QX/T 370-2017 in English
VALIDIdentification method for El Ni?o/La Ni?a events
- Issued on:2017-02-10
- Implemented on:2017-03-15
- File Format:PDF
- Delivery:Via email within 1~3 business days
$369.00
| Standard No: | QX/T 370-2017 |
| Document status: | VALID |
| Title in English: | Identification method for El Ni?o/La Ni?a events |
| Title in Chinese: | 厄尔尼诺/拉尼娜事件判别方法 |
| Language: | English |
| File Format: | Electronic (PDF) |
| Delivery: | Via email within 1~3 business days |
| Issued on: | 2017-02-10 |
| Implemented on: | 2017-03-15 |
| ICS Classification: | 07.060-Geology. Meteorology. Hydrology |
| Chinese Classification: | A47-Meteorology |
| Professional Classification: | QX-Meteorology |
| Related Topics: | event
you Ni Helnia promise Na Lin Brno double discriminant method Secondary discriminant method 2. Discrimination method secondary discrimination Hena Helium + Na distinguish La Niña event El Nino Discriminant analysis QX la nina sentence Neil Neil Nila El Niño event El Niño event event x squared civil trial Knoll ring test Aperture identification method Knoll Ring Stretch How to identify gross errors How to identify gross errors Discriminant response graph fitting method |
Introduction
Background and significance of the standard
QX/T 370-2017 is the first unified El Niño/La Niña event discrimination standard in my country's meteorological industry, compiled by the National Climate Center and a number of climate experts. The introduction of this standard fills the domestic regulatory gap in this field. Its technical points include:
- Using the NINO3.4 area Sea Surface Temperature Anomaly (SSTA) as the core indicator
- Clearly define the event intensity level (weak/moderate/strong/super strong)
- For the first time, distinguish between eastern type and central type events
Core discrimination indicator system
| Index name | Monitoring area | Calculation formula | Discrimination threshold |
|---|---|---|---|
| NINO3.4 index | 170°W-120°W,5°S-5°N | Regional SSTA average | ≥0.5℃（El Nino）≤-0.5℃（La Nina） |
| Eastern Type Index | NINO3 Area | TNINO3-αTNINO4 | Continued ≥3 months and ≥0.5℃ |
| Central Type Index | NINO4 Area | TNINO4-βTNINO3 | Continued ≥3 months and ≥0.5℃ |
Event characteristic quantification standard
Intensity classification standard
The peak intensity of the 3-month moving average NINO3.4 index is used as the basis for judgment:
- Weak event: 0.5-1.3℃ (equivalent to 1.5 times the standard deviation)
- Moderate event: 1.3-2.0℃
- Strong event: 2.0-2.5℃
- Super strong event: ≥2.5℃ (such as the 1997/1998 event)
Duration requirement
The threshold must be met for 5 consecutive months or more, among which:
- Starting month: the month when the standard is first met
- End month: the last month that meets the standard
- Total number of months: the cumulative value between the start and end months
Analysis of historical event characteristics
Appendix A of the standard provides detailed statistics of 35 typical events from 1950 to 2016:
- Super El Niño: events in 1982/83, 1997/98, and 2015/16
- Longest La Niña: lasted 24 months in 1998/2000
- Type change: the event changed from central type to eastern type in 2009/10
Business application suggestions
- Data source selection: HadISST data was used before 1982, and OIv2 data is recommended thereafter
- Real-time monitoring: 3-month sliding average should be calculated to eliminate seasonal fluctuations
- Type determination: Both the eastern and central types need to be calculated
- Intensity prediction: Refer to the development patterns of similar historical events
Loading PDF document...
Error loading PDF. Please make sure the file is valid and try again.
We also recommend
-
QX/T 705-2023 in English
Technical Specifications for Division of Lightning-prone Areas
2023-12-30 -
QX/T 712-2024 in English
Climate Change Impact Assessment Food Crop Yield Vulnerability
2024-06-20 -
QX/T 333-2016 in English
Ship pilotage meteorological conditions level
2016-09-29 -
QX/T 214-2025 in English
Greenhouse Gas Sampling Methods for Stainless Steel Tanks
2025-05-19 -
QX/T 41-2022 in English
air quality forecast
2022-01-07
