Long-term data correlation
Measure-correlate-predict analysis against long-term reference data.
Long-term data correlation
We correlate short-term site data with long-term references (MCP).
This captures the long-term resource, not just the campaign period.
Scope in detail
Correlation
We correlate the site's short-term measured data against long-term reference stations using an appropriate measure-correlate-predict method — typically regression-based — selecting the technique that best fits the relationship strength between site and reference data rather than defaulting to a single standard method regardless of fit quality. Correlation strength is reported explicitly since a weak correlation undermines confidence in the long-term correction.
Reference data
Long-term reference datasets — nearby met stations, reanalysis data — are assessed for length of record, data quality and physical relevance to the site before being used as the basis for long-term correction, since a reference station with a different climate regime can introduce more error than it resolves. We document why each reference source was selected or rejected.
Adjustment
The long-term adjustment applies the correlation relationship to extend the site's short measurement period into a statistically representative long-term estimate, accounting for the specific years covered by the reference record relative to the broader climatological trend. We check the adjusted result against independent reference sources where available, rather than relying on a single correlation.
Report
MCP methodology, correlation statistics and the resulting long-term adjustment are documented in a correlation report structured so a reviewing engineer can verify the correction independently, including the reference data used, the correlation coefficient achieved and the sensitivity of the result to the method chosen.
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