Comparison of high resolution observational and grid-interpolated weather data and application to thermal stress on herd average milk production traits in a temperate environment

Abstract

To study the effects of heat stress in dairy cattle, animal performance records are merged with weather data from nearby meteorological stations. However, the stations location and distribution may render them less reliable. Alternatively, weather information from several meteorological stations can be interpolated using empirical algorithms to produce gridded estimates of weather parameters at desired spatio-temporal resolutions. The objective of this study was to compare and apply observational weather station data (WSD) and gridded numerical weather prediction (NWP) model data with high spatio-temporal resolution to identify thermal stress thresholds for milk production traits. Weather data were from the German meteorological service and reanalysis was based on the COnsortium for Small-Scale MOdelling (COSMO)-REA6 model. Milk performance data were from over 16 million monthly test-day records for the period 2010 to 2019 in southern Bavaria, Germany. Individual cow records were transformed to herd averages resulting to 797,455 herd test-days from 9,726 herds. These were merged with temperature and temperature humidity index (THI) data from 53 weather stations and corresponding gridded data. There was good agreement between WSD and NWP model data with correlation coefficients of 0.97 for both daily average temperature and THI and 0.84 for relative humidity. However, positive and negative biases were observed in the pre-Alpine regions. The average herd reaction norms were in good agreement and followed similar trends when estimated from WSD and NWP. The heat stress threshold at which milk yield and protein yield started to decline was 16.0 °C for temperature and 60 units for THI. The responses of fat yield, protein and fat contents were generally linear decline with no definite thresholds. Milk urea increased in a non-linear accelerating pattern and there was no undesired effects on SCS. The thresholds obtained in this study may be applied to implement necessary management strategies to mitigate losses.