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。     

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。     

GPRS/CDMA无线通信技术在GPS数据传输中的应用

GPRS/CDMA作为移动通信2.5代的技术是一种成熟的行业专业数据无线传输手段。该技术具有永远在线、快速登录、按量收费等优点。从2004年10月开始,北京市气象局采用GPRS/CDMA无线通信技术开发了一套地基GPS大气水汽遥测网远程数据通信和控制系统,替代了原有的基于公众电话交换网和调制解调器的远程通信与控制系统。新开发的系统实现了准实时、全自动的数据传输功能,设备可靠性高,维护方便,安装简易。目前该系统已正式投入日常业务运行。     

基于恒模算法的智能天线系统波束形成

结合智能天线波束形成的特性,提出了将恒模算法运用到波束形成中的新方案.利用恒模算法来训练加权因子以获得理想的信号增益.仿真实验验证了该方案的合理性.     

两种背景场改进方案对新疆“狭管”风区风场预报性能评估

为了客观评价Wind Energy Resource Assessment System /CMA(简称WERAS/CMA)系统(CTL方案)和将其中的客观分析法改成四维同化系统(简称FDDA方案)对既受狭管效应影响、又受湖陆风影响的阿拉山口和达坂城-小草湖风区起伏下垫面中的风能资源数值模拟的优劣,根据2009年7、10月和2010年1、4月 12UTC的NCEP再分析资料以及同期CMACAST下发的WMO各种常规观测资料开展了风场预报效果对比实验。结果表明:(1)对复杂区域而言,两种方案比过去单纯只用中尺度模式进行风场模拟的平均相对误差至少减小10%;(2)总体而言,两种方案对70 m高度处的风速模拟误差要大于30、50、100 m处的误差,在受多种环流尺度影响区域,模式在刻画平均风速/风向频率廓线方面的缺陷均极其相似;(3)在70 m高度上,两种方案5 m·s^-1以内的风速平均相对误差可达60%～130%,>5 m·s^-1的误差可控制在15%以内;对受湖陆风影响区域的模拟误差明显偏大,误差大小与湖陆风效应的季节变化有关; (4)两种方案均能抓住70 m左右高度上不同等级风速段的气候背景,对达坂城风区5～15 m·s^-1风速段的Ts预报评分可达0.6～0.7,对阿拉山口和小草湖风区≤5 m·s^-1风速段的Ts预报评分分别可达0.6～0.7和0.9左右。然而,对达坂城风区≤5 m·s^-1风速段的Ts预报评分仅0.3～0.4;(5)两种方案对所有风区需采取停机保护措施的、15 m·s^-1以上强风预报的Ts评分仅在0.4～0.6;(6)同一测风塔不同高度上,FDDA方案对风的预报效果不一定总优于CTL方案,但在70 m高度上,FDDA总体略优于CTL;即使同一风区,各个测风塔之间两种方案的预报效果也是因局地多尺度环流影响的不同或因预报的高度不同或预报季节的不同而异,这种预报误差差异的机理还有待探究。     

Blind equalization based on RLS algorithm using adaptive forgetting factor for underwater acoustic channel

Blind equalization based on adaptive forgetting factor, recursive least squares （RLS） with constant modulus algorithm （CMA）, is investigated. The cost function of CMA is simplified to meet the second norm form to ensure the stability of RLS-CMA, and thus an improved RLS-CMA （RLS-SCMA） is established. To further improve its performance, a new adaptive forgetting factor RLS-SCMA （ARLS-SCMA） is proposed. In ARLS-SCMA, the forgetting factor varies with the output error of the blind equalizer during the iterative process, which leads to a faster convergence rate and a smaller steady-state error. The simulation results prove the effectiveness under the condition of the underwater acoustic channel.     

Combination of FEM and CMA‐ES algorithm for transmissivity identification in aquifer systems

In this paper, we propose a coupling of a finite element model with a metaheuristic optimization algorithm for solving the inverse problem in groundwater flow (Darcy's equations). This coupling performed in 2 phases is based on the combination of 2 codes: This is the HySubF‐FEM code (hydrodynamic of subsurface flow by finite element method) used for the first phase allowing the calculation of the flow and the CMA‐ES code (covariance matrix adaptation evolution strategy) adopted in the second phase for the optimization process. The combination of these 2 codes was implemented to identify the transmissivity field of groundwater by knowing the hydraulic head in some point of the studied domain. The integrated optimization algorithm HySubF‐FEM/CMA‐ES has been validated successfully on a schematic case offering an analytical solution. As realistic application, the integrated optimization algorithm HySubF‐FEM/CMA‐ES was applied to a complex groundwater in the north of France to identify the transmissivity field. This application does not use zonation techniques but solves an optimization problem at each internal node of the mesh. The obtained results are considered excellent with high accuracy and fully consistent with the hydrogeological characteristics of the studied aquifer.However, the various numerical simulations performed in this paper have shown that the CMA‐ES algorithm is time‐consuming. Finally, the paper concludes that the proposed algorithm can be considered as an efficient tool for solving inverse problems in groundwater flow.     

2014—2018年内蒙古大兴安岭地区干雷电时空分布特征

利用2014—2018年内蒙古大兴安岭地区闪电定位仪监测的雷电及CLDAS逐日降水数据,确定干雷电期间降水阈值并筛选干雷电监测数据,分析干雷电在大兴安岭地区的时空分布特征,为大兴安岭地区雷击火的防范提供科学依据.结果表明:大兴安岭地区CLDAS降水与气象站点降水的误差较小,有较高的适用性,可以满足干雷电的分析需求.大兴...     

Comparison of precipitation products to observations in Tibet during the rainy season

Precipitation is an important component of global water and energy transport and a major aspect of climate change. Due to the scarcity of meteorological observations, the precipitation climate over Tibet has been insufficiently documented. In this study, the distribution of precipitation during the rainy season over Tibet from 1980 to 2013 is described on monthly to annual time scales with meteorological observations. Furthermore, four precipitation products are compared to observations over Tibet. These datasets include products derived from the Asian Precipitation-Highly-Resolved Observational Data(APHRO), the Global Precipitation Climatology Centre(GPCC), the University of Delaware(UDel), and the China Meteorological Administration(CMA). The error, relative error, standard deviation, root-mean-square error, correlations and trends between these products for the same period are analyzed with in situ precipitation during the rainy season from May to September. The results indicate that these datasets can broadly capture the temporal and spatial precipitation distribution over Tibet. The precipitation gradually increases from northwest to southeast. The spatial precipitation in GPCC and CMA are similar and positively correlated to observations. Areas with the largest deviations are located in southwestern Tibet along the Himalayas. The APHRO product underestimates, while the UDel, GPCC, and CMA datasets overestimates precipitation on the basis of monthly and inter-annual variation. The biases in GPCC and CMA are smaller than those in APHRO and UDel with a mean relative error lower than 10% during the same periods. The linear trend of precipitation indicates that the increase in precipitation has accelerated extensively during the last 30 years in most regions of Tibet. The CMA generally achieves the best performance of these four precipitation products. Data uncertainty in Tibet might be caused by the low density of stations, complex topography between the grid points and stations, and the interpolation methods, which can also produce an obvious difference between the gridded data and observations.