Coordination of Atmospheric Dispersion Activities for the Real-Time Decision Support System RODOS
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Climate Models and Their Evaluation
8 Climate Models and Their Evaluation Coordinating Lead Authors: David A. Randall (USA), Richard A. Wood (UK) Lead Authors: Sandrine Bony (France), Robert Colman (Australia), Thierry Fichefet (Belgium), John Fyfe (Canada), Vladimir Kattsov (Russian Federation), Andrew Pitman (Australia), Jagadish Shukla (USA), Jayaraman Srinivasan (India), Ronald J. Stouffer (USA), Akimasa Sumi (Japan), Karl E. Taylor (USA) Contributing Authors: K. AchutaRao (USA), R. Allan (UK), A. Berger (Belgium), H. Blatter (Switzerland), C. Bonfi ls (USA, France), A. Boone (France, USA), C. Bretherton (USA), A. Broccoli (USA), V. Brovkin (Germany, Russian Federation), W. Cai (Australia), M. Claussen (Germany), P. Dirmeyer (USA), C. Doutriaux (USA, France), H. Drange (Norway), J.-L. Dufresne (France), S. Emori (Japan), P. Forster (UK), A. Frei (USA), A. Ganopolski (Germany), P. Gent (USA), P. Gleckler (USA), H. Goosse (Belgium), R. Graham (UK), J.M. Gregory (UK), R. Gudgel (USA), A. Hall (USA), S. Hallegatte (USA, France), H. Hasumi (Japan), A. Henderson-Sellers (Switzerland), H. Hendon (Australia), K. Hodges (UK), M. Holland (USA), A.A.M. Holtslag (Netherlands), E. Hunke (USA), P. Huybrechts (Belgium), W. Ingram (UK), F. Joos (Switzerland), B. Kirtman (USA), S. Klein (USA), R. Koster (USA), P. Kushner (Canada), J. Lanzante (USA), M. Latif (Germany), N.-C. Lau (USA), M. Meinshausen (Germany), A. Monahan (Canada), J.M. Murphy (UK), T. Osborn (UK), T. Pavlova (Russian Federationi), V. Petoukhov (Germany), T. Phillips (USA), S. Power (Australia), S. Rahmstorf (Germany), S.C.B. Raper (UK), H. Renssen (Netherlands), D. Rind (USA), M. Roberts (UK), A. Rosati (USA), C. Schär (Switzerland), A. Schmittner (USA, Germany), J. Scinocca (Canada), D. Seidov (USA), A.G. -
Evaluation of Fast Atmospheric Dispersion Models in a Regular
Evaluation of fast atmospheric dispersion models in a regular street network Denise Hertwig, Lionel Soulhac, Vladimír Fuka, Torsten Auerswald, Matteo Carpentieri, Paul Hayden, Alan Robins, Zheng-Tong Xie, Omduth Coceal To cite this version: Denise Hertwig, Lionel Soulhac, Vladimír Fuka, Torsten Auerswald, Matteo Carpentieri, et al.. Eval- uation of fast atmospheric dispersion models in a regular street network. Environmental Fluid Me- chanics, Springer Verlag, 2018, 10.1007/s10652-018-9587-7. hal-01761232 HAL Id: hal-01761232 https://hal.archives-ouvertes.fr/hal-01761232 Submitted on 8 Apr 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Environ Fluid Mech manuscript No. (will be inserted by the editor) 1 Evaluation of fast atmospheric dispersion models in a regular 2 street network 3 Denise Hertwig · Lionel Soulhac · Vladim´ır 4 Fuka · Torsten Auerswald · Matteo Carpentieri · 5 Paul Hayden · Alan Robins · Zheng-Tong Xie · 6 Omduth Coceal 7 8 Received: date / Accepted: date 9 Abstract The need to balance computational speed and simulation accuracy is a key chal- 10 lenge in designing atmospheric dispersion models that can be used in scenarios where near 11 real-time hazard predictions are needed. -
Results from the Implementation of the Elastic Viscous Plastic Sea Ice Rheology in Hadcm3 W
Results from the implementation of the Elastic Viscous Plastic sea ice rheology in HadCM3 W. M. Connolley, A. B. Keen, A. J. Mclaren To cite this version: W. M. Connolley, A. B. Keen, A. J. Mclaren. Results from the implementation of the Elastic Viscous Plastic sea ice rheology in HadCM3. Ocean Science, European Geosciences Union, 2006, 2 (2), pp.201- 211. hal-00298295 HAL Id: hal-00298295 https://hal.archives-ouvertes.fr/hal-00298295 Submitted on 23 Oct 2006 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Ocean Sci., 2, 201–211, 2006 www.ocean-sci.net/2/201/2006/ Ocean Science © Author(s) 2006. This work is licensed under a Creative Commons License. Results from the implementation of the Elastic Viscous Plastic sea ice rheology in HadCM3 W. M. Connolley1, A. B. Keen2, and A. J. McLaren2 1British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, UK 2Met Office Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK Received: 13 June 2006 – Published in Ocean Sci. Discuss.: 10 July 2006 Revised: 21 September 2006 – Accepted: 16 October 2006 – Published: 23 October 2006 Abstract. We present results of an implementation of the a full dynamical model incorporating wind stresses and in- Elastic Viscous Plastic (EVP) sea ice dynamics scheme into ternal ice stresses leads to errors in the detailed representa- the Hadley Centre coupled ocean-atmosphere climate model tion of sea ice and limits our confidence in its future predic- HadCM3. -
Atmospheric Dispersion Modelling of Bioaerosols That Are Pathogenic to Humans and Livestock – a Review to Inform Risk Assessment Studies
Microbial Risk Analysis 1 (2016) 19–39 Contents lists available at ScienceDirect Microbial Risk Analysis journal homepage: www.elsevier.com/locate/mran Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock – A review to inform risk assessment studies J.P.G. Van Leuken a,b,∗,A.N.Swarta, A.H. Havelaar a,b,c, A. Van Pul d, W. Van der Hoek a, D. Heederik b a Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands b Institute for Risk Assessment Sciences (IRAS), Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands c Emerging Pathogens Institute and Animal Sciences Department, University of Florida, Gainesville, FL, United States of America d Environment & Safety (M&V), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands article info abstract Article history: In this review we discuss studies that applied atmospheric dispersion models (ADM) to bioaerosols that Received 19 May 2015 are pathogenic to humans and livestock in the context of risk assessment studies. Traditionally, ADMs have Revised 25 June 2015 been developed to describe the atmospheric transport of chemical pollutants, radioactive matter, dust, and Accepted 17 July 2015 particulate matter. However, they have also enabled researchers to simulate bioaerosol dispersion. Availableonline26July2015 To inform risk assessment, the aims of this review were fourfold, namely (1) to describe the most im- Keywords: portant physical processes related to ADMs and pathogen transport, (2) to discuss studies that focused on Airborne the application of ADMs to pathogenic bioaerosols, (3) to discuss emission and inactivation rate parameter- Pathogens isations, and (4) to discuss methods for conversion of concentrations to infection probabilities (concerning Respiratory infections quantitative microbial risk assessment). -
Dispersion Modeling of Air Pollutants in the Atmosphere: a Review
Cent. Eur. J. Geosci. • 6(3) • 2014 • 257-278 DOI: 10.2478/s13533-012-0188-6 Central European Journal of Geosciences Dispersion modeling of air pollutants in the atmosphere: a review Research Article Ádám Leelossy˝ 1, Ferenc Molnár Jr.2, Ferenc Izsák3, Ágnes Havasi3, István Lagzi4, Róbert Mészáros1∗ 1 Department of Meteorology, Eötvös Loránd University, Budapest, Hungary 2 Department of Physics, Applied Physics, and Astronomy, Rensselaer Polytechnic Institute, Troy, New York, USA 3 Department of Applied Analysis and Computational Mathematics, Eötvös Loránd University, Budapest, Hungary 4 Department of Physics, Budapest University of Technology and Economics, Budapest, Hungary Received 22 October 2013; accepted 15 May 2014 Abstract: Modeling of dispersion of air pollutants in the atmosphere is one of the most important and challenging scientific problems. There are several natural and anthropogenic events where passive or chemically active compounds are emitted into the atmosphere. The effect of these chemical species can have serious impacts on our environment and human health. Modeling the dispersion of air pollutants can predict this effect. Therefore, development of various model strategies is a key element for the governmental and scientific communities. We provide here a brief review on the mathematical modeling of the dispersion of air pollutants in the atmosphere. We discuss the advantages and drawbacks of several model tools and strategies, namely Gaussian, Lagrangian, Eulerian and CFD models. We especially focus on several recent advances in this multidisciplinary research field, like parallel computing using graphical processing units, or adaptive mesh refinement. Keywords: air pollution modeling • Lagrangian model • Eulerian model • CFD; accidental release • parallel computing © Versita sp. -
Influence of Ozone Recovery and Greenhouse Gas Increases on Southern Hemisphere Circulation Alexey Y
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, D22117, doi:10.1029/2010JD014423, 2010 Influence of ozone recovery and greenhouse gas increases on Southern Hemisphere circulation Alexey Y. Karpechko,1,2 Nathan P. Gillett,3 Lesley J. Gray,4 and Mauro Dall’Amico5,6 Received 27 April 2010; revised 6 September 2010; accepted 13 September 2010; published 24 November 2010. [1] Stratospheric ozone depletion has significantly influenced the tropospheric circulation and climate of the Southern Hemisphere (SH) over recent decades, the largest trends being detected in summer. These circulation changes include acceleration of the extratropical tropospheric westerly jet on its poleward side and lowered Antarctic sea level pressure. It is therefore expected that ozone changes will continue to influence climate during the 21st century when ozone recovery is expected. Here we use two contrasting future ozone projections from two chemistry‐climate models (CCMs) to force 21st century simulations of the HadGEM1 coupled atmosphere‐ocean model, along with A1B greenhouse gas (GHG) concentrations, and study the simulated response in the SH circulation. According to several studies, HadGEM1 simulates present tropospheric climate better than the majority of other available models. When forced by the larger ozone recovery trends, HadGEM1 simulates significant deceleration of the tropospheric jet on its poleward side in the upper troposphere in summer, but the trends in the lower troposphere are not significant. In the simulations with the smaller ozone recovery trends the zonal mean zonal wind trends are not significant throughout the troposphere. The response of the SH circulation to GHG concentration increases in HadGEM1 includes an increase in poleward eddy heat flux in the stratosphere and positive sea level pressure trends in southeastern Pacific. -
Performance Assessment of General Circulation Model in Simulating Daily Precipitation and Temperature Using Multiple Gridded Datasets
water Article Performance Assessment of General Circulation Model in Simulating Daily Precipitation and Temperature Using Multiple Gridded Datasets Najeebullah Khan 1,2, Shamsuddin Shahid 1 , Kamal Ahmed 1,2, Tarmizi Ismail 1 , Nadeem Nawaz 2 and Minwoo Son 3,* 1 School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Malaysia; [email protected] (N.K.); [email protected] (S.S.); [email protected] (K.A.); [email protected] (T.I.) 2 Faculty of Water Resource Management, Lasbela University of Agriculture Water and Marine Sciences (LUAWMS), 90150 Uthal, Balochistan, Pakistan; [email protected] 3 Department of Civil Engineering, Chungnam National University, Daejeon 34134, Korea * Correspondence: [email protected]; Tel.: +82-42-821-5676 Received: 28 September 2018; Accepted: 4 December 2018; Published: 6 December 2018 Abstract: The performance of general circulation models (GCMs) in a region are generally assessed according to their capability to simulate historical temperature and precipitation of the region. The performance of 31 GCMs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) is evaluated in this study to identify a suitable ensemble for daily maximum, minimum temperature and precipitation for Pakistan using multiple sets of gridded data, namely: Asian Precipitation– Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Berkeley Earth Surface Temperature (BEST), Princeton Global Meteorological Forcing (PGF) and Climate Prediction Centre (CPC) data. An entropy-based robust feature selection approach known as symmetrical uncertainty (SU) is used for the ranking of GCM. It is known from the results of this study that the spatial distribution of best-ranked GCMs varies for different sets of gridded data. -
General Circulation Models and Their Role in the Climate Modeling Hierarchy
Solving Problems with GCMs: General Circulation Models and Their Role in the Climate Modeling Hierarchy Michael Ghil and Andrew W. Robertson Department of Atmospheric Sciences & Institute of Geophysics and Planetary Physics University of California at Los Angeles, Los Angeles, California 90095-1565 Revised version April 28, 1999 In General Circulation Model Development: Past, Present, and Future (Arakawa Festschrift), D. Randall (Ed.), Academic Press, sub judice. Abstract We outline the familiar concept of a hierarchy of models for solving problems in climate dynamics. General circulation models (GCMs) occupy a special position at the apex of this hierarchy, and provide the main link between basic concepts—best captured by very simple, “toy” models—and the incomplete and inaccurate observations of climate variability in space and time. We illustrate this role of GCMs in addressing the problems of climate variability on three time scales: intraseasonal, seasonal-to-interannual, and interdecadal. The problems involved require the use of atmospheric, oceanic, and coupled ocean-atmosphere GCMs. We emphasize the role of dynamical systems theory in communicating between the rungs of the modeling hierarchy—toy models, intermediate ones, and GCMs—and between modeling results and observations. - 2 - Table of Contents Page Nos. I. Introduction: the modeling hierarchy 4 A. Atmospheric modeling 4 B. Ocean and coupled modeling 8 C. Dynamical systems theory 9 II. Intraseasonal oscillations, their theory and simulation 11 A. Extratropical oscillations: observations and theory 12 B. GCM simulations and their validation 14 III. El Niño–Southern Oscillation, from the Devil’s Staircase to prediction 16 A. ENSO's regularity and irregularity 16 B. -
Wind Energy Department Annual Progress Report 2001
View metadata,Downloaded citation and from similar orbit.dtu.dk papers on:at core.ac.uk Dec 19, 2017 brought to you by CORE provided by Online Research Database In Technology Wind Energy Department annual progress report 2001 Skrumsager, Birthe; Larsen, Søren Ejling; Madsen, Peter Hauge Publication date: 2002 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Skrumsager, B., Larsen, S. E., & Madsen, P. H. (2002). Wind Energy Department annual progress report 2001. (Denmark. Forskningscenter Risoe. Risoe-R; No. 1317(EN)). General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Risø-R-1317(EN) Wind Energy Department Annual Progress Report 2001 Birthe Skrumsager, Søren E. Larsen and Peter Hauge Madsen (Eds) Risø National Laboratory, Roskilde October 2002 Abstract The report describes the work of the Wind Energy Department at Risø National Laboratory in 2001. -
Meteorology and Atmospheric Dispersion
3.3 Meteorology and atmospheric dispersion A system integrated comprehensive atmospheric dispersion module has been built from models suitable for fast real-time atmospheric dispersion calculations as suggested by [1], cf. Table 1. TABLE 1: THE MET-RODOS MODULE: Associated models and data Near-range flow and dispersion models, including pre-processors: · Meteorological pre-processor (PAD) · Mass Consistent Flow model (MCF) · Linearized flow model (LINCOM) · Puff model with gamma dose (RIMPUFF) · Near-range elongated puff model (ATSTEP) Complex terrain models (stand alone system): · Prognostic flow model (ADREA) and Lagrangian dispersion model (DIPCOT) Mesoscale and Long-range Models: · Hybrid Lagrangian-Eulerian model (MATCH) On-line Weather Forecast data: · Numerical Weather Prediction data (DMI-HIRLAM and SPA -TYPHOON) The module is called MET-RODOS and it consists of models and pre-processors contributed to by Work Group 2 (Atmospheric Dispersion) partners. 3.3.1 The MET-RODOS module A schematic overview of the system integrated MET-RODOS atmospheric dispersion module [2] is presented in Figure 1. Details about the systems „functionality specification“ is described in [3] whereas the systems User’s manual [4] holds references to the systems User’s guides, input/output specifications and test runs. The MET-RODOS dispersion module contains three distinguishable sub-systems: • The Local-Scale Pre-processor LSP, • The Local-Scale Model Chain LSMC, and • The long-range Model Chain LRMC 57 On-site Off-site N So dar ’ s Met- +4 Hr Towers W -
(Non-LWR) Reactor Mechanistic Source Term Analysis
ANL/NSE-20/39 SAND2021-3250 R Survey and Assessment of Computational Capabilities for Advanced (Non-LWR) Reactor Mechanistic Source Term Analysis Nuclear Science and Engineering Division, Argonne National Laboratory Nuclear Energy Safety Technologies Group, Sandia National Laboratories About Argonne National Laboratory Argonne is a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC under contract DE-AC02-06CH11357. The Laboratory’s main facility is outside Chicago, at 9700 South Cass Avenue, Argonne, Illinois 60439. For information about Argonne and its pioneering science and technology programs, see www.anl.gov. About Sandia National Laboratories Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. DOCUMENT AVAILABILITY Online Access: U.S. Department of Energy (DOE) reports produced after 1991 and a growing number of pre-1991 documents are available free at OSTI.GOV (http://www.osti.gov/), a service of the US Dept. of Energy’s Office of Scientific and Technical Information. Reports not in digital format may be purchased by the public from the National Technical Information Service (NTIS): U.S. Department of Commerce National Technical Information Service 5301 Shawnee Rd Alexandria, VA 22312 www.ntis.gov Phone: (800) 553-NTIS (6847) or (703) 605-6000 Fax: (703) 605-6900 Email: [email protected] Reports not in digital format are available to DOE and DOE contractors from the Office of Scientific and Technical Information (OSTI): U.S. -
The Atmosphere-Ocean General Circulation Model EMAC-MPIOM
Geosci. Model Dev., 4, 771–784, 2011 www.geosci-model-dev.net/4/771/2011/ Geoscientific doi:10.5194/gmd-4-771-2011 Model Development © Author(s) 2011. CC Attribution 3.0 License. The Atmosphere-Ocean General Circulation Model EMAC-MPIOM A. Pozzer1,2, P. Jockel¨ 2,*, B. Kern2, and H. Haak3 1The Cyprus Institute, Energy, Environment and Water Research Center, Nicosia, Cyprus 2Atmospheric Chemistry Department, Max-Planck Institute for Chemistry, Mainz, Germany 3Ocean in the Earth System, Max-Planck Institute for Meteorology, Hamburg, Germany *now at: Deutsches Zentrum fur¨ Luft- und Raumfahrt, Institut fur¨ Physik der Atmosphare,¨ Oberpfaffenhofen, Germany Received: 8 February 2011 – Published in Geosci. Model Dev. Discuss.: 4 March 2011 Revised: 6 September 2011 – Accepted: 6 September 2011 – Published: 9 September 2011 Abstract. The ECHAM/MESSy Atmospheric Chemistry constituent cycles, such as the carbon, sulfur or nitrogen cy- (EMAC) model is coupled to the ocean general circulation cle are to be studied. Historically, the different model com- model MPIOM using the Modular Earth Submodel System ponents have been mostly developed independently, and at (MESSy) interface. MPIOM is operated as a MESSy sub- a later stage they have been connected to create AO-GCMs model, thus the need of an external coupler is avoided. The (Valcke, 2006; Sausen and Voss, 1996). However, as indi- coupling method is tested for different model configurations, cated by the Fourth Assessment Report of the Intergovern- proving to be very flexible in terms of parallel decompo- mental Panel on Climate Change (IPCC AR4), no model sition and very well load balanced. The run-time perfor- used in the AR4 presented a complete and online calcula- mance analysis and the simulation results are compared to tion of atmospheric chemistry.