Summary
Abstract. Near-surface air temperature (Ta) is an important physical parameter that reflects climate change. Many methods are used to obtain the daily maximum (Tmax), minimum (Tmin), and average (Tavg) temperature, but are affected by multiple factors. To obtain daily Ta data (Tmax, Tmin, and Tavg) with high spatio-temporal resolution in China, we fully analyzed the advantages and disadvantages of various existing data. Different Ta reconstruction models were constructed for different weather conditions, and the data accuracy was improved by building correction equations for different regions. Finally, a dataset of daily temperature (Tmax, Tmin, and Tavg) in China from 1979 to 2018 was obtained with a spatial resolution of 0.1∘. For Tmax, validation using in situ data shows that the
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.