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851.
852.
用WRF模式对2007年4月21—22日的一次中α低涡暴雨过程进行了高分辨率模拟,结果表明:(1)该低涡的产生与湖北西部的地形条件有一定的联系,低压倒槽系统为其提供了必要的环流背景,反演自FY-2 C卫星的TBB资料较好地反映了该中α低涡的整个活动过程。(2)对低涡发展最强阶段的动力和热力结构分析表明,低涡右侧为较强的上升运动,而其左侧则为下沉运动,在中低层冷空气上部有南侧暖湿空气上爬造成的次级上升运动;低涡左侧存在较明显的湿斜压锋区,后部则有明显的干冷气切入;南风风量对总体水汽输送的贡献要大于西风风量。(3)WRF模式中NOAH和热扩散陆面方案的对比分析表明,NOAH方案更加有利于低涡中心的发展,因此能够产生较热扩散方案更强的中心区降水,但是这种增强作用主要分布在低涡区附近,其他地区差别不大。 相似文献
853.
Summary The uncertainty in aerosol size distributions is a main source of errors in aerosol optical thickness determined from satellite
measurements. To reduce the errors resulting from the uncertainty in aerosol size distributions, we have performed sensitivity
analyses. It is found the errors resulting from the uncertainty in aerosol size distribution can be considerably reduced by
using the Junge power law to approximate the aerosol size distribution in an actual atmosphere, if the exponent value is determined
at the same time. An iterative algorithm is then developed for the simultaneous determination of aerosol optical thickness
and the exponent of the Junge power law over ocean areas from the upwelling radiances measured in AVHRR visible and near infrared
channels. A number of numerical experiments are carried out to investigate the validity of the Junge power law approximation
by assuming the aerosol size distributions in an actual atmosphere are bimodal with different mode parameters, and by using
the actual aerosol size distributions determined at several places by Kaufman et al. (1994). The results show that the errors
in determined aerosol optical thickness resulting from the Junge power law approach are significantly reduced. The iterative
algorithm is investigated further by comparing the aerosol optical thickness deduced from satellite measurement with that
observed by a sun photometer.
Received October 10, 2001 Revised December 28, 2001 相似文献
854.
The neuro‐controller training algorithm based on cost function is applied to a multi‐degree‐of‐freedom system; and a sensitivity evaluation algorithm replacing the emulator neural network is proposed. In conventional methods, the emulator neural network is used to evaluate the sensitivity of structural response to the control signal. To use the emulator, it should be trained to predict the dynamic response of the structure. Much of the time is usually spent on training of the emulator. In the proposed algorithm, however, it takes only one sampling time to obtain the sensitivity. Therefore, training time for the emulator is eliminated. As a result, only one neural network is used for the neuro‐control system. In the numerical example, the three‐storey building structure with linear and non‐linear stiffness is controlled by the trained neural network. The actuator dynamics and control time delay are considered in the simulation. Numerical examples show that the proposed control algorithm is valid in structural control. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
855.
1961—2009年辽河流域水文气象要素变化特征 总被引:1,自引:0,他引:1
依据1961—2009年辽河流域5个气象观测站点逐日降水和气温观测资料,运用非参数检验方法(Mann-Kendall法),对辽河流域降水和气温的变化趋势进行了分析。利用2006—2010年夏季共162d降水日的铁岭站日降水量与铁岭水文站径流量资料,探讨了日降水量与径流量之间的相关关系。结果表明:辽河流域年降水量减少趋势明显,降水量偏少年份明显增加,其主要原因为占全年降水量65%的夏季降水以7.4 mm/10 a的气候趋势倾向率递减,呈现出明显的减少趋势;辽河流域的年平均气温是在波动中逐渐上升的,且升温趋势明显,春季呈明显的升温趋势,夏季略有下降,秋季变化不大,冬季是气温上升最明显的季节;日降水量与径流量存在正相关关系,且日降水量与降水第二日的径流量相关显著。 相似文献
856.
2011年江苏出梅日界定之我见 总被引:1,自引:0,他引:1
利用实况观测数据和NCEP/NCAR再分析资料,对2011年江苏出梅日的界定进行探讨,并将7月4 -20日的低温高湿多雨、寡照的异常气候判定为“倒黄梅”,在此基础上,对比分析了2011年和2009年的两次“倒黄梅”天气过程.结果表明:(1)2011年江苏出梅日为6月30日;(2)出梅后的7月4-20日是“倒黄梅”天气过程;(3)北上台风对梅雨和“倒黄梅”结束具有重要的指示意义;(4)“倒黄梅”和梅雨(含“二度梅”)的天气特点为:前者冷暖空气频繁交替、雨带多经向分布、中低空温湿场反位相配置,常为低温高湿的局地对流性降水;而后者冷暖空气稳定对峙、雨带多纬向分布、中低空温湿场同位相配置,常为高温高湿的大范围稳定性降水. 相似文献
857.
858.
2011年初夏我国长江中下游降水的气候特征及成因 总被引:3,自引:3,他引:3
文章主要分析了2011年初夏长江中下游降水的气候特征及其成因。结果表明:2011年5月长江中下游降水异常偏少,6月转为异常偏多,出现了明显的旱涝转换。长江中下游地区的旱涝转换主要受南海季风、东亚季风强度以及西太平洋副热带高压(副高)的异常快速北跳的影响。研究还发现,6月亚洲中高纬长期维持两槽一脊的环流形势,东北冷涡活动频繁,多次引导冷空气南下。同时,副高异常偏北、偏西,并出现多次西伸过程。由于冷涡的加强南压与西伸的副高相互作用,促使长江以南地区西南气流明显增强,使得冷暖空气在长江中下游地区交汇,最终导致该地降水偏多。 相似文献
859.
A Simulation Study on the Extreme Temperature Events of the 20th Century by Using the BCC_AGCM 总被引:2,自引:1,他引:2 下载免费PDF全文
DONG Min WU Tongwen WANG Zaizhi CHENG Yanjie ZHANG Fang 《Acta Meteorologica Sinica》2012,26(4):489-506
Extreme temperature events are simulated by using the Beijing Climate Center Atmospheric General Circulation Model (BCC AGCM) in this paper. The model has been run for 136 yr with the observed external forcing data including solar insolation, greenhouse gases, and monthly sea surface temperature (SST). The daily maximum and minimum temperatures are simulated by the model, and 16 indices representing various extreme temperature events are calculated based on these two variables. The results show that the maximum of daily maximum temperature (TXX), maximum of daily minimum (TNX), minimum of daily maximum (TXN), minimum of daily minimum (TNN), warm days (TX90p), warm nights (TN90p), summer days (SU25), tropical nights (TR20), and warm spell duration index (WSDI) have increasing trends during the 20th century in most regions of the world, while the cold days (TX10p), cold nights (TN10p), and cold spell duration index (CSDI) have decreasing trends. The probability density function (PDF) of warm/cold days/nights for three periods of 1881-1950, 1951- 1978, and 1979-2003 is examined. It is found that before 1950, the cold day/night has the largest probability, while for the period of 1979-2003, it has the smallest probability. In contrast to the decreasing trend of cold days/nights, the PDF of warm days/nights exhibits an opposite trend. In addition, the frost days (FD) and ice days (ID) have decreasing trends, the growing season has lengthened, and the diurnal temperature range is getting smaller during the 20th century. A comparison of the above extreme temperature indices between the model output and NCEP data (taken as observation) for 1948-2000 indicates that the mean values and the trends of the simulated indices are close to the observations, and overall there is a high correlation between the simulated indices and the observations. But the simulated trends of FD, ID, growing season length, and diurnal temperature range are not consistent with the observations and their correlations are low or even negative. This indicates that the model is incapable to simulate these four indices although it has captured most indices of the extreme temperature events. 相似文献
860.