河西走廊东部强降温气候特征及预报方法研究

doi:10.11924/j.issn.1000-6850.casb18120061

摘要/Abstract

摘要：

利用河西走廊东部1961—2010年5个气象站强降温资料[24 (48) h最低气温下降≥8 (10)℃、最低气温降至≤4℃],采用统计学方法系统分析了该区域强降温的时空分布、强度等气候特征,结果表明：河西走廊东部强降温次数海拔较高的山区和北部沙漠边缘明显多于绿洲平原区。年代、年强降温次数总体呈减少趋势,强降温主要发生在1—5月和9—12月,强降温次数4月最多。各强度强降温次数的变率较大,随着降温强度的增大,强降温次数迅速减少,24 h强降温强度总体呈弱减小趋势,48 h强降温强度总体呈弱增加趋势。利用2004—2013年1—5月和9—12月逐日20时ECMWF数值预报格点场资料,运用Press准则和逐步回归方法进行预报因子初选和因子精选,使用最优子集回归建立各地月最低气温预报方程,采用CSC双评分准则确定了全局最优的最低气温预报方程,预报方程通过了α=0.01显著性水平检验。采用最大靠近原则确定强降温预报的临界值和预报级别。预报拟合率24、48 h分别为80.0%~83.3%、81.3%~86.2%,预报准确率24、48 h分别为71.4%~75.0%、73.3%~77.1%,达到了较高的拟合和预报水平,可为强降温预报和预警提供客观有效的指导产品。

关键词: 强降温, 气候特征, ECMWF, 数值预报

Abstract:

Using strong cooling data [the lowest temperature decline rate of 24 (48) h was ≥8 (10)℃ and the lowest temperature was ≤4℃] of five meteorological stations in eastern Hexi corridor during 1961 to 2010, climatic characteristics of temporal and spatial distribution and intensity of strong cooling were analyzed systematically by statistical methods. The results showed that strong cooling times were more obvious in high elevation mountainous and northern desert edge than that in oasis plain area. Strong cooling times of age and year had an overall reducing tendency. Strong cooling weather occurred mainly from January to May and from September to December, mostly in April. The variable rate of strong cooling times of each strength was relatively large, and strong cooling times reduced rapidly with the cooling intensity increased. The strong cooling intensity of 24 h showed an overall weak reducing tendency, and that of 48 h showed a weak increasing tendency. Selecting ECMWF numerical forecast grid field data at 20:00 day by day from January to May and from September to December during 2004 to 2013, forecast factors were selected initially and precisely by Press criterion and stepwise regression method. The monthly lowest temperature forecast equations of each region were built with optimal subset regression, and the overall situation and optimal forecast equations were determined finally with the CSC double grading criterion. The forecast equations passed significance level examination of α=0.01. Forecast marginal value and forecast rank of strong cooling were determined with the biggest approaches principle. Forecast fitting rate of 24 and 48 h was 80.0%-83.3% and 81.3%-86.2%, respectively, and the forecast accuracy rate of 24 and 48 h was 71.4%-75.0% and 73.3%-77.1%, respectively, reaching high fitting and forecast level, and could provide objective and effective guiding products for strong cooling forecast and early warning.

Key words: strong cooling, climate characteristics, ECMWF, numerical forecast

中图分类号:

P466

张金秀, 杨晓玲, 孙占峰, 彭祥荣. 河西走廊东部强降温气候特征及预报方法研究[J]. 中国农学通报, 2020, 36(10): 114-121.

Jinxiu Zhang, Xiaoling Yang, Zhanfeng Sun, Xiangrong Peng. Climatic Characteristics and Forecast Method of Strong Cooling in Eastern Hexi Corridor[J]. Chinese Agricultural Science Bulletin, 2020, 36(10): 114-121.

图/表 9

参考文献 22

[1]	朱乾根,林锦瑞,寿绍文,等.天气学原理和方法(第四版)[M].北京:气象出版社,2007:266-296.
[2]	罗晓玲,郭良才,兰晓波.河西走廊春季强冻害成因及防御对策[J].新疆气象,2006,29(3):20-21.
[3]	高凤荣,王锡稳,冀兰芝,等.西北区东部寒潮天气短期预报[J].甘肃气象,1996,14(3):3-7.
[4]	朴春兰. 寒潮特征和短期预报方法[J].黑龙江气象,2005(2):4-5.
[5]	钱莉,杨晓玲,丁文魁.一次区域性冻害天气的成因分析[J].干旱气象,2005,23(2):39-43.
[6]	伍东亮,蒋运志,夏小曼.2008年初我国南方低温雨雪冰冻灾害的回顾与反思[J].农技服务,2008,25(10):159-160.
[7]	王遵娅,张强,陈峪,等.2008年初我国低温雨雪冰冻灾害的气候特征[J].气候变化研究进展,2008,4(2):63-67.
[8]	周鸣盛,张廷.一次雪面降温引起的异常寒冷天气分析[J].气象学报,1997,55(2):219-229.
[9]	许爱华,乔林,詹丰兴,等.2005年3月一次寒潮天气过程的诊断分析[J].气象,2006,32(3):49-55.
[10]	杨宝玲,郑鹏徽,顾宁,等.宁夏石嘴山一次强寒潮天气诊断分析[J].宁夏工程技术,2009,8(4):310-312,316.
[11]	孟祥君,吴正方,杜海波,等.1961—2010年东北地区寒潮活动的时空特征分析[J].干旱区资源与环境,2013,27(1):142-147.
[12]	梁旭,丁建军,曹宁.宁夏自然灾害综合分区及多尺度特征分析[J].干旱区资源与环境,2011,25(4):62-68.
[13]	白肇烨,许国昌,孙学筠,等.中国西北天气[M].北京:气象出版社,1988:161.
[14]	马玉芬,张广兴,杨莲梅.天山地形对新疆大风和降温天气作用的数值模拟研究[J].干旱区资源与环境,2012,26(5):113-118.
[15]	中国气象局科教司编.省地气象台短期预报岗位培训教材[M].北京:气象出版社,1998:75-111.
[16]	裴洪芹,邰庆国,吴君,等.临沂中尺度数值预报系统及应用[J].气象科技,2007,35(4):464-469.
[17]	陈百炼. 降水温度分县客观预报方法研究[J].气象,2003,29(8):48-51.
[18]	牛叔超,朱桂林,李燕,等.T106产品夏季降水概率预报自动化系统[J].气象,2000,26(3):37-39.
[19]	俞善贤. 一个着眼于预测能力及稳定性的因子普查方法[J].气象,1991,17(9):40-43.
[20]	谷湘潜,李燕,陈勇,等.省地气象台精细化天气预报系统[J].气象科技,2007,35(2):166-170.
[21]	俞善贤,汪锋.试用最优子集与岭迹分析相结合的方法确定回归方程[J].大气科学,1998,12(4):382-388.
[22]	张万诚,郑建萌,解明恩.最优子集回归模型在低纬高原雨季开始期预报中的应用试验[J].气象,2000,26(11):24-27.

时段	24 h					48 h
时段	永昌	凉州	民勤	古浪	天祝	永昌	凉州	民勤	古浪	天祝
20世纪60年代	-1.2	1.8	29.2	4.4	-4.0	2.2	1.2	6.8	9.0	-2.6
20世纪70年代	2.8	7.8	1.2	2.4	7.0	0.2	0.2	5.8	1.0	4.4
20世纪80年代	-0.2	-4.2	-8.8	-8.6	1.0	-2.8	-4.8	-8.2	-10.0	2.4
20世纪90年代	3.8	2.8	-9.8	-3.6	-2.0	3.2	0.2	-1.2	-12.0	-5.6
21世纪00年代	-5.2	-8.2	-11.8	5.4	-2.0	-2.8	3.2	-3.2	12.0	1.4

时段	24 h					48 h
时段	永昌	凉州	民勤	古浪	天祝	永昌	凉州	民勤	古浪	天祝
20世纪60年代	-1.2	1.8	29.2	4.4	-4.0	2.2	1.2	6.8	9.0	-2.6
20世纪70年代	2.8	7.8	1.2	2.4	7.0	0.2	0.2	5.8	1.0	4.4
20世纪80年代	-0.2	-4.2	-8.8	-8.6	1.0	-2.8	-4.8	-8.2	-10.0	2.4
20世纪90年代	3.8	2.8	-9.8	-3.6	-2.0	3.2	0.2	-1.2	-12.0	-5.6
21世纪00年代	-5.2	-8.2	-11.8	5.4	-2.0	-2.8	3.2	-3.2	12.0	1.4

项目		永昌	凉州	民勤	古浪	天祝
24 h	倾向率/(次/10 a)	-0.084	-0.272	-0.947	-0.032	-0.036
24 h	趋势系数	-0.071	-0.270	-0.536	-0.034	-0.043
48 h	倾向率/(次/10 a)	-0.092	0.057	-0.205	-0.016	-0.003
48 h	趋势系数	-0.093	0.062	-0.149	-0.010	-0.002

项目		永昌	凉州	民勤	古浪	天祝
24 h	倾向率/(次/10 a)	-0.084	-0.272	-0.947	-0.032	-0.036
24 h	趋势系数	-0.071	-0.270	-0.536	-0.034	-0.043
48 h	倾向率/(次/10 a)	-0.092	0.057	-0.205	-0.016	-0.003
48 h	趋势系数	-0.093	0.062	-0.149	-0.010	-0.002

站点	24 h			48 h
站点	8℃≤△T₂₄<10℃	10℃≤△T₂₄<12℃	△T₂₄≥12℃	10℃≤△T₄₈<12℃	12℃≤△T₄₈<14℃	△T₄₈≥14℃
永昌	112	21	3	78	24	12
凉州	72	14	10	58	23	13
民勤	143	34	7	96	43	12
古浪	84	26	8	102	43	20
天祝	79	23	8	102	33	18