Short-term climate forecast method based on Kalman filtering and evolution modeling

Abstract

The invention discloses a short-term climate forecast method based on Kalman filtering and evolution modeling. The method comprises the following steps of: establishing a linear model about a forecast factor by the Kalman filtering at first; and simulating an error sequence approaching the Kalman filtering by using a non-linear ordinary differential equation math model on the basis of the linear model a, and performing error forecast. An evolution algorithm is an evolution process for simulating the nature by using a computer, in particular a calculation method for solving complicated problems by simulating biological evolution processes, and has the intelligent characteristics of self-adaptation, self-organization, self-learning, internal parallelism and the like. The two algorithms are combined with each other, so the natural characteristic of the climate can be simulated better than being simulated by a pure linear model, so the climate forecast precision is enhanced. By the method, short-term sunshine duration, temperature and rainfall can be forecast, so future knowledge of the short-term climate can be provided.

Description

technical field [0001] The invention belongs to a short-term climate prediction method, in particular to a short-term climate prediction method based on Kalman filtering and evolution modeling. This method can be used to solve short-term climate predictions that fluctuate greatly over time, such as sunshine hours and temperature, and is also suitable for long-term climate predictions. Background technique [0002] With the rapid development of my country's national economy, the country increasingly needs more accurate short-term climate prediction, especially in the departments of national planning, agriculture, water conservancy and disaster prevention and mitigation. Short-term climate prediction is a frontier topic in the field of international atmospheric science and earth science, and it is also an extremely difficult interdisciplinary problem. At present, short-term climate prediction mainly faces three major problems. First, there are many uncertain factors in climat...

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Problems solved by technology

At present, short-term climate prediction mainly faces three major problems. First, there are many uncertain factors in climate change. The time series of short-term climate data fluctuates too much, and its accurate model cannot be determined.

The second is that the prediction equations for short-term climate change are extremely complex, and how to correctly characterize the interaction between various factors mathematically and physically has not yet been fully resolved

Therefore, facing the difficulty of prediction theory, short-term climate prediction cannot follow the principles and methods of long-term climate prediction, and must develop new theories and methods in the face of the entire complex climate system and its changes, and its technical level is also affected by the development of other related disciplines Restrictions and limitations

The third is the lack of data and data. In order to reveal the macro and micro laws of short-term climate prediction, a large amount of historical data in this area is needed

At present, there are no public reports on short-term climate prediction based on Kalman filtering and evolution modeling

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