Microclimate, freezing tolerance, and cold acclimation along an elevation gradient for seedlings of the Great Basin Desert shrub, Artemisia tridentata

Vegetation, microclimate, seedling frequency, freezing tolerance, and cold acclimation were compared for seedlings of Artemisia tridentata collected from 1775, 2175, and 2575 m elevation in the eastern Sierra Nevada, California. Data were used to test the hypothesis that ecotypic differences in stress physiology are important for seedling survival along gradients from desert to montane ecosystems. The vegetation canopy cover and A. tridentata seedling frequency were greatest at 2575 m, compared to 1775 and 2175 m. Snow cover ameliorated temperatures near the soil surface for part of the winter and depth varied across elevations. Freezing tolerance was compared for seedlings maintained in growth chambers at day/night air temperatures of 25°C/15°C. The temperature at which electrolyte leakage and Photosystem II function (F_V/F_M) from leaves were half-maximum was approximately −13·5°C for leaves of seedlings from all three elevations. Shifting day/night air temperatures from 25°C/15°C to 15°C/5°C initiated about 1·5° of acclimation by plants from all three altitudes, with seedlings from the highest elevation exhibiting the greatest acclimation change. Measurements of ambient air and canopy temperatures at the three elevations indicated that wintertime average low temperatures were consistent with the measured degree of freezing tolerance. At small spatial scales used in this study, pollen and seed dispersal between study sites may have precluded resolution of ecotypic differences. Patterns of freezing tolerance and cold acclimation may depend on a combination of mesoclimate and microclimate temperatures, canopy cover, snow depth, and snow melt patterns.     

Methodology for construction, calibration and validation of a national hydrological model for Denmark

An integrated groundwater/surface water hydrological model with a 1 km² grid has been constructed for Denmark covering 43,000 km². The model is composed of a relatively simple root zone component for estimating the net precipitation, a comprehensive three-dimensional groundwater component for estimating recharge to and hydraulic heads in different geological layers, and a river component for streamflow routing and calculating stream–aquifer interaction. The model was constructed on the basis of the MIKE SHE code and by utilising comprehensive national databases on geology, soil, topography, river systems, climate and hydrology. The present paper describes the modelling process for the 7330 km² island of Sjælland with emphasis on the problems experienced in combining the classical paradigms of groundwater modelling, such as inverse modelling of steady-state conditions, and catchment modelling, focussing on dynamic conditions and discharge simulation. Three model versions with different assumptions on input data and parameter values were required until the performance of the final, according to pre-defined accuracy criteria, model was evaluated as being satisfactory. The paper highlights the methodological issues related to establishment of performance criteria, parameterisation and assessment of parameter values from field data, calibration and validation test schemes. Most of the parameter values were assessed directly from field data, while about 10 ‘free’ parameters were subject to calibration using a combination of inverse steady-state groundwater modelling and manual trial-and-error dynamic groundwater/surface water modelling. Emphasising the importance of tests against independent data, the validation schemes included combinations of split-sample tests (another period) and proxy-basin tests (another area).     

Scaling effects on modeled surface energy-balance components using the NOAH-OSU land surface model

As surface exchange processes are highly non-linear and heterogeneous in space and time, it is important to know the appropriate scale for the reasonable prediction of these exchange processes. For example, the explicit representation of surface variability has been vital in predicting mesoscale weather events such as late-afternoon thunderstorms initiated by latent heat exchanges in mid-latitude regions of the continental United States. This study was undertaken to examine the effects of different spatial scales of input data on modeled fluxes, so as to better understand the resolution needed for accurate modeling. A statistical procedure was followed to select two cells from the Southern Great Plains 1997 hydrology experiment region, each 20 km×20 km, representing the most homogeneous and the most heterogeneous surface conditions (based on soil and vegetation) within the study region. The NOAH-OSU (Oregon State University) Land Surface Model (LSM) was employed to estimate surface energy fluxes. Three scales of study (200 m, 2 and 20 km) were considered in order to investigate the impacts of the aggregation of input data, especially soil and vegetation inputs, on the model output. Model results of net radiation and latent, sensible and ground heat fluxes were compared for the three scales. For the heterogeneous area, the model output at the 20-km resolution showed some differences when compared with the 200-m and 2-km resolutions. This was more pronounced in latent heat (12% decrease), sensible heat (22% increase), and ground heat flux (44% increase) estimation than in net radiation. The scaling effects were much less for the relatively homogeneous land area with 5% increase in sensible heat and 4% decrease in ground heat flux estimation. All of the model outputs for the 2- and 20-km resolutions were in close agreement. The results suggested that, for this study region, soils and vegetation input resolution of about 2 km should be chosen for realistic modeling of surface exchange processes. This resolution was sufficient to capture the effects of sub-grid scale heterogeneity, while avoiding the data and computational difficulties associated with higher spatial resolutions.     

An experimental investigation of LNAPL migration in an unsaturated/saturated sand

Accidental spills of hydrocarbons, such as Light Non-Aqueous Phase Liquids (LNAPLs), are one of the most common sources of subsurface contamination. Migration of LNAPL in a porous medium is influenced by various factors such as the number of fluids present in the unsaturated/saturated zones and the proportion of pores occupied by each fluid. The results for relationship between matric suction and degree of saturation are presented in this paper for water–air, water–LNAPL and LNAPL–air systems in a sand. A simple and reliable setup using Buchner funnel was designed to obtain these relations. It was found that the relationship between matric suction head and degree of saturation is hysteretic for all the fluid systems (water–air, water–LNAPL and LNAPL–air). Furthermore, the amount of hysteresis depended upon the fluid system, with the maximum hysteresis occurring for water–air system. The results suggest that the amount of trapped air depends upon the reversal degree of saturation from drying to wetting.     

北京地区大气能见度变化规律及影响因子统计分析

1990～ 2 0 0 0年北京地区大气能见度的统计分析表明 ,大气能见度有明显的年际变化、季节变化和日变化特征。冬、春、秋三季及全年日平均年际变化表现为 2 0世纪 90年代中期能见度较好 ,前期和末期能见度较差 ,2 0 0 0年能见度迅速好转 ;夏季能见度年际变化在 1997年以前与其他季节相反 ,1995年能见度最差。大气能见度与同期地面气象条件和主要污染物浓度的相关性比较表明 ,春、夏、秋三季以空气湿度、PM10 和风速为主要影响因子 ,冬季以PM10 、SO2 、空气湿度和风速为主要影响因子。能见度与相对湿度和空气污染物浓度呈反相关 ,与风速的相关性较为复杂 (有时呈正相关 ,有时呈反相关 ) ;高湿度 (相对湿度 f≥ 80 % )、小风速 (地面风速u≤ 2m·s-1)和雾是造成低能见度的主要气象条件 ;污染物浓度对能见度的影响以冬季最为明显 ,秋季次之 ,夏季最差     

北京地区一次典型大雾天气的空气污染过程物理量分布特征

2002年11月30至12月4日，北京持续4天大雾天气，空气污染物在持续的稳定层结条件下，空气质量连续3天达5级以上。文中分析了大雾天气各主要污染物的变化特征，以及此次过程中天气形势的特点及演变，并对造成大雾日空气污染天气的物理量分布特征进行分析。结果表明：高空WNW气流、稳定性持续增加、逆温层结持续存在、低空风速较小、相对湿度大，导致局地污染物不能及时随大气扩散；1000～700hPa有弱的上升气流形成和维持，与500hPa高空下沉气流之间在低空的某层高度上形成稳定层结(逆温层)，导致大雾及重污染的形成；850hPa为暖区，850～500hPa为冷平流，有利于大雾的形成和加重。     

广东省空气质量预报系统

文章介绍了广东省气象系统开展空气质量预报的概况，包括使用的预报工具，其预报能力与业务运行的预报质量分析，以及进一步提高预报水平的一些设想。     

一种新的城市SO2污染统计预报方法及其应用

针对目前采用的统计方法存在的不足, 即在选择预报因子时没有考虑预报因子之间的相关性, 挑选的预报因子由于非正交, 使回归计算的结果不稳定, 给计算带来一定的误差。该文提出把一元线性回归分析、自然正交函数 (EOF) 和逐步回归方法结合起来, 从而得到一种新的建立统计预报模型的方法。以西安市采暖期和夏季SO₂日均浓度为预报对象, 使用该方法建立预报模型。拟合及预报试验表明, 这些预报模型不但可以很好地拟合变化趋势, 而且还能作出较准确的预报, 采暖期预报的级别命中率为72.5 %, 夏季级别预报命中率为100%。通过对比试验, 此方法优于目前常用的逐步回归方法, 具有很好的应用前景。     

海南岛中低纬冷暖系统相互作用下的非台暴雨分析

通过对1993年～2002年共10年的天气资料分析发现,在海南,中纬度的冷空气与低纬度在南海上活动的低压之间的相互作用,是秋季产生非台暴雨的非常重要的环流形势;同时发现,低空急流的存在与暴雨的产生有密切联系。并且对2000年10月13日～15日的暴雨过程利用T106物理量场诊断分析,说明暴雨形成的原因。     

冬春季格陵兰海冰变化与初夏中国气温/降水关系的初步分析

采用英国Hadley中心GISST海冰面积资料，NCEP／NCAR再分析资料以及中国地面降水和气温资料，运用EOF分解，小波分析和合成分析等方法，初步探讨了格陵兰岛两侧附近冬春季海冰面积变化特征及其与初夏6月中国气温和降水的关系，结果表明，格陵兰岛东西两侧海冰面积呈显著反相变化，并且具有明显的年际和年代际周期性振荡，冬春季格陵兰－寻威海海冰与初夏6月中国长江以北气温（降水）正相关（反相关），与长江以南气温（降水）反相关（正相关），而对于戴维斯海峡－拉布拉多海海冰则具有相反的相关型，大尺度500hPa环流合成分析初步表明，冬春季格陵兰附近海冰面积变化伴随着北极极涡环流和北半球阻塞高压的持续异常，海冰变化可能是影响初夏中国气温和降水的因子之一。