The NOAA/FAA/NCAR Winter Precipitation Test Bed: How Well Are We Measuring Snow? t Roy Rasmussen 1, Bruce Baker 2, John Kochendorfer 2, Tilden Myers 2, Scott Landolt 1, Alex Fisher 3, Jenny Black 1, Julie Theriault 1, Paul Kucera 1, David Gochis 1, Craig Smith 3, Rodica Nitu 3,Mark Hall 2,Steve Cristanelli 1 and Ethan Gutmann 1 1. National Center for Atmospheric Research (NCAR) 2. NOAA 3. Environment Canada

The NOAA/FAA/NCAR Winter Precipitation Test Bed: How Well Are We Measuring Snow? t Roy Rasmussen 1, Bruce Baker 2, John Kochendorfer 2, Tilden Myers 2, Scott Landolt 1, Alex Fisher 3, Jenny Black 1, Julie Theriault 1, Paul Kucera 1, David Gochis 1, Craig Smith 3, Rodica Nitu 3,Mark Hall 2,Steve Cristanelli 1 and Ethan Gutmann 1 1. National Center for Atmospheric Research (NCAR) 2. NOAA 3. Environment Canada

The NOAA/FAA/NCAR Winter Precipitation Test Bed was initially established in 1991 at NCAR in Boulder, Colorado to address FAA needs for real-time snowfall rates in support of ground deicing The NOAA Climate Reference Network program started using the site in the late 90’s to evaluate snow measuring instrumentation for climate purposes (Bruce Baker, lead).

Challenges of automatic snow fall rate measurements: 1.Wind under-catch - Gauge acting as obstacle to the flow, generating updrafts 2.Cap over of the orifice by snow accumulating on the gauge 3.Minimum detectable signal often large (to overcome noise) 4.Minimum detectable signal impacted by wind speed (higher the wind, the larger the minimum detectable signal) 5.Eliminating blowing snow false accumulations 6.High maintenance -Need to empty the bucket after snow fills up and refill bucket with glycol and oil.

National Center for Atmospheric Research Updraft generated upstream of gauge

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Methods devised to solve the challenges: 1.Wind effect: - Wind shields used to prevent updrafts from forming over weighing gauges. 2.Orifice blocking effect - Heaters used to prevent snow build up on the body of the gauge. 3.Reduce minimum detectable signal by software and hardware: -Improved software to reduce false tips by vibration. -Improved hardware to eliminate vibrations and other noise. 4. Reduce the minimum detectable signals increase with wind speed -Use wind shields that have high efficiency (e.g. WMO Double Fence Intercomparison Reference Shield)

Insert image of the Marshall site with DFIR To address these challenges, developed the NOAA/FAA/NCAR Solid Precipitation Test Site near Boulder, Colorado Core to the site: Double Fence Inter-comparison Reference (DFIR) shields as “truth” gauge

Layout of site: Flat and level site located 7 km south of Boulder, Colorado NCAR owned and operated with security fence

10 Aerial View of the NOAA/FAA/NCAR Test site

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12 View of test site to the South

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14 View of test site towards the West

15 Developed and tested double Alter shield

16 Developed and tested 2/3 DFIR shield (CRN)

17 Developed and tested hotplate snowgauge

18 Testing multiple hotplates

19 Documented snow under- catch behavior of various shields and gauges Single Alter Double Alter Small DFIR DFIR Hotplate Wind speed

Established transfer functions for various shields and gauges

Data used to develop transfer function shows significant scatter!

22 Thank You! Rasmussen et al. 2001

23 Numerical studies of flow past various shield/gauge combinations help explain scatter (Julie Therialt talk later in this session)

24 Mapped airflow around shields/gauges using sonic anemometers and numerical modeling

25 Established that visibility is a poor method to estimate the liquid equivalent rate of snow (light, moderate, heavy) HVY MOD LGT 1.7 mm/hr Moderate

27 Developed and tested the Liquid Water Equivalent system for ground deicing use

28 Developed method to heat the orifice of a gauge using temperature controlled heat tape (max temperature 2 ˚C)

Precipitation Type sensor (HSS) WXT temperature, humidity, and wind sensor (Vaisala) Hotplate (Yankee) Weighing Snowgauge (GEONOR) Snow Liquid Water Equivalent System Liquid Equivalent snowfall rate determination Moderate Snow Precipitation Type sensor (Vaisala PWD-22)

30 Aircraft Deicing Fluid testing

31 Accurate snow depth measurements remain a challenge!

32 Measured snow particle size distribution using video disdrometer

Disdrometer Observations 2DVD Specifications Measurement area = 10 cm x 10 cm Scan rate = 51.3 kHz Horizontal resolution = 0.15 mm Vertical resolution = 0.03 mm for snowflakes, 0.1 mm for raindrops Particle Characteristics Height and width Volume Terminal velocity Front viewSide view [mm] ~4 mm

Rain Period: 1230 (17 March)-0200 UTC (18 March ) UTC 17 March UTC 17 March Terminal Velocity vs Equ. Diameter Hydrometeor Size Distribution

Snow Period: UTC Temperature slightly above 0 o C; Small crystals UTC UTC Crystal Type: Irregulars (hvy) 1-2 mm Aggregrate sizes 3-4 mm UTC Terminal Velocity vs Equ. Diameter Hydrometeor Size Distribution

36 Summary The NOAA/FAA/NCAR Winter Precipitation Test Bed has been used to investigate a number of important aspects of winter precipitation: 1.Under-catch of snow as a function of shield type and the development of transfer functions 2.Develop and test new wind shields 3.Evaluate the use of various gauge/shield combinations for both real-time and climate snow measurements. 4.Develop and test new precipitation instruments (hotplate) 5.Real-time measurement of snow for aircraft ground deicing purposes 6.The use of visibility to measure snow intensity 7.Snow size distributions and terminal velocity 8.Radar- reflectivity snowfall relationships

37 Summary How well are we measuring snow? While advances in shields and gauges have been made, we still don’t fully understand the significant scatter in the data nor have we designed the perfect wind shield to reduce the scatter. Need to use direct measurements of the liquid equivalent rate of snow to estimate snow intensity in METARs rather than use visibility The automated measurement of precipitation type and snow depth remains a significant challenge. The upcoming WMO Solid Precipitation Intercomparison Experiment mentioned by Rodica can help address these challenges.

38 Thank You!