Seawater temperature field prediction method based on improved EOF

Abstract

The invention relates to a seawater temperature field prediction method based on improved EOF, and the seawater temperature field prediction method comprises the following steps: reconstructing historical data; extracting geographic information of the current sea area to form a mask file; obtaining spatial change characteristic parameters through spatial-temporal orthogonal empirical decomposition; fitting a time coefficient; forecasting the temperature in the future N days; and performing regional temperature field reconstruction. According to the seawater temperature field prediction method,on the basis of a traditional spatio-temporal empirical orthogonal decomposition method, ocean elements are reconstructed in time and space, and a good prediction result is obtained. Through multipleverifications, the seawater temperature field prediction method can achieve the long-time prediction of the temperature field. In engineering application, computing resources are saved, and practicability is high, and future ocean temperature forecasting information can be provided for ship navigation and other offshore platforms.

Description

technical field [0001] The invention relates to the field of marine environment protection research, based on historical data, using statistics and probability theory methods, to realize the statistical analysis and forecasting method of marine element forecasting. [0002] Use historical data to find out the relationship between historical data and current data, and then realize the statistical analysis and forecasting method of ocean element forecasting, and predict the temperature information of the target sea area in the next few days. This algorithm has high precision, long forecast time, and wide coverage of the effective area, which can provide future seawater temperature information for marine security. Background technique [0003] Ocean elements are variables that vary significantly in time and space. Using the definition of principal components, we can use the interrelationships among multiple variables to construct a few new variables that can not only comprehen...

AI Technical Summary

Problems solved by technology

[0004] The temperature forecast technology represented by numerical forecast has high precision and the physical model is relatively mature. However, with the increase of the forecast period, the forecast ability drops sharply. The reliability of the forecast results after 7 days is low, and the deviation from the actual situation is large.

Images