COST Action ES nd Snow Science Winter School February 2016, Preda, Switzerland STSM Report

Similar documents
Proceedings, International Snow Science Workshop, Banff, 2014

Tracking Changes in Buried Melt Freeze Crusts

Modeling microwave emission in Antarctica. influence of the snow grain size

Proceedings, International Snow Science Workshop, Breckenridge, Colorado, 2016

L. ARNAUD, G. PICARD, N. CHAMPOLLION, F. DOMINE, J.C. GALLET, E. LEFEBVRE, M. FILY, J.M. BARNOLA {

Darkening of soot-doped natural snow: Measurements and model

Penetrometer for Soil and Snowpack Characterization

An operational supporting tool for assessing wet-snow avalanche danger

Microstructural investigation of snow metamorphism with the SnowMicroPenetrometer

Science 1206 Chapter 1 - Inquiring about Weather

Arctic Snow Microstructure Experiment for the development of snow emission modelling

The DMRT-ML model: numerical simulations of the microwave emission of snowpacks based on the Dense Media Radiative Transfer theory

Instruments and Methods New shortwave infrared albedo measurements for snow specific surface area retrieval

GLACIOLOGY LAB SNOW Introduction Equipment

How to assess a snowpack with your group:

On modelling the formation and survival of surface hoar in complex terrain

Microwave scattering coefficient of snow: Microstructural requirements beyond density and grain size

Position calibration of cryogenic dark matter detectors

Exercise: guided tour

CONTINUOUS MEASUREMENTS OF LIQUID WATER CONTENT AND DENSITY IN SNOW USING TDR

Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550 nm

International Snow Science Workshop Grenoble Chamonix Mont-Blanc

Proceedings, International Snow Science Workshop, Breckenridge, Colorado, 2016 OBSERVER INDEPENDENT MEASURES OF SNOW INSTABILITY

- SNOW - DEPOSITION, WIND TRANSPORT, METAMORPHISM

3 Tools and Measurement

Snow micro-structure to micro-wave modelling

How does the surface type and moisture content affect the surfaceʼs temperature?

Chapter 1. Essentials of Geography Pearson Education, Inc.

Measuring snowpack changes in Arctic Russia - second season

Physics 240 Fall 2003: Final Exam. Please print your name: Please list your discussion section number: Please list your discussion instructor:

Proceedings, International Snow Science Workshop, Breckenridge, Colorado, 2016

Comparing different MODIS snow products with distributed simulation of the snowpack in the French Alps

URL: < /2013jf003017>

Guided Notes Weather. Part 2: Meteorology Air Masses Fronts Weather Maps Storms Storm Preparation

Temperature control for Varian Cary line of UV/Vis Spectrophotometers and the Eclipse Fluorometer

3 Severe Weather. Critical Thinking

A PORTABLE CAPACITANCE SNOW SOUNDING INSTRUMENT

Chapter Introduction. Weather. Patterns. Forecasts Chapter Wrap-Up

MS482 Materials Characterization ( 재료분석 ) Lecture Note 11: Scanning Probe Microscopy. Byungha Shin Dept. of MSE, KAIST

High resolution ground-based snow measurements during the NASA CLPX-II campaign, North Slope, Alaska

MTO s Road Weather Information System (RWIS)

GIS Techniques for Avalanche Path Mapping and Snow Science Observations. By Douglas D. Scott AVALANCHE MAPPING/IDEA INTEGRATION

The Main Point. Familiar Optics. Some Basics. Lecture #8: Astronomical Instruments. Astronomical Instruments:

What we are trying to accomplish during the winter season

UNIVERSITY OF CAMBRIDGE INTERNATIONAL EXAMINATIONS International General Certificate of Secondary Education

International Snow Science Workshop, Davos 2009, Proceedings

7. The weather instrument below can be used to determine relative humidity.

SPECIFICATIONS PARTICLE SENSOR KS-28B Higashimotomachi, Kokubunji, Tokyo , Japan

Cambridge International Examinations Cambridge International General Certificate of Secondary Education

Surface temperature what does this data tell us about micro-meteorological processes?

Remote sensing with FAAM to evaluate model performance

Clouds and Rain Unit (3 pts)

1. Electrostatic Lab [1]

Spitzer Space Telescope

SLOPE SCALE AVALANCHE FORECASTING IN THE ARCTIC (SVALBARD)

FACETED SNOW AND DEEP SLAB INSTABILITIES IN THE MARITIME CLIMATE OF THE CASCADES. Jon Andrews* Stevens Pass Ski Area

HELICOPTER-BASED MICROWAVE RADAR MEASUREMENTS IN ALPINE TERRAIN

A self-portrait of the Northern Lights outside Nybyen and photos from our tour of the Kjell Henriksen Observatory and the EISCAT Svalbard Radar.

Help from above. used in road weather information. system (RWIS) applications and, to a lesser extent, as components of recent

MEASURING THE MECHANICAL PROPERTIES OF SNOW RELEVANT FOR DRY-SNOW SLAB AVA- LANCHE RELEASE USING PARTICLE TRACKING VELOCIMETRY

Photon Instrumentation. First Mexican Particle Accelerator School Guanajuato Oct 6, 2011

Chemistry Instrumental Analysis Lecture 15. Chem 4631

Period 5: Thermal Energy, the Microscopic Picture

Lesson 4b Remote Sensing and geospatial analysis to integrate observations over larger scales

Simple and Low Cost Polarimeter System

Problem Solving. radians. 180 radians Stars & Elementary Astrophysics: Introduction Press F1 for Help 41. f s. picture. equation.

Road Weather: The Science Behind What You Know

Instruments and Methods Stability algorithm for snow micro-penetrometer measurements

Principles of Radiative Transfer Principles of Remote Sensing. Marianne König EUMETSAT

3. The map below shows an eastern portion of North America. Points A and B represent locations on the eastern shoreline.

Neutron Imaging at Spallation Neutron Sources

WORLD S CHOICE FOR GEO IMAGING. Advanced Baseline Imager (ABI)

ICSE Board Class IX Physics Paper 1

Forecasts include: Temperature. Barometric (air) Pressure. Wind direction/speed Humidity

NAME:.ADM NO: SCHOOL..CANDIDATE S SIGNATURE 232/1 PHYSICS PAPER 1 TIME 2 HOURS

Weather and climate. reflect. what do you think? look out!

Infrared Experiments of Thermal Energy and Heat Transfer

CHARACTERIZATION of NANOMATERIALS KHP

Calibrating the Thermal Camera

Proceedings, International Snow Science Workshop, Banff, 2014

Proceedings, International Snow Science Workshop, Breckenridge, Colorado, 2016

Laboratory 3&4: Confocal Microscopy Imaging of Single-Emitter Fluorescence and Hanbury Brown and Twiss setup for Photon Antibunching

Ice core stratigraphy using dual energy x-ray absorptiometry (DEXA)

How does your eye form an Refraction

Lecture 8: Snow Hydrology

CHAPTER 6 Air-Sea Interaction Pearson Education, Inc.

Studying snow cover in European Russia with the use of remote sensing methods

Laboratory 3: Confocal Microscopy Imaging of Single Emitter Fluorescence and Hanbury Brown, and Twiss Setup for Photon Antibunching

The Secret Behind the Nobeyama 45-m Radio Telescope s Excellent

IV. Atmospheric Science Section

How does your eye form an Refraction

25.1 Air Masses. Section 25.1 Objectives

Name: Period: Air Masses Notes 7 Minutes Page 2 Watch the air masses video. Make sure you follow along.

PREDICTING SNOW COVER STABILITY WITH THE SNOW COVER MODEL SNOWPACK

NIVEXC: an electronic snow-pole for real-time monitoring of avalanche starting zones

Sea Ice and Satellites

Linear Attenuation Coefficients and Gas Holdup Distributions in Bubble Column with Vertical Internal for Fischer-Tropsch (FT) Synthesis

ICSE Board Class IX Physics Paper 5

Recent evolution of the snow surface in East Antarctica

Development of Snow Avalanche Forecasting System in Japan

Transcription:

Süheyla Sena AKARCA BIYIKLI COST Action ES1404 2 nd Snow Science Winter School 14-20 February 2016, Preda, Switzerland STSM Report 1. Introduction I have attended 2nd Snow Science Winter School which was held in 14-20 February 2016, Preda and Davos, Switzerland. The host organization was SLF, WSL (Swiss Federal Institute for Forest, Snow and Landscape Research) Institute for Snow and Avalanche Research. There were 26 attendees coming from European countries, USA, Canada, Russia and Turkey who are studying in snow science with different backgrounds (physics, chemistry, engineering, etc.) The objective of the Snow Science Winter School was to teach advanced techniques to measure snow properties, as micro-tomography, measurement of specific surface area by reflection and spectroscopy, near-infrared photography and high-resolution penetrometry, and to introduce the modern concepts of snow science. The school can be divided into three sections which will be explained in detail in the next section: a) Lectures, given by 9 lecturers introducing different parts of latest concepts of snow science. b) Field Measurements, were held in Preda, which is located in the east of Switzerland with 1800m altitude, at three different locations (open site, forest site, above tree line). c) Laboratory visit was one day trip to Davos, SLF Main Building. Laboratory infrastructure and Instruments used in snow science were introduced. 2. Activities during Snow Science Winter School 2.1 Lectures: Lectures were very useful, each one introducing different aspects of snow science like snow microstructure, advanced field measurement methods, remote sensing of snow properties, snow albedo and affects on energy balance, snow-forest interactions and snowpack modeling. Also spending whole week at the same place with the lecturers was a great opportunity to ask questions about their studies and questions about snow science. 2.2 Measurements: First day, we were divided into groups of 3 or 4 for field measurements. Starting from digging a pit, several measurement techniques were introduced:

2.2.1 Basic Snow Profiling Measurements Depth: First the snow pit depth was measured as seen in the Fig. 1. Figure 1. Snow pit depth and temperature measurement Temperature: air temperature, surface temperature and snow temperature at every 5 cm were noted by a digital thermometer to get a temperature profile of the snowpack. Snow-water equivalent: A metal cylinder tube with a certain depth was weighed with a spring scale and calibrated as zero while it is empty, then it is inserted into snow and weighed with the scale calibrated according to SWE mm values. Density was measured with the tool named density cutter, seen in the figure. It was a 100cc density cutter and inserted in the snow, excess snow was cut by the cover lid and weighed by a digital scale. Density is calculated as =Mass/Volume Figure 2. Density cutter (left) inserted into the snow layer (right)

Figure 3. Excess snow is cutted with the lid (left) DC fulled with snow is weighed by digital scale Grain Size and Type: Grain size and type measurements are rather subjective measurements. From each layer of the pit some snow was taken onto the milimetric part of the crystal card seen in the figure. Then we looked at the grains by the magnifier and decide the size and shape by comparing the pictures at the below part of the plate. Figure 4. Magnifier (left) and crystal card (right). 2.2.2 Near-infrared photography (NIP) NIR photography is used to detect the layers of the snowpack and determine the snow grain size or Specific Surface Area (SSA). Digital cameras in which a special filter blocks all wavelengths outside the near-infrared (NIR) spectrum are used for NIR photography. Different intensities in the NIR image indicate different snow grain sizes (or different SSA). NIR images allow the individual layers of the snowpack to be clearly distinguished, while the photograph in visible light shows hardly any contrasts. First, camera is calibrated with a white styrofoam plate, then picture of the snow layer is taken.

Figure 5: Preparing to take an NIR photograph of a snow profile (left). Image of a snow profile captured by NIP (right). The picture clearly reveals the individual layers, even if they are very thin. 2.2.3 Laser Reflectometry is used to find Specific Surface Area (SSA) of snow (Gallet et al, 2009). Snow SSA is defined as the surface area per unit mass. Two devices IRIS (InfraRed Integrating Sphere) and IceCube were introduced depending on the same principle. The working principle of these devices relies on the relationship between the infrared hemispherical reflectance of snow and SSA. A snow sample is illuminated directly by the collimated beam of a laser diode at 1310 nm. Light reflected by the snow is collected via an integrating sphere by an InGaAs photodiode and converted to voltage. A calibration curve, obtained using certified standards, provides the signal-to-reflectance relationship. This reflectance is then converted into SSA using a radiative transfer model and calibration using the well-established methane adsorption method. Figure 6. Working principle of laser reflectometer

The main difference between the IRIS and IceCube systems is the sphere geometries. IRIS sphere has 10 cm inner diameter whereas, IceCube has a larger inner diameter (15 cm) and wider ports. Figure 7. Laser reflectometer devices. IceCube (right) IRIS (left) Figure 8. Extracted sample for IRIS measurement (left) Sample is placed inside IRIS under the sphere 2.2.4 Snow MicroPen (SMP) The SMP is a high-resolution snow penetrometer. It is capable of measuring the bonding force between snow grains. The SMP can be used in different application areas as snow profiling (avalanche forecasting, snow stratigraphy, remote sensing ground truth), ski track characterization (ski racing) or snow runway characterization (stability testing). The SMP is composed of a piezoelectric force sensor that is fixed on the head of a 1.5 m long rod which is driven into the snow pack by a motor unit and a controller unit.

The motor unit of the SMP is the part which drives up and down the rod. At the front side of the rod, a piezo electric force sensor is fixed. On the force sensor there is a conical and really thin tip which actually breaks the bonds between the snow grains. The black ski poles are used to hold the SMP on the same position above the snow surface during the measurement. Figure 9. Measuring tip at the end of the rod (left) Motor unit, black poles and the tip (middle) measurement by an SMP (right) In the next days we have used these measurement techniques in an open site, forest site to see the effect of trees on snow properties, and the above tree line to see the effect of elevation and slope. Detailed data analysis of each site will be presented in our group report submitted to the Snow School organization committee. 2.3 Laboratory Visit Laboratory was in the SLF main building in Davos. The facilities in the lab were introduced and data analysis methods for Micro-CT measurements were explained. Also we brought snow samples, taken from the sites in Preda, to the lab in Styrofoam boxes filled with dry ice. There were 5 temperature-controlled cold chambers that can be operated between -35 to 0 C. These cold chambers are used for making of nature-identical snow; the conduct of mechanical, optical and thermodynamic experiments; producing computer tomography scans, machining snow samples (by sawing, turning and drilling); and storing snow samples. In the cold lab we cut the snow samples to get ready for the micro-ct measurements. The instruments seen in the cold lab were: Snowmaker machine is used to make nature-identical snow in the cold laboratory with reproducible conditions. Working principle is similar to the nature, cold air is saturated with water vapour, then channelled into a colder chamber, where the further reduction in temperature inevitably prompts the release of moisture from the air. The excess moist air freezes on suspended nylon threads serving as condensation cultivators.

Figure 10. : SnowMaker (left) and nature-identical dendritic snow on the cultivating threads (right). Computertomograph (CT) There were two X-ray computed tomography scanners used to perform three-dimensional analyses of the snow structure in a non-destructive imaging procedure with a resolution of up to 10 µm. So they are called as micro-ct. Besides examining stationary snow structures, they can also be used to investigate processes taking place within the snow structure over time (snow metamorphism). The CT scanners were located in the cold laboratory at -20 C as standard. Figure 11. Two Computer tomographs in the cold lab. μct80 (left), μct40 (right) Our samples were given to a researcher for micro-ct measurements. Images were taken after the snow school to be used in the report. The SSA and density calculated from CT images will be compared to ground data. 3. Conclusion It was a great opportunity to meet lecturers and students from all over the world to have a broader perspective on snow science. Also it was a good experience working in groups with people from different backgrounds and cultures. Hands-on field work was very instructive, we did not only see the measurements but also experienced all steps, digging the pit, taking the samples, doing the measurements.

References: Gallet, J.-C., F. Domine, C. S. Zender, and G. Picard (2009), Measurement of the specific surface area of snow using infrared reflectance in an integrating sphere at 1310 and 1550nm, The Cryosphere, 3, 167 182. Montpetit, B., A. Royer, A. Langlois, P. Cliche, A. Roy, N. Champollion, G. Picard, F. Domine, R. Obbard, (2012) Instruments and Methods: New shortwave infrared albedo measurements for snow specific surface area retrieval, Journal of Glaciology, Vol. 58, No. 211. Proksch, M., H. Löwe, and M. Schneebeli (2015), Density, specific surface area, and correlation length of snow measured by high-resolution penetrometry, J. Geophys. Res. Earth Surf., 120, 346 362, http://www.slf.ch/ueber/organisation/schnee_permafrost/schneephysik/infrastruktur/index_en