Commercial weather systems, data loggers, and weather databases

1. Commercial weather systems, data loggers, and weather databases Ned Bair US Army Corps of Engineers Cold Regions Research and Engineering Laboratory Earth Research Institute, UC - Santa Barbara

2. Weather systems • Some companies offer “one stop” shopping, e.g. Campbell offers instruments, logger, and software packages.

3. Two US companies that offer commercial systems • Campbell Scientific • Scientific applications, remote (no power) installations • Campbell makes instruments, loggers, and software • Andover • Facilities system • provides controllers • SQL Server interface

5. CR3000

10. Data loggers • Record measurements from instruments into tables • Often convert a voltage into a physical quantity using a linear equation • Also can use serial protocols • Use a simple high level programming language, e.g. Edlog for Campbell

11. Weather databases • What is a relational database? • What is the difference between databases and spreadsheets? • When should one use a database versus a spreadsheet?

12. Spreadsheet/delimited flat file

13. Table in a database

14. Getting logger data into a database • This is the hard part! • Commercial solutions • Campbell LNDB • Vista Datavision • Roll your own (e.g. UNIX shell scripting or Python)

15. What is UNIX/LINUX • A plain text operating system. Linux (1991) is based on UNIX, developed in 1969 by Bell Labs. • Tons of text tools, makes it great for processing scientific data • Cygwin is unix emulator for PCs.

18. Relational database systems • Microsfot SQL Server • MySQL • PostegreSQL

19. SQL • Structured query language

20. Primary keys • A unique identifier for a row

21. Foreign keys • a field that links to a row in another table

22. Normalization, first normal form From http://edn.embarcadero.com/article/25209

23. In practice • Each table should contain as few columns as possible • Converting a table from more columns to more rows usually results in a more normalized form

24. CUES_CR3K_2_SNOW_DEPTH_2012rev CUES_CR3K_1_WS600Weather

25. Normalized form, transaction table

26. Instruments Measurements Transaction table List of tables Mappings Logger table

27. How much time should I spend dealing with database issues? • It depends on the scale of your system. • If you only have a few instruments, then a basic system that spits out logger tables, e.g. Campbell is fine. • If you have lots of instruments and things change frequently, then you need a database system,e.g. Andover.

28. Why spend the effort of normalizing? • For more complex systems you will spend much less time overall with an efficient and normalized DB. • E.g. adding deleting columns in a flat file sucks. It’s not an issue with a transaction table. • For the bigger systems I suggest becoming good friends with a DBA, preferably one who works for the same employer and likes patrol/avalanche work/etc.

29. Wind heads • “Birds” - RM Young • Pros: Cheap • Cons: Rime and break easily, no heat. • Cylindrical - Phil Taylor • Pros: can accurately measure very strong peak winds (220 mph); great heaters. • Cons: Spin-down time; expensive; phil will retire soon • Sonic – Campbell, Lufft • Pros: No moving parts; not too expensive for 2d version • Cons: arms can rime up and break, but heated version is offered

30. Temperature/RH sensors • usually combo probes • simple install, but MUST be shielded from radiation. • Mammoth’s super signs, bank signs, and high school signs are often not shielded. • e.g. Campbell HMP45C

31. Tipping Buckets • Work by filling a small bucket with melted precip until it tips, tips are counted by the gauge. • e.g. MetOne • Pros: accuracy, cost • Cons: clogging by ice; undercatch bias

32. Weighing gauges • Precipfalls into an antifreeze/water mixture on top of a pressure transducer. • Increases in transducer weight correspond to precip increases. • e.g Noah, Sutron • Pros: accuracy, cost; • Cons: clogging by ice; undercatch bias; need to be emptied, sometimes 2X or more a season.

33. Undercatch Goodison, B., Louie, P. Y. T., and Yang, D.: WMO Solid precipitation measurement intercomparison, World Meteorological Organization, 1998.

34. Undercatch at Mammoth

35. Snow pillows • Custom-made deals, e.g. CA DWR • Stainless steel, usually 2 x 2 filled with antifreeze (ethylene glycol) • Antifreeze is piped to a pressure transducer, e.g. GE Druck that outputs a voltage, eg. 0-5 V, 0-100 in water • Pros – only decent measure of SWE on the ground • Cons – not very sensitive; expensive and hard to get • Custom rigs

36. Radiometers • Shortwave • Clear (200-1200nm) and nIR(1200-1500nm), e.g. Eppley labs • Direct and diffuse (e.g. auto shadow band, Sunshine pyranometer) • Longwave – 3.5 µm

37. Depth pingers • Ultrasonic • Send a ultrasonic chirp down to snow surface, then calculate depth based on its return time back to the sensor • E.g. Judd, Campbell • Pros • cheap, accurate, durable • Cons • Can give null readings during heavy snow

38. Cool shit • Gamma ray SWE detectors • Measure SWE via attenuation of gamma radiation emitted from earth’s core. • Campbell makes a commercial sensor • Pros: no moving parts • Cons: water kills signal, low SWE limit, expensive • FMCW radar • Measures stratigraphy by scanning through radars frequencies • Pros: nondestructive stratigraphy • Cons: expensive and needs modeled grain sizes • Lysimeters • Tipping buckets buried in the ground • Measure melt water • Pros: cheap, great way to measure when water 1st gets through pack • Cons: not commercial systems available, get silted up. • Capacitance probes • Measure SWE via dielectric constant • Pros: very accurate • Cons: water kills signal

39. Instrument calibration • All instruments require maintenance and calibration. • Some instruments are more robust than others, e.g. Phil Taylor wind heads versus sonic anemometers. • This is an integral part of your budget that you can’t skimp on. • Cap-Ex’s are usually easier sells than other budget items like pay raises.