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Spatial and Temporal Distributions of Probability Classification of Precipitation and Temperature Anomalies over China
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摘要: 采用全国160站1951—2009年月降水和气温资料，分析了短期气候预测业务评分办法中六级要素概率时空分布特征，并以1月、7月为代表获得了不同地区、不同级别降水和气温异常发生频率。结果表明：降水和气温的六级异常分布存在显着空间不均匀性和年代际变化特征，1980—2009年，北方降水在1月出现特少、特多等级和7月出现特少、偏少等级的概率较大，南方降水出现6个等级的概率基本相同；全国气温在1月和7月出现正常略低、正常略高和偏高等级的概率较大。1980—2009年与1951—1979年相比，全国1月降水为特多、偏多等级和7月降水为偏少等级的站数明显增加，全国1月气温为正常略高、偏高和特高等级的站数明显增加，呈明显的年代际变化特征。Abstract: Based on the standard of the probability classification definition and scoring method in short term climate prediction operation, analysis is conducted on six-level probability classification of monthly precipitation and temperature anomalies in January and July. Spatial and temporal distributions are obtained through the monthly precipitation and temperature data at 160 stations in China, which are operationally used by National Climate Center of CMA. The six levels are defined as much more than normal (L1), moderately more than normal (L2), slightly more than normal (L3), slightly less than normal (L4), moderately less than normal (L5), much less than normal (L6).The results indicate that the issued six-level probability classification is suitable for symmetrical distribution cases for positive and negative anomalies but neglecting spatial inhomogeneous distributions and inter-decadal variations of monthly temperature and precipitation. During the period of 1980—2009, the probability of L1 and L6 for precipitation in North China is high in January whereas that of L6 and L5 is elevated in South China in July. The six-level probability for precipitation in January and July is generally similar in South China. The probability of L4, L3, and L2 temperature is high whereas that of L6, L5, and L1 is low for temperature in China in both January and July. Compared to those in the period of 1951—1979, the station numbers of L1 and L2 in January and L5 for precipitation in July have significantly increased but those of L6 precipitation in January and L6 and L4 for precipitation in July have remarkably decreased in the period of 1980—2009. Meanwhile, the station numbers of L4, L5, L6 for temperature in January have substantially decreased but those of L1, L2, L3 for temperature in January increases significantly and the six-level temperature probability in July shows no variability since 1980.The above results could provide an important reference for climate forecasters to fully consider inter-decadal, inter-annual and inter-seasonal variability. The standard of the scoring method for the climate prediction focuses on the accurate rate of classification prediction, and especially emphasizes the abnormal level of precipitation and temperature. Therefore, the scoring method will help promote climate prediction services. The six-level scoring method for precipitation is more reasonable, while for temperature the method needs appropriate improvements.
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图 1 1980—2009年1月和7月我国降水距平百分率的均方差 (单位：%)
Fig. 1 The standard deviation of precipitation percentage anomalies in China in January and July from 1980 to 2009(unit:%)
图 2 1980—2009年1月我国降水六级概率分布 (单位：%)
(阴影区表示概率分布超过20%的区域)
Fig. 2 Distributions of the six-level probability of precipitation anomalies in January from 1980 to 2009(unit:%)
(the shaded area denotes the probability over 20%)
图 4 1980—2009年1月和7月全国气温均方差 (单位：℃)
Fig. 4 The standard deviation of temperature in China in January and July from 1980 to 2009(unit:℃)
图 7 1月和7月的降水与气温六级概率大于25%的站数
Fig. 7 The number of stations where the six-level probability of precipitation and temperature anomalies greater than 25% in January and July
图 8 1980—2009年与1951—1979年全国降水概率的差值分布 (单位：%)
(阴影区表示达到0.1显着性水平)
Fig. 8 Precipitation probability anomalies between the periods of 1980—2009 and 1951—1979(unit:%)
(the shaded area denotes passing the test of 0.1 level)
图 9 1980—2009年与1951—1979年全国气温概率的差值分布 (单位：%)
(阴影区表示达到0.1显着性水平)
Fig. 9 Temperature probability differences between the periods of 1980—2009 and 1951—1979(unit:%)
(the shaded area shows passing the test of 0.1 level)
表 1 降水和气温趋势预测六级评分制用语及等级划分标准
Table 1 The terminology of six-level scoring method and the classification standards of each level for precipitation and temperature prediction
预测用语 ΔR/% ΔT/℃ 特少 (特低) ΔR≤-50 ΔT≤-2.0 偏少 (偏低) -50＜ΔR≤-20 -2.0＜ΔT≤-1.0 正常略少 (正常略低) -20＜ΔR＜0 -1.0＜ΔT＜0 正常略多 (正常略高) 0≤ΔR＜20 0≤ΔT＜1.0 偏多 (偏高) 20≤ΔR＜50 1.0≤ΔT＜2.0 特多 (特高) 50≤ΔR 2.0≤ΔT 注：ΔR为降水距平百分率; ΔT为气温距平。 
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表 2 单站降水和气温趋势预测六级评分制评分表
Table 2 The six-level scoring method for precipitation and temperature predictions at one station
实况 预测 特少 (特低) 偏少 (偏低) 正常略少 (正常略低) 正常略多 (正常略高) 偏多 (偏高) 特多 (特高) 特少 (特低) 100 80+10 60 20 0 0 偏少 (偏低) 80+10 100 80 40 20 0 正常略少 (正常略低) 60 80+10 100 60 40 20 正常略多 (正常略高) 20 40 60 100 80+10 60 偏多 (偏高) 0 20 40 80 100 80+10 特多 (特高) 0 0 20 60 80+10 100
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