GB/T 44955-2024 in English
VALIDClimate prediction verification—El Nino/La Nina
- Issued on:2024-11-28
- Implemented on:2025-03-01
- File Format:PDF
- Delivery:Via email within 1~3 business days
$204.00
| Standard No: | GB/T 44955-2024 |
| Document status: | VALID |
| Title in English: | Climate prediction verification—El Nino/La Nina |
| Title in Chinese: | 气候预测检验 厄尔尼诺/拉尼娜 |
| Language: | English |
| File Format: | Electronic (PDF) |
| Delivery: | Via email within 1~3 business days |
| Issued on: | 2024-11-28 |
| Implemented on: | 2025-03-01 |
| ICS Classification: | 07.060-Geology. Meteorology. Hydrology |
| Chinese Classification: | A47-Meteorology |
| Professional Classification: | GB-National Standard |
| Related Keywords: | climate forecast verification el nino/la nina
climate prediction verification el nino/la nina introduction unified el nino/la nina index calculation standard national standard comparison el nino/la nina index including nino3.4 el nino/la nina phenomena |
| Related Topics: | Inno test
|
《GB/T 44955-2024气候预测检验 厄尔尼诺/拉尼娜》由TC540（全国气候与气候变化标准化技术委员会）归口，主管部门为中国气象局。
Introduction
1. Background and significance of the standard
GB/T 44955—2024 "Climate Forecast Verification El Nino/La Nina" is an important standard in my country's climate change field, aiming to improve the accuracy of climate forecasts and the level of operational application of El Nino/La Nina phenomena. The standard was jointly drafted by the National Climate Center and other authoritative institutions, combining years of research and practical experience.
2. Comparative analysis of standard frameworks
| Standard Dimensions | GB/T 44955—2024 | National Standard Comparison |
|---|---|---|
| El Nino/La Nina Index | Including NINO3.4, NINO3, NINO4 and other indicators | In line with international standards, supporting multi-dimensional monitoring |
| Historical Return Test | Using the Time Correlation Coefficient Indicator (TCC) | Introducing accuracy level classification (high, relatively high, relatively low, low) |
| Real-time Forecast Scoring | Relative Real-time Forecast Error (RPE) and Real-time Forecast Score (RPS) | Support dynamic adjustment of forecast accuracy assessment |
3. Standard Implementation Recommendations
Implementation Focus:
- Business departments should establish a unified El Nino/La Nina Index calculation standard to ensure data consistency.
- Scientific research institutions need to optimize forecast model parameters based on long-term observation data.
- It is recommended to adopt a standardized process to regularly evaluate the accuracy of inspection indicators (such as TCC and RPS).
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