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1.
高留喜  朱蓉  常蕊 《气象》2014,40(10):1240-1247
对QuikSCAT和ASCAT原始轨道10 m反演风场与浮标资料在中国南海北部的统计检验分析结果表明:两套卫星资料在中国南海北部具有较好的适用性,QuickSCAT反演风速偏高0.46 m·s~(-1),ASCAT反演风速在近海偏高0.45 m·s~(-1),在开阔海域偏高0.07 m·s~(-1)。超过半数的QuickSCAT反演风向误差30°。在近岸海域,ASCAT反演风向误差30°的超过56%,在开阔海域,误差绝对值30°的达到64%。小风时卫星反演风速偏大,大风时卫星反演风速明显偏小,且白天的偏差大于夜间;在5~10 m·s~(-1)风速条件下,两者的一致性较好。用WRF模式模拟的近海风能资源存在高估的可能,卫星资料对近海风能资源评估是个有益的补充,本文对卫星反演风场误差的分析结果也可以为卫星反演风场的资料同化提供参考。  相似文献   

2.
应用MM5模式对地面大风过程的模拟试验   总被引:6,自引:2,他引:6  
用MM5模式对2 0 0 1年4月1 7~1 9日、5月1 2~1 5日辽宁省出现的大风过程进行了模拟,并与1 3个代表点的气象观测站资料或野外风电场测风资料作了对比。结果表明:模式能较好地模拟区域风场的演变和分布特征;对逐时风速的模拟与实况有一定差异,但模拟值与实况变化比较同步,基本反映出单点风速变化的趋势;对瞬时风速大于1 0m·s-1和平均风速大于9 0m·s-1的模拟明显偏小。模拟试验初步说明,MM5模式对区域地面风场形势、单点风速随时间变化特征的模拟较好,但可能减弱大风的实际强度。  相似文献   

3.
利用中尺度气象数值模式WRF和动力降尺度模式CALMET,对江西山地风电场不同高度层风速进行4个月逐时数值模拟,结合测风塔实测资料,对两种模式的模拟结果进行准确性、误差特征等方面研究,结果表明:1) WRF模式和CALMET模式均能较好地模拟出风速的日变化特征,在大风速时间段两个模式模拟误差变大,可能是由于出现台风、降雨伴随大风等天气时,WRF模式边界层方案对大风速时拖曳作用不充分造成,今后可考虑通过天气过程模拟的敏感性研究及历史数据对模拟结果进行订正。2)从各月模拟结果来看,WRF模式与CALMET模式各月模拟值与实测值间相关系数均大于0. 65,两个模式对70 m高度层模拟结果均优于对10 m高度层的模拟结果,并且CALMET模式均方根误差低于WRF模式的。3) CALMET模式在各风速段模拟效果均优于WRF模式的。两个模式在0~3 m·s-1低风速的模拟效果最优,在大风速段( 8 m·s~(-1))模拟结果平均绝对误差最大,今后应对大风模拟结果的订正开展进一步研究。  相似文献   

4.
基于陆面数据同化系统改进中国区域土壤湿度的模拟研究   总被引:1,自引:0,他引:1  
利用中国区域地面气象要素驱动数据集(China Meteorological Forcing Dataset,CMFD),驱动中国科学院大气物理研究所陆面数据同化系统(LDAS-IAP/CAS-1.0),得到了2003—2010年中国区域土壤湿度数据集,同时不考虑同化卫星遥感亮温数据,直接驱动CLM3.0模拟了2003—2010年中国区域土壤湿度时空变化。将二者土壤湿度模拟结果、地面土壤湿度观测值、美国国家环境预报中心(NCEP)气候再分析数据(CFSR)、基于主动和被动微波传感器的全球土壤湿度数据(SM-MW)进行对比分析发现,考虑同化卫星遥感亮温后与不考虑同化模拟的土壤湿度空间分布有明显差异。将模拟、同化土壤湿度值与观测值对比发现,同化后的青海、甘肃、宁夏和陕西地区土壤湿度较模拟结果有一定的改善。相对于CFSR再分析数据和SM-MW遥感反演数据,模拟和同化土壤湿度值在35°N以南对土壤湿度空间分布的细节刻画更为细致。同化卫星遥感亮温数据后,从2003—2010年土壤湿度四季和年平均空间分布看出,土壤湿度空间分布从西北向东南增加。东北、江淮地区及青藏高原为土壤湿度高值区,新疆和内蒙古为土壤湿度低值区。从变化趋势来看,内蒙古、青藏高原和新疆南部年平均土壤湿度呈增加趋势,其他地区以减小趋势为主。  相似文献   

5.
使用GRAPES模式对南海季风爆发进行模拟研究。针对模拟预报中初始场信息偏弱的情况,引入NOAA17卫星AMSU-B资料改进初值。直接利用GRAPES三维变分同化系统,设计了两个同化试验方案:试验1(T1)同时同化探空资料和AMSU-B资料、试验2(T2)仅仅同化常规探空资料,然后应用GRAPES有限区域模式进行模拟预报。通过对比试验发现,该模式对初始场的改变十分敏感,可以比较成功地模拟出南海夏季风的爆发时间和爆发候的高、低层风场配置以及季风与季风雨带的向北推进。然而该方案对于雨量和副热带高压位置的模拟,与观测相比尚存在一定的偏差,主要表现为副热带高压位置模拟偏西、偏北;南海地区的降水量模拟偏大、降水范围偏大。  相似文献   

6.
利用2015-2018年新疆境内兰新铁路沿线32个大风监测站逐小时风速资料,基于统计学方法、空间分析法,从平均大风日数、大风历时、不同风速的贡献率以及平均风速不同时间尺度和地域分布的变化特征等,对兰新铁路新疆段内两个最强风区带——百里风区和前百里风区的大风特征进行统计和对比分析。结果表明:较之百里风区,前百里风区更易出现极端大风天气(大于11级风),同时具有风速"昼弱夜强"、地域分布差异性大、主导风向与兰新铁路运行方向基本垂直以致横风强劲等特点。该分析结果能够有效弥补前百里风区这一无人区气象规律探索的空白,可为探明特殊地域强风区大风最新变化规律、关键区的大风逐小时内精细化预报、专项试验研究、风速灾害预警阈值的制定等提供基础。  相似文献   

7.
利用2013年洛川国家基准气候站迁站前后气温、相对湿度、降水量、风向风速等观测资料对比分析,发现新站月平均气温、月最低气温、降水量、2min月平均风速、最大风速大于旧站,大风日多于旧站,6—8月最高气温、相对湿度小于旧站,新旧站风向有显著差异。造成迁站前后气象要素差异的原因,主要是观测场周围环境、下垫面性质改变,海拔高度变化对气象要素的影响不明显。  相似文献   

8.
利用江苏省气象局与美国强风暴实验室联合开发的高精度数值分析及预报系统(Precision Weather Analysis and Forecast System,PWAFS)对雷达资料同化中径向速度资料的两种坐标转换方案进行对比分析。Grid方案将雷达径向速度资料通过最小二乘法从极坐标映射到模式三维网格;Tilt方案将雷达径向速度资料通过双线性插值在水平方向插值至标量水平网格,但在垂直方向不进行插值,保留在雷达仰角对应的高度上。两种方案对反射率资料的处理均是插值到模式三维网格点。Grid方案在近雷达处进行平滑,在远雷达处进行插值,会导致低层数据平滑,Tilt方案减少了雷达径向风观测垂直插值引发的误差,更多的保留了雷达观测的特性。本研究分别通过龙卷、大风及梅雨锋暴雨个例对这两种方案的同化结果进行对比分析。龙卷个例中Grid方案得到了部分虚假的较大的同化风场,Tilt方案结果清楚展示了龙卷发生位置的回波及流场的精细结构。大风个例中两种方案得到的最大风速值差3 m·s^-1,Tilt方案的结果更接近观测最大风速值,且得到的大风速区分布更符合观测。梅雨锋暴雨个例中Grid方案对东北及西南两个区域的大风速区均未能很好的反映,Tilt方案得到的水平风速大值区范围明显优于Grid方案。在靠近雷达中心的低层,观测资料密集,Tilt方案能够更好的反应实际大气状态。但是因为缺乏其他观测资料进行验证,两种方案的效果还需要利用数值预报或其他方法进行对比。  相似文献   

9.
为了实现复杂地形下高分辨率风场的数值模拟及特征分析,采用中尺度气象模式WRF(Weather Research and Forecasting M odel)结合牛顿松弛逼近Nudging资料同化技术,实现哈密地区水平分辨率1 km的近地层风场数值模拟计算。基于模拟区域测风塔实测数据的对比检验发现,同化观测资料后风速风向的模拟结果均与实测更加接近,70 m高度风速模拟结果的绝对误差降低0. 25 m·s~(-1),同化后的模拟结果可以较好的修正风速较小时模拟值偏高和风速较大时模拟值偏小的问题,同时风廓线的模拟结果也与实测更加吻合。通过分析哈密复杂地形下水平分辨率1 km逐10 min风场输出结果发现:(1)哈密地区地形比较复杂,风速平面分布差异很大,4月份风速较大区域主要分布在山北地区和西部山南垭口附近,而7月份风速较大区域则位于西部的山坳南部和北部地区;(2)复杂地形下风速较小时风速为负切变,且平均风速越小负切变值越大,地形越复杂负切变值越大;风速较大即使是复杂地形下同样为正切变,但是正切变值比平坦地区的值要小,平坦地形下风速越大正切变值越大;(3)哈密地区复杂地形下,风速12~25 m·s~(-1)的风速占比在时间和空间上分布差异较大,风速较大的4月份,大部分地区占比达到20%以上,尤其是山北和西部垭口附近,占比甚至达到了50%以上,风速为12~25 m·s~(-1)的情况下80 m高度平均风速比60 m高0. 60~0. 80 m·s~(-1),比月平均风速的垂直变化值要大;(4)风速较大时,风向10 min变化不明显,风速较小时,风向变化值较大,且地形较平坦地区风向变化值较大,地形复杂地区变化值较小;(5)风向的垂直变化与风速大小关系比较明显,风速越小,其垂直变化越大,风向垂直变化的区域分布与地形复杂程度相关,地形越复杂风向的垂直变化值越大。  相似文献   

10.
散射计和下投式探空仪资料对台风模拟的影响   总被引:2,自引:1,他引:1       下载免费PDF全文
为了评估同化QuikSCAT海平面气压场资料和Dropsonde资料对台风"Bilis"和"Kat-rina"模拟的影响,通过WRF-3DVAR变分同化系统将QuikSCAT海平面气压场资料和Dropsonde资料同化到WRF模式中,并以未同化任何资料和同化了QuikSCAT海平面气压场以及同化了Drop-sonde资料的数据为初始场,应用WRF模式进行模拟预报,并对得到的初始分析场和模拟预报得到的结果与台风实况报文进行了对比,得到的结论是:对台风初始时刻海平面气压场分布、初始台风中心定位、台风初始暖心结构的改善、台风路径、海平面最低气压场、海面最大风速和雷达回波的模拟方面,同化QuikSCAT海平面气压场的效果比同化Dropsonde资料明显,其中二者对海平面最低气压场的改进效果比海面最大风速的要好。但是两种资料的同化对初始相对湿度和台风强度细节变化方面都没有产生明显改善作用。同化QuikSCAT海平面气压场试验虽然仅仅同化了单层海平面气压场,但是在三维变分同化系统的动力约束作用下,也可以影响到中高层的各个要素场。  相似文献   

11.
To achieve a high-quality simulation of the surface wind field in the Chukchi/Beaufort Sea region, quick scatterometer (QuikSCAT) ocean surface winds were assimilated into the mesoscale Weather Research and Forecasting model by using its three-dimensional variational data assimilation system. The SeaWinds instrument on board the polar-orbiting QuikSCAT satellite is a specialized radar that measures ice-free ocean surface wind speed and direction at a horizontal resolution of 12.5 km. A total of eight assimilation case studies over two five-day periods, 1–5 October 2002 and 20–24 September 2004, were performed. The simulation results with and without the assimilation of QuikSCAT winds were then compared with QuikSCAT data available during the subsequent free-forecast period, coastal station observations, and North American Regional Reanalysis data. It was found that QuikSCAT winds are a potentially valuable resource for improving the simulation of ocean near-surface winds in the Chukchi/Beaufort Seas region. Specifically, the assimilation of QuikSCAT winds improved, (1) offshore surface winds as compared to unassimilated QuikSCAT winds, (2) sea-level pressure, planetary boundary-layer height, as well as surface heat fluxes, and (3) low-level wind fields and geopotential height. Verification against QuikSCAT data also demonstrated the temporal consistency and good quality of QuikSCAT observations.  相似文献   

12.
台风模拟中QuikSCAT风场的非对称加强订正及同化应用   总被引:1,自引:0,他引:1  
针对QuikSCAT 散射计风场资料对台风级别的强风速区还无法准确刻画这个技术问题,引入台风移速、移向、摩擦等客观因素对该风场产品资料进行非对称加强订正;然后利用四维同化技术,并设计了先同化后预报两个阶段的试验方案,对“云娜”台风进行了数值模拟试验。试验结果表明:通过模式约束调整,四维同化技术可以把QuikSCAT 海面风场资料引入到整层模式大气中,并对整层风场和气压场的强度及路径模拟都有很大的改进,而且该资料还提高了预报阶段台风强度的模拟效果,并对登陆点的预报起到了积极作用。  相似文献   

13.
As an approach to the technological problem that the wind data of QuikSCAT scatterometer cannot accurately describe the zone of typhoon-level strong wind speed, some objective factors such as the typhoon moving speed, direction and friction are introduced in this study to construct the asymmetric strengthening of the QuikSCAT wind field. Then by adopting a technology of four-dimensional data assimilation, an experiment that includes both the assimilation and forecasting phases is designed to simulate Typhoon Rananim numerically. The results show that with model constraints and adjustment, this technology can incorporate the QuikSCAT wind data to the entire column of the model atmosphere, improve greatly the simulating effects of the whole-column wind, pressure field and the track as well as the simulated typhoon intensity covered by the forecast phase, and work positively for the forecasting of landfall locations.  相似文献   

14.
基于WRF-3DVAR同化多源融合数据对近海风模拟的改进试验   总被引:1,自引:1,他引:0  
本文利用WRF模式及其3DVAR同化系统,以2008年4月20日00时—23日00时的江苏近海10 m风场为研究个例,对Quik SCAT、Wind SAT、多源测风融合数据进行同化试验,通过比较WRF-3DVAR同化系统对模拟风场初始场和预报场的改进,检验了同化不同类型资料后WRF模式对研究区域内单点及区域近地层风速的预报效果。结果表明:同化试验对初始场有改进,且对预报场的改进较FNL资料明显;不同资料对风场模拟的影响不同,同化星星、星地多源融合资料效果最佳,Quik SCAT次之,Wind SAT最差。此外,在模式分辨率一定的情况下,提高观测资料的分辨率并不一定能够改善模拟效果,资料的稀疏分辨率存在最佳选择。  相似文献   

15.
Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Quick Scatterometer (QuikSCAT) near surface winds, Special Sensor Microwave/Imager (SSM/I)-derived Total Precipitable Water (TPW), and Meteosat-7-derived Atmospheric Motion Vectors (AMVs) on the track and intensity prediction of tropical cyclones over the North Indian Ocean. The case of tropical cyclone, Gonu (June 2007; Arabian Sea), is first tested and the results show significant improvements particularly due to the assimilation of QuikSCAT winds. Three other cases, cyclone Mala (April 2006; Bay of Bengal), Orissa super cyclone (October 1999; Bay of Bengal), and Very Severe Cyclonic storm (October 1999; Bay of Bengal), are then examined. The prediction of cyclone tracks improved significantly with the assimilation of QuikSCAT winds. The track improvement resulted from the relocation of the initial cyclonic vortices after the assimilation of QuikSCAT wind vectors. After the assimilation of QuikSCAT winds, the mean (for four cyclone cases) track errors for first, second, and third day forecasts are reduced to 72, 101, and 166?km, respectively, from 190, 250, and 381?km of control (without QuikSCAT winds) runs. The assimilation of QuikSCAT winds also shows positive impact on the intensity (in terms of maximum surface level winds) prediction particularly for those cyclones, which are at their initial stages of the developments at the time of data assimilation. The assimilation of SSM/I TPW has significant influence (negative and positive) on the cyclone track. In three of the four cases, the assimilation of the SSM/I TPW resulted in drying of lower troposphere over cyclonic region. This decrease of moisture in TPW assimilation experiment resulted in reduction of cyclonic intensity. In three of the four cyclones, the assimilation of Meteosat-7 AMVs shows negative impact on the track prediction.  相似文献   

16.
A low pressure system that formed on 21 September 2006 over eastern India/Bay of Bengal intensified into a monsoon depression resulting in copious rainfall over north-eastern and central parts of India. Four numerical experiments are performed to examine the performance of assimilation schemes in simulating this monsoon depression using the Fifth Generation Mesoscale Model (MM5). Forecasts from a base simulation (with no data assimilation), a four-dimensional data assimilation (FDDA) system, a simple surface data assimilation (SDA) system coupled with FDDA, and a flux-adjusting SDA system (FASDAS) coupled with FDDA are compared with each other and with observations. The model is initialized with Global Forecast System (GFS) forecast fields starting from 19 September 2006, with assimilation being done for the first 24 hours using conventional observations, sounding and surface data of temperature and moisture from Advanced TIROS Operational Vertical Sounder satellite and surface wind data over the ocean from QuikSCAT. Forecasts are then made from these assimilated states. In general, results indicate that the FASDAS forecast provides more realistic prognostic fields as compared to the other three forecasts. When compared with other forecasts, results indicate that the FASDAS forecast yielded lower root-mean-square (r.m.s.) errors for the pressure field and improved simulations of surface/near-surface temperature, moisture, sensible and latent heat fluxes, and potential vorticity. Heat and moisture budget analyses to assess the simulation of convection revealed that the two forecasts with the surface data assimilation (SDA and FASDAS) are superior to the base and FDDA forecasts. An important conclusion is that, even though monsoon depressions are large synoptic systems, mesoscale features including rainfall are affected by surface processes. Enhanced representation of land-surface processes provides a significant improvement in the model performance even under active monsoon conditions where the synoptic forcings are expected to be dominant.  相似文献   

17.
1971—2015年大连地区低风速气象特征分析   总被引:2,自引:0,他引:2  
祝青林  王丽娜  徐梅  牛桂萍 《气象》2017,43(12):1578-1583
利用1971—2015年大连地区7个国家气象站的气象资料, 统计低风速条件下的累积频率、日变化、月变化和持续性等特征,分析低风速频率空间分布和年际变化特征。结果表明: (1)大连地区低风速频率较低,平均约20%,地区间差异显著,近海区域长海站最低,为8%,内陆的普兰店地区较高,达32%。(2)近45年,低风速频率呈增加趋势,大连、长海和普兰店站增加趋势显著,特别是近10年增幅更大。(3)大连站低风速频率具有显著的日变化,主要表现为白天偏低、中午时段最低,夜间高,半夜达到最高。(4)3—7月,大连地区低风速频率低;9月至次年2月较高,最大值出现在9月。(5)低风速持续时间长海站最长,持续10 h以上低风速频率达到27%,持续20 h以上接近9%,大连站低风速持续时长最短,持续4 h以下的占85%。  相似文献   

18.
This paper focuses on the data assimilation methods for sea surface winds, based on the level-2B HY-2A satellite microwave scatterometer wind products. We propose a new feature thinning method, which is herein used to screen scatterometer winds while maintaining the key structure of the wind field in the process of data thinning for highresolution satellite observations. We also accomplish feeding the ambiguous wind solutions directly into the data assimilation system, thus making better use of the retrieved information while simplifying the assimilation process of the scatterometer products. A numerical simulation experiment involving Typhoon Danas shows that our method gives better results than the traditional approach. This method may be a valuable alternative for operational satellite data assimilation.  相似文献   

19.
The present study is conducted to verify the short-range forecasts from mesoscale model version5 (MM5)/weather research and forecasting (WRF) model over the Indian region and to examine the impact of assimilation of quick scatterometer (QSCAT) near surface winds, spectral sensor microwave imager (SSM/I) wind speed and total precipitable water (TPW) on the forecasts by these models using their three-dimensional variational (3D-Var) data assimilation scheme for a 1-month period during July 2006. The control (without satellite data assimilation) as well as 3D-Var sensitivity experiments (with assimilating satellite data) using MM5/WRF were made for 48 h starting daily at 0000 UTC July 2006. The control run is analyzed for the intercomparison of MM5/WRF short-range forecasts and is also used as a baseline for assessing the MM5/WRF 3D-Var satellite data sensitivity experiments. As compared to the observation, the MM5 (WRF) control simulations strengthened (weakened) the cross equatorial flow over southern Arabian sea near peninsular India. The forecasts from MM5 and WRF showed a warm and moist bias at lower and upper levels with a cold bias at the middle level, which shows that the convective schemes of these models may be too active during the simulation. The forecast errors in predicted wind, temperature and humidity at different levels are lesser in WRF as compared to MM5, except the temperature prediction at lower level. The rainfall pattern and prediction skill from day 1 and day 2 forecasts by WRF is superior to MM5. The spatial distribution of forecast impact for wind, temperature, and humidity from 1-month assimilation experiments during July 2006 demonstrated that on average, for 24 and 48-h forecasts, the satellite data improved the MM5/WRF initial condition, so that model errors in predicted meteorological fields got reduced. Among the experiments, MM5/WRF wind speed prediction is most benefited from QSCAT surface wind and SSM/I TPW assimilation while temperature and humidity prediction is mostly improved due to latter. The largest improvement in MM5/WRF rainfall prediction is due to the assimilation of SSM/I TPW. The assimilation of SSM/I wind speed alone in MM5/WRF degraded the humidity and rainfall prediction. In summary the assimilation of satellite data showed similar impact on MM5/WRF prediction; largest improvement due to SSM/I TPW and degradation due to SSM/I wind speed.  相似文献   

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