Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model （CERES3.0） was coupled into the Biosphere-Atmosphere Transfer Scheme （BATS）, which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China： one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.

Parameterization of Heat Fluxes at Heterogeneous Surfaces by Integrating Satellite Measurements with Surface Layer and Atmospheric Boundary Layer Observations

The regional heat flux exchange between heterogeneous landscapes and the nearby surface layer （SL） is a key issue in the study of land-atmosphere interactions over arid areas such as the Heihe River basin in northwestern China and in high elevation areas such as the Tibetan Plateau. Based on analysis of the land surface heterogeneity and its effects on the overlying air flow, the use of SL observations, atmospheric boundary layer （ABL） observations, and satellite remote sensing （RS） measurements along with three parameterization methodologies （here, termed as the RS, tile, and blending approaches） have been proposed to estimate the surface heat flux densities over heterogeneous landscapes. The tile and blending approaches have also been implemented during HEIhe basin Field Experiment （HEIFE）, the Coordinated Enhanced Observing Period （CEOP） Asia-Australia Monsoon Project on the Tibetan Plateau （CAMP/Tibet）, the Arid Environment Comprehensive Monitoring Plan ＇95 （AECMP＇95）, and the DunHuang Experiment （DHEX）. The results showed that these two proposed parameterization methodologies can be accurately used over heterogeneous land surfaces.

干旱及半干旱地区地表能量通量的卫星遥感参数化(英)

Dealing with the regional land surfaces heat fluxes over inhomogeneous land surfaces in arid and semi-arid areas is an important but not an easy issue. In this study, one parameterization method based on satellite remote sensing and field observations is proposed and tested for deriving the regional land surface heat fluxes over inhomogeneous landscapes. As a case study, the method is applied to the Dunhuang experimental area and the HEIFE (Heihe River Field Experiment, 1988-1994) area. The Dunhuang area is selected as a basic experimental area for the Chinese National Key Programme for Developing Basic Sciences: Research on the Formation Mechanism and Prediction Theory of Severe Climate Disaster in China (G1998040900, 1999-2003). The four scenes of Landsat TM data used in this study are 3 June 2000, 22 August 2000, and 29 January 2001 for the Dunhuang area and 9 July 1991 for the HEIFE area. The regional distributions of land surface variables, vegetation variables, and heat fluxes over inhomogeneous landscapes in arid and semi-arid areas are obtained in this study.

Effects of Optimized Root Water Uptake Parameterization Schemes on Water and Heat Flux Simulation in a Maize Agroecosystem

As root water uptake（RWU）is an important link in the water and heat exchange between plants and ambient air,improving its parameterization is key to enhancing the performance of land surface model simulations.Although different types of RWU functions have been adopted in land surface models,there is no evidence as to which scheme most applicable to maize farmland ecosystems.Based on the 2007–09 data collected at the farmland ecosystem field station in Jinzhou,the RWU function in the Common Land Model（Co LM）was optimized with scheme options in light of factors determining whether roots absorb water from a certain soil layer（W_x）and whether the baseline cumulative root efficiency required for maximum plant transpiration（W_c）is reached.The sensibility of the parameters of the optimization scheme was investigated,and then the effects of the optimized RWU function on water and heat flux simulation were evaluated.The results indicate that the model simulation was not sensitive to W_x but was significantly impacted by W_c.With the original model,soil humidity was somewhat underestimated for precipitation-free days;soil temperature was simulated with obvious interannual and seasonal differences and remarkable underestimations for the maize late-growth stage;and sensible and latent heat fluxes were overestimated and underestimated,respectively,for years with relatively less precipitation,and both were simulated with high accuracy for years with relatively more precipitation.The optimized RWU process resulted in a significant improvement of Co LM’s performance in simulating soil humidity,temperature,sensible heat,and latent heat,for dry years.In conclusion,the optimized RWU scheme available for the Co LM model is applicable to the simulation of water and heat flux for maize farmland ecosystems in arid areas.