Interpolating hourly temperatures for computing agroclimatic metrics

Area of Science:

• Agricultural Meteorology
• Environmental Data Science
• Climatology

Background:

• Continuous hourly temperature data are essential for calculating critical agroclimatic metrics like chill and heat accumulation in orchards.
• Gaps in hourly temperature records are common, forcing reliance on less precise daily data or incomplete hourly datasets.
• Existing methods for interpolating hourly temperature records have limitations.

Purpose of the Study:

• To develop and evaluate a novel procedure, SolveHours, for filling gaps in hourly temperature records.
• To improve the accuracy of agroclimatic metric calculations by generating gapless hourly temperature data.
• To provide a robust tool for researchers and farm managers dealing with incomplete temperature datasets.

Main Methods:

• The SolveHours procedure integrates measured hourly temperatures, idealized daily temperature curves, and proxy data to interpolate missing values.
• It determines daily temperature extremes by solving linear equations and fills initial gaps using bias-corrected proxy data or linear interpolation.
• An idealized temperature curve is generated, and deviations from recorded data are used to create a final, gapless hourly temperature record.

Main Results:

• SolveHours achieved high performance, with Ratio of Performance to Interquartile Distance (RPIQ) values of 6.7 and 8.2, and low root mean square errors (1.3-1.6 °C).
• The procedure significantly outperformed alternative gap-filling algorithms in reproducing accumulated Chill Portions and Growing Degree Hours.
• The method's effectiveness was validated using a dataset with randomly introduced gaps.

Conclusions:

• SolveHours provides a highly accurate and reliable method for reconstructing gapless hourly temperature records.
• This advancement enables more precise calculation of essential agroclimatic metrics for orchard management and research.
• The SolveHours procedure is available as part of the R programming package 'chillR'.