomogeneous clouds characterized by a small information codimension, a large cloud optical thickness, and a large single-scattering albedo and for which absorptance is much larger than for their homogeneous counterpart. However, this increase was less than 5% of the homogeneous cloud absorptance. The use of the effective optical thickness also enabled us to treat an inhomogeneous absorbing cloud as an equivalent homogeneous absorbing cloud and to estimate the radiative flux of the equivalent homogeneous cloud as an approximation to the one in the inhomogeneous cloud. We found no immediate need to conceive of a direct effect of the cloud inhomogeneity on the single-scattering albedo, as far as we considered this treatment as a first-order approximation. We discussed the use of the effective optical thickness in twostream radiative approximations. We also compared our results with those based on the independent pixel approximation.

Microphysical properties of mixed-phase & Ice clouds retrieved from In Situ airborne “polar nephelometer” measurements

In this paper we present microphysical properties of natural clouds retrieved from an airborne “Polar Nephelometer” measurements. The retrieval was done by means of an iterative inversion method, which is based on the bi-component (water droplets and ice crystals) representation of ice and mixed phase cloud composition. The present study shows that experimental scattering phase functions of ice crystals are characterized by high information content with respect to the aspect ratio of ice crystals which can be estimated in addition to their effective size distributions.

Molecular dissipation of turbulent fluctuations in the convective mixed layer part I: Height variations of dissipation rates

During the Limagne and Beauce experiments, the INAG-IGN Aerocommander FL 280 aircraft made extensive ‘in situ’ measurements of turbulent fluctuations in diurnally evolving convective boundary layers. In this paper, these measurements were used to investigate characteristics of the molecular dissipation of turbulent fluctuations through the mixed layer and well into the overlying stable layer. The dimensionless dissipation rates of turbulent kinetic energy, temperature and humidity variances, and temperature-humidity covariance (ψ, ψθ, ψqand ψθq) were computed and their height variations analysed.The behaviour of the dissipation rate ψ was found to differ significantly from those observed for the other rates. In the lowest region of the mixed layer, ψ does not obey the local free convection prediction. Instead, it follows practically a relationship similar to the one established in the surface layer by Wyngaard et al. (1971). The dissipation rate ψ remains fairly constant in the bulk of the mixed layer (0.3 ≤ z/Zi≤ 0.8) and shows a very rapid decrease above the inversion. These results confirm those reported previously from the Minnesota and Ashchurch data by Kaimal et al. (1976), Caughey and Palmer (1979), etc.The height variations for the other dissipation rates were found to obey, as expected, the (z/Zi)-4/3 decrease predicted under the local free convection similarity hypothesis in the lowest region of the mixed layer. This region extends to the height z/Zi- 0.4, 0.1, and 0.3, respectively, for ψθ, ψq, and ψθq. Above these levels, the dissipation rates ψθ and ψq show, on average, a slight increase to reach peak-values near the mixed-layer top, while the ‘dissipation’ rate ψθqchanges sign from positive to negative around the height z/Zi, - 0.7. These characteristics confirm the fact that the structures of temperature and humidity fluctuations are considerably affected by their entrainment-induced fluctuations. Therefore, an attempt has been made to non-dimensionalize the dissipation rates near the mixed-layer top with the interfacial scaling factors.

Statistical analysis of cloud light scattering and microphysical properties obtained from airborne measurements

A new statistical analysis of the in situ scattering phase function measurements performed by the Laboratoire de Meteorologie Physiques airborne polar nephelometer is implemented. A principal component analysis along with neural networks leads to the classification of a large data set into three typical averaged scattering phase functions. The cloud classification in terms of particle phase composition (water droplets, mixed-phase, and ice crystals) is done by a neural network and is validated by direct Particle Measuring Systems, Inc., probe measurements. The results show that the measured scattering phase functions carry enough information to accurately retrieve component composition and particle size distributions. For each classified cloud, we support the statement by application of an inversion method using a physical model of light scattering to the average scattering phase function. Furthermore, the retrievals are compared with size composition obtained by independent direct measurements.

Inhomogeneity effects of 1D and 2D bounded cascade model clouds on their effective radiative properties

Abstract Inhomogeneous clouds generated with the bounded cascade process were used in a number of recent studies on the interaction between the radiative transfer process and inhomogeneous clouds. In this study, we investigate how the EHCA could be applied to 1D and 2D bounded cascade inhomogeneous absorbing clouds generated with different pairs of fractal parameters H and f . Firstly, we found that the empirical formulas we previously established were still applicable to other 1D and 2D inhomogeneous clouds with different single scattering albedo and with various types of fluctuations of the optical depth, except the case of very intermittent inhomogeneous clouds generated with H = 0 whatever f and H = 0.25 and f ≥ 0.3 (i.e. ϱ τ > 1.5 ∼ 2, where ϱ τ is a relative cloud inhomogeneity parameter defined as the standard deviation of the optical depth normalized by the mean optical depth). Secondly, we also found that the bias in the bidirectional reflectance factor between 1D and 2D inhomogeneous clouds radiance and their EHCA counterpart remained rather small (≤ 5%), again except the case of very intermittent inhomogeneous clouds with ϱ τ > 1.5 ∼ 2, for which this bias reached 20% to 60%.

Neural network analysis of the radiative interaction between neighboring pixels in inhomogeneous clouds

In this study, we analyzed the effect of the radiative interaction between neighboring pixels on the high-resolution radiant flux of bounded cascade inhomogeneous clouds by using a one-layer mapping neural network as generalized regression analysis. The analysis was done for reflectance, transmittance, and absorptance at different wavelengths under different conditions of illumination. The sign and magnitude of output coefficients indicate how neighboring pixels contribute to the radiant flux of a target pixel. We found that the variation of output coefficients with the distance from the target pixel changes significantly in its shape and horizontal extent not only with the type of radiant flux we consider but also with the wavelength and solar zenith angle. The mapping neural network clearly reveals the asymmetric feature of radiative interaction between neighboring pixels under oblique illumination, which illustrates the shadowing and enhancing effects of local cloud inhomogeneity. The present analysis shows that the mapping neural network is a flexible method of analysis when used as a generalized regression analysis.