运用体积降水量预测2008年西江洪水的方法

针对2008年西江流域大洪水期间提出了体积降水量的概念及其计算方法,在计算出西江流域和其各子流域逐日和总体积降水量的基础上,将体积降水量与水文站的水位进行了对比分析,并建立洪水水位预测的计算公式。结果表明:可以提前3天作出西江下游水位的预测,如果利用数值天气预报产品在预报体积降水量方面的优势,可以进行体积降水量的客观预报,为防汛工作提供重要的依据。     

渭河流域2次洪灾期间体积降水量分析

针对2003年8—10月和2005年9—10月期间渭河流域洪涝灾害,提出了过程体积降水量的概念及其计算方法,在计算出洛河、泾河、渭河流域上游、渭河流域下游及渭河流域总体积降水量的基础上,将体积降水量与临潼、华县水文站的水位和流量进行了对比分析。结果表明:水位对体积降水量有较好的即时响应,流量对体积降水量有较好的延迟响应。     

渭河流域2次洪灾期间体积降水量分析

针对2003年8—10月和2005年9—10月期间渭河流域洪涝灾害,提出了过程体积降水量的概念及其计算方法,在计算出洛河、泾河、渭河流域上游、渭河流域下游及渭河流域总体积降水量的基础上,将体积降水量与临潼、华县水文站的水位和流量进行了对比分析。结果表明:水位对体积降水量有较好的即时响应,流量对体积降水量有较好的延迟响应。

     

水库流域体积降水量预报方法研究

根据广东飞来峡水库流域汇流特征,将全流域划分为5个支流,并采用求积仪分别计算各支流面积;然后用加权平均法计算各支流的面雨量,并将各支流面雨量对相应的支流面积进行积分,计算各支流体积降雨量;利用洪水过程飞来峡水库入库流量、出库流量和水库流域蒸发量对体积降水量预报结果进行验证,求出误差订正系数.结果表明:利用加权平均法计算的水库流域体积降水量,经过误差订正后,预报准确率可控制在90%左右,基本满足预报业务服务要求.     

ECMWF细网格要素预报场在乌鲁木齐米东区的预报性能检验

利用升级后的ECMWF细网格模式2m温度、大尺度降水量(LSP)、累积降水量(TP)及850hPa风速等气象要素预报场,采用客观分析和统计学方法,对2015年2月至2017年1月乌鲁木齐米东区气温、降水及风速进行检验分析。结果表明:2m温度场对于米东区最高、最低气温有较好的预报能力,最高、最低气温年均准确率ECMWF细网格模式产品均高于中央气象台指导预报产品,分别达69.1%和73.8%。细网格和中央气象台指导预报的晴雨准确率均接近或超过80%,对降水天气预报有较好的参考价值;降水分级检验上看,ECMWF细网格和中央指导预报准确率均不太高;对于降雨天气,细网格的预报能力略高于指导预报;对于降雪天气,指导预报对小雪和大雪的预报准确率高于细网格;ECMWF细网格850hPa风速产品与实况风速有较好的相关性,对逐日风的预报有较好地指示意义。     

淮河流域2016年汛期洪水预报试验

预报大流域降雨径流与洪水是非常复杂的预报难题。本研究建立气象水文耦合预报模型对复杂大流域的洪水预报进行预报试验。模型采用中央气象台格点化降水预报产品作为预见期内降水,驱动水文水动力学耦合模型进行洪水预报。选择新安江水文模型用于流域降雨径流模拟,基于扩散波与柱蓄和楔蓄理论建立Muskingum-Cunge水位流量演算模型进行具有行蓄洪区的复杂河系洪水预报。以淮河鲁台子站以上流域2016年汛期洪水为例,将构建的气象水文耦合预报模型进行洪水预报试验。结果表明,模型取得了较好的预报精度,应用格点化降水预报产品考虑预见期内降水预报的洪水预报对于不考虑预见期降水预报,洪水预报预见期得到一定的有效延长,对同类流域预报有一定的借鉴意义。     

淮河流域2016年汛期洪水预报试验

预报大流域降雨径流与洪水是非常复杂的预报难题。本研究建立气象水文耦合预报模型对复杂大流域的洪水预报进行预报试验。模型采用中央气象台格点化降水预报产品作为预见期内降水,驱动水文水动力学耦合模型进行洪水预报。选择新安江水文模型用于流域降雨径流模拟,基于扩散波与柱蓄和楔蓄理论建立Muskingum-Cunge水位流量演算模型进行具有行蓄洪区的复杂河系洪水预报。以淮河鲁台子站以上流域2016年汛期洪水为例,将构建的气象水文耦合预报模型进行洪水预报试验。结果表明,模型取得了较好的预报精度,应用格点化降水预报产品考虑预见期内降水预报的洪水预报对于不考虑预见期降水预报,洪水预报预见期得到一定的有效延长,对同类流域预报有一定的借鉴意义。     

低纬度地区局地暴雨的神经网络预报方法研究

以南宁市所辖8个站暴雨集中的6-8月逐日降水量作为预报对象,采用人工神经网络方法进行了新的数值预报产品释用预报方法研究.通过运用动力相似法,结合日本降水预报模式对未来暴雨发生的可能性进行判别,然后通过对欧洲中期数值预报中心预报场进行滑动分区车氏展开计算,求出与降水量序列相关较好的预报因子,并对这些因子进行自然正交分解,有效浓缩数值预报产品因子,建立了南宁市逐日暴雨的神经网络释用预报模型.利用该预报模型,对2006年6-8月的逐日暴雨预报试验结果表明,该预报模型对南宁市的暴雨强降水具有很好的预报能力.     

细网格数值预报产品在精细化预报中的释用

利用齐齐哈尔市十个自动站降水和温度资料对2013年欧洲中心确定性模式高分辨率预报产品、东北半球T639数值产品、日本高分辨率大气模式产品和中央气象台的全国城市预报产品进行系统误差订正基础上,进行基于超级集合思想的多模式动态变权集成预报。结果表明:三种细网格和中央气象台的全国城市预报产品对齐齐哈尔地区的降水预报都存在着较多的空报现象;对四种模式预报进行集成平均,在齐齐哈尔地区预报效果极其有限;动态权重集成预报能够较好地利用各种数值预报的优势,从而得到质量好的定性预报产品。定性降水、最低温度和最高温度的集成预报比任何单一的数值预报成员TS预报评分都要高,尤其是最低温度预报质量得到了很大的提升,给预报员提供了很好的参考工具。     

一种由单值预报生成定量降水概率预报的方法及初步应用

利用1981年1月1日至2003年12月31日淮河流域59个站的降水观测及同时段美国GFS集合预报模式回算的24 h降水量集合平均预报资料,建立条件亚正态分布函数的概率预报模型并得到集成预报.针对淮河流域子流域的试验结果表明:新方法生成的集成预报的均方根误差在所有子流域和各个季节的误差都有显著降低,其中蚌埠至洪泽湖流域6月的均方根误差降低了3.11 mm.4个子流域通过该模型得到的集成预报的Brier技巧评分在0.16～0.61,说明该集成预报在整年都具有一定预报价值.在淮河上游大坡岭至息县流域,当实际日面雨量阈值为0.00～7.82 mm的预报时,夏季的集成预报出现不同程度的低报;但当实际日面雨量阈值为18.12 mm时,夏季的集成预报表现出较好的可靠性.百分位评估则进一步表明该集成预报能较好地预报出小量级的面雨量,而对30.00 mm以上面雨量的预报能力相对较弱.     

Humidity Effect and Its Influence on the Seasonal Distribution of Precipitation δ18O in Monsoon Regions

The humidity effect, namely the markedly positive correlation between the stable isotopic ratio in precipitation and the dew-point deficit △Td in the atmosphere, is put forward firstly and the relationships between the δ18O in precipitation and △Td are analyzed for the Urumqi and Kunming stations, which have completely different climatic characteristics. Although the seasonal variations in δ18O and △Td exhibit differences between the two stations, their humidity effect is notable. The correlation coefficient and its confidence level of the humidity effect are higher than those of the amount effect at Kunming, showing the marked influence of the humidity conditions in the atmosphere on stable isotopes in precipitation.Using a kinetic model for stable isotopic fractionation, and according to the seasonal distribution of meanmonthly temperature at 500 hPa at Kunming, the variations of the δ18O in condensate in cloud aresimulated. A very good agreement between the seasonal variations of the simulated mean δ18O and themean monthly temperature at 500 hPa is obtained, showing that the oxygen stable isotope in condensateof cloud experiences a temperature effect. Such a result is markedly different from the amount effect atthe ground. Based on the simulations of seasonal variations of δ18O in falling raindrops, it can be foundthat, in the dry season from November to April, the increasing trend with falling distance of δ18O in fallingraindrops corresponds remarkably to the great ATd, showing a strong evaporation enrichment function infalling raindrops; however, in the wet season from May to October, the δ18O in falling raindrops displaysan unapparent increase corresponding to the small ATd, except in May. By comparing the simulated meanδ18O at the ground with the actual monthly δ18O in precipitation, we see distinctly that the two monthlyδ18O variations agree very well. On average, the δ18O values are relatively lower because of the highlymoist air, heavy rainfall, small △Td and weak evaporation enrichment function of stable isotopes in thefalling raindrops, under the influence of vapor from the oceans; but they are relatively higher because of the dry air, light rainfall, great △Td and strong evaporation enrichment function in falling raindrops, under the control of the continental air mass. Therefore, the δ18O in precipitation at Kunming can be used to indicate the humidity situation in the atmosphere to a certain degree, and thus indicate the intensity of the precipitation and the strength of the monsoon indirectly. The humidity effect changes not only the magnitude of the stable isotopic ratio in precipitation but also its seasonal distribution due to its influence on the strength of the evaporation enrichment of stable isotopes in falling raindrops and the direction of the net mass transfer of stable isotopes between the atmosphere and the raindrops. Consequently, it is inferred that the humidity effect is probably one of the foremost causes generating the amount effect.     

Spectra of temperature derivatives in the atmospheric surface layer

Measured spectra ofθ _x,θ _y,θ _z, the derivatives of temperature in streamwise, lateral and vertical directions, respectively, indicate that the spectral densities ofθ _z andθ _y are nearly similar but significantly different from the spectral density ofθ _x. The high-frequency parts of the three spectra satisfy, in a qualitative sense, local isotropy requirements. In the high-frequency end of the inertial subrange, the relative behaviour of spectra ofθ _x,θ _y andθ _z is also consistent with local isotropy.     

CHAOTIC OUTPUT OF SST FLUCTUATION STOCHASTIC MODEL WITH GIVEN PARAMETERS

Starting from the Saltzman's air-sea stochastic climatic model, we have derived a langevin-type equation describing SST fluctuation and the related pokker-Plank expression, which were then numerically solved with parameters given, yielding the probability density curve P(x, t) of multiple bifurcations, with the Cantor set of images given in phase space of P(x, t) and P(x, t+τ), thereby indicating that chaotic output comes from the random system under the conditions of the above parameters.     

用微气象方法估算淮河流域能量平衡(HUBEX/IOP 1998/99)的统计分析和比较研究

In order to study energy and water cycles in the Huaihe River Basin, micrometeorological measurements were carried out in Shouxian County, Anhui Province, during HUBEX/IOP (May to August 1998 and June to July 1999). The employed techniques included Bowen Ratio-Energy Balance (BREB) and Eddy Covariance (EC) methods. In this paper, the basic characteristics of the energy balance components in the district are analyzed. Furthermore, the results are compared with those from other regions of China.The main results are as follows: (1) There was a consistency between the available energy (Rn-G) and the sum of sensible (H) and latent (E) heat fluxes measured by the EC method (H+E)ec, but Ebr was slightly larger (about 10%) than Eec; (2) Most of the net radiation (Rn) was used to evaporate water from the surface. During HUBEX/IOP in 1998 and 1999, the mean daily amounts of Rn were 13.89 MJ m-2 d-1 and 11.83 MJ m-2 d-1, and the mean Bowen Ratios (β) were 0.14 (over ruderal) and 0.06 (over paddy) respectively; (3) The diurnal variation characteristic of β was larger and unsteady at sunrise and sunset, and smaller and steady during the rest of the daytime. Local advection appeared in the afternoon over paddy areas in 1999; (4) In comparison with the results from other regions of China, the nean β was the lowest (0.06) over paddy areas in the Huaihe River Basin and the highest (0.57) during June-August 1998 in Inner Mongolia grassland. The Bowen Ratio β is mainly related to the soil humidity.     

Simulations of Stable Isotopic Fractionation in Mixed Cloud in Middle Latitudes―Taking the Precipitation at ürǖmqi as an Example

The introduced mathematical model takes into account the role of the kinetic fractionation effect in a supersaturation environment at the ice surface as liquid and solid phases coexist in mixed cloud. Using the model, the temperature effect of stable isotopes in precipitation is simulated under different cooling conditions. The rate of change of δ18O against temperature in the process of wet adiabatic cooling is smaller than in the process of isobaric cooling under the same humidity. The increasing supersaturation ratio at the ice surface, Si, leads to the strengthening of the kinetic fractionation effect. The kinetic fractionation function makes the synthesis fractionation factor decreased and the change of δ18O with temperature flatted, compared with that in the equilibrium state. The simulated results show that the slope parameter b and the intercept d of the meteoric water line (MWL), δD = bδ18O+d, in wet adiabatic cooling are both greater than those in isobaric cooling. The global MWL lies between the two MWLs simulated under wet adiabatic and isobaric cooling processes, respectively. The magnitudes of b and d are directly proportional to Si. The greater the Si, the stronger the kinetic fractionation effect, and thus the greater the b and d, and vice versa. However, b and d have low sensitivity to the liquid-water contents in the cloud. Using the kinetic fractionation model, the variation of stable isotopes in precipitation at Urumqi is simulated. The simulated stable isotopic ratio vs temperature and the δD vs δ18O curves are very consistent with the actual regressions and MWL at Uruimqi, respectively.     

The prediction of dust erosion by wind: An interactive model

We have devised a partial differential equation for the prediction of dust concentration in a thin layer near the ground. In this equation, erosion (detachment), transport, deposition and source are parameterised in terms of known quantities. The interaction between a wind prediction model in the boundary layer and this equation affects the evolution of the dust concentration at the top of the surface layer. Numerical integrations are carried out for various values of source strength, ambient wind and particle size. Comparison with available data shows that the results appear very reasonable and that the model should be subjected to further development and testing.Notation (x, y, z, t) space co-ordinates and time (cm,t) - u, v components of horizontal wind speed (cm s^–1) - u _g, v_g components of the geostrophic wind (cm s^–1) - V=(u²+v²)^1/2 (cm s^–1) - (û v)= 1/(h – k) _k ^h(u, v)dz(cm s^–1) - V _* friction velocity (cm s^–1) - z ₀ roughness length (cm) - k ₁ von Karman constant =0.4 - V _d deposition velocity (cm s^–1) - V _g gravitational settling velocity (cm s^–1) - h height of inversion (cm) - k height of surface layer (cm) - potential temperature (°K) - _gr potential temperature at ground (°K) - _K potential temperature at top of surface layer (°K) - P pressure (mb) - P ₀ sfc pressure (mb) - C _p/C_v - (t)= /z lapse rate of potential temperature (°K cm^–1) - A(z) variation of wind with height in transition layer - B(z) variation of wind with height in transition layer - Cd drag coefficient - C _HO transfer coefficient for sensible heat - C dust concentration (g m^–3) - C _K dust concentration at top of surface layer (g m^–3) - D(z) variation with height of dust concentration - u, v, w turbulent fluctuations of the three velocity components (cm s^–1) - A ₁ constant coefficient of proportionality for heat flux =0.2 - Ri Richardson number - g gravitational acceleration =980 cm s^–2 - Re Reynolds number = - D _s thickness of laminar sub-layer (cm) - v molecular kinematic viscosity of air - coefficient of proportionality in source term - dummy variable - t time step (sec) - n time index in numerical equations On sabbatical leave at University of Aberdeen, Department of Engineering, September 1989–February 1990.     

A K-Theory of Dispersion,Settling and Deposition in the Atmospheric Surface Layer

Dispersion estimates with a Gaussian plume model are often incorrect because of particle settling (β), deposition (γ) or the vertical gradient in diffusivity (K _v (z) = K ₀ + μz). These “non-Gaussian” effects, and the interaction between them, can be evaluated with a new Hankel/Fourier method. Due to the deepening of the plume downwind and reduced vertical concentration gradients, these effects become more important at greater distance from the source. They dominate when distance from the source exceeds L _β = K ₀ U/β ², L _γ  = K ₀ U/γ ² and L _μ = K ₀ U/μ ² respectively. In this case, the ratio β/μ plays a central role and when β/μ = 1/2 the effects of settling and K gradient exactly cancel. A general computational method and several specific closed form solutions are given, including a new dispersion relation for the case when all three non-Gaussian effects are strong. A more general result is that surface concentration scales as C(x) ~ γ ⁻² whenever deposition is strong. Categorization of dispersion problems using β/μ, L _γ and L _μ is proposed.     

Sea-breeze Front Variations in Space and Time

Summary  This paper is a contribution to experimental meteorology: A sea-breeze front was investigated by aircraft observations and thorough numerical analysis using an unprecedented number of runs crossing the same front within a timespan of . The 33 runs were flown in a situation of offshore geostrophic wind of 5 m/s in 1000 hPa and with the strategy of obtaining information on the four-dimensional field (t=time, x=cross-coastal coordinate, y=coast-parallel coordinate, z=height): 9 runs in x-direction (and reverse) at different heights to yield x,z-cross-sections of the observed meteorological quantities (specific humidity q, potential temperature Θ and the components u, v and w of the wind velocity), assuming a frozen structure in time; the next 7 runs again in x-direction but all at the same level and on the same track to yield x,t-diagrams of the same quantities in order to study the temporal changes compared to those with x and z; the next 10 runs as a zig-zagging flight track crossing the front but drifting in y-direction, all at the same height, in order to obtain the y-dependency; andfinally 7 runs for another x,z-cross-sectional analysis, which can be compared to that evaluated from the runs at the beginning of the mission. The paper describes the 4-dimensional dependencies in detail. Pure x-variations at constant z are expressed by VCM low-pass filtered space series (VCM=variance conserving multiresolution, according to Howell and Mahrt, 1994). The x,z-analyses are similar to those in Kraus et al. (1990) and Finkele et al. (1995) verifying these results. The comparison of the x,z-studies gained from the data at the beginning and at the end of the mission show how the sea-breeze frontal area changes its structure. The fluctuations (in time) revealed by the low-pass filtered x,t-runs (same track and same height) are smaller than the contour intervals chosen in the x,z-cross-sections. This shows, that the single runs, from which the x,z-cross-sections are constructed, reliably and significantly contribute to the interpolated structure. The paper also demonstrates the overall development of the front within the 3^1/2 h of continuous observation. The x,y-fields demonstrate that the y-dependency of the various quantities is generally one order of magnitude smaller than the x-dependency and that the assumption of negligible y-dependency holds in the first order of approximation for a fairly homogeneous coast. Convective disturbances of a horizontal scale of 1 to 4 km at the landward side of the front, embedded in the offshore flow and bouncing against the landward propagating sea-breeze front, considerably contribute to variations of the frontal propagation speed and of the frontal shape and also to changes of the parameters with the along-frontal coordinate y. Received April 24, 1998 Revised November 3, 1998     

Measurement and investigation of chamber radical sources in the European Photoreactor (EUPHORE)

It is essential to quantify the background reactivity of smog-chambers, since this might be the major limitation of experiments carried out at low pollutant concentrations typical of the polluted atmosphere. Detailed investigation of three chamber experiments at zero-NO _x in the European Photoreactor (EUPHORE) were carried out by means of rate-of-production analysis and two uncertainty analysis tools: local uncertainty analysis and Monte Carlo simulations with Latin hypercube sampling. The chemical mechanism employed was that for methane plus the inorganic subset of the Master Chemical Mechanism (MCMv3.1). Newly installed instruments in EUPHORE allowed the measurement of nitrous acid and formaldehyde at sub-ppb concentrations with high sensitivity. The presence of HONO and HCHO during the experiments could be explained only by processes taking place on the FEP Teflon walls. The HONO production rate can be described by the empirical equation W(HONO)_EUPHORE ^dry = a × j _{NO 2}× exp (− T ₀/T) in the low relative humidity region (RH < 2%, a = 7.3×10²¹ cm⁻³, T ₀ = 8945K), and by the equation W(HONO)_EUPHORE ^humid = W(HONO)_EUPHORE ^dry+ j _{NO 2}× b × RH ^q in the higher relative humidity region (2% < RH < 15%, b = 5.8×10⁸ cm⁻³ and q = 0.36, and RH is the relative humidity in percentages). For HCHO the expression W(HCHO)_EUPHORE = c × j _{NO 2}exp (− T′₀/T) is applicable (c = 3.1×10¹⁷ cm⁻³ and T′₀ = 5686 K). In the 0–15% relative humidity range OH production from HONO generated at the wall is about a factor of two higher than that from the photolysis of 100 ppb ozone. Effect of added NO₂ was found to be consistent with the dark HONO formation rate coefficient of MCMv3.1.