Atmospheric InstrumentationM. D. Eastin Principles of Measurement and Instrumentation.

Atmospheric Instrumentation M. D. Eastin

Principles of Measurement and Instrumentation


Outline


• Basics about Sensors and Instruments• Instrument Performance Characteristics• Measurement Standards• Interpretation / Reporting of Measurements• Preliminary Data Analysis


Components of a Measurement System:

Instrument: A physical device or system, used to measure or monitor a measurand, that containsa sensor, an energy transfer device, an amplifier, a datadisplay, and a storage device

Parameter: Physical quantity to be measured (ex: pressure). Also called the measurand

Sensor: Device which responds directly to changes in the measurand and produces an output signal. Typical output signals include: (1) mechanical deflection,

(2) a rotation rate, (3) a voltage, (4) a resistance, or (5) a frequency

Primary input: Desired (ex: barometer measures pressure)Secondary input: Undesired / unavoidable (ex: barometer sensitive to wind)

Transducer: Device that converts an output signal to a more useful signal for convenient signal processing, display, transmission, and/or recording

Analog signal: Sensor output that fluctuates continuously with the measurandDigital signal: Sensor output that fluctuates in discrete steps for a given small

change in the measurand

Basics about Sensors and Instruments


Components of a Measurement System:

Instrument: A physical device or system, used to measure or monitor a measurand, that containsa sensor, an energy transfer device, an amplifier, a datadisplay, and a storage device

Amplifier: Device that magnifies a small output signal into a larger signal, that extendsover a greater range, to better discern small changes in the measurand

[ These devices are common in most instruments due to a number ][ of electrical engineering considerations (see Chapter 3)

]

Meter: Displays the “final” (converted and amplified) output signal - digital or analogOften converts the electrical signal (ex: voltage) into physical units (ex: °C)

Recorder: Device employing a retrieval method whereby successive meter readings can be preserved (e.g., paper, film, computer hard drive)

Transmitter: Device that transfers any electronically recorded data to another site viawired or wireless communication systems (ex: phone lines or satellites)

Basics about Sensors and Instruments


Instrument PerformanceCharacteristics


Instrument Performance CharacteristicsTerms and Definitions:

Static Characteristics: Those that do not change in time. Examples include: (1) bias,(2) accuracy, (3) precision, (4) resolution, (5) sensitivity, and (6) dynamic range → all of these will be defined soon!

Specific values determined through careful calibration

Dynamic Characteristics: Those that involve changes with time. Examples include: (1) response time, and (2) drift

Specific values determined through careful calibration

Exposure Characteristics:Those resulting from unique local conditions at the site where an instrument is located. Examples include: (1) conduction (2) radiation effect, (3) wind effects, (4) wetting effects,

and (5) obstructions

Often dynamic in nature since they are related to changes inlocal weather (rain -- sunshine) and obstructions (trees grow)

Cannot be determined through careful calibration – Must be accounted for by instrument design and careful siting


Instrument Performance CharacteristicsTerms and Definitions:

Calibration: A series of performance tests between a new instrument and a high-quality instrument used to determine performance and uncertainty characteristics

These tests can be conducted in a controlled laboratory setting or in the field through a series of inter-comparisons (or “buddy checks).

Laboratory Calibration Field Calibration


Terms and Definitions:

Systematic Error: A consistent / repeated offset in a measurement as a result of a fixedor regular discrepancy in the instrument response

Also called a “bias” – can be accounted for or removed

Random Error: Variations in measurement due to statistical fluctuations in the quantitysensed, the internal operation of the instrument, or some combinationof the two – cannot be removed

Instrument Performance Characteristics



Accuracy: A measure of the overall uncertainty in the value of the measured parameter, when compared against an external standard – determined by the combination

of random and systematic errors

Precision: An instrument is precise if, in repeated trials, it is able to give the same output response for the same input parameter – determined by systematic errors

Note: A precise instrument can still be inaccurate




Resolution: The smallest change in a parameter measureable by an instrument

Sensitivity: Ratio of the instrument response to a unit change in the parameter sensed

Linear response: Accuracy is the same regardless of parameter magnitudeResponse is characterized by a straight line

Non-Linear response: Accuracy varies with parameter magnitudeResponse is characterized by a polynomial function

Linear Non- Linear




Dynamic Range: The full range of parameter values over which an instrument can detect a measureable response

Instruments unable to measure the full range of possible values will “saturate” at a maximum / minimum measureable value and report no further variation

An instrument with insufficient dynamic range

“Saturation” occurred atmaximum

measurablevalue




Response Time (τ): How long an instrument takes to respond by a required amount to a sudden / step change in the parameter being sensed.

Requiredamount

Suddenchange

Full Response Time (3τ)

“Long”

“Short”

“Average”




Response Time (τ): How long an instrument takes to respond by some fractional amount to a typical oscillation in the parameter being sensed.

“Long”“Small Fraction”

“Short”“Large Fraction”

“Average”




Drift Error: Due to physical changes that occur in the sensor with time. These errors are difficult to detect during initial calibration, and are often compensated through

frequent calibrations

ASOS instruments are calibrated at least once per year to account for any drift

Days



Examples: Davis Instrument Vantage Pro-2 surface weather station

See Pages 3-8 in Davis-Vantage-Pro2-Specfication.PDF on course website (Page 6 for Temperature Sensor performance shown below)

Resolution

DynamicRange

ResponseTime

Accuracy

??? +2 slides



Examples: Davis Instrument Vantage Pro-2 surface weather station

Which of the following sensors exhibit → linear sensitivity?→ non-linear sensitivity?→ How do you know?

Pressure

Humidity

Temperature

Reported (Expected) AccuracyParameter




Exposure Error: Due to imperfect coupling between the sensor and the desired parameter to be measured – site specific – cannot be accounted for in calibration

Example: A thermometer designed to measure air temperature willnever exactly measure the true air temperature due to anumber of errors introduced by thermometer mountingand exposure to other parameters that can influence the measured temperature

Stagnation heating(at low wind speeds)

(prevents a regular air flow)(that provides “offset cooling”)

(of any conduction heating)

Solar heating(in direct sunlight)

Evaporative Cooling(when wetted)

(by rain or dew)

Conduction heating(due to solar heating )(of mounting brackets)

Infrared heating(close to a “heated”)

(building)




Exposure Error: Example: Reduced by placing instruments away from large buildings and in well-designed fan-aspirated shelters

Rain shield

Sensor

ConcentricAir Intakes

Fan

Fan Aspiration(maintains regular)(flow of ambient air)

(prevents)(stagnation heating)

Rain Shield(prevents sensor wetting)(and evaporative cooling)

Bright WhiteShield

(Limits both )(solar heating)

(and) (conduction heating)

(by)(mounting hardware)

“Open” exposure(Placement away from)

(buildings)(limits)

(IR heating)


Measurement Standards


Measurement StandardsCalibration Standards:

• In the United States, the “calibration standards” (or high-quality instruments) are maintainedby the National Institute of Standards and technology (NIST)

• Each calibration laboratory must acquire their “standards” from NIST• Each country has its own “standards” institute

Performance Standards:

•A common set of methods used to determine instrument specifications, such as(1) sensitivity, (2) resolution, (3) dynamic range, (4) accuracy, and (5) time constant

•In the United States, the American Society of Testing and Materials (ASTM) establishand maintain these standards

Procedural Standards:

• A common set of methods and documentation, such as (1) averaging periods, (2) wireless communication frequencies, and (3) station description “metadata” that documents each station’s characteristics (location, land cover, exposure, instruments, calibration dates)

• World Meteorological Organization (WMO) sets averaging periods (wind speed → 10 min)• International agreements set communication frequencies (wx balloons → 400-405 MHz)• National Climate Data Center (NCDC) maintains station metadata files


Measurement StandardsExposure Standards: Surface Stations

• World Meteorological Organization (WMO) sets exposure requirements for each parameter

Wind Instruments → Mounted at 10-m above ground level in open terrain, whereby the shortest distance between the anemometerand an obstruction (buildings, trees, etc.) must be at leastten times the height of the obstruction (e.g., at least 100-maway from a 10-m tall tree). No rooftop mounting!

PTH Instruments → Mounted inside a radiation / rainfall shield, with or withoutforced ventilation, at a height of 1.5 to 2.0-m above

ground level in open terrain, whereby the site is not located on a

steep slope or in a depression where thermal conditions might

not be representative of the larger scale. No rooftop mounting!

Precipitation → All gauges should be situated in open terrain with a gauge-mounted wind screen to minimize the effects of blowing

windon “gauge catch” – especially in areas expecting snowfall.Any frozen precipitation must be melted to obtain a liquid equivalent


Measurement Standards

NOAAASOS

SurfaceStation

(operational)

Conformsto WMO

Standards

Most arelocated

at airports

Precipitation(heated)

(tipping bucket)(with)

(wind screen)

Wind Speed / Direction(cup anemometer)

(and wind vane)(at 10 m)

Temperatureand

Humidity(fan-aspirated)

(at 1.5 m)

Pressure(at 1.5 m)

Note the open and level terrain

away from obstructions


Interpretation and Reportingof Measurements


Interpretation and Reporting of MeasurementsWhat does an instrument REALLY measure and then RECORD?

•Most automated (electronic) instruments collect measurements (every 5-10 seconds)•Surface weather stations are required to report once per hour (usually at 5 min to the hour)

What happens to the 600+ individual measurements made each hour by the sensor?


What does an instrument REALLY measure and then REPORT?

•Most automated (electronic) instruments collect measurements (every 5-10 seconds)•Surface weather stations are required to report once per hour (usually at 5 min to the hour)

What happens to the 600+ individual measurements made each hour by the sensor?

• These individual observations are NOT reported• Many are used to estimate a sample mean (X̅@ ) over some time interval

where: Xi = one individual observation

N = total observations collected in specified time interval

The instrument records this sample mean!

N

iiN X

NXXX

NX

121

1)...(

1

Interpretation and Reporting of Measurements


How should YOU report the observation?

•Since we now know that an instrument’s “measurement” is really an average of manyindividual observations, it is important to include the expected variability in thereported value of that parameter

•If the instrument only reports a sample mean (X̅G ), how do we know the variability (σ) associated

with that sample mean?

X

where: μ = true meanX̅$ = sample meanσ = expected variability




•Since we now know that an instrument’s “measurement” is really an average of manyindividual observations, it is important to include the expected variability in thereported value of that parameter

•If the instrument only reports a sample mean (X̅G ), how do we know the variability (σ) associated

with that sample mean? → We don’t!

•However, we do know the expected variability associated with any sample mean observed by

that instrument → the reported accuracyobtained via calibration

X





•Suppose the temperature sensor on a Davis InstrumentsVantage Pro-2 reports the following:

T̅$ = 18.753°C

•We know from the specifications manual:

σ = ±0.5°C → sensor accuracy (see page 6)

•Thus, after accounting for significant figures,the reported observation should be:

18.8 ± 0.5 °C

Note: See Chapter 2 in the text for how to account for expected variability whenmultiple observed parameters are used to calculate another parameter

Example: Vantage Pro-2 stations calculate dewpoint temperature from theobserved temperature and relative humidity

X





•Such variability should also be reported in graphical displays using error bars

X


Incorrect(without error bars)

Temperature (°C) Temperature (°C)

Correct(with error bars)



Preliminary DataAnalysis


Preliminary Data AnalysisA very important step!

•All reported / recorded observations should be checked:

• Do the observations fall within the expected range• Are there any unphysical outliers that need to be removed.• Calibration procedures are not perfect!• Exposure errors can never be completely removed!

•This step is often called quality control and can be automated, but automation will only identify common errors, so a visual inspection is always wise

Step 1: Convert output signal to physical units

•This step is accomplished by applying transfer equations obtained during calibration(see the next slide)

•Most instruments and/or instrument display software come pre-programmed with the transfer equations obtained during the original calibration

•Additional transfer equations may need to be applied to account for any drift error or exposure error determined during subsequent field calibrations


Preliminary Data AnalysisStep 1: Convert output signal to physical units


Preliminary Data AnalysisStep 2: Check for outliers and

out-of-range values

•This step is accomplished by plotting ALL observations as a function of time using the provided display software or custom software, and then methodically removing the suspicious observations


Summary


• Components of Instrument (terms and definitions)

• Instrument Performance Characteristics• Static / Dynamic / Exposure• Calibration• Bias / Accuracy / Precision• Resolution / Sensitivity / Dynamic Range• Response Time / Drift• Exposure errors (types and reduction methods

• Measurement Standards• Winds / PTH / Precipitation

• Interpretation / Reporting of Measurements• What does an instrument really record?

• Preliminary Data Analysis• Methods and Steps


References

Bradley, J.T., K. Kraus, and T. Townsend, 1991: Federal siting criteria for automated weather observations, Preprints 7th Symposium on Meteorological observations and Instrumentation, New Orleans, LA, American Meteorological Society, pp 207-210.

Brock, F. V., and S. J. Richardson, 2001: Meteorological Measurement Systems, Oxford University Press, 290 pp.

Brock, F. V., K. C. Crawford, R. L. Elliot, G. W. Cuperus, S. J. Stadler, H. L. Johnston, M.D. Eilts, 1993: The Oklahoma Mesonet - A technical overview. Journal of Atmospheric and Oceanic Technology, 12, 5-19.

Harrison, R. G., 2015: Meteorological Instrumentation and Measurements, Wiley-Blackwell Publishing, 257 pp.

Helmes, L., and R. Jaenicke, 1985: Hidden information within series of measurement – four examples from atmospheric science, Journal of Atmospheric Chemistry, 3, 171-185

Huffman, G. J., and J. N. Cooper, 1989: Design issues in nearly real-time meteorological systems and sites. Journal of Atmospheric and Oceanic Technology, 6, 353-358.

Parker, D.E., 1994: Effects of changing exposure of thermometers at land stations, International Journal of Climatology, 14, 1-31.

Stokes, G.M., and S. E. Schwartz, 1994: The Atmospheric Radiation Measurement (ARM) Program: Programmatic background and design of the cloud and radiation test bed. Bulletin of the American Meteorological Society, 75, 1201-1221.

Atmospheric InstrumentationM. D. Eastin Principles of Measurement and Instrumentation.

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