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NEX-GDDP和CMIP5对青藏高原地区近地面气象场历史和未来模拟的评估与偏差校正

青藏高原是全球变化研究的热点区域,气候模式模拟是研究该区域气候变化的重要数据来源.本文使用基于中国地面台站的插值格点数据集(CN05.1),对国际气候耦合模式第5次比较计划(CMIP5)及其高分辨率统计降尺度数据集(NEX-GDDP)中15个模式1966-2005年间的逐日最高/最低气温、降水和平均风速在青藏高原区域的...     

The GRAPES Variational Bias Correction Scheme and Associated Preliminary Experiments

The variational assimilation theory is generally based on unbiased observations. In practice, however, almost all observations suffer from biases arising from observational instruments, radiative transfer operator, precondition of data, and so on. Therefore, a bias correction scheme is indispensable. The current scheme for radiance bias correction in the GRAPES 3DVar system is an offline scheme. It is actually a static correction for the radiance bias before the process of cost function minimization. In consideration of its effects on forecast results, this kind of scheme has some shortcomings. Thus, this study provides a variational bias correction (VarBC) scheme for the GRAPES 3DVar system following Dee’s idea. In the VarBC scheme, the observation operator is modified and a new control variable is defined by taking the predictor coefficients as the control parameters. According to the feature of the GRAPES-3DVAR, an incremental formulation is applied and the original bias correction scheme is maintained in the actual process of observations. The VarBC is designed to co-exist with the original scheme, because it is a dynamic revision to the observational operator on the basis of the old method, i.e., it adjusts the model state vector along with the control parameters to an unbiased state in the process of minimization and the assimilation system remains consistent with available information automatically. Preliminary experimental results show that the mean departures of background-minus-observation and analysis-minus-observation are reduced as expected. In a case study of the heavy rainfall that happened in South China on 11–13 June 2008, the 500-hPa geopotential height is better simulated using the analyzed field from the VarBC as the initial condition.     

基于频率匹配法的中国降水多模式预报订正研究

基于TIGGE资料中欧洲中期天气预报中心、日本气象厅、美国国家环境预报中心及英国气象局1～7 d日降水量预报以及中国自动站观测资料与CMORPH降水产品融合的逐时降水量网格数据集,利用频率匹配法(Frequency-Matching Method,FMM)对中国降水预报进行客观订正。首先利用卡尔曼滤波方法对降水频率进行调整,并根据不同区域降水强度差异将全国分为7个子区域分别进行频率匹配。结果表明,FMM可以有效减小降水量预报的误差。经过频率匹配法订正后各模式降水预报的平均绝对误差(Mean Absolute Error,MAE)大幅减小,且订正后各量级降水的雨区面积更加接近实际观测值。FMM对小于5 mm和大于15 mm的降水预报技巧改进明显。此外,FMM降低了模式预报的小雨空报率和大雨漏报率,并且明显提高了晴雨预报的准确率。FMM明显消除了大范围小雨空报区域,但是对强降水预报FMM仅能调整降水量大小,强降水落区预报并不能得到明显改善。     

The delesse relation in a concentrically zoned sphere. I. The section-number bias

Zonal areas of a randomly chosen section through a concentrically zoned sphere yield an estimate of the (volumetric) amount of the outer zone which is subject to a large positive bias that decreases rapidly with increase in the number of sections on which the estimate is based. It will not exceed 3% of the amount present if an analysis is based on as many as 8 sections and will be less than 1% if 32 sections are used.     

IGS事后精密星历产品不连续性分析及处理方法

IGS的事后精密钟差产品采取以天为单位的数据处理策略这导致在天与天之间的交界处卫星的钟差基准不连续 对需要进行跨天数据处理的精密单点定位用户会发生基准跳跃的卫星模糊度在交界历元处不连贯这无异于产生了一个无法修复的非整周的周跳使得滤波需要重新收敛 详细分析了30d每颗卫星跳跃的量级以及对精密单点定位用户的影响在详细阐述IGS钟差解算策略的基础上分析了产生这种不连续性的原因并提出了两种应对策略 在IGS精密钟差产品中加入钟差基准跳跃信息供用户使用 将钟差基准在多天连续估计 最后给出了这两种策略的数据处理结果验证了两种方法的有效性.     

Bias estimation and correction for triangle-based surface area calculations

The calculation of surface area is meaningful for a variety of space-filling phenomena, e.g., the packing of plants or animals within an area of land. With Digital Elevation Model (DEM) data we can calculate the surface area by using a continuous surface model, such as by the Triangulated Irregular Network (TIN). However, just as the triangle-based surface area discussed in this paper, the surface area is generally biased because it is a nonlinear mapping about the DEM data which contain measurement errors. To reduce the bias in the surface area, we propose a second-order bias correction by applying nonlinear error propagation to the triangle-based surface area. This process reveals that the random errors in the DEM data result in a bias in the triangle-based surface area while the systematic errors in the DEM data can be reduced by using the height differences. The bias is theoretically given by a probability integral which can be approximated by numerical approaches including the numerical integral and the Monte Carlo method; but these approaches need a theoretical distribution assumption about the DEM measurement errors, and have a very high computational cost. In most cases, we only have variance information on the measurement errors; thus, a bias estimation based on nonlinear error propagation is proposed. Based on the second-order bias estimation proposed, the variance of the surface area can be improved immediately by removing the bias from the original variance estimation. The main results are verified by the Monte Carlo method and by the numerical integral. They show that an unbiased surface area can be obtained by removing the proposed bias estimation from the triangle-based surface area originally calculated from the DEM data.     

ERA-Interim气温数据在中国区域的适用性评估

运用中国756个观测站点的逐月平均气温数据,对比分析了ERA-Interim再分析资料的误差。结果发现:ERA-Interim再分析资料能够很好地反映观测值的年际变化,相关性达到0.955~0.995。ERA-Interim在580个站点的冷偏差或暖偏差小于1℃,占站点总数的76.7%,可信度较高。64个站点的冷偏差或暖偏差大于5℃,可信度较低。ERA-Interim在东部地区的暖偏差多于西部地区,冷偏差的高值主要集中在西部地区的高海拔站点。海拔低于200 m的站点偏差最小,适用性好,多数海拔3 000 m以上的站点呈现较大冷偏差,适用性较差。通过回归分析发现,观测站点与ERA-Interim格点的高度差是导致误差的主要原因,因此通过高程校正能够有效降低误差,提高ERA-Interim适用性。