230 likes | 325 Views
Alberta Agriculture and Food (AF). Surface Meteorological Stations and Data Quality Control Procedures. Presentation Overview. Existing and proposed (AF) network Data QA/QC Parameter list Quality states QA/QC checks Data filling Conclusions. Meteorological Station Expansion.
E N D
Alberta Agriculture and Food (AF) Surface Meteorological Stations and Data Quality Control Procedures
Presentation Overview • Existing and proposed (AF) network • Data QA/QC • Parameter list • Quality states • QA/QC checks • Data filling • Conclusions
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
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)
ACGM (AF) IMCIN (AF) Other (AENV AES SRD) Existing and proposed stations in Alberta’s Near-Real-Time Network AGDM (AF) 20 km buffer
A QA/QC and Data-Filling Decision Support System forNear Real-Time Climate Data Providing computer-assisted quality assurance, quality control and data filling
Parameter List (Hourly) • Temperature • Humidity • Solar Radiation • Wind Speed • Wind Direction • Precipitation (hourly and 6 hourly) • Soil Moisture • Soil Temperature
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
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)
Methodology for Defining QA/QC checks • We used the hourly period of record supplied by Environment Canada that contains >25 million records from 250 stations in and around Alberta • An adjustable trigger point for the “suspect” occurrences was set at 0.01% (1:10,000) for each test • Arbitrary and adjustable (default or station specific) • For 200 stations examine @ 50hourly values per day
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 Missingand then filled
Range Checks:Solar Radiation Invalid Suspect Valid -0 950 Hourly Solar Radiation (W m-2)
Data Filling • Temporal filling • Spatial filling (IDW) • Spatial-temporal filling (IDW+) • Manual filling In every parameter’s daily rollup you know how many records were filled so you can judge the validity of the daily value
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
valid valid susp. susp. valid Persistence Check Difference of Maximum and Minimum over n steps must be greater than y susp. Persistance Checks
valid Step Difference of maximum and minimum over n steps must be at most y susp. valid valid valid valid Step Checks
Other Tests • Like Sensors • Relating wind speed 2M to wind speed 10M • Relating occurrence of precipitation to humidity • Nearest Neighbors
M M M M Temporal Filling:for 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
Spatial filling:Inverse 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
Distribution of total ppt. by day at nearest station 0.44*16.4 0.35*16.4 0.21*16.4 Estimated ppt at Barnwell Spatial-Temporal Filling:Precipitation Total ppt. at Barnwell using IDW = 16.4 Data Filling