Abstract

Daily meteorological observation data of the early period (pre-1950) were critically important for investigating the long-term trends and multi-decadal scale variability of extreme climate events. The high-resolution surface air temperature (SAT) data for time period before 1950 are lacking in China. We extended the SAT observations of China back to 1840 through developing a pre-1950 daily SAT dataset. The early-period daily SAT were manually corrected for the input and clerical errors, and then according to the length or coverage of time, the main series for each of the cities was determined. The observation time system of unknown sites was determined by the minimum difference method. After these operations, the data of all sites were unified into the same format. By using the ridge regressions established based on data from modern reference stations, the missing maximum temperature (Tmax) and minimum temperature (Tmin) were interpolated. The early-period data were combined with modern data to form the long-term daily SAT dataset of 1840–2020 in China. RHtest software was used to detect and adjust the inhomogeneities in the station data series. Finally, the century-long homogenized daily SAT dataset including 45 key city stations in China was obtained. Among the stations, there are 20 stations with observation record more than one hundred years. The length of temperature observation series of 17 stations is between 80 and 100 years. The series length of the remaining 7 stations is between 68 and 80 years. Finally, the angular distance weighting (ADW) method was used to interpolate the data into grid products, and the grid size is 2.5 ° × 2.5 °. The dataset was named CUG-CMA CHDT, which is applicable in monitoring, studies and assessments of regional extreme temperature change and variability in China.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.