Design and Construction of Daily-updating Objective Climate Prediction System Based on the Real-time Forecast of CFSv2

Hao Ma, Fei Yu, Ming Yang, Jingwen Ge, Gaofeng Fan, Ying Liu, Zheyong Xu, Jianjiang Wang, Hangyuan Sun
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Abstract

— The CFSv2 forecast products have been widely used in climate prediction operation all over the world. Although the real-time forecast is able to basically capture large pattern of climate anomaly, there still exists obvious bias, which may have enormous impacts on predicted result and thus cannot be neglected. Presently, how to smartly use the massive modeling outputs to improve forecast skill is very important for objective prediction. In this paper, a statistical downscaling strategy for correcting systematic bias through recovering modeling-climatology to its observational counterpart is introduced, and with such methodology, an operational platform conducting real-time 1-30d and 10-30d temperature and precipitation objective prediction is constructed for Zhejiang province. Various verification schemes of the Ps score, Pc score, ACC, SCC, RMSE, the absolute bias, relative bias, and sign coherence are applied on long-term temperature and rainfall assessment. Given the behavior of 335 independent forecast ensembles from January 1 st to November 30 th in 2019, predictive ability of the downscaling model is forecast. In general, forecast presentation demonstrates this system is practically useful and valuable.
基于CFSv2实时预报的日更新客观气候预测系统设计与构建
CFSv2预报产品已广泛应用于全球气候预报业务。实时预报虽然能够基本捕捉到气候异常的大格局,但仍然存在明显的偏差,对预测结果影响巨大,不容忽视。目前,如何巧妙地利用海量的建模输出来提高预测技能,对于客观预测是非常重要的。本文介绍了利用模式气候学数据向观测数据的还原来修正系统偏差的统计降尺度策略,并以此方法构建了浙江省1-30d和10-30d温度和降水实时客观预报的业务平台。将Ps评分、Pc评分、ACC、SCC、RMSE、绝对偏差、相对偏差和符号一致性等验证方案应用于长期温度和降雨评估。以2019年1月1日至11月30日335个独立预报组合的天气表现为例,对降尺度模式的预测能力进行了预测。总体而言,预测演示表明该系统具有实际用途和价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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