自然资源学报 ›› 2011, Vol. 26 ›› Issue (10): 1775-1788.doi: 10.11849/zrzyxb.2011.10.014

• 资源研究方法 • 上一篇    下一篇

地表反照率动态参数化方案研究——以玉米农田为例

蔡福1,2,3, 周广胜1, 李荣平3, 明惠青4, 张果1, 何奇瑾1, 段居奇1   

  1. 1. 中国气象科学研究院,北京 100081;
    2. 南京信息工程大学,南京 210044;
    3. 中国气象局 沈阳大气环境研究所,沈阳 110016;
    4. 辽宁省气象科技服务中心,沈阳 110016
  • 收稿日期:2010-11-23 修回日期:2011-03-17 出版日期:2011-10-20 发布日期:2011-10-20
  • 通讯作者: 周广胜 E-mail:gszhou@cams.cma.gov.cn
  • 作者简介:蔡福(1980- ),男,辽宁海城人,助理研究员,博士生,从事区域气候变化和陆面过程方面的研究。E-mail: caifu_80@163.com
  • 基金资助:

    国家杰出青年基金项目(40625015);国家重点基础研究发展计划(973计划)( 2010CB951303)。

Dynamic Parameterization Scheme of Surface Albedo: A Case Study on Rained Maize Field

CAI Fu1,2,3, ZHOU Guang-sheng1, LI Rong-ping3, MING Hui-qing4, ZHANG Guo1, HE Qi-jin1, DUAN Ju-qi1   

  1. 1. Chinese Academy of Meteorological Sciences, Beijing 100081,China;
    2. Nanjing University of Information Science and Technology, Nanjing 210044, China;
    3. Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110016,China;
    4. Liaoning Province Meteorological Science and Technology Service Center, Shenyang 110016, China
  • Received:2010-11-23 Revised:2011-03-17 Online:2011-10-20 Published:2011-10-20

摘要: 利用2006—2008年锦州玉米农田生态系统野外观测站的通量、气象及生物因子观测资料研究了地表反照率(α)的动态参数化方案。结果表明:α与太阳高度角(hθ)呈对数关系,与表层土壤湿度(SWC)呈对数或线性关系,与叶面积指数(LAI)呈指数或线性关系。非生长季,hθSWCα的主要影响因子,与α分别呈对数和线性关系时α的模拟精度明显好于其他关系,除初春外,大部时段的α模拟误差都较小。生长季,α主要受hθ、SWCLAI的影响。采用α分别与hθ、SWCLAI呈对数、线性和指数关系时α的模拟精度较高,受资料限制,大部分时段的α被明显低估,玉米营养生长阶段的模拟精度更差。引入植被覆盖度(Fveg)对裸土和植被分别赋权重所建立的α动态参数化模型,在生长季内α的模拟误差明显减小,营养生长时段α的模拟精度显著提高。该研究将为陆面过程模型提供动态的植被反照率参数,从而可提高模拟的准确性。

关键词: 玉米农田, 地表反照率, 参数化方案

Abstract: Using continuous flux data, meteorological data and biological data from 2006 to 2008 from Jinzhou agricultural ecosystem research station, dynamic parameterization scheme of surface albedo(α) was investigated. The results show that α has logarithm, logarithm or linear, exponential or linear relationships with solar altitude(hθ), surface soil water contents(SWC) and leaf area index(LAI), respectively. The model founded considering respectively logarithm and linear relationship between α and hθ and SWC is better than those considering other relationships and is able to simulate diurnal pattern of α with smaller error in most of the non-growing season except early spring. In the growing season, the simulation precision of the α parametric model founded with statistical regression method considering respectively logarithm, linear and exponential relationships between α and hθ, SWC and LAI play an important role in α which is higher than those considering other relationships. For the limitation of data, the model underestimates evidently α in most of the period especially in vegetative growth phase of maize. As vegetation coverage (FVEG) introduced and used to bestow weighing to soil and vegetation, the model whose simulation error decreases significantly in total growing season especially in vegetative growth phase is able to reflect seasonal variation of α and has dynamic simulation ability, which changes an untrue hypothesis that vegetation α is only constant in many land surface models and makes the model universal-adapted to simulate dynamic α in different phases of maize field. By this study, land surface process model will be offered dynamic parameter of vegetation α and then whose simulation accuracy will be improved.

Key words: rainfed maize field, surface albedo, dynamic parameterization scheme

中图分类号: 

  • P422.4