Transcript ned_wed_weather_systems_dataloggers_databasesx

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
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Weather systems
• Some companies offer “one stop” shopping,
e.g. Campbell offers instruments, logger, and
software packages.
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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
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CR3000
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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
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Weather databases
• What is a relational database?
• What is the difference between databases and
spreadsheets?
• When should one use a database versus a
spreadsheet?
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Spreadsheet/delimited flat file
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Table in a database
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Getting logger data into a database
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This is the hard part!
Commercial solutions
Campbell LNDB
Vista Datavision
Roll your own (e.g. UNIX shell scripting or
Python)
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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.
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Relational database systems
• Microsfot SQL Server
• MySQL
• PostegreSQL
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SQL
• Structured query language
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Primary keys
• A unique identifier for a row
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Foreign keys
• a field that links to a row in another table
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Normalization, first normal form
From http://edn.embarcadero.com/article/25209
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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
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CUES_CR3K_2_SNOW_DEPTH_2012rev
CUES_CR3K_1_WS600Weather
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Normalized form, transaction table
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Instruments
Measurements
Transaction table
List of tables
Mappings
Logger table
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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.
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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.
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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
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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
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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
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Weighing gauges
– Precip falls 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.
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Undercatch
Goodison, B., Louie, P. Y. T., and Yang, D.: WMO Solid precipitation measurement
intercomparison, World Meteorological Organization, 1998.
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Undercatch at Mammoth
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
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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
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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
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Cool shit
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Gamma ray SWE detectors
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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
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Lysimeters
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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
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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.
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