Research On The Surface Energy Imbalance And Parameterization Of Land-surface Processes In The Semi-arid Region Of The Loess Plateau

The surface energy imbalance problem has been a challenge in the study of surface land process since it was found in the late1980s. Besides, physical parameters related to land-surface processes are significant to land surface process models. Based on the data collected at the Semi-Arid Climate and Environment Observatory of Lanzhou University （SACOL） from2007to2009, the paper analyzed characteristics of land surface radiation and energy budget in summer, investigated characteristics of the surface energy imbalance and mechanisms causing it and calculated physical parameters related to land-surface processes over the natural vegetation surface in the Loess Plateau of middle Gansu. Main results arc concluded as follows:（l）By studying the impacts of different weather conditions on micrometcorological characteristics, the asymmetric structure of diurnal variation of surface albedo appears on the morning of sunny days with larger albedo values. The surface energy budget on a sunny day has a larger amount of imbalance, compared with that on a cloudy day. Besides.the shower on an obscure day can also lead to large energy imbalance. The unclosure of energy balance obtained by using OLS（Ordinary Least Squares） linear regression method is19.6%.In the semi-arid area, the clouds and the precipitation cause about25%disturbances to each component of energy balance. Weakening impact of clouds and precipitation on surface energy budget is apparent and much stronger than Dunhuang Gobi. Furthermore, it shows that the mean climatic characteristics in summer relatively close to those of cloudy days with more clouds（5=Mean total cloud amount<8）. Moreover, the maximum daily average Bowen ratio in July reaches4.1and the monthly mean value is1.95. The Bowen ratio in Yuzhong is much smaller than that in Dunhuang Gobi, which reflects the semi-arid area is more humid than the extreme arid area.（2）The soil heat storage between the ground surface and the heat flux plate at5cm depth was calculated from some soil thermal parameters, and the surface energy imbalance condition was re-estimated. When the soil heat storage as an energy budget component was taken into the surface energy balance equation, the mean absolute value of surface energy balance residual decreases23W m^-2 and the mean unclosure of energy balance is reduced by0.104. Moreover, the unclosure of energy balance obtained by using OLS（Ordinary Least Squares） linear regression method decreases0.085.Overall,the storage term can improve the surface energy budget condition and makes a large contribution to the unclosurc of energy balance, which can also be seen from the frequency distributions of the surface energy balance unclosure during the day and night.However,even if we take the soil heat storage into account, the surface energy imbalance still exists and it remains apparent.（3）The paper estimates the heat storage associated with change of air temperature and humidity as well as the energy stored in plants due to the photosynthesis, determines the water vertical flux in the shadow soil layer both by water conservation principle and two-level soil temperature, and investigates impacts of air and plant photosynthesis energy storages and heat transferred by the soil water movement on the surface energy budget. It is found that the diurnal variation peaks of averaged energy storages of air and plant photosynthesis reach1.5and2.0W m^-2 respectively. Additionally, the diurnal variation peak of mean heat transferred by vertical water movement is close to8.0W^-2. The closure of energy balance is improved from88.1%to89.6%by adding the three additional energy terms to the energy balance equation. As a whole, the energy storage related to air and the plant photosynthesis, and the heat transferred by the soil water movement both promote the surface energy balance to some extent. Furthermore, the semi-arid climate and the vegetation condition of Loess Plateau essentially lead to significant differences of various energy storages among this area and other climatic districts.（4）The paper studied averaged diurnal variations and the frequency distributions of the bulk transfer coefficients in different seasons, and analyzed the trend of surface roughness as well as effects of precipitation on the roughness. Monthly averages of the roughness in a normal year for precipitation have more changes compared with those in a dryer year and increasing the precipitation tends to increase the roughness. The roughness in a normal year is9×10^-3m, while the roughness in a dryer year decreases to6×10^-3m. Relationships among the bulk transfer coefficients and the two factors including surface roughness and the Richardson number are discussed. The role of dynamical transfer in land-atmosphere energy exchange over the Loess Plateau is dominant. Additionally, the neutral bulk transfer coefficient for momentum is close to those over movable dune at Naiman in Inner Mongolia and the neutral bulk transfer coefficient for momentum is close to those over Gobi. We also analyzed effects of solar elevation angle and soil moisture on surface albedo and preliminarily a multiple factorial parameterization formulae of surface albedo are raised.Generally, the albedo over the Loess Plateau is smaller than that over the desert of Dunhuang and larger than that over pine forest in Changbai Mountain. Various vegetation covers and soil types in the three regions lead to differences of albedo.By testing the simulation results of the albedo formula, it is found that albedo with low solar elevation angles is sensitive to other factors except soil moisture and solar elevation angle, while soil moisture and solar elevation angle affect albedo with high solar elevation angles significantly.What’s more, soil thermal parameters including soil thermal conductivity and thermal diffusion are calculated. In the same soil moisture, the soil thermal conductivity larger than that in desert of Dunhuang In the end, a parameterization formula of soil thermal conductivity is gotten by fitting thermal conductivity and soil moisture.