Snow, Weather, and Avalanches
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A Winter Forecasting Handbook Winter Storm Information That Is Useful to the Public
A Winter Forecasting Handbook Winter storm information that is useful to the public: 1) The time of onset of dangerous winter weather conditions 2) The time that dangerous winter weather conditions will abate 3) The type of winter weather to be expected: a) Snow b) Sleet c) Freezing rain d) Transitions between these three 7) The intensity of the precipitation 8) The total amount of precipitation that will accumulate 9) The temperatures during the storm (particularly if they are dangerously low) 7) The winds and wind chill temperature (particularly if winds cause blizzard conditions where visibility is reduced). 8) The uncertainty in the forecast. Some problems facing meteorologists: Winter precipitation occurs on the mesoscale The type and intensity of winter precipitation varies over short distances. Forecast products are not well tailored to winter Subtle features, such as variations in the wet bulb temperature, orography, urban heat islands, warm layers aloft, dry layers, small variations in cyclone track, surface temperature, and others all can influence the severity and character of a winter storm event. FORECASTING WINTER WEATHER Important factors: 1. Forcing a) Frontal forcing (at surface and aloft) b) Jetstream forcing c) Location where forcing will occur 2. Quantitative precipitation forecasts from models 3. Thermal structure where forcing and precipitation are expected 4. Moisture distribution in region where forcing and precipitation are expected. 5. Consideration of microphysical processes Forecasting winter precipitation in 0-48 hour time range: You must have a good understanding of the current state of the Atmosphere BEFORE you try to forecast a future state! 1. Examine current data to identify positions of cyclones and anticyclones and the location and types of fronts. -
METAR/SPECI Reporting Changes for Snow Pellets (GS) and Hail (GR)
U.S. DEPARTMENT OF TRANSPORTATION N JO 7900.11 NOTICE FEDERAL AVIATION ADMINISTRATION Effective Date: Air Traffic Organization Policy September 1, 2018 Cancellation Date: September 1, 2019 SUBJ: METAR/SPECI Reporting Changes for Snow Pellets (GS) and Hail (GR) 1. Purpose of this Notice. This Notice coincides with a revision to the Federal Meteorological Handbook (FMH-1) that was effective on November 30, 2017. The Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM) approved the changes to the reporting requirements of small hail and snow pellets in weather observations (METAR/SPECI) to assist commercial operators in deicing operations. 2. Audience. This order applies to all FAA and FAA-contract weather observers, Limited Aviation Weather Reporting Stations (LAWRS) personnel, and Non-Federal Observation (NF- OBS) Program personnel. 3. Where can I Find This Notice? This order is available on the FAA Web site at http://faa.gov/air_traffic/publications and http://employees.faa.gov/tools_resources/orders_notices/. 4. Cancellation. This notice will be cancelled with the publication of the next available change to FAA Order 7900.5D. 5. Procedures/Responsibilities/Action. This Notice amends the following paragraphs and tables in FAA Order 7900.5. Table 3-2: Remarks Section of Observation Remarks Section of Observation Element Paragraph Brief Description METAR SPECI Volcanic eruptions must be reported whenever first noted. Pre-eruption activity must not be reported. (Use Volcanic Eruptions 14.20 X X PIREPs to report pre-eruption activity.) Encode volcanic eruptions as described in Chapter 14. Distribution: Electronic 1 Initiated By: AJT-2 09/01/2018 N JO 7900.11 Remarks Section of Observation Element Paragraph Brief Description METAR SPECI Whenever tornadoes, funnel clouds, or waterspouts begin, are in progress, end, or disappear from sight, the event should be described directly after the "RMK" element. -
Weather and Snow Observations for Avalanche Forcasting: an Evaluation of Errors in Measurement and Interpretation
143 WEATHER AND SNOW OBSERVATIONS FOR AVALANCHE FORCASTING: AN EVALUATION OF ERRORS IN MEASUREMENT AND INTERPRETATION R.T. Marriottl and M.B. Moorel Abstract.--Measurements of weather and snow parameters for snow stability forecasting may frequently contain false or misleading information. Such error~ can be attributed primarily to poor selection of the measuring sites and to inconsistent response of the sensors to changing weather conditions. These problems are examined in detail and some remedies are suggested. INTRODUCTION SOURCES OF ERROR A basic premise of snow stability analysis for Errors which arise in instrumented snow and avalanche forecasting is that point measurements of weather measurements can be broken into two, if snow and weather parameters can be used to infer the somewhat overlapping, parts: those associated with snow and weather conditions over a large area. Due the representativeness of the site where the to the complexity of this process in the mountain measurements are to be taken, and those associated environment, this "extrapolation" of data has with the response of the instrument to its largely been accomplished subjectively by an environment. individual experienced with the area in question. This experience was usually gained by visiting the The first source of error is associated with areas of concern, during many differing types of the site chosen for measurements. The topography of conditions, allowing a qualitative correlation mountains results in dramatic variations in between the measured point data and variations in conditions over short distances and often times the snow and weather conditions over the area. these variations are not easily predictable. For example, temperature, which may often be In many instances today, the forecast area has extrapolated to other elevations using approximate expanded, largely due to increased putlic use of lapse rates, may on some occasions be complicated by avalanche-prone terrain (e.g. -
ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARY
ESSENTIALS OF METEOROLOGY (7th ed.) GLOSSARY Chapter 1 Aerosols Tiny suspended solid particles (dust, smoke, etc.) or liquid droplets that enter the atmosphere from either natural or human (anthropogenic) sources, such as the burning of fossil fuels. Sulfur-containing fossil fuels, such as coal, produce sulfate aerosols. Air density The ratio of the mass of a substance to the volume occupied by it. Air density is usually expressed as g/cm3 or kg/m3. Also See Density. Air pressure The pressure exerted by the mass of air above a given point, usually expressed in millibars (mb), inches of (atmospheric mercury (Hg) or in hectopascals (hPa). pressure) Atmosphere The envelope of gases that surround a planet and are held to it by the planet's gravitational attraction. The earth's atmosphere is mainly nitrogen and oxygen. Carbon dioxide (CO2) A colorless, odorless gas whose concentration is about 0.039 percent (390 ppm) in a volume of air near sea level. It is a selective absorber of infrared radiation and, consequently, it is important in the earth's atmospheric greenhouse effect. Solid CO2 is called dry ice. Climate The accumulation of daily and seasonal weather events over a long period of time. Front The transition zone between two distinct air masses. Hurricane A tropical cyclone having winds in excess of 64 knots (74 mi/hr). Ionosphere An electrified region of the upper atmosphere where fairly large concentrations of ions and free electrons exist. Lapse rate The rate at which an atmospheric variable (usually temperature) decreases with height. (See Environmental lapse rate.) Mesosphere The atmospheric layer between the stratosphere and the thermosphere. -
A Meteorological and Blowing Snow Data Set (2000–2016) from a High-Elevation Alpine Site (Col Du Lac Blanc, France, 2720 M A.S.L.)
Earth Syst. Sci. Data, 11, 57–69, 2019 https://doi.org/10.5194/essd-11-57-2019 © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. A meteorological and blowing snow data set (2000–2016) from a high-elevation alpine site (Col du Lac Blanc, France, 2720 m a.s.l.) Gilbert Guyomarc’h1,5, Hervé Bellot2, Vincent Vionnet1,3, Florence Naaim-Bouvet2, Yannick Déliot1, Firmin Fontaine2, Philippe Puglièse1, Kouichi Nishimura4, Yves Durand1, and Mohamed Naaim2 1Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d’Etudes de la Neige, Grenoble, France 2Univ. Grenoble Alpes, IRSTEA, UR ETNA, 38042 St-Martin-d’Hères, France 3Centre for Hydrology, University of Saskatchewan, Saskatoon, SK, Canada 4Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan 5Météo France, DIRAG, Point à Pitre, Guadeloupe, France Correspondence: Florence Naaim-Bouvet (fl[email protected]) Received: 12 June 2018 – Discussion started: 25 June 2018 Revised: 8 October 2018 – Accepted: 9 November 2018 – Published: 11 January 2019 Abstract. A meteorological and blowing snow data set from the high-elevation experimental site of Col du Lac Blanc (2720 m a.s.l., Grandes Rousses mountain range, French Alps) is presented and detailed in this pa- per. Emphasis is placed on data relevant to the observations and modelling of wind-induced snow transport in alpine terrain. This process strongly influences the spatial distribution of snow cover in mountainous terrain with consequences for snowpack, hydrological and avalanche hazard forecasting. In situ data consist of wind (speed and direction), snow depth and air temperature measurements (recorded at four automatic weather stations), a database of blowing snow occurrence and measurements of blowing snow fluxes obtained from a vertical pro- file of snow particle counters (2010–2016). -
Chemical Properties of Snow Cover As an Impact Indicator for Local Air Pollution Sources
INFRASTRUKTURA I EKOLOGIA TERENÓW WIEJSKICH INFRASTRUCTURE AND ECOLOGY OF RURAL AREAS No IV/2/2017, POLISH ACADEMY OF SCIENCES, Cracow Branch, pp. 1591–1607 Commission of Technical Rural Infrastructure DOI: http://dx.medra.org/10.14597/infraeco.2017.4.2.120 CHEMICAL PROPERTIES OF SNOW COVER AS AN IMPACT INDICATOR FOR LOCAL AIR POLLUTION SOURCES Krzysztof Jarzyna, Rafał Kozłowski, Mirosław Szwed Jan Kochanowski University Abstract In this article, selected physical and chemical properties of water originating from melted snow collected in the area of the city of Ostrowiec Świętokrzyski (Poland) in January 2017 were determined. The analysed samples of snow were collected at 18 measurement sites located along the axis of cardinal directions of the world and with a central point in the urban area of Ostrowiec Świętokrzyski in January 2017. Chemical com- position was determined using the Dionex ICS 3000 Ion Chromatograph at the Environmental Research Laboratory of the Chair of Environmental Protection and Modelling at the Jan Kochanowski University in Kielce. The obtained results indicated a substantial contribution of pollutants pro- duced by a local steelworks in the chemical composition of melted snow. Keywords: precipitation chemistry, anthropopressure, snow cover INTRODUCTION The use of snow cover as an indicator for the magnitude of deposition of atmospheric air pollutants has already had several decades of tradition in Poland and Europe (Engelhard et al. 2007, Kozłowski et al. 2012, Siudek et al. 2015, Stachnik et al. 2010,). The snow cover proves itself as an efficient collector of airborne pollutants which allows for quick and efficient estimation of airborne pollution concentrations over the entire period of lingering snow cover occur- This is an open access article under the Creative Commons BY-NC-ND license (http://creativecommons.org/licences/by-nc-nd/4.0/) 1591 Krzysztof Jarzyna, Rafał Kozłowski, Mirosław Szwed rence. -
Snow Accumulation Algorithm for the Wsr-88D Radar: Supplemental Report
R-99-11 SNOW ACCUMULATION ALGORITHM FOR THE WSR-88D RADAR: SUPPLEMENTAL REPORT November 1999 U.S. DEPARTMENT OF THE INTERIOR Bureau of Reclamation Technical Service Center Civil Engineering Services Materials Engineering and Research Laboratory Denver, Colorado R-99-11 SNOW ACCUMULATION ALGORITHM FOR THE WSR-88D RADAR: SUPPLEMENTAL REPORT by Edmond W. Holroyd, III Technical Service Center Civil Engineering Services Materials Engineering and Research Laboratory Denver, Colorado November 1999 UNITED STATES DEPARTMENT OF THE INTERIOR ò BUREAU OF RECLAMATION ACKNOWLEDGMENTS This work extends previous efforts that were supported primarily by the WSR-88D (Weather Surveillance Radar - 1988 Doppler) OSF (Operational Support Facility) and the NEXRAD (Next Generation Weather Radar) Program. Significant additional support was provided by the Bureau of Reclamation’s Research and Technology Transfer Program, directed by Dr. Stanley Ponce, and by the NOAA (National Oceanic and Atmospheric Administration) Office of Global Programs GEWEX (Global Energy and Water Cycle Experiment) GCIP (Continental-Scale International Project ), directed by Dr. Rick Lawford. Most of the work for this supplemental report was performed and coordinated by Dr. Arlin B. Super, since retired. Programming and data support was provided by Ra Aman, Linda Rogers, and Anne Reynolds. In additional, we had useful feedback from several NWS (National Weather Service) personnel. Reviewer comments by Curt Hartzell and Mark Fresch were very helpful. U.S. Department of the Interior Mission Statement The Mission of the Department of the Interior is to protect and provide access to our Nation’s natural and cultural heritage and honor our trust responsibilities to tribes. Bureau of Reclamation Mission Statement The mission of the Bureau of Reclamation is to manage, develop, and protect water and related resources in an environmentally and economically sound manner in the interest of the American public. -
Snow to Water Ratios 88
Snow to Water Ratios 88 The amount of snow from a storm can look impressive when it covers your house and cars, but if you melted the snow you would discover that very little water is actually involved. The 'snow to ice ratio' or Snow Ratio expresses how much volume of snow you get for a given volume of water. Typically a ratio of 10:1 (ten to one) means that every 10 inches of snowfall equals one inch of liquid water. Problem 1 - During a winter storm called 'Snowmageddon' in 2010, the Washington DC region received about 24 inches of snow fall. If this was dry, uncompacted snow, about how many inches of rain would this equal if the Snow Ratio was 10:1 ? Problem 2 - The Snow Ratio depends on the temperature of the air as shown in the table below: o o o o o o Temp (F) 30 25 18 12 5 -10 Ratio 10:1 15:1 20:1 30:1 40:1 50:1 o If 30 inches of snow fell in Calgary, Alberta at 18 F, and 25 inches of snow fell in o Denver, Colorado where the temperature was 25 F, at which location would the most water have fallen? Space Math http://spacemath.gsfc.nasa.gov Answer Key 88 Problem 1 - During a winter storm called 'Snowmageddon' in 2010, the Washington DC region received about 24 inches of snow fall. If this was dry, uncompacted snow, about how many inches of rain would this equal if the Snow Ratio was 10:1 ? Answer: 24 inches of snow x (1 inch water/10 inches of snow) = 2.4 inches of water. -
Snow Removal Brochure
LEHI CITY SNOW REMOVAL A Guide to Managing Winter Storms THE LEHI CITY STREETS DIVISION’S PRIORITY IS TO PROVIDE THE SAFEST POSSIBLE DRIVING CONDITIONS. SNOW REMOVAL IS DEPENDENT ON A NUMBER OF FACTORS, INCLUDING THE TIMING AND DURATION OF A SNOWSTORM AND THE DENSITY OF THE SNOW. THIS GUIDE PROVIDES RESIDENTS WITH INFORMATION ABOUT THE SNOW REMOVAL PROGRAM AND SETS EXPECTATIONS DURING AND AFTER A STORM. SNOW CONDITIONS The Lehi City Streets Division makes it a priority to be responsive during and immediately after a storm. Response time to individual streets and neighborhoods will depend on several factors, including timing and duration of the storm. TIMING Crews will make every effort to keep major streets clear of snow and ice. Heavily traveled roads and bus routes will receive top priority to ensure everyone’s safety. Once major commuter roads have been deemed safe for travel, secondary and side streets will be cleared. During evening and early morning storms, crews should have ample time to prepare for commuting hours. Plows will continue to clean, treat, and widen roadways until reasonably safe conditions are met. DURATION The duration of a storm plays an important role in snow plowing operations. Storms of extended duration require all available resources to keep roads open over an extended period of time. A snow storm of four inches over a 24-hour period will require more time and man hours than a storm of six inches over an 8-hour period. Please keep in mind that plows are still hard at work well after the snow has stopped falling. -
Vol.37 No.6 D'océanographie
ISSN 1195-8898 . CMOS Canadian Meteorological BULLETIN and Oceanographic Society SCMO La Société canadienne de météorologie et December / décembre 2009 Vol.37 No.6 d'océanographie Le réseau des stations automatiques pour les Olympiques ....from the President’s Desk Volume 37 No.6 December 2009 — décembre 2009 Friends and colleagues: Inside / En Bref In late October I presented the CMOS from the President’s desk Brief to the House of Allocution du président Commons Standing by/par Bill Crawford page 177 Committee on Finance at its public hearing in Cover page description Winnipeg. (The full text Description de la page couverture page 178 of this brief was published in our Highlights of Recent CMOS Meetings page 179 October Bulletin). Ron Correspondence / Correspondance page 179 Stewart accompanied me in this presentation. Articles He is a past president of CMOS and Head of the The Notoriously Unpredictable Monsoon Department of by Madhav Khandekar page 181 Environment and Geography at the The Future Role of the TV Weather Bill Crawford Presenter by Claire Martin page 182 CMOS President University of Manitoba. In the five minutes for Président de la SCMO Ocean Acidification by James Christian page 183 our talk we presented three requests for the federal government to consider in its The Interacting Scale of Ocean Dynamics next budget: Les échelles d’interaction de la dynamique océanique by/par D. Gilbert & P. Cummins page 185 1) Introduce measures to rapidly reduce greenhouse gas emissions; Interview with Wendy Watson-Wright 2) Invest funds in the provision of science-based climate by Gordon McBean page 187 information; 3) Renew financial support for research into meteorology, On the future of operational forecasting oceanography, climate and ice science, especially in tools by Pierre Dubreuil page 189 Canada’s North, through independent, peer-reviewed projects managed by agencies such as CFCAS and Weather Services for the 2010 Winter NSERC. -
Snowpack and Firn Densification in the Energy Exascale Earth System Model
https://doi.org/10.5194/gmd-2020-247 Preprint. Discussion started: 13 August 2020 c Author(s) 2020. CC BY 4.0 License. Snowpack and firn densification in the Energy Exascale Earth System Model (E3SM) (version 1.2) Adam M. Schneider1, Charles S. Zender1, and Stephen F. Price2 1University of California, Irvine, Department of Earth System Science, Croul Hall, Irvine, CA 92697-3100 2Fluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, U.S.A. Correspondence: Adam Schneider ([email protected]) Abstract. Earth’s largest island, Greenland, and the Antarctic continent are both covered by massive ice sheets. A large fraction of their surfaces consist of multi-year snow, known as firn, which has undergone a process of densification since falling from the atmosphere. Until now this firn densification has not been fully accounted for in the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM). Here, we expand the E3SM Land Model (ELM) snowpack from 1 m to up to 60 m to 5 enable more accurate simulation of snowpack evolution. We test four densification models in a series of century-scale land surface simulations forced by atmospheric re-analyses, and evaluate these parameterizations against empirical density-versus- depth data. To tailor candidate densification models for use across the ice sheets’ dry-snow zones, we optimize parameters using a regularized least squares algorithm applied to two distinct stages of densification. We find that a dynamic implementation of a semi-empirical compaction model, originally calibrated to measurements from the Antarctic peninsula, gives results more 10 consistent with ice core measurements from the cold, dry snow zones of Greenland and Antarctica, compared to when using the original ELM snow compaction physics. -
ICA Vol. 1 (1956 Edition)
·wMo o '-" I q Sb 10 c. v. i. J c.. A INTERNATIONAL CLOUD ATLAS Volume I WORLD METEOROLOGICAL ORGANIZATION 1956 c....._/ O,-/ - 1~ L ) I TABLE OF CONTENTS Pages Preface to the 1939 edition . IX Preface to the present edition . xv PART I - CLOUDS CHAPTER I Introduction 1. Definition of a cloud . 3 2. Appearance of clouds . 3 (1) Luminance . 3 (2) Colour .... 4 3. Classification of clouds 5 (1) Genera . 5 (2) Species . 5 (3) Varieties . 5 ( 4) Supplementary features and accessory clouds 6 (5) Mother-clouds . 6 4. Table of classification of clouds . 7 5. Table of abbreviations and symbols of clouds . 8 CHAPTER II Definitions I. Some useful concepts . 9 (1) Height, altitude, vertical extent 9 (2) Etages .... .... 9 2. Observational conditions to which definitions of clouds apply. 10 3. Definitions of clouds 10 (1) Genera . 10 (2) Species . 11 (3) Varieties 14 (4) Supplementary features and accessory clouds 16 CHAPTER III Descriptions of clouds 1. Cirrus . .. 19 2. Cirrocumulus . 21 3. Cirrostratus 23 4. Altocumulus . 25 5. Altostratus . 28 6. Nimbostratus . 30 " IV TABLE OF CONTENTS Pages 7. Stratoculllulus 32 8. Stratus 35 9. Culllulus . 37 10. Culllulonimbus 40 CHAPTER IV Orographic influences 1. Occurrence, structure and shapes of orographic clouds . 43 2. Changes in the shape and structure of clouds due to orographic influences 44 CHAPTER V Clouds as seen from aircraft 1. Special problellls involved . 45 (1) Differences between the observation of clouds frolll aircraft and frolll the earth's surface . 45 (2) Field of vision . 45 (3) Appearance of clouds. 45 (4) Icing .