Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal...Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal conditions in East Asia for up to five years.We compare temperature-based agroclimatic indicators from atmospheric reanalysis data with the firstyear prediction of the Decadal Prediction System version 4(DePreSys4),initialized annually from November 1960 to 2024.Our analysis reveals that first-year predictions accurately represent observed spatial climatological patterns,although trends in agroclimatic indicators based on daily maximum temperature are overestimated.High skill scores are observed in predicting the beginning of the growing season,frost-free days,agricultural hot days,and heat intensity in major cropping regions.However,the end of the growing season is less predictable due to longer lead times.Notably,five-year average predictions show higher skill than first-year predictions due to smoothed interannual variability.These improved climate predictions enable farmers and policymakers to make informed decisions about crop selection and agricultural infrastructure.展开更多
基金supported by a National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(Grant No.RS-2024-00342219)the Korea Meteorological Administration Research and Development Program(Grant No.RS-2025-02313090)S.-Y.JUN and B.-J.PARK were supported by Korea Polar Research Institute(KOPRI)grants funded by the Ministry of Oceans and Fisheries(Grant No.KOPRI PE25010).
文摘Climate change poses significant risks to agriculture,particularly in East Asia,a major crop-producing region.This study evaluates the effectiveness of near-term climate predictions in forecasting agricultural thermal conditions in East Asia for up to five years.We compare temperature-based agroclimatic indicators from atmospheric reanalysis data with the firstyear prediction of the Decadal Prediction System version 4(DePreSys4),initialized annually from November 1960 to 2024.Our analysis reveals that first-year predictions accurately represent observed spatial climatological patterns,although trends in agroclimatic indicators based on daily maximum temperature are overestimated.High skill scores are observed in predicting the beginning of the growing season,frost-free days,agricultural hot days,and heat intensity in major cropping regions.However,the end of the growing season is less predictable due to longer lead times.Notably,five-year average predictions show higher skill than first-year predictions due to smoothed interannual variability.These improved climate predictions enable farmers and policymakers to make informed decisions about crop selection and agricultural infrastructure.
