Abstract:

To adapt to climate change and develop and utilize winter agroclimatic resources in Baise city properly, based on the daily observation data of average temperature, precipitation and sunshine duration from 12 national meteorological stations during December 1970 to February 2023 in Baise City, the distribution characteristics, evolution and future change trend of winter agroclimatic resources in Baise City were analyzed by using linear trend analysis, Mann-Kendall mutation test, wavelet analysis. The results indicated that: (1) Baise City had abundant heat resources in winter. The average temperature and accumulated temperature ≥10℃ were the highest in Youjiang River Valley and the lowest in northern mountainous area. The precipitation was more in the south and less in the north. Sunshine duration in the north and middle of Youjiang River Valley were generally higher than those in other areas. (2) From 1971 to 2023, the winter climate of Baise showed a warm and humid trend, and the average winter temperature and accumulated temperature ≥10℃ showed a significant upward trend in general, with the rates of 0.18 ℃/10a and 27.30 ℃·d/10a respectively, and both showed an abrupt increase around 1991. Precipitation showed a significant increasing trend with a rate of 5.27 mm/10a, with a sudden increase in 2010. The sunshine duration in winter showed a significant decreasing trend, and the change rate was -10.36h /10a. In the study period, the four factors all had an interdecadal scale change cycle of 10 to 16 years. (3) The results of projection show that under RCP4.5 and RCP8.5 scenarios, the average winter temperature and accumulated temperature ≥10℃ in Baise City during 2024-2080 show a significant upward trend, while the trend of precipitation is not significant. Sunshine duration increases significantly under RCP4.5. Climate warming brings better heat conditions to winter agricultural production in Baise City, but the fluctuation of precipitation and sunshine duration is great, which increases the instability of agricultural production.

Key words: climate change, Baise City, winter, agroclimatic resources, projection, linear trend analysis, mann-kendall mutation test, wavelet analysis