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中国农学通报 ›› 2016, Vol. 32 ›› Issue (19): 120-129.doi: 10.11924/j.issn.1000-6850.casb16040019

所属专题: 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

春秋季冷空气过程对不同养殖水体水温的影响分析

邓爱娟,刘志雄,刘可群,秦鹏程,邓环   

  1. 武汉区域气候中心,武汉区域气候中心,武汉区域气候中心,武汉区域气候中心,武汉区域气候中心
  • 收稿日期:2016-04-05 修回日期:2016-06-03 接受日期:2016-05-13 出版日期:2016-07-15 发布日期:2016-07-15
  • 通讯作者: 邓爱娟
  • 基金资助:
    2016 年湖北省气象科技课题“小龙虾养殖与气象条件关系研究”(2016Y03);公益性气象行业专项“水产养殖气象保障关键技术”(GYHY201006029)

Cold Air in Spring and Autumn: Effect on Temperature of Different Aquatic Water

  • Received:2016-04-05 Revised:2016-06-03 Accepted:2016-05-13 Online:2016-07-15 Published:2016-07-15

摘要: 为了探讨冷空气活动对不同大小的水体水温造成的影响,利用2011~2012年春秋季冷空气资料及两个不同水体在冷空气发生前后时段的逐层水温资料,采用统计分析法,研究分析了各层水温对冷空气活动的响应和变化,建立了逐层水温降幅模型。结果表明:1)冷空气过后,浅表层水温比深层水温降幅大,大水体的水温极低值出现时间比小水体明显偏晚;2)冷空气强度越大,大小水体的水温降幅差异越大,小水体更容易降温;3)小水体的水温降幅与气象要素的相关性要好于大水体,且浅层水温更易受气象要素的影响,深层水温尤其是大水体的深层水温受外界环境影响明显较小;4)建立的水温降幅模型中,小水体模拟效果较好,大水体的浅层10~50cm层模拟效果相对较好,而深层100~150cm效果相对较差。据此,利用相关气象要素建立的预报模型可在春秋季水产养殖关键期有冷空气活动时提供生产指导和预警服务。

关键词: 城乡居民, 城乡居民, 养老保险, 发展水平

Abstract: The paper aims to reveal the effect of cold air process on temperature of different aquatic water. The response and variation of water temperature of each water layer caused by cold air process were studied based on water temperature data of two different water bodies during the occurrence of cold air in spring and autumn in 2011 and 2012, by using statistical analysis method. Besides, the water temperature reduction prediction models of each water layer were also established. The results showed that: (1) after the cold air, the amplitude reduction of water temperature of shallow layer was larger than that of deep one, and the minimum water temperature of large water body appeared obviously later than that of small water body; (2) the greater the intensity of cold air process, the greater the difference of water temperature reduction was, temperature of small water body was more likely to decrease under cold air; (3) the correlation between small water body’s temperature reduction and meteorological elements was much better than that of larger water body’s; and shallow water layer’s temperature was more vulnerable to the change of external meteorological elements, while the effect on deep layer was relatively inconspicuous, especially in deep layer of large water body; (4) the simulation result of established water temperature reduction model of small water body was much better, and the result was relatively good in the shallow layers (10 to 50 cm water layer) of large water body, while less satisfied in the deep layers (100 to 150 cm water layer). Thus, the predictive model established based on related meteorological factors can provide production guidance and warning during the critical aquaculture period in spring and autumn.

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