三种气温预报产品黑龙江省预报效果检验

doi:10.3969/j.issn.1673-503X.2022.02.003

Abstract

Abstract:

Using the T639 model forecast products and air temperature observations at 83 national weather stations in Heilongjiang province, we selected forecast factors using an optimal selection method, and established the Model Output Statistics (MOS) prediction equations for daily maximum air temperature (TMAX) and daily minimum air temperature (TMIN) using a multiple regression method.In addition, we comparatively analyzed and validated the forecast performance of TMAX and TMIN from the MOS, the guide forecasts of the Central Meteorological Observatory (SCMOS), and three air temperature forecast products from the T639 model, and examined the consistency of spatiotemporal distribution between the predicted and observed air temperature using the Empirical Orthogonal Function (EOF) method.The results showed that the MOS and SCMOC perform better in predicting the spatiotemporal distribution of air temperature, while the T639 model performs relatively poorer.The values of 2℃ forecast accurate rate (TT₂) for TMAX and TMIN from the MOS and SCMOC are mostly higher than those using the T639 model, and the TT₂ values for TMAX/TMIN from the MOS are higher/lower than those from SCMOC.MOS can improve the air temperature forecast from the T639 model, especially for the TMIN forecast in winter.There is a negative correlation between the improvement of MOS relative to the T639 forecast and the performance of the T639 forecast.The MOS's improvement is better over mountain areas with low TT₂ predicted by the T639 model than that over plain areas.In spring and summer, the MOS's improvement is better for the TMAX with low TT₂ than the TMIN, while in winter, the MOS improvement is better for the TMIN with low TT₂ than the TMAX.This MOS air temperature forecast method has a good forecast capability and can be applied to the interpretation and application of other numerical model products.The SCMOC can be used in the TMIN forecast in Heilongjiang province considering its good forecast performance; the TMIN parameter is usually difficult to forecast in Heilongjiang province.

Key words: Forecast products of air temperature, Optimal forecast factor, Prediction accurate rate, Forecast capability

CLC Number:

P457.3

Ying-ying MENG, Shu-ling LI, Ling ZHAO, Xue-mei BAI, Min-hui YAN. Validation of three forecast products of air temperature in Heilongjiang province[J]. Journal of Meteorology and Environment, 2022, 38(2): 21-30.

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References 19

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时效	极端气温	预报产品	春季	夏季	秋季	冬季
24 h	TMAX	SCMOC	57.1	68.4	86.6	47.1
		T639	52.4	51.9	53.7	45.6
		MOS	77.3^*	70.1^*	98.8^*	54.4^*
	TMIN	SCMOC	56.2^*	69.1	48.3^*	58.1^*
		T639	46.2	71.2^*	23.4	24.4
		MOS	49.9	51.8	44.1	56.1
48 h	TMAX	SCMOC	57.5	56.7	-	38.7
		T639	47.8	51.4	-	35.2
		MOS	71.3^*	64.0^*	-	42.1^*
	TMIN	SCMOC	51.5^*	67.6^*	45.9^*	54.5^*
		T639	41.6	66.4	17.4	23.2
		MOS	47.9	51.3	40.2	52.9
72 h	TMAX	SCMOC	43.4	41.5	-	39.3
		T639	41.5	38.0	-	43.6^*
		MOS	63.9^*	57.7^*	-	37.5
	TMIN	SCMOC	44.2^*	68.4^*	43.3^*	42.0
		T639	37.2	59.8	15.9	25.0
		MOS	43.4	52.8	39.0	45.7^*

个例	日期	SCMOC	T639	MOS
极端TMAX	20180601	50.00	56.10	65.90
极端TMIN	20160130	41.50	19.50	34.10

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Validation of three forecast products of air temperature in Heilongjiang province

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