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关于农业气候区划,目前绝大多数都采用主导指标与辅助指标相结合的方法,一般以热量为Ⅰ级指标,水分为Ⅱ级指标,灾害作为Ⅲ级指标,然后进行套叠,定出区界,这种方法也有一定的人为主观性,为使区界的确定客观定量化,可用模糊聚类法和逐步聚类法划分农业气候相似区。采用决定熟制的热量条件即≥0℃的活动积温为主导因子以<0℃的负积温为限制因子;辅之以年干燥度和年降水量。把以上四因子作为分区的综合指标,这样既考虑了热量条件,又兼顾了全年的水分平衡。北京市所辖土地面积虽小,但境内地形复杂、气候差异较大.仅用现有气象站资料不能全面地反映这些差异,定出明确的区界,故此,我们选取86个站点(包括各地区县气象站),以期比较充分地反映出农业气候的差异性。
On the agricultural climate zoning, the vast majority of the current use of a combination of leading indicators and auxiliary indicators, the general heat to grade Ⅰ indicators, water level Ⅱ indicators, disasters as a Ⅲ-level indicators, and then nested, set the boundaries , This method also has certain man-made subjectivity. In order to make the determination of the boundaries objectively and quantitatively, fuzzy analogy and stepwise clustering can be used to divide agricultural climatic zones. Adopting the ripening heat condition (≥0 ℃) as the dominant factor, the negative accumulated temperature of <0 ℃ is the limiting factor, and the annual dryness and annual precipitation are supplemented. The above four factors as a comprehensive indicator of the district, so that not only considers the heat conditions, but also take into account the annual water balance. Although the size of the land under Beijing’s jurisdiction is small, but the terrain is complicated and the climate is quite different, only the existing weather station data can not fully reflect these differences and define a clear boundary. Therefore, we selected 86 sites Regional county weather station), with a view to more fully reflect the differences in agricultural climate.