38 resultados para Calipso


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Since 1995 the eruption of the andesitic Soufrière Hills Volcano (SHV), Montserrat, has been studied in substantial detail. As an important contribution to this effort, the Seismic Experiment with Airgunsource-Caribbean Andesitic Lava Island Precision Seismo-geodetic Observatory (SEA-CALIPSO) experiment was devised to image the arc crust underlying Montserrat, and, if possible, the magma system at SHV using tomography and reflection seismology. Field operations were carried out in October–December 2007, with deployment of 238 seismometers on land supplementing seven volcano observatory stations, and with an array of 10 ocean-bottom seismometers deployed offshore. The RRS James Cook on NERC cruise JC19 towed a tuned airgun array plus a digital 48-channel streamer on encircling and radial tracks for 77 h about Montserrat during December 2007, firing 4414 airgun shots and yielding about 47 Gb of data. The main objecctives of the experiment were achieved. Preliminary analyses of these data published in 2010 generated images of heterogeneous high-velocity bodies representing the cores of volcanoes and subjacent intrusions, and shallow areas of low velocity on the flanks of the island that reflect volcaniclastic deposits and hydrothermal alteration. The resolution of this preliminary work did not extend beyond 5 km depth. An improved three-dimensional (3D) seismic velocity model was then obtained by inversion of 181 665 first-arrival travel times from a more-complete sampling of the dataset, yielding clear images to 7.5 km depth of a low-velocity volume that was interpreted as the magma chamber which feeds the current eruption, with an estimated volume 13 km3. Coupled thermal and seismic modelling revealed properties of the partly crystallized magma. Seismic reflection analyses aimed at imaging structures under southern Montserrat had limited success, and suggest subhorizontal layering interpreted as sills at a depth of between 6 and 19 km. Seismic reflection profiles collected offshore reveal deep fans of volcaniclastic debris and fault offsets, leading to new tectonic interpretations. This chapter presents the project goals and planning concepts, describes in detail the campaigns at sea and on land, summarizes the major results, and identifies the key lessons learned.

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In this paper, data from spaceborne radar, lidar and infrared radiometers on the “A-Train” of satellites are combined in a variational algorithm to retrieve ice cloud properties. The method allows a seamless retrieval between regions where both radar and lidar are sensitive to the regions where one detects the cloud. We first implement a cloud phase identification method, including identification of supercooled water layers using the lidar signal and temperature to discriminate ice from liquid. We also include rigorous calculation of errors assigned in the variational scheme. We estimate the impact of the microphysical assumptions on the algorithm when radiances are not assimilated by evaluating the impact of the change in the area-diameter and the density-diameter relationships in the retrieval of cloud properties. We show that changes to these assumptions affect the radar-only and lidar-only retrieval more than the radar-lidar retrieval, although the lidar-only extinction retrieval is only weakly affected. We also show that making use of the molecular lidar signal beyond the cloud as a constraint on optical depth, when ice clouds are sufficiently thin to allow the lidar signal to penetrate them entirely, improves the retrieved extinction. When infrared radiances are available, they provide an extra constraint and allow the extinction-to-backscatter ratio to vary linearly with height instead of being constant, which improves the vertical distribution of retrieved cloud properties.

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The A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud (penetrated only by the radar). In this paper, several versions of the VarCloud retrieval are compared with the CloudSat standard ice-only retrieval of ice water content, two empirical formulas that derive ice water content from radar reflectivity and temperature, and retrievals of vertically integrated properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) radiometer. The retrieved variables typically agree to within a factor of 2, on average, and most of the differences can be explained by the different microphysical assumptions. For example, the ice water content comparison illustrates the sensitivity of the retrievals to assumed ice particle shape. If ice particles are modeled as oblate spheroids rather than spheres for radar scattering then the retrieved ice water content is reduced by on average 50% in clouds with a reflectivity factor larger than 0 dBZ. VarCloud retrieves optical depths that are on average a factor-of-2 lower than those from MODIS, which can be explained by the different assumptions on particle mass and area; if VarCloud mimics the MODIS assumptions then better agreement is found in effective radius and optical depth is overestimated. MODIS predicts the mean vertically integrated ice water content to be around a factor-of-3 lower than that from VarCloud for the same retrievals, however, because the MODIS algorithm assumes that its retrieved effective radius (which is mostly representative of cloud top) is constant throughout the depth of the cloud. These comparisons highlight the need to refine microphysical assumptions in all retrieval algorithms and also for future studies to compare not only the mean values but also the full probability density function.

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In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.

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The West African summer monsoon (WAM) is an important driver of the global climate and locally provides most of the annual rainfall. A solid climatological knowledge of the complex vertical cloud structure is invaluable to forecasters and modelers to improve the understanding of the WAM. In this paper, 4 years of data from the CloudSat profiling radar and CALIPSO are used to create a composite zonal mean vertical cloud and precipitation structure for the WAM. For the first time, the near-coincident vertical radar and lidar profiles allow for the identification of individual cloud types from optically thin cirrus and shallow cumulus to congestus and deep convection. A clear diurnal signal in zonal mean cloud structure is observed for the WAM, with deep convective activity enhanced at night producing extensive anvil and cirrus, while daytime observations show more shallow cloud and congestus. A layer of altocumulus is frequently observed over the Sahara at night and day, extending southward to the coastline, and the majority of this cloud is shown to contain supercooled liquid in the top. The occurrence of deep convective systems and congestus in relation to the position of the African easterly jet is studied, but only the daytime cumulonimbus distribution indicates some influence of the jet position.

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Ice cloud representation in general circulation models remains a challenging task, due to the lack of accurate observations and the complexity of microphysical processes. In this article, we evaluate the ice water content (IWC) and ice cloud fraction statistical distributions from the numerical weather prediction models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office, exploiting the synergy between the CloudSat radar and CALIPSO lidar. Using the last three weeks of July 2006, we analyse the global ice cloud occurrence as a function of temperature and latitude and show that the models capture the main geographical and temperature-dependent distributions, but overestimate the ice cloud occurrence in the Tropics in the temperature range from −60 °C to −20 °C and in the Antarctic for temperatures higher than −20 °C, but underestimate ice cloud occurrence at very low temperatures. A global statistical comparison of the occurrence of grid-box mean IWC at different temperatures shows that both the mean and range of IWC increases with increasing temperature. Globally, the models capture most of the IWC variability in the temperature range between −60 °C and −5 °C, and also reproduce the observed latitudinal dependencies in the IWC distribution due to different meteorological regimes. Two versions of the ECMWF model are assessed. The recent operational version with a diagnostic representation of precipitating snow and mixed-phase ice cloud fails to represent the IWC distribution in the −20 °C to 0 °C range, but a new version with prognostic variables for liquid water, ice and snow is much closer to the observed distribution. The comparison of models and observations provides a much-needed analysis of the vertical distribution of IWC across the globe, highlighting the ability of the models to reproduce much of the observed variability as well as the deficiencies where further improvements are required.

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El objetivo de este trabajo consiste en interpretar la forma en que la novela Calypso metaforiza el encuentro – desencuentro entre la cultura meseteña y la cultura del Caribe costarricense. Con base en las características históricas de ese encuentro, Tatiana Lobo pone frente a frente a los dos grupos culturales y recrea los rasgos básicos de cada uno de ellos. A partir de aquí, desarrolla una valoración de ambas culturas en la que destaca sus profundas diferencias en la concepción del mundo, para lo cual utiliza una metáfora muy productiva que le permite, por un lado, recrear la imposibilidad que tiene el blanco de entender al negro y, por otro, parodiar negativamente la cultura costarricense meseteña. El recurso que utiliza es el caly(i)pso, como manifestación propia de la cultura afrocaribeña, pero además como elemento evocador de la cultura clásica griega.

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CALIPSO (Cloud-Aerosol Lidar and Pathfinder Satellite Observations) Level 3 (CL3) data were compared against EARLINET (European Aerosol Research Lidar Network) monthly averages obtained by profiles during satellite overpasses. Data from EARLINET stations of Évora, Granada, Leipzig, Naples and Potenza, equipped with advanced multi-wavelength Raman lidars were used for this study. Owing to spatial and temporal differences, we reproduced the CL3 filtering rubric onto the CALIPSO Level 2 data. The CALIPSO monthly mean profiles following this approach are called CALIPSO Level 3*, CL3*. This offers the possibility to achieve direct comparable datasets. In respect to CL3 data, the agreement typically improved, in particular above the areas directly affected by the anthropogenic activities within the planetary boundary layer. However in most of the cases a subtle CALIPSO underestimation was observed with an average bias of 0.03 km-1. We investigated the backscatter coefficient applying the same screening criteria, where the mean relative difference in respect to the extinction comparison improved from 15.2% to 11.4%. Lastly, the typing capabilities of CALIPSO were assessed outlining the importance of the correct aerosol type (and associated lidar ratio value) assessment to the CALIPSO aerosol properties retrieval.

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The Ozone Monitoring Instrument (OMI) aboard EOS-Aura and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS-Aqua fly in formation as part of the A-train. Though OMI retrieves aerosol optical depth (AOD) and aerosol absorption, it must assume aerosol layer height. The MODIS cannot retrieve aerosol absorption, but MODIS aerosol retrieval is not sensitive to aerosol layer height and with its smaller pixel size is less affected by subpixel clouds. Here we demonstrate an approach that uses MODIS-retrieved AOD to constrain the OMI retrieval, freeing OMI from making an a priori estimate of aerosol height and allowing a more direct retrieval of aerosol absorption. To predict near-UV optical depths using MODIS data we rely on the spectral curvature of the MODIS-retrieved visible and near-IR spectral AODs. Application of an OMI-MODIS joint retrieval over the north tropical Atlantic shows good agreement between OMI and MODIS-predicted AODs in the UV, which implies that the aerosol height assumed in the OMI-standard algorithm is probably correct. In contrast, over the Arabian Sea, MODIS-predicted AOD deviated from the OMI-standard retrieval, but combined OMI-MODIS retrievals substantially improved information on aerosol layer height (on the basis of validation against airborne lidar measurements). This implies an improvement in the aerosol absorption retrieval, but lack of UV absorption measurements prevents a true validation. Our study demonstrates the potential of multisatellite analysis of A-train data to improve the accuracy of retrieved aerosol products and suggests that a combined OMI-MODIS-CALIPSO retrieval has large potential to further improve assessments of aerosol absorption.

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The information on altitude distribution of aerosols in the atmosphere is essential in assessing the impact of aerosol warming on thermal structure and stability of the atmosphere.In addition, aerosol altitude distribution is needed to address complex problems such as the radiative interaction of aerosols in the presence of clouds. With this objective,an extensive, multi-institutional and multi-platform field experiment (ICARB-Integrated Campaign for Aerosols, gases and Radiation Budget) was carried out under the Geosphere Biosphere Programme of the Indian Space Research Organization (ISRO-GBP) over continental India and adjoining oceans during March to May 2006. Here, we present airborne LIDAR measurements carried out over the east Coast of the India during the ICARB field campaign. An increase in aerosol extinction (scattering + absorption) was observed from the surface upwards with a maximum around 2 to 4 km. Aerosol extinction at higher atmospheric layers (>2 km) was two to three times larger compared to that of the surface. A large fraction (75-85%) of aerosol column optical depth was contributed by aerosols located above 1 km. The aerosol layer heights (defined in this paper as the height at which the gradient in extinction coefficient changes sign) showed a gradual decrease with an increase in the offshore distance. A large fraction (60-75%) of aerosol was found located above clouds indicating enhanced aerosol absorption above clouds. Our study implies that a detailed statistical evaluation of the temporal frequency and spatial extent of elevated aerosol layers is necessary to assess their significance to the climate. This is feasible using data from space-borne lidars such as CALIPSO,which fly in formation with other satellites like MODIS AQUA and MISR, as part of the A-Train constellation.

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Recent studies, over regions influenced by biomass burning aerosol, have shown that it is possible to define a critical cloud fraction' (CCF) at which the aerosol direct radiative forcing switch from a cooling to a warming effect. Using 4 years of multi-satellite data analysis, we show that CCF varies with aerosol composition and changed from 0.28 to 0.13 from postmonsoon to winter as a result of shift from less absorbing to moderately absorbing aerosol. Our results indicate that we can estimate aerosol absorption from space using independently measured top of the atmosphere (TOA) fluxes Cloud Aerosol Lidar with Orthogonal Polarization-Moderate resolution Imaging Spectroradiometer-Clouds and the Earth's Radiant Energy System (CALIPSO-MODIS-CERES)] combined algorithms for example.