NWP 模式热量系统误差的动力诊断分析

文章证明了模式在预报时段的位温误差，是由于在模式大气和真实大气中，该时段内位温变化过程的不同而造成的。还证明了原始方程的无加速定理对各强迫因子的线性分解同样适用于研究NWP模式热量误差的成因。对国家气象中心T42L9模式1992年1月和7月预报结果的动力诊断表明，模式对纬向位温分布具有较好的预报能力，但在各纬带也存在明显的误差。通过无加速定理的分解分析，研究了这些误差的成因及改善模式的可能途径。     

提高月预报业务水平的动力相似集合方法

针对基于大气环流模式的月预报问题,提出了一种能有效减小预报误差并提高预报技巧的动力相似集合预报新方法。该方法着眼于动力模式与统计经验的内在结合,在模式积分过程中通过提取大气环流历史相似性信息,对模式误差进行参数化处理,形成多个时变的相似强迫量来扰动生成预报的集合成员。将这一集合新方法应用到中国国家气候中心业务大气环流模式(BCC AGCM1.0),一组10 a准业务环境下回报试验结果显示,相比于业务集合预报,动力相似集合预报方法能有效改进模式对于大气环流的纬向平均、超长波和长波预报,从而有效提高了月平均环流预报技巧(几乎达到业务可用标准)和逐日环流预报技巧,并显著降低了预报误差,合理增加集合离散度,使二者配置关系得以改善,有望在业务预报中应用。     

原始方程系统中的无加速定理II:纬向平均温度的变化

利用作者在本文第Ⅰ部分提出的原始方程系统中的无加速定理,这部分讨论大气动量、热量的内外源强迫对纬向平均温度场的作用。数值计算结果表明:外源热力强迫引起的温度场的变化主要在对流层下层;而热力内强迫的作用在中高纬对流层中分布较均匀,两者在维持纬向平均温度场的变化中十分重要。机械外强迫和机械内强迫各自的贡献次之。平均经圈环流的贡献则主要在对流层顶附近及平流层中,由于热力内强迫产生的位温变化在一定程度上大致被热力外强迫所平衡,而机械内、外强迫则具有相似的空间分布,从而,总的热力强迫所引起的位温变化的分布基本上为总的机械强迫作用所平衡,纬向平均位温的准定常状态由此得以维持。     

原始方程系统中的无加速定理——Ⅱ:纬向平均温度的变化

利用作者在本文第Ⅰ部分提出的原始方程系统中的无加速定理,这部分讨论大气动量、热量的内外源强迫对纬向平均温度场的作用。数值计算结果表明:外源热力强迫引起的温度场的变化主要在对流层下层;而热力内强迫的作用在中高纬对流层中分布较均匀,两者在维持纬向平均温度场的变化中十分重要。机械外强迫和机械内强迫各自的贡献次之。平均经圈环流的贡献则主要在对流层顶附近及平流层中,由于热力内强迫产生的位温变化在一定程度上大致被热力外强迫所平衡,而机械内、外强迫则具有相似的空间分布,从而,总的热力强迫所引起的位温变化的分布基本上为总的机械强迫作用所平衡,纬向平均位温的准定常状态由此得以维持。     

青藏高原对东亚纬向型环流形成的动力作用

本文用大气环流的气候资料,指出东亚地区纬向型环流较多。利用原始方程数值模拟和简单的理论分析讨论了形成区类环流特征的动力机制;并指出东亚纬向型环流比北美多,可能是与青藏高原和洛矶山高原的地形强迫性动力作用的特点不同有关。     

纬向平均环流预报的系统性误差及其改进

大量的月预报实例分析表明,纬向平均环流(本指高度场纬向平均分量)存在明显的系统性预报误差,且在总误差中占有可观的份额。国内外其它模式也存在类似的现象。为克服这一困难,本尝试了“结合”(hybrid)的途径。应用重构相空间理论和非线性时空序列预测方法,在大量历史资料的基础上,构造了月尺度逐侯纬向平均高度场(零波分量)距平场的非线性预报模型。然后,将非线性预报和谱模式动力预报结合起来,即将非线性预报结果转化为模式需要的颅报量,再在模式积分过程中的每一步取代其相应部分,实施过程订正。初步试验结果表明,这种途样合效地减少了模式纬向环流的预报误差;特别是通过非线性波流相互作用,还改善了部分波动分量的预报。     

与非线性区域预测方法结合的月延伸预报试验Ⅰ:纬向平均环流的预报

为克服数值模式普遍存在的纬向平均环流预报误差,文中在36a NCEP/NCAR再分析高度场资料的基础上,应用非线性时空序列预测理论的局域近似法构建了200,300,500和700hPa4个等压面上的月尺度逐候纬向平均高度距平场非线性动力学区域预报模型.对1996年12个月所做的预报试验表明,无论是南、北半球中高纬度地区还是低纬度地区,非线性模型的候纬向平均高度预报结果均优于持续性预报、气候预报和T42L9模式动力预报.用非线性结果对T42L9模式月平均高度场预报结果进行订正,则使该谱模式系统性预报误差显著减少,也大大减少了其预报高度场的均方根误差,相应地,高度场距平相关评分也有一定程度的提高,表明纬向平均高度的非线性预报比谱模式动力预报包含了更多的有用信息.     

热带大气平均环流的纬向不均匀性和Kelvin波的动力作用

本文利用一个包含Wave-CISK机制以及蒸发、感热与扰动风场的反馈机制，并引入实际的下垫面温度分布和海陆差异的热带大气模式，较好地模拟了低纬平均环流在风场、散度场及低层位势高度场上的纬向非均匀性。分析表明这种纬向非对称性是由于下垫面的热力非均匀性造成的强迫与大气内部的热力-动力反馈过程相互作用的结果。对热力强迫的响应形成了西太平洋暖水区上的西风和东太平洋上的东风，而对简化模式的解析分析说明，由于热力-动力反馈造成的Kelvin波的发展过程，可以解释平均东风强于西风的事实。     

7月中低纬地区流场的模拟特征

利用ｐ－σ混合坐标系原始方程５层球带模式，对７月中低纬流进行数值模拟，重点分析近地面流场，经圈环流、纬向风随高度的变化及越赤道气流的模拟特征，结果表明，季风区和非季风区的经圈环流及纬向风的垂直分布，存在着明显的差异，并能清楚地看到海陆热力差异对大气环流的影响。     

与非线性区域预测方法结合的月延伸预报试验I:纬向平均环流的预报

为克服数值模式普遍存在的纬向平均环流预报误差 ,文中在 3 6aNCEP/NCAR再分析高度场资料的基础上 ,应用非线性时空序列预测理论的局域近似法构建了 2 0 0 ,3 0 0 ,50 0和 70 0hPa 4个等压面上的月尺度逐候纬向平均高度距平场非线性动力学区域预报模型。对 1996年 12个月所做的预报试验表明 ,无论是南、北半球中高纬度地区还是低纬度地区 ,非线性模型的候纬向平均高度预报结果均优于持续性预报、气候预报和T 42L9模式动力预报。用非线性结果对T42L9模式月平均高度场预报结果进行订正 ,则使该谱模式系统性预报误差显著减少 ,也大大减少了其预报高度场的均方根误差 ,相应地 ,高度场距平相关评分也有一定程度的提高 ,表明纬向平均高度的非线性预报比谱模式动力预报包含了更多的有用信息     

DIAGNOSIS OF NWP SYSTEMATIC FORECAST ERRORS IN ZONAL MEAN CIRCULATION

It is proved in this paper that NWP systematic forecast errors in the zonal mean circulation aredue to the difference in westerly acceleration process during the forecasting period between model andreal atmospheres.Those forcing factors which evoke the zonal mean wind variation can be split into various linearterms according to the non-acceleration theorem in a primitive equation system,By applying this tech-nique to the diagnosis of the forecast produets of the T42L9 model in January 1992 and in July 1992,it is indicated that the model has the ability to forecast the zonal mean wind to a reasonable extent,but there are still some errors in several places,especially in the upper troposphere and lower strato-sphere in the mid-latitude region as well as near the surface.The results of analysis by employing thisscheme reveal the reason responsible for the systematic forecast errors of the zonal mean wind in themodel and the possible way of improving it.It is also shown that non-acceleration theorem can be used as an efficient tool to diagnose thephysical processes of NWP models.     

各种物理强迫激发的平均经圈环流特征及其对数值天气预报模式系统误差的贡献

本文证明7种强迫作用激发经圈环流的线性叠加性，分项考察了各种物理强迫激发经圈环流的特征，通过考察一个数值模式的模式大气和实际大气各种物理强迫激发经圈环流的差异，分析了模式系统误差的成因，这种建立在动力背景之上的模式误差分析方法，其物理意义明确，具有较为普遍的适用性。     

The impact of the assimilation of scatterometer winds on surface wind and wave forecasts

Recent work has demonstrated that surface marine winds from the Bureau of Meteorology's operational Numerical Weather Prediction (NWP) systems are typically underestimated by 5 to 10%. This is likely to cause significant bias in modelled wave fields that are forced by these winds. A simple statistical adjustment of the wind components is shown to reduce the observed bias in Significant Wave Height considerably. The impact of increasing the vertical resolution of the NWP model and assimilating scatterometer data into the model is assessed by comparing the resulting forecast wind and waves to observations. It is found that, in general, the inclusion of scatterometer observations improves the accuracy of the surface wind forecasts. However, most of the improvement is shown to arise from the increased number of vertical levels in the atmospheric model, rather than directly from the use of the observations. When the wave model is forced with surface winds from the NWP model that includes scatterometer data, it is found that the scatterometer assimilation does not reduce the systematic bias in surface wave forecasts, but that the random errors are reduced.     

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.     

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.     

数值天气预报多要素深度学习融合订正方法

数值天气预报作为现代天气预报的主流技术方法,近年来不断朝着精细化方向发展,但预报误差至今仍无法避免.文中在CU-Net模型中引入稠密卷积模块形成数值预报要素偏差订正模型Dense-CUnet,在此基础上进一步融合多种气象要素和地形特征构建了Fuse-CUnet模型,开展不同模型的偏差订正试验和对比分析.以均方根误差(R...     

GRAPES_GFS 2.0模式非系统误差评估

选取2014年1月、4月、7月、10月的GRAPES_GFS 2.0预报产品和对应时刻的NCEP FNL分析资料进行对比。从时间演变看,南、北半球的非系统误差均在各自冬季达到极盛,误差呈现周期性变化规律。位势高度场的非系统误差随时间演变先呈指数增长,后呈线性增长,温度场和纬向风场的误差则近似于线性增长。从空间分布看,GRAPES_GFS 2.0的非系统误差大值主要分布在中高纬度地区,呈条带状分布,误差大值区域基本不随预报时效的变化而发生变化;位势高度场和纬向风场的误差大值区出现在对流层顶附近,而温度场的误差大值区则出现在边界层顶附近。将误差增长曲线参数化拟合后发现,南半球的初始场误差、可预报上限和初始场误差占比均高于北半球,随离地高度增加初始场误差占比逐渐减小。     

2004年主汛期各数值预报模式定量降水预报评估

随着数值预报技术的飞速发展, 模式定量降水预报已成为天气预报业务工作中的主要参考依据。本文对目前在国家气象中心应用的3个业务运行模式T213L31, HLAFS0.25, 华北中尺度模式MM5和德国模式及日本模式的降水预报产品进行了季节空间分布、区域时间序列演变及统计检验, 试图从空间、时间及统计方面对降水预报产品的预报性能进行综合评估。检验结果表明:目前的数值预报模式对短期时效内定量降水预报均具有一定的空间预报能力, 但强降水中心位置有一定的偏差; 从时间序列演变检验来看, 模式对区域强降水过程的发展趋势具有较强的预报能力, 但降水量预报与实况有一定的差距; 从累加统计评分检验结果来看, 模式短期时效的预报性能差别不大, 全球模式在小中雨预报方面有一定优势, 其中日本模式的综合预报性能最好, 大雨以上量级的预报则是国内的模式有一定的优势, 其中华北中尺度MM5模式, T213L31模式各有所长, 但均存在预报量和预报区偏大问题。