CLM3.5模式对青藏高原玛曲站陆面过程的数值模拟研究

利用通用陆面过程模式(CLM3.5)和青藏高原玛曲站2010年6月-2011年2月的观测资料进行了9个月的单点数值模拟试验。通过比较辐射通量、能量通量、土壤温度及土壤含水量的模拟值和观测值,结果表明,CLM3.5模式能较成功地模拟玛曲地区的陆面能量与水分特征。该模式对夏季向上短波辐射的模拟较好,冬季整体偏小。向上长波辐射的模拟整体较好,但模拟值稍偏大。净辐射的模拟整体较好,模拟值与观测值的相关系数为0.99,偏差为-1.28 W.m-2。感热通量的模拟较差,整体显著偏高。潜热通量的模拟较好,随季节变化特征明显。土壤热通量的模拟夏季较好,冬季土壤冻结及消融期的偏差较大,主要原因与冬季模拟的积雪偏少有关。土壤温度的模拟夏季较好、冬季较差,6层土壤温度模拟值与观测值的相关系数均在0.98以上,平均偏差为-1.80℃。模式较好地模拟出了冬季土壤冻结后存留的未冻水,冻结后土壤含水量的模拟较该模式以前的版本有了很大的改善,6层土壤含水量模拟值与观测值的平均相关系数为0.94,平均偏差为-0.015m3.m-3。     

CLM4.5模式对青藏高原土壤湿度的数值模拟及评估

本文利用1981～2016年的CRUNCEP资料（0.5°×0.5°）作为大气驱动数据,驱动CLM4.5（Community Land Model version 4.5）模式模拟了青藏高原地区1981～2016 年的土壤湿度时空变化。将模拟数据与台站观测资料、再分析资料（ERA-Interim和GLDAS-CLM）和微波遥感FY-3B/MWRI土壤湿度资料对比验证,表明了CLM4.5模拟资料可以合理再现青藏高原地区土壤湿度的空间分布和长期变化趋势。而且基于多种卫星遥感资料建立的较高分辨率（0.1°×0.1°）的青藏高原地表数据更加细致地刻画了土壤湿度的空间变化。对比结果表明:CLM4.5模拟土壤湿度与各个台站观测的时空变化一致,各层土壤湿度的模拟和观测均显著相关,且对浅层的模拟优于深层,但模拟结果比台站观测系统性偏大。模拟与再分析资料和微波遥感资料土壤湿度的空间分布具有一致性,均表现为从青藏高原的西北部向东南部逐渐增加的分布特点,三江源湿地和高原东南部为土壤湿度的高值区,柴达木盆地和新疆塔里木盆地的沙漠地区为低值区,土壤湿度由浅层向深层增加。土壤湿度的长期变化趋势基本表现为“变干—变湿”相间的带状分布,不同层次的土壤湿度变化趋势基本一致。模拟资料也合理地再现了夏季土壤湿度逐月的变化:高原西南地区的土壤湿度明显大范围增加,北部的柴达木盆地的干旱范围也明显的向北收缩,高原南部外围土壤湿度也明显增加,CLM4.5模拟土壤湿度比再分析资料和微波遥感资料更加细致地描述了夏季逐月土壤湿度空间分布及其变化特征。     

An improvement of soil temperature simulations on the Tibetan Plateau

The simulation of soil temperature on the Tibetan Plateau (TP) plays a dominant role in the performance of both global climate and numerical weather forecast models. To improve the simulation of soil temperature on the TP, the Johansen soil thermal conductivity parameterization scheme was introduced into Community Land Model 3.5 (CLM3.5) and Regional Climatic Model 4 (RegCM4). The improved CLM3.5 and RegCM4-CLM were utilized to conduct offline and regional simulation experiments on the TP. Comparison of the new and old schemes revealed that CLM3.5 provides high thermal conductivity parameters of mineral soil solid on the TP. The Johansen scheme is more practical for the TP than the soil thermal conductivity parameterization in CLM3.5. The simulation of soil temperature and liquid water content was improved in offline experiment. The improved parameterization scheme can also reduce the simulation error of soil temperature in winter throughout the entire TP.     

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.     

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.     

华北平原冬小麦—夏玉米轮作区DLM与CLM5模型模拟对比研究

作物生长与气候的互馈是当前气候变化研究的热点之一。陆面模型作为一项重要的研究工具,其模型框架、算法设计及参数化方案的不同会直接导致模拟结果的不确定性。为探究陆面模型DLM(dynamic land model)和CLM5(community land model)在作物生长及农田热通量模拟方面的差异及原因,评估2个模型在华北平原作物研究中的适用程度,论文开展了冬小麦—夏玉米轮作站点的模拟对比研究。结果显示,DLM的夏玉米叶面积指数和生态系统总初级生产力的模拟值更高,与观测值更为接近;CLM5模型则在冬小麦模拟中略优。DLM的潜热模拟值与观测值的相关性普遍更高,可能反映了DLM采用的彭曼公式、双叶策略比CLM5采用基于水势梯度质量守恒、大叶策略的潜热计算方法更具优势。对于产量,模型当前的估测能力并不理想。总的来说,在默认设定下,2个模型的模拟结果能基本反映研究区农田站点内夏玉米和冬小麦的生长规律,但与实测值存在一定偏差。模型在该区域的适用性可能需要通过添加农田管理措施、算法优化和参数本地化等方式进一步提高。     

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...     

Evaluation of evapotranspiration models over semi‐arid and semi‐humid areas of China

Evapotranspiration (ET) is a critical component in the hydrological cycle. However, its actual values appear to be difficult to obtain, especially in areas in which precipitation has high inter‐annual variability. Here, we evaluated eight commonly used ET models in semi‐arid and semi‐humid areas of China. The order of overall performance from best to worst is as follows: the revised Priestley–Taylor model (PT‐JPL, 0.71, 1.65 [18.37%], 4.72 [49.19%]) a a Statistics (model abbreviation, coefficient of determination, bias [relative value], standard deviation [relative value]).
, the modified PT‐JPL model (M1‐PT‐JPL, 0.67, ?0.68 [7.56%], 3.87 [40.31%]), the Community Land Model (CLM, 0.68, ?2.52 [28.01%], 5.10 [53.17%]), the modified PT‐JPL model (M2‐PT‐JPL, 0.63, 0.57 [6.27%], 5.04 [52.52%]), the revised Penman–Monteith model (RS‐PM, 0.62, 3.56 [37.40%], 6.11 [63.68%]), an empirical model (Wang, 0.59, ?1.04 [11.57%], 5.61 [58.43%]), the advection‐aridity model (AA, 0.55, 5.56 [61.78%], 7.45 [77.60%]), and the energy balance model (SEBS, 0.35, 5.11 [56.72%], 9.43 [98.18%]). The performance of all of the models is comparably poor in winter and summer, except for the PT‐JPL model, and relatively good in spring and autumn. Because of the vegetation control on ET, the Wang, RS‐PM, PT‐JPL, M1‐PT‐JPL, and M2‐PT‐JPL models perform better for cropland, whereas the AA model, SEBS model and CLM perform better for grassland. The CLM, PT‐JPL, and Wang models perform better in semi‐arid region than in semi‐humid region, whereas the opposite is true for SEBS and RS‐PM. The AA, M1‐PT‐JPL, and M2‐PT‐JPL models perform similarly in semi‐arid and semi‐humid regions. When considering the inter‐annual variability in precipitation, the Wang model has relatively good performance under only some annual precipitation conditions; the performance of the PT‐JPL and AA models is reduced under conditions of high precipitation; the two modified PT‐JPL models inherited the steady performance of the PT‐JPL model and improved the performance under conditions of high annual precipitation by the modification of the soil moisture constraint. RS‐PM is more appropriate for humid conditions. CLM and PT‐JPL models could be effectively applied to all precipitation conditions because of their good performance across a wide annual precipitation range. Copyright © 2016 John Wiley & Sons, Ltd.     

农作物分布对南水北调受水区域陆面过程模拟的影响

本文将中国陆面覆盖资料(CLCV)与全球农作物分布资料融合,获取了一套包含小麦、玉米和水稻这些农作 物分布的陆面覆盖资料(CLCV- 3C),并将该陆面覆盖资料以及CLCV 应用于陆面模式CLM针对南水北调受水区域 的数值模拟试验以探讨该区域农作物分布对陆面能量水分过程模拟的影响。结果显示,与原来没有区分这三种主 要农作物分布相比,考虑农作物分布后,小麦区模拟的多年平均净辐射、感热、径流会增加,而蒸散发会减少;玉米 区和水稻区的多年平均净辐射、感热、蒸散发均会增加,而径流会减少。这些研究表明,农作物分布对南水北调受水 区域陆面水分能量过程有不可忽视的影响。     

陆面过程模式CLM4.5在半干旱区退化草原站的模拟性能评估

利用国际协同强化观测期(CEOP)在中国半干旱区退化草地站——通榆站的观测资料,对一个较为完善的陆面过程模式NCAR_CLM4.5(Community Land Model 4.5)的模拟性能进行检验。模拟结果与观测资料的对比表明,CLM4.5能很好地模拟出观测站点的辐射通量、水热交换、土壤温湿的空间分布和时间变化特征。但地表吸收的辐射模拟值略低,土壤湿度偏低,地表吸收的辐射及土壤温度等日变化略大;大气强迫变量处于某些特定的形势下时,模拟存在较大误差,如8月底的模拟。此外,冬季辐射通量、水热交换以及土壤温湿的模拟均存在较大误差,说明CLM4.5模式在冬季地表物理过程的参数化方案上需要进一步改进。