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Off-Line Algorithm for Calculation of Vertical Tracer Transport in The
EGU Journal Logos (RGB) Open Access Open Access Open Access Advances in Annales Nonlinear Processes Geosciences Geophysicae in Geophysics Open Access Open Access Natural Hazards Natural Hazards and Earth System and Earth System Sciences Sciences Discussions Open Access Open Access Atmos. Chem. Phys., 13, 1093–1114, 2013 Atmospheric Atmospheric www.atmos-chem-phys.net/13/1093/2013/ doi:10.5194/acp-13-1093-2013 Chemistry Chemistry © Author(s) 2013. CC Attribution 3.0 License. and Physics and Physics Discussions Open Access Open Access Atmospheric Atmospheric Measurement Measurement Techniques Techniques Off-line algorithm for calculation of vertical tracer transport in the Discussions Open Access troposphere due to deep convection Open Access Biogeosciences 1,2 1 3,4,5 6 7 8 Biogeosciences9 10 D. A. Belikov , S. Maksyutov , M. Krol , A. Fraser , M. Rigby , H. Bian , A. Agusti-Panareda , D. Bergmann , Discussions P. Bousquet11, P. Cameron-Smith10, M. P. Chipperfield12, A. Fortems-Cheiney11, E. Gloor12, K. Haynes13,14, P. Hess15, S. Houweling3,4, S. R. Kawa8, R. M. Law14, Z. Loh14, L. Meng16, P. I. Palmer6, P. K. Patra17, R. G. Prinn18, R. Saito17, 12 Open Access and C. Wilson Open Access 1Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa,Climate Tsukuba, Ibaraki, Climate 305-8506, Japan of the Past 2 of the Past Division for Polar Research, National Institute of Polar Research, 10-3, Midoricho, Tachikawa, Tokyo 190-8518, Japan Discussions 3SRON Netherlands Institute for Space Research, Sorbonnelaan -
Gridded Model Output Statistics: Improving and Expanding
6A.6 GRIDDED MODEL OUTPUT STATISTICS: IMPROVING AND EXPANDING Kathryn K. Gilbert*, Bob Glahn, Rebecca L. Cosgrove1, Kari L. Sheets, Geoffrey A. Wagner2 Meteorological Development Laboratory National Weather Service, NOAA Silver Spring, MD 1National Center for Environmental Prediction, National Weather Service, Camp Springs, MD 2Wyle Information Systems, McLean, VA 1. INTRODUCTION Since the original implementation, gridded MOS has undergone several adaptations to improve For years, National Weather Service (NWS) consistency as well as regional applicability. MDL forecasters have used Model Output Statistics developers have welcomed assessments of grid- (MOS) guidance (Glahn and Lowry 1972) as an ded MOS from local forecasters in order to make aid in producing text forecast products issued to adjustments to provide guidance which is both the user community. However, the methods fore- representative of the local area, and compatible casters use to generate products have changed with the process for generating forecasts for because of requirements to produce the official NDFD. Some of the improvements resulting from NWS 7-day forecasts on high-resolution grids. forecaster feedback include: removal of unrepre- These gridded, or digital, forecasts are put into a sentative forecasts from the analysis, expansion of National Digital Forecast Database (NDFD; Glahn the grid coverage, and modifications to the and Ruth 2003). NWS forecasters need support- land/water mask. ing guidance available on a grid, at a resolution comparable to the grid resolution used at the local In this paper, we discuss the current state of forecast office. One approach to the problem of the gridded MOS suite, as well as ongoing en- providing guidance on the required grid is to objec- hancements to the operational GFS-based MOS tively analyze forecasts at MOS stations. -
Verification of a Multimodel Storm Surge Ensemble Around New York City and Long Island for the Cool Season
922 WEATHERANDFORECASTING V OLUME 26 Verification of a Multimodel Storm Surge Ensemble around New York City and Long Island for the Cool Season TOM DI LIBERTO * AND BRIAN A. C OLLE School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York NICKITAS GEORGAS AND ALAN F. B LUMBERG Stevens Institute of Technology, Hoboken, New Jersey ARTHUR A. T AYLOR Meteorological Development Laboratory, NOAA/NWS, Office of Science and Technology, Silver Spring, Maryland (Manuscript received 21 November 2010, in final form 27 June 2011) ABSTRACT Three real-time storm surge forecasting systems [the eight-member Stony Brook ensemble (SBSS), the Stevens Institute of Technology’s New York Harbor Observing and Prediction System (SIT-NYHOPS), and the NOAA Extratropical Storm Surge (NOAA-ET) model] are verified for 74 available days during the 2007–08 and 2008–09 cool seasons for five stations around the New York City–Long Island region. For the raw storm surge forecasts, the SIT-NYHOPS model has the lowest root-mean-square errors (RMSEs) on average, while the NOAA-ET has the largest RMSEs after hour 24 as a result of a relatively large negative surge bias. The SIT-NYHOPS and SBSS also have a slight negative surge bias after hour 24. Many of the underpredicted surges in the SBSS ensemble are associated with large waves at an offshore buoy, thus illustrating the potential importance of nearshore wave breaking (radiation stresses) on the surge pre- dictions. A bias correction using the last 5 days of predictions (BC) removes most of the surge bias in the NOAA-ET model, with the NOAA-ET-BC having a similar level of accuracy as the SIT-NYHOPS-BC for positive surges. -
Seasonal and Diurnal Performance of Daily Forecasts with WRF V3.8.1 Over the United Arab Emirates
Geosci. Model Dev., 14, 1615–1637, 2021 https://doi.org/10.5194/gmd-14-1615-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates Oliver Branch1, Thomas Schwitalla1, Marouane Temimi2, Ricardo Fonseca3, Narendra Nelli3, Michael Weston3, Josipa Milovac4, and Volker Wulfmeyer1 1Institute of Physics and Meteorology, University of Hohenheim, 70593 Stuttgart, Germany 2Department of Civil, Environmental, and Ocean Engineering (CEOE), Stevens Institute of Technology, New Jersey, USA 3Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates 4Meteorology Group, Instituto de Física de Cantabria, CSIC-University of Cantabria, Santander, Spain Correspondence: Oliver Branch ([email protected]) Received: 19 June 2020 – Discussion started: 1 September 2020 Revised: 10 February 2021 – Accepted: 11 February 2021 – Published: 19 March 2021 Abstract. Effective numerical weather forecasting is vital in T2 m bias and UV10 m bias, which may indicate issues in sim- arid regions like the United Arab Emirates (UAE) where ex- ulation of the daytime sea breeze. TD2 m biases tend to be treme events like heat waves, flash floods, and dust storms are more independent. severe. Hence, accurate forecasting of quantities like surface Studies such as these are vital for accurate assessment of temperatures and humidity is very important. To date, there WRF nowcasting performance and to identify model defi- have been few seasonal-to-annual scale verification studies ciencies. By combining sensitivity tests, process, and obser- with WRF at high spatial and temporal resolution. vational studies with seasonal verification, we can further im- This study employs a convection-permitting scale (2.7 km prove forecasting systems for the UAE. -
Verification of Model Output Statistics Forecasts Associated with the North
Allison Monarski, University of Maryland Masters Scholarly Paper, December 6, 2011 1 Department of Atmospheric and Oceanic Science Verification of Model Output Statistics forecasts associated with the North American Mesoscale model upgrade Results of work done during the Student Career Experience Program tour with the Statistical Modeling Branch (SMB) of the Meteorological Development Lab (MDL) of the National Weather Service (NWS), Silver Spring, MD, under the guidance of Mark Antolik & Kathy Gilbert, NWS/MDL/SMB I. Introduction and Motivation For the past four decades, the model output statistics (MOS) technique has been in operation and forecasters and meteorologists globally have used forecasts generated through MOS. MOS is a statistical approach to forecasting which involves determination of a relationship between a predictand and numerical weather prediction (NWP) model output for a variety of variables (predictors) at the same projection times (Glahn and Lowry 1972). Through the years, MOS has provided reliable forecasts, predicting quantities that the underlying NWP model is unable to predict. Specifically, the MOS technique can account for local effects on certain elements that the coarser resolution NWP model cannot detect (Antolik and Baker 2009). Usually, statistical forecasting systems, such as MOS, rely on many years of stable development data for optimal performance. However, due to frequent changes in the underlying structure, physics, and dynamics of the NWP models, this kind of data is difficult to obtain. Fortunately, developers at the National Weather Service’s (NWS) Meteorological Development Laboratory (MDL) have been able to show that reliable MOS forecasts can be produced using as little as just two years of data from models which are evolving (Antolik and Baker 2009). -
High-Resolution Simulations of Freezing Drizzle and Freezing Rain and Comparisons to Observations
High-resolution simulations of freezing drizzle and freezing rain and comparisons to observations Greg Thompson Research Applications Laboratory National Center for Atmospheric Research additional contributions by: Roy Rasmussen, Trude Eidhammer, Kyoko Ikeda, Changhai Liu, Pedro Jimenez, Mei Xu, Stan Benjamin Winterwind 7 Feb 2017, Skelleftea, Sweden Outline • Brief History • High-Resolution Forecasts o Supercooled water drops aloft o Ground icing • Verification o Weather Research & Forecasting, WRF o High Resolution Rapid Refresh, HRRR • Next steps o Time-lag ensemble average o Making clouds better o WISLINE project and AROME model With respect to Numerical Weather Prediction The microphysics scheme is a component in a weather model responsible for: • Condensing water vapor into droplets • Model collisions with other droplets to become drizzle/rain • Creating ice crystals via droplet freezing or vapor-to-ice conversion • Growing ice crystals to snow size • Letting snow collect cloud water droplets (riming or accretion) • Large drops freeze into hail, snow rimes heavily to create graupel • Making rain, snow, and graupel fall to earth • etc. The treatment of processes going between water vapor, liquid water, and ice. Cloud physics & precipitation NCAR-RAL microphysics scheme Scheme version/generation Research or operational model Reisner, Rasmussen, Bruintjes (1998MWR) MM5 Rapid Update Cycle (RUC) Thompson, Rasmussen, Manning (2004MWR) MM5 WRF RUC Thompson, Field, Rasmussen, Hall (2008MWR) MM5 WRF & HWRF RUC Rapid Refresh (RAP) High-Res -
FAA Advisory Circular AC 91-74B
U.S. Department Advisory of Transportation Federal Aviation Administration Circular Subject: Pilot Guide: Flight in Icing Conditions Date:10/8/15 AC No: 91-74B Initiated by: AFS-800 Change: This advisory circular (AC) contains updated and additional information for the pilots of airplanes under Title 14 of the Code of Federal Regulations (14 CFR) parts 91, 121, 125, and 135. The purpose of this AC is to provide pilots with a convenient reference guide on the principal factors related to flight in icing conditions and the location of additional information in related publications. As a result of these updates and consolidating of information, AC 91-74A, Pilot Guide: Flight in Icing Conditions, dated December 31, 2007, and AC 91-51A, Effect of Icing on Aircraft Control and Airplane Deice and Anti-Ice Systems, dated July 19, 1996, are cancelled. This AC does not authorize deviations from established company procedures or regulatory requirements. John Barbagallo Deputy Director, Flight Standards Service 10/8/15 AC 91-74B CONTENTS Paragraph Page CHAPTER 1. INTRODUCTION 1-1. Purpose ..............................................................................................................................1 1-2. Cancellation ......................................................................................................................1 1-3. Definitions.........................................................................................................................1 1-4. Discussion .........................................................................................................................6 -
Large-Scale Tropospheric Transport in the Chemistry–Climate Model Initiative (CCMI) Simulations
Atmos. Chem. Phys., 18, 7217–7235, 2018 https://doi.org/10.5194/acp-18-7217-2018 © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations Clara Orbe1,2,3,a, Huang Yang3, Darryn W. Waugh3, Guang Zeng4, Olaf Morgenstern 4, Douglas E. Kinnison5, Jean-Francois Lamarque5, Simone Tilmes5, David A. Plummer6, John F. Scinocca7, Beatrice Josse8, Virginie Marecal8, Patrick Jöckel9, Luke D. Oman10, Susan E. Strahan10,11, Makoto Deushi12, Taichu Y. Tanaka12, Kohei Yoshida12, Hideharu Akiyoshi13, Yousuke Yamashita13,14, Andreas Stenke15, Laura Revell15,16, Timofei Sukhodolov15,17, Eugene Rozanov15,17, Giovanni Pitari18, Daniele Visioni18, Kane A. Stone19,20,b, Robyn Schofield19,20, and Antara Banerjee21 1Goddard Earth Sciences Technology and Research (GESTAR), Columbia, MD, USA 2Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA 3Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, USA 4National Institute of Water and Atmospheric Research, Wellington, New Zealand 5National Center for Atmospheric Research (NCAR), Atmospheric Chemistry Observations and Modeling (ACOM) Laboratory, Boulder, USA 6Climate Research Branch, Environment and Climate Change Canada, Montreal, QC, Canada 7Climate Research Branch, Environment and Climate Change Canada, Victoria, BC, Canada 8Centre National de Recherches Météorologiques UMR 3589, Météo-France/CNRS, -
1999-2000 Annual Report
Anglo-Australian Observatory Annual Report of the Anglo-Australian Telescope Board 1 July 1999 to 30 June 2000 ANGLO-AUSTRALIAN OBSERVATORY PO Box 296, Epping, NSW 1710, Australia 167 Vimiera Road, Eastwood, NSW 2122, Australia PH (02) 9372 4800 (international) + 61 2 9372 4800 FAX (02) 9372 4880 (international) + 61 2 9372 4880 e-mail [email protected] ANGLO-AUSTRALIAN TELESCOPE BOARD PO Box 296, Epping, NSW 1710, Australia 167 Vimiera Road, Eastwood, NSW 2122, Australia PH (02) 9372 4813 (international) + 61 2 9372 4813 FAX (02) 9372 4880 (international) + 61 2 9372 4880 e-mail [email protected] ANGLO-AUSTRALIAN TELESCOPE/UK SCHMIDT TELESCOPE PriVate Bag, Coonabarabran, NSW 2357, Australia PH (02) 6842 6291 (international) + 61 2 6842 6291 AAT FAX (02) 6884 2298 (international) + 61 2 6884 298 UKST FAX (02) 6842 2288 (international) + 61 2 6842 2288 WWW http://www.aao.gov.au/ © Anglo-Australian Telescope Board 2000 ISSN 1443-8550 COVER: A digital image of the Antennae galaxies (NGC4038-39) made by combining three images from the Tek2 CCD on the AAT (Steve Lee and David Malin). A new wide field CCD Imager (WFI) will come into use in 2000 and will enable many more images like this to be made. COVER DESIGN: Encore International COMPUTER TYPESET AT THE: Anglo-Australian ObserVatory ii The Right Honourable Stephen Byers, MP, President of the Board of Trade and Secretary of State for Trade and Industry, Government of the United Kingdom of Great Britain and Northern Ireland The Honourable Dr David Kemp, MP, Minister for Education, Training and Youth Affairs GoVernment of the Commonwealth of Australia In accordance with Article 8 of the Agreement between the Australian GoVernment and the GoVernment of the United Kingdom to proVide for the establishment and operation of an optical telescope at Siding Spring Mountain in the state of New South Wales, I present herewith a report by the Anglo-Australian Telescope Board for the year from 1 July 1999 to 30 June 2000. -
Assimila Blank
NERC NERC Strategy for Earth System Modelling: Technical Support Audit Report Version 1.1 December 2009 Contact Details Dr Zofia Stott Assimila Ltd 1 Earley Gate The University of Reading Reading, RG6 6AT Tel: +44 (0)118 966 0554 Mobile: +44 (0)7932 565822 email: [email protected] NERC STRATEGY FOR ESM – AUDIT REPORT VERSION1.1, DECEMBER 2009 Contents 1. BACKGROUND ....................................................................................................................... 4 1.1 Introduction .............................................................................................................. 4 1.2 Context .................................................................................................................... 4 1.3 Scope of the ESM audit ............................................................................................ 4 1.4 Methodology ............................................................................................................ 5 2. Scene setting ........................................................................................................................... 7 2.1 NERC Strategy......................................................................................................... 7 2.2 Definition of Earth system modelling ........................................................................ 8 2.3 Broad categories of activities supported by NERC ................................................. 10 2.4 Structure of the report ........................................................................................... -
A Guide to Smartphone Astrophotography National Aeronautics and Space Administration
National Aeronautics and Space Administration A Guide to Smartphone Astrophotography National Aeronautics and Space Administration A Guide to Smartphone Astrophotography A Guide to Smartphone Astrophotography Dr. Sten Odenwald NASA Space Science Education Consortium Goddard Space Flight Center Greenbelt, Maryland Cover designs and editing by Abbey Interrante Cover illustrations Front: Aurora (Elizabeth Macdonald), moon (Spencer Collins), star trails (Donald Noor), Orion nebula (Christian Harris), solar eclipse (Christopher Jones), Milky Way (Shun-Chia Yang), satellite streaks (Stanislav Kaniansky),sunspot (Michael Seeboerger-Weichselbaum),sun dogs (Billy Heather). Back: Milky Way (Gabriel Clark) Two front cover designs are provided with this book. To conserve toner, begin document printing with the second cover. This product is supported by NASA under cooperative agreement number NNH15ZDA004C. [1] Table of Contents Introduction.................................................................................................................................................... 5 How to use this book ..................................................................................................................................... 9 1.0 Light Pollution ....................................................................................................................................... 12 2.0 Cameras ................................................................................................................................................ -
Anexo Ii: Catálogos De Espectros Estelares
ANEXO II: CATÁLOGOS DE ESPECTROS ESTELARES Base de datos de espectros estelares del enfoque híbrido I 1 (continuación) 2 (continuación) Catálogo G. H. Jacoby & D. A. Hunter & C. A. Christian 3 4 (continuación) 5 (continuación) Catálogo A.J. Pickles 1988 6 7 (continuación) Catálogo Silva 1992 8 Num Name Sp Type Vr Teff log g 1 HD000245 G2V -93.73 5433. 3.50 2 HD000358 B8IVmnp.. -33.90 14007. 3.77 3 HD000400 F8IV -15.13 6146. 4.09 4 HD000693 F5V 14.79 6156. 4.13 5 HD001227 G8II-III -0.03 5063. 2.65 6 HD001835 G3V -2.46 5777. 4.45 7 HD002665 G5IIIwe -382.34 5004. 2.27 8 HD002665 G5IIIwe -382.57 5004. 2.27 9 HD002796 Fw -61.36 4920. 1.39 10 HD003268 F7V -23.40 6130. 4.01 11 HD003546 G5III... -84.14 4769. 2.22 12 HD003567 F5V -47.62 5991. 3.96 13 HD003628 G2V -27.09 5701. 4.06 14 HD003712 K0II-IIIva -4.49 4608. 2.20 15 HD003712 K0II-IIIva -4.45 4608. 2.20 16 HD004306 G0 -61.71 4933. 1.96 17 HD004306 G0 -61.71 4933. 1.96 18 HD004307 G2V -10.36 5806. 4.04 19 HD004395 G5 -0.75 5471. 3.32 20 HD004614 G0V... 8.29 5890. 4.40 21 HD005234 K2III -23.56 4385. 1.58 22 HD005395 G8III-IV -48.08 4708. 2.42 23 HD005448 A5V 9.60 8029. 3.90 24 HD005516 G8III-IV -25.49 4940. 2.70 25 HD005600 F8 3.70 6631. 3.98 26 HD005916 G8III-IV -68.17 4874.