天津臭氧浓度与气象因素的相关性及其预测方法

气象因素在影响夏季臭氧浓度水平和变化特征方面扮演着重要作用.通过对2008年夏季天津地面臭氧体积浓度和气象因素的相关分析,揭示高浓度臭氧发生时的典型气象特征,并初步建立了预测地面臭氧浓度的气象学方法.结果表明:影响臭氧浓度的主要气象因素是气温、相对湿度和风速、风向,当14时气温大于30℃,相对湿度低于60%,风向为偏西或偏南时,高浓度臭氧的发生概率较高.采用14时气温、相对湿度和风速等气象参数拟合臭氧体积浓度,效果良好.     

天津城区大气气溶胶质量浓度分布特征与影响因素

根据中国气象局天津大气边界层观测站2009年的气溶胶观测资料和同期气象资料,对天津城区PM10和PM2.5质量浓度变化特征,及其与气象条件的相互关系进行研究,结果表明：PM10和PM2.5年均质量浓度为153.24和68.78μg·m-3,其日均值超标率近半,表明南部城区尤其是交通干道附近气溶胶污染较为严重;PM10和PM2.5质量浓度逐月变化呈现明显的冬季高、夏季低的特征,其日变化特征呈明显的双峰型,早晚污染高峰主要受交通源影响;气象条件对气溶胶质量浓度作用显著,气溶胶质量浓度与气温正相关,相对湿度的增高易导致细粒子吸湿性增长,但高湿状态下易引起降水有利于气溶胶的湿清除,西南气流和偏北风是PM10和PM2.5高浓度的主要影响风向,静小风易造成气溶胶堆积,高风速可引起PM10排放增多,但对PM2.5影响不大。     

冬季降雪过程对城市大气气态汞污染的影响

2009年降雪和非降雪期间对北京西北城区的气态总汞浓度进行了连续采样,比较了降雪期间、非降雪期间的气态总汞浓度日变化过程;降雪期间气态总汞浓度的降低和恢复过程。结果表明,降雪和非降雪期间大气气态总汞浓度的日均值有显著差异,降雪期间气态总汞的平均浓度为5．64ng·m^-3,非降雪期间的平均浓度为7．43ng·m^-3,前者约为后者的70％。降雪后约7h气态总汞浓度恢复到降雪前水平。研究中分析了气象因素（气压、风速、阵风速度、气温和相对湿度）对于气态总汞浓度的影响,结果表明：降雪期间主要受到风速（r=-0．527）和阵风速度（r=-0．574）的影响;非降雪期间主要受到风速（r=-0．691）,阵风速度（r=-0．726）和相对湿度（r=0．692）的影响,并且相对湿度的影响与风速的影响相近。降雪和非降雪期间气态总汞的日变化有所差异：非降雪期间气态总汞浓度在午夜和清晨较高,日变化趋势与相对湿度一致;降雪期间气态总汞的日变化没有明显规律。     

Intercomparison of Two Models,ETA and RAMS,with TRACT Field Campaign Data

In this work a model intercomparison between RAMS and ETA models is carried out, with the aim of evaluating the quality and accuracy of these mesoscale models in reproducing the time evolution of the meteorology in real complex terrain. This is of great importance not only for meteorological forecast but also for air quality assessment. Numerical simulations are performed to reproduce the mean variables' fields and to compare them with measurements collected during the field campaign TRACT. The domain covers the Rhine valley and surrounding mountainous region and we consider a time period of two days. Results from simulations are compared to observations relative to ground stations and radiosoundings. A qualitative analysis is joined to a quantitative estimation of some reference statistical indexes. Both RAMS and ETA models performances are satisfactory when compared to the measured data and also their relative agreement is good. The mean variable fields are reproduced with a satisfactory degree of reliability, even if the simulated profiles are not able to describe the largest fluctuations of the variables. At the surface stations, the best agreement between predictions and observations is obtained for the wind velocity, while the quality of the results is lower for temperature and humidity.     

A comparative study of prognostic MM5 meteorological modeling with aircraft, wind profiler, lidar, tethered balloon and RASS data over Philadelphia during a 1999 summer episode

This study presents a comparative evaluation of the prognostic meteorological Fifth Generation NCAR Pennsylvania State University Mesoscale Model (MM5) using data from the Northeast Oxidant and Particle Study (NE-OPS) research program collected over Philadelphia, PA during a summer episode in 1999. A set of model simulations utilizing a nested grid of 36 km, 12 km and 4 km horizontal resolutions with 21 layers in the vertical direction was performed for a period of 101 h from July 15, 1999; 12 UTC to July 19, 1999; 17 UTC. The model predictions obtained with 4 km horizontal grid resolution were compared with the NE-OPS observations. Comparisons of model temperature with aircraft data revealed that the model exhibited slight underestimation as noted by previous investigators. Comparisons of model temperature with aircraft and tethered balloon data indicate that the mean absolute error varied up to 1.5 °C. The comparisons of model relative humidity with aircraft and tethered balloon indicate that the mean relative error varied from –11% to –22% for the tethered balloon and from –5% to –30% for the aircraft data. The mean relative error for water vapor mixing ratio with respect to the lidar data exhibited a negative bias consistent with the humidity bias corresponding to aircraft and tethered balloon data. The tendency of MM5 to produce estimates of very low wind speeds, especially in the early-mid afternoon hours, as noted by earlier investigators, is seen in this study also. It is indeed true that the initial fields as well as the fields utilized in the data assimilation also contribute to some of the differences between the model and observations. Studies such as these which compare the grid averaged mean state variables with observations have inherent difficulties. Despite the above limitations, the results of the present study broadly conform to the general traits of MM5 as noted by earlier investigators.     

广州市空气污染物和气象要素的主成分与典型相关分析

用主成分和典型相关分析方法分析广州市近4a(2001—2004年)的空气污染物与气象要素之间的关系,按夏半年、冬半年和全年3个时间尺度分别进行。结果表明:污染物数据所得到的主成分分别代表机动车污染源(汽油燃烧和扬尘)和工业污染源(工业燃煤和燃油),气象数据的主成分分析表明空气的温度、湿度及对流速度对空气污染作用明显,而污染物和气象要素的主成分分析表明气温高低和空气干湿程度对大气污染的影响较大。污染物与气象要素两组数据之间的典型相关分析表明污染物与气象要素之间存在显著的相关关系,其中温度和风速对气态污染物有显著影响。     

气候因子对靖远松叶蜂暴发的影响

运用SAS8.2中的主成份分析法分析了1988~1997年的气象数据,研究了温度、湿度、降雨量与靖远松叶蜂发生的关系,用实验数据对统计分析结果进行了解释,并运用典型判别分析建立了非时滞和时滞预报模型,进一步研究各种气候因子的综合作用.结果表明,10月份较高的气温与较高的湿度有利于靖远松叶蜂大量结茧,为来年的暴发提供虫源;靖远松叶蜂小幼虫的死亡率与温度呈显著线性正相关(r=0.4,P=0.036),与相对湿度呈弱的线性负相关(r=-0.25,P=0.147),即7月较高的温度与较低的湿度有利于靖远松叶蜂的暴发.1991年靖远松叶蜂开始小规模暴发与1990年初霜期异常推迟有关,8月份过多或过少的降雨可能会妨碍靖远松叶蜂病毒的流行,从而有利于靖远松叶蜂大规模暴发.非时滞预报模型回代正判率为81.8%,时滞预报模型回代正判率为72.7%.典型判别函数表明,温度因子是决定靖远松叶蜂暴发的最主要气象因子.图3表4参9     

Examination of model predictions at different horizontal grid resolutions

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs and data requirements increase significantly with increasing grid resolution. Therefore, it is important to examine, for any given application, whether the expected benefit of increased grid resolution justifies the extra costs. In this study, we examine temperature and ozone observations and model predictions for three high ozone episodes that occurred over the northeastern United States during the summer of 1995. In the first set of simulations, the meteorological model RAMS4a was run with three two-way nested grids of 108/36/12 km grid spacing covering the United States and the photochemical model UAM-V was run with two grids of 36/12 km grid spacing covering the eastern United States. In the second set of simulations, RAMS4a was run with four two-way nested grids of 108/36/12/4 km grid spacing and UAM-V was run with three grids of 36/12/4 km grid spacing with the finest resolution covering the northeastern United States. Our analysis focuses on the comparison of model predictions for the finest grid domain of the simulations, namely, the region overlapping the 12 km and 4 km domains. A comparison of 12 km versus 4 km fields shows that the increased grid resolution leads to finer texture in the model predictions; however, comparisons of model predictions with observations do not reveal the expected improvement in the predictions. While high-resolution modeling has scientific merit and potential uses, the currently available monitoring networks, in conjunction with the scarceness of highly resolved spatial input data and the limitations of model formulation, do not allow confirmation of the expected superiority of the high-resolution model predictions.The U.S. Governments right to retain a non-exclusive royalty-free licence in and to any copyright is acknowledged.     

Sensitivity of atmospheric dispersion simulations by HYSPLIT to the meteorological predictions from a meso-scale model

Mesoscale transport and dispersion of air pollutants from a few major point sources in the Mississippi Gulf coastal region is calculated using a coupled modeling system consisting of the atmospheric dynamical model WRF and the lagrangian particle model HYSPLIT. The sensitivity of the dispersion model results to the meteorological fields is studied by conducting an ensemble of simulations using the WRF model for the same dispersion case. Several parameterization schemes for the physical processes of boundary layer turbulence and land surface temperature/moisture prediction in WRF are used in various combinations to produce different meteorological members which are then used for dispersion simulation. The uncertainty in the simulated concentration probabilities to the meteorological model configurations and the ensemble mean are presented. The parameters used for determining the uncertainties include the wind fields, temperature, area of concentration and the levels of concentration. The results indicate that dispersion model results are influenced by the choices made in respect of the planetary boundary layer and land surface schemes in the mesoscale model to produce the meteorological forecast thereby leading to certain amount of uncertainty in the resultant concentrations. Results show that the specific choices made about the atmospheric model configuration can significantly after the simulated concentrations.     

Numerical Investigation of Boundary-Layer Evolution and Nocturnal Low-Level Jets: Local versus Non-Local PBL Schemes

Numerical simulations of the evolution of the planetary boundary layer (PBL) and nocturnal low-level jets (LLJ) have been carried out using MM5 (version 3.3) with four-dimensional data assimilation (FDDA) for a high pollution episode in the northeastern United States during July 15–20, 1999. In this paper, we assess the impact of different parameterizations on the PBL evolution with two schemes: the Blackadar PBL, a hybrid local (stable regime) and non-local (convective regime) mixing scheme; and the Gayno–Seaman PBL, a turbulent kinetic energy (TKE)-based eddy diffusion scheme. No FDDA was applied within the PBL to evaluate the ability of the two schemes to reproduce the PBL structure and its temporal variation. The restriction of the application of FDDA to the atmosphere above the PBL or the lowest 8 model levels, whichever is higher, has significantly improved the predicted strength and timing of the LLJ during the night. A systematic analysis of the PBL evolution has been performed for the primary meteorological fields (temperature, specific humidity, horizontal winds) and for the derived parameters such as the PBL height, virtual potential temperature, relative humidity, and cloud cover fraction. There are substantial differences between the PBL structures and evolutions simulated by these two different schemes. The model results were compared with independent observations (that were not used in FDDA) measured by aircraft, RASS and wind profiler, lidar, and tethered balloon platforms during the summer of 1999 as part of the NorthEast Oxidant and Particle Study (NE-OPS). The observations tend to support the non-local mixing mechanism better than the layer-to-layer eddy diffusion in the convective PBL.     

北京市秋季大气颗粒物的污染特征研究

大气颗粒物是造成城市空气污染的重要原因之一,并已经成为我国北京等大中城市空气污染中的首要污染。为了分析北京市大气细颗粒物的污染水平及其影响因素,以大气中的PM10和PM2.5为研究对象,于2005年秋季在北京市设立了9个采样点进行采样监测,通过对所采集到的PM10和PM2.5质量浓度的对比来分析大气颗粒物的空间分布和时间变化特征,并建立起PM10和PM2.5质量浓度与风力、温度、湿度等气象条件的对应关系来分析各种气象因素对大气细颗粒物污染水平的影响。结果表明:北京市不同区域的PM10和PM2.5的质量浓度差异较大,同时,值得注意的是通过对同一地点同一采样时间大气颗粒物质量浓度的对比发现PM2.5质量浓度的空间分布并不完全同于PM10,这主要是与采样点所处的环境中不同污染源影响的强弱有关;气象条件稳定时,PM10和PM2.5质量浓度的日变化表现出一定的规律性,这种时间变化的特征主要取决于所在环境中排放的污染物变化情况;气象条件是影响PM10和PM2.5污染程度的重要因素,在一定的范围内,颗粒物质量浓度随着温度的上升而下降,随着相对湿度的升高而增大,随着风力的增强而减小。     

Performance analysis of WRF and LES in describing the evolution and structure of the planetary boundary layer

We implemented the Weather Research and Forecast (WRF) model and WRF Large-Eddy Simulation (WRF–LES), focusing on calculations for the planetary boundary layer (PBL), and compared the results against a data set of a well-documented campaign, in the Houston–Galveston area, Texas, in summer 2006. A methodology using WRF in a mesoscale and LES was implemented to assess the performance of the model in simulating the evolution and structure of the PBL over Houston during the Vertical Mixing Experiment. Also, the WRF model in a real case mode was examined to explore potential differences between the results of each simulation approach. We analyzed both WRF results for key meteorological parameters like wind speed, wind direction and potential temperature, and compared the model results against the observations. The reasonably good agreement of LES results forced with observed surface fluxes provides confidence that LES describes turbulence quantities such as turbulent kinetic energy correctly and warrants further turbulence structure analysis. The LES results indicate a weak but noticeable nighttime turbulent kinetic energy which was produced by wind shear in Houston’s planetary boundary layer and which may likely be related to intermittent turbulence. This is supported by observations made at the University of Houston Moody Tower air quality station when intermittent peaks of carbon monoxide occurred in the evening, although the variability in wind conditions was very little.     

黄土高原陆地表层最大可能蒸散量的变化特征

基于黄土高原1961—2008年月平均气温、最高气温、最低气温、相对湿度、降水量、风速和日照百分率等气候要素资料,应用修订的Penman-Monteith（P-M）模型计算了最大可能蒸散量,分析其时空分布、异常分布特征和次区域时间演变特征。结果表明：1961—2008年间,黄土高原最大可能蒸散量多年平均在400~800 mm之间,大部分区域650~750 mm之间。一致性异常分布是黄土高原最大可能蒸散量的最主要空间模态。黄土高原最大可能蒸散量的异常空间分布可分为以下3个关键区：高原西北部区、高原东北部区和高原东南部区。高原西北部区域最大可能蒸散量呈显著增加趋势,且发生了突变现象;高原东北部区域最大可能蒸散量呈显著下降的趋势,也发生了突变;而高原东南部区域下降趋势不显著,未发生突变。黄土高原最大可能蒸散量的3个空间分区中,3 a的周期振荡表现得比较显著。     

天气条件对福州近地层臭氧分布的影响

利用2009—2010年福州市近地层臭氧连续观测资料,并结合气象资料分析不同天气型对臭氧浓度变化的影响,以及臭氧浓度与气象要素的相关性。结果表明：在高压后部、地面倒槽等6种天气型影响下,福州市臭氧浓度值较高;在低涡锋面、台风（热带辐合带）等4种天气型影响下,臭氧浓度值较低。导致福州市臭氧平均浓度值最高的天气型是台风（热带辐合带）外围,最低的是低涡锋面系统。高压后部、地面倒槽和锋前暖区等强暖性、且非常不利于污染物扩散的天气型易造成臭氧浓度超标。臭氧浓度与气象要素关系密切,与温度、日照、太阳辐射显著正相关,与云量、相对湿度、降水量显著负相关,受偏南和偏东风影响,平均风速较大时,臭氧浓度较高,在SSE方位上臭氧小时浓度超标率最高。     

The performance of RAMS in representing the convective boundary layer structure in a very steep valley

Data from a comprehensive field study in the Riviera Valley of Southern Switzerland are used to investigate convective boundary layer structure in a steep valley and to evaluate wind and temperature fields, convective boundary layer height, and surface sensible heat fluxes as predicted by the mesoscale model RAMS. Current parameterizations of surface and boundary layer processes in RAMS, as well as in other mesoscale models, are based on scaling laws strictly valid only for flat topography and uniform land cover. Model evaluation is required to investigate whether this limits the applicability of RAMS in steep, inhomogeneous terrain. One clear-sky day with light synoptic winds is selected from the field study. Observed temperature structure across and along the valley is nearly homogeneous while wind structure is complex with a wind speed maximum on one side of the valley. Upvalley flows are not purely thermally driven and mechanical effects near the valley entrance also affect the wind structure. RAMS captured many of the observed boundary layer characteristics within the steep valley. The wind field, temperature structure, and convective boundary layer height in the valley are qualitatively simulated by RAMS, but the horizontal temperature structure across and along the valley is less homogeneous in the model than in the observations. The model reproduced the observed net radiation, except around sunset and sunrise when RAMS does not take into account the shadows cast by the surrounding topography. The observed sensible heat fluxes fall within the range of simulated values at grid points surrounding the measurement sites. Some of the scatter between observed and simulated turbulent sensible heat fluxes are due to sub-grid scale effects related to local topography.     

2019年秋季三亚市一次典型臭氧污染个例气象成因解析

三亚市位于海南岛最南端,旅游资源丰富,生态环境良好,是海南建设国际旅游岛和国家生态文明试验区的重要城市之一.2019年秋季三亚市出现的一次臭氧(Ozone,O3)污染过程,为科学认识三亚市此次O3污染特征及气象学成因,也为进一步开展O3污染预警预报和科学治理提供技术支撑,利用2019年11月1—6日三亚市生态环境局对外...     

河西走廊极端干旱区PM10质量浓度分布特征及其与气象要素关系研究

利用敦煌和酒泉2007—2011年的PM10质量浓度资料和风速、气温、相对湿度、气压、天气现象等相关气象要素资料,分析了河西走廊西部极端干旱区不同下垫面环境PM。0质量浓度的时空分布特征,结果表明,下垫面是沙地环境的敦煌PMl0质量浓度年平均值为128．9lμg·m-1,明显高于绿洲环境酒泉的76．1mg·m-1两站均是春季大于其他季节,尤以4月最为显著,敦煌和酒泉分别达到272．1lμg·m0和151lμg·m-2;PMl0质量浓度的不同分布特征与气象因素有密切的关系,尤其受沙尘天气的影响较大,其最大值可以反映沙尘天气的强度,非沙尘日PMl0质量浓度在不同下垫面条件下虽有一定相差,但空气质量状况均在“良”以上。两站PM10质量浓度日变化差异较大,敦煌四季的日变化特征均不特别显著,变化比较平稳,基本都呈单峰单谷型分布,最大值出现在17：00时左右,最小值出现在6：00左右;酒泉春、秋季日变化基本一致,呈单峰型,最大值出现在正午时段;夏季日变化规律性不明显,变化幅度比较平缓;冬季呈双峰双谷型,最大值和次大值分别出现在16：00和2：00左右,最小值和次小值分别出现在10：00和0：00左右。进一步分析发现,在沙尘日和非沙尘日PM10质量浓度明显不同,其对应的压、温、湿、风及能见度也有一定规律,沙尘日的日均风速和日最大风速大于非沙尘日,相对湿度、气压和能见度小于非沙尘日。两站的气温、气压、相对湿度、风速等气象要素与PM10质量浓度均有一定相关性,但PM10质量浓度的分布最终是受各要素综合影响的结果,敦煌和酒泉,PM值与PM10质量浓度日均值的相关性都很显著,相关系数分别为0．8961和0．9152,远高于其他各单气象要素与PM10质量浓度的相关性。两站沙尘日的昂M均值分别是非沙尘日2-3倍,因此气象影响指数能有效的区别沙尘日和非沙尘日。IPM的分布也能较好的反映PMl0质量浓度的分布,因此可用抽d来量化评价PM10质量浓度。     

雅砻江流域生长季植被时空变化特征及对气象因子的响应分析

在全球气候变化背景下,开展植被变化对气象因子的响应研究对流域生态环境保护和水土资源合理利用具有重要的现实意义。以雅砻江流域为研究区,基于1982—2015年GIMMS NDVI数据,首先采用多种数理统计方法揭示生长季NDVI的时空变化特征,基于滞后相关系数法分析NDVI对气象因子的时滞效应,在此基础上建立各像元NDVI与气象因子的主成分回归方程,分析影响NDVI变化的主要气象因子及其贡献率,进而揭示NDVI对各气象因子的响应变化特征。结果表明:雅砻江流域NDVI在年内呈单峰型变化,峰值出现在8月,生长季NDVI年际变化呈不显著下降趋势。流域NDVI自下游向上游逐渐减小,植被退化面积占30%,改善面积占24.28%,中游植被改善和退化面积占比最大,就各植被类型变化而言,针叶林改善比重相对较大,灌丛和草甸退化较为严重。导致流域植被变化的主控气象因子为降水和气温,其对植被变化的贡献率分别为27.68%和26.31%,其中,流域上游及中游北部地区植被变化主要受气象因素影响,中游南部及下游地区植被受气象因子与其他因子(如人类活动)的共同影响。各像元NDVI变化的主控气象因子存在显著差异,降水、平均气温和相对湿度是中上游植被变化的主控气象因子,而降水和日照时数是下游植被变化的主控气象因子。流域植被对各气象因子的响应存在一定的时滞效应,植被对各气象因子滞后响应面积大小顺序为:平均风速>降水>日照时数>平均气温>相对湿度。中上游植被对主控气象因子降水、平均气温和相对湿度的响应主要为当月及滞后1个月;下游植被对主控气象因子降水的响应主要为滞后1个月和滞后3个月,而对主控气象因子日照时数的响应主要为当月。     

成都市大气颗粒污染物与气象要素的关系

通过对2004年成都市API指数及API>100日数百分数的再分析,探讨了大气颗粒物污染季节分布、区域分布状况与气象要素的相互关系,并尝试用因子分析法研究了污染物浓度年际变化与气象因子的关系。研究表明,大气污染的季节分布为冬季>春季>秋季>夏季;API>100时数百分数的季节变化状况为春季>冬季>秋季>夏季,区域分布为城西北>城东>城北>城中心>城东南>城西>城南。城市发展对风向的改变比较明显,对风速的改变不明显。大气颗粒污染物年际变化与气象因子的相关性研究表明,PM10浓度与SO2、NOX、湿度、气压呈正相关,与风速、蒸发量、温度呈负相关关系。     

Improving simulations of sulfate aerosols during winter haze over Northern China: the impacts of heterogeneous oxidation by NO2

Incorporating the missing heterogeneous oxidation of S(IV) by NO₂ into the WRF-Chem model. Sulfate production is not sensitive to increase in SO₂ emission. The newly added reaction reproduces sulfate concentrations well during winter haze. We implemented the online coupled WRF-Chem model to reproduce the 2013 January haze event in North China, and evaluated simulated meteorological and chemical fields using multiple observations. The comparisons suggest that temperature and relative humidity (RH) were simulated well (mean biases are -0.2K and 2.7%, respectively), but wind speeds were overestimated (mean bias is 0.5 m?s⁻¹). At the Beijing station, sulfur dioxide (SO₂) concentrations were overpredicted and sulfate concentrations were largely underpredicted, which may result from uncertainties in SO₂ emissions and missing heterogeneous oxidation in current model. We conducted three parallel experiments to examine the impacts of doubling SO₂ emissions and incorporating heterogeneous oxidation of dissolved SO₂ by nitrogen dioxide (NO₂) on sulfate formation during winter haze. The results suggest that doubling SO₂ emissions do not significantly affect sulfate concentrations, but adding heterogeneous oxidation of dissolved SO₂ by NO₂ substantially improve simulations of sulfate and other inorganic aerosols. Although the enhanced SO₂ to sulfate conversion in the HetS (heterogeneous oxidation by NO₂) case reduces SO₂ concentrations, it is still largely overestimated by the model, indicating the overestimations of SO₂ concentrations in the North China Plain (NCP) are mostly due to errors in SO₂ emission inventory.