Alberta Agriculture and Food (AF)

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Alberta Agriculture and Food (AF)

• Surface Meteorological Stations and Data Quality
  Control Procedures

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Presentation Overview

• Existing and proposed (AF) network
• Data QA/QC
• Parameter list
• Quality states
• QA/QC checks
• Data filling
• Conclusions

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Meteorological Station Expansion

• 67 N-R-T scalable station platforms
• ?all season ppt (GEONOR) ?temperature ?humidity
• ? GOES platform ? 2M wind speed
• ? Campbell Cr10x-2m loggers
• Additional sensors can be added later
• Data will be freely accessible and sensors can be
  added by any one with dollars, with the caveat
  that all data would be public domain.
• Currently 44 are installed and operational
• 23 more will be operational by May 1, 2008

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AF Stations(N 113)

• Common Elements
• ?All season ppt (GEONOR) ?Temperature ?Humidity
• ?Wind speed 2 m ?GOES platform ? Campbell
  Cr10x-2m loggers
• 36 Drought Net Stations (AGDM)
• Incoming short-wave solar radiation (26)
• Net solar radiation (3)
• Wind speed and direction at 10 m (36)
• Soil moisture and temperature at 5, 20, 50, 100
  cm (30)
• 10 IMCIN Stations
• Incoming short-wave solar radiation (10)
• Wind speed and direction at 10 m (10)
• 67 Agriculture Climate Monitoring Stations (AGCM)
• Wind direction at 2m (15)
• Incoming Short-wave solar radiation(15)

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Existing and proposed stations in Albertas
Near-Real-Time Network
AGDM (AF)
20 km buffer
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A QA/QC and Data-Filling Decision Support System
forNear Real-Time Climate Data

• Providing computer-assisted quality assurance,
  quality control and data filling

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Parameter List (Hourly)

• Temperature
• Humidity
• Solar Radiation
• Wind Speed
• Wind Direction
• Precipitation (hourly and 6 hourly)
• Soil Moisture
• Soil Temperature

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Quality States

• Valid
• Not needed to be checked by a human
• Suspect
• Needs to be checked by a human and validated or
  filled
• Invalid
• Needs to be checked by a human and filled
• Missing
• Needs to be checked by a human and filled

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QA/QC Checks

• Range
• within a reasonable range
• Step
• maximum allowable change
• Persistence
• minimum allowable change
• Like Sensor
• similar value to similar sensors
• Spatial
• similar value to neighboring stations (parameter
  dependent)

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Methodology for Defining QA/QC checks

• We used the hourly period of record supplied by
  Environment Canada that contains gt25 million
  records from 250 stations in and around Alberta
• An adjustable trigger point for the suspect
  occurrences was set at 0.01 (110,000) for each
  test
• Arbitrary and adjustable (default or station
  specific)
• For 200 stations examine _at_ 50 hourly values per
  day

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Range Checks

• Three range checks
• Valid
• Suspect
• Invalid
• If the data falls within the inner range then it
  will be marked Valid If it falls in between the
  outer range and the inner range it will be marked
  Suspect
• If data falls outside the outer range it will be
  marked as Invalid
• If the data is missing it will be marked Missing
  and then filled

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Range ChecksSolar Radiation
Invalid
Suspect
Valid
-0
950
Hourly Solar Radiation (W m-2)
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Range ChecksTemperature
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Data Filling

• Temporal filling
• Spatial filling (IDW)
• Spatial-temporal filling (IDW)
• Manual filling

In every parameters daily rollup you know how
many records were filled so you can judge the
validity of the daily value
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Conclusions

• Relatively dense high quality and scalable
  network in the Agricultural area of Alberta
• We have a state of the art QA/QC process that is
  both flexible and data driven
• Reduces man power
• Capable of generating error logs for maintenance
  checks

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Persistence Check
Difference of Maximum and Minimum over n steps
must be greater than y
susp.
Persistance Checks
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Step
Difference of maximum and minimum over n steps
must be at most y
susp.
valid
valid
valid
valid
Step Checks
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Other Tests

• Like Sensors
• Relating wind speed 2M to wind speed 10M
• Relating occurrence of precipitation to humidity
• Nearest Neighbors

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Temporal Fillingfor most parameters
One value missing either side Simply average of
two values adjacent values
Up to X values missing linearly interpolate
missing values from valid end points
Missing or Invalid
If more than X consecutive values are missing use
spatial interpolation

• 3 for most parameters
• 6 for Soil Temperature
• 12 for Soil Moisture

Data Filling
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Spatial fillingInverse Distance Weighting

• Adjustable parameter dependent radius
• Max 8 neighbors
• Rainfall 70 km radius
• Other 120 km radius
• Else use nearest station if within X radius
• Else use nearest station and mark as suspect

Data Filling
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Spatial-Temporal FillingPrecipitation
Total ppt. at Barnwell using IDW 16.4
Data Filling