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A METHOD APPLICABLE TO THE ENSO FORECAST OF THE OCEAN-AIR COUPLING MODEL

An air-coupling, model technology, applied in weather forecasting, meteorology, alarms, etc., can solve problems affecting the initial value of the model and ENSO forecasting skills, so as to improve forecasting skills, improve forecasting skills, and reduce personnel and property losses. Effect

Active Publication Date: 2021-04-02
INST OF ATMOSPHERIC PHYSICS CHINESE ACADEMY SCI
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AI Technical Summary

Problems solved by technology

However, how the SST-nudging strength affects model initial values ​​and ENSO forecast skills is an unresolved problem so far

Method used

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  • A METHOD APPLICABLE TO THE ENSO FORECAST OF THE OCEAN-AIR COUPLING MODEL
  • A METHOD APPLICABLE TO THE ENSO FORECAST OF THE OCEAN-AIR COUPLING MODEL

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Embodiment 1

[0016] Such as figure 1 As shown, the present invention provides a method suitable for model forecasting ENSO, comprising the following steps,

[0017] S1. Obtain at least 5 initialization parameters by changing the initialization parameter SST-nudging strength value;

[0018] S2. For each initialization parameter, a set of first initial value sets consisting of at least 10 initial values ​​is generated, and a total of five sets of first initial value sets and at least 50 initial values ​​are obtained;

[0019] S3. Select at least one initial value from each set of first initial values ​​to form a second initial value set consisting of at least 10 initial values, and obtain a forecast result of the second initial value set;

[0020] S4. Count the forecast results corresponding to the second initial value set, that is, obtain the final forecast result.

[0021] In this embodiment, in step S1, the number of initialization parameters can be set according to the actual situation...

Embodiment 2

[0025] Such as figure 2 As shown, a specific example is provided in this embodiment to illustrate the use of this method:

[0026] Time period: 1981-2010

[0027] Forecast object: ENSO (Nino3.4 index)

[0028] The optimized random selection scheme is as follows: from 5 groups of first initial value sets each with 10 initial values, each group of first initial value sets randomly selects 2 initial values, a total of 10 initial values, and compares their corresponding From 1981 to 2010, the forecast results of 1-12 months in advance are ensemble averaged to obtain the ensemble forecast results.

[0029] In order to verify the significance of the scheme, we use the Monte Carlo method to do the significance test. The specific operation is as follows: use the above method to randomly select 20,000 sets of initial values, and obtain the corresponding 20,000 sets of forecast results, and use the set The predicted Nino3.4 index and the Nino3.4 index of the sea temperature observat...

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Abstract

The invention discloses a method suitable for model forecasting of ENSO. The method comprises the steps of: S1, changing the numerical value of an initialization parameter, namely the SST-nudging intensity, so that at least five initialization parameters are obtained; S2, generating a first initial value set at least composed of ten initial values by each initialization parameter, and totally obtaining five first initial value sets and at least fifty initial values; S3, respectively and at least selecting an initial value from each first initial value set, so that a second initial value set atleast composed of ten initial values is formed, and obtaining a forecasting result of the second initial value set; and S4, counting the forecasting result corresponding to the second initial value set, so that the final forecasting result is obtained. The method in the invention has the advantages that: the model ENSO forecasting skill is improved; the forecasting bottleneck of the original scheme is broken through; the model forecasting skill is easily improved; simultaneously, the ENSO forecasting skill of a global sea-air coupling model is improved; forecasting and early warning of a climatic disaster can be easily realized; and thus, personnel and property loss can be reduced.

Description

technical field [0001] The invention relates to the field of ENSO forecasting, in particular to a method suitable for model forecasting ENSO. Background technique [0002] The El Niño-Southern Oscillation (ENSO) has a major impact on the global climate and can cause severe flooding. Therefore, improving ENSO forecasting skills is beneficial to disaster prevention and mitigation for all countries. In existing technical schemes, the intensity of SST-nudging (sea surface temperature forcing scheme) is generally set to a fixed value to generate an initial value closer to the observed data. However, the observation data in the initialization process is generally the reanalysis data generated by the real data after a series of assimilation simulation processing, which is not completely equivalent to the actual situation. Ultimately, even if the initial value is the closest to the observed data, it will cause the instability of the forecasting system. This makes the technical bo...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08B31/00G08B21/10G01W1/10
CPCG01W1/10G08B21/10G08B31/00
Inventor 黄平王妍凤王磊王鹏飞张志华严邦良
Owner INST OF ATMOSPHERIC PHYSICS CHINESE ACADEMY SCI
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