中国降水测量误差的研究

20世纪 ,国际上许多国家对降水测量进行了对比试验工作 ,以研究降水测量中的误差大小与分布。由于各个国家降水测量仪器的型式、尺寸以及安装高度不同 ,试验对比的降水测量误差的大小也就不同。为了弄清中国降水测量误差的大小 ,中国气象局选择了 30个基准基本站 ,建立标准雨量站网进行试验对比。本文介绍了中国标准雨量站网的设置以及对比资料的获取情况 ,对比分析了中国降水测量的随机误差、沾湿与蒸发误差、风场变形误差。经 30个标准雨量站 7a 2 90 0 0多次的 1台坑式雨量器、2台台站雨量器的对比观测 ,给出了中国降水量测量误差的大小、降水测量中的随机误差与系统误差的分布情况。经分析 ,对于收集口口径为 2 0cm ,安装高度为 70cm的台站普通雨量器 ,每次测量随机误差累计平均值为 0 .0mm ,沾湿误差为 0 .2mm ,蒸发误差为 0 .0mm ,降雨风场变形误差为 0 .19mm ,降雪为 0 .32mm。降雨测量的平均相对误差约为 4 .34%～ 15 .2 8% ,降雪测量的平均相对误差约为 6 .17%～ 39.99%。     

探空温度传感器受太阳辐射影响的仿真分析

随着高空温度探测精度要求的日益提高,如何减小温度传感器测量误差已成为亟需解决的问题,而太阳辐射作为影响温度传感器探测性能的重要因素已成为该领域研究的热点.利用计算机仿真技术,引入太阳高度角、引线夹角2个影响因子,根据流体动力学模型模拟分析探空温度传感器从海平面上升到32 km高空时所受太阳辐射的影响,最终得到辐射误差与海拔高度的关系曲线族,仿真结果将为开展高空温度传感器误差分析提供基础依据,从而提高传感器测量准确度.     

Mean Profiles of Moisture Fluxes in Snow-Filled Boundary Layers

Profiles of moisture fluxes have been examined for convective boundary layers containing clouds and snow, using data derived from aircraft measurements taken on four dates during the 1983/1984 University of Chicago lake-effect snow project. Flux profiles were derived from vertical stacks of aircraft cross-wind flight legs taken at various heights over Lake Michigan near the downwind shore. It was found that, if ice processes are taken into account, profiles of potential temperature and water content were very similar to those presented in past studies of convective boundary layers strongly heated from below. Profiles of total water content and equivalent potential temperature adjusted for ice were nearly invariant with height, except very near the top of the boundary layer, suggesting that internal boundary-layer mixing processes were rapid relative to the rates at which heat and vapour were transported into the boundary layer through entrainment and surface fluxes. Ice was found to play a significant, measurable role in boundary-layer moisture fluxes. It was estimated that 40 to 57% of the upward vapour flux was returned to the surface in the form of snow, converting about 45 to 64% of the surface latent heat flux into sensible heat in the snow-producing process. Assuming advective fluxes are relatively small (thought to be appropriate after the first few tens of km over the lake as suggested by past studies), the boundary layer was found to warm at a rate faster than could be explained by surface heat fluxes and latent heat releases alone, the remainder of the heating presumably coming from radiational processes and entrainment. Discussions of moisture phase change processes throughout the boundary layer and estimates of errors of these flux measurements are presented.     

GRAPES全球三维变分同化中卫星微波温度计亮温的背景误差及在质量控制中的应用

模式变量背景误差在观测空间的投影,也即观测变量的背景误差包含了变分同化系统的重要信息,其在诊断和分析变分同化系统中资料的影响等方面具有重要作用,特别是在背景场检查质量控制中。在GRAPES全球三维变分同化(3DVar)系统中仅给定了控制变量的背景误差,并未直接给定观测变量的背景误差。为了能够对GRAPES全球3DVar进行全面的诊断和分析,改进卫星微波温度计资料的质量控制,推导出GRAPES全球3DVar同化系统控制变量随机扰动方法估计观测变量的背景误差的公式,为分析和改进GRAPES全球3DVar提供了一个有力工具,并进而估计了AMSU-A亮温的背景误差,分析了AMSU-A不同通道亮温的背景误差特征,将其应用于GRAPES全球3DVar的AMSU-A亮温的背景场检查质量控制中。结果表明,控制变量随机扰动方法估计的GRAPES全球3DVar同化系统AMSU-A亮温的背景误差正确合理。同化循环预报试验结果表明,亮温的背景误差在背景场检查中的应用显著提高了GRAPES全球3DVar同化的亮温资料的数量,显著提高了GRAPES南半球对流层中高层位势高度场的预报技巧。在GRAPES全球3DVar同化系统中推导和实现的控制变量扰动方法为诊断和分析GRAPES全球3DVar观测资料同化效果提供了有力工具。      

Two-Dimensional Variational Analysis of Near-Surface Moisture from Simulated Radar Refractivity-Related Phase Change Observations

Because they are most sensitive to atmospheric moisture content, radar refractivity observations can provide high-resolution information about the highly variable low-level moisture field. In this study, simulated radar refractivity-related phase-change data were created using a radar simulator from realistic highresolution model simulation data for a dryline case. These data were analyzed using the 2DVAR system developed specifically for the phase-change data. Two sets of experiments with the simulated observations were performed, one assuming a uniform target spacing of 250 m and one assuming nonuniform spacing between 250 m to 4 km. Several sources of observation error were considered, and their impacts were examined. They included errors due to ground target position uncertainty, typical random errors associated with radar measurements, and gross error due to phase wrapping. Without any additional information, the 2DVAR system was incapable of dealing with phase-wrapped data directly. When there was no phase wrapping in the data, the 2DVAR produced excellent analyses, even in the presence of both position uncertainty and random radar measurement errors. When a separate pre-processing step was applied to unwrap the phase-wrapped data, quality moisture analyses were again obtained, although the analyses were smoother due to the reduced effective resolution of the observations by interpolation and smoothing involved in the unwrapping procedure. The unwrapping procedure was effective even when significant differences existed between the analyzed state and the state at a reference time. The results affirm the promise of using radar refractivity phase-change measurements for near-surface moisture analysis.     

北京等7个气象台站太阳总辐射观测资料的准确度评估

基于地面太阳短波总辐射对气溶胶光学特性和地表反照率的敏感性, 该文提出了一个评估我国气象台站总辐射资料准确度的方法。该方法选用气溶胶光学厚度和太阳天顶角较小情形下的晴天辐射资料, 从太阳直射辐射反演气溶胶光学厚度, 用于计算宽带透过率, 再从该透过率和总辐射资料反演太阳常数E_{0, P}, 并采用E_{0, P}对世界辐射基准 (WRR) 的偏差表示总辐射资料的不确定性。模拟结果表明:气溶胶折射率虚部和大气柱水汽含量的输入误差是两个主要的评估不确定因子。用于准确度评估的资料越多, 越有利于平滑气溶胶、水汽含量等输入参数随机误差的效应, 评估结果越合理。应用这一方法, 该文评估了2000— 2004年我国沈阳、额济纳旗、北京、乌鲁木齐、格尔木、上海和广州7个气象台站总辐射资料的准确度。7个站共有1161个太阳常数反演值, 都满足太阳天顶角余弦 (μ₀) 大于0.7的条件。这些E_{0, P}值对WRR的最大偏差为7.33%, 97.78%的E_{0, P}值对WRR的偏差小于5%, 总平均E_{0, P}值对WRR偏差只有-1.15 %。依据这些结果, 当μ₀≥0.7时, 这些台站的晴天总辐射资料的不确定度估计为5%。     

双线偏振多普勒雷达测量精度的理论分析

双线偏振雷达的主要任务之一是定量测量降水，反射率因子ZH、差反射率因子ZDR、差相移率常数K_DP都可以用来反演降雨强度，而K_DP的测量误差大小是影响反演降雨强度效果的关键。本文从理论公式出发，计算和分析了不同方位平均、距离平均、不同谱宽σV等因素对差传播相移ΦDP测量精度的影响。理论计算结果表明:ΦDP的测量误差随着样本对数M、距离平均区间的增大而减小，随σV的增大而增大(σV=1 m/s时例外)，此外，还总结了3种由ΦDP计算K_DP的方法，并对这3种方法的测量误差进行了比较，发现方法二的测量误差很大，方法一和方法三在一定的条件下都能使K_DP测量精度达到0.1°/km。     

An online model correction method based on an inverse problem: Part I—Model error estimation by iteration

Errors inevitably exist in numerical weather prediction (NWP) due to imperfect numeric and physical parameterizations. To eliminate these errors, by considering NWP as an inverse problem, an unknown term in the prediction equations can be estimated inversely by using the past data, which are presumed to represent the imperfection of the NWP model (model error, denoted as ME). In this first paper of a two-part series, an iteration method for obtaining the MEs in past intervals is presented, and the results from testing its convergence in idealized experiments are reported. Moreover, two batches of iteration tests were applied in the global forecast system of the Global and Regional Assimilation and Prediction System (GRAPES-GFS) for July-August 2009 and January-February 2010. The datasets associated with the initial conditions and sea surface temperature (SST) were both based on NCEP (National Centers for Environmental Prediction) FNL (final) data. The results showed that 6th h forecast errors were reduced to 10% of their original value after a 20-step iteration. Then, off-line forecast error corrections were estimated linearly based on the 2-month mean MEs and compared with forecast errors. The estimated error corrections agreed well with the forecast errors, but the linear growth rate of the estimation was steeper than the forecast error. The advantage of this iteration method is that the MEs can provide the foundation for online correction. A larger proportion of the forecast errors can be expected to be canceled out by properly introducing the model error correction into GRAPES-GFS.     

Limitations of an Eddy-Covariance System in Measuring Low Ammonia Fluxes

Green manuring of legume crops can improve soil fertility and sustainability. To evaluate its agronomic and environmental effectiveness, gaseous losses of ammonia (NH₃) in the surface layer need to be quantified by direct measurements in the field. However, the application of the eddy-covariance technique to atmospheric NH₃ is challenging: its high reactivity, water solubility, and low background concentrations all hinder the response time of closed-path sensors for fast measurements of NH₃ concentration. Ammonia emissions following green manuring were measured for 21 days using a flux system equipped with a fast-pulsed quantum-cascade tunable-infrared-laser spectrometer. The noisy cross-covariance function for this configuration indicates flux measurements are close to the limit of detection; the low signal-to-noise ratio further increases the uncertainties, introducing a mirroring effect on the fluxes, which results in the rapid alternation between emission and deposition, within the limit of detection (around 13 and 20 ng m^?2 s^?1, at the 95 and 99% confidence limits, respectively). An evaluation of the measurement errors is presented, focussing on three technical aspects of the eddy-covariance system: (1) time lag, (2) random error, and (3) limit of detection. The NH₃ fluxes measured by the spectrometer are close to its limit of detection, with a random error of the same order as the flux.

     

The influence of errors in precipitation measurements on the accuracy of the evaporation measurements performed by a class A evaporation pan

Summary Since uncorrected precipitation measurements are used for calculating the evaporation measured by a class A pan, precipitation measurement errors are introduced into the evaporation results. In defining the total error of the evaporation measurement it is necessary to consider the fact that the class A pan orifice and the rain gauge orifice are at different elevations. This paper presents a model to estimate the average value for the total error of evaporation. It is also shown that the evaporation measured by a class A pan is smaller than the actual evaporation by between 5 and 20%.     

Role of Parameter Errors in the Spring Predictability Barrier for ENSO Events in the Zebiak–Cane Model

ABSTRACT The impact of both initial and parameter errors on the spring predictability barrier （SPB） is investigated using the Zebiak Cane model （ZC model）. Previous studies have shown that initial errors contribute more to the SPB than parameter errors in the ZC model. Although parameter errors themselves are less important, there is a possibility that nonlinear interactions can occur between the two types of errors, leading to larger prediction errors compared with those induced by initial errors alone. In this case, the impact of parameter errors cannot be overlooked. In the present paper, the optimal combination of these two types of errors [i.e., conditional nonlinear optimal perturbation （CNOP） errors] is calculated to investigate whether this optimal error combination may cause a more notable SPB phenomenon than that caused by initial errors alone. Using the CNOP approach, the CNOP errors and CNOP-I errors （optimal errors when only initial errors are considered） are calculated and then three aspects of error growth are compared： （1） the tendency of the seasonal error growth; （2） the prediction error of the sea surface temperature anomaly; and （3） the pattern of error growth. All three aspects show that the CNOP errors do not cause a more significant SPB than the CNOP-I errors. Therefore, this result suggests that we could improve the prediction of the E1 Nifio during spring by simply focusing on reducing the initial errors in this model.     

Errors and correction of precipitation measurements in China

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.     

A forecast error correction method in numerical weather prediction by using recent multiple-time evolution data

The initial value error and the imperfect numerical model are usually considered as error sources of numerical weather prediction (NWP). By using past multi-time observations and model output, this study proposes a method to estimate imperfect numerical model error. This method can be inversely estimated through expressing the model error as a Lagrange interpolation polynomial, while the coefficients of polynomial are determined by past model performance. However, for practical application in the full NWP model, it is necessary to determine the following criteria: (1) the length of past data sufficient for estimation of the model errors, (2) a proper method of estimating the term "model integration with the exact solution" when solving the inverse problem, and (3) the extent to which this scheme is sensitive to the observational errors. In this study, such issues are resolved using a simple linear model, and an advection-diffusion model is applied to discuss the sensitivity of the method to an artificial error source. The results indicate that the forecast errors can be largely reduced using the proposed method if the proper length of past data is chosen. To address the three problems, it is determined that (1) a few data limited by the order of the corrector can be used, (2) trapezoidal approximation can be employed to estimate the "term" in this study; however, a more accurate method should be explored for an operational NWP model, and (3) the correction is sensitive to observational error.     

On the individual calibration of hailpads

This paper is a comparative study between the two most common hailpad calibration systems: one annual calibration of a whole consignment of material, and the individual calibration of each plate after a hailfall. Individual calibration attempts to minimize errors due to differences in sensitivity to the impact of hailstones between plates from the same consignment, or due to differences in the inking process before the actual measurement.The comparison was carried out using calibration data from the past few years in the hailpad network in south-western France, and data from an individual calibration process on material provided by the hailpad network in Lleida (Spain). The same type of material was used in the two cases.The results confirm that the error in measuring hailstone sizes is smaller in the case of an individual calibration of hailpads than when one single calibration process was carried out for a whole consignment. The former is approximately 80% of the latter. However, this error could have been higher if it had not been the same person carrying out the single calibration process and the measuring of the dents: it has been found that differences in the inking process may account for up to 20% of the error in the case of small hailstones. Calibration errors affecting other variables, e.g. energy or parameter λ of the exponential size distribution are generally higher (5% and 18%, respectively) than errors due to the spatial variability of the hailstones. However, the calibration method does not influence the maximum size, since the relative error attributed to the spatial variability is about 8 times the calibration error.In conclusion, if errors in determining energy or parameter λ are to be reduced to a minimum, it is highly advisable to be consistent in applying the measuring procedure (if possible with the same person carrying out the measurements all the time), and even to use individual calibration on each plate, always bearing in mind that technicians have to be trained appropriately in order to achieve the highest possible degree of uniformity.     

The equilibrium constant of NO2 with N2O4 and the temperature dependence of the visible spectrum of NO2: A critical review and the implications for measurements of NO2 in the polar stratosphere

Measurements of stratospheric NO₂ by ground-based visible spectrometers rely on laboratory measurements of absorption cross-sections. We review low-temperature laboratory measurements, which disagree by amounts claimed to be significant. Our recalculation of their errors shows that in general disagreements are not significant and that errors in the ratios of cross-sections at low to room temperature are between ±3% and ±8.8%. Of these errors, up to ±3.5% was contributed by errors in the equilibrium constant,K _p, in those measurements where the pressure was above 0.1 mbar.We review measurements and calculations ofK _p, which were accurate to ±5% from 300 to 233 K. Each method was potentially flawed. For example, infrared measurements of the partial pressure of NO₂ ignored the dependence of absorption on total pressure. From thermodynamic theory, formulae forK _pcan be derived from expressions for the variation of heat capacity with temperature. Contrary to common belief, coefficients in the formulae used by spectroscopists were not derived from the thermodynamic quantities. Rather, they were fitted to measurements or to calculations. Hence, they are empirical and it is dangerous to extrapolate below 233 K, the lowest temperature of the measurements.There are no measurements of NO₂ cross-sections below 230 K. Extrapolation of these cross-sections to analysis of measurements of NO₂ at the low temperatures of the Arctic and Antarctic stratosphere is also dangerous. For satisfactory analysis of polar spectra, the NO₂ cross-sections should be measured at temperatures down to 190 K with a relative accuracy of ±1%. This difficult experiment would need a cell of minimum length 32 m whose length can be adjusted. Because their effects are circular, many errors cannot be removed simply. Although circular errors also arise in the measurements ofK _pand of the infrared spectrum, their weights differ from those in the visible spectrum. The optimum experiment might therefore simultaneously measure the visible and infrared spectra andK _p.     

二等皮托管测风误差分析及偏差模拟计算

皮托管是组成风速检定装置的主要计量标准设备,其测量精度对检定质量具有重要影响.从皮托管测风原理出发,详细介绍了影响皮托管测风误差的相关因素,模拟计算了各因素对风速测量产生的影响,分析了影响皮托管测风误差的主要因子.结果表明：温度和阻塞系数是影响二等皮托管测风误差的主要因素.当环境温度偏差为±8℃时,可引起二等皮托管风速测量误差为干0.44 m/s（v=30 m/s）.当阻塞修正系数偏差±0.02时,可引起二等皮托管风速测量误差±o.6 m/s（v=30 m/s）;皮托管系数、大气压力和湿度经修正后对二等皮托管测风精度影响相对较小.     

双亮度差方法测量白天气象能见度时的误差分析

对数字摄像能见度观测系统采用双亮度差方法测量白天气象能见度时非标准观测条件引起的误差进行理论分析, 并给出了相应的误差控制措施。结果表明:对于正南、正北方地平线附近天空亮度的分布, 除了天空布满均匀云层和晴天的中午较为均匀以外, 其他时刻垂直相对梯度都较大, 通常在4%/°～10%/°范围内, 而水平相对梯度大多较小, 低于2%/°;不同组的目标-背景视线方向不一致是不容忽视的一个误差源, 为了限制和最大程度地减小其不利影响, 最好选择具有相同视线仰角的目标物和天空背景, 且视线方位角的差异越小越好;可对目标物两侧的天空背景的亮度进行测量, 内插获得与目标物视线方向一致的天空背景的亮度;视线方向上气柱照明不均匀会导致测量误差且人工无法调控, 应尽量选择下垫面特性较为均匀的观测场地, 通过多次采样平均在一定程度上能够减小其影响, 也可实时监测视野范围内场地和天空的亮度分布, 识别较差的照明状况以免获得误差较大的观测记录;利用树木、草丛、山体、墙壁和窗户等暗目标物难以满足双亮度差方法对观测条件的要求, 最好采用反射率足够低的人工实用黑体目标物。     

登陆热带气旋路径和强度预报的效益评估初步研究

近年来有关热带气旋(TC)灾情的评估指标和方法的研究取得明显进展,但较少涉及TC预报对减少灾害损失的贡献(即效益)分析。基于中央气象台的TC实时路径和强度预报,针对登陆中国大陆的TC,初步分析了TC的路径和强度预报误差与其造成的直接经济损失之间的可能关系,并在此基础上建立了包含TC路径和强度预报误差的TC直接经济损失的预估模型。TC登陆前后24 h的路径和强度预报误差与TC所致直接经济损失均呈正相关关系;对于单个登陆TC而言,若24 h TC路径预报误差每减小1 km可减少因灾直接经济损失约0.97亿元,若强度预报每减小1 m/s可减少因灾直接经济损失约3.8亿元(以2014年为基准年)。可见,提高TC路径和强度预报精度对于减灾的效益巨大,且当前尤以提高强度预报能力的效益为佳。      

Inversion method for multi-point source pollution identification: Sensitivity analysis and application to European Tracer Experiment data

Fast and accurate identification of unknown pollution sources plays a crucial role in the emergency response and source control of air pollution. In this work, the applicability of a previously proposed two-step inversion method is investigated with sensitivity experiments and real data from the first release of the European Tracer Experiment (ETEX-1). The two-step inversion method is based on the principle of least squares and carries out additional model correction through the residual iterative process. To evaluate its performance, its retrieval results are compared with those of two other existing algorithms. It is shown that for those cases with richer measurements, all three methods are less sensitive to errors, while for cases where measurements are sparse, their retrieval accuracy will rapidly decrease as errors increase. From the results of sensitivity experiments, the new method provides higher estimation accuracy and a more stable performance than the other two methods. The new method presents the smallest maximum location error of 18.20 km when the amplitude of the measurement error increases to 100%, and 22.67 km when errors in the wind fields increase to 200%. Moreover, when applied to ETEX-1 data, the new method also exhibits good performance, with a location error of 4.71 km, which is the best estimation with respect to source location.摘要快速并且准确地识别未知污染源, 在大气污染应急响应和源头控制过程中起着至关重要的作用. 本文利用敏感性试验及欧洲示踪物测场试验(ETEX-1)数据研究了新提出的两步反演算法的实用性, 并将其反演结果与现有的两种算法进行了对比分析. 敏感试验表明, 在观测数据较为丰富的情况下, 三种算法对观测误差和风场误差的敏感性均较低; 而当观测数据较为稀疏时, 所有算法的估计精度都将随着误差的增加而下降, 但与其他两种算法相比, 两步反演算法具有更高的估计精度以及更稳定的估计性能. 此外, 欧洲示踪物测场试验的源项估计结果也表明, 在三个算法中, 两步反演算法具有最小的位置估计误差.