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1.
本研究利用WRF模式及其三维变分同化系统实现了对NOAA-16 AMSU-A微波资料的直接同化,针对2010年6月19日江西地区的一次强降水过程开展模拟与同化试验,并利用中国区域土壤湿度同化系统(CLSMDAS—China Land Soil Moisture Data Assimilation System)输出的土壤湿度值替换NCEP(National Centers for Environmental Prediction)资料中的土壤湿度,研究土壤湿度初值对辐射率资料直接同化中观测场与背景场偏差调整的影响。结果表明:采用CLSMDAS输出土壤湿度初值条件下模拟的亮温值与实际观测值更为接近,经过质量控制和偏差订正后更多的观测资料能够进入到同化系统中,说明改进的土壤湿度初值条件下观测算子的计算值得到正的调整,对低层地表通道的改进效果明显,尤其以50.3 GHz的窗区通道3的结果最为理想;针对此次强降水过程中24 h累积降水分布的模拟结果,CLSMDAS输出土壤湿度初值条件下同化AMSU-A资料,能够较为准确的把握整个雨带的走向、大雨以上级别降水的落区范围、降水中心落区及强度等。说明准确的土壤湿度初值能够改进卫星辐射率资料的同化结果,进而提高数值模式的模拟预报能力。 相似文献
2.
Two sets of assimilation experiments on a landfalling typhoon—Typhoon Dan(1999)over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that are the 3-Dimensional Variational data assimilation of Mapped observation(3DVM)and the 4-dimensional variational data assimilation(4DVar).Results show that:(1)both the 3DVM and 4DVar successfully improved the simulations of typhoon intensity and track incorporating the satellite AMSU-A retrieved temperature and wind data into the initial conditions,and the 3DVM more significantly due to the flow-dependent of background error covariance matrix and observation error covariance matrix like 3-dimensional variational data assimilation(3DVar)circle;(2)inclusions of extra model integration iterations at each observation time in the 3DVM make it more consistent with prediction model;(3)the 3DVM is much more time-saving due to the exclusion of the adjoint technique in it. 相似文献
3.
运用美国NOAA-15极轨气象卫星高分辨率的AMSU探测资料, 结合NCEP/NCAR再分析资料和GMS-5气象卫星红外云顶亮温(TBB)资料, 对2004年Chaba(0417)台风(TC)变性前后的热力结构特征进行分析。发现变性前TC暖核结构呈对称分布, 在高空存在一强暖心; 变性后原TC对称暖心结构消失, 存在于温带气旋上空的相对暖区呈现出倾斜的非对称分布, 在高、低层各形成一弱的暖区中心, 锋面的斜压特性显著。通过热力结构对比, 进一步揭示出TC在向高纬度方向移动时, 与中纬度系统相互作用发生变性, 实质上是两个相继过程, 即热带气旋的消亡和温带气旋的生成发展。TC西侧高空干冷空气的入侵下沉, 破坏了其发展所需的水汽条件, 造成TC对称暖核结构的削弱和损毁。与此同时, 在TC残留区域, 由于空气较暖且存在气旋式环流, 暖空气在东侧呈气旋式上升, 与西侧高空入侵下沉的干冷空气形成偶极, TC暖气团与冷空气相交发展形成斜压的结果, 则为温带气旋的生成和发展创造了有利条件。 相似文献
4.
Back propagation neural networks are used to retrieve atmospheric temperature profiles from NOAA-16 Advanced Microwave Sounding Unit-A (AMSU-A) measurements over East Asia. The collocated radiosonde observation and AMSU-A data over land in 2002-2003 are used to train the network, and the data over land in 2004 are used to test the network. A comparison with the multi-linear regression method shows that the neural network retrieval method can significantly improve the results in all weather conditions. When an offset of 0.5 K or a noise level of ±0.2 K is added to all channels simultaneously, the increase in the overall root mean square (RMS) error is less than 0.1 K. Furthermore, an experiment is conducted to investigate the effects of the window channels on the retrieval. The results indicate that the brightness temperatures of window channels can provide significantly useful information on the temperature retrieval near the surface. Additionally, the RMS errors of the profiles retrieved with the trained neural network are compared with the errors from the International Advanced TOVS (ATOVS) Processing Package (IAPP). It is shown that the network-based algorithm can provide much better results in the experiment region and comparable results in other regions. It is also noted that the network can yield remarkably better results than IAPP at the low levels and at about the 250-hPa level in summer skies over ocean. Finally, the network-based retrieval algorithm developed herein is applied in retrieving the temperature anomalies of Typhoon Rananim from AMSU-A data. 相似文献
5.
AMSU-A (Advanced Microwave Sounding Unit-A) measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction (NWP) models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting (WRF) model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation (WRF-VAR) system, the surface parameters from the operational Microwave Surface and Precipitation Products System (MSPPS) are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error (RMSE) and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction (NCEP) global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land. 相似文献
6.
同化卫星对地敏感通道微波亮温观测的模拟试验 总被引：1，自引：0，他引：1
借助快速辐射传输模式RTTOV v10（Radiative Transfer for TOVS）及其地表微波发射率模块,针对江淮区域晴天和雨天2类不同天气状况,采用理想试验手段,利用集合平方根滤波（En SRF）方法同化AMSU-A对地敏感第1通道的模拟亮温资料,探究改善中尺度模式WRF（Weather Research and Forecasting）初始场的可行性。结果表明：晴天时,同化对位温、水汽混合比及水平风速u和v整体上均有不同程度的改善,但不同高度改善程度有所差异,相对而言水平风场的改进程度最大,位温最小;有降水时,4个要素场整体改进程度与晴天时类似,但分析场误差的水平空间分布与晴天时不同。 相似文献
7.
采用支持向量机(SVM,Support Vector Machine)方法,对AMSU-A进行了临边调整试验。利用全球廓线数据集和快速辐射传输模式计算的理想亮温资料,以及AMSU-A全球实际亮温资料的分析表明,临边效应增大了窗区通道边缘视场的亮温,减小了5～14通道边缘视场亮温。临边效应对于各通道影响明显,且随着视角的增大而增大。通过理想试验分析表明,与多元线性回归方法相比,支持向量机方法对于窗区通道调整效果改进较多,对于通道5～14,同样优于多元线性回归方法。除窗区通道1、2、15边缘少数视场外,各视场调整均方根(RMS,Root Mean Square)误差在AMSU-A仪器噪声范围之内。对实际资料的试验表明,支持向量机方法调整效果同样优于多元线性回归方法。 相似文献
8.
T639-GSI全球系统同化AMSU-A资料的过程中,目前使用的月平均积雪产品并不能反映中高纬度大陆上快速地降雪/融雪过程,而FY-3C日积雪产品在时间精度上要高于GSI月平均积雪覆盖数据。由于同化系统对AMSU-A较低通道辐射率资料的质量控制需要依据更准确的地表积雪信息,所以本文结合冬春季节的FY-3C日积雪产品和NCEP再分析资料,研究了北半球中高纬度地区不同积雪覆盖率初值对分析场不同高度层温度场的影响,以及在同化过程中对预报结果的影响。结果表明,在对AMSU-A辐射率资料的质量控制中,月平均积雪数据和日积雪产品对温度场影响较大的区域与两者积雪覆盖差异区域有明显的对应;冬春季节,使用FY-3C日积雪产品代替GSI月平均积雪数据作为背景场中积雪下垫面数据,对进入同化系统的AMSU-A辐射率资料质量控制时,120 h之内1000—600 h Pa的中低层温度场的预报效果得到改善。 相似文献
9.
本文以2015年13号超强台风“苏迪罗”为个例,利用WRF模式及其3DVar同化系统对NOAA15、NOAA18和NOAA19的AMSU-A微波遥感资料分别同化及组合同化,探究同化不同卫星的同一种微波遥感资料对于台风路径模拟效果的影响。结果表明:同化不同卫星的同一种微波遥感资料对于台风路径模拟具有不同的调整,本文中NOAA15的同化效果最好,其次是NOAA18,最后是NOAA19;同时同化NOAA15、NOAA18和NOAA19的AMSU-A资料并没有取得最好的同化效果,而组合NOAA15和NOAA18则取得了最好的同化效果,即不是同化的卫星数量越多,同化效果越好;同化试验3个时刻的增量场表明同化不同卫星的同一种微波遥感资料对物理场具有不同的调整,这与其对台风模拟路径的调整有着较好的对应,相对于温度场、海平面气压场、位势高度场和风场的增量结构与模拟台风路径的调整更为密切。 相似文献
10.
先进的微波垂直探测器AMSU（Advanced Microwave Sounding Unit）能接收到穿透一定厚度云层的微波辐射信息,适合于分析热带气旋暖核特征.由辐射传输方程和静力学方程可知,气旋暖核强度同中心海平面气压距平相关联. 本文利用搭载于极轨气象卫星NOAA-16/17/18上的AMSU A亮温资料,根据2002～2006年之间发生在西北太平洋区域热带气旋的移动路径,匹配出47个热带气旋的183时次个例,并将各时次的暖核最大亮温距平同气象业务部门发布的热带气旋强度报告值建立统计回归方程. 为进一步提高估测精度,在计算亮温距平过程中,提出用于修正扫描点分辨率不均匀所带来取样偏差的方法,并综合利用AMSU-A的7、8双通道信息来进行估测,利用修正后算法得到暖核亮温距平同气旋强度之间的相关系数为0.80,标准偏差为12.2 hPa,对近年来影响我国较大的两个台风（0414“云娜”和0608“桑美”）进行个例估测,平均偏差约6 hPa. 相似文献