Sea surface temperature (SST) prediction plays an important role in planning marine operations and forecasting climate. With the rapid development of remote sensing technology, there are plenty of SST data available for scientific research. However, most previous studies ignored the quality of SST ...
where the predicted sea surface temperature is lower than the observed data. The prediction error is mainly caused by the ConvLSTM model and the land mask. In our implementations, the land mask is applied to the study area. The ConvLSTM exploits the spatial and temporal features of the...
C. Sea Surface Temperature Prediction Lins et al. [24] investigated SST in tropical Atlantic using an SVM. Patil et al. [25] adopted an artificial neural network to predict the sea surface temperature. It performs well only in the case of forecasting with the lead time from 1 to 5 days...
Sea surface temperature (SST) prediction has widespread applications in the field of marine ecology, fisheries, sports and climate change studies. At present, the real-time SST forecasts are made by numerical models which are categorically based on physics-based assumptions subjected to boundary and ...
今天找到了一篇比较早的论文看,内容是利用长短期记忆对海水温度进行预测。现在就按照论文的顺序对于这篇论文做一下自己的总结笔记。 论文首先对其所用的LSTM模型进行了介绍,提出了一种LSTM+全连接层的网络结构,成功的实现了对海水温度的预测,其中主要分两个layer。一个是LSTM layer,一个是全连接layer。
Nonseasonal variability of sea level pressure (SLP) and sea surface temperature (SST) in the mid-latitude North Pacific Ocean is examined. The objective is examination of the basic scales of the variability and determination of possible causal connections which might allow prediction of short-term ...
Relationship Between Cyclone Intensities and Sea Surface Temperature in the Tropical Indian Ocean In most cyclone prediction models, sea surface temperature (SST) is the only oceanographic input, even though storms are known to be impacted by the therma... MM Ali,D Swain,T Kashyap,... - 《IEE...
There is strong evidence that Indian Ocean sea surface temperatures (SSTs) influence the climate variability of Southern Asia and Africa; hence, accurate prediction of these SSTs is a high priority. In this study, we use canonical correlation analysis (CCA) to design empirical models to assess th...
A stochastic model of IndoPacific sea surface temperature anomalies An "inversemodeling" approach is used. That is, the relevant parameters of the best-fit stable linear process are obtained from observations and, given ... Cécile,Penland - 《Physica D Nonlinear Phenomena》 被引量: 302发表: ...
North Atlantic sea surface temperature exhibits high decadal predictability potential.Model bias hinders exploiting the decadal predictability potential.An innovative method was developed to overcome some of the bias problem.North Atlantic sea surface temperature will stay anomalously warm until about 2030.关...