Development and Operational Testing of a Super‐Ensemble Artificial Intelligence Flood‐Forecast Model for a Pacific Northwest River

Coastal catchments in British Columbia, Canada, experience a complex mixture of rainfall‐ and snowmelt‐driven contributions to flood events. Few operational flood‐forecast models are available in the region. Here, we integrated a number of proven technologies in a novel way to produce a super‐ensemble forecast system for the Englishman River, a flood‐prone stream on Vancouver Island. This three‐day‐ahead modeling system utilizes up to 42 numerical weather prediction model outputs from the North American Ensemble Forecast System, combined with six artificial neural network‐based streamflow models representing various slightly different system conceptualizations, all of which were trained exclusively on historical high‐flow data. As such, the system combines relatively low model development times and costs with the generation of fully probabilistic forecasts reflecting uncertainty in the simulation of both atmospheric and terrestrial hydrologic dynamics. Results from operational testing by British Columbia's flood forecasting agency during the 2013‐2014 storm season suggest that the prediction system is operationally useful and robust.     

2006~2010年珠三角地区SO2特征分析

对广州番禺大气成分站2006~2010年期间的SO2资料进行了分析,讨论了珠江三角洲(珠三角)地区地面SO2体积分数的年、季节、月、日变化特征和概率的分布特征.珠三角地区地面SO2变化特征的分析结果表明,2010年地面SO2体积分数的总体水平相对近年来有一定下降,高浓度事件发生频率降低;冬、春季SO2各项统计值要高于夏、秋季,干季明显高于湿季,可能与大气边界层高度和太阳辐射等因素的季节性变化相关;SO2干湿季的日变化趋势相仿,日最高峰时间相同,只是湿季达次高峰和最低点的时间比干季要提前1 h,这可能与季节性的大气边界层高度和辐射强度变化,以及日照时间长度有关;SO2体积分数的概率分布特征比较复杂,各月谱型分布各有不同,可能与季节性因素的变化规律相关.     

黄河中上游能源化工区大气污染跨界环境影响分析

对黄河中上游能源化工区近地面和边界层顶气象流场及该区域大气污染长距离输送产生的跨界环境影响趋势特征进行了分析。结果表明,该区域近地面和边界层顶的流场总体上为西北向东南流动,大气污染物长距离输送可能影响的区域主要为华中地区;区域冷空气的活动对其大气污染物的清除起重要作用;通过CALPUFF模型的模拟结果表明,该区域SO2的影响程度和范围明显大于NO2,在区域内部存在污染物浓度较高的区域,但未对区外造成显著跨界环境影响。     

2015年10月南京霾污染过程分析

为探讨南京秋季霾污染过程发生的主要影响因素,利用南京信息工程大学太阳光度计观测霾污染发生天气下AOD（aerosol optical depth,气溶胶光学厚度）数据,计算AE_440-1020（?ngstr?m Exponent,波长指数）以及a₂（光谱曲率）,结合CALIPSO（Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations）卫星气溶胶组分分析以及MODIS（Moderate Resolution Imaging Spectroradiometer）火点数据,对2015年10月南京霾污染过程进行分析.结果表明:2015年10月出现的两次霾污染过程期间南京地区AE_440-1020均高于1.0并且a₂呈负值,其中10月16日AQI达到峰值（201）,AOD₅₀₀达1.51,AE_440-1020达1.37,a₂达-0.77;这两次较为严重的霾污染过程均主要由人为因素（工业污染、城市建设、生物质燃烧、汽车尾气排放等）产生的细粒子所致.后向轨迹分析发现,2015年10月16日南京地区霾污染天气发生的主要原因是区域型污染,同时受长距离输送影响,大量携带人为因素产生的细粒子以及少量沙尘等污染物的空气团途经内蒙古、山东等地到达南京,加剧了当日的污染程度;2015年10月23日南京地区霾污染天气的发生则主要受长距离输送影响,同时也受到区域型污染影响,加剧了当日的污染程度.研究显示,在稳定的气象条件下,较高的相对湿度、较低的地表风速、低混合层高度以及贴地逆温的出现是诱发霾污染天气产生的有利气象条件.      

SACRAMENTO RIVER FLOW RECONSTRUCTED TO A.D. 869 FROM TREE RINGS1

ABSTRACT: A time series of annual flow of the Sacramento River, California, is reconstructed to A.D. 869 from tree rings for a long‐term perspective on hydrologic drought. Reconstructions derived by principal components regression of flow on time‐varying subsets of tree‐ring chronologies account for 64 to 81 percent of the flow variance in the 1906 to 1977 calibration period. A Monte Carlo analysis of reconstructed n‐year running means indicates that the gaged record contains examples of drought extremes for averaging periods of perhaps = 6 to 10 years, but not for longer and shorter averaging periods. For example, the estimated probability approaches 1.0 that the flow in A.D. 1580 was lower than the lowest single‐year gaged flow. The tree‐ring record also suggests that persistently high or low flows over 50‐year periods characterize some parts of the long‐term flow history. The results should contribute to sensible water resources planning for the Sacramento Basin and to the methodology of incorporating tree‐ring data in the assessment of the probability of hydrologic drought.     

黑龙江省影响水稻安全生产的气象要素

在分析水稻安全生产条件的基础上，探讨了有关气象因素及灾害对水稻生长发育和产量的影响。重点分析了地区冷害的发生状况及干湿条件，在充分考虑黑龙江省地区气候特征、农业生产区域及品种熟性的基础上，确定了影响水稻安全生产的灾害和气象指标。利用多年气象资料，计算了黑龙江省各地的冷害发生机率及稻田干燥度指数等，通过指标对比分析，初步提出了黑龙江省水稻安全生产的区域划分，为水稻生产的防灾减灾提供了科学的气象依据。     

重庆近11年大气混合层厚度研究

根据新闻颁国家标准ＧＢ／Ｔ１３２０１－９１的规定，计算了重庆地区近１１年大气混合厚度，分析结果表明，重庆地区大气混合层厚度有明显日变化和季节变化，大气稳定度是混合层厚度的主要决定因子。     

Characterisation of PM10, PM2.5 and Benzene Soluble Organic Fraction of Particulate Matter in an Urban Area of Kolkata, India

In this study, the relationship between inhalable particulate (PM₁₀), fine particulate (PM_2.5), coarse particles (PM_{2.5 – 10}) and meteorological parameters such as temperature, relative humidity, solar radiation, wind speed were statistically analyzed and modelled for urban area of Kolkata during winter months of 2003–2004. Ambient air quality was monitored with a sampling frequency of twenty-four hours at three monitoring sites located near traffic intersections and in an industrial area. The monitoring sites were located 3–5 m above ground near highly trafficked and congested areas. The 24 h average PM₁₀ and PM_2.5 samples were collected using Thermo-Andersen high volume samplers and exposed filter papers were extracted and analysed for benzene soluble organic fraction. The ratios between PM_2.5 and PM₁₀ were found to be in the range of 0.6 to 0.92 and the highest ratio was found in the most polluted urban site. Statistical analysis has shown a strong positive correlation between PM₁₀ and PM_2.5 and inverse correlation was observed between particulate matter (PM₁₀ and PM_2.5) and wind speed. Statistical analysis of air quality data shows that PM₁₀ and PM_2.5 are showing poor correlation with temperature, relative humidity and solar radiation. Regression equations for PM₁₀ and PM_2.5 and meteorological parameters were developed. The organic fraction of particulate matter soluble in benzene is an indication of poly aromatic hydrocarbon (PAH) concentration present in particulate matter. The relationship between the benzene soluble organic fraction (BSOF) of inhalable particulate (PM₁₀) and fine particulate (PM_2.5) were analysed for urban area of Kolkata. Significant positive correlation was observed between benzene soluble organic fraction of PM₁₀ (BSM10) and benzene soluble organic fraction of PM_2.5 (BSM2.5). Regression equations for BSM10 and BSM2.5 were developed.     

Characterization and Identification of the Sources of Chromium, Zinc, Lead, Cadmium, Nickel, Manganese and Iron in Pm10 Particulates at the Two Sites of Kolkata, India

Monitoring of ambient PM₁₀ (particulate matter which passes through a size selective impactor inlet with a 50% efficiency cut-off at 10 μm aerodynamic diameter) has been done at residential (Kasba) and industrial (Cossipore) sites of an urban region of Kolkata during November 2003 to November 2004. These sites were selected depending on the dominant anthropogenic activities. Metal constituents of atmospheric PM₁₀ deposited on glass fibre filter paper were estimated using Inductively Coupled Plasma Atomic Emission Spectrometer (ICP-AES). Chromium (Cr), zinc (Zn), lead (Pb), cadmium (Cd), nickel (Ni), manganese (Mn) and iron (Fe) are the seven toxic trace metals quantified from the measured PM₁₀ concentrations. The 24 h average concentrations of Cr, Zn, Pb, Cd, Ni, Mn and Fe from ninety PM₁₀ particulate samples of Kolkata were found to be 6.9, 506.1, 79.1, 3.3, 7.4, 2.4 and 103.6 ng/m³, respectively. The 24 h average PM₁₀ concentration exceeded national ambient air quality standard (NAAQS) as specified by central pollution control board, India at both residential (Kasba) and industrial (Cossipore) areas with mean concentration of 140.1 and 196.6 μg/m³, respectively. A simultaneous meteorology study was performed to assess the influence of air masses by wind speed, wind direction, rainfall, relative humidity and temperature. The measured toxic trace metals generally showed inverse relationship with wind speed, relative humidity and temperature. Factor analysis, a receptor modeling technique has been used for identification of the possible sources contributing to the PM₁₀. Varimax rotated factor analysis identified four possible sources of measured trace metals comprising solid waste dumping, vehicular traffic with the influence of road dust, road dust and soil dust at residential site (Kasba), while vehicular traffic with the influence of soil dust, road dust, galvanizing and electroplating industry, and tanning industry at industrial site (Cossipore).     

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.