Distributed Virtual System (DIVIRS) Project

As outlined in our continuation proposal 92-ISI-50R (revised) on contract NCC 2-539, we are (1) developing software, including a system manager and a job manager, that will manage available resources and that will enable programmers to program parallel applications in terms of a virtual configuration of processors, hiding the mapping to physical nodes; (2) developing communications routines that support the abstractions implemented in item one; (3) continuing the development of file and information systems based on the virtual system model; and (4) incorporating appropriate security measures to allow the mechanisms developed in items 1 through 3 to be used on an open network. The goal throughout our work is to provide a uniform model that can be applied to both parallel and distributed systems. We believe that multiprocessor systems should exist in the context of distributed systems, allowing them to be more easily shared by those that need them. Our work provides the mechanisms through which nodes on multiprocessors are allocated to jobs running within the distributed system and the mechanisms through which files needed by those jobs can be located and accessed

DIstributed VIRtual System (DIVIRS) Project

The development of Prospero moved from the University of Washington to ISI and several new versions of the software were released from ISI during the contract period. Changes in the first release from ISI included bug fixes and extensions to support the needs of specific users. Among these changes was a new option to directory queries that allows attributes to be returned for all files in a directory together with the directory listing. This change greatly improves the performance of their server and reduces the number of packets sent across their trans-pacific connection to the rest of the internet. Several new access method were added to the Prospero file method. The Prospero Data Access Protocol was designed, to support secure retrieval of data from systems running Prospero

Architectural Tradeoffs for Unifying Campus Grid Resources

Most universities have a powerful collection of computing resources on campus for use in areas from high performance computing to general access student labs. However, these resources are rarely used to their full potential. Grid computing offers a way to unify these resources and to better utilize the capability they provide. The complexity of some grid tools makes learning to use them a daunting task for users not familiar with using the command line. Combining these tools together into a single web portal interface provides campus faculty and students with an easy way to access the campus resources. This paper presents some of the grid and portal tools that are currently available and tradeoffs in their selection and use. The successful implementation of a subset of these tools at the University of Arkansas and the functionality they provide are discussed in detail

XML content warehousing: Improving sociological studies of mailing lists and web data

In this paper, we present the guidelines for an XML-based approach for the sociological study of Web data such as the analysis of mailing lists or databases available online. The use of an XML warehouse is a flexible solution for storing and processing this kind of data. We propose an implemented solution and show possible applications with our case study of profiles of experts involved in W3C standard-setting activity. We illustrate the sociological use of semi-structured databases by presenting our XML Schema for mailing-list warehousing. An XML Schema allows many adjunctions or crossings of data sources, without modifying existing data sets, while allowing possible structural evolution. We also show that the existence of hidden data implies increased complexity for traditional SQL users. XML content warehousing allows altogether exhaustive warehousing and recursive queries through contents, with far less dependence on the initial storage. We finally present the possibility of exporting the data stored in the warehouse to commonly-used advanced software devoted to sociological analysis

The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007-2016)

One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in-situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide columnintegrated aerosol measurements, but observationally-constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean sea and parts of Central Asia, and the Atlantic and Indian Oceans between 2007 and 2016. The horizontal resolution is 0.1° latitude × 0.1° longitude, and the temporal resolution is 3 hours. The reanalysis was produced using Local Ensemble Transform Kalman Filter (LETKF) data assimilation in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper air (dust mass concentrations and extinction coefficient), surface (dust deposition and solar irradiance fields, among them) and total column (e.g., dust optical depth and load) variables. Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20 μm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector.We acknowledge the DustClim project which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union’s Horizon 2020 research and innovation programme (Grant n. 690462)

The MONARCH high-resolution reanalysis of desert dust aerosol over Northern Africa, the Middle East and Europe (2007–2016)

One of the challenges in studying desert dust aerosol along with its numerous interactions and impacts is the paucity of direct in situ measurements, particularly in the areas most affected by dust storms. Satellites typically provide column-integrated aerosol measurements, but observationally constrained continuous 3D dust fields are needed to assess dust variability, climate effects and impacts upon a variety of socio-economic sectors. Here, we present a high-resolution regional reanalysis data set of desert dust aerosols that covers Northern Africa, the Middle East and Europe along with the Mediterranean Sea and parts of central Asia and the Atlantic and Indian oceans between 2007 and 2016. The horizontal resolution is 0.1◦ latitude × 0.1◦ longitude in a rotated grid, and the temporal resolution is 3 h. The reanalysis was produced using local ensemble transform Kalman filter (LETKF) data assimilation in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) developed at the Barcelona Supercomputing Center (BSC). The assimilated data are coarse-mode dust optical depth retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Level 2 products. The reanalysis data set consists of upper-air variables (dust mass concentrations and the extinction coefficient), surface variables (dust deposition and solar irradiance fields among them) and total column variables (e.g. dust optical depth and load). Some dust variables, such as concentrations and wet and dry deposition, are expressed for a binned size distribution that ranges from 0.2 to 20 µm in particle diameter. Both analysis and first-guess (analysis-initialized simulation) fields are available for the variables that are diagnosed from the state vector. A set of ensemble statistics is archived for each output variable, namely the ensemble mean, standard deviation, maximum and median. The spatial and temporal distribution of the dust fields follows well-known dust cycle features controlled by seasonal changes in meteorology and vegetation cover. The analysis is statistically closer to the assimilated retrievals than the first guess, which proves the consistency of the data assimilation method. Independent evaluation using Aerosol Robotic Network (AERONET) dust-filtered optical depth retrievals indicates that the reanalysis data set is highly accurate (mean bias = −0.05, RMSE = 0.12 and r = 0.81 when compared to retrievals from the spectral de-convolution algorithm on a 3-hourly basis). Verification statistics are broadly homogeneous in space and time with regional differences that can be partly attributed to model limitations (e.g. poor representation of small-scale emission processes), the presence of aerosols other than dust in the observations used in the evaluation and differences in the number of observations among seasons. Such a reliable high-resolution historical record of atmospheric desert dust will allow a better quantification of dust impacts upon key sectors of society and economy, including health, solar energy production and transportation. The reanalysis data set (Di Tomaso et al., 2021) is distributed via Thematic Real-time Environmental Distributed Data Services (THREDDS) at BSC and is freely available at http://hdl.handle.net/21.12146/c6d4a608-5de3-47f6-a004-67cb1d498d98 (last access: 10 June 2022).This research has been supported by the DustClim project, which is part of ERA4CS, an ERA-NET programme co-funded by the European Union’s Horizon 2020 research and innovation programme (grant no. 690462); the European Research Council (FRAGMENT (grant no. 773051)); grant no. RYC-2015- 18690 funded by MCIN/AEI/10.13039/501100011033 and ESF Investing in your future; grant no. CGL2017-88911-R funded by MCIN/AEI/10.13039/501100011033 and ERDF A way of making Europe; the AXA Research Fund (AXA Chair on Sand and Dust Storms); the European Commission, Horizon 2020 Framework Programme (grant no. 792103 (SOLWARIS)); and ATMO-ACCESS (Access to Atmospheric Research Facilities) funded in the frame of the programme H2020-EU.1.4.1.2 (grant no. 101008004, 1 April 2021–31 March 2025). Jerónimo Escribano and Martina Klose have received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements H2020-MSCACOFUND-2016-754433 and H2020-MSCA-IF-2017-789630, respectively. Martina Klose received further support through the Helmholtz Association’s Initiative and Networking Fund (grant no. VH-NG-1533). This work has been partially funded by the contribution agreement between AEMET and BSC to carry out development and improvement activities of the products and services supplied by the World Meteorological Organization (WMO) Barcelona Dust Regional Center (i.e. the WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) Regional Center for Northern Africa, the Middle East and Europe).Peer ReviewedArticle signat per 24 autors/es: Enza Di Tomaso (1) , Jerónimo Escribano (1) , Sara Basart (1) , Paul Ginoux (2) , Francesca Macchia (1) , Francesca Barnaba (3) , Francesco Benincasa (1), Pierre-Antoine Bretonnière (1), Arnau Buñuel (1), Miguel Castrillo (1), Emilio Cuevas (4) , Paola Formenti (5) , María Gonçalves (1,6), Oriol Jorba (1), Martina Klose (1,7), Lucia Mona (8), Gilbert Montané Pinto (1) , Michail Mytilinaios (8), Vincenzo Obiso (1,a), Miriam Olid (1), Nick Schutgens (9) , Athanasios Votsis (10,11), Ernest Werner (12), and Carlos Pérez García-Pando (1,13) // (1) Barcelona Supercomputing Center (BSC), Barcelona, Spain; (2) NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA; (3) Consiglio Nazionale delle Ricerche–Istituto di Scienze dell’Atmosfera e del Clima (CNR–ISAC), Rome, Italy; (4) Izaña Atmospheric Research Center (IARC), Agencia Estatal de Meteorología (AEMET), Santa Cruz de Tenerife, Spain; (5) Université Paris Cité and Univ Paris-Est Créteil, CNRS, LISA, 75013 Paris, France; (6) Department of Project and Construction Engineering, Universitat Politècnica de Catalunya – BarcelonaTech (UPC), Terrassa, Spain; (7) Department Troposphere Research, Institute of Meteorology and Climate Research (IMK-TRO), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; (8) Consiglio Nazionale delle Ricerche–Istituto di Metodologie per l’Analisi Ambientale (CNR–IMAA), Tito Scalo (PZ), Italy; (9) Department of Earth Sciences, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands; (10) Section of Governance and Technology for Sustainability (BMS-CSTM), University of Twente, Enschede, the Netherlands; (11) Weather and Climate Change Impact Research, Finnish Meteorological Institute (FMI), Helsinki, Finland; (12) Agencia Estatal de Meteorología (AEMET), Barcelona, Spain; (13) ICREA, Catalan Institution for Research and Advanced Studies, Barcelona, Spain anow at: NASA Goddard Institute for Space Studies (GISS), New York, New York, USAObjectius de Desenvolupament Sostenible::13 - Acció per al Clima::13.3 - Millorar l’educació, la conscienciació i la capacitat humana i institucional en relació amb la mitigació del canvi climàtic, l’adaptació a aquest, la reducció dels efectes i l’alerta primerencaObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaPostprint (published version

Saharan dust transport and deposition towards the tropical northern Atlantic

We present a study of Saharan dust export towards the tropical North Atlantic using the regional dust emission, transport and deposition model LM-MUSCAT. Horizontal and vertical distribution of dust optical thickness, concentration, and dry and wet deposition rates are used to describe seasonality of dust export and deposition towards the eastern Atlantic for three typical months in different seasons. Deposition rates strongly depend on the vertical dust distribution, which differs with seasons. Furthermore the contribution of dust originating from the Bodélé Depression to Saharan dust over the Atlantic is investigated. A maximum contribution of Bodélé dust transported towards the Cape Verde Islands is evident in winter when the Bodélé source area is most active and dominant with regard to activation frequency and dust emission. Limitations of using satellite retrievals to estimate dust deposition are highlighted

Mobile Open Systems Technologies For The Utilities Industries

This chapter considers the provision of mobile computing support for field engineers in the electricity industry. Section 11.2 describes field engineers current working practices and from these derives a set of general requirements for a mobile computing environment to support utilities workers. A key requirement which is identified is the need for field engineers to access real-time multimedia information in the field and it is on this requirement that the remainder of the chapter focuses. Sections 11.3 and 11.4 present a survey of enabling technologies to support distributed systems operating in both local and wide area wireless environments. The impact of these technologies on the provision of mobile computing support is assessed in section 11.5. Section 11.6 describes a software architecture which attempts to address the requirements highlighted in section 11.2 and in particular is designed to support real-time access to data in the field. Finally, section 11.7 considers the degree to which utilities workers requirements can be met by the surveyed technologies and considers the likely impact of remote data access on field engineers working practices