A land data assimilation system using the MODIS-derived land data and its application to numerical weather prediction in East Asia

Land Data Assimilation Systems have been developed to generate the surface initial conditions such as soil moisture and temperature for better prediction of weather and climate. We have constructed Korea Land Data Assimilation System (KLDAS) based on an uncoupled land surface modeling framework that integrates high-resolution in-situ observation, satellite data, land surface information from the WRF Preprocessing System (WPS) and the MODIS land products over the East Asia. To present better surface conditions, the KLDAS is driven by atmospheric forcing data from the in-situ rainfall gauges and satellite. In this study, we 1) briefly introduce the KLDAS, 2) evaluate the meteorological states near the surface and the surface fluxes reproduced by the KLDAS against the in-situ observation, and then 3) examine the performance of the mesoscale model initialized by the KLDAS. We have generated a 5-year, 10 km, hourly atmospheric forcing dataset for use in KLDAS operating across East Asia. The KLDAS has effectively reproduced the observed patterns of soil moisture, soil temperature, and surface fluxes. Further scrutiny reveals that the numerical simulations incorporating the KLDAS outputs show better agreement in both the simulated near-surface conditions and rainfall distribution over the Korean Peninsula, compared to those without the KLDAS.     

不同陆面模式对我国地表温度模拟的适用性评估

基于CLDAS大气驱动数据驱动CLM3.5陆面模式和3种不同参数化方案下的Noah-MP陆面模式模拟得到的地表温度,利用中国气象局2009-2013年2000多个国家级地面观测站地表温度进行质量评估。结果表明:从时间分布看,模拟地表温度与观测的偏差及均方根误差均呈季节性波动;从空间分布看,模拟地表温度与观测的偏差及均方根误差在中国东部地区相对于中国西部地区更小。选择Noah-MP陆面模式3种不同参数化方案模拟结果进行对比,结果表明:Noah-MP模式的非动态植被方案不变时,考虑植被覆盖度的二流近似辐射传输方案的Noah-MP陆面模式模拟的地表温度优于考虑太阳高度角和植被三维结构的二流近似辐射传输方案Noah-MP陆面模式模拟的地表温度;选择动态植被方案的Noah-MP陆面模式模拟的地表温度优于选择非动态植被方案的Noah-MP陆面模式;总体而言,考虑动态植被方案的Noah-MP陆面模式模拟的地表温度优于其他两种参数化方案的Noah-MP陆面模式以及CLM3.5陆面模式模拟的地表温度。     

内蒙古地区下垫面变化对土壤湿度数值模拟的影响

利用第二次全国土壤调查土壤质地数据（SNSS）和中国区域陆地覆盖资料（CLCV）将陆面过程模式CLM3.5（Community Land Model version 3.5）中基于联合国粮食农业组织发展的土壤质地数据（FAO）和MODIS卫星反演的陆地覆盖数据（MODIS）进行了替换,使用中国气象局陆面数据同化系统（CMA Land Data Assimilation System,CLDAS）大气强迫场资料,分别驱动基于同时改进土壤质地和陆地覆盖数据的CLM3.5（CLM-new）、基于只改进陆地覆盖数据的CLM3.5（CLM-clcv）、基于只改进土壤质地数据的CLM3.5（CLM-snss）和基于原始下垫面数据的CLM3.5（CLM-ctl）,对内蒙古地区2011～2013年土壤湿度的时空变化进行模拟试验,研究下垫面改进对CLM3.5模拟土壤湿度的影响。将四组模拟结果与46个土壤水分站点观测数据进行对比分析,结果表明:相对于控制试验,CLM-clcv、CLM-snss和CLM-new都能不同程度地改进土壤湿度模拟,其中CLM-clcv主要在呼伦贝尔改进明显,CLM-snss则在除呼伦贝尔以外的大部地区改进显著,CLM-ctl模拟的土壤湿度在各层上均系统性偏大,而CLM-new模拟土壤湿度最好地反映出内蒙古地区观测的土壤湿度的时空变化特征,显著改善了土壤湿度的模拟,体现在与观测值有着更高的相关系数和更小的平均偏差与均方根误差。     

基于陆面模式基准平台ILAMB对陆面模式CoLM的评估

模式评估是模式发展中不可或缺的重要一环。本文利用最新版陆面模式评估软件—ILAMB（International Land Model Benchmarking）对通用陆面模式 (The Common Land Model, CoLM)进行客观评估,并与NCAR陆面模式CLM5(Community Land Model version 5)结果进行比较。作为一个陆面模式评估软件,ILAMB能对参与评估的模式变量自动生成诊断图形并对模式性能进行评分。评估结果表明,CoLM总体性能良好,模拟结果与基准数据较为接近。与CLM5相比,CoLM在总初级生产力及水文方面的表现略微逊色,在辐射方面则表现相当,对部分变量如地表向上长波辐射、地表净辐射等的模拟甚至优于CLM5。通过对比CRUNCEPv7和GSWP3v1两种强迫资料发现,它们在气候平均态上具有一定的差异,模式在GSWP3v1强迫下的表现相对较好。CoLM和CLM5在CRUCNEPv7强迫下模拟的潜热通量在亚马逊平原、亚洲东部和南部地区以及北美东部一带正偏差显著,而在GSWP3v1强迫下的模拟则有明显改善。这两个模式对感热通量的模拟在非洲北部、亚洲中部一带均明显偏高。在辐射方面,CoLM模拟的地表向上短波辐射在全球以偏高为主,这在一定程度上造成了地表净辐射的模拟偏低。各组试验模拟的地表向上长波辐射得分相差不大,但在具体的空间分布上有一定的差别。     

A 10-Yr Global Land Surface Reanalysis Interim Dataset (CRA-Interim/Land): Implementation and Preliminary Evaluation

A land surface reanalysis dataset covering the most recent decades is able to provide temporally consistent initial conditions for weather and climate models, and thus is crucial to verifying/improving numerical weather/climate forecasts/predictions. In this paper, we report the development of a 10-yr China Meteorological Administration (CMA) global Land surface ReAnalysis Interim dataset (CRA-Interim/Land; 2007–2016, 6-h intervals, approximately 34-km horizontal resolution). The dataset was produced and evaluated by using the Global Land Data Assimilation System (GLDAS) and NCEP Climate Forecast System Reanalysis (CFSR) global land surface reanalysis datasets, as well as in situ observations in China. The results show that the global spatial patterns and monthly variations of the CRA-Interim/Land, GLDAS, and CFSR climatology are highly consistent, while the soil moisture and temperature values of the CRA-Interim/Land dataset are in between those of the GLDAS and CFSR datasets. Compared with ground observations in China, CRA-Interim/Land soil moisture is comparable to or better than that of GLDAS and CFSR datasets for the 0-10-cm soil layer and has higher correlations and slightly lower root mean square errors (RMSE) for the 10-40-cm soil layer. However, CRA-Interim/Land shows negative biases in 10-40-cm soil moisture in Northeast China and north of central China. For ground temperature and the soil temperature in different layers, CRA-Interim/Land behaves better than the CFSR, especially in East and central China. CRA-Interim/Land has added value over the land components of CRA-Interim due to the introduction of global precipitation observations and improved soil/vegetation parameters. Therefore, this dataset is potentially a critical supplement to the CRA-Interim. Further evaluation of the CRA-Interim/Land, assimilation of near-surface atmospheric forcing variables, and extension of the current dataset to 40 yr (1979–2018) are in progress.     

CLDAS和GLDAS土壤温度数据在陕西省的适用性评估

利用陕西省2016年97站逐日5cm土壤温度观测数据,结合相关系数、平均偏差和均方根误差等统计参数,评估了中国气象局陆面数据同化系统CLDAS2.0和美国全球陆面数据同化系统不同陆面模式(Noah-GLDAS2.1,Noah-GLDAS1,CLM-GLDAS1)土壤温度数据在陕西省的适用性。结果表明:(1)CLDAS2.0在陕西省的相关系数最高,均方根误差最小,Noah-GLDAS2.1次之,Noah-GLDAS1最差。(2)从陕西省3个区域的时间演变序列的分析可以看到,CLDAS2.0和Noah-GLDAS2.1能很好模拟出土壤温度的季节变化以及日变化,Noah-GLDAS1、CLMGLDAS1对于日变化的模拟较差,且前两者偏差也明显小于后两者。(3)Noah-GLDAS2.1在陕北与关中地区土壤温度模拟能力与CLDAS2.0相差无几,但在陕南地区CLDAS2.0要好于Noah-GLDAS2.1。总体来看,CLDAS2.0对陕西省土壤温度模拟能力最好,在陕西省有着更好的适用性。     

Regional and Global Land Data Assimilation Systems: Innovations,Challenges, and Prospects

Since the North American and Global Land Data Assimilation Systems(NLDAS and GLDAS) were established in2004, significant progress has been made in development of regional and global LDASs. National, regional, projectbased, and global LDASs are widely developed across the world. This paper summarizes and overviews the development, current status, applications, challenges, and future prospects of these LDASs. We first introduce various regional and global LDASs including their development history and innovations, and then discuss the evaluation, validation, and applications(from numerical model prediction to water resources management) of these LDASs. More importantly, we document in detail some specific challenges that the LDASs are facing: quality of the in-situ observations, satellite retrievals, reanalysis data, surface meteorological forcing data, and soil and vegetation databases; land surface model physical process treatment and parameter calibration; land data assimilation difficulties; and spatial scale incompatibility problems. Finally, some prospects such as the use of land information system software, the unified global LDAS system with nesting concept and hyper-resolution, and uncertainty estimates for model structure,parameters, and forcing are discussed.     

An Assessment of CAMS-CSM in Simulating Land–Atmosphere Heat and Water Exchanges

The Chinese Academy of Meteorological Sciences (CAMS) has been devoted to developing a climate system model (CSM) to meet demand for climate simulation and prediction for the East Asian region. In this study, we evaluated the performance of CAMS-CSM in regard to sensible heat flux (H), latent heat flux (LE), surface temperature, soil moisture, and snow depth, focusing on the Atmospheric Model Intercomparison Project experiment, with the aim of participating in the Coupled Model Intercomparison Project phase 6. We systematically assessed the simulation results achieved by CAMS-CSM for these variables against various reference products and ground observations, including the FLUXNET model tree ensembles H and LE data, Climate Prediction Center soil moisture data, snow depth climatology data, and Chinese ground observations of snow depth and winter surface temperature. We compared these results with data from the ECMWF Interim reanalysis (ERA-Interim) and Global Land Data Assimilation System (GLDAS). Our results indicated that CAMS-CSM simulations were better than or comparable to ERAInterim reanalysis for snow depth and winter surface temperature at regional scales, but slightly worse when simulating total column soil moisture. The root-mean-square differences of H in CAMS-CSM were all greater than those from the ERA-Interim reanalysis, but less than or comparable to those from GLDAS. The spatial correlations for H in CAMS-CSM were the lowest in nearly all regions, except for North America. CAMS-CSM LE produced the lowest bias in Siberia, North America, and South America, but with the lowest spatial correlation coefficients. Therefore, there are still scopes for improving H and LE simulations in CAMS-CSM, particularly for LE.     

长时间序列多源土壤湿度产品在中国地区的比较分析

研究利用实测数据对遥感产品(ECV CCI)、全球陆面同化系统产品(GLDAS/CLM、NOAH2.7、NOAH3.3、VIC、MOSAIC)、再分析资料(ERA-Interim、NCEP/DOE)等不同来源的8套长时间序列土壤湿度产品进行时空比较。结果表明:上述产品均可以模拟出中国不同区域土壤湿度的空间分布;从各产品平均态与实测数据的偏差、均方根误差、相关系数统计结果来看,NOAH模式和ERA-Interim表现最好,MOSAIC和NCEP/DOE与实测相差较大;从区域尺度上来看,所有产品在东北区域表现最好,在华南、西南南区和西北西区较差;ERA-Interim有效的模拟了土壤湿度的年际变化。     

通用陆面模式CLM在东亚不同典型下垫面的验证试验

利用野外观测资料,考察了通用陆面过程模式(CLM)对东亚地区3种典型下垫面(高原稀疏植被下垫面、森林、水田)的模拟能力.验证结果表明,在高原稀疏植被下垫面,CLM模拟的地表气温跟实测较为接近,同时CLM还可以较好地模拟出土壤温度随时间和深度的变化特征,但模式模拟的地面温度的幅值跟观测相比显著偏小;对于能量通量而言,除感热通量外,CLM所模拟出的其它能量通量的变化均与观测实况比较一致.对于淮河流域的森林下垫面,CLM所模拟出陆气间的各能量通量均与实测较为接近,尤以夏季(8月份)的模拟性能最好.对于水田下垫面,CLM模式较好地模拟出了各能量通量的主要变化特征及其季节差异,如水田的净辐射以及潜热通量夏季最大,而感热通量则是秋季最大等.     

基于HRCLDAS/CLM陆面数据同化系统的青藏高原地区土壤湿度模拟研究

利用最新的高时空分辨率（1 km、1 h）的中国气象局高分辨率陆面数据同化系统（HRCLDAS-V1.0）大气近地面强迫资料,驱动由NCAR发展的通用陆面模式（CLM）,对青藏高原地区2015年1月1日至9月30日的土壤湿度开展了模拟研究。结果表明模拟得到的高时空分辨率（1 km、1 h）土壤湿度能够体现出青藏高原地区从东南向西北逐渐变低的空间分布特征,较好地表现出各层土壤湿度的时间变化特征,6~9月土壤湿度波动较大,1~5月波动较平缓,上层土壤湿度变幅较大,深层变化较平缓。0~5 cm、0~10 cm和10~40 cm深度土壤湿度模拟结果与观测值的相关系数均在0.8以上,其中0~5 cm土层的相关系数达到0.92,各层土壤湿度观测值与模拟值的均方根误差变化则相反,3个土层土壤湿度模拟结果与观测值的偏差均小于0.04 mm3 mm-3,但模式对于研究时段土壤湿度变化的低值有高估现象,且模拟能力随着土层深度的加深而减弱。     

基于CLDAS资料的内蒙古干旱监测分析

以内蒙古地区为研究区域,对中国气象局陆面数据同化系统（CMA Land Data Assimilation System,CLDAS）的土壤湿度和降水数据进行了评估,使用土壤相对湿度法和连续无降水日数法监测2014年夏季干旱,并选择干旱年（2014年）和湿润年（2013年）与标准化降水指数和降水百分位指数法进行验证分析。结果表明：CLDAS资料能够很好地再现日土壤相对湿度动态变化情况和降水落区与量级,能够满足干旱监测的需求;基于CLDAS数据的土壤相对湿度法可以方便、快捷地监测干旱日变化和区域性变化,连续无有效降水日数法对评估长时间、持续性干旱较为有效;CLDAS同化数据在时效性、分辨率、代表性上能够满足气象服务的需求,可作为观测资料的重要补充广泛应用于业务和科研,特别是对于地广人稀且气象站点相对较少的内蒙古地区气象服务潜力巨大。     

Comparisons of Simulations of Soil Moisture Variations in the Yellow River Basin Driven by Various Atmospheric Forcing Data Sets

Based on station observations, The European Centre for Medium-Range Weather Forecasts reanalysis (ERA40), the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and Princeton University's global meteorological forcing data set (Princeton), four atmospheric forcing fields were constructed for use in driving the Community Land Model version 3.5 (CLM3.5). Simulated soil moisture content throughout the period 1951-2000 in the Yellow River basin was vali...     

ＣＬＭ３０对中国区域陆面过程的模拟试验 及评估Ⅱ：土壤湿度

利用NCAR公用陆面模式（Community Land Model 3.0,CLM3.0）及普林斯顿大学1948—2001年1°×1°、3 h一次的全球大气近地面强迫资料,对中国地区1948-2001年的土壤温度进行了off-line模拟试验,通过对模拟结果和全国台站观测土壤温度资料的对比,评估了CLM3.0对中国区域不同层次土壤温度的模拟能力。结果表明：模式能模拟出中国地区多年平均土壤温度的空间分布型,除部分地区模拟比观测偏高外,模式模拟的土壤温度普遍偏低;模式能较好地反映出中国地区土壤温度的年际变化,对4月的模拟稍好于7月。对于划分的8个子区域,东部区域模拟好于其它各区,除高原一带外,表层的模拟均好于深层;模式基本能抓住土壤温度的变化趋势,而且模拟出了7月长江流域以南地区土壤温度显著降低这一趋势,但模拟的趋势比观测有所偏弱。     

The coupling of the Common Land Model (CLM0) to a regional climate model (RegCM)

Summary We replace the existing land surface parameterization scheme, the Biosphere-Atmosphere Transfer Scheme (BATS), in a regional climate model (RegCM) with the newly developed Common Land Model (CLM0). The main improvements of CLM0 include a detailed 10-layer soil model, the distinction between soil ice and water phases, a linked photosynthesis-stomatal conductance model, a multilayer snow model, and an improved runoff parameterization. We compare the performance of CLM0 and BATS as coupled to the RegCM in a one year simulation over East Asia. We find that the RegCM/CLM0 improves the winter cold bias present in the RegCM/BATS simulation. With respect to the surface energy balance, lower CLM0 albedos allow the absorption of more solar radiation at the surface. CLM0 tends to simulate higher sensible heat and lower latent heat fluxes than its BATS counterpart. The surface water balance also changes considerably between the two land surface schemes. Compared to BATS, CLM0 precipitation is reduced overall and surface runoff is increased, thereby allowing less water to enter the soil column. Evapotranspiration is lower in CLM0 due to lower ground evaporation, which leads to a wetter surface soil in CLM0 in spite of less precipitation input. However, transpiration is greater in CLM0 than BATS, which has an overall effect of less surface storage during the summertime. Comparison with station observations indicates that CLM0 tends to improve the simulation of root zone soil water content compared to BATS. Another pronounced difference between the two schemes is that CLM0 produces lower snow amounts than BATS because of different snow models and warmer CLM0 temperatures. In this case, BATS snow cover amounts are more in line with observations. Overall, except for the snow amounts, CLM0 appears to improve the RegCM simulation of the surface energy and water budgets compared to BATS.     

CLDAS融合土壤相对湿度产品适用性评估及在气象干旱监测中的应用

基于2008—2017年全国自动气象观测站逐旬土壤相对湿度观测数据,综合评估中国气象局陆面数据同化系统（CMA Land Data Assimilation System,CLDAS）0～20 cm层融合土壤相对湿度产品在中国地区的适用性,评估表明CLDAS土壤相对湿度产品在中国东北、西北、江南大部及华南等地区存在较大系统性误差,总体上适用性较差。为消除CLDAS土壤相对湿度产品的系统性误差,采用回归订正法、7旬滑动平均订正法和临近加权前旬订正法对CLDAS土壤相对湿度产品进行误差订正处理,对订正结果评估发现：订正处理后CLDAS土壤相对湿度产品与站点观测的相关性显著增加,系统偏差基本消除,适用性明显提高,3种订正方法中临近加权前旬订正法的订正效果最优。最后,采用经不同方法订正后的CLDAS土壤相对湿度产品对2017年5月东北—华北地区一次气象干旱个例进行重现,对比验证表明：相对其他两种订正方法,经临近加权前旬订正法处理后的CLDAS土壤相对湿度产品能更为精准地重现2017年5月东北—华北地区气象干旱的落区和强度。〖JP〗     

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。     

Evaluation of the Community Microwave Emission Model Coupled with the Community Land Model over East Asia

The Community Microwave Emission Model (CMEM) developed by the European Centre for Me-dium-Range Weather Forecasts (ECMWF) can provide a link between surface states and satellite observations and simulate the passive microwave brightness temperature of the surface at low frequencies (from 1 GHz to 20 GHz).This study evaluated the performance of the CMEM cou-pled with the Community Land Model (CLM) (CMEM-CLM) using C-band (6.9 GHz) microwave brightness temperatures from the Advanced Microwave Scanning Radiometer on Earth Observing System (AMSR-E) over East Asia.Preliminary results support the argument that the simulated brightness temperatures of CMEM-CLM from July 2005 to June 2010 are comparable to AMSR-E observational data.CMEM-CLM performed better for vertical polarization,for which the root mean square error was approximately 15 K,compared to over 30 K for horizontal polarization.An evaluation performed over seven sub-regions in China indicated that CMEM-CLM was able to capture the temporal evolution of C-band brightness temperatures well,and the best correlation with AMSR-E appeared over western Northwest China (over 0.9 for vertical polarization).However,larger biases were found over southern North China and the middle and lower reaches of the Yangtze River.     

根系吸水过程参数化方案对青藏高原陆面过程模拟的影响研究

根系吸水过程对地表能量平衡和水循环起着重要作用，目前不同的根系吸水过程参数化方案对青藏高原陆面过程模拟的影响尚不明确，探讨相关参数化方案的影响，可以为今后建立陆面过程模式根系参数化方案提供参考。本文利用2010年6月1日至9月30日青藏高原玛曲站的观测资料作为大气强迫资料，驱动BCC_AVIM模式（北京气候中心陆面模式）引入不同的根系吸水过程参数化方案，对玛曲站2010年6月1日至9月30日时段感热通量、潜热通量、土壤温度、土壤含水量等要素进行数值模拟，分析根系吸水过程参数化方案对青藏高原地区陆面过程的影响。模式中有关根系吸水过程的参数化方案主要分为根分布模型和土壤水分对根系有效性函数两类，根分布模型用Jackson方案、Schenk方案替换，土壤水分对根系有效性函数用Li方案、LSM1.0方案、CLM4.5方案替换。对比结果表明:不同的根系吸水过程参数化方案对土壤温度、土壤含水量的模拟影响较小，对感热通量、潜热通量模拟影响较大，尤其对冠层蒸腾量模拟差异显著，相关参数化方案的变动直接影响冠层蒸腾量。两类方案模拟的差异受降水的影响，在多雨期，根分布对比方案与原模式方案模拟的感热、潜热通量间存在较大差异；在少雨期，土壤水分对根系有效性函数对比方案与原模式方案模拟的感热、潜热通量间存在较大差异。     

改进的CLDAS降水驱动对中国区域积雪模拟的影响评估

积雪因为其特定的属性在气候变化和水文循环中扮演着重要角色,在大气和陆面之间起到了调节能量和水交换的显著作用,而陆面驱动数据的质量直接决定着模式对积雪的模拟效果。本文采用CLDAS(CMA Land Data Assimilation System)和改进后的降水驱动(CLDAS-Prcp)分别驱动Noah3.6陆面模式对积雪变量进行模拟,并对中国主要的积雪区东北区域、新疆区域、青藏高原区域的积雪覆盖率、雪深、雪水当量的模拟效果进行了评估。结果表明,CLDAS-Prcp改善了原有驱动在冬季由于低估降水所造成的模拟积雪量偏少的情况;东北区域模拟结果与观测的时间变率最为一致,积雪覆盖率、雪深、雪水当量的相关系数分别为0.42,0.78,0.93;而雪水当量的改进效果最明显,均方根误差和偏差分别减小了54.8%和83.1%,相关系数提高了0.47;同时,CLDAS-Prcp不仅能反映积雪变量的年际变率,而且能够较准确地反映出强度较大的突发降雪事件。