Daily Temperature Prediction with CMIP6 in the Historical Period of Hong Kong

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外文摘要：An ensemble forecast of historical climate simulations consisting of CMIP6 models was used to project years during World War Ⅱ for which temperature data were missing for Hong Kong。 In multi-model ensemble prediction， since the deep learning in this paper considers that GCM has dependencies between continuous values， the overall effect of prophecy may be better than machine learning。 The daily temperature recorded by the Hong Kong Observatory and the extreme temperature index are used to evaluate the daily temperature forecast effect of CMIP6 in the historical period。 In the 139-year record span of the Hong Kong Observatory， comparing the forecast results with and without CMIP6， the results show that except for the TN10p and TX10p cold indicators， all other indicators are on the rise， indicating that the temperature is rising。

外文关键词：

daily temperature trendHongkongcmip6ensemble prediction

作者：

Qishu Chen

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作者单位：

Faculty of Data Science, City University of Macau, Avenida Xu Risheng, Taipa, Macau, China

会议名称：

International Conference on Geographic Information and Remote Sensing Technology

会议地点：

Qingdao(CN)

会议母体文献：

Second International Conference on Geographic Information and Remote Sensing Technology

页码：

1279706.1-1279706.10

出版时间：

2023

DOI：

10.1117/12.3007398