極端氣溫事件對安徽省農(nóng)業(yè)生產(chǎn)的動態(tài)影響分析

doi:10.3969/2014jms.0007

首頁 > 過刊瀏覽>2014年第34卷第4期 >443-449. DOI:10.3969/2014jms.0007

極端氣溫事件對安徽省農(nóng)業(yè)生產(chǎn)的動態(tài)影響分析
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                        10.3969/2014jms.0007
                    
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基金項目:國家自然科學基金資助項目（41071337）；公益性行業(yè)（農(nóng)業(yè)）科研專項（200903003）

Dynamic effect of extreme temperature events on agricultural production in Anhui

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用安徽省17個城市逐日的最高氣溫、最低氣溫數(shù)據(jù)，采用百分位法計算了1988-2010年安徽省年際極端氣溫事件，并以計量經(jīng)濟學的結構向量自回歸模型為基礎，將極端氣溫事件作為一個因子與農(nóng)業(yè)總產(chǎn)值、國內(nèi)生產(chǎn)總值、農(nóng)業(yè)機械總動力構建了新的經(jīng)濟-極端氣溫事件模型。進一步通過脈沖響應函數(shù)和方差分解方法，定量分析了極端氣溫事件對安徽省農(nóng)業(yè)生產(chǎn)的動態(tài)影響，結果表明：極端高溫事件對農(nóng)業(yè)生產(chǎn)的影響總體為負向，并表現(xiàn)出一定的滯后性；而極端低溫事件對農(nóng)業(yè)生產(chǎn)的影響初期為正向，后期逐漸轉(zhuǎn)為負向。極端高溫事件對農(nóng)業(yè)生產(chǎn)的影響程度較高，可達0.033%，極端低溫事件次之。模型內(nèi)引起農(nóng)業(yè)生產(chǎn)變化的各因子中，極端高溫事件的貢獻比例可達25.3%，是重要的影響因子，極端低溫事件的貢獻比例最高為10.9%，也是比較主要的影響因子。

Abstract:

By using the daily maximum and minimum temperature data of 17 cities in Anhui, the interannual extreme temperature events' number in Anhui during 1988-2010 was calculated with the centesimal value method. Based on the structural vector autoregression model in econometrics, a new economy-extreme temperature event model was built by combining extreme temperature event, taken as a factor, with agricultural output, gross domestic product and agricultural machinery gross power. Furthermore, the dynamic effect of extreme temperature events on agricultural production was quantitatively analyzed by impulse response functions and variance decomposition. The results show that the overall effect of extreme high temperature events on agricultural production is negative with a certain lagging characteristics; the early effect of extreme low temperature events is positive, then turns to negative. The effect of extreme high temperature events on agricultural production is 0.033%, higher than the extreme low ones. The extreme high temperature event is the most important one among the factors involving agricultural production change in the modelm, its contributions ratio is 25.3%, while the extreme low temperature came second with 10.9%, which was stin a relatively major factor.

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付偉,許信旺,司紅君,劉蕾,朱琦.極端氣溫事件對安徽省農(nóng)業(yè)生產(chǎn)的動態(tài)影響分析.氣象科學,2014,34(4):443-449 FU Wei, XU Xinwang, SI Hongjun, LIU Lei, ZHU Qi. Dynamic effect of extreme temperature events on agricultural production in Anhui. Journal of the Meteorological Sciences,2014,34(4):443-449

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收稿日期:2013-11-24
最后修改日期:2014-01-09
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在線發(fā)布日期: 2014-08-29
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