首页|基于时间滞后集合和实时偏差订正的气温精细化预报研究

基于时间滞后集合和实时偏差订正的气温精细化预报研究

Refined Air Temperature Forecast Based on Time-lagged Ensemble and Real-time Bias Correction

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基于SWC-WINGS模式 0.01°×0.01°分辨率的小时 2 m气温产品,利用时间滞后集合和实时偏差订正,得到新的逐小时滚动更新的 1 km网格气温预报,并基于预报准确率、平均误差、平均绝对误差等指标,对 2022年 7-8月逐日逐时气温预报结果进行检验分析.结果表明:时间滞后集合预报准确率在各时效均高于SWC-WINGS模式最新时次预报,实时偏差订正可明显提升临近时效准确率,1～6 h时效的平均提高率为 17.3%.SWC-WINGS模式对于四川地区高、低温预报存在明显的系统性偏差,时间滞后集合对于系统性偏差的改进能力有限,而实时偏差订正可将 1 h时效上四川大部分地区低温和高温预报的平均绝对误差分别控制在 1℃和 2℃以内.针对 2022年 8月 13日四川地区高温天气,时间滞后集合与实时偏差订正集成预报对SWC-WINGS模式预报有较好的订正效果.
Based on hourly 2m air temperature product of SWC-WINGS model with a resolution of 0.01°×0.01°,a new 1km grid air temperature forecast with hourly rolling update was obtained by using time-lagged ensemble and real-time bias correction.The hourly air temperature forecast from July to August 2022 was verified by prediction accuracy,average error,and average absolute error.The results showed the accuracy of time-lagged ensemble forecast was higher than that of the up-to-date forecast,and the real-time bias correction leaded to obvious improvement with 17.3%in 1～6 h forecasts.The SWC-WINGS model had obvious systematic bias in the prediction of high and low temperature in Sichuan,and the time-lagged ensemble reduced the deviation weakly.The real-time bias correction could con-trol the average absolute error of low and high temperature forecast in most areas of Sichuan within 1℃ and 2℃,respectively.For the high temperature weather in Sichuan on 13 August 2022,the integration forecast of time-lagged ensemble and real-time bias correction had a high positive skill compared with SWC-WINGS model.

1km gridSWC-WINGSTime lagBias correction

张武龙、陈朝平、杨康权、周威、银航

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四川省气象台,成都 610072

高原与盆地暴雨旱涝灾害四川省重点实验室,成都 610072

1公里网格 SWC-WINGS 时间滞后 偏差订正

国家重点研发计划项目四川智能网格预报创新团队项目中国气象局气象能力提升联合研究专项重点专项四川省重点实验室项目四川省重点实验室项目四川省重点研发项目四川省重点研发项目西南区域创新团队项目中国气象局创新发展专项中国气象局创新发展专项

2021YFC3000900SCQXCXTD-20220122NLTSZ006SCQXKJZD202101SCQXKJYJXMS2021122022YFS05422022YFS0540XNQYCXTD-202202CXFZ2023J016CXFZ2024J013

2024

10.3969/j.issn.1674-2184.2024.01.006

高原山地气象研究
中国气象局成都高原气象研究所 中国气象学会高原气象学委员会

高原山地气象研究

CSTPCD
影响因子：1.313
ISSN：1674-2184
年,卷(期)：2024.44(1)