140 resultados para Doppler radar.


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Collocations between two satellite sensors are occasions where both sensors observe the same place at roughly the same time. We study collocations between the Microwave Humidity Sounder (MHS) on-board NOAA-18 and the Cloud Profiling Radar (CPR) on-board CloudSat. First, a simple method is presented to obtain those collocations and this method is compared with a more complicated approach found in literature. We present the statistical properties of the collocations, with particular attention to the effects of the differences in footprint size. For 2007, we find approximately two and a half million MHS measurements with CPR pixels close to their centrepoints. Most of those collocations contain at least ten CloudSat pixels and image relatively homogeneous scenes. In the second part, we present three possible applications for the collocations. Firstly, we use the collocations to validate an operational Ice Water Path (IWP) product from MHS measurements, produced by the National Environment Satellite, Data and Information System (NESDIS) in the Microwave Surface and Precipitation Products System (MSPPS). IWP values from the CloudSat CPR are found to be significantly larger than those from the MSPPS. Secondly, we compare the relation between IWP and MHS channel 5 (190.311 GHz) brightness temperature for two datasets: the collocated dataset, and an artificial dataset. We find a larger variability in the collocated dataset. Finally, we use the collocations to train an Artificial Neural Network and describe how we can use it to develop a new MHS-based IWP product. We also study the effect of adding measurements from the High Resolution Infrared Radiation Sounder (HIRS), channels 8 (11.11 μm) and 11 (8.33 μm). This shows a small improvement in the retrieval quality. The collocations described in the article are available for public use.

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The congruential rule advanced by Graves for polarization basis transformation of the radar backscatter matrix is now often misinterpreted as an example of consimilarity transformation. However, consimilarity transformations imply a physically unrealistic antilinear time-reversal operation. This is just one of the approaches found in literature to the description of transformations where the role of conjugation has been misunderstood. In this paper, the different approaches are examined in particular in respect to the role of conjugation. In order to justify and correctly derive the congruential rule for polarization basis transformation and properly place the role of conjugation, the origin of the problem is traced back to the derivation of the antenna height from the transmitted field. In fact, careful consideration of the role played by the Green’s dyadic operator relating the antenna height to the transmitted field shows that, under general unitary basis transformation, it is not justified to assume a scalar relationship between them. Invariance of the voltage equation shows that antenna states and wave states must in fact lie in dual spaces, a distinction not captured in conventional Jones vector formalism. Introducing spinor formalism, and with the use of an alternate spin frame for the transmitted field a mathematically consistent implementation of the directional wave formalism is obtained. Examples are given comparing the wider generality of the congruential rule in both active and passive transformations with the consimilarity rule.

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This paper examines a hydrographic response to the wind‐driven coastal polynya activity over the southeastern Laptev Sea shelf for April–May 2008, using a combination of Environmental Satellite (Envisat) advanced synthetic aperture radar (ASAR) and TerraSAR‐X satellite imagery, aerial photography, meteorological data, and SBE‐37 salinity‐temperature‐depth and acoustic Doppler current profiler land‐fast ice edgemoored instruments. When ASAR observed the strongest end‐of‐April polynya event with frazil ice formation, the moored instruments showed maximal acoustical scattering within the surface mixed layer, and the seawater temperatures were either at or 0.02°C below freezing. We also find evidence of the persistent horizontal temperature and salinity gradients across the fast ice edge to have the signature of geostrophic flow adjustment as predicted by polynya models.

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The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

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Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50 % after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.