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There is a clear positive correlation between boreal summer tropical Atlantic sea-surface temperature and annual hurricane numbers. This motivates the idea of trying to predict the sea-surface temperature in order to be able to predict…

大气与海洋物理 · 物理学 2007-05-23 Thomas Laepple , Stephen Jewson

One possible method for the year-ahead prediction of hurricane numbers would be to make a year-ahead prediction of sea surface temperature (SST), and then to apply relationships that link SST to hurricane numbers. As a first step towards…

大气与海洋物理 · 物理学 2007-05-23 Jonathan Meagher , Stephen Jewson

We are building a hurricane number prediction scheme based on first predicting main development region sea surface temperature (SST), then predicting the number of hurricanes in the Atlantic basin given the SST prediction, and finally…

大气与海洋物理 · 物理学 2007-05-23 Stephen Jewson , Roman Binter , Shree Khare , Kechi Nzerem , Adam O'Shay

We consider two ways that one might convert a prediction of sea surface temperature (SST) into a prediction of landfalling hurricane numbers. First, one might regress historical numbers of landfalling hurricanes onto historical SSTs, and…

大气与海洋物理 · 物理学 2007-05-23 Stephen Jewson , Thomas Laepple , Kechi Nzerem , Jeremy Penzer

We are building a hurricane number prediction scheme that relies, in part, on statistical modelling of the empirical relationship between Atlantic sea surface temperatures and landfalling hurricane numbers. We test out a number of simple…

大气与海洋物理 · 物理学 2007-05-23 Roman Binter , Stephen Jewson , Shree Khare

One way to predict hurricane numbers would be to predict sea surface temperature, and then predict hurricane numbers as a function of the predicted sea surface temperature. For certain parametric models for sea surface temperature and the…

大气与海洋物理 · 物理学 2007-05-23 Stephen Jewson

In situ and remotely sensed observations have potential to facilitate data-driven predictive models for oceanography. A suite of machine learning models, including regression, decision tree and deep learning approaches were developed to…

大气与海洋物理 · 物理学 2020-06-24 Stefan Wolff , Fearghal O'Donncha , Bei Chen

The growing adoption of machine learning (ML) in modelling atmospheric and oceanic processes offers a promising alternative to traditional numerical methods. It is essential to benchmark the performance of both ML and physics-informed ML…

大气与海洋物理 · 物理学 2024-12-02 Akshay Sunil , B Deepthi , Gaurav Ganjir , Muhammed Rashid , Rahul Sreedhar , Adarsh S

Tropical cyclone and sea surface temperature data have been used in several studies to forecast the total number of hurricanes in the Atlantic Basin. Sea surface temperature (SST) and latent heat flux (LHF) are correlated with tropical…

应用统计 · 统计学 2018-05-10 Marcela Alfaro Córdoba , Montserrat Fuentes , Joseph Guinness , Lian Xie

Traditionally, numerical models have been deployed in oceanography studies to simulate ocean dynamics by representing physical equations. However, many factors pertaining to ocean dynamics seem to be ill-defined. We argue that transferring…

机器学习 · 计算机科学 2023-05-03 Yuxin Meng , Feng Gao , Eric Rigall , Ran Dong , Junyu Dong , Qian Du

In this paper, we study the problem of forecasting the next year's number of Atlantic hurricanes, which is relevant in many fields of applications such as land-use planning, hazard mitigation, reinsurance and long-term weather derivative…

应用统计 · 统计学 2024-11-19 Pietro Colombo , Raffaele Mattera , Philipp Otto

The sea surface temperature (SST), a key environmental parameter, is crucial to optimizing production planning, making its accurate prediction a vital research topic. However, the inherent nonlinearity of the marine dynamic system presents…

机器学习 · 计算机科学 2025-04-25 Yin Wang , Chunlin Gong , Xiang Wu , Hanleran Zhang

We study the temporal correlations in the sea surface temperature (SST) fluctuations around the seasonal mean values in the Atlantic and Pacific oceans. We apply a method that systematically overcome possible trends in the data. We find…

统计力学 · 物理学 2009-11-07 Roberto A. Monetti , Shlomo Havlin , Armin Bunde

The rising number of extreme climate events in the past decades has motivated the need for a thorough consideration of tropical cyclone genesis and intensity, given the sea-surface temperature (SST). In this paper, we present an analysis of…

大气与海洋物理 · 物理学 2025-06-13 Jingyang Wu , Rohitash Chandra

We employ a statistical model of North Atlantic tropical cyclone (TC) tracks to investigate the relationship between sea-surface temperature (SST) and North American TC landfall rates. The track model is conditioned on summer SST in the…

大气与海洋物理 · 物理学 2008-01-08 Timothy Hall , Stephen Jewson

The spatial pattern of sea surface temperature (SST) plays a central role in shaping the climate system, yet the influence of land surface temperature (LST) remains poorly understood. Using a state-of-the-art coupled ocean--land--atmosphere…

大气与海洋物理 · 物理学 2026-04-07 Bosong Zhang , Timothy M. Merlis

This letter adopts long short-term memory(LSTM) to predict sea surface temperature(SST), which is the first attempt, to our knowledge, to use recurrent neural network to solve the problem of SST prediction, and to make one week and one…

计算机视觉与模式识别 · 计算机科学 2017-11-22 Qin Zhang , Hui Wang , Junyu Dong , Guoqiang Zhong , Xin Sun

Sea surface temperature (SST) is uniquely important to the Earth's atmosphere since its dynamics are a major force in shaping local and global climate and profoundly affect our ecosystems. Accurate forecasting of SST brings significant…

机器学习 · 计算机科学 2023-04-20 Xiaohan Li , Gaowei Zhang , Kai Huang , Zhaofeng He

Sea surface temperature (SST) is a fundamental physical parameter characterising the thermal state of sea surface. Due to the intricate thermal interactions between land, sea, and atmosphere, the spatial gradients of SST in coastal waters…

大气与海洋物理 · 物理学 2025-05-14 Yiqing Guo , Nagur Cherukuru , Eric Lehmann , Xiubin Qi , Mark Doubelld , S. L. Kesav Unnithan , Ming Feng

Sea surface temperature (SST) is a fundamental determinant of global climate dynamics and economic activity. Reliable projections of future SST patterns depend critically on a rigorous characterization of the underlying spatial random…

统计方法学 · 统计学 2026-05-07 Leonardo Marchesin , Alessandra Menafoglio , Piercesare Secchi
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