两种陆面模式对中国区域土壤温度模拟的对比分析

为研究不同陆面模式对中国区域土壤温度的模拟效果,基于中国气象局陆面数据同化系统（CMA Land Data Assimilation System,CLDAS）大气驱动数据分别驱动Noah和Noah-MP陆面模式进行中国区域土壤温度的模拟（简称:CLDAS_Noah和CLDAS_Noah-MP试验）,使用2010—2018年中国气象局2380个土壤温度观测站点10和40 cm观测数据以及美国全球陆面数据同化系统（The Global Land Data Assimilation System,GLDAS）驱动的Noah模式（GLDAS_Noah试验）模拟的土壤温度结果,从空间分布、季节、分区等角度进行了评估,实现了不同驱动数据相同陆面模式和相同驱动数据不同陆面模式的对比分析。结果表明: GLDAS_Noah、CLDAS_Noah和CLDAS_Noah-MP试验均能合理模拟出中国区域土壤温度空间分布,但在量级上有一定差异,主要表现在中国东北、新疆、青藏高原等积雪区。对于相同陆面模式不同驱动数据,均方根误差显示CLDAS_Noah试验在季节与分区上均优于GLDAS_Noah试验,间接表明CLDAS大气驱动数据优于GLDAS大气驱动数据,且大气驱动数据是提高土壤温度模拟精度的重要因素之一;对于相同驱动数据不同陆面模式,总体上CLDAS_Noah-MP试验棋拟效果优于CLDAS_Noah试验,其中CLDAS_Noah试验模拟的10和40 cm深度土壤温度在冬季积雪区误差明显大于CLDAS_Noah-MP试验,可能与Noah-MP模式改进了积雪方案有关,但10和40 cm深度下CLDAS_Noah-MP试验在东北、华北、青藏高原地区对春季土壤温度模拟误差明显大于CLDAS_Noah试验,可能与Noah-MP模式融雪方案有关。总之,本研究对于后续开展土壤温度多模式集成、土壤温度站点资料同化,最终研制中国区域高质量土壤温度数据集具有一定的参考意义。      

陆面过程模式对土壤含水量初值的敏感性研究

利用IAP94陆面过程模式,采用淮河流域能量与水份循环试验(HUBEX)期间两种下垫面(森林和旱田)、不同季节(5月、8月和11月)的观测资料,研究了模式对土壤含水量初值的敏感性.结果表明:对于森林和旱田下垫面,当土壤含水量减少时,地表净辐射均略有减少,同时潜热通量减少而感热通量增加.另外,模式对土壤含水量初值的敏感性有较明显的季节差异,相对而言在晚春和夏季较强,而在秋季明显减弱.这说明春夏季节的土壤含水量初值在淮河流域区域气候的模拟和预测中尤其值得关注.     

基于历史样本投影的四维变分陆面数据同化方法及其初步应用

法面临着计算量上的挑战。本研究将一种历史样本投影的四维变分同化方法(Historical-Sample-Projection4DVar,简写为HSP-4DVar)应用于陆面数据同化,建立起CoLM陆面模型的HSP-4DVar系统。相比其他四维变分同化方法,HSP-4DVar的分析值是显式求解,不需要编写和使用伴随模式,从而大大节省了计算量,是一种易于实现的同化方案。通过同化56个月的土壤湿度观测数据表明,新的陆面同化系统不仅省时,而且能够有效吸取观测信息,使得同化后的均方根误差显著降低,各层土壤湿度模拟都有所改善,陆表1000mm层的改善最为明显。     

利用NOAA/AMSU资料和GRAPES同化系统对陆面比辐射率计算的改进研究

地表比辐射率计算的不确定性,直接影响到卫星资料在数值预报中同化应用的效果。本文采用美国NOAA/NESDIS的Weng等[1,2]提出的复杂陆面比辐射率模式,同时用NOAA卫星AMSU-ACh1或Ch2反演的地表比辐射率来调整该模式所需的地表参数,从而在缺少详细地表参数的情况下,改进AMSU-A Ch3和Ch15的地表比辐射率计算精度。在积雪地表情况下,用NOAA卫星AMSU-A资料直接反演各通道的比辐射率,在GRAPES同化系统中的应用表明,结果有明显的改进。     

GRAPES混合同化方法在青藏高原区域的初步试验

针对青藏高原地区气象观测站点稀少和模式同化分析质量较低的问题,将GRAPES区域集合变分(En-3DVAR)混合同化系统应用于青藏高原地区,进行了单点理想试验和真实观测资料同化分析预报试验,分析评估青藏高原混合同化分析增量及预报误差的水平垂直结构特征及其合理性,并与中国东部平原地区进行比对。单点理想试验表明,En-3DVAR混合同化系统中背景误差协方差具备流依赖属性。真实资料混合同化试验结果表明,基于集合预报估计的分析增量具有流依赖的特征,特别是在高原地区和槽脊系统附近;青藏高原地区分析场的绝对误差总体低于3DVAR系统,其平均绝对误差在中层和高层低于平原地区,说明在青藏高原地区的改进效果略优于平原地区。需要关注的是,青藏高原地区En-3DVAR混合同化分析增量总体大于3DVAR,特别是近地面层u风分量分析增量明显偏大,这可能与青藏高原复杂地形有关。     

地面观测资料同化在GRAPES模式中的应用研究

本文运用GRAPES_Meso业务模式(3.1版)通过四个同化地面不同观测要素方案及没有同化任何地面要素的控制试验对2012年7月初发生在四川的一次降水过程做了数值模拟,结果表明:五个模拟方案对不同区域不同量级的降水皆存在不同程度的空报和漏报现象,空报和漏报相对较严重的是控制试验和同化水平风场的同化方案,随着预报时效的增加各方案模拟可信度减小;四个同化方案的同化作用随着预报时效的增加表现出不稳定,相对较稳定的是同化所有地面观测要素的方案;在模式初期和后期,同化作用表现相对明显的是同化所有地面观测要素的方案,只同化水平风场的方案同化作用较小,同化中期各同化方案同化作用皆不稳定;随着预报时效的增加,几个模拟方案之间的差异程度越来越小,但同实况间的差异越来越大。     

陆面气温资料的一种推广三维变分同化方法及其在简化情形的检验

发展了一种同化窗口为1个月的陆面气温推广三维变分资料同化方法,并建立了逐日资料到月平均资料的观测算子.作为对该同化方法的初步检验,以2000年1月中国陆地区域时间分辨率低、空间分辨率较高且在高原地区与台站观测资料比较接近的CRU(Climate Research Unit)月平均陆面气温资料作为观测,以时间分辨率高、空间分辨率较低且在高原地区与台站资料有较大误差的NCEP逐日气温资料作为背景场,采用背景误差协方差矩阵(简称B矩阵)的两种简化对角形式进行同化试验,得到高时空分辨率的格点陆面气温分析场,并进行对比分析和均方根误差检验.结果显示,由两种简化形式得到的逐日资料和月平均资料的质量均得到改善,在我国东南和中部大部分地区与台站观测基本一致,在青藏高原、新疆等台站稀疏地区与地形对应良好,为M-SDGVM模型或其他陆面过程模式高质量陆面气象驱动场的准备提供了一种新的手段.尤其在B矩阵中考虑了方差逐日变化的简化形式所得到的分析场整体上要优于不考虑的,这为最终在B矩阵中考虑协方差(即对推广三维变分同化不作简化)进一步改进同化效果打下了基础.     

陆气相互作用及陆面模式的研究进展

较为全面地回顾了有关陆气相互作用的研究进展及陆面模式的发展现状，结合近年来开展的有关陆气相互作用的20多个大型国际研究计划和目前国内外具有代表性的陆面模式，分析了当前陆气相互作用及陆面模式研究中存在并有待进一步解决的问题，探讨了未来陆面模式的发展趋势。     

再分析资料和陆面数据同化资料土壤湿度产品在中国北方地区的适用性评估

土壤湿度是地球系统模拟的重要参数之一,准确获得其时空分布和变化特征是研究陆-气相互作用的基础。再分析资料和陆面数据同化资料均可提供全球或区域高分辨率土壤湿度产品,但在使用前需要对其进行评估分析。利用土壤湿度观测数据,计算ERA5、ERA5-Land、NCEP-DOE R2、CRA40再分析资料和GLDAS-Noah、GLDAS-CLSM、CLDAS陆面数据同化资料土壤湿度产品与观测数据的中位数、模拟偏差、相关系数等统计指标,并分季节和气候区讨论不同土壤湿度产品在中国北方地区的模拟效果。结果表明：整体来看,CRA40与观测值的相关性最好,ERA5和ERA5-Land分别对干中心、湿中心模拟效果更好,GLDAS-Noah对于较干土壤地区模拟略偏湿,CLDAS对较湿土壤地区模拟结果以系统性偏干为主,NCEP-DOE R2和GLDAS-CLSM模拟效果较差;ERA5、ERA5-Land、NCEP-DOE R2、GLDAS-Noah和CLDAS在所有季节均为模拟正偏差,春季模拟效果较好的是CRA40、ERA5-Land,夏季和秋季ERA5-Land、ERA5和CRA40与观测值相关性较好,不同产...     

基于集合卡尔曼滤波的土壤温湿度同化试验

以通用陆面模式CLM 3.0(Community Land Model 3.0)为模型算子,基于集合卡尔曼滤波(Ensemble Kalman Filter,En KF)发展了一个土壤温湿度同化系统,主要用于改进模式对土壤温湿度和地表水热通量的模拟精度,并考察集合样本数、同化频率及不同观测量的组合对同化效果的影响。该系统同化了FLUXNET两个站点(阿柔和Bondville)不同土壤深度、不同时间频率的土壤温度和湿度数据。通过对阿柔站不同集合样本数的设计,综合考虑计算成本和计算精度,最终将集合样本数设置为40。通过分析三种同化方案对同化频率的敏感性得出,同化土壤温度最为敏感,同时同化土壤温湿度次之,同化土壤湿度最不敏感。对于阿柔站点,同化系统对不同土壤深度温度和湿度的模拟精度均能提高90%,潜热通量的均方根误差由94.0 W·m~(-2)降为46.3 W·m~(-2),感热通量均方根误差由55.9 W·m~(-2)降为24.6 W·m~(-2)。Bondville站点浅层土壤温度的改进在30%左右,深层土壤温度改进达到60%,对土壤湿度的改进均在70%以上,潜热通量和感热通量的均方根误差分别从57.4 W·m~(-2)和54.4 W·m~(-2)降为51.0 W·m~(-2)和42.5 W·m~(-2)。试验结果表明,同化站点土壤温湿度数据对土壤水热状况及通量的模拟改进非常有效,同时也验证了同化土壤水分遥感产品的可行性和必要性。     

CoLM模式地表温度变分同化研究

本文采用变分方法对通用陆面模式 (CoLM) 中的地表温度进行同化.同化伴随约束条件采用CoLM模式中的地表及植被能量平衡方程,调节因子采用裸土及植被蒸发比.采用美国通量网 (AmeriFlux) 中的Bonville站数据对同化方法进行了单点验证,验证结果表明同化后地表温度以及蒸散结果更加接近于实测值.选取中国华北地区对同化方法进行区域验证,结果显示每天仅采用白天一次观测值对地表温度进行同化的方法是有效的.通过对同化前后地表温度误差直方图比较可以发现,在有MODIS观测值的区域,同化后白天地表温度误差大大降低,同时,同化后地表蒸散空间分布图也发生了变化.单点验证以及区域验证结果都表明了变分同化方法是可靠的.变分同化方法可以改进陆面模式模拟结果,对于地表过程研究中的植被生态、水文等研究具有重要意义,同时,陆面模式可以与数值预报模式进行耦合,改进数值预报结果.     

Influence of Surface Temperature and Emissivity on AMSU-A Assimilation over Land

AMSU-A (Advanced Microwave Sounding Unit-A) measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction (NWP) models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting (WRF) model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation (WRF-VAR) system, the surface parameters from the operational Microwave Surface and Precipitation Products System (MSPPS) are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error (RMSE) and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction (NCEP) global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.     

红外高光谱资料近地面通道应用

由于下垫面的复杂性,卫星近地面通道的辐射率资料没有得到充分开发和利用。就我国自主研发的GRAPES 3DVar而言,红外高光谱近地面通道资料还没有应用于陆地,即使在下垫面相对简单的海洋,由于背景场海表温度估计不够准确,红外高光谱资料的使用效果也不甚理想。针对GRAPES模式的背景场海表温度估计不够准确这一问题,本文利用大气红外探测仪器AIRS(The Atmospheric Infrared Sounder)辐射率观测资料通过一维变分（1DVar）方法对其晴空视场点内的背景场海表温度进行调整,再运用GRAPES全球分析预报系统进行同化分析,研究了海表温度调整后对分析场的影响。结果表明,利用一维变分调整后的海表温度不仅使得低层通道的模拟亮温与观测亮温更加匹配,而且有效地改进了分析场,对位势高度场高、中、低层均有不错的改进,对低层湿度场以及风场的改进也较为明显。     

Assimilation of Sea Surface Temperature in a Global Hybrid Coordinate Ocean Model

The Hybrid Coordinate Ocean Model(HYCOM) uses different vertical coordinate choices in different regions. In HYCOM, the prognostic variables include not only the seawater temperature, salinity and current fields, but also the layer thickness. All prognostic variables are usually adjusted in the assimilation when multivariate data assimilation methods are used to assimilate sea surface temperature(SST). This paper investigates the effects of SST assimilation in a global HYCOM model using the Ensemble Optimal Interpolation multivariate assimilation method. Three assimilation experiments are conducted from 2006–08. In the first experiment, all model variables are adjusted during the assimilation process. In the other two experiments, the temperature alone is adjusted in the entire water column and in the mixed layer. For comparison, a control experiment without assimilation is also conducted. The three assimilation experiments yield notable SST improvements over the results of the control experiment. Additionally, the experiments in which all variables are adjusted and the temperature alone in all model layers is adjusted, produce significant negative effects on the subsurface temperature. Also, they yield negative effects on the subsurface salinity because it is associated with temperature and layer thickness. The experiment adjusting the temperature alone in the mixed layer yields positive effects and outperforms the other experiments. The heat content in the upper 300 m and 300–700 m layers further suggests that it yields the best performance among the experiments.     

An Ensemble-Based Three-Dimensional Variational Assimilation Method for Land Data Assimilation

Land surface models are often highly nonlinear with model physics that contain parameterized discontinuities. These model attributes severely limit the application of advanced variational data assimilation methods into land data assimilation. The ensemble Kalman filter （EnKF） has been widely employed for land data assimilation because of its simple conceptual formulation and relative ease of implementation. An updated ensemble-based three-dimensional variational assimilation （En3-DVar） method is proposed for land data assimilation This new method incorporates Monte Carlo sampling strategies into the 3-D variational data assimilation framework. The proper orthogonal decomposition （POD） technique is used to efficiently approximate a forecast ensemble produced by the Monte Carlo method in a 3-D space that uses a set of base vectors that span the ensemble. The data assimilation process is thus significantly simplified. Our assimilation experiments indicate that this new En3-DVar method considerably outperforms the EnKF method by increasing assimilation precision. Furthermore, computational costs for the new En3-DVar method are much lower than for the EnKF method.     

Improvement of the Surface Pressure Operator in GRAPES and Its Application in Precipitation Forecasting in South China

In this study we investigated the problems involved in assimilating surface pressure in the current global and regional assimilation and prediction system, GRAPES. A new scheme of assimilating surface pressure was proposed, including a new interpolation scheme and a refreshed background covariance. The new scheme takes account of the differences between station elevation and model topography, and it especially deals with stations located at elevations below that of the first model level. Contrast experiments were conducted using both the original and the new assimilation schemes. The influence of the new interpolation scheme and the updated background covariance were investigated. Our results show that the new interpolation scheme utilized more observations and improved the quality of the mass analysis. The background covariance was refreshed using statistics resulting from the technique proposed by Parrish and Derber in 1992. Experiments show that the updated vertical covariance may have a positive influence on the analysis at higher levels of the atmosphere when assimilating surface pressure. This influence may be more significant if the quality of the background field at high levels is poor. A series of assimilation experiments were performed to test the validity of the new scheme. The corresponding simulation experiments were conducted using the analysis of both schemes as initial conditions. The results indicated that the new scheme leads to better forecasting of sea level pressure and precipitation in South China, especially the forecast of moderate and heavy rain.     

Validation of Land Surface Temperature Derived from 37-GHz AMSR-E over Northern China

A validation study of land surface temperature (LST) obtained from the Ka band (37 GHz) vertically polarized brightness temperature over northern China is presented.The remotely sensed LST derived jointly by the Vrije Universiteit Amsterdam and the NASA Goddard Space Flight Center (VUA-NASA) from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) were compared to the daily in-situ top soil temperature/infrared surface temperature observations from eleven/three Enhanced Coordinated Observation stations in arid and semi-arid regions of northern China.The VUA-NASA LST from the descending path exhibited a stronger correspondence to the in-situ infrared surface temperature than soil temperature observations,whereas correlations (R 2) of the latter ranged from 0.41 to 0.86.Meanwhile,the ascending overpass LST was generally warmer than the in-situ soil temperature observations at all stations,and the correlation (R 2) was between 0.07 and 0.72.Furthermore,the correlation of the descending path was generally greater than that of the ascending path at the same station.The descending path VUA-NASA LST was sensitive to precipitation and presented good agreement with ground temperature dynamics.The analyses demonstrated that the descending overpass LST was reliable to reflect reasonable patterns of temperature dynamics for land surface temperature in the region.     

MODIS反照率产品在模拟黄河源区陆面过程和降水中的应用

地表反照率是陆面过程中一个重要的物理量, 其变化直接影响地表能量的收支状况, 进而可以影响气温和降水等其它气象要素。本文利用WRF (Weather Research and Forecasting) 模式, 通过两组数值模拟试验分别探讨了地表反照率改变在黄河源区不同下垫面情况下潜热、 感热的分配关系, 详细分析了地表反照率改变对降水变化的影响机制, 最后应用EOS/MODIS地表反照率产品替代原模式低时空分辨率的地表反照率。研究结果表明: (1)当地表反照率减少(增加)时, 模拟的区域平均地表温度、感热、潜热数值相应增大(减少)。当地表反照率减少0.1时, 地表温度上升约1.0 K, 感热和潜热量增量比约为3∶1。 (2) 地表反照率改变对降水量变化影响最大的区域是黄河源区下游的草场区域, 其次是黄河源头区域, 最小的是黄河源区北部的稀疏植被区域。地表反照率通过对大气动力、 热力以及水汽条件的影响, 使得降水发生的环境改变, 主要体现在: 当地表反照率减少时, 地表气压的减少使得大气低层的辐合气流增强, 有利于上升运动的发生; 2.0 m气温的升高增强了大气近地层的热力不稳定度; 2.0 m比湿的增加表明近地层空气水汽含量增加。 (3) 与实况对比分析发现, 使用卫星遥感产品后在月尺度上能够更准确地模拟降水量的变化过程。