拟合风频法计算重庆大气稳定度频率

本文用韦伯分布拟合风频,在确定大气稳定度的三因子太阳高度角、云量和风速是相互独立的变量的假定下,用计算单个变量频率的方法,计算了重庆5年的P—T大气稳定度频率,其结果与原P—T法统计结果十分吻合。对误差综合分析后给出了合理的订正方案,个例订正表明了方案的正确性。通过大量迭代推算给出重庆风速韦伯分布最佳函数值,以供选用。     

What drives television weather coverage?

Weather forecasts meet the classic economic definition of a public good, since the content can be easily relayed to non-payers and the cost of sharing the forecast with an additional person is zero. Freeriding by consumers leads to the potential for an inefficiently small supply of public goods by the market. Yet television networks and stations provide a large quantity of weather coverage. This paper explores the investment by US television stations in weather coverage. Specifically, we examine whether greater investments are made in cities where weather is potentially more dangerous. We find strong evidence that tornado risk drives coverage and weaker evidence for floods and hurricanes, but discover that snowfall is unrelated to investment. In addition, stations in larger markets invest more in weather coverage, and we also find regional patterns in coverage.     

A Hydrologic Drying Bias in Water‐Resource Impact Analyses of Anthropogenic Climate Change

For water‐resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (E_p) as inputs. Because E_p is not a climate‐model output, an intermediary model of E_p must be introduced to connect the climate model to the hydrologic model. Several E_p methods are used. The suitability of each can be assessed by noting a credible E_p method for offline analyses should be able to reproduce climate models’ ACC‐driven changes in actual evapotranspiration in regions and seasons of negligible water stress (E_w). We quantified this ability for seven commonly used E_p methods and for a simple proportionality with available energy (“energy‐only” method). With the exception of the energy‐only method, all methods tend to overestimate substantially the increase in E_p associated with ACC. In an offline hydrologic model, the E_p‐change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC‐induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water‐resource impact analyses.     

Prediction of global solar radiation using support vector machines

This article utilizes Support Vector Machines (SVM) for predicting global solar radiation (GSR) for Sharurha, a city in the southwest of Saudi Arabia. The SVM model was trained using measured air temperature and relative humidity. Measured data of 1812 values for the period from 1998–2002 were obtained. The measurement data of 1600 were used for training the SVM, and the remaining 212 were used for comparison between the measured and predicted values of GSR. The GSR values were predicted using the following four combinations of data sets: (i) Daily mean air temperature and day of the year as inputs, and global solar radiation as output; (ii) daily maximum air temperature and day of the year as inputs, and GSR as output; (iii) daily mean air temperature and relative humidity and day of the year as inputs, and GSR as output; and (iv) daily mean air temperature, day of the year, relative humidity, and previous day’s GSR as inputs, and GSR as output. The mean square error was found to be 0.0027, 0.0023, 0.0021, and 7.65 × 10^?4 for case (i), (ii,), (iii), and (iv) respectively, while the corresponding absolute mean percentage errors were 5.64, 5.08, 4.48, and 2.8%. Obtained results show that the SVM method is capable of predicting GSR from measured values of temperature and relative humidity.     

淮河流域一次梅雨锋暴雨的中尺度动力特征分析

针对2007年7月8日发生在苏皖淮河流域的暴雨,采用WRF中尺度数值模式模拟结果、FNL每日4次1°*1°再分析资料、6h地面实况观测降水资料和FY-2相当黑体亮温TBB资料对该次降水的发生、发展过程进行了分析研究。结果表明:(1)该次降水在有利的大气环流形势下,强降水发生在呈准东西向分布的梅雨锋上。位于蒙古国与我国华北—东北交界处上空的切断低压给淮河流域输入了冷空气。冷空气与西南低空急流带来的暖湿气流交汇,增强了大气斜压性;(2)正的非热成风涡度的发展促进了高层相对于低层的辐散减压,有利于垂直上升运动的发展;(3)低空强急流带所形成的动力、热力和水汽条件对暴雨落区位置产生了重要影响。     

Hydrologic Resilience from Summertime Fog and Recharge: A Case Study for Coho Salmon Recovery Planning

Fog and low cloud cover (FLCC) and late summer recharge increase stream baseflow and decrease stream temperature during arid Mediterranean climate summers, which benefits salmon especially under climate warming conditions. The potential to discharge cool water to streams during the late summer (hydrologic capacity; HC) furnished by FLCC and recharge were mapped for the 299 subwatersheds ranked Core, Phase 1, or Phase 2 under the National Marine Fisheries Service Recovery Plan that prioritized restoration and threat abatement action for endangered Central California Coast Coho Salmon evolutionarily significant unit. Two spatially continuous gridded datasets were merged to compare HC: average hrs/day FLCC, a new dataset derived from a decade of hourly National Weather Satellite data, and annual average mm recharge from the USGS Basin Characterization Model. Two use‐case scenarios provide examples of incorporating FLCC‐driven HC indices into long‐term recovery planning. The first, a thermal analysis under future climate, projected 65% of the watershed area for 8–19 coho population units as thermally inhospitable under two global climate models and identified several units with high resilience (high HC under the range of projected warming conditions). The second use case investigated HC by subwatershed rank and coho population, and identified three population units with high HC in areas ranked Phase 1 and 2 and low HC in Core. Recovery planning for cold‐water fish species would benefit by including FLCC in vulnerability analyses.     

华北地区天气型对区域大气污染的影响

分析了2000—2001年采暖期重污染天气型演变、垂直温湿层结结构及区域污染特征。区域性重污染背景为各类重污染天气型相继影响的复合系统,其中有各类天气型组成的污染物传输、汇聚和区域污染同步累积系统。华北平原区域性同步污染现象受制于高空持续稳定的西风及低空各类稳定的天气型配置。各地同一时期污染指数的差异与排放源群结构及输送汇聚天气型移动和演变影响有关。区域性重污染温湿层结多为喇叭口状(沙尘型污染除外)。      

大气环境影响评价中污染气象分析

结合环境影响评价技术导则的要求,就实际大气环境影响评价工作中污染气象分析与大气影响预测脱节的问题,对污染气象分析应注意的要点提出探讨与建议,使污染气象分析能够更为真实地反映该地区的实际气象条件对大气污染物浓度的影响情况。     

多源降水数据在长江上游流域比较研究

降水是洪水预报重要的输入因子,是保证洪水预报精度的前提条件。提出一种从站点、子流域以及全流域3种空间尺度上评价水情遥测降水数据精度的方法。采用该方法,以国家气象信息中心公开发布的日降水数据为基准,针对覆盖宜昌-宜宾425 000 km2的377个遥测雨量站降雨数据进行精度评价。在日、月时间尺度上,综合评价了中国长江三峡集团所属的遥测雨量数据精度特征。结果表明,其遥测雨量数据与国家气象信息中心公开发布的日降水数据,具有较高的相关度,相关指标R2到达0.81。部分数据受到地形以及站点位置差异等因素的影响,存在一定差异。这些差异为雨量站的调整和补充提供重要依据。为验证其他遥测站网的降水数据精度提供了范例,利用该方法,可对运行多年的遥测雨量站网进行评价,也可开展多源降水融合相关工作,提高地面遥测降水数据的代表性和准确性。     

2009年8~9月成都市颗粒物污染及其与气象条件的关系

对成都市3个不同点位PM2.5和PM10进行了为期30d的连续观测,研究了大气颗粒物浓度的时空分布特征,及其与气象条件的关系.研究表明,观测期间成都市大气颗粒物PM2.5和PM10质量浓度日均值分别为66,94μg/m3,两者浓度变化范围较大,但变化趋势相同.从空间分布来看,大气颗粒物浓度均是熊猫基地>草堂寺>丽都花园,即下风向污染状况最严重,商业繁华地段次之,生活居住区最好;从时间分布来看,大气颗粒物污染最严重出现在9月17~19日,9月5~9日2个时间段,不利的气象因素和污染物的累积是造成该时间段大气颗粒物污染加重的主要原因.PM2.5与PM10质量浓度的相关性为0.93,PM2.5对PM10的贡献较大,两者质量浓度的比值达0.69.气温对大气颗粒物浓度变化没有显著影响;降水以及风速对颗粒物浓度影响较大,主要是对颗粒物的湿清除和促进扩散作用;在一定相对湿度范围内,高湿度条件容易造成大气颗粒物的较重污染.能见度与大气颗粒物浓度呈明显负相关性,且与PM2.5的相关系数大于与PM10的相关系数.