Climate Data for Field Trials: Onsite Micro Stations Versus ClimateNA

Abstract Ecological studies in diverse environmental fields require accurate climate data for point locations that are often distant from reliable public weather stations. ‘Onsite’ micro weather stations can be established directly at research locations, but purchase, establishment, and maintenance costs and data gaps can limit their feasibility. Alternatively, climate data for point locations can be predicted from ClimateNA, a publicly available software package, but the prediction accuracy in remote and mountainous locations is uncertain. We compared ClimateNA predictions with observations from onsite weather stations located at 11 interior spruce provenance trials in British Columbia, Canada. We found that ClimateNA predictions were highly accurate for temperature variables (average prediction error 0.77°C; most R2 values > 0.99) but moderate for precipitation variables (average prediction error 27mm; 0.21 < R2 values < 0.58) when compared with onsite weather data. Growth response functions developed with the two data sources showed similar shapes for temperature variables. Our results suggest that 1) temperature variables can be accurately predicted at remote and mountainous locations using ClimateNA; 2) precipitation variables are more accurately predicted with ClimateNA than with onsite weather stations, which were considerably affected by random factors; and 3) response functions provide an effective, independent tool to assess alternative sources of climate data. Our results recommend the use of ClimateNA over onsite weather stations, except where highly accurate precipitation data are required, in which case, high-quality onsite weather stations must be established and carefully maintained.