Snow to Water Ratios 88

Total Page：16

File Type：pdf, Size：1020Kb

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. o Problem 2 - If 30 inches of snow fell in Calgary, Alberta at 18 F, and 25 inches of o snow fell in Denver, Colorado where the temperature was 25 F, at which location would the most water have fallen? o o Answer - In Alberta, the Snow Ratio for 18 F is 20:1 and in Denver at 25 F it is 15:1. The amount of water that fell in Alberta is then 30 inches of snow x (1 inch water/20 inches snow) = 1.3 inches of water. In Denver it is 25 inches of snow x (1 inch water/15 inches snow) = 1.7 inches of water. So more water fell in Denver, even though there was less snow on the ground! Space Math http://spacemath.gsfc.nasa.gov .

Copy Link

Recommended publications

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.
[Show full text]
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.
[Show full text]
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).
[Show full text]
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.
[Show full text]
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.
[Show full text]
Storms Are Thunderstorms That Produce Tornadoes, Large Hail Or Are Accompanied by High Winds
From February 17 to 19, a severe storm blasted the Lebanese coast with 100- kilometer (60-mile) winds and dropped as much as 2 meters (7 feet) of snow on parts of the country, news sources said. Temperatures dropped to near freezing along the coast, while snowplows struggled to clear the main roadway between Beirut and Damascus. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite captured this natural-color image on February 20, 2012. Snow covers much of Lebanon, and extends across the border with Syria. Another expanse of snow occurs just north of the Syria-Jordan border. Snow in Lebanon is not uncommon, and the country is home to ski resorts. Still, this fierce storm may have been part of a larger pattern of cold weather in Europe and North Africa. References The Daily Star. (2012, February 18). Lebanon hit by extreme weather conditions. Accessed February 21, 2012. Naharnet. (2012, February 19). Storm subsides after coating Lebanon in snow. Accessed February 21, 2012. NASA image courtesy LANCE/EOSDIS MODIS Rapid Response Team at NASA GSFC. Caption by Michon Scott. Instrument: Terra - MODIS Flooding is the most common of all natural hazards. Each year, more deaths are caused by flooding than any other thunderstorm related hazard. We think this is because people tend to underestimate the force and power of water. Six inches of fast-moving water can knock you off your feet. Water 24 inches deep can carry away most automobiles. Nearly half of all flash flood deaths occur in automobiles as they are swept downstream.
[Show full text]
Hazard Mitigation Plan – Dutchess County, New York 5.4.1-1 December 2015 Section 5.4.1: Risk Assessment – Coastal Hazards
Section 5.4.1: Risk Assessment – Coastal Hazards 5.4.1 Coastal Hazards 7KH IROORZLQJ VHFWLRQ SURYLGHV WKH KD]DUG SURILOH KD]DUG GHVFULSWLRQ ORFDWLRQ H[WHQW SUHYLRXV RFFXUUHQFHV DQG ORVVHV SUREDELOLW\ RI IXWXUH RFFXUUHQFHV DQG LPSDFW RI FOLPDWH FKDQJH DQG YXOQHUDELOLW\ DVVHVVPHQW IRU WKH FRDVWDO KD]DUGV LQ 'XWFKHVV &RXQW\ 3URILOH +D]DUG 'HVFULSWLRQ $ WURSLFDO F\FORQH LV D URWDWLQJ RUJDQL]HG V\VWHP RI FORXGV DQG WKXQGHUVWRUPV WKDW RULJLQDWHV RYHU WURSLFDO RU VXEWURSLFDO ZDWHUV DQG KDV D FORVHG ORZOHYHO FLUFXODWLRQ 7URSLFDO GHSUHVVLRQV WURSLFDO VWRUPV DQG KXUULFDQHV DUH DOO FRQVLGHUHG WURSLFDO F\FORQHV 7KHVH VWRUPV URWDWH FRXQWHUFORFNZLVH DURXQG WKH FHQWHU LQ WKH QRUWKHUQ KHPLVSKHUH DQG DUH DFFRPSDQLHG E\ KHDY\ UDLQ DQG VWURQJ ZLQGV 1:6 $OPRVW DOO WURSLFDO VWRUPV DQG KXUULFDQHV LQ WKH $WODQWLF EDVLQ ZKLFK LQFOXGHV WKH *XOI RI 0H[LFR DQG &DULEEHDQ 6HD IRUP EHWZHHQ -XQH DQG 1RYHPEHU KXUULFDQH VHDVRQ $XJXVW DQG 6HSWHPEHU DUH SHDN PRQWKV IRU KXUULFDQH GHYHORSPHQW 12$$ D 2YHU D WZR\HDU SHULRG WKH 86 FRDVWOLQH LV VWUXFN E\ DQ DYHUDJH RI WKUHH KXUULFDQHV RQH RI ZKLFK LV FODVVLILHG DV D PDMRU KXUULFDQH +XUULFDQHV WURSLFDO VWRUPV DQG WURSLFDO GHSUHVVLRQV SRVH D WKUHDW WR OLIH DQG SURSHUW\ 7KHVH VWRUPV EULQJ KHDY\ UDLQ VWRUP VXUJH DQG IORRGLQJ 12$$ E )RU WKH SXUSRVH RI WKLV +03 DQG DV GHHPHG DSSURSULDWHG E\ WKH 'XWFKHVV &RXQW\ 6WHHULQJ DQG 3ODQQLQJ &RPPLWWHHV FRDVWDO KD]DUGV LQ WKH &RXQW\ LQFOXGH KXUULFDQHVWURSLFDO VWRUPV VWRUP VXUJH FRDVWDO HURVLRQ DQG 1RU (DVWHUV ZKLFK DUH GHILQHG EHORZ Hurricanes/Tropical Storms $ KXUULFDQH LV D WURSLFDO
[Show full text]
Current and Future Snow Avalanche Threats and Mitigation Measures in Canada
CURRENT AND FUTURE SNOW AVALANCHE THREATS AND MITIGATION MEASURES IN CANADA Prepared for: Public Safety Canada Prepared by: Cam Campbell, M.Sc.1 Laura Bakermans, M.Sc., P.Eng.2 Bruce Jamieson, Ph.D., P.Eng.3 Chris Stethem4 Date: 2 September 2007 1 Canadian Avalanche Centre, Box 2759, Revelstoke, B.C., Canada, V0E 2S0. Phone: (250) 837-2748. Fax: (250) 837-4624. E-mail: [email protected] 2 Department of Civil Engineering, University of Calgary, 2500 University Drive NW. Calgary, AB, Canada, T2N 1N4, Canada. E-mail: [email protected] 3 Department of Civil Engineering, University of Calgary, 2500 University Drive NW. Calgary, AB, Canada, T2N 1N4, Canada. Phone: (403) 220-7479. Fax: (403) 282-7026. E-mail: [email protected] 4 Chris Stethem and Associates Ltd., 120 McNeill, Canmore, AB, Canada, T1W 2R8. Phone: (403) 678-2477. Fax: (403) 678-346. E-mail: [email protected] Table of Contents EXECUTIVE SUMMARY This report presents the results of the Public Safety Canada funded project to inventory current and predict future trends in avalanche threats and mitigation programs in Canada. The project also updated the Natural Resources Canada website and map of fatal avalanche incidents. Avalanches have been responsible for at least 702 fatalities in Canada since the earliest recorded incident in 1782. Sixty-one percent of these fatalities occurred in British Columbia, with 13% in Alberta, 11% in Quebec and 10% in Newfoundland and Labrador. The remainder occurred in Ontario, Nova Scotia and the Yukon, Northwest and Nunavut Territories. Fifty-three percent of the fatalities were people engaged in recreational activities, while 18% were people in or near buildings, 16% were travelling or working on transportation corridors and 8% were working in resource industries.
[Show full text]
Snowpack As Indicators of Atmospheric Pollution: the Valday Upland
atmosphere Article Snowpack as Indicators of Atmospheric Pollution: The Valday Upland Marina Dinu *, Tatyana Moiseenko * and Dmitry Baranov * Vernadsky Institute of Geochemistry and Analytical Chemistry, 119334 Moscow, Russia * Correspondence: [email protected] (M.D.); [email protected] (T.M.); [email protected] (D.B.) Received: 23 March 2020; Accepted: 1 May 2020; Published: 3 May 2020 Abstract: Snowpack is a unique indicator in assessing both local and transboundary contaminants. We considered the features of the snow chemical composition of the Valday Upland, Russia, as a location without a direct influence of smelters (conditional background) in 2016–2019. We identified the influence of a number of geochemical (landscape), biological (trees of the forest zone, vegetation), and anthropogenic factors (technogenic elements—lead, nickel) on the formation of snow composition. We found increases in the content of metals of technogenic origin in city snowfall in the snowpack: cadmium, lead, and nickel in comparison with snowfall in the forest. Methods of sequential and parallel membrane filtration (in situ) were used along with ion-exchange separation to determine metal speciation (labile, unlabile, inorganic speciation with low molecular weight, connection with organic ligands) and explain their migration ability. We found that forest snow samples contain metal compounds (Cu, Pb, and Ni) with different molecular weights due to the different contributions of organic substances. According to the results of filtration, the predominant speciation of metals in the urban snow samples is suspension emission (especially more 8 mkm). The buffer abilities of snowfall in the forest (in various landscapes) and in the city of Valday were assessed.
[Show full text]
Snow, Weather, and Avalanches
SNOW, WEATHER, AND AVALANCHES: Observation Guidelines for Avalanche Programs in the United States SNOW, WEATHER, AND AVALANCHES: Observation Guidelines for Avalanche Programs in the United States 3rd Edition 3rd Edition Revised by the American Avalanche Association Observation Standards Committee: Ethan Greene, Colorado Avalanche Information Center Karl Birkeland, USDA Forest Service National Avalanche Center Kelly Elder, USDA Forest Service Rocky Mountain Research Station Ian McCammon, Snowpit Technologies Mark Staples, USDA Forest Service Utah Avalanche Center Don Sharaf, Valdez Heli-Ski Guides/American Avalanche Institute Editor — Douglas Krause — Animas Avalanche Consulting Graphic Design — McKenzie Long — Cardinal Innovative © American Avalanche Association, 2016 ISBN-13: 978-0-9760118-1-1 American Avalanche Association P.O. Box 248 Victor, ID. 83455 [email protected] www. americanavalancheassociation.org Citation: American Avalanche Association, 2016. Snow, Weather and Avalanches: Observation Guidelines for Avalanche Programs in the United States (3rd ed). Victor, ID. FRONT COVER PHOTO: courtesy Flathead Avalanche Center BACK COVER PHOTO: Chris Marshall 2 PREFACE It has now been 12 years since the American Avalanche Association, in cooperation with the USDA Forest Service National Ava- lanche Center, published the inaugural edition of Snow, Weather and Avalanches: Observational Guidelines for Avalanche Programs in the United States. As those of us involved in that first edition grow greyer and more wrinkled, a whole new generation of avalanche professionals is growing up not ever realizing that there was a time when no such guidelines existed. Of course, back then the group was smaller and the reference of the day was the 1978 edition of Perla and Martinelli’s Avalanche Handbook.
[Show full text]
The Spatial and Temporal Variability of Rain-On-Snow
In Proceedings of the International Snow Science Workshop, 1-6 October 2000, Big Sky, Montana. American Avalanche Association. 178-183. THE SPATIAL AND TEMPORAL VARIABILITY OF RAIN-ON-SNOW Sue A. Ferguson* USDA-FS, Pacific Northwest Research Station ABSTRACT: Snow melt during rainfall causes large-scale flooding and avalanching. These rain-on- snow events are most well-documented in the coastal mountain ranges of western North America. To determine what role they play in interior mountains, we analyzed flood frequencies in the Columbia River basin and modeled rain-on-snow potential from daily temperature and precipitation data. Applying the model with geographically distributed weather data allowed maps of rain-on-snow potential at 2km spatial resolution to be generated for characteristic climate years of 1982 (cold and wet), 1988 (warm and dry), and 1989 (average). It was found that rain-on-snow events are more likely during cool, wet years (such as 1982). A greater number of events and more widespread distribution of events occur during this type of climate. The cool temperatures allow low-elevation snow to accumulate and frequent storms bring the possibility of mid-winter rain. Warm, dry years (1988) are less likely to experience rain-on-snow events. There is little low-elevation snow at these times and only occasional precipitation. During all years, areas most susceptible to rain-on-snow are those where topography allows incursion of relatively warm, moist marine air that flows from the Pacific Ocean into the Columbia Plateau and up the Snake River Valley. These areas include the Cascade mountains; northern Idaho, northeastern Washington, and northwestern Montana where valleys open into the Columbia plateau; the Blue Mountains of northeastern Oregon; and western Wyoming and central Idaho adjacent to the Snake River.
[Show full text]
Weather Symbol Full Chart
CLOUD Code Code Code SKY mph knots ABBREVIATION cH High Cloud Description cM Middle Cloud Description cL Low Cloud Description Nh N COVERAGE ff Cu of fair weather with little vertical development Filaments of Ci, or “mares tails,” scattered Thin As (most of cloud layer semi-transparent) No clouds Calm Calm Symbolic Station Model and not increasing and seemingly flattened 0 St or Fs = Stratus or 1 1 1 Fractostratus Cu of considerable development, generally Dense Ci and patches or twisted sheaves, Thick As, greater part sufficiently dense to Less than one-tenth 1 - 2 1 - 2 usually not increasing, sometimes like remains towering with or without other Cu or Sc bases or one-tenth Ci = Cirrus hide sun (or moon), or Ns 1 2 of Cb; or towers or tufts 2 2 all at the same level Two-tenths or Cb with tops lacking clear cut outlines but 3 - 8 3 - 7 Dense Ci, often anvil-shaped, derived from Thin Ac, mostly semi-transparent; cloud elements three tenths ff Cs = Cirrus distinctly not cirriform or anvil-shaped, or associated with Cb not changing much and at a single level 2 H 3 3 3 with or without Cu, Sc or St C Four-tenths 9 - 14 8 - 12 Cc = Cirrocumulus Ci, often hook-shaped,gradually spreading Thin Ac in patches; cloud elements continually Sc formed by the spreading out of Cu; Cu 3 dd 4 over the sky and usually thickening as a whole 4 changing and/or occurring at more than one level 4 often present also T T CM Five-tenths Ac = Altocumulus Ci and Cs, often in converging bands, or Cs alone; 15 - 20 13 - 17 PPP Thin Ac in bands or in a layer gradually
[Show full text]