第30卷第11期K江科學院院報Vol.30 No. 112013年11月Journal of Yangtze River Scientific Research InstituteNov.2013DOI:10. 3969/j. issn. 1001 - 5485.2013. 11. 0042013 ,30(11):16-19基于信息熵的河南省年降水量時空變化研究王振亞'，吳德波“,朱余生(1.河南省氣象臺，鄭州450003; 2.黃河水利委員會水文水資源局,鄭州450003; 3.機械工業(yè)第六設計研究院有限公司,鄭州450003; 4.中國氣象局河南省農(nóng)業(yè)氣象保障與應用技術重點實驗室,鄭州450003)摘要:選取河南省1960- 2006 年共83個站年降水量,將信息熵理論應用在河南省年降水量時空變化研究上,計算每站的年降水量時間序列和年降水量與其極小值的相對量序列的熵估計值全省各年年降水量分布和年降水量與其多年平均降水量的相對值分布的熵估計值。計算結(jié)果表明:河南省年降水量的年際變化自西北東南方向增大,自南向北減小，自西向東增大,在西南東北方向則沒有明顯的規(guī)律;河南省年降水量相對值的年際變化自西南東北方向增大,在其他方向上則沒有明顯的規(guī)律;1966,1976,1999和2001年的河南省年降水量的空間分布較均勻,2000年的年降水量的空間分布不均勻;1986年的年降水量與其多年平均的相對值空間分布較均勻,2000年的年降水量與其多年平均的相對值空間分布不均勻。關鍵詞:信息熵;年降水量;時空變化;不確定性中圖分類號:TV125文獻標志碼:A文章編號:1001 - 5485 (2013)11 -0016-04降水量始終是氣候變化研究的一個重要方量,逐站求取各站年降水量時間序列。面"。降水量時空分布的不確定性易形成旱澇災1.2 研究理論和方法害,對水資源、工業(yè)、農(nóng)業(yè)和生態(tài)環(huán)境等方面產(chǎn)生重物理學中,熵是熱力學系統(tǒng)的某種狀態(tài)函數(shù),它大影響。C. E. Shannon把Boltzmann的概念引人信是對系統(tǒng)混亂度的度量,熵增使系統(tǒng)的混亂度增加,息論中,把熵作為-個隨機事件的不確定性或信息熵減使系統(tǒng)的有序性增加'”。隨著信息論的發(fā)展量的度量(2]。這種不確定性應用在年降水量的時與應用,信息熵問題得到了不少學者的積極研究,取間序列上可以研究降水量的年際變化規(guī)律,應用在得了大量的成果,其具有代表性的模型有Renyi的年降水量的空間分布上可以研究年降水在空間上分信息熵、模糊集合的信息熵、高艾期的有效信息熵。布是否均勻。張繼國'31將信息熵的理論與方法應1948年,C.E.Shannon提出了基于離散型變量用在淮河流域降雨的時空分布研究上,取得較好的的信息熵。1994 年,N. Ebrahimi等(8)提出了熵估計研究結(jié)果。的2個改進式,可以由觀測數(shù)據(jù)直接得到X的熵估河南省地處北亞熱帶向暖溫帶過渡的大陸性季計,并且證明了這2個估計式分別以概率收斂到風氣候區(qū)內(nèi)(4),境內(nèi)地理條件復雜,降水量的水平H(X)。蒙特卡洛模擬顯示這2個改進的估計式有較及垂直差異顯著。--些學者基于統(tǒng)計學方法對河南小的偏差和平均平方誤差[”)。本研究采用其中的省降水量的時空變化進行了相關研究[5-6),其主要一個改進式作為計算熵的估計值。基于定性描述,筆者將信息熵理論應用在河南省年設x,x,..x。是來自總體X的一組觀測值，降水量時空變化研究方面,該方法將時空變化規(guī)律則所求熵的估計值為轉(zhuǎn)化為對信息熵的定量計算,理論依據(jù)明確,計算方H.(m,n) = -SInYitm = Yi-m。(1)n臺c:m/n法簡單。其中1≤i≤m ;1資料和方 法C; =2m +1≤i≤n-m ;1.1 研究資料n-m+1≤i≤n。選取河南省1960- -2006 年共83個站日降水中國煤化工收稿日期:2012 -09 -18;修回日期:2012 -10-22作者簡介:王振亞( 1981 -) ,男,河南正陽人,工程師,碩士研究生,主要從事水文氣象方面..---_”信箱)huwzy1981.JYH@ 163. com。.第11期王振亞等基于信息熵的河南省年降水量時空變化研究19(10): 84 - 86. 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Spatiotemporal Distribution of(編輯:趙衛(wèi)兵)Precipitation and Temperature Change in Henan ProvinceResearch on Spatio-Temporal Variation of Annual Precipitation inHenan Province by Information EntropyWANG Zhen-ya'4 , WU De-bo2 ,ZHU Yu-sheng'(1. Henan Meteorological Observatory ，Zhengzhou 450003 ，China; 2. Hydrology Bureau of Yellow RiverConservancy Commission, Zhengzhou 450003, China; 3. SIPPR Engineering Group Co.，Ltd. ,Zhengzhou450003, China; 4. Henan Provincial Key Laboratory of Agrometeorological Ensuring and Applied Techniqueunder China Meteorological Administration, Zhenghou 450003 , China)Abstract :The temporal and spatial variation of annual precipitation in Henan province was researched based on thetheory of information entropy. The annual precipitation time series at 83 stations from 1960 to 2006 was selected.The estimated information entropy of the annual precipitation time series and the relative value of annual precipitati-on to its minimum at each station, as well as the estimated information entropy of the annual precipitation' s spatialdistribution and the relative value of annual precipitation to its multi-year average in each year , were calculated.Results show that the interannual variation of annual precipitation increases from northwest to southeast and fromwest to east, and reduces from south to north, but has no obvious regularity from southwest to northeast; while theinterannual variation of the relative value of annual precipitation to its minimum increases from southwest to north-east but has no obvious regularity in the other directions. The spatial distribution of annual precipitation was uni-form in 1966, 1976, 1999 and 2001 and nonuniform in 2000; the spatial distribution of the relative value of annualprecipitation to its multi-year average is uniform in 1986 and nonuniform in 2000.Key words : information entropy ; annual precipitation; temporal and spatial variation; uncertainty.....................................................央(上接第15頁)tree -ring index sequence. The results show that there are three positive phase stages and four negative phase stagesin the low-frequency information of reconstruction sequence. Except for transitory positive phase in mid-1970s andaround 1990s , the overall trend of Ispo is negative phase from 1914 to 1948 , positive phase from 1948 to 1965, andgenerally negative phase since the mid-1960s. Comparative analysis shows that the reconstructed summer IApo se-quence is well synchronic with another summer IAPO reconstruction sequence.Key words: summer Asian-Pacific Oscillation index (Ipo); tree-ring中國煤化工is; XiaowutaiMountainMYHCNMHG