长江中下游气候的长期变化及基本态特征

研究了1885年以来，我国长江中下游四季及年降水量，四季及年平均气温的长期变化，指出长江中下游四个季及年的总降水量（平均气温）都是正的趋势，但有季节的差异，春季是升温同时增雨最显著的季节，还研究了我国长江中下游降水与气温的气候基本态及气候变率的特征及时间演变规律，指出，60年代以后夏季气温变化的异常程度几乎比以前大了一倍，在冬季，近期在暖背景下的冬季气温变率变小的特征表明长江中下游可能出现持续发暖冬特征，还指出，80年代后我国的长江中下游存季降水处于高基本态与高气候变率时段，应注意频繁发生的夏季洪涝灾害，研究还指出，长江中下游夏季降水与印度季风的气候基本态反相关密切，印度季风及东亚夏季风与长江中下游夏季气温变化在各种尺度上有明显的正相关。     

北半球100 hPa等压面经向风与臭氧总量年变化

本文用多年平均的北半球100hPa经向风和臭氧总量资料分析了两者的关系,结果发现:臭氧总量的变化与100 hPa经向风密切相关,与100 hPa面上北风相对应的是臭氧高值区,与南风对应的是低值区,前者支配后者.充分说明了臭氧总量变化主要受低层平流层环流影响.     

基于CC2530的智能温度传感器节点设计

采用TI公司生产的ZigBee芯片CC2530作为主控芯片和通讯芯片,将铂电阻PT100作为温度传感器,在TI公司的Z-Stack协议栈的基础上进行采集、传输和管理等软件运行程序的编写,实现了对温度要素的采集和无线传输。硬件电路的设计和软件程序的编写充分考虑了低功耗、高可靠性的设计。整个温度传感器采用锂电池进行供电,使用太阳能电池板给锂电池进行充电,可独立在户外环境下长时间稳定运行。     

重庆城区近百余年旱涝变化

用Z指数作为旱涝等级标准,利用重庆城区百余年降水量资料,分析了历年及四季旱涝出现的频率,采用趋势分析、最大熵谱分析以及小波分析方法,研究了重庆城区年及四季旱涝的变化特征。结果表明:重庆城区年及四季干旱和洪涝发生频率均在25%以上,重庆旱涝灾害较频繁;多项式拟合和周期分析表明,城区年及四季旱涝具有阶段性变化特征,某些阶段年际变化特征也很显著,总体而言,年及夏季旱涝的年代际变化特征较明显,其它三个季节则是年际变化特征较明显。近几年的年旱涝变化处于偏涝阶段;而近几年夏季的旱涝变化,从年代际尺度来看,目前处在偏旱阶段,出现干旱的可能性较大;而其它三季则处于偏涝阶段。     

南京市浅层地温场监测方案和地温分布特点研究

浅层地温能作为可再生能源,已经引起广泛关注。为了有效地监测南京市浅层地温场的时空演化,针对4种温度传感器：DTS、FBG、Pt100和iButton,通过野外和室内试验进行分析对比,从测温精度、适用范围、工作特性等方面展开研究。结合试验结果和目前的实际应用情况,总结出四种传感器在浅层地温场监测方面的优缺点和特性,并制定出一套较为完善的监测方案,为浅层地温场的长期时空监测提供参考：在所有钻孔中埋设分布式测温光纤,并根据地温钻孔的土层分布和所获取的地温分布数据,选取两个较为典型的地温钻孔布设FBG测温串;在所有钻孔点距地表5 cm处布设iButton,并使用Pt100监测地表以下25 m内的精确地温。根据已获得的监测数据,可总结出南京地区浅层地温在垂向上的大体分布规律,发现其分布在空间上具有差异性,浅地表地温与地表覆盖层、大气及太阳辐射有关,深部地温受地质构造和水文地质条件等因素控制。     

Optical Photometric Observations of 7-Ray Loud Blazars

We report results of our optical photometric observations of ten gamma-ray loud blazers, namely: 0219+428 (3C66A), PKS 0420-014 (OA 129), S5 0716+714, 0754+100 (OI 090.4), 0827+243 (OJ248), 1652+398 (Mrk 501), 2200+420 (BL Lacertae), 2230+114 (CTA 102), 2251+158 (3C 454.3) and 2344+514. The observations were carried out in September-October, 2000 using the 70 cm optical telescope at Abstumani Observatory, Georgia. We found intra-day variations in 0420-014, S5 0716+714, BL Lacertae and CTA 102. A variation of 0.3 magnitude over a time scale of about 3 hours was observed in the R passband in BL Lacertae on JD 2451827. We did not detect any variation in 3C 66A, Mrk 501, or 3C 454.3 during our observations. Nor did we detect any clear evidence of variation in 1ES 2344+514 during our two weeks' observing run of the TeV gamma-ray source.     

Instrument intercomparison study on cloud droplet size distribution measurements: Holography vs. laser optical particle counter

During the EUROTRAC Ground Based Cloud Experiment (GCE) 1990, a newly developed HODAR (Holographic Droplet and Acrosol Recording) was operated for the first time to measure cloud droplet size distributions by recording Fraunhofer in-line holograms of small cloud sample volumes in situ and analyzing the holographic images in the laboratory.This technical note compares the resulting size distributions with those obtained from two FSSP-100 laser optical particle counters. For all holograms analyzed during the GCE90 field experiment, the size distributions obtained from the two different methods agree well. Additionally, the liquid water contents (LWC) were measured directly by a Gerber particulate volume monitor PVM-100. The LWC calculated from the measured droplet size distributions deviate from the PVM-100 data.     

2013 年夏秋季黄、渤海悬浮颗粒物粒径分布特征

悬浮颗粒物及粒径是水质重要参数,研究其分布特征有助于加深对海洋生态环境的了解。利用2013年6月和2013年11月LISST-100观测数据,研究了黄、渤海区域悬浮物粒径和浓度的分布情况,浓度分布整体上近岸高远岸低,粒径分布呈现近岸细远岸粗的特征,季节分布特征明显。通过典型断面分析发现,悬浮物粒径和浓度随着水深变化明显,连续站数据分析结果表明,大风对底层颗粒物的再悬浮作用显著,潮流对悬浮物的时空分布有着重要影响;水体衰减系数随着体积浓度变化明显。此外,还研究了悬浮颗粒物粒径Junge分布在黄、渤海区域的适用性。     

Evaluation of GEV model for frequency analysis of annual maximum water levels in the coast of United States

The three-parameter generalized-extreme-value (GEV) model has been recommended by FEMA [FEMA (Federal Emergency Management Agency of the United States), 2004. Final Draft Guidelines for Coastal Flood Hazard Analysis and Mapping for the Pacific Coast of the United States. http://www.fema.gov/library/viewRecord.do?id=2188] for frequency analysis of annual maximum water levels in the Pacific coast of the United States. Yet, the GEV model's performance in other coastal areas still needs to be evaluated. The GEV model combines three types of probability distributions into one expression. The probability distributions can be defined by one of the three parameters of the GEV model. In this study, annual maximum water levels at nine water-level stations with long history data (more than 70 years) were chosen for analysis in five coastal areas: Pacific, Northeast Atlantic, East Atlantic, Southeast Atlantic, and Gulf of Mexico coasts. Parameters of the GEV model are estimated by the maximum likelihood estimation (MLE) method. Results indicate that probability distributions are characterized by the GEV Type III model at stations in the Pacific, Northeast, and East Atlantic coastal areas, while they are described by GEV Type II in stations of the Southeast Atlantic and Gulf of Mexico coastal areas. GEV model predictions of extreme water levels show good correlation to observations with correlation coefficients of 0.89 to 0.99. For predictions of 10% annual maximum water levels, the GEV model predictions are very good with errors equal to or less than 5% for all nine stations. Comparison of observations and GEV model estimations of annual maximum water levels for the longest recorded return periods, close to 100 years, revealed errors equal to or less than 5% for stations in the Pacific and Northeast Atlantic coastal areas. However, the errors range from 10% to 28% for other stations located in the East and Southeast Atlantic coasts as well as Gulf of Mexico coastal areas. Findings from this study suggest caution regarding the magnitudes of errors in applying the GEV model to the East and Southeast Atlantic coasts and Gulf of Mexico coast for estimating 100-year annual maximum water levels for coastal flood analysis.