Continuity of long-term climate data series after the transition from manual to automatic weather station

In climatology, transitioning from conventional manual weather stations (MWS) to automatic weather stations (AWS) presents challenges in maintaining the homogeneity of long-term data series. At the Skalnate Pleso Observatory (1778 m a.s.l., High Tatras), manual meteorological measurements have been conducted since 1943 using the same methods and devices at the same location. In 2014, the AWS Physicus was installed to record meteorological data parallelly with manual measurements. This study processed six years of parallel measurements (2017-2022) to derive corrections for AWS monthly atmospheric precipitation totals and maximum (Tmax), minimum (Tmin) and mean air temperatures (Tmean) measured in 2023. Two correction approaches were proposed: monthly regressions (MR) and cumulative distribution functions (CDF), including Generalized Extreme Value (GEV) distribution, normal distribution (GAUSS), and Gamma distribution (GAMMA). Analyses of monthly data revealed an underestimation of precipitation totals in AWS data, with a mean bias error (MBE) of -6.8 mm and a root mean squared error (RMSE) of 20.0 mm. The most suitable correction method was the MR, which decreased MBE to 1.5 mm and RMSE to 11.1 mm. AWS monthly air temperature data were overestimated by 0.1 degree celsius, 0.3 degree celsius, and 0.1degree celsius for Tmax, Tmin, and Tmean, respectively. For Tmax, correction using the MR and GEV methods reduced the MBE to 0.0 degree celsius and achieved RMSE of 0.1 degree celsius for both. After applying GAUSS, MBE and RMSE decreased to 0.1 degree celsius. The most appropriate correction method for Tmin was the MR resulting in MBE of 0.0 degree celsius and RMSE of 0.3 degree celsius. For Tmean, the MR and GEV methods reduced the MBE to 0.0 degree celsius and the RMSE to 0.1 degree celsius for both methods. These results demonstrate that AWS monthly data, when corrected using the presented methods, have the potential to maintain the continuity of historical climate data series at Skalnate Pleso Observatory.