Overall Statistics RMSE WRF-UA: 159 W m -2 WRF-UCSD: 171 W m -2 STDERR ‘Bias-corrected RMSE’
Objectives Differentiate accuracy, precision, error, and uncertainty. Discuss the dimensions of...
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![Page 1: Objectives Differentiate accuracy, precision, error, and uncertainty. Discuss the dimensions of geographic data quality. Discuss how to compute RMSE for.](https://reader036.fdocuments.net/reader036/viewer/2022062320/56649d6c5503460f94a4cb9b/html5/thumbnails/1.jpg)
Objectives
• Differentiate accuracy, precision, error, and uncertainty.
• Discuss the dimensions of geographic data quality.
• Discuss how to compute RMSE for positional accuracy.
• Describe why data standards are beneficial
• Key terms: metadata
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•Accuracy—how close to “true”
•Precision—how exactly measured and stored
•Error—deviation from “true” value
•Uncertainty—lack of confidence due to incomplete knowledge
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Inherent = Source
Operational = user
or processing
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Semantic DiscrepanciesSemantic Discrepancies
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• RMSE = sqrt(average(squared discrepancies))
• x, y, and z (or e)
• p = sqrt(x²+ y²) (Positional)
• Use p and e for map overall
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Metadata—Geographic Data Quality
• Lineage
• Positional accuracy
• Attribute accuracy
• Logical consistency
• Completeness
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Spatial autocorrelation
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Sampling
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Standards vs Translators