【摘要】：從服務新型城鎮化進程出發,本文基于氣候條件與人類活動的相互作用關系,同時考慮氣候的資源和災害雙重屬性,識別并構建了包含氣候資源供給、氣候災害限制和城鎮化協調發展水平三方面要素的氣候承載力評價指標體系,進而采用熵權法、耦合協調度模型和GIS技術等方法實現了指標的量化,形成了氣候承載力的綜合評價指標和模型。以皖江城市帶為例,應用該套指標方法探討了氣候承載力的空間格局與關鍵影響因子,結果表明,皖江城市帶城鎮化發展格局與氣候承載力分布較為一致,氣候承載力較高的地區意味著可容納的城市發展負荷量較高,而與之對應的這些地區城鎮化集聚程度也較高;但氣候承載力水平空間差異顯著,區域整體氣候承載力還有待進一步優化提升。根據城鎮化集聚度和氣候承載力特點,將皖江城市帶分為4個等級和12種類型,并進一步揭示了不同類型地區存在的承載力"短板"和問題現狀。
[Abstract]:Based on the interaction between climate conditions and human activities, and considering the dual attributes of climate resources and disasters, this paper identifies and constructs the supply of climate resources from the perspective of serving the new urbanization process. The evaluation index system of climate bearing capacity of the three elements of climate disaster restriction and urbanization coordinated development level is presented. Then, the quantification of the index is realized by using entropy weight method, coupling coordination model and GIS technology, etc. The comprehensive evaluation index and model of climate bearing capacity are formed. Taking the urban belt of Wanjiang River as an example, the spatial pattern of climate carrying capacity and the key influencing factors are discussed by using this set of index methods. The results show that the distribution of urbanization pattern and climate carrying capacity in the urban belt of Anhui River is consistent with the distribution of climate carrying capacity. The higher bearing capacity of climate means that the amount of urban development load can be higher, and the corresponding degree of urbanization agglomeration is higher in these areas, but the spatial difference of the level of climate carrying capacity is significant. The overall climate bearing capacity of the region needs to be further optimized and enhanced. According to the characteristics of urbanization concentration and climate bearing capacity, the urban belt of Wanjiang River is divided into 4 grades and 12 types, and the "short plates" and problems of bearing capacity in different types of areas are further revealed.
【作者單位】： 安徽省氣象局氣候中心;安徽省大氣科學與衛星遙感重點實驗室;安徽省氣象局公共氣象服務中心;
【基金】：中國氣象局氣候變化專項(CCSF201507,CCSF201734);中國氣象局青年英才計劃 中國清潔發展機制基金贈款項目(2013028) 安徽省氣象局創新團隊建設計劃
【分類號】：P463.3

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