Logarithme d'harmoniques sphériques pour le rendu d'ombres douces de champs de hauteurs et de maillages

Les ombres sont un élément important pour la compréhension d'une scène. Grâce à elles, il est possible de résoudre des situations autrement ambigües, notamment concernant les mouvements, ou encore les positions relatives des objets de la scène. Il y a principalement deux types d'ombres: des ombres dures, aux limites très nettes, qui résultent souvent de lumières ponctuelles ou directionnelles; et des ombres douces, plus floues, qui contribuent à l'atmosphère et à la qualité visuelle de la scène. Les ombres douces résultent de grandes sources de lumière, comme des cartes environnementales, et sont difficiles à échantillonner efficacement en temps réel. Lorsque l'interactivité est prioritaire sur la qualité, des méthodes d'approximation peuvent être utilisées pour améliorer le rendu d'une scène à moindre coût en temps de calcul. Nous calculons interactivement les ombres douces résultant de sources de lumière environnementales, pour des scènes composées d'objets en mouvement et d'un champ de hauteurs dynamique. Notre méthode enrichit la méthode d'exponentiation des harmoniques sphériques, jusque là limitée aux bloqueurs sphériques, pour pouvoir traiter des champs de hauteurs. Nous ajoutons également une représentation pour les BRDFs diffuses et glossy. Nous pouvons ainsi combiner les visibilités et BRDFs dans un même espace, afin de calculer efficacement les ombres douces et les réflexions de scènes complexes. Un algorithme hybride, qui associe les visibilités en espace écran et en espace objet, permet de découpler la complexité des ombres de la complexité de la scène.

Spectrally-invariant behavior of zenith radiance around cloud edges simulated by radiative transfer

In a previous paper, we discovered a surprising spectrally-invariant relationship in shortwave spectrometer observations taken by the Atmospheric Radiation Measurement (ARM) program. The relationship suggests that the shortwave spectrum near cloud edges can be determined by a linear combination of zenith radiance spectra of the cloudy and clear regions. Here, using radiative transfer simulations, we study the sensitivity of this relationship to the properties of aerosols and clouds, to the underlying surface type, and to the finite field-of-view (FOV) of the spectrometer. Overall, the relationship is mostly sensitive to cloud properties and has little sensitivity to other factors. At visible wavelengths, the relationship primarily depends on cloud optical depth regardless of cloud phase function, thermodynamic phase and drop size. At water-absorbing wavelengths, the slope of the relationship depends primarily on cloud optical depth; the intercept, by contrast, depends primarily on cloud absorbing and scattering properties, suggesting a new retrieval method for cloud drop effective radius. These results suggest that the spectrally-invariant relationship can be used to infer cloud properties near cloud edges even with insufficient or no knowledge about spectral surface albedo and aerosol properties.

A fast radiative transfer model for the assimilation of water vapor radiances from the Kalpana very high resolution radiometer

A fast radiative transfer model (RTM) to compute emitted infrared radiances for a very high resolution radiometer (VHRR), onboard the operational Indian geostationary satellite Kalpana has been developed and verified. This work is a step towards the assimilation of Kalpana water vapor (WV) radiances into numerical weather prediction models. The fast RTM uses a regression‐based approach to parameterize channel‐specific convolved level to space transmittances. A comparison between the fast RTM and the line‐by‐line RTM demonstrated that the fast RTM can simulate line‐by‐line radiances for the Kalpana WV channel to an accuracy better than the instrument noise, while offering more rapid radiance calculations. A comparison of clear sky radiances of the Kalpana WV channel with the ECMWF model first guess radiances is also presented, aiming to demonstrate the fast RTM performance with the real observations. In order to assimilate the radiances from Kalpana, a simple scheme for bias correction has been suggested.

On the equivalence between radiance and retrieval assimilation

The need for consistent assimilation of satellite measurements for numerical weather prediction led operational meteorological centers to assimilate satellite radiances directly using variational data assimilation systems. More recently there has been a renewed interest in assimilating satellite retrievals (e.g., to avoid the use of relatively complicated radiative transfer models as observation operators for data assimilation). The aim of this paper is to provide a rigorous and comprehensive discussion of the conditions for the equivalence between radiance and retrieval assimilation. It is shown that two requirements need to be satisfied for the equivalence: (i) the radiance observation operator needs to be approximately linear in a region of the state space centered at the retrieval and with a radius of the order of the retrieval error; and (ii) any prior information used to constrain the retrieval should not underrepresent the variability of the state, so as to retain the information content of the measurements. Both these requirements can be tested in practice. When these requirements are met, retrievals can be transformed so as to represent only the portion of the state that is well constrained by the original radiance measurements and can be assimilated in a consistent and optimal way, by means of an appropriate observation operator and a unit matrix as error covariance. Finally, specific cases when retrieval assimilation can be more advantageous (e.g., when the estimate sought by the operational assimilation system depends on the first guess) are discussed.

Micropolar flow in a porous channel with high mass transfer

Two dimensional flow of a micropolar fluid in a porous channel is investigated. The flow is driven by suction or injection at the channel walls, and the micropolar model due to Eringen is used to describe the working fluid. An extension of Berman's similarity transform is used to reduce the governing equations to a set of non-linear coupled ordinary differential equations. The latter are solved for large mass transfer via a perturbation analysis where the inverse of the cross-flow Reynolds number is used as the perturbing parameter. Complementary numerical solutions for strong injection are also obtained using a quasilinearisation scheme, and good agreement is observed between the solutions obtained from the perturbation analysis and the computations.