Iowa (SMAPVEX16-IA) Experiment Plan

Total Page:16

File Type:pdf, Size:1020Kb

Iowa (SMAPVEX16-IA) Experiment Plan Soil Moisture Active Passive Validation Experiment 2016- Iowa (SMAPVEX16-IA) Experiment Plan Iowa Landscape July 2014 Ver. 5/20/16 Table of Contents 1. Introduction .........................................................................................................................8 1.1. Role of Field Campaigns in SMAP Cal/Val...................................................................8 1.2. Science Objectives for a Post-Launch SMAP Aircraft-Based Field Campaign ...............9 1.2.1. Investigate and resolve anomalous observations and products ...............................9 1.2.2. Improving up-scaling functions for CVS .............................................................. 10 1.2.3. Contribution to a broader scientific/application objective.................................... 10 1.2.4. Validate the L2SMAP algorithm process: pending new directions ....................... 13 2. SMAPVEX16 Aircraft Experiment Concept ...................................................................... 13 3. South Fork (SF), Iowa Study Area ..................................................................................... 13 3.1. General Description .................................................................................................... 13 3.2. Land Cover/Vegetation ............................................................................................... 14 3.3. Soils ............................................................................................................................ 15 3.4. Climate ....................................................................................................................... 16 3.5. Soil Moisture Network ................................................................................................ 16 4. Flux Towers in Central Iowa .............................................................................................. 20 5. SMAP Validation Grids ..................................................................................................... 21 6. Aircraft Experiment Design ............................................................................................... 22 6.1. PALS Instrument and Aircraft Description .................................................................. 22 6.2. Flight Lines and Flight Plans ....................................................................................... 22 7. Ground-based Sampling ..................................................................................................... 25 7.1. Soil Moisture .............................................................................................................. 25 7.1.1. Temporary Network ............................................................................................. 25 7.1.2. Soil Moisture Rover ............................................................................................. 26 7.1.3. High Density Gravimetric Sampling .................................................................... 27 7.3. Vegetation................................................................................................................... 28 7.3.1. Vegetation Communities and Sites ....................................................................... 29 7.3.2. Overall Protocol For Each Site ........................................................................... 29 8. Precipitation Characterization ............................................................................................ 30 9. Ground-based Microwave Observations ............................................................................. 33 9.1. Field Setup .................................................................................................................. 33 9.2. Sensors ....................................................................................................................... 34 9.2.1. University of Florida L-band Microwave Radiometer (UFLMR) .......................... 34 9.2.2. University of Michigan L-band Microwave Radiometer (UMLMR) ...................... 36 9.2.3. University of Florida Radar System ..................................................................... 39 9.2.4. Thermal Infrared Sensor ...................................................................................... 41 9.2.5. Soil Temperature Probes ..................................................................................... 41 9.2.6. Soil Moisture Probes ........................................................................................... 42 9.2.7. Precipitation........................................................................................................ 43 9.2.8. Air Temperature and Relative Humidity............................................................... 43 9.2.9. Net Radiometer .................................................................................................... 43 9.3. Vegetation Sampling ................................................................................................... 44 9.3.1. Vegetation Sampling at the Corn Site .................................................................. 44 9.3.2. Vegetation Sampling at the Soybean Site ............................................................. 44 10. Satellites and Overpass Schedules ...................................................................................... 46 10.1. SMAP and Other Passive Microwave Satellites ........................................................... 46 [2] 10.2. Radar Satellites ........................................................................................................... 47 10.2.1. RADARSAT2 ....................................................................................................... 47 10.2.2. Sentinel 1............................................................................................................. 50 11. CFIS .................................................................................................................................. 54 12. Security.............................................................................................................................. 56 13. Safety................................................................................................................................. 56 13.1. General Field Safety.................................................................................................... 56 13.2. Ticks ........................................................................................................................... 58 13.3. Drying Ovens .............................................................................................................. 58 13.4. Driving ....................................................................................................................... 58 13.5. Lightning .................................................................................................................... 58 13.6. Medical ....................................................................................................................... 58 14. Logistics ............................................................................................................................ 60 14.1. Hotels ......................................................................................................................... 60 14.2. Directions from the Des Moines Airport to Ames ........................................................ 60 14.3. Local Contacts ............................................................................................................ 62 14.4. Shipping Address ........................................................................................................ 63 15. Protocols ............................................................................................................................ 64 15.1. Watershed Site Surface Soil Moisture and Temperature .............................................. 64 15.2. Regional Site Surface Soil Moisture and Temperature ................................................. 67 15.3. Theta Probe Soil Moisture Sampling and Processing ................................................... 69 15.4. Gravimetric Soil Moisture Sampling with the Scoop Tool ........................................... 75 15.5. Gravimetric Soil Moisture Sample Processing ............................................................. 77 15.5.1. Wet Weight Procedure ......................................................................................... 77 15.5.2. Dry Weight Procedure ......................................................................................... 77 15.5.3. Data Processing .................................................................................................. 77 15.6. Watershed Site Soil Bulk Density and Surface Roughness .......................................... 78 15.6.1. Securing the Apparatus to the Ground ................................................................. 78 15.6.2. Leveling the Apparatus Horizontally to the Ground ............................................. 79 15.6.3. Determining the Volume from the Ground to the Hook Gauge ............................. 79 15.6.4. Finding the Volume of the Hole ........................................................................... 80 15.6.5. Calculating the Bulk Density of the Sample ......................................................... 80 15.7. Soil Temperature
Recommended publications
  • High Concentrations of Biological Aerosol Particles and Ice Nuclei Open Access During and After Rain Biogeosciences Biogeosciences Discussions J
    EGU Journal Logos (RGB) Open Access Open Access Open Access Advances in Annales Nonlinear Processes Geosciences Geophysicae in Geophysics Open Access Open Access Natural Hazards Natural Hazards and Earth System and Earth System Sciences Sciences Discussions Open Access Open Access Atmos. Chem. Phys., 13, 6151–6164, 2013 Atmospheric Atmospheric www.atmos-chem-phys.net/13/6151/2013/ doi:10.5194/acp-13-6151-2013 Chemistry Chemistry © Author(s) 2013. CC Attribution 3.0 License. and Physics and Physics Discussions Open Access Open Access Atmospheric Atmospheric Measurement Measurement Techniques Techniques Discussions Open Access High concentrations of biological aerosol particles and ice nuclei Open Access during and after rain Biogeosciences Biogeosciences Discussions J. A. Huffman1,2, A. J. Prenni3, P. J. DeMott3, C. Pohlker¨ 2, R. H. Mason4, N. H. Robinson5, J. Frohlich-Nowoisky¨ 2, Y. Tobo3, V. R. Despres´ 6, E. Garcia3, D. J. Gochis7, E. Harris2, I. Muller-Germann¨ 2, C. Ruzene2, B. Schmer2, 2,8 9 2 9 5 3 4 Open Access B. Sinha , D. A. Day , M. O. Andreae , J. L. Jimenez , M. Gallagher , S. M. Kreidenweis , A. K. Bertram , and Open Access U. Poschl¨ 2 Climate 1 Climate Department of Chemistry and Biochemistry, University of Denver, 2190 E. Illif Ave., Denver, CO, 80208, USA of the Past 2Max Planck Institute for Chemistry, P.O. Box 3060, 55020, Mainz, Germany of the Past 3Department of Atmospheric Science, Colorado State University, 1371 Campus Delivery, Fort Collins, CO, 80523, USA Discussions 4Department of Chemistry, University of British Columbia, Room D223, 2036 Main Mall, Vancouver, BC, V6T1Z1, Canada Open Access 5Centre for Atmospheric Sciences, University of Manchester, Simon Building, Oxford Road, Manchester, M139PL, UK Open Access 6Institute for General Botany, Johannes Gutenberg University, Mullerweg¨ 6, 55099, Mainz,Earth Germany System Earth System 7National Center for Atmospheric Research, P.O.
    [Show full text]
  • Physical Process Cruise 2018 020720
    Physical Process Cruise 2018 Cruise Report The Nansen Legacy Report Series 2/2020 Physical Process Cruise 2018 Cruise 2018709 R.V. Kronprins Haakon Longyearbyen-Longyearbyen September 14 -September 24, 2018 Authors: Ilker Fer – cruise leader Frank Nilsen- cruise co-leader Anthony Bosse Eva Falck Trygve Fossum Lars R Hole Zoe Koenig Eivind Kolås Aleksander Dürr Libæk Ben Lincoln Martin Ludvigsen Marika Marnela Malte Müller Petter Norgren Inger Lise Næss Jean Rabault Andrew Siedl Ragnheid Skogseth Inga Breisnes Utkilen To be cited as: Ilker Fer, Frank Nilsen, Anthony Bosse, Eva Falck, Trygve Fossum, Lars R Hole, Zoe Koenig, Eivind Kolås, Aleksander Dürr Libæk, Ben Lincoln, Martin Ludvigsen, Marika Marnela, Malte Müller, Petter Norgren, Inger Lise Næss, Jean Rabault, Andrew Siedl, Ragnheid Skogseth and Inga Breisnes Utkilen (2020). Physical Process Cruise 2018: Cruise Report. The Nansen Legacy Report Series, 2/2020. DOI: https://doi.org/10.7557/nlrs.5503 © The authors. This report is licensed under the Creative Commons Attribution 4.0 International license ISSN 2703-7525 Publisher: Septentrio Academic Publishing, Tromsø, Norway 1 Contents 1. Background ......................................................................................................................................... 4 2. Survey area ......................................................................................................................................... 5 3. Activity reports .................................................................................................................................
    [Show full text]
  • Comparison of the Compact Dopplar Radar Rain Gauge and Optical
    Short Paper J. Agric. Meteorol. 67 (3): 199–204, 2011 Comparison of the compact dopplar radar rain gauge and optical disdrometer Ko NAKAYA†, and Yasushi TOYODA (Central Research Institute of Electric Power Industry, 1646 Abiko, Abiko, Chiba, 270–1194, Japan) Abstract The operations of a compact Doppler radar rain gauge (R2S; Rufft, FRG) and optical disdrometer (LPM; THIES, FRG) are based on raindrop size distribution (DSD) measurements. We checked the instrumental error of these sensors and compared each sensor with a reference tipping-bucket rain gauge. This is because both rain gauges can detect fine particles and so they can function as rain sensors. The R2S has a measuring bias of rainfall intensity when the drop size distribution differs from the assumed statistical DSD model. The instrumental error on the LPM is small; in fact, the LPM shows good agreement with the reference rain gauge. Where the atmospheric density differs remarkably from the standard elevation, as is the case in highland areas, the R2S requires calibration using a reference rain gauge. The resultant calibration coefficient of the R2S to convert the reading into a reference tip- ping-bucket rain-gauge equivalent was 0.51 in a forest at an elevation of 1380 m. Further gathering of calibration coefficients obtained at different elevations will improve the R2S’s applicability. Key words: Doppler radar rain gauge, Drop size distribution, Optical disdrometer, Tipping-bucket rain gauge. Although the accuracy and suggested errors of rainfall 1. Introduction observations using typical Doppler radar have been Rainfall properties, such as the intensity, amount, reviewed in many studies (Maki et al., 1998, for duration, and type, constitute important meteorological example), reviews for the R2S compared to a reference information that is useful for agriculture and forestation rain gauge are few.
    [Show full text]
  • Measurement of Precipitation
    CHAPTER CONTENTS Page CHAPTER 6. MEASUREMENT OF PRECIPITATION ..................................... 186 6.1 General ................................................................... 186 6.1.1 Definitions ......................................................... 186 6.1.2 Units and scales ..................................................... 186 6.1.3 Meteorological and hydrological requirements .......................... 187 6.1.4 Measurement methods .............................................. 187 6.1.4.1 Instruments ................................................ 187 6.1.4.2 Reference gauges and intercomparisons ........................ 188 6.1.4.3 Documentation. 188 6.2 Siting and exposure ........................................................ 189 6.3 Non-recording precipitation gauges .......................................... 190 6.3.1 Ordinary gauges .................................................... 190 6.3.1.1 Instruments ................................................ 190 6.3.1.2 Operation. 192 6.3.1.3 Calibration and maintenance ................................. 192 6.3.2 Storage gauges ..................................................... 192 6.4 Precipitation gauge errors and corrections ..................................... 193 6.5 Recording precipitation gauges .............................................. 196 6.5.1 Weighing-recording gauge ........................................... 196 6.5.1.1 Instruments ................................................ 196 6.5.1.2 Errors and corrections. 197 6.5.1.3 Calibration
    [Show full text]
  • Meteorological Monitoring Guidance for Regulatory Modeling Applications
    United States Office of Air Quality EPA-454/R-99-005 Environmental Protection Planning and Standards Agency Research Triangle Park, NC 27711 February 2000 Air EPA Meteorological Monitoring Guidance for Regulatory Modeling Applications Air Q of ua ice li ff ty O Clean Air Pla s nn ard in nd g and Sta EPA-454/R-99-005 Meteorological Monitoring Guidance for Regulatory Modeling Applications U.S. ENVIRONMENTAL PROTECTION AGENCY Office of Air and Radiation Office of Air Quality Planning and Standards Research Triangle Park, NC 27711 February 2000 DISCLAIMER This report has been reviewed by the U.S. Environmental Protection Agency (EPA) and has been approved for publication as an EPA document. Any mention of trade names or commercial products does not constitute endorsement or recommendation for use. ii PREFACE This document updates the June 1987 EPA document, "On-Site Meteorological Program Guidance for Regulatory Modeling Applications", EPA-450/4-87-013. The most significant change is the replacement of Section 9 with more comprehensive guidance on remote sensing and conventional radiosonde technologies for use in upper-air meteorological monitoring; previously this section provided guidance on the use of sodar technology. The other significant change is the addition to Section 8 (Quality Assurance) of material covering data validation for upper-air meteorological measurements. These changes incorporate guidance developed during the workshop on upper-air meteorological monitoring in July 1998. Editorial changes include the deletion of the “on-site” qualifier from the title and its selective replacement in the text with “site specific”; this provides consistency with recent changes in Appendix W to 40 CFR Part 51.
    [Show full text]
  • A Lysimetric Snow Pillow Station at Kùhtai/Tyrol R. KIRNBAUER & G. BLÔSCHL Institut Fur Hydraulik, Gewâsserkunde U. Wasse
    Hydrology in Mountainous Regions. J - Hydrological Measurements; the Water Cycle (Proceedings of two Lausanne Symposia, August 1990). IAHS Publ. no. 193, 1990. A lysimetric snow pillow station at Kùhtai/Tyrol R. KIRNBAUER & G. BLÔSCHL Institut fur Hydraulik, Gewâsserkunde u. Wasserwirtschaft, Technische Universitât Wien, Karlsplatz 13, 1040 Vienna, Austria ABSTRACT For properly forecasting snowmeIt-runoff the understanding of processes associated with a melting snow cover may be of primary importance. For this purpose a snow monitoring station was installed at Kuhtai/Tyrol at an elevation of 1930 m a.s.l. In order to study individual physical processes typical snow cover situations are examined. These situations include cold and wet snow under varying weather conditions. Based on a few examples the diversity of phenomena occuring at the snow surface and within the snow cover is demonstrated. INTRODUCTION Within a short-term flood-forecasting system a snowmelt model should be capable of representing extreme conditions. As Leavesley (1989) points out, a more physically based understanding of the processes involved will improve forecast capabilities. Subjective watching of phenomena together with measuring adequate data of sufficient accuracy and time resolution may form the foundations of process understanding. Most field studies performed so far concentrated on investigating the energy input to snow, particularly under melting conditions (see e.g. Kuusisto, 1986). Differences in the relative importance of processes during contrasting weather conditions have been reported by numerous authors (e.g. Lang, 1986). Considering these differences some of the authors (e.g. Anderson, 1973) distinguished between advection and radiation melt situations in their models. In this study meteorological data and snowpack observations from an alpine experimental plot are presented.
    [Show full text]
  • Data Requirements for Ceiling and Visibility Products Development 6
    DOT/FAA/RD-94/5 Project Report ATC-212 Data Requirements for Ceiling and Visibility Products Development J. L. Keller 13 April 1994 Lincoln Laboratory MASSACHUSETTS INSTITUTE OF TECHNOLOGY LEXINGTON, MASSACHUSETTS Prepared for the Federal Aviation Administration, Washington, D.C. 20591 This document is available to the public through the National Technical Information Service, Springfield, VA 22161 This document is disseminated under the sponsorship of the Department of Transportation in the interest of information exchange. The United States Government assumes no liability for its contents or use thereof. TECHNICAL REPORT STANDARD TITLE PAGE 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. ATC-212 DOTfFAAJRD-94/5 4. TItle and Subtitle 5. Report Date 13 April 1994 Data Requirements for Ceiling and Visibility Products Development 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. John L. Keller ATC-212 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) Lincoln Lahoratory, MIT P.O. Box 73 11. Contract or Grant No. Lexington, MA 02173-9108 DTFAO1-93-Z-02012 12. Sponsoring Agency Name and Address 13. Type of Report and Period Covered Department of Transportation Project Report Federal Aviation Administration Washington, DC 20591 14. Sponsoring Agency Code 15. Supplementary Notes This report is hased on studies performed at Lincoln Laboratory, a center for research operated hy Massachusetts Institute of Technology. The work was sponsored hy the Air Force under Contract Fl9628-90-C-0002. 16. Abstract The Federal Aviation Administration (FAA) Integrated Terminal Weather System (ITWS) is supporting the development of weather products important for air traffic control in the terminal area.
    [Show full text]
  • An Overview of the Integrated Meteorological Observations in Complex Terrain Region at Dali National Climate Observatory, China
    atmosphere Review An Overview of the Integrated Meteorological Observations in Complex Terrain Region at Dali National Climate Observatory, China Anlun Xu 1,2 and Jian Li 3,* 1 Dali National Climate Observatory, Dali 671003, China; xualun@126.com 2 Dali Mountain Meteorological Field Experiment Base, China Meteorological Administration, Dali 671003, China 3 State Key Laboratory Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing 100081, China * Correspondence: lij@cma.gov.cn Received: 14 February 2020; Accepted: 9 March 2020; Published: 12 March 2020 Abstract: Systematically observing components of the climate system as well as their processes and interactions are crucial to understand the weather, climate, climate change, etc. In order to launch long-term, continuous, stereoscopic, and integrated meteorological observations for key regions of the climate system in southwestern China where it is sensitive to interactions among multiple layers and exchanges of mass and energy, the Dali National Climate Observatory (DNCO) was established in May 2006. To date, the DNCO has gradually performed an integrated meteorological observation network in a complex terrain region over the southeastern Tibetan Plateau including the conventional observations of weather and climate, and the special observations of radiation, lightning, soil moisture, wind profile, water vapor, water quality, water level, water temperature profile, turbulent fluxes of momentum, sensible heat, latent heat, carbon dioxide, and methane, etc. Furthermore, the DNCO mainly focuses on the field observation experiments and scientific research activities for mountain meteorology. This paper presents an overview of the DNCO including its location, climatology, scientific objectives, research tasks, and existing observation projects. The progresses in observation and associated research including data quality controls and assessments, recent observation results, and regional numerical model tests are summarized.
    [Show full text]
  • Snow Data Intercomparison on Remote and Glacierized High Elevation Areas
    The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-124 Manuscript under review for journal The Cryosphere Discussion started: 18 July 2017 c Author(s) 2017. CC BY 4.0 License. 1 Snow data intercomparison on remote and glacierized high elevation 2 areas (Forni Glacier, Italy) 3 4 Senese Antonella1, Maugeri Maurizio1, Meraldi Eraldo2, Verza Giampietro3, Azzoni Roberto Sergio1, 5 Compostella Chiara4, Diolaiuti Guglielmina1 6 1 Department of Environmental Science and Policy, Università degli Studi di Milano, Milan, Italy. 7 2 ARPA Lombardia, Centro Nivometeorologico di Bormio, Bormio, Italy. 8 3 Ev-K2-CNR - Pakistan, Italian K2 Museum Skardu Gilgit Baltistan, Islamabad, Pakistan. 9 4 Department of Earth Sciences, Università degli Studi di Milano, Milan, Italy. 10 11 Correspondence to: Antonella Senese (antonella.senese@unimi.it) 12 13 Abstract. 14 We present and compare 11 years of snow data (snowfall, snow depth and snow water equivalent (SWE)) measured by an 15 Automatic Weather Station and by some field campaigns on the Forni Glacier. The data have been acquired by means of i) a 16 Campbell SR50 sonic ranger from October 2005 (snow depth data), ii) manual snow pits from January 2006 (snow depth and 17 SWE data), iii) a Sommer USH8 sonic ranger from May 2014 (snow depth data), iv) a Park Mechanical SS-6048 snow pillow 18 from May 2014 (SWE data), v) a manual snow weighting tube (Enel-Valtecne ©) from May 2014 (snow depth and SWE data). 19 The aim of the analyses is to assess the mean value of fresh snow density and the most appropriate method to evaluate SWE 20 for this measuring site.
    [Show full text]
  • Turf Smart Solutions 2021 Product Catalog
    TURF SMART SOLUTIONS 2021 PRODUCT CATALOG EASY ORDERING - REQUEST A QUOTE At Spectrum Technologies, we pride Online www.specmeters.com ourselves on helping our valued customers transform plant measurements into more E-mail info@specmeters.com profitable growing decisions. Since 1987, Phone 1 (800) 248-8873 (Toll Free U.S. & Canada) we have manufactured and distributed affordable, leading-edge plant measurement 1 (815) 436-4440 technology to agricultural, horticultural, Fax 1 (815) 436-4460 environmental, and turf markets throughout the world, serving more than 3600 Thayer Court 14,000 customers in over 80 countries. Aurora, IL 60504 USA We proudly work alongside researchers, growers, golf course superintendents, Order Total Shipping/Handling (USA Only) and industry suppliers to provide a broad $25.01 to $99.99 $18.00 line of innovative devices and software Standard $100.00 to $499.99 $24.00 for better environmental monitoring, Ground Delivery: $500.00 to $999.99 $30.00 nutrient management, soil moisture $1,000.00 to $1,999.99 $35.00 measurement, irrigation scheduling, and Express Delivery: $2,000.00 to $2,999.99 $44.00 pest management. (Contact for charges) $3,000.00 to $4,999.99 $56.00 Canadian Delivery: $5,000.00 to $9,999.99 $78.00 (Contact for charges) 10,000 or more Contact for pricing Our products will positively impact the way you grow your turf; therefore, we stand behind every product with our 100% ORDERING INFORMATION Satisfaction Guarantee. Our friendly and Purchase Orders: We accept purchase orders from accredited universities, governments, businesses, and nonprofit organizations. Completed credit application knowledgeable product support team is may be required.
    [Show full text]
  • Advanced Weather Monitoring for a Cable Stayed Bridge
    Advanced weather monitoring for a Cable stayed bridge Chandrasekar Venkatesh June 11, 2018 Bachelors in Electrical and Electronics Engineering Ph.D. in Electrical Engineering Department of Electrical Engineering and Computer Science, College of Engineering and Applied Science Committee Chair: Dr. Arthur Helmicki Committee Members: Dr.Victor Hunt Dr. Douglas Nims Dr. Ali Minai Dr. William Wee Abstract In the northern United States, Canada, and many northern European countries, snow and ice pose serious hazards to motorists. Potential traffic disruptions caused by ice and snow are challenges faced by transportation agencies. Successful winter maintenance involves the selection and application of the most optimum strategy, over optimum time intervals. The risk associated with operating the bridges during winter emergencies varies depending on the size of the structure, the material of the stays, volume of average daily traffic, geographical location, nature of terrain and surroundings etc. The ‘Dashboard’, a monitoring system designed to help the bridge maintenance and operation personnel was developed at University of Cincinnati Infrastructure Institute. This was implemented at the Veterans Glass City Skyway Bridge in Toledo, Ohio. This system was also extended to the Port Mann Bridge in Vancouver, Canada. The aim of this research is to come up with an advanced monitoring system which will help the bridge management team make control actions during winter emergencies on the VGCS and Port Mann bridges. The current monitoring system gives information on the status of ice accumulation/ snow accretion or shedding based on last one hour’s weather data. This dissertation focuses on adding intelligence to the existing system through addition of sensors, identifying patterns in events, adding cost-benefit analysis and incorporating forecast parameters, while also extending the system to other bridges and structures.
    [Show full text]
  • Estimating Snow Water Equivalent on Glacierized High Elevation Areas (Forni Glacier, Italy)
    1 Estimating the snow water equivalent on glacierized high elevation 2 areas (Forni Glacier, Italy) 3 4 Senese Antonella1, Maugeri Maurizio1, Meraldi Eraldo2, Verza Gian Pietro3, Azzoni Roberto Sergio1, 5 Compostella Chiara4, Diolaiuti Guglielmina1 6 7 1 Department of Environmental Science and Policy, Università degli Studi di Milano, Milan, Italy. 8 2 ARPA Lombardia, Centro Nivometeorologico di Bormio, Bormio, Italy. 9 3 Ev-K2-CNR - Pakistan, Italian K2 Museum Skardu Gilgit Baltistan, Islamabad, Pakistan. 10 4 Department of Earth Sciences, Università degli Studi di Milano, Milan, Italy. 11 12 Correspondence to: Antonella Senese (antonella.senese@unimi.it) 13 14 Abstract. 15 We present and compare 11 years of snow data (snow depth and snow water equivalent, SWE) measured by an Automatic 16 Weather Station corroborated by data resulting from field campaigns on the Forni Glacier in Italy. The aim of the analyses is 17 to estimate the SWE of new snowfall and the annual peak of SWE based on the average density of the new snow at the site 18 (corresponding to the snowfall during the standard observation period of 24 hours) and automated depth measurements, as 19 well as to find the most appropriate method for evaluating SWE at this measuring site. 20 The results indicate that the daily SR50 sonic ranger measures allow a rather good estimation of the SWE (RMSE of 45 mm 21 w.e. if compared with snow pillow measurements), and the available snow pit data can be used to define the mean new snow 22 density value at the site. For the Forni Glacier measuring site, this value was found to be 149 ± 6 kg m-3.
    [Show full text]