Search results for "clouds"

Modeling and simulation of dense cloud dispersion in urban areas by means of computational fluid dynamics

2011

Abstract The formation of toxic heavy clouds as a result of sudden accidental releases from mobile containers, such as road tankers or railway tank cars, may occur inside urban areas so the problem arises of their consequences evaluation. Due to the semi-confined nature of the dispersion site simplified models may often be inappropriate. As an alternative, computational fluid dynamics (CFD) has the potential to provide realistic simulations even for geometrically complex scenarios since the heavy gas dispersion process is described by basic conservation equations with a reduced number of approximations. In the present work a commercial general purpose CFD code (CFX 4.4 by Ansys®) is employe…

Dalītās paralēlās bojājumpiecietīgās failu sistēmas

2015

Bakalaura darba tēma ir „dalītās paralēlās bojājumpiecietīgās failu sistēmas”. Darba mērķis ir iepazīties ar šāda veida failu sistēmām, izprast, kā tās darbojas un kādi ir to plusi un mīnusi. Darba gaitā ir uzstādīta viena no šādām failu sistēmām (Ceph) uz vairākiem serveriem, lai varētu izpētīt tās darbību un arhitektūru, kā arī izprast tās darbību.

CloudSim: A fair benchmark for comparison of methods for times series reconstruction from cloud and atmospheric contamination

2015

Cloud contamination of optical data is a constant and annoying feature of time series analyses, whether while using vegetation indices or surface temperatures, since it tends to decrease artificially the values taken by these parameters. Therefore, any time series analysis of optical data needs a previous step for gap-filling reconstruction of the time series. Numerous techniques have been presented in the literature to carry out this preliminary and mandatory step. However, the evaluation and comparison of these techniques is difficult, since no “truth” time series is available. We present here a probabilistic model (CloudSim) to provide global typical annual time series for NDVI (Normaliz…

Laboratory unraveling of matter accretion in young stars

2017

When matter accretes onto a young star, a shell of dense material can form around the impact, reducing its x-ray emission.

Overionization in X-ray spectra: a new paradigm for Mixed-Morphology SNRs

2011

Mixed-morphology SNRs are characterized by a shell-like radio emission, a centrally peaked X-ray morphology, and by interaction with molecular clouds. Many models have been proposed to explain these peculiar remnants, but their physical origin is still unclear. The recent discovery of over-ionized (i. e. recombining) ejecta in 3 mixed-morphology SNRs has dramatically challenged all the previous models and opened up new, unexpected scenarios. I review the main properties of these remnants and their peculiar X-ray spectral properties. I also discuss the hydrodynamic model developed to explain the presence of over-ionized ejecta in W49B and present a list of open issues that still need to be c…

High-energy γ-ray detection of supernova remnants in the Large Magellanic Cloud

2022

We present the results of a cluster search in the gamma-ray sky images of the Large Magellanic Cloud (LMC) region by means of the Minimum Spanning Tree (MST) and DBSCAN algorithms, at energies higher than 6 and 10 GeV, using 12 years of Fermi-LAT data. Several significant clusters were found, the majority of which associated with previously known gamma-ray sources. We confirm our previous detection of the Supernova Remnants N 49B and N 63A and found new significant clusters associated with the SNRs N 49, N 186D and N 44. These sources are among the brightest X-ray remnants in the LMC and corresponds to core-collapse supernovae interacting with dense HII regions, indicating that an hadronic …

Negative and positive feedback from a supernova remnant with SHREC

2022

Supernova remnants (SNRs) contribute to regulate the star formation efficiency and evolution of galaxies. As they expand into the interstellar medium (ISM), they transfer vast amounts of energy and momentum that displace, compress and heat the surrounding material. Despite the extensive work in galaxy evolution models, it remains to be observationally validated to what extent the molecular ISM is affected by the interaction with SNRs. We use the first results of the ESO-ARO Public Spectroscopic Survey SHREC, to investigate the shock interaction between the SNR IC443 and the nearby molecular clump G. We use high sensitivity SiO(2-1) and H$^{13}$CO$^+$(1-0) maps obtained by SHREC together wit…

Shock-cloud interactions in the Vela SNR: preliminary results of an XMM-Newton observation

2004

Dehydration potential of ultrathin clouds at the tropical tropopause

2003

[1] We report on the first simultaneous in situ and remote measurements of subvisible cirrus in the uppermost tropical troposphere. The observed cirrus, called UTTCs ( ultrathin tropical tropopause clouds), are the geometrically (200-300 m) and optically (t approximate to 10(-4)) thinnest large-scale clouds ever sampled (approximate to10(5) km(2)). UTTCs consist of only a few ice particles per liter with mean radius approximate to5 mum, containing only 1-5 % of the total water. Yet, brief adiabatic cooling events only 1-2 K below mean ambient temperature destabilize UTTCs, leading to large sedimenting particles (r approximate to 25 mm). Due to their extreme altitude above 17 km and low part…

Cloud top altitude retrieved from Lidar measurements during ACLOUD at 1 second resolution

2021

During the ACLOUD aircraft campaign (23.5.2017 - 26.6.2017) the AMALi Lidar was installed mostly nadir pointing. This dataset contains the cloud top altitude from those measurements (altitudes with a strong signal increase) as well as a cloud mask, derived from the optical depth of the column at 1 second resolution. The majority of the data was collected northwest of the Svalbard archipelago. More details on the campaign can be found in Wendisch 2018 and Ehrlich 2019 and here (https://home.uni-leipzig.de/~ehrlich/ACLOUD_wiki_doku). Please check the data documentation (https://download.pangaea.de/reference/108729/attachments/readme_documentation_AMALi_cloudtop.pdf) before using this dataset.