WQSRTP方法在甘肃省高低温客观预报中的应用

doi:10.13866/j.azr.2023.07.03

摘要/Abstract

摘要：

基于ECMWF细网格数值预报产品和国家级考核站气温观测数据，采用加权准对称滑动训练期方法（WQSRTP）生成甘肃省智能网格最高（低）客观产品，检验该产品的预报效果，将其与中国气象局智能网格指导预报产品（SCMOC）、甘肃省城镇网格预报产品（SPCC）进行对比。结果表明：WQSRTP订正方法能够显著改善ECMWF细网格数值模式24 h最高（低）气温的预报能力，24 h最高、最低气温预报准确率分别提升了32.16%、15.48%；WQSRTP订正产品相对于SCMOC、SPCC和ECMWF最高（低）气温产品均为正订正技巧，且最高气温订正能力优于最低气温订正能力。空间误差检验来看，WQSRTP订正方法可有效提升祁连山区和甘岷山区等地形复杂地区的最高（低）气温预报准确率，显著降低了平均绝对误差。

关键词: 高低温预报, 订正技巧, 准确率, 甘肃

Abstract:

Based on the ECMWF fine grid numerical prediction product and the temperature observation data of the national assessment station, the weighted quasi-symmetric running training period method (WQSRTP) was used to generate the maximum (low) objective product of the smart grid in Gansu Province. The results were compared with the smart grid guidance forecast product (SCMOC) of China Meteorological Administration and the urban grid forecast product (SPCC) of Gansu Province. The results show that the WQSRTP correction method can significantly improve the ability to predict the 24 h maximum (low) temperature of the ECMWF fine grid numerical model, and the predictive accuracy of the 24 h maximum and minimum temperatures increased by 32.16% and 15.48%, respectively. Compared with SCMOC, SPCC, and ECMWF, the modified WQSRTP products are positive correction techniques, and the modified ability of maximum temperature is better than that of minimum temperature. According to the spatial error test, the WQSRTP correction method can effectively improve the accuracy of maximum (low) temperature forecast in the Qilian Mountains and the Southwest Mountains, and significantly reduce the mean absolute error. Moreover, the effect of correction for predicting the maximum temperature is better than that of minimum temperature.

Key words: high and low temperature forecast, correction skills, accuracy rate, Gansu

王基鑫, 黎倩, 栗晗, 张君霞, 刘新雨. WQSRTP方法在甘肃省高低温客观预报中的应用[J]. 干旱区研究, 2023, 40(7): 1052-1064.

WANG Jixin, LI Qian, LI Han, ZHANG Junxia, LIU Xinyu. Application of WQSRTP method in objective forecast of high and low temperature in Gansu Province[J]. Arid Zone Research, 2023, 40(7): 1052-1064.

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预报时效/h	预报产品	最高气温				最低气温
预报时效/h	预报产品	准确率/%	MAE/℃	RMSE/℃		准确率/%	MAE/℃	RMSE/℃
24	SCMOC	52.64	2.50	3.36		54.61	2.29	2.99
	SPCC	47.24	2.87	3.78		55.86	2.27	2.99
	ECMWF	40.60	3.31	4.26		53.89	2.42	3.19
	WQSRTP	72.76	1.53	1.99		69.37	1.62	2.10
48	SCMOC	49.86	2.62	3.48		52.95	2.36	3.06
	SPCC	45.85	2.91	3.80		53.72		2.35	3.07
	ECMWF	40.53	3.30	4.26	53.46		2.45	3.22
	WQSRTP	69.83	1.59	2.07	65.47		1.74	2.25
72	SCMOC	47.22	2.74	3.59	51.47	2.42	3.12
	SPCC	45.24	2.95	3.87	51.83		2.42	3.14
	ECMWF	26.10	4.67	5.74	38.12		3.32	4.20
	WQSRTP	65.74	1.73	2.29	62.94		1.81	2.33

预报时效/h	预报产品	最高气温订正技巧/%	最低气温订正技巧/%
24	SCMOC	40.62	30.26
	SPCC	43.65	28.65
	ECMWF	53.89	44.85
48	SCMOC	40.45	27.00
	SPCC	44.35	26.18
	ECMWF	50.61	41.12
72	SCMOC	36.23	25.48
	SPCC	42.84	24.33
	ECMWF	62.88	47.20