Technical specifications for meteorological disaster risk assessment—Hail

Standard number: QX/T 511-2019
Standard name: Technical specifications for meteorological disaster risk assessment
--Hail English name: Technical specifications for meteorological disaster risk assessment--Hail ||
tt||Standard format: PDF
Release time: 2019-12-26
Implementation time: 2020-04-01
Standard size: 0.98M
Standard introduction: This standard specifies the data collection, processing and assessment methods for hail disaster risk assessment.
This standard is applicable to hail disaster risk assessment. This standard was drafted in accordance with the rules given in GB/T1.1-2009
This standard was proposed and managed by the National Technical Committee for Meteorological Disaster Prevention and Mitigation (SAC/TC345).
This standard was drafted by: Anhui Provincial Climate Center, National Climate Center. The main drafters of this standard are: Tian Hong, Tang Wei'an, Gao Ge, Lu Yanyu, Xie Wusan.
This standard specifies the data collection, processing and assessment methods for hail disaster risk assessment. This standard is applicable to hail disaster risk assessment.

ICS07.060
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Meteorological Industry Standard of the People's Republic of Chinabzxz.net
QX/T511—2019
Technical specifications for meteorological disaster risk assessment
Assessment-Hail Industry Standard Information Service Platform
Released on 2019-12-26
China Meteorological Administration
Implemented on 2020-04-01
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Industry Standard Information Service Platform
2 Terms and Definitions
Data Collection and Processing
Assessment Method
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Appendix A (Informative Appendix)
Appendix B (Informative Appendix)
Appendix C (Informative Appendix)
Appendix D (Informative Appendix)
References
Normalization Processing·
Pearson Correlation Coefficient
Regression Coefficient Determination Method
Percentile Method
QX/T 511—2019
Industry Standard Information Service Platform
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Industry Standard Information Service Platform
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This standard was drafted in accordance with the rules given in GB/T1.1—2009. This standard was proposed and managed by the National Technical Committee for Standardization of Meteorological Disaster Prevention and Mitigation (SAC/TC345). Drafting units of this standard: Anhui Provincial Climate Center, National Climate Center The main drafters of this standard: Tian Hong, Tang Wei'an, Gao Ge, Lu Yanyu, Xie Wusan. QX/T511-2019
Industry Standard Information Service Platform
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Industry Standard Information Service Platform
1 Scope
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Technical Specifications for Meteorological Disaster Risk Assessment
This standard specifies the data collection, processing and assessment methods for ice disaster risk assessment. This standard applies to ice disaster risk assessment. 2 Terms and Definitions
The following terms and definitions apply to this document. 2.1
Ice and snow hail
Hard spherical, conical or irregular solid precipitation. [GB/T27957—2011. Definition 2.1]
Maximum ice mine diameter diameter of the maximum hail The maximum diameter of the maximum ice observed during a single drop. 2.3
Duration of hailfallDuration of hailfallThe duration from the beginning to the end of hailfall.
Extreme wind speed during hailfall
The maximum instantaneous wind speed during hailfall. 2.5
Ice and snow disaster factor mnail hazard
QX/T511—2019
Standard
The natural abnormal factors causing ice disasters, mostly referring to the maximum ice diameter, duration of hailfall, and maximum wind speed during hailfall.
Disaster loss index
Disaster loss index
Hui Service Platform
The ratio of the economic losses caused by hailfall disasters in the assessment area to the gross domestic product (GDP) of the region in that year. 2.7
Risk index
riskindex
Quantitative assessment indicators for the expected losses of ice disasters. 3 Data collection and processing
3.1 Data collection
General requirements
Collect no less than 30 samples with the following four elements: maximum ice mine diameter (in millimeters (mm), integer), duration of fall1
QX/T511—2019
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(in minutes (min), integer), maximum wind speed during fall (in meters/second (m/s), one decimal place) and direct economic loss (in 10,000 yuan, one decimal place). 3.1.2 Meteorological data
Earn records of ice bracts in the ground meteorological monthly reports, meteorological disaster yearbooks, meteorological chronicles, local chronicles and related literature since the establishment of the meteorological station in the assessment area, including maximum ice bract diameter, duration of fall and maximum wind speed during fall. 3.1.3 Economic Development Data
GDP of cities, counties (districts) over the years released by government departments, in units of 10,000 yuan. 3.1.4 Disaster Data
Direct economic losses of wind disasters with ice and electricity processes released by government departments. 3.2 Data Processing
3.2.1 Quantitative Conversion of Ice and Electricity Records
Convert the qualitative description of the maximum ice bract diameter in the historical records into quantitative data. The conversion basis is shown in Table 1. Conversion table of maximum ice mine diameter
Unit is millimeter (mm)
Qualitative description of maximum ice bract
Table tennis
Quail egg
Peanut
Normalization
Conversion diameter
Normalize the maximum ice diameter, duration of power drop, and maximum wind speed during power drop. See Appendix A3.2.3 for the method. Determination of disaster loss index
The direct economic loss caused by an ice bract disaster in the assessment area is divided by the GDP of the medical or medical area in that year to obtain the disaster loss index (Formula (1)): Platform
Where:
Disaster loss index;|| tt||Direct economic loss, in ten thousand yuan;
GDP of the year, in ten thousand yuan,
...(1)
4 Evaluation method
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4.1.1 Identification of ice mold disaster factors
QX/T511—2019
The Pearson correlation coefficient calculation method is used to calculate the correlation coefficients between the loss index and the normalized maximum ice diameter, duration of power drop, and maximum wind speed during power drop, and the factors that pass the significance test (α=0.05) are selected as the ice mold disaster factors. For the calculation method of Pearson correlation coefficient, see Appendix B. 4.1.2 Construction of risk assessment model
The ice-electric disaster risk assessment model is constructed according to formula (2): bh
Where:
Risk index:
The number of identified disaster factors;
The normalized value of the th disaster factor;
Regression coefficient, the determination method is shown in Appendix C. Complete construction of risk index sequence
For cases with only ice but no disaster in historical records, the risk index (1) is estimated using formula (2), and the existing disaster loss index (I) is regarded as the risk index (1), and the two constitute a complete risk index sequence. 4.1.4 Risk level classification
Based on the risk index sequence completely constructed in 4.1.3, the "percentile method" (see Appendix D) is used to divide the ice disaster risk into four levels: transition, moderate, severe and extremely severe (Table 2), and the corresponding risk index threshold is calculated according to the percentile interval. Every 5 years, new data should be added to the sequence and the risk index threshold should be recalculated. Table 2 Ice and mine disaster risk level
Risk index percentile (R) interval
Risk level
4.1.5 Determination of risk assessment results
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