深度学习显示出在南极海冰迅速减少情况下进行季节性预测的前景

IF 6.5 2区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Advances in Atmospheric Sciences Pub Date : 2024-02-06 DOI:10.1007/s00376-024-3380-y

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引用次数: 0

摘要

摘要迅速变化的南极海冰引起了人们的极大兴趣。为了提高海冰的预测能力，响应南方海冰预测网络的最新号召，本研究利用卷积长短期记忆（ConvLSTM）网络对南极海冰面积和范围进行了重新预测，结果显示，ConvLSTM能够捕捉南极海冰的年际和季节间变化。重新预测实验表明，ConvLSTM 成功捕捉到了南极海冰的年际和季节间变化，其表现优于欧洲中期天气预报中心。在此基础上，我们提出了 2023 年 12 月至 2024 年 6 月的预测结果，表明南极海冰将保持在低位，但可能不会创下新低。这项研究凸显了深度学习在南极海冰预测中的应用前景。

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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Deep Learning Shows Promise for Seasonal Prediction of Antarctic Sea Ice in a Rapid Decline Scenario

Abstract

The rapidly changing Antarctic sea ice has garnered significant interest. To enhance the prediction skill for sea ice and respond to the Sea Ice Prediction Network-South’s latest call, this study presents the reforecast results of Antarctic sea-ice area and extent from December to June of the coming year with a Convolutional Long Short-Term Memory (ConvLSTM) Network. The reforecast experiments demonstrate that ConvLSTM captures the interannual and interseasonal variability of Antarctic sea ice successfully, and performs better than the European Centre for Medium-Range Weather Forecasts. Based on this, we present the prediction from December 2023 to June 2024, indicating that the Antarctic sea ice will remain at lows, but may not create a new record low. This research highlights the promising application of deep learning in Antarctic sea-ice prediction.

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来源期刊

Advances in Atmospheric Sciences 地学-气象与大气科学

CiteScore

9.30

自引率

5.20%

发文量

154

审稿时长

6 months

期刊介绍： Advances in Atmospheric Sciences, launched in 1984, aims to rapidly publish original scientific papers on the dynamics, physics and chemistry of the atmosphere and ocean. It covers the latest achievements and developments in the atmospheric sciences, including marine meteorology and meteorology-associated geophysics, as well as the theoretical and practical aspects of these disciplines. Papers on weather systems, numerical weather prediction, climate dynamics and variability, satellite meteorology, remote sensing, air chemistry and the boundary layer, clouds and weather modification, can be found in the journal. Papers describing the application of new mathematics or new instruments are also collected here.