Sampling Biases in Datasets of Historical Mean Air Temperature over Land

Thursday, 18 December 2014
Kaicun Wang, Beijing Normal University, Beijing, China
Global mean surface air temperature have risen by 0.74 °C over the last 100 years. However, the definition of mean surface air temperature is still a subject of debate. The most defensible definition might be the integral of the continuous temperature measurements over a day (Td0). However, for technological and historical reasons, mean temperatures (Td1) over land have been taken to be the average of the daily maximum and minimum temperature measurements. All existing principle global temperature analyses over land are primarily based on Td1. Here, I make a first quantitative assessment of the bias in the use of Td1 to estimate trends of mean air temperature using hourly air temperature observations at 5600 globally distributed weather stations from the 1970s to 2013. I find that the use of Td1 has a negligible impact on the global mean warming rate. However, the trend of Td1 has a substantial bias at regional and local scales, with a root mean square error of over 25% at 5°×5° grids. Therefore, caution should be taken when using mean air temperature datasets based on Td1 to examine spatial patterns of global warming.