Marine multi-element medium-and-long-term statistical prediction method based on empirical orthogonal function decomposition

Abstract

The invention discloses a marine multi-element medium-and-long-term statistical prediction method based on empirical orthogonal function decomposition. The method comprises the following steps of (1)based on the to-be-analyzed and predicted marine re-analysis data, constructing a marine statistical re-analysis sample matrix day by day over the years; (2) separating the seasonal signals and non-seasonal signals of various marine elements to obtain a marine re-analysis range sample matrix which is day-by-day over the years; (3) constructing a marine multi-element space-time four-dimensional orthogonal mode; (4) constructing a marine multi-element medium-and-long-term statistical prediction model; and (5) forecasting various marine elements by adopting the marine multi-element medium-and-long-term statistical prediction model constructed in the step (4). According to the invention, based on the marine re-analysis products with enough long-time sequences, the medium-and-long-term prediction method for the marine dynamic thermal environment is constructed through statistical rules, so that the marine prediction greatly improves the time efficiency of marine prediction on the basis of atraditional marine prediction mode, and a technical foundation is laid for effectively improving the safety guarantee level of the medium-and-long-term marine environment.

Description

technical field [0001] The present invention relates to marine element forecast technology, in particular to a medium- and long-term statistical forecasting method for ocean multi-element based on empirical orthogonal function (Empiricalorthogonal function, EOF) decomposition. The method of the invention is mainly applied to the forecasting of marine elements when the underwater mobile platform performs tasks, and makes forecasts with a time limit of 1 to 3 months for elements such as sea surface height and sea surface temperature. Background technique [0002] At present, marine environmental information such as seawater salinity, temperature, ocean current, and density required for marine environmental protection mainly depends on a large amount of historical data, based on statistical analysis or reanalysis, to obtain statistical analysis products of marine climate states or long-term oceanographic data. Reanalysis products, but such products are descriptions of the state...

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Problems solved by technology

[0003] When the underwater mobile platform performs its mission, it usually has to dive underwater for about 3 months. During this period, the protection of the marine environment mainly depends on the observation equipment it carries or the statistical analysis products of the marine climate state. For the sake of concealment, It is necessary to predict the marine environment information within a certain range around the underwater mobile platform in advance, but the observation equipment carried by the mobile platform itself can only observe the current marine environment information on the track, and the climatic products cannot provide future forecasts , so it is necessary for operational oceanography to provide marine numerical forecasting and forecasting results with a timeliness of about 1 to 3 months, as a support for marine environmental security

[0004] The current ocean prediction technology mainly relies on numerical models, but the model is limited by the longest forecast time limit of the corresponding meteorological driving field to only 10 days, and cannot provide numerical forecast products of more than 10 days

At the same time, the traditional marine numerical prediction model has great requirements in terms of parameter selection and computing platform

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