土壤质地对中国区域陆面过程模拟的影响

利用陆面过程模式(CLM3.5)和中国区域两种土壤质地数据(分别来自第二次中国土壤调查SNSS和联合国粮食农业组织FAO),研究了土壤质地变化对于模式模拟的陆表水热变量的影响。结果显示,土壤质地对土壤水文学变量的影响远大于对土壤热力学变量的影响,尤其是对于饱和土壤含水量和饱和水力传导率的影响。对于模式的输出,土壤质地影响比较明显的有土壤湿度、总径流和土壤渗透等水文学变量以及地表潜热、地表感热和土壤热通量等热力学变量,而影响相对较小的有地面吸收的太阳辐射和地表反照率。同时,发现基于SNSS模拟的土壤湿度与站点观测值更加接近。因此,本研究认为基于SNSS土壤质地数据可以有效地改进模式模拟结果,建议以后在陆面模式试验中尽可能使用以观测为基础的SNSS土壤质地数据。     

Evaluation of AMSR-E——Derived Soil Moisture over Northern China

In this study,the authors evaluated two re-motely sensed surface soil moisture datasets derived from the Advanced Microwave Scanning Radiometer of the Earth Observing System (AMSR-E) over northern China.The soil moisture datasets were derived from algorithms developed by the National Snow and Ice Data Center (NSIDC) and jointly developed by the Vrije Universiteit Amsterdam and NASA Goddard Space Flight Center (VUA-NASA).The NSIDC and VUA-NASA products were compared to in situ soil moisture data from nine enhanced coordinated observation stations.The VUA-NASA dataset presented a strong correlation with top layer in situ soil moisture observations,and the correla-tion coefficients ranged from 0.34 to 0.73 (p0.01).The correlation coefficients decreased as the observed soil layer depth increased.The correlation coefficients be-tween the NSIDC retrievals and the top layer in situ ob-servations were between 0.10 and 0.62 (p0.01).Fur-thermore,VUA-NASA soil moisture variations agreed well with in situ soil moisture dynamics and responded sensitively to precipitation events.In contrast,the NSIDC dataset failed to capture signals of soil moisture dynamics.The analyses demonstrated that the VUA-NASA product was capable of representing soil moisture conditions over northern China.     

长江中下游地区1988—2010年遥感土壤湿度的时空变化

利用农业气象站观测资料对长江中下游地区1988-2010年遥感土壤湿度进行了验证,并与NCEP和ERA-Interim土壤湿度做了对比分析。研究表明,ECV遥感土壤湿度冬季平均土壤湿度最高,春季和秋季次之,夏季平均土壤湿度最低;这种季节性干湿变化与农业气象站观测资料一致。但是,NCEP和ERA-Interim土壤湿度再分析资料,则夏季平均土壤湿度高,春季和秋季次之,而冬季平均土壤湿度最低;这种季节性变化与ECV遥感土壤湿度和农业气象站观测资料呈反位相。就年际变化而言,ECV遥感土壤湿度与农业气象站观测资料和两套再分析资料均有较高的一致性,并在春季和秋季最高,尤其是在长江以北地区和长江以南洞庭湖、鄱阳湖两大湖区,相关系数达到0.7~0.9;而夏季一致性最低,相关系数仅为0.4左右。在研究时段,ECV土壤湿度在冬季明显增加,在夏季则有明显下降趋势。     

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。     

基于风云三号气象卫星微波亮温资料反演东北地区土壤湿度及其对比分析

土壤湿度在陆面过程中发挥着重要作用,是联系陆地水循环和能量循环的纽带和关键环节。遥感技术可以实时地对土壤湿度进行长期、大区域动态监测,已成为监测土壤湿度的有效手段。本文基于风云三号气象卫星（FY3B）微波亮温资料,利用基于微波能量辐射传输方程的陆面参数反演模型（LPRM）反演了中国东北地区的土壤湿度（FY3B_LPRM）。把反演获得的FY3BLRPM土壤湿度与中国气象局农业气象站土壤湿度观测资料、NCEP和ERA-Interim土壤湿度再分析资料、欧洲空间局多卫星融合ECV（Essential Climate Variable）土壤湿度产品和国家卫星气象中心FY3B官方土壤湿度产品（FY3B_offical）进行了对比分析。结果表明:（1）本文反演的FY3B土壤湿度与农业气象站观测资料有较高的一致性;卫星土壤湿度整体上呈现自西向东逐渐增加的空间变化,与农业气象站观测资料较为一致;在季节变化上,两者高度相关,在大部分地区的相关系数都达到0.7以上。（2）在大兴安岭和东北三省东部等地表相对湿润的地区,FY3B_LPRM土壤湿度与NCEP、ERA-Interim和FY3B_offical土壤湿度呈现较强的负相关;再分析资料和FY3B_offical土壤湿度均无法反映该地区土壤干湿状况的季节性变化,甚至与观测资料呈反位相变化特征。FY3B_LPRM土壤湿度与欧洲空间局研发的多卫星融合ECV土壤湿度产品在绝大多数地区有较好的一致性。本文基于风云三号极轨气象卫星微波亮温反演的土壤湿度资料,可用于干旱监测、数值同化与天气预报、水文水资源等领域。     

Exploring spatiotemporal patterns and physical controls of soil moisture at various spatial scales

Soil moisture variability of various spatial scales is analyzed based on empirical orthogonal function (EOF) method using soil moisture datasets with various spatial resolutions: 1 km eco-hydrological model simulation, 0.25° passive microwave (Advanced Microwave Scanning Radiometer for the Earth Observing System, AMSR-E) dataset, and 0.5° land surface model simulation from Climate Predictor Center (CPC). All three datasets generate EOFs that explain similar variances with those generated from in situ observations from agro-meteorological network. Using AMSR-E product and eco-hydrological model simulation, it is found that the primary spatial pattern of soil moisture obtained from watershed scale has a strong connection to topographic attributes, followed by soil texture and rainfall variability, as suggested by the correlation between the primary EOF mode (EOF1) of soil moisture and landscape attributes. However, the EOF analysis of both AMSR-E and CPC datasets at regional scale reaches the conclusion that soil texture indices, such as sand and clay content, is of higher importance to soil moisture EOF1 spatial pattern (explaining 61 % variance) than topography is. Furthermore, correlation between soil moisture EOF1 and soil property is higher in spring than in autumn, which indicates that soil water-holding and drainage capabilities are more important under dry conditions. At national scale, the combined effects of topographic feature and soil property are clearly exhibited in EOF1. The study results reveal that different emphases should be placed on accurate acquisition of landscape attributes for soil moisture estimation according to various spatial scales.     

黄河源区土壤温湿和大气参量变化特征

利用中国科学院西北生态环境资源研究院玛曲土壤温湿观测网2008-2009年、2013-2014年数据验证了3套再分析资料ERA-Interim,CFSR（Climate Forecast System Reanalysis）和JRA-55（Japanese 55-year Reanalysis）在黄河源区的适用性,结合中国气象数据网玛曲气象站1980-2014年观测资料与CLM4.5（Community Land Model 4.5）进一步分析了黄河源区近35年气候变迁、土壤温湿分布和变化,结果表明:CFSR能够较好地描绘黄河源区土壤湿度变化,ERA-Interim对于土壤温度刻画能力更强,JRA-55效果较差;35年来气温、土壤温湿总体呈上升趋势且发生突变;近年来10 cm土壤温湿有暖干化趋势,降水量稍有增加,土壤冷季冻结周期变短,暖季持续时间拉长;CLM4.5模拟精度高,能够较好地刻画源区土壤温湿变化细节,两湖及黄河周边暖季为冷湿中心,冷季为暖干中心。     

辽宁省未来7d土壤墒情逐日滚动预报方法研究

基于气象台定量预报数据和自动土壤水分监测数据等实时和历史资料,采用土壤水分平衡原理,研究了辽宁省未来7 d土壤墒情逐日滚动预报方法。结果表明:预报模型稳定性好,能够较好地模拟出辽宁省未来7 d土壤墒情的定量演变趋势,首次实现了土壤墒情的定量化预报、精细化(县级)预报及逐日滚动预报。该方法成功实现的关键之处在于采用回归分析方法实现了气象台提供的预报要素和模型所用预报要素之间的转换。     

Trends and scales of observed soil moisture variations in China

A new soil moisture dataset from direct gravimetric measurements within the top 50-cm soil layers at 178 soil moisture stations in China covering the period 1981-1998 are used to study the long-term and seasonal trends of soil moisture variations, as well as estimate the temporal and spatial scales of soil moisture for different soil layers. Additional datasets of precipitation and temperature difference between land surface and air (TDSA) are analyzed to gain further insight into the changes of soil moisture. There are increasing trends for the top 10 cm, but decreasing trends for the top 50 cm of soil layers in most regions. Trends in precipitation appear to dominantly influence trends in soil moisture in both cases. Seasonal variation of soil moisture is mainly controlled by precipitation and evaporation, and in some regions can be affected by snow cover in winter. Timescales of soil moisture variation are roughly 1-3 months and increase with soil depth. Further influences of TDSA and precipitation on soil moisture in surface layers, rather than in deeper layers, cause this phenomenon. Seasonal variations of temporal scales for soil moisture are region-dependent and consistent in both layer depths. Spatial scales of soil moisture range from 200-600 km, with topography also having an affect on these. Spatial scales of soil moisture in plains are larger than in mountainous areas. In the former, the spatial scale of soil moisture follows the spatial patterns of precipitation and evaporation, whereas in the latter, the spatial scale is controlled by topography.     

中国土壤湿度的分布与变化 I. 多种资料间的比较

土壤湿度是影响气候的重要因子之一, 但观测资料的欠缺制约着该领域研究工作的开展。本文汇总了目前国际上运用较为广泛的四套土壤湿度资料: ERA40和NCEP/NCAR再分析资料、全球土壤湿度计划资料(GSWP2)、以及NCAR最近完成的利用观测资料强迫“通用陆面模式”CLM所产生的土壤湿度资料。在此基础上, 利用中国区域观测的19年 (1981～1999年) 的土壤湿度和13年 (1992～2004年) 的土壤相对湿度资料, 对四套资料在中国区域的可靠性进行了分析和比较, 主要结论如下: 四套资料基本揭示出土壤湿度的空间分布, GSWP2揭示了四套资料最多的共性, 即东北、 华南湿, 华北、 西北干, 土壤湿度基本由西北向东北和东南呈梯度增加的特征; GSWP2较好地描述了土壤湿度的季节循环; ERA40土壤湿度的年际变化与观测相关最好; 观测资料和四套资料都表明前期降水会增加土壤湿度, 但土壤湿度异常对后期降水的影响则不显著; 气温与土壤湿度的关系较复杂, 不同的区域有不同的特征。     

两套土壤湿度再分析资料在黑河流域的对比分析

利用黑河流域少量观测台站的实测降水和土壤湿度资料, 对比分析了欧洲中心ERA40及美国NCEP R-1两套常用的土壤湿度再分析资料在黑河流域的空间分布、 年际变化和季节循环特征, 结果表明:两套资料在黑河流域均能表现出“南湿北干”的分布格局, 湿度高值中心位于祁连山区东南部\.以此为中心, 土壤湿度从上游山区向中下游递减。ERA40土壤湿度在祁连山区年际变化明显, 与降水的响应关系要好于NCEP资料, 在中下游站点, NCEP 10 cm层土壤湿度对降水的响应好于ERA40。祁连站ERA40土壤湿度在6~8月接近观测值, 在额济纳站两套资料对于土壤湿度的描述都不理想。     

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.     

Remotely sensed soil moisture integration in an ecosystem carbon flux model. The spatial implication

While remote sensing is able to provide spatially explicit datasets at regional to global scales, extensive application to date has been found only in the reporting and verification of ecosystem carbon fluxes under the Kyoto Protocol. One of the problems is that new remote sensing datasets can be used only with models or data assimilation schemes adapted to include a data input interface dedicated to the type and format of these remote sensing datasets. In this study, soil water index data (SWI), derived from the ERS scatterometer (10-daily time period with a spatial resolution of 50 km), are integrated into the ecosystem carbon balance model C-Fix to assess 10-daily Net Ecosystem Productivity (NEP) patterns of Europe from the remote sensing perspective on an approximate 1-by-1 km² pixel scale using NDVI-AVHRR data. The modeling performance of NEP obtained with and without the assimilation of remotely sensed soil moisture data in the carbon flux model C-Fix is evaluated with EUROFLUX data. Results show a general decrease of the RRMSE of up to 11 with an average of 3.46. C-Fix is applied at the European scale to demonstrate the potential of this ecosystem carbon flux model, based on remote sensing inputs. More specifically, the strong impact of soil moisture on the European carbon balance in the context of the Kyoto Protocol (anthropogenic carbon emissions) is indicated at the country level. Results suggest that several European countries shift from being a carbon sink (i.e., NEP > 1) to being a carbon source (i.e., NEP < 0) whether or not short-term water availability (i.e., soil moisture) is considered in C-Fix NEP estimations.     

土壤数据集对全球陆面过程模拟的影响

基于通用陆面模式（Common Land Model, CoLM）,首次评估了两套最新的全球土壤数据集GSDE（Global Soil Dataset for Earth System Model）和SG（SoilGrids）对全球陆面过程模拟的影响。比较分析了两套数据中砂粒、粘粒、砾石、有机碳的含量和容重这五个土壤属性在全球分布上的差异以及这种差异造成的对模式估计的土壤特性参数、水力热力变量的影响。结果表明,土壤特性参数在全球的空间分布主要受土壤粒径分布（砂粒、粉粒和粘粒）影响,同时也受砾石、有机碳和容重的影响。土壤资料对全球模拟结果影响主要体现在区域差异,对水文学变量的影响（R_e最大达到±100%）大于对土壤热力学变量的影响（R_e<±10%）,对地表辐射变量的影响较小（R_e<±5%）。其中,土壤体积含水量在加拿大中部及西北部、俄罗斯东南部及中西部和澳大利亚中部地区模拟结果相差较大,总径流在低纬地区模拟结果出现较大的差异,热力学变量在非洲北部、加拿大西北部以及俄罗斯中北部的差异稍大。将模拟的土壤体积含水量与站点观测相比,两套数据的表现接近,与站点观测相比都存在一定的偏差,但SG更接近观测,其中在Molly Caren站点（39°57′N,83°27′W）上SG相比GSDE整体提高约0.01～0.02。本研究表明,模式模拟结果受不同土壤数据集的影响显著,可优先考虑诸如SG较准确的土壤数据。土壤属性对陆面模拟的影响需进一步研究。     

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,不同产品模拟的冬季土壤湿度和观测值相关性是全年中最小的;不同土壤湿度产品在干旱区以模拟偏湿为主,GLDAS-Noah模拟效果最佳,但模拟土壤湿度峰值和谷值的出现时间较观测较早,GLDAS-Noah、CRA40、ERA5能较好模拟季风区干、湿土壤的持续时段和土壤湿度变化振幅,大部分产品能模拟出夏季风影响过渡区较干土壤和较湿土壤的出现时间。     

An overview of soil moisture drought research in China: Progress and perspective

Soil moisture drought (SMD) directly affects agricultural yield and land water resources. Understanding and predicting the occurrences and evolution of SMD are of great importance for a largely agricultural country such as China. Compared to other drought categories, SMD receives less attention due to the lack of long-term soil moisture datasets. In recent decades, SMD research has been greatly developed in China, benefiting from increased ground and satellite measurements along with state-of-the-art land surface models. Here, the authors provide a brief overview of the recent progress in SMD research in China, focus on historical drought identification and its prediction, and then raise some future perspectives. Based on historical SMD studies, drought frequency has increased overall and drought duration has been prolonged since the 1950s for China as a whole, but they both show substantial temporal variations at the regional scale. Research on SMD prediction has mainly relied on the statistical relationship between soil moisture and climate variables. Few studies based on the dynamical approach in seasonal drought prediction have highlighted the importance of initial conditions and atmospheric forcing datasets. Given the importance of SMD in agricultural practice and water resource management in China, it is necessary to emphasize the following: 1) conducting research on multiple time scales (e.g., from days to the centurial time scale) and cross-regional drought identification research; and 2) developing a SMD prediction system that takes advantage of climate prediction systems, land surface models, and multisource soil moisture datasets.摘要论文回顾了中国土壤湿度干旱 (SMD) 历史重建和季节预测研究进展, 并对未来研究进行了展望. 自1950s年代以来, 全国整体干旱频率增加, 持续时间延长, 且有明显区域特征. SMD预测多是利用土壤湿度与气候变量之间的统计关系, 而少量基于动力学方法的干旱预测研究强调了初始条件和大气强迫数据对季节尺度干旱预测的重要性. 本论文提出: 1) 加强多时间尺度, 跨区域的SMD研究; 2)联合气候预测系统, 陆面模式和多源土壤湿度数据研制SMD预测系统.     

四套土壤湿度再分析数据在中国西北东部—华北—江淮地区的适用性研究

基于1992~2010年全国778个农业气象站土壤湿度观测资料、ERA-Interim、JRA55、NCEP-DOE R2和20CR土壤湿度再分析资料,通过平均差值、相关系数、差值标准差、标准差比四个参数,利用Brunke排名方法和EOF(Empirical Orthogonal Function)分析,对四套土壤湿度再分析资料在中国西北东部—华北—江淮区域的适用性进行了分析。主要结论如下:不同季节的平均偏差空间分布上,JRA55资料同观测数据的平均偏差在±0.08m~3 m~(-3)之间,春、夏季西北东部JRA55土壤湿度偏小,ERA-Interim、NCEP-DOE R2、20CR资料较观测数据偏湿,华北南部、江淮地区平均偏差小于西北东部、华北北部。在年际变化上,各个季节ERA-Interim资料同观测资料最为接近,能稳定地再现西北东部、华北、江淮地区土壤湿度干湿变化趋势,反映出重要的旱涝年。整体而言,四套再分析资料中ERA-Interim资料同观测资料接近,JRA55、NCEP-DOE R2资料次之,20CR资料最差。     

雅鲁藏布江流域夏季降水的年际变化及其原因

本文通过多套观测与再分析降水资料的比较,分析了雅鲁藏布江流域夏季降水的特征,从水汽含量与水汽输送的角度检验了雅鲁藏布江水汽通道的特点,研究了流域夏季降水的年际变化及其原因。分析表明:（1）该流域夏季降水大值位于雅鲁藏布江出海口至大峡谷一带,观测中流域平均降水可达5.8 mm d-1。不同资料表现的降水空间分布一致,但再分析降水普遍强于观测,平均为观测的2倍左右。（2）该流域夏季的水汽主要来自印度洋和孟加拉湾的偏南暖湿水汽输送,自孟加拉湾出海口沿布拉马普特拉河上溯至大峡谷,即雅鲁藏布江水汽通道。水汽收支诊断表明,夏季流域南部（即水汽通道所在处）是水汽辐合中心,流域平均的辐合约9.5 mm d-1,主要来自风场辐合与地形坡度的贡献。（3）不同再分析资料表现的流域降水和水汽分布特征总体一致,但量值差异较大。NCEP（美国国家环境预报中心）气候预报系统再分析资料CFSR、日本气象厅再分析资料JRA-25较欧洲中期天气预报中心再分析ERA-Interim资料更适于研究该流域（青藏高原东南部）的水汽特征,因为后者给出的流域降水和水汽偏强。（4）近30年该流域夏季降水无显著趋势,以年际变率为主。年际异常的水汽辐合（约为气候态的35.4%）源自异常西南风导致的局地水汽辐合（纬向、经向辐合分别贡献了16.5%、83.5%）,地形作用很小。流域夏季降水的年际变化是由印度夏季风活动导致的异常水汽输送造成的,其关键系统是印度季风区北部的异常气旋（反气旋）式水汽输送。     

Sensitivity of MM5-simulated planetary boundary layer height to soil dataset: comparison of soil and atmospheric effects

The effects of two soil datasets on planetary boundary layer (PBL) height are analyzed, using model simulations. Simulations are performed with the MM5 weather prediction system over the Carpathian Basin, with 6?km horizontal resolution, investigating three summer days, two autumn, and one winter day of similar synoptic conditions. Two soil datasets include that of the United States Department of Agriculture, which is globally used, and a regional Hungarian called Hungarian unsaturated soil database. It is shown that some hydraulic parameter values between the two datasets can differ up to 5–50%. These differences resulted in 10% deviations in the space–time-averaged PBL height (averaged over Hungary and over 12?h in the daytime period). Over smaller areas, these relative deviations could reach 25%. Daytime course changes in the PBL height for reference run conditions were significant (p?<?0.01) in ≈70% of the grid points covering Hungary. Ensemble runs using different atmospheric parameterizations and soil moisture initialization setups are also performed to analyze the sensitivity under changed conditions. In these cases, the sensitivity test showed that irrespective of the radiation and PBL scheme, the effect of different soil datasets on PBL height is roughly the same. PBL height is also sensitive to field capacity (Θ_f) and wilting point (Θ_w) changes. Θ_f changes seem to be more important for loamy sand, while Θ_w changes for the clay soil textural class.