地表反照率动态参数化对陆-气通量模拟的影响:以东北玉米农田为例

A simulative study of effects of dynamic parameterization of surface albedo on land-atmosphere flux exchanges: A case study of rainfed maize field in northeast China

利用考虑了生物因子(叶面积指数)和环境因子(太阳高度角、表层土壤湿度)影响的地表反照率α动态参数化方案对BATS1e模型进行改进,基于2008年玉米农田生态系统的通量、气象及生物因子的连续观测资料,研究α动态参数化对玉米农田生态系统与大气间通量交换的影响。结果表明,引入α动态参数化方案后,模型实现了地表反照率α的日、季动态模拟,模型效率系数提高0.65,误差明显减小,使陆-气通量交换热力作用的模拟准确性有所提高,其中,净入射短波辐射模拟改进最为明显,全年改进量为81772kJ/m2,占年总辐射的1.7%;表层土壤温度的年均改进量为0.62K,多数月份的改进量在1K以上。另外,模型改进实现了叶面积指数和植被覆盖度等决定下垫面性质各参数的动态变化,使各种通量交换过程更接近于实际,感热和潜热模拟的模型效率系数分别提高0.516和0.1,模拟值对实测值的解释能力在生长季分别提高6%和9%,大于非生长季。

Based on the continuous observations of land-atmosphere flux exchanges, meteorological and biological elements in 2008 from the Jinzhou agricultural ecosystem research station, and by introducing a dynamic surface albedo （α） parameterization scheme that takes the leaf area index （LAD, the solar altitude （hθ） and the surface soil water contents （SWC） into account, the BATSle model was modified and used to investigate effects of dynamic surface albedo parameterization on flux exchanges between the maize farmland e- cosystem and the atmosphere. The results showed that α was able to be dynamically simulated and its simulation error and the Nash- Sutcliffe efficiency factor （NS） decreased obviously and increased by 0. 65, respectively, which increased the simulation accuracy of the thermal action in land-atmosphere flux exchanges such as the net absorbed solar energy flux which was improved most obviously among the radiation elements and whose annual improved magnitude was 81772 kJ/m2 making up about 1.7 percent of the annual global solar radiation and the surface soil temperature whose annual and monthly mean improved magnitudes were 0.62 K and above 1 K in most of months, respectively. In addition, the improved model realized the dynamic change of main canopy structure parameters reflecting sur- face characteristics such as LAI and the vegetation coverage and made flux exchange processes more close to the real for example sensi- ble heat flux and latent heat flux whose simulation accuracies were also improved with their NSs increasing 0. 516 and 0.1 as well as the explanatory ability of simulations to observations increased by 6% and 9% in the growing season, respectively, which were larger than in the no-growing season.