Automated Surface Observing System (ASOS) User's Guide

Total Page:16

File Type:pdf, Size:1020Kb

Automated Surface Observing System (ASOS) User's Guide Automated Surface Observing System (ASOS) User’s Guide National Oceanic and Atmospheric Administration Department of Defense Federal Aviation Administration United States Navy March 1998 Foreward The 1990s have witnessed a carefully planned and executed modernization of the nation’s weather services. The Automated Surface Observing System (ASOS) is the first system to be operationally deployed as part of theis modernization. ASOS is therefore in the forefront of system deployments and associated service improvements that will require most of this decade to complete. In this sense, ASOS is the harbinger of 21st century weather services. In the end state, ASOS will be operational at about 1,000 airports across the United States. This system is the primary surface weather observing system in the United States, which supports the essential aviation observation programs of the National Weather Service (NWS), the Federal Aviation Administration (FAA), and the Department of Defense (DOD). The implementation of ASOS brings with it many opportunities and challenges. The opportunities include the unprecedented availability of timely, continuous and objective observations from many more locations. The challenges generally related to institutional learning needed to fully understand and adjust operation to take the greatest advantage of this new technological resource. The potential applications of the ASOS data go beyond that of providing basic weather information for aviation and forecasting; ASOS also will provide enhanced support to vital national programs such as public safety, hydrology, climatology, agriculture, and environmental protection, just to name a few. The ASOS User’s Guide is intended as basic reference and introduction to ASOS for a broad range of users. As of this writing (March 1998), there are about 500 commissioned ASOS’s nationwide. An additional 500 are coming on-line in the next few years. This deployment fulfills the commitment of the Government made over a decade ago to provide the nation a highly cost-effective, capable and reliable automated weather observing system for safe, efficient aviation operations and other applications. This achievement is made possible by the dedicated effort of many people throughout the government and private industry working together as a team to conceive, plan, develop, test and evaluate, implement, commission, monitor, maintain and operate a system. This ASOS User’s Guide is gratefully dedicated to all who have worked so hard to make ASOS a reality. Special thanks are extended to Dr. Jim Bradley for mentoring this program from the very beginning. Finally I wish to thank Dave Mannarano for coordinating the writing and production of this ASOS User’s Guide. Vickie L. Nadolski ASOS Program Manager Executive Summary Since the last Automated Surface Observing System (ASOS) User’s Guide was published in June 1992, numerous changes have occurred. These changes have, to the maximum practical extent, been incorporated into this updated version of the ASOS User’s Guide. These changes include the transition of observing code format from the Surface Aviation Observation (SAO) code to the Aviation Routine Weather Report (METAR) code in 1996; the implementation of new software loads into ASOS up to and including software Version 2.6; the incorporation of various sensor enhancements and improvements, including modification to the Heated Tipping Bucket precipitation accumulation gauge, the hygrothermometer, and anemometer; and incorporation of the Freezing Rain and Lightning Sensors into the ASOS sensor suite. Additional product improve- ment efforts are underway to further expand and improve the capabilities of ASOS. These efforts are also described in the ASOS User’s Guide. As of this writing (March 1998), there are about 500 commissioned ASOS’s nationwide. An additional 400 + are coming on-line in the next few years. This deployment fulfills the commitment the Government made over a decade ago to provide the nation a highly cost-effective, capable and reliable automated weather observing system for safe, efficient aviation operations and other applications. This achievement is made possible by the dedicated efforts of many people through- out the government and private industry working together as a team to conceive, plan, develop, test and evaluate, implement, commission, monitor, maintain and operate the system. This ASOS User’s Guide is gratefully dedicated to all who have worked so hard to make ASOS a reality. Special thanks are extended to Dr. Jim Bradley for mentoring this program from the very beginning. Finally I wish to thank Dave Mannarano for coordinating the writing and production of this ASOS User’s Guide. Vickie L. Nadolski ASOS Program Manager i Table of Contents CHAPTER ONE ..................................................................................................................................1 1.0 Introduction ................................................................................................................................ 1 1.1 Purpose and Scope .................................................................................................................... 1 1.2 Background ................................................................................................................................ 1 1.3 Total Surface Observation Concept........................................................................................... 2 1.4 Quality Control ........................................................................................................................... 2 1.5 General Conventions .................................................................................................................. 3 CHAPTER TWO .................................................................................................................................5 2.0 System Description .................................................................................................................... 5 2.1 System Components .................................................................................................................. 5 2.1.1 ASOS Sensor Groups ..................................................................................................... 5 2.1.2 Acquisition Control Unit .................................................................................................. 5 2.1.3 Operator Interface Device.............................................................................................. 9 2.2 ASOS Data Outlets ................................................................................................................... 9 2.3 ASOS Data Types ..................................................................................................................... 9 2.4 METAR Elements ..................................................................................................................... 9 2.5 Automated METAR vs. Manual METAR .............................................................................. 10 CHAPTER THREE .......................................................................................................................... 11 3.0 Automating the Objective Weather Elements.......................................................................... 11 3.1 Ambient and Dew Point Temperature ..................................................................................... 11 3.1.1 Ambient/Dew Point Temperature Sensor ..................................................................... 11 3.1.2 Ambient Temperature/Dew Point Temperature Algorithm .......................................... 12 3.1.3 Ambient Temperature/Dew Point Temperature Strengths and Limitations .................. 13 3.2 Wind ......................................................................................................................................... 14 3.2.1 Wind Sensor .................................................................................................................. 15 3.2.2 Wind Algorithm ............................................................................................................. 15 3.2.2.1 Wind Direction and Speed ................................................................................ 15 3.2.2.2 Wind Character ................................................................................................. 16 3.2.2.2a Gusts ................................................................................................. 16 3.2.2.2b Variable Wind ................................................................................... 16 3.2.2.2c Squalls............................................................................................... 17 3.2.2.3 Wind Remarks .................................................................................................. 17 3.2.2.3a Wind Shift ......................................................................................... 17 3.2.2.3b Peak Wind ........................................................................................ 18 3.2.3 Wind Strengths and Limitations ..................................................................................... 18 3.3 Pressure ................................................................................................................................... 18 3.3.1 Pressure Sensor ...........................................................................................................
Recommended publications
  • Geometric Characteristics of Clouds from Ceilometer Measurements and Radiosounding Methods
    GEOMETRIC CHARACTERISTICS OF CLOUDS FROM CEILOMETER MEASUREMENTS AND RADIOSOUNDING METHODS Montserrat Costa Surós Dipòsit legal: Gi. 1888-2014 http://hdl.handle.net/10803/284084 http://creativecommons.org/licenses/by/4.0/deed.ca Aquesta obra està subjecta a una llicència Creative Commons Reconeixement Esta obra está bajo una licencia Creative Commons Reconocimiento This work is licensed under a Creative Commons Attribution licence GEOMETRIC CHARACTERISTICS OF CLOUDS FROM CEILOMETER MEASUREMENTS AND RADIOSOUNDING METHODS DOCTORAL THESIS Montserrat Costa Surós 2014 DOCTORAL THESIS GEOMETRIC CHARACTERISTICS OF CLOUDS FROM CEILOMETER MEASUREMENTS AND RADIOSOUNDING METHODS Montserrat Costa Surós 2014 Doctoral Programme in Experimental Sciences and Sustainability Supervisors: Josep Calbó Angrill José Abel González Gutiérrez Thesis submitted for the degree of Doctor of Philosophy by the University of Girona El Dr. Josep Calbó Angrill i el Dr. José Abel González Gutiérrez, professors titulars del Departament de Física de la Universitat de Girona, CERTIFIQUEN: Que aquest treball, titulat “Geometric characteristics of clouds from ceilometer measurements and radiosounding methods”, que presenta la Montserrat Costa Surós per a l’obtenció del títol de doctora, ha estat realitzat sota la seva direcció. I, perquè així consti i tingui els efectes oportuns, signen aquest document. Dr. Josep Calbó Angrill Dr. José Abel González Gutiérrez Girona, 29 de juliol de 2014. Un esforç total és una victòria completa M. Ghandi Acknowledgments First and the most important I would like to thank my supervisors Dr. Josep Calbó and Dr. Josep- Abel González for giving me the opportunity to begin my research career with them, which has led to this doctoral thesis, and for their guidance and support during these years.
    [Show full text]
  • CHAPTER CONTENTS Page CHAPTER 5
    CHAPTER CONTENTS Page CHAPTER 5. SPECIAL PROFILING TECHNIQUES FOR THE BOUNDARY LAYER AND THE TROPOSPHERE .............................................................. 640 5.1 General ................................................................... 640 5.2 Surface-based remote-sensing techniques ..................................... 640 5.2.1 Acoustic sounders (sodars) ........................................... 640 5.2.2 Wind profiler radars ................................................. 641 5.2.3 Radio acoustic sounding systems ...................................... 643 5.2.4 Microwave radiometers .............................................. 644 5.2.5 Laser radars (lidars) .................................................. 645 5.2.6 Global Navigation Satellite System ..................................... 646 5.2.6.1 Description of the Global Navigation Satellite System ............. 647 5.2.6.2 Tropospheric Global Navigation Satellite System signal ........... 648 5.2.6.3 Integrated water vapour. 648 5.2.6.4 Measurement uncertainties. 649 5.3 In situ measurements ....................................................... 649 5.3.1 Balloon tracking ..................................................... 649 5.3.2 Boundary layer radiosondes .......................................... 649 5.3.3 Instrumented towers and masts ....................................... 650 5.3.4 Instrumented tethered balloons ....................................... 651 ANNEX. GROUND-BASED REMOTE-SENSING OF WIND BY HETERODYNE PULSED DOPPLER LIDAR ................................................................
    [Show full text]
  • Downloaded 09/25/21 08:19 AM UTC 662 JOURNAL of ATMOSPHERIC and OCEANIC TECHNOLOGY VOLUME 15 Mer 1987; Muller and Beekman 1987; Crescenti Et Al
    JUNE 1998 BREAKER ET AL. 661 Preliminary Results from Long-Term Measurements of Atmospheric Moisture in the Marine Boundary Layer in the Gulf of Mexico* LAURENCE C. BREAKER National Weather Service, NCEP, NOAA, Washington, D.C. DAVID B. GILHOUSEN National Weather Service, National Data Buoy Center, NOAA, Stennis Space Center, Mississippi LAWRENCE D. BURROUGHS National Weather Service, NCEP, NOAA, Washington, D.C. (Manuscript received 1 April 1997, in ®nal form 18 July 1997) ABSTRACT Measurements of boundary layer moisture have been acquired from Rotronic MP-100 sensors deployed on two National Data Buoy Center (NDBC) buoys in the northern Gulf of Mexico from June through November 1993. For one sensor that was retrieved approximately 8 months after deployment and a second sensor that was retrieved about 14 months after deployment, the pre- and postcalibrations agreed closely and fell within WMO speci®cations for accuracy. A second Rotronic sensor on one of the buoys provided the basis for a detailed comparison of the instruments and showed close agreement. A separate comparison of the Rotronic instrument with an HO-83 hygrometer at NDBC showed generally close agreement over a 1-month period, which included a number of fog events. The buoy observations of relative humidity and supporting data from the buoys were used to calculate speci®c humidity. Speci®c humidities from the buoys were compared with speci®c humidities computed from observations obtained from nearby ship reports, and the correlations were generally high (0.7± 0.9). Uncertainties in the calculated values of speci®c humidity were also estimated and ranged between 0.27% and 2.1% of the mean value, depending on the method used to estimate this quantity.
    [Show full text]
  • An LES-Based Airborne Doppler Lidar Simulator and Its Application to Wind Profiling in Inhomogeneous flow Conditions
    Atmos. Meas. Tech., 13, 1609–1631, 2020 https://doi.org/10.5194/amt-13-1609-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. An LES-based airborne Doppler lidar simulator and its application to wind profiling in inhomogeneous flow conditions Philipp Gasch1, Andreas Wieser1, Julie K. Lundquist2,3, and Norbert Kalthoff1 1Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany 2Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO 80303, USA 3National Renewable Energy Laboratory, Golden, CO 80401, USA Correspondence: Philipp Gasch ([email protected]) Received: 26 March 2019 – Discussion started: 5 June 2019 Revised: 19 February 2020 – Accepted: 19 February 2020 – Published: 2 April 2020 Abstract. Wind profiling by Doppler lidar is common prac- profiling at low wind speeds (< 5ms−1) can be biased, if tice and highly useful in a wide range of applications. Air- conducted in regions of inhomogeneous flow conditions. borne Doppler lidar can provide additional insights relative to ground-based systems by allowing for spatially distributed and targeted measurements. Providing a link between the- ory and measurement, a first large eddy simulation (LES)- 1 Introduction based airborne Doppler lidar simulator (ADLS) has been de- veloped. Simulated measurements are conducted based on Doppler lidar has experienced rapidly growing importance LES wind fields, considering the coordinate and geometric and usage in remote sensing of atmospheric winds over transformations applicable to real-world measurements. The the past decades (Weitkamp et al., 2005). Sectors with ADLS provides added value as the input truth used to create widespread usage include boundary layer meteorology, wind the measurements is known exactly, which is nearly impos- energy and airport management.
    [Show full text]
  • Creating Super Soldiers for Warfare: a Look Into the Laws of War
    CREATING SUPER SOLDIERS FOR WARFARE: A LOOK INTO THE LAWS OF WAR Christopher E. Sawin* I. Introduction “The wars of the future are very likely going to resemble many of the science fiction movies that we are watching right now.”1 Extreme developments in technology coupled with competition for global control have triggered futuristic ideas of utilizing super human * J.D. Candidate, Suffolk University Law School, 2017; Journal of High Technol- ogy Law Managing Editor 2016-2017; B.A. Criminal Justice, Curry College, 2013; United States Marine Corps Veteran, Infantry, 2005-2009. 1 See Michael Snyder, The U.S. Military is Creating Iron Men, Super Soldiers and Terminator Robots to Fight Future Wars, TRUTH (Oct. 10, 2013), archived at http://perma.cc/6ZTE-MYP4 (envisioning that future wars will be fought utilizing robots or human enhancement technology); see also Sean Adl-Tabatabai, US Army Says Next Major War Will Be Fought By Robots and Cyborgs, YOUR NEWS WIRE (July 25, 2015), archived at http://perma.cc/3GUM-Q5VQ (predicting that by around the year 2050, war fighting will be performed by robots and genetically modified super soldiers, rather than ordinary humans). The battlefield of the future will be populated by fewer humans, but these humans would be physically and mentally augmented with enhanced capabilities that improve their ability to sense their environment, make sense of their environment, and interact with one another, as well as with ‘unenhanced humans,’ automated processes, and machines of various kinds. ALEXANDER KOTT ET AL., VISUALIZING THE TACTICAL GROUND BATTLEFIELD IN THE YEAR 2050: WORKSHOP REPORT 7-8 (2015).
    [Show full text]
  • Clouds, Precipitation and Their Remote Sensing Intergovernmental
    25.09.12 Clouds, Precipitation and their Remote Sensing Prof. Susanne Crewell AG Integrated Remote Sensing Institute for Geophysics and Meteorology University of Cologne Susanne Crewell, Kompaktkurs, Jülich24. 25 September September 2012 2012 Intergovernmental Panel on Climate Change (IPCC) www.ipcc.ch Nobel price 2007 IPCC Fourth Assessment Report (FAR), 2007: "Warming of the climate system is unequivocal", and "Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations". Aerosols, clouds and their interaction with climate is still the most uncertain area of climate change and require multidisciplinary coordinated research efforts. SusanneSusS sanna ne Crewell,Crewewellelll,K, Kompaktkurs,Kompakta kurs, JülichJülJüü ichchc 252 SeptemberSSeeptetetembembber 201220121 1 25.09.12 Why are clouds so complex? Cloud microphysical processes occur on small spatial scales and need to be parametrized in atmospheric models Cloud microphysics is strongly connected to other sub-grid scale processes (turbulence, radiation) Cloud droplets 0.01 mm diameter 100-1000 per cm3 Condensation nuclei Drizzle droplets 0.001 mm diameter 0.1 mm diameter 1000 per cm3 1 per cm3 Rain drops ca. 1 mm diameter, 1 drops per liter Susannesa Crewell, Kompaktkurs, Jülich 25 September 2012 Why are clouds so complex? From hydrometeors to single clouds to Einzelwolken to the global and cloud fields system Susanne Crewell, Kompaktkurs, Jülich 25 September
    [Show full text]
  • The Error Is the Feature: How to Forecast Lightning Using a Model Prediction Error [Applied Data Science Track, Category Evidential]
    The Error is the Feature: How to Forecast Lightning using a Model Prediction Error [Applied Data Science Track, Category Evidential] Christian Schön Jens Dittrich Richard Müller Saarland Informatics Campus Saarland Informatics Campus German Meteorological Service Big Data Analytics Group Big Data Analytics Group Offenbach, Germany ABSTRACT ACM Reference Format: Despite the progress within the last decades, weather forecasting Christian Schön, Jens Dittrich, and Richard Müller. 2019. The Error is the is still a challenging and computationally expensive task. Current Feature: How to Forecast Lightning using a Model Prediction Error: [Ap- plied Data Science Track, Category Evidential]. In Proceedings of 25th ACM satellite-based approaches to predict thunderstorms are usually SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19). based on the analysis of the observed brightness temperatures in ACM, New York, NY, USA, 10 pages. different spectral channels and emit a warning if a critical threshold is reached. Recent progress in data science however demonstrates 1 INTRODUCTION that machine learning can be successfully applied to many research fields in science, especially in areas dealing with large datasets. Weather forecasting is a very complex and challenging task requir- We therefore present a new approach to the problem of predicting ing extremely complex models running on large supercomputers. thunderstorms based on machine learning. The core idea of our Besides delivering forecasts for variables such as the temperature, work is to use the error of two-dimensional optical flow algorithms one key task for meteorological services is the detection and pre- applied to images of meteorological satellites as a feature for ma- diction of severe weather conditions.
    [Show full text]
  • Precipitation Effects of Giant Cloud Condensation Nuclei Artificially Introduced Into Stratocumulus Clouds
    Atmos. Chem. Phys., 15, 5645–5658, 2015 www.atmos-chem-phys.net/15/5645/2015/ doi:10.5194/acp-15-5645-2015 © Author(s) 2015. CC Attribution 3.0 License. Precipitation effects of giant cloud condensation nuclei artificially introduced into stratocumulus clouds E. Jung1, B. A. Albrecht1, H. H. Jonsson2, Y.-C. Chen3,4, J. H. Seinfeld3, A. Sorooshian5, A. R. Metcalf3,*, S. Song1, M. Fang1, and L. M. Russell6 1Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, USA 2Center for Interdisciplinary Remotely-Piloted Aircraft Studies, Naval Postgraduate School, Monterey, California, USA 3California Institute of Technology, Pasadena, California, USA 4Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA 5Department of Chemical and Environmental Engineering, and Department of Atmospheric Sciences, University of Arizona, Tucson, Arizona, USA 6Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA *now at: Department of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota, California, USA Correspondence to: E. Jung ([email protected]) Received: 7 November 2014 – Published in Atmos. Chem. Phys. Discuss.: 7 January 2015 Revised: 6 April 2015 – Accepted: 11 April 2015 – Published: 22 May 2015 Abstract. To study the effect of giant cloud condensation 1 Introduction nuclei (GCCN) on precipitation processes in stratocumulus clouds, 1–10 µm diameter salt particles (salt powder) were The stratocumulus (Sc) cloud deck is the most persistent released from an aircraft while flying near the cloud top on cloud type in the world, and the variations of the cloud 3 August 2011 off the central coast of California. The seeded amount and the albedo can significantly impact the climate area was subsequently sampled from the aircraft that was system through their radiative effects on the earth system equipped with aerosol, cloud, and precipitation probes and (e.g., Hartmann et al., 1992; Slingo, 1990).
    [Show full text]
  • Touching the Clouds Activity Guide
    Touching the Clouds Activity Guide Purpose Provide a mental representation of each cloud type Create a tactile cloud identification chart Overview Individuals will construct and touch a tactile model of common types of clouds to learn how to describe the clouds based on their shape and texture. They will compare their descriptions with the standard classifications using the cloud types identified in the GLOBE Clouds Protocol. Time: 45 minutes to 1 ½ hours, depending on individual’s age Level: All Materials (per person) One large sheet of cardstock (18” x 12”) Tape One set of Braille labels for each cloud type and/or markers One small feather A layered piece of blanket or soft fabric (eight 1’ X 1” pieces) Cotton balls of varied sizes One tissue Organza or a similar material, cut into pieces, one layered 1” x 1” piece Pillow stuffing, one 1” x 1” piece A tsp of sand Three paper clips Liquid glue Scissors Baby Wipes Preparation Use tape to divide the large cardstock sheet in four sections: one for the cloud title at the top and three for the altitudes: using a portrait layout, place three pieces of tape horizontally, from side to side of the sheet. 1. 1” off the upper edge of the sheet 2. 8” off the upper edge of the sheet 1 Steps What to do and how to do it: Making A Tactile Cloud Identification Chart 1. Discuss that clouds come in three basic shapes: cirrus, stratus and cumulus. a. Feel of the 4” feather and describe it; discuss that these wispy clouds are high in the sky and are named cirrus.
    [Show full text]
  • 6.4 the Warning Time for Cloud-To-Ground Lightning in Isolated, Ordinary Thunderstorms Over Houston, Texas
    6.4 THE WARNING TIME FOR CLOUD-TO-GROUND LIGHTNING IN ISOLATED, ORDINARY THUNDERSTORMS OVER HOUSTON, TEXAS Nathan C. Clements and Richard E. Orville Texas A&M University, College Station, Texas 1. INTRODUCTION shear and buoyancy, with small magnitudes of vertical wind shear likely to produce ordinary, convective Lightning is a natural but destructive phenomenon storms. Weisman and Klemp (1986) describe the short- that affects various locations on the earth’s surface lived single cell storm as the most basic convective every year. Uman (1968) defines lightning as a self- storm. Therefore, this ordinary convective storm type will propagating atmospheric electrical discharge that results be the focus of this study. from the accumulation of positive and negative space charge, typically occurring within convective clouds. This 1.2 THUNDERSTORM CHARGE STRUCTURE electrical discharge can occur in two basic ways: cloud flashes and ground flashes (MacGorman and Rust The primary source of lightning is electric charge 1998, p. 83). The latter affects human activity, property separated in a cloud type known as a cumulonimbus and life. Curran et al. (2000) find that lightning is ranked (Cb) (Uman 1987). Interactions between different types second behind flash and river flooding as causing the of hydrometeors within a cloud are thought to carry or most deaths from any weather-related event in the transfer charges, thus creating net charge regions United States. From 1959 to 1994, there was an throughout a thunderstorm. Charge separation can average of 87 deaths per year from lightning. Curran et either come about by inductive mechanisms (i.e. al. also rank the state of Texas as third in the number of requires an electric field to induce charge on the surface fatalities from 1959 to 1994, behind Florida at number of the hydrometeor) or non-inductive mechanisms (i.e.
    [Show full text]
  • Rightsizing Project Nextgen IOC Sensor Assessment Summary AJP
    RightSizing Project NextGen IOC Sensor Assessment Summary AJP-6830 1 of 64 December 1, 2009 RightSizing Project NextGen IOC Sensor Assessment Summary TABLE OF CONTENTS EXECUTIVE SUMMARY ............................................................................................................ 3 1 INTRODUCTION ................................................................................................................ 4 1.1 Context and Motivation .....................................................................................................4 1.1.1 NextGen ......................................................................................................................4 1.1.2 4D weather cube ........................................................................................................4 1.1.3 Weather observation and forecast requirements to meet NextGen goals .................5 1.2 RightSizing Project Goals ....................................................................................................6 1.2.1 Assessment of Sensor Network ..................................................................................7 1.2.2 Identification of gaps based on functional and performance requirements ..............8 1.2.3 Development of master plan to meet NextGen weather observation requirements .8 1.3 Scope of this Report (FY 2009) ...........................................................................................8 2 PROGRAM MANAGEMENT AND SCHEDULE ......................................................................
    [Show full text]
  • Raman Lidar for Meteorological Observations, RALMO – Part 1: Open Access Instrument Description Climate Climate of the Past 1 1 2 2 1,3 4 of The1 Past T
    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 Atmospheric Atmospheric Chemistry Chemistry and Physics and Physics Discussions Open Access Open Access Atmos. Meas. Tech., 6, 1329–1346, 2013 Atmospheric Atmospheric www.atmos-meas-tech.net/6/1329/2013/ doi:10.5194/amt-6-1329-2013 Measurement Measurement © Author(s) 2013. CC Attribution 3.0 License. Techniques Techniques Discussions Open Access Open Access Biogeosciences Biogeosciences Discussions Open Access Raman Lidar for Meteorological Observations, RALMO – Part 1: Open Access Instrument description Climate Climate of the Past 1 1 2 2 1,3 4 of the1 Past T. Dinoev , V. Simeonov , Y. Arshinov , S. Bobrovnikov , P. Ristori , B. Calpini , M. Parlange , and H. van den Discussions Bergh5 1 Open Access Laboratory of Environmental Fluid Mechanics and Hydrology (EFLUM), Ecole Polytechnique Fed´ erale´ de Lausanne Open Access EPFL-ENAC, Station 2, 1015 Lausanne, Switzerland Earth System 2 Earth System V.E. Zuev Institute of Atmospheric Optics SB RAS1, Academician Zuev Square, Tomsk, 634021, Russia Dynamics 3Division´ Lidar, CEILAP (UNIDEF-CITEDEF-MINDEF-CONICET), San Juan Bautista de La SalleDynamics 4397 (B1603ALO), Villa Martelli, Buenos Aires, Argentina Discussions 4Federal Office of Meteorology and Climatology MeteoSwiss, Atmospheric Data, P.O. Box 316, 1530 Payerne, Switzerland 5 Open Access Laboratory of Air and Soil Pollution, Ecole Polytechnique Fed´ erale´ de Lausanne EPFL, StationGeoscientific 6, Geoscientific Open Access 1015 Lausanne, Switzerland Instrumentation Instrumentation Correspondence to: V. B.
    [Show full text]