一次闽南暖区暴雨的多尺度动力过程

作为气象研究中的一个难点问题,暖区暴雨的动力学一直为学界所关注。基于多尺度子空间变换(MWT)以及基于MWT的局地多尺度能量学分析和正则传输理论,对2018年5月7日的一次闽南暖区暴雨进行研究以了解其多尺度动力过程。首先将原始物理量场重建到三个尺度子空间:背景流子空间、天气尺度子空间和暴雨子空间。重构场上可以很好地看出背景环流尺度的高低空急流,以及暴雨尺度上的垂直环流。以往的研究普遍认为暖区暴雨的动力过程具有弱斜压性这一特征,而就此次事件而言,正压失稳和斜压失稳都起着很关键的作用,暴雨主要落区内既发生了正压失稳,也发生了斜压失稳。研究表明,对流层不同高度上的动力学存在差异,低层主要表现为正压失稳,天气尺度子空间与背景流子空间向暴雨子空间传输的动能相当; 中层主要是混合失稳,除正压失稳外,斜压正则传输也将有效位能从背景流子空间传输到了暴雨子空间,再通过浮力转换将有效位能转为动能,从而维持暴雨在中层的动力过程; 高层则与低层相似,但只存在背景流子空间向暴雨子空间的能量传输。      

快速中值滤波方法及其在Doppler雷达资料处理中的应用

提出了一种适用于Doppler雷达信号处理的快速中值滤波方法,与传统方法相比,它的特点是考虑了相邻中值滤波窗口内信号数据的相关性。在滤波过程中,由于该方法保留了前面滤波窗口内数据的排序信息,作为下一个滤波窗口内数据排序的参考,减少了当前滤波窗口内比较运算的次数,因此,提高了运算效率。我们将该种方法应用于Doppler雷达信号处理中,进行了3点、5点和7点中值滤波试验。结果表明,5点中值滤波较为适用于Doppler雷达信号处理,它既较好地保留了Doppler雷达信号,又有效地滤除了随机脉冲噪声。同时,由于Doppler雷达观测特点,对于雷达信号不宜进行方位中值滤波。     

Multi-sliding time windows based changing trend of mean temperature and its association with the global-warming hiatus

Based on three global annual mean surface temperature time series and three Chinese annual mean surface air temperature time series, climate change trends on multiple timescales are analyzed by using the trend estimation method of multi-sliding time windows. The results are used to discuss the so-called global-warming hiatus during 1998–2012. It is demonstrated that different beginning and end times have an obvious effect on the results of the trend estimation, and the implications are particularly large when using a short window. The global-warming hiatus during 1998–2012 is the result of viewing temperature series on short timescales; and the events similar to it, or the events with even cold tendencies, have actually occurred many times in history. Therefore, the global-warming hiatus is likely to be a periodical feature of the long-term temperature change. It mainly reflects the decadal variability of temperature, and such a phenomenon in the short term does not alter the overall warming trend in the long term.     

GRAPES-GFS模式2 m温度预报的最优时窗滑动订正方法

利用2017—2018年GRAPES-GFS模式预报资料和广西区域自动站逐时气温观测资料,分析模式预报偏差特征,发现GRAPES-GFS模式对广西区域2m温度的预报系统性偏低,随着预报时效增加,预报偏差增大,系统性偏差主要出现在桂北山区、左右江河谷及沿海;春夏秋三季的午后气温预报偏差有明显的系统性,冬季午后气温和四季凌晨气温预报偏差的随机性较大。为了确定滑动订正的最优时窗,通过活动时窗长度的方法,设计不同的滑动订正方案,制定最优时窗滑动订正方案,并进一步利用2020年最优时窗滑动订正业务试验产品,对比验证了该方案的订正效果。结果表明:分别采用固定时窗、季节最优时窗、月份最优时窗等滑动平均订正方案进行订正,春夏秋3季的订正效果明显好于冬季、午后订正技巧高于夜间,其中固定时窗滑动平均方案中的长时窗(15～60d)订正、季节最优时窗滑动订正以及月份最优时窗滑动订正这几种方式订正效果最优;所制定的最优时窗滑动平均订正方案,可以在不同滑动方案的基础上稳定地提高预报准确率,达到最优时窗滑动的目的。     

基于ERA Interim的L波段探空秒级风速算法检验

本文基于L波段探空雷达高垂直分辨率方位数据,通过在不同探空高度处选取不同尺度的时间窗口,设计了计算秒级风速的3种方案。通过比较3种计算方案得到的秒级风速与ERA-Interim再分析资料在平均偏差Bias和均方根误差RMSE等指标上的差异,给出了计算秒级风速的最优算法。结果表明:由于雷达的定位存在系统偏差,窗口选取过大或过小均会引入较大的秒级风速误差,选取适当尺度的时间窗口是准确计算秒级风速的必要条件。另外,基于ERA-Interim再分析资料具备良好的时空一致性,本文提出了1种检验L波段秒级风速算法优劣的新方案。     

Intermittency and the Exchange of Scalars in the Nocturnal Surface Layer

The determination of nocturnal surface fluxes in low wind conditions is a major problem for micrometeorological studies. The eddy correlation technique, extensively used in field measurements, becomes inappropriate if not enough turbulent activity exists. At the same time, the phenomenon of turbulence intermittency is responsible for the existence of localized events of short duration within which a large fraction of the total nighttime scalar exchange occurs. The scalar flux within a certain intermittent event varies considerably depending on the window used for the flux calculation. In many cases, events with very different time durations occur in the same night, and therefore, the proper determination of the surface flux would require averaging within data windows of different sizes for each event. In this work, the surface exchanges of temperature, moisture and carbon dioxide are analysed at a micrometeorological tower at southern Brazil. Intermittent turbulence is a common occurrence at the location. The analysis shows that the fluxes vary with turbulence intensity and the estimation technique. A variable-window size method for flux estimation is suggested and shown to cause an increase in the magnitude of the nocturnal surface fluxes     

滑动时间窗技术在地基GPS数据实时解算中的应用

滑动时间窗技术使用移动的时间窗定义参与解算的GPS(全球卫星定位系统)数据的起止时间,使得最新的观测数据得以加入实时的数据解算,获得最接近实况的观测结果。使用固定宽度的时间窗,可在保证模糊度解算精度的同时,占用最少的计算机资源。以2008年中国境内6个IGS(国际全球卫星定位服务局)测站全年数据为例,采用滑动时间窗技术,用不同的时间窗宽度计算各测站的逐时对流层参数,以CODE网站上公布的上述测站的逐日天顶总延迟(Zenith Total Delay,ZTD)作为标准值,分别统计其标准差,分析不同宽度的时间窗对ZTD解算精度的影响。结果表明,业务化的"地基GPS实时水汽反演系统"应用滑动时间窗技术,将时间窗宽度设定在8h左右,可以在获得高精度对流层参数的同时,满足业务的实时性需要。     

压、温、湿三线图的计算机屏幕绘制

该文提出了在显示器分辨率为ＥＶＧＡ的计算机屏幕上，绘制气象要素时间变化曲线的思路，给出了在同一显示屏上，开设多个显示窗口，模拟动画，图形局部放大，不同类别图象窗口快速切换等技巧，可供基层台站在业务工作中参考使用。     

Localized multiscale energy and vorticity analysis: I. Fundamentals

A new methodology, multiscale energy and vorticity analysis (MS-EVA), is developed to investigate the inference of fundamental processes from oceanic or atmospheric data for complex dynamics which are nonlinear, time and space intermittent, and involve multiscale interactions. Based on a localized orthogonal complementary subspace decomposition through the multiscale window transform (MWT), MS-EVA is real problem-oriented and objective in nature. The development begins with an introduction of the concepts of scale and scale window and the decomposition of variables on scale windows. We then derive the evolution equations for multiscale kinetic and available potential energies and enstrophy. The phase oscillation reflected on the horizontal maps from Galilean transformation is removed with a 2D large-scale window synthesis. The resulting energetic terms are analyzed and interpreted. These terms, after being carefully classified, provide four types of processes: transport, transfer, conversion, and dissipation/diffusion. The key to this classification is the transfer–transport separation, which is made possible by looking for a special type of transfer, the so-called perfect transfer. The intricate energy source information involved in perfect transfers is differentiated through an interaction analysis.The transfer, transport, and conversion processes form the basis of dynamical interpretation for GFD problems. They redistribute energy in the phase space, physical space, and space of energy types. These processes are all referred to in a context local in space and time, and therefore can be easily applied to real ocean problems. When the dynamics of interest is on a global or duration scale, MS-EVA is reduced to a classical Reynolds-type energetics formalism.     

Policy invention and entrepreneurship: Bankrolling the burying of carbon in the EU

This article presents the case of a policy invention where various kinds of entrepreneurship and a window of opportunity played important roles. In 2008 the EU adopted a new Carbon Capture and Storage (CCS) policy with an inventive funding instrument at its core: the NER 300 fund, based on revenues from the auctioning of emissions trading allowances. Thus far, the literature on policy entrepreneurs has focused more on success factors that enable particular persons to be especially influential than on the defining characteristics of entrepreneurship. We contribute to the literature on entrepreneurship and windows of opportunity by distinguishing two entrepreneurial techniques – framing and procedural engineering – and two categories of commitment – ‘tortoise’ and carpe diem. We conclude that ‘tortoises’ who contributed to creating the broad and general climate policy window paved the way for issue-specific carpe diemers who promoted the more specific NER 300 policy invention. Furthermore, we distinguish and discuss four different entrepreneurship mechanisms that may influence policy invention processes.     

Distributions of Downwelling Radiance at 10 and 20 μm in the High Arctic

In the Arctic, most of the infrared (IR) energy emitted by the surface escapes to space in two atmospheric windows centred at 10 and 20?μm. As the Arctic warms and its water vapour burden increases, the 20?μm cooling-to-space window, in particular, is expected to become increasingly opaque (or “closed”), trapping more IR radiation, with implications for the Arctic’s radiative energy balance. Since 2006, the Canadian Network for the Detection of Atmospheric Change has measured downwelling IR radiation with Atmospheric Emitted Radiance Interferometers at the Polar Environment Atmospheric Research Laboratory at Eureka, Canada, providing measurements of the 10 and 20?μm windows in the High Arctic. In this work, measurements of the distribution of downwelling 10 and 20?µm brightness temperatures at Eureka are separated based on cloud cover, providing a comparison to an existing 10?µm climatology from the Southern Great Plains. The downwelling radiance at both 10 and 20?μm exhibits strong seasonal variability as a result of changes in cloud cover, temperature, and water vapour. Given the 20?µm window’s limited transparency, its ability to allow surface IR radiation to escape to space is found to be highly sensitive to changes in atmospheric water vapour and temperature. When separated by season, brightness temperatures in the 20?µm window are independent of cloud optical thickness in the summer, indicating that this window is opaque in the summer. This may have long-term consequences, particularly as warmer temperatures and increased water vapour “close” the 20?μm window for a prolonged period each year.     

一次典型的平流层爆发性增温中的局地多尺度洛伦兹循环

利用一种新的工具,多尺度子空间变换(MWT),以及基于MWT的局地多尺度能量与涡度分析(MS-EVA)与Lorenz循环诊断方法,对2009年1月中下旬平流层发生的一次强爆发性增温(SSW)事件的内在动力学过程进行了研究。首先用MWT将各个场重构于三个尺度子空间,即平均尺度、爆发性增温尺度(或SSW尺度)和天气尺度子空间上。结果表明,极地迅速增长的温度主要是由于SSW尺度子空间上极区内的斜压不稳定引起的正则传输(有效位能从平均尺度子空间传输到SSW尺度子空间)造成的,显著增加的有效位能(APE)转换到了SSW尺度子空间的动能(KE)中,加之快速增温前极区内正压不稳定引起的正则传输(动能从平均尺度子空间传输到SSW尺度子空间)的作用,共同导致了极夜急流的反转。     

Variational Assimilation of GPS Precipitable Water Vapor and Hourly Rainfall Observations for a Meso-β Scale Heavy Precipitation Event During the 2002 Mei-Yu Season

Recent advances in Global Positioning System （GPS） remote sensing technology allow for a direct estimation of the precipitable water vapor （PWV） from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational （4DVAR） data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems （MCS） along the mei-yu front in China. The experiments with GPS-PWV assimilation cluster and also eliminated the erroneous rainfall successfully simulated the evolution of the observed MCS systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.     

雷达观测对应模式变量非线性特征及对四维变分同化的影响

四维变分同化（4DVar）中切线性模式和伴随模式的时间积分长度即为同化时间窗的长度。为理解线性模式时间积分长度对4DVar的具体影响,在雷达观测对应变量非线性分析的基础上,进行了一系列不同时间窗（10 min、20 min和30 min）4DVar单点观测试验和一次降雨的实际雷达同化和预报试验。从径向风同化来看:短时间窗（10 min）的风场增量更大、更局地;长时间窗(20 min、30 min)的风场增量则更具系统性特征,但会丢失一些小尺度信息,导致暴雨预报能力降低。从反射率同化来看:短时间窗对6 h内强降水预报有较明显的改善,较长时间窗甚至会降低降水预报效果。研究旨在为合理设置4DVar的同化时间窗提供参考,以有效利用高时空分辨率的雷达观测资料,又尽量减小线性化造成的误差,进而快速有效地同化雷达信息。      

Variational Assimilation of GPS Precipitable Water Vapor and Hourly Rainfall Observations for a Meso-β Scale Heavy Precipitation Event During the 2002 Mei-Yu Season

Recent advances in Global Positioning System (GPS) remote sensing technology allow for a direct estimation of the precipitable water vapor (PWV) from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational (4DVAR) data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems (MCS) along the mei-yu front in China.The experiments with GPS-PWV assimilation successfully simulated the evolution of the observed MCS cluster and also eliminated the erroneous rainfall systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.     

陆面气温资料的一种推广三维变分同化方法及其在简化情形的检验

发展了一种同化窗口为1个月的陆面气温推广三维变分资料同化方法,并建立了逐日资料到月平均资料的观测算子.作为对该同化方法的初步检验,以2000年1月中国陆地区域时间分辨率低、空间分辨率较高且在高原地区与台站观测资料比较接近的CRU(Climate Research Unit)月平均陆面气温资料作为观测,以时间分辨率高、空间分辨率较低且在高原地区与台站资料有较大误差的NCEP逐日气温资料作为背景场,采用背景误差协方差矩阵(简称B矩阵)的两种简化对角形式进行同化试验,得到高时空分辨率的格点陆面气温分析场,并进行对比分析和均方根误差检验.结果显示,由两种简化形式得到的逐日资料和月平均资料的质量均得到改善,在我国东南和中部大部分地区与台站观测基本一致,在青藏高原、新疆等台站稀疏地区与地形对应良好,为M-SDGVM模型或其他陆面过程模式高质量陆面气象驱动场的准备提供了一种新的手段.尤其在B矩阵中考虑了方差逐日变化的简化形式所得到的分析场整体上要优于不考虑的,这为最终在B矩阵中考虑协方差(即对推广三维变分同化不作简化)进一步改进同化效果打下了基础.     

Adaptation and the Guardrail Approach to Tolerable Climate Change

Windows delineating tolerable or "acceptable" conditions associated with climate change can be defined in terms of a variety of parameters; a preliminary window offered by the Scientific Advisory Council on Global Change of the Federal Government of Germany sets limits on temperature change and the rate of temperature change. Investment in adaptation can alter the size and shape of these windows, and different emissions trajectories are associated with different limiting points on their boundaries. As a result, the value of adaptation depends upon both the underlying structure of the tolerable window and the basecase emissions trajectory. Given uncertainty about both, the best near-term policy should be cast in a sequential decision-making framework. Seen in this light, improved adaptive potential can either reduce the cost of sustaining tolerable climate change or increase the opportunity cost of holding to more restrictive boundaries.     

不同 AMDAR资料同化时间窗对台风“摩羯”预报影响研究

2018年第14号台风“摩羯”对山东造成了大范围暴雨和大风天气,基于WRF（Weather Research and Forecasting）模式及其Hybrid-3DVAR混合同化预报系统,对Hybrid-3DVAR不同集合协方差比例和不同航空气象数据转发（aircraft meteorological data relay,以下简称AMDAR）资料同化时间窗对台风“摩羯”预报的影响进行了数值研究。结果表明：加大集合协方差比例对台风“摩羯”路径预报有较大影响和改进;当全部取来自集合体的流依赖误差协方差时,预报的台风路径最好,降水预报也最接近实况;AMDAR资料同化对于台风路径和降水预报也有正的改进作用,但加大集合协方差比例到100%时对台风路径预报影响更大;不同资料同化时间窗会影响同化的AMDAR资料数量,从而影响台风降水精细化预报;45 min同化时间窗的要素预报误差最小,对台风造成的强降水精细特征预报最接近实况;不同资料同化时间窗主要影响台风降水预报落区分布,对台风路径预报影响相对较小。     

Comparison of fractal dimension oscillations and trends of rainfall data from Pastaza Province,Ecuador and Veneto,Italy

Since climate trends are getting considerable attention in recent years, we aimed in this study to compare trends and rhythms of complexity (fractal dimension, FD) of rainfall data series between two continents: Latin America and Europe. Two parallel nonlinear methods for calculating FD of a temporal data series, Higuchi's and consecutive differences, were combined with Fast Fourier Transform (FFT) to obtain FD oscillations of monthly accumulated rainfall. The data were collected for the last thirty years in Pastaza province, Ecuador and Veneto province, Italy. In order to calculate their FD time dependence, FD(t), moving windows of different lengths (short, 10–20 and long 21–350 samples), were applied. Both methods, each combined with FFT, detected identical (or very similar) rhythms of detrended FD(t) in the two data series, but frequencies with dominant amplitudes differed (4.4 years in Ecuador, 10.3 years in Italy). Long-term FD(t) trends were also studied using optimized long window lengths (~ 200 samples). A linear positive trend was obtained for the Ecuadorian rainfall data over the whole recorded period. Italian fractal trend profile was, however, characterized by two periods: a constant high value for years 1974–1993, followed by a linear decrease for 1993–2005. Trend results, obtained with two different methods, were also similar. Accordance of the results, reported in the present paper by applying these two methods, validates their use as a tool in future fractal meteorological measurements. As well, these results indicate that positive FD trend obtained for Pastaza (Ecuador) and negative trend computed for Veneto (Italy) account for a local or regional phenomenon, most probably caused by extensive deforestation and land use change (Ecuador) and continental or global atmospheric pattern variability (Italy).     

Improving the methodology for spectral analysis of climatic time series

The paper discusses a methodology able to estimate both the discrete and continuous spectra without any assumption on the shape of spectral densities. The approach to estimate the spectral density is based on a robust smoothing of the periodogram. Bandwidth, a quantity similar to the width of spectral windows traditionally used in spectral analysis, is estimated locally in contrast to intuitively chosen global window lengths. Detection and estimation of frequencies forming discrete spectra are also addressed. The procedure is applied to Central England temperature (CEt), North Atlantic Oscillation (NAO) index and Oxygen Isotope of North Greenland Ice Core Project (δ¹⁸O of NGRIP) data. Annual and half annual cycles were detected in CEt data, whilst 118.2- and 41.7-ky cycles were found in δ¹⁸O of NGRIP. This latter periodicity is almost as intense as the dominant longer cycle. Several local peaks of spectral densities were recognised in each time series that mostly cover earlier results. However, a few previous findings at low frequencies have not been reinforced by the present method. Identification of modest local peaks or discrete amplitudes at low frequencies is an extremely challenging task as climatic data generally have spectral densities rising to low frequencies.