Multidimensional Modeling of Atmospheric Effects and Surface Heterogeneities on Remote Sensing

The overall goal of this project is to establish a modeling capability that allows a quantitative determination of atmospheric effects on remote sensing including the effects of surface heterogeneities. This includes an improved understanding of aerosol and haze effects in connection with structural, angular, and spatial surface heterogeneities. One important objective of the research is the possible identification of intrinsic surface or canopy characteristics that might be invariant to atmospheric perturbations so that they could be used for scene identification. Conversely, an equally important objective is to find a correction algorithm for atmospheric effects in satellite-sensed surface reflectances. The technical approach is centered around a systematic model and code development effort based on existing, highly advanced computer codes that were originally developed for nuclear radiation shielding applications. Computational techniques for the numerical solution of the radiative transfer equation are adapted on the basis of the discrete-ordinates finite-element method which proved highly successful for one and two-dimensional radiative transfer problems with fully resolved angular representation of the radiation field

Three-dimensional effects in polarization signatures as observed from precipitating clouds by low frequency ground-based microwave radiometers

International audienceConsistent negative polarization differences (i.e. differences between the vertical and the horizontal brightness temperature) are observed when looking at precipitating systems by ground-based radiometers at slant angles. These signatures can be partially explained by one-dimensional radiative transfer computations that include oriented non-spherical raindrops. However some cases are characterized by polarization values that exceed differences expected from one-dimensional radiative transfer. A three-dimensional fully polarized Monte Carlo model has been used to evaluate the impact of the horizontal finiteness of rain shafts with different rain rates at 10, 19, and 30 GHz. The results show that because of the reduced slant optical thickness in finite clouds, the polarization signal can strongly differ from its one-dimensional counterpart. At the higher frequencies and when the radiometer is positioned underneath the cloud, significantly higher negative values for the polarization are found which are also consistent with some observations. When the observation point is located outside of the precipitating cloud, typical polarization patterns (with troughs and peaks) as a function of the observation angle are predicted. An approximate 1-D slant path radiative transfer model is considered as well and results are compared with the full 3-D simulations to investigate whether or not three-dimensional effects can be explained by geometry effects alone. The study has strong relevance for low-frequency passive microwave polarimetric studies

Evaluation of radar multiple scattering effects in Cloudsat configuration

International audienceMonteCarlo simulations have been performed to evaluate the importance of multiple scattering effects in co- and cross-polar radar returns for 94 GHz radars in Cloudsat and airborne configurations. Thousands of vertically structured profiles derived from some different cloud resolving models are used as a test-bed. Mie theory is used to derive the single scattering properties of the atmospheric hydrometeors. Multiple scattering effects in the co-polar channel (reflectivity enhancement) are particularly elusive, especially in airborne configuration. They can be quite consistent in satellite configurations, like CloudSat, especially in regions of high attenuation and in the presence of highly forward scattering layers associated with snow and graupel particles. When the cross polar returns are analysed [but note that CloudSat does not measure any linear depolarization ratio (LDR hereafter)], high LDR values appear both in space and in airborne configurations. The LDR signatures are footprints of multiple scattering effects; although depolarization values as high as ?5 dB can be generated including non-spherical particles in single scattering modelling, multiple scattering computations can produce values close to complete depolarization (i.e. LDR=0 dB). Our simulated LDR profiles from an air-borne platform well reproduce, in a simple frame, some experimental observations collected during the Wakasa Bay experiment. Since LDR instrumental uncertainties were not positively accounted for during that experiment, more focused campaigns with air-borne polarimetric radar are recommended. Multiple scattering effects can be important for CloudSat applications like rainfall and snowfall retrievals since single scattering based algorithms will be otherwise burdened by positive biases

Evaluation of radar multiple scattering effects in Cloudsat configuration

MonteCarlo simulations have been performed to evaluate the importance of multiple scattering effects in coand cross-polar radar returns for 94 GHz radars in Cloudsat and airborne configurations. Thousands of vertically structured profiles derived from some different cloud resolving models are used as a test-bed. Mie theory is used to derive the single scattering properties of the atmospheric hydrometeors. Multiple scattering effects in the co-polar channel (reflectivity enhancement) are particularly elusive, especially in airborne configuration. They can be quite consistent in satellite configurations, like CloudSat, especially in regions of high attenuation and in the presence of highly forward scattering layers associated with snow and graupel particles. When the cross polar returns are analysed [but note that CloudSat does not measure any linear depolarization ratio (LDR hereafter)], high LDR values appear both in space and in airborne configurations. The LDR signatures are footprints of multiple scattering effects; although depolarization values as high as -5 dB can be generated including non-spherical particles in single scattering modelling, multiple scattering computations can produce values close to complete depolarization (i.e. LDR=0dB). Our simulated LDR profiles from an air-borne platform well reproduce, in a simple frame, some experimental observations collected during the Wakasa Bay experiment. Since LDR instrumental uncertainties were not positively accounted for during that experiment, more focused campaigns with air-borne polarimetric radar are recommended. Multiple scattering effects can be important for CloudSat applications like rainfall and snow-fall retrievals since single scattering based algorithms will be otherwise burdened by positive biases

Evaluation of radar multiple-scattering effects from a GPM perspective. Part I: Model description and validation

A numerical model based on the Monte Carlo solution of the vector radiative transfer equation has been adopted to simulate radar signals. The model accounts for general radar configurations such as airborne/ spaceborne/ground based and monostatic/bistatic and includes the polarization and the antenna pattern as particularly relevant features. Except for contributions from the backscattering enhancement, the model is particularly suitable for evaluating multiple-scattering effects. It has been validated against some analytical methods that provide solutions for the first and second order of scattering of the copolar intensity for pencil-beam/Gaussian antennas in the transmitting/ receiving segment. The model has been applied to evaluate the multiple scattering when penetrating inside a uniform hydrometeor layer. In particular, the impact of the phase function, the range-dependent scattering optical thickness, and the effects of the antenna footprint are considered. © 2006 American Meteorological Society

Ueber das Verhalten der Alkaloidsalze und anderer organischer Substanzen zu den Lösungsmitteln der Perforationsmethode, insbesondere Chloroform, sowie über Reduktionswirkungen der Alkaloide

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Two adaptive radiative transfer schemes for numerical weather prediction models

Radiative transfer calculations in atmospheric models are computationally expensive, even if based on simplifications such as the δ-two-stream approximation. In most weather prediction models these parameterisation schemes are therefore called infrequently, accepting additional model error due to the persistence assumption between calls. This paper presents two so-called adaptive parameterisation schemes for radiative transfer in a limited area model: A perturbation scheme that exploits temporal correlations and a local-search scheme that mainly takes advantage of spatial correlations. Utilising these correlations and with similar computational resources, the schemes are able to predict the surface net radiative fluxes more accurately than a scheme based on the persistence assumption. An important property of these adaptive schemes is that their accuracy does not decrease much in case of strong reductions in the number of calls to the δ-two-stream scheme. It is hypothesised that the core idea can also be employed in parameterisation schemes for other processes and in other dynamical models

Purification and analytical characterization of an anti- CD4 monoclonal antibody for human therapy

A purification process for the monclonal anti-CD4 antibody MAX.16H5 was developed on an analytical scale using (NH&SO, precipitation, anion-exchange chromatography on MonoQ or Q-Sepharose, hydrophobic interaction chromatography on phenyl- Sepharose and gel filtration chromatography on Superdex 200. The purification schedule was scaled up and gram amounts of MAX.16H5 were produced on corresponding BioPilot columns. Studies of the identity, purity and possible contamination by a broad range of methods showed that the product was highly purified and free from contaminants such as mouse DNA, viruses, pyrogens and irritants. Overall, the analytical data confirm that the monoclonal antibody MAX.16H5 prepared by this protocol is suitable for human therapy