利用GLDAS资料分析黄土高原半干旱区土壤湿度对气候变化的响应

利用GLDAS资料分析了1948~2010年黄土高原半干旱区气温、降水和土壤湿度的变化趋势,并重点讨论了气温和降水对土壤湿度的影响和相对贡献。结果表明:近60 a来黄土高原半干旱区整体呈现暖干化趋势,增温速率明显高于全球平均增温速率;不同深度的土壤湿度的长期变化均呈减小趋势,且年际间变化明显。不同深度的土壤湿度和气温呈负相关关系,并随着土壤加深,两者的相关性加强;土壤湿度和降水则呈正相关关系,相关关系最大出现在表层土壤。通过分析气温和降水在不同季节对土壤湿度的相对贡献发现,春季和冬季气温对土壤湿度的相对贡献较降水显著,秋季恰好相反,夏季气温和降水对土壤湿度的相对贡献大小相当。对比不同深度层降水、气温对土壤湿度的相对贡献得出,降水对浅层土壤湿度有显著作用,而气温对深层土壤湿度的作用更明显。     

青藏高原春季土壤湿度异常对我国夏季降水影响的模拟研究

利用耦合的全球海气模式（NCAR CCSM3）, 对青藏高原春季土壤湿度异常影响我国夏季7月降水的机制进行了数值模拟。结果表明, 高原6~62 cm深度的中层土壤湿度异常与表层土壤湿度异常有很好的一致性, 相对而言, 中层土壤湿度异常的持续性较好。若5月高原中层土壤偏湿, 则春末至夏初高原地面蒸发、 潜热通量增加, 而感热通量、 地面温度降低, 高原表面的加热作用减弱, 使得印度高压西撤偏晚, 环流系统的季节性转换偏晚, 东亚地区形成有利于我国夏季出现第I类雨型的环流分布形势, 使我国东部雨带偏北, 华北地区多雨, 江淮地区降水偏少, 华南地区降水偏多; 反之亦然。     

土壤湿度对东亚夏季气候潜在可预报性影响的数值模拟

利用全球大气环流模式NCARCAM3进行了在给定的观测海温条件下的22a（1979—2000年）5—8月的2组集合试验。运用方差分析方法,分析了在气候态和年际变化的表层土壤湿度情况下,CAM3模式模拟的东亚夏季气候潜在可预报性及其差异。结果表明：在给定的观测海温条件下,采用气候态的土壤湿度时,CAM3模式模拟的东亚夏季气候的潜在可预报性偏低;而采用年际变化的土壤湿度时,模拟的夏季气候潜在可预报性有所提高,尤其是在中国西北地区;后者模拟的中国西北地区夏季降水和气温的潜在可预报性比前者的模拟结果提高0．1以上。其原因可能是：采用年际变化的土壤湿度时,模式可以更好地模拟出中国西北地区的地表蒸发量和湍流热通量的年际变化,进而使得模式对该地区夏季气候的预报技巧得到提高。     

一次强降水模拟中土壤湿度初值的影响研究

为了分析WRFV3.3.1模式中土壤湿度初值对降水模拟的影响,在4个陆面方案的分析对比基础上,采用中国区域土壤湿度同化系统（CLSMDAS）输出的土壤湿度替换模式初始场中的土壤湿度,对2010年6月19日江西出现的一次强降水过程进行模拟,分析改进后的土壤湿度初值对模式模拟降水的影响。结果表明,耦合Noah方案的模拟结果要优于SLAB、RUC、PX方案;通过对比试验发现CLSMDAS输出的土壤湿度初始条件下的模拟结果比NCEP资料的模拟结果更接近于实况,能够很好地模拟出24 h累积降水的范围与强度,对应地表能量的响应也更为明显,表现出很好的区域波动性,能够捕捉到细节降水信息,且统计检验结果中各量级降水的TS评分基本都要高于NCEP土壤湿度初值条件下的结果,空报率、漏报率和预报偏差进一步减小,说明准确的土壤湿度初值能够提高模式的模拟预报能力。     

中国不同气候区土壤湿度特征及其气候响应

为获得中国不同气候区各层深度土壤湿度变化特征及其对气候变化的响应,利用中国区域台站观测土壤湿度资料、降水及气温资料,采用趋势、相关性分析及突变检验等方法,讨论了东北、河套、江淮区域1981~1999年不同深度土壤湿度变化特征及其对气温、降水的响应。结果表明:东北、江淮地区为土壤湿度高值区,河套地区为土壤湿度低值区,土壤湿度由浅层至深层呈上升趋势;东北、河套地区降水和土壤湿度变化呈正相关,江淮地区降水和土壤湿度呈负相关;东北、河套地区气温和土壤湿度变化呈负相关,江淮地区气温与土壤湿度呈正相关关系。土壤湿度对降水的响应比对气温变化的响应更加显著。      

四川盆地土壤湿度时空分布及影响因子分析

基于四川盆地24个农业气象站1996~2012年浅层10cm的旬土壤湿度、温度、降水和日照等观测资料,采用统计分析方法,分析了盆地四季多年土壤湿度时空分布特征以及气象因子对土壤湿度的影响。结果表明:四川盆地浅层土壤湿度空间分布整体呈现南多北少的态势,其大小为春、冬两季偏低;夏、秋相对较高,其中以秋季为一年内最高。时间变化趋势则表现为春夏有微弱的降低趋势,而秋冬呈现微弱上升趋势。小波分析表明,各季节普遍存在4~6年的准周期。从倾向率分析来看,在不同季节表现出减少的区域主要集中在南部及东北部地区,四川盆地其余各地呈现不同程度增加趋势,以绵阳地区变化较为显著,夏、秋两季均达到了1.4%/a。与气象因子相关分析中得出,在相对偏干的盆地西北部,浅层土壤湿度变化受降水的影响最大,而在较为湿润的南部和东北部受日照影响最大。      

中国华北暖季土壤湿度的变化特征

通过与土壤湿度观测资料比较验证发现,GLDAS同化数据能够较好地反映中国地区暖季土壤湿度的时空分布和变化特征,特别是在华北地区,两者显著相关。在此基础上,为研究中国区域干旱化特征,利用1948~2010年的GLDAS数据分析了中国华北地区暖季土壤湿度的周期信号和长期变化,并初步探讨了气温和降水对土壤湿度的影响。结果表明:1948~2010年华北地区暖季4个不同深度层土壤湿度的变化特征基本一致,主要存在3 a、5~7 a和15 a周期信号,其中以5~7 a周期最为显著;长期变化均呈现减小趋势,且中间2层土壤湿度的减小比表层和最深层更为迅速。不同深度的土壤湿度和降水呈正相关关系,且相关性随土壤深度的增加而逐渐减小,与气温呈负相关关系,且中间2层的相关性大于表层和最深层。     

土壤湿度初值对边界层物理量预报影响的分析

使用全球中期数值预报模式T213L31,对不同的土壤湿度初值对边界层物理量预报的影响进行敏感试验分析。试验表明土壤湿度初值的准确性非常重要,其变化导致模式计算的感热通量、潜热通量、地表温度和2m温度发生较大变化。而当使用与观测值相近的土壤湿度初值时得到的边界层物理量(如2m温度)更加准确。通过使用固定值与6h预报的背景场加权平均作为土壤湿度的初值,改进原有采用固定值的方法,经过检验模式系统,2m温度的预报误差明显减小。     

延伸期预报中大气初值与海温边值的相对作用

初始条件记忆和下垫面条件是延伸期可预报性的主要来源,它们在不同时段、不同区域的相对作用存在明显不同。利用中国国家气候中心最新一代大气环流模式BCC_AGCM,设计了由4组不同大气初值与海温边值构成的组合试验,研究了（大气）初值与（海温）边值对全球不同区域延伸期预报的相对作用。结果显示,模式预测技巧在3周以内强烈依赖于初值。在相同的边值条件强迫下,不同初值在月内尺度上的预测技巧差异非常明显,且在更长的时间尺度上,初值仍然能够提供一定的预测信息。从全球来看,边值强迫对预测技巧的影响从一周左右开始。在低层的850 hPa高度场上,边值的作用在热带地区于第4-5候与初值相当,其他区域的边值影响达到与初值相当的时间滞后于热带地区;在北半球500 hPa高度场上,边值的作用在热带地区第5候前后达到与初值作用相当,其他区域这个时间则推迟至第6候前后,比对低层的影响时间滞后1-2候;对于东亚地区而言,边值的贡献在第2候就已显现,对预测技巧产生了明显的改进。在延伸期尺度上,边值强迫主要作用的区域为低纬度区域,且对500 hPa高度场的影响更为稳定,在该区域第5候以后有较为明显的改进。初值与边值对延伸期预报都具有相当重要的作用,认识初、边值条件的相对作用能够为延伸期预报的改进奠定基础。     

夏季青藏高原不同层次土壤湿度时空变化特征

基于1950—2009年GLDAS Noah 2.0逐月平均土壤湿度资料,分析了夏季青藏高原各层土壤湿度的时空变化特征。结果表明:(1)夏季青藏高原各层土壤湿度整体上呈自南向北递减的空间分布,但在高原中部地区中层、深层土壤湿度均有一个极值中心。(2)夏季高原中东部地区表层、浅层、中层、深层土壤湿度之间的差值(深层与中层除外)均表现为"上湿下干"的垂直分布,而中部偏西地区各层土壤湿度差值则表现为"下湿上干"的垂直分布。(3)夏季高原各层土壤湿度第一模态均呈现西南—东北反向型分布,且随着深度的增加,零线向东北移。(4)夏季高原主体各层土壤湿度的年际变化特征明显,除深层(呈现不显著增加趋势)外整体均呈现显著下降趋势,前期土壤湿度较高,后期较低。从空间趋势分布来看,除深层土壤湿度在高原中部有增大趋势外,各层土壤湿度变化趋势在高原上均以减小为主。(5)去趋势后,除深层外其他各层土壤湿度最大年际变化幅度在高原中部随着土层的增加而减小,而高原中东部则随土层的增加而增大。     

Relevance of soil moisture for seasonal atmospheric predictions: is it an initial value problem?

Ensembles of boreal summer atmospheric simulations, spanning a 15-year period (1979–1993), are performed with the ARPEGE climate model to investigate the influence of soil moisture on climate variability and potential predictability. All experiments are forced with observed monthly mean sea surface temperatures. In addition to a control experiment with interactive soil moisture boundary conditions, two sensitivity experiments are performed. In the first, the interannual variability of the deep soil moisture is removed during the whole season, through a relaxation toward the monthly mean model climatology. In the second, only the variability of the initial soil moisture conditions is suppressed. While it is shown that soil moisture strongly contributes to the climate variability simulated in the control experiment, an analysis of variance indicates that soil moisture does not represent a significant source of predictability in most continental areas. The main exception is the North American continent, where climate predictability is clearly reduced through the use of climatological initial conditions. Using climatological soil moisture boundary conditions does not lead to strong and homogeneous impacts on potential predictability, thereby suggesting that the climate signals driven by the sea surface temperature variability are not generally amplified by interactive soil moisture and that the relevance of soil moisture for seasonal forecasting is mainly an initial value problem.     

土壤湿度对卫星辐射率资料直接同化的影响

本研究利用WRF模式及其三维变分同化系统实现了对NOAA-16 AMSU-A微波资料的直接同化,针对2010年6月19日江西地区的一次强降水过程开展模拟与同化试验,并利用中国区域土壤湿度同化系统(CLSMDAS—China Land Soil Moisture Data Assimilation System)输出的土壤湿度值替换NCEP(National Centers for Environmental Prediction)资料中的土壤湿度,研究土壤湿度初值对辐射率资料直接同化中观测场与背景场偏差调整的影响。结果表明:采用CLSMDAS输出土壤湿度初值条件下模拟的亮温值与实际观测值更为接近,经过质量控制和偏差订正后更多的观测资料能够进入到同化系统中,说明改进的土壤湿度初值条件下观测算子的计算值得到正的调整,对低层地表通道的改进效果明显,尤其以50.3 GHz的窗区通道3的结果最为理想;针对此次强降水过程中24 h累积降水分布的模拟结果,CLSMDAS输出土壤湿度初值条件下同化AMSU-A资料,能够较为准确的把握整个雨带的走向、大雨以上级别降水的落区范围、降水中心落区及强度等。说明准确的土壤湿度初值能够改进卫星辐射率资料的同化结果,进而提高数值模式的模拟预报能力。     

Relative contribution of soil moisture and snow mass to seasonal climate predictability: a pilot study

Land surface hydrology (LSH) is a potential source of long-range atmospheric predictability that has received less attention than sea surface temperature (SST). In this study, we carry out ensemble atmospheric simulations driven by observed or climatological SST in which the LSH is either interactive or nudged towards a global monthly re-analysis. The main objective is to evaluate the impact of soil moisture or snow mass anomalies on seasonal climate variability and predictability over the 1986–1995 period. We first analyse the annual cycle of zonal mean potential (perfect model approach) and effective (simulated vs. observed climate) predictability in order to identify the seasons and latitudes where land surface initialization is potentially relevant. Results highlight the influence of soil moisture boundary conditions in the summer mid-latitudes and the role of snow boundary conditions in the northern high latitudes. Then, we focus on the Eurasian continent and we contrast seasons with opposite land surface anomalies. In addition to the nudged experiments, we conduct ensembles of seasonal hindcasts in which the relaxation is switched off at the end of spring or winter in order to evaluate the impact of soil moisture or snow mass initialization. LSH appears as an effective source of surface air temperature and precipitation predictability over Eurasia (as well as North America), at least as important as SST in spring and summer. Cloud feedbacks and large-scale dynamics contribute to amplify the regional temperature response, which is however, mainly found at the lowest model levels and only represents a small fraction of the observed variability in the upper troposphere.     

Contribution of realistic soil moisture initial conditions to boreal summer climate predictability

Seasonal climate forecasts mainly rely on the atmospheric sensitivity to its lower boundary conditions and on their own predictability. Besides sea surface temperature (SST), soil moisture (SM) may be an additional source of climate predictability particularly during boreal summer in the mid-latitudes. In this work, we investigate the role of SM initial conditions on near-surface climate predictability during ten boreal summer seasons using three complementary ensembles of AMIP-type simulations performed with the Arpège-Climat atmospheric general circulation model. First we have conducted an assessment of the SM predictability itself through a comparison of simple empirical SM models with Arpège-Climat. The statistical and dynamical models reveal similar SM prediction skill patterns but the Arpège-Climat reaches higher scores suggesting that it is at least suitable to explore the influence of SM initialization on atmospheric predictability. Then we evaluate the relationships between SM predictability and some near surface atmospheric predictability. While SM initialization obviously improves the predictability of land surface evaporation, it has no systematic influence on the precipitation and near surface temperature skills. Nevertheless, the summer hindcast skill is clearly improved during specific years and over certain regions (mainly north America and eastern Europe in the Arpège-Climat model), when and where the SM forcing is sufficiently widespread and strong. In this case, a significant impact is also found on the occurrence of heat waves and heavy rains, whose predictability at the seasonal timescale is a crucial challenge for years to come.     

Impacts of Soil Moisture on the Numerical Simulation of a Post-Landfall Storm

Surface heat and moisture fluxes are important to the evolution of a tropical storm after its landfall. Soil moisture is one of the essential components that influence surface heating and moisture fluxes. In this study, the impact of soil moisture on a pre-landfall numerical simulation of Tropical Storm Bill(2015), which had a much longer lifespan over land, is investigated by using the research version of the NCEP Hurricane Weather Research and Forecasting(HWRF) model. It is found that increased soil moisture with SLAB scheme before storm's landfall tends to produce a weaker storm after landfall and has negative impacts on storm track simulation. Further diagnoses with different land surface schemes and sensitivity experiments indicate that the increase in soil moisture inside the storm corresponds to a strengthened vertical mixing within the storm boundary layer, which is conducive to the decay of storm and has negative impacts on storm evolution. In addition, surface diabatic heating effects over the storm environment are also found to be an important positive contribution to the storm evolution over land, but their impacts are not so substantial as boundary layer vertical mixing inside the storm. The overall results highlight the importance and uncertainty of soil moisture in numerical model simulations of landfalling hurricanes and their further evolution over land.     

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。     

半干旱区陆面模式参数对水分循环的敏感性研究

植被覆盖对陆气之间物质和能量交换过程具有极其重要的影响,但植被覆盖对于交换过程的影响因子很多,关系复杂.作者研究了各种植被因子对陆气之间水分循环的作用和相对重要性.首先通过单点NO-AH模式对吉林通榆农田下垫面2004年土壤和边界层各物理量进行模拟,并与观测结果比较和评价,肯定了单点NOAH模式模拟能力.使用这一模式进行敏感试验,将与植被有关的参数分别在其取值范围取较大与较小值,比较水分循环各物理量如土壤湿度、土壤蒸发、植被蒸腾等的变化情况.试验表明在各参数中植被气孔阻抗、根系深度、土壤湿度初值和反照率对水分循环的影响较大,而叶面积指数、粗糙度和冠层阻抗则影响较小.     

Recent Researches on the Short-Term Climate Prediction at IAP－A Brief Review

回顾了近年来在中国科学院大气物理研究所开展的有关短期气候预测研究的进展。第一个短期气候数值预测是曾庆存等利用一个耦合了热带太平洋海洋环流模式的全球大气环流模式作出的。1997年，一个基于海气耦合模式的ENSO预测系统，包括一个海洋初始化方案被建立起来，同时也开展了基于海温异常的东亚气候可预测性研究。利用气候变动的准两年信号，王会军等提出了一个可以显著改进模式预测准确率的模式结果修正方案。为了考虑土壤湿度的初始异常对夏季气候的影响，一个利用大气资料如温度、降水等经验地反演土壤湿度的方法也被建立起来。还通过一系列的数值试验研究了 1998年夏季大水发生当中海温异常和大气环流初始异常的作用。     

Recent Researches on the Short-Term Climate Prediction at IAP－A Brief Review

Studies on the seasonal to extraseasonal climate prediction at the Institute of Atmospheric Physics (IAP) in recent years were reviewed. The first short-term climate prediction experiment was carried out based on the atmospheric general circulation model (AGCM) coupled to a tropical Pacific oceanic general circulation model (OGCM). In 1997, an ENSO prediction system including an oceanic initialization scheme was set up. At the same time, researches on the SST-induced climate predictability over East Asia were made. Based on the biennial signal in the interannual climate variability, an effective method was proposed for correcting the model predicted results recently. In order to consider the impacts of the initial soil mois ture anomalies, an empirical scheme was designed to compute the soil moisture by use of the atmospheric quantities like temperature, precipitation, and so on. Sets of prediction experiments were carried out to study the impacts of SST and the initial atmospheric conditions on the flood occurring over China in 1998.