Impacts of model initialization on an integrated surface water–groundwater model

Integrated hydrologic models characterize catchment responses by coupling the subsurface flow with land surface processes. One of the major areas of uncertainty in such models is the specification of the initial condition and its influence on subsequent simulations. A key challenge in model initialization is that it requires spatially distributed information on model states, groundwater levels and soil moisture, even when such data are not routinely available. Here, the impact of uncertainty in initial condition was explored across a 208 km² catchment in Denmark using the ParFlow.CLM model. The initialization impact was assessed under two meteorological conditions (wet vs dry) using five depth to water table and soil moisture distributions obtained from various equilibrium states (thermal, root zone, discharge, saturated and unsaturated zone equilibrium) during the model spin‐up. Each of these equilibrium states correspond to varying computation times to achieve stability in a particular aspect of the system state. Results identified particular sensitivity in modelled recharge and stream flow to the different initializations, but reduced sensitivity in modelled energy fluxes. Analysis also suggests that to simulate a year that is wetter than the spin‐up period, an initialization based on discharge equilibrium is adequate to capture the direction and magnitude of surface water–groundwater exchanges. For a drier or hydrologically similar year to the spin‐up period, an initialization based on groundwater equilibrium is required. Variability of monthly subsurface storage changes and discharge bias at the scale of a hydrological event show that the initialization impacts do not diminish as the simulations progress, highlighting the importance of robust and accurate initialization in capturing surface water–groundwater dynamics. Copyright © 2015 John Wiley & Sons, Ltd.     

Evaluation of hydrologic components of community land model 4 and bias identification

Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. We have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties in the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.     

青藏高原多雪年与少雪年土壤水热特征模拟分析

利用耦合了陆面过程模式(CLM4.5)的区域气候模式(RegCM4)分别对青藏高原的一个多雪年和少雪年进行了数值模拟.通过对比模拟雪深与遥感雪深、土壤温湿度的模拟值与观测值、多雪年与少雪年的土壤温湿度模拟值,结果表明,RegCM4-CLM4.5可以有效模拟出高原的多雪年与少雪年特征,模拟雪深大值中心比遥感雪深高10～2...     

地表能量平衡方程在新疆地表温度模拟中的应用

地表温度是影响地表能量收支平衡和气候变化的重要因子,也是评价陆面模式性能的主要指标.新疆下垫面包括沙漠、绿洲、冰川、积雪等多种类型,其地表温度变化对生态环境和天气气候变化有重要影响.为了找到影响第三代陆面模式NCAR CLM4.5模拟新疆地表温度效果的主要因子,促进该模式发展,在对ERA-5再分析资料评估基础上,以其作...     

中国区域陆面覆盖变化的气候效应模拟研究

基于MODIS和CLCV陆面覆盖资料,利用区域气候模式RegCM4分别进行两组24年（1978-2001年）的数值模拟试验,研究中国区域陆面覆盖变化对区域气候的影响。结果表明,以荒漠化和植被退化为主要特征的陆面覆盖变化通过改变陆面能量、水分平衡与大尺度环流进而对气候要素产生重要影响。夏季,中国南方地区普遍降温,季风边缘区及藏北高原气温升高,降水减少;季风边缘区与西北地区气温年际波动加剧;内蒙古中东部地区西南风增强,进而水汽输送增强,一定程度上增加了该地区降水。冬季,中国东部地区偏北气流增强,更多干燥冷空气南下,使得黄河以南地区降水减少、气温降低。     

三个陆面过程模式在西北半干旱区的模拟性能对比

利用NOAH(The Community Noah Land Surface Model)、SHAW(Simultaneous Heat and Water)和CLM(Community Land Model)3个不同的陆面过程模式及兰州大学(Semi-Arid Climate Observatory and Laboratory,SACOL)2007年的观测资料,对黄土高原半干旱区的陆面过程进行了模拟研究。通过与观测值间的对比,考察不同陆面过程模式在半干旱区的适用性。研究结果表明:3个模式在半干旱区的模拟性能有较大差异。其中,CLM模式模拟的20 cm以上的浅层土壤温度最优,SHAW模式模拟的深层土壤温度最优;SHAW模式模拟的土壤含水量与观测值最为接近,而NOAH和CLM模式模拟值有较大偏差;3个模式均能较好地模拟地表反射辐射,其中SHAW模式模拟值与观测值的偏差最小;对地表长波辐射的模拟,CLM模式的模拟最优;3个模式均能较好地反映感热、潜热通量的变化趋势,其中CLM模式对感热的模拟性能优于其他两个模式,在有降水发生后的湿润条件下,CLM模式对潜热的模拟性能最优,而无降水的干燥条件下,CLM模式的模拟偏差最大,NOAH模式对冬季潜热的模拟最优。总体而言,CLM模式能够更好地再现半干旱区地气之间的相互作用,但模式对土壤含水量及干燥条件下的潜热通量的模拟较差,模式对半干旱区陆气间的水文过程还有待进一步的研究和改进。     

Transpiration and evaporation of grassland using land surface modelling

Partitioning transpiration (T) from evapotranspiration (ET) is a key process for understanding the interaction between land surfaces and the atmosphere. This paper reports daily partitioning results for a grassland over a 10-year period, obtained using the Community Land Model 3.5 (CLM3.5) land surface model. Hourly forcing data were collected from a long-term observation system located in the northeast of Japan ( http://doi.org/10.24575/0001.198108 ). To test the model behavior, total ET was validated using eddy correlation measurements combined with the energy balance method. The results were compared with previous research using an isotope approach for partitioning. The results demonstrate that our model can capture the dynamics of ET and its components at this location. Evaporation (E), originating from the ground and canopy, varied inter-annually, and from 2006 to 2015, average annual E was approximately 285 mm/year from the ground and 45 mm/year from the canopy. Average, T, was approximately 302 mm/year, accounting for approximately 48% of the total ET. Inter-annual results demonstrate that the water flux transported by vegetation ranges from 17 to 83% during the April–October period. A sensitivity test conducted with forcing data indicates air temperature, incident solar radiation, and longwave radiation exhibited a notable effect on all ET components. Relative humidity exhibited the only negative feedback to both evaporation and transpiration, contrary to the other forcing parameters. Our study reemphasized the effectiveness of CLM3.5 in partitioning T from ET and in understanding the complex interaction between land surfaces and the atmosphere.     

Impact of rain snow threshold temperature on snow depth simulation in land surface and regional atmospheric models

This study investigates the impact of rain snow threshold (RST) temperatures on snow depth simulation using the Community Land Model (CLM) and the Weather Research and Forecasting model (WRF-coupled with the CLM and hereafter referred to as WRF CLM), and the difference in impacts. Simulations were performed from 17 December 1994 to 30 May 1995 in the French Alps. Results showed that both the CLM and the WRF CLM were able to represent a fair simulation of snow depth with actual terrain height and 2.5℃ RST temperature. When six RST methods were applied to the simulation using WRF CLM, the simulated snow depth was the closest to observations using 2.5℃ RST temperature, followed by that with Pipes’, USACE, Kienzle’s, Dai’s, and 0℃ RST temperature methods. In the case of using CLM, simulated snow depth was the closest to the observation with Dai’s method, followed by with USACE, Pipes’, 2.5℃ RST temperature, Kienzle’s, and 0℃ RST temperature method. The snow depth simulation using the WRF CLM was comparatively sensitive to changes in RST temperatures, because the RST temperature was not only the factor to partition snow and rainfall. In addition, the simulated snow related to RST temperature could induce a significant feedback by influencing the meteorological variables forcing the land surface model in WRF CLM. In comparison, the above variables did not change with changes in RST in CLM. Impacts of RST temperatures on snow depth simulation could also be influenced by the patterns of temperature and precipitation, spatial resolution, and input terrain heights.     

基于CLM模式的青藏高原土壤冻融过程陆面特征研究

使用位于青藏高原东部若尔盖站的观测数据驱动CLM3.5模式,设计一组去除模式中冻融过程的"退化试验",进行为期一年的模拟研究。通过对比原试验与敏感性试验模拟结果,初步分析冻融过程在土壤温度变化、各能量通量分配中的作用,得到以下结论：（1）冻融过程是土壤温度变化的"缓冲器",冻结过程向周围环境释放能量减缓了土壤降温的速率,使土壤温度不至降得太低,而消融过程从周围环境吸收能量减缓了土壤升温的速率,使土壤温度不至升高太多;（2）冻融过程改变了地表辐射通量,土壤冻结改变了地表反照率,改变了向上短波辐射,且由于冻结过程减缓了地表温度的下降,改变了地表向上长波辐射,进而改变了净辐射通量;（3）冻融过程显著地改变了陆面能量的分配,通过相变能量的释放和吸收增大了地气间能量的传输,显著地增大了地表土壤热通量,且通过改变地表温度和地表蒸发,改变了感热及潜热通量。在冻结过程及完全冻结阶段,感热及潜热通量均增大,但在消融过程阶段,感热及潜热通量均减小。冻融过程对土壤热通量及感热通量的影响在冻结过程及完全冻结阶段更为显著,而对潜热的影响则是在消融过程阶段更为显著。     

Evaluation of multiple surface soil moisture for Korean regional flux monitoring network sites: Advanced Microwave Scanning Radiometer E,land surface model,and ground measurements

In the past few decades, there have been great developments in remotely sensed soil moisture, with validation efforts using land surface models (LSMs) and ground‐based measurements, because soil moisture information is essential to understanding complex land surface–atmosphere interactions. However, the validation of remotely sensed soil moisture has been very limited because of the scarcity of the ground measurements in Korea. This study validated Advanced Microwave Scanning Radiometer E (AMSR‐E) soil moisture data with the Common Land Model (CLM), one of the most widely used LSMs, and ground‐based measurements at two Korean regional flux monitoring network sites. There was reasonable agreement regarding the different soil moisture products for monitoring temporal trends except National Snow and Ice Data Centre (NSIDC) AMSR‐E soil moisture, albeit there were essential comparison limitations by different spatial scales and soil depths. The AMSR‐E soil moisture data published by the National Aeronautics and Space Administration and Vrije Universiteit Amsterdam (VUA) showed potential to replicate temporal variability patterns (root‐mean‐square errors = 0·10–0·14 m³ m^?3 and wet BIAS = 0·09 ? 0·04 m³ m^?3) with the CLM and ground‐based measurements. However, the NSIDC AMSR‐E soil moisture was problematic because of the extremely low temporal variability and the VUA AMSR‐E soil moisture was relatively inaccurate in Gwangneung site characterized by complex geophysical conditions. Additional evaluations should be required to facilitate the use of recent and forthcoming remotely sensed soil moisture data from Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive missions at representative future validation sites. Copyright © 2011 John Wiley & Sons, Ltd.