利用气温与云顶亮温差值检测云方法研究     

黄毅梅  郝剑平  杜春丽 《气象与环境科学》2013,36(4):22-28

利用2005年7-12月卫星资料、地面观测资料、探空资料和地形资料,统计分析了无云条件下气温与云顶亮温的差值,结果表明：无云情况下气温与云顶亮温差值平均为5.04℃,且具有较大的日变化性。由此提出了按时次分别求取阈值用以检测云。通过个例对比分析,初步得出该方法检测云具有以下特点：可用于全天候云检测;不受地形地貌等因素的影响;该云检测方法应用于反演计算,不仅反演的中、高云区域与实测的比较一致,而且反演的低云区域与实测结果也比较一致。  相似文献   

基于MODIS-EVI数据的神农架林区植被指数变化特征研究   总被引：1，自引：0，他引：1  

黄靖  夏智宏 《气象与环境科学》2013,36(3):39-43

对植被覆盖动态变化监测可以提供生态系统状况有价值的信息,可以检测到人类或气候作用引起的变化.以2003-2012年MODIS的遥感数据为信息源,利用增强型植被指数(EVI),采用最大值合成法,对神农架林区植被覆盖动态变化进行监测,并与同期的气候因子进行相关性分析,结果表明:10 a来神农架林区植被覆盖整体呈增加趋势,且东部地区的EVI增幅大于西部增幅,特别是近5 a(2008-2012年),除2010年外,植被指数均为正距平.说明神农架林区近5 a来植被生长状况较好,生态环境得到了进一步改善.与气候因子进行相关性分析说明,气温是制约神农架植被生长的主要气候因子,而降水和日照是影响该地区植被生长的重要气候因子.  相似文献   

2012年桂西北一次地面人工增雨作业天气条件的分析和捕捉     

何飞  刘丽君  黄晓辉  张正国 《气象研究与应用》2013,34(1):55-59

以百色市田林县一次降雨过程的人工增雨作业天气和作业实况作为研究对象,对相应天气形势和物理量场进行剖析并对增雨效果进行检验。得出:在短波槽、切变线和弱冷空气为主的中低层天气系统影响下,低层水汽充足,上升运动的加剧及弱冷空气的入侵可激发降雨的产生;在降雨初期对液水含量大,冰晶含量偏低的冷云及时进行人工催化作业,可收到明显的增雨效果。  相似文献   

2018年春季长江流域上游降水异常特征及历史相似性分析     

高雅琦  杜良敏  郭广芬 《气象与环境科学》2020,43(3):78-83

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红壤旱地棉田间作小气候效应初步研究   总被引：2，自引：0，他引：2       下载免费PDF全文

崔爱花  杜传莉  黄国勤 《气象与减灾研究》2016,39(4):290-294

为研究棉田间作对田间小气候的影响,共设置4个处理:棉花单作、棉花间作花生、棉花间作甘薯、棉花间作大豆,研究不同间作棉田群体对不同层次的光强、土壤温度以及棉花农艺性状及产量的影响。结果表明,与棉花单作系统相比,间作系统可通过改变受光结构、土壤温度、土壤含水量等促进棉花生长发育,利于棉花种植获得高产;棉花间作大豆模式是较适宜在红壤旱地推广的间作模式。  相似文献   

Preliminary Calibration of GPS Signals and Its Effects on Soil Moisture Estimation   总被引：1，自引：0，他引：1       下载免费PDF全文

WAN Wei  LI Huang  CHEN Xiuwan  LUO Peng  WAN Jiahuan 《Acta Meteorologica Sinica》2013,27(2):221-232

In recent years, Global Navigation Satellite Systems Reflectometry (GNSS-R) is developed to estimate soil moisture content (SMC) as a new remote sensing tool. Signal error of Global Positioning System (GPS) bistatic radar is an important factor that affects the accuracy of SMC estimation. In this paper, two methods of GPS signal calibration involving both the direct and reflected signals are introduced, and a detailed explanation of the theoretical basis for such methods is given. An improved SMC estimation model utilizing calibrated GPS L-band signals is proposed, and the estimation accuracy is validated using the airborne GPS data from the Soil Moisture Experiment in 2002 (SMEX02). We choose 21 sites with soybean and corn in the Walnut Creek region of the US for validation. The sites are divided into three categories according to their vegetation cover: bare soil, mid-vegetation cover (Mid-Veg), and high-vegetation cover (High-Veg). The accuracy of SMC estimation is 11.17% for bare soil and 8.12% for Mid-Veg sites, much better than that of the traditional model. For High-Veg sites, the effect of signal attenuation due to vegetation cover is preliminarily taken into consideration and a linear model related to Normalized Difference Vegetation Indices (NDVI) is adopted to obtain a factor for rectifying the "over-calibration", and the error for High-Veg sites is finally reduced to 3.81%.  相似文献   

Development of climate change projections for small watersheds using multi-model ensemble simulation and stochastic weather generation   总被引：1，自引：0，他引：1  

Hua Zhang  Guo H. Huang 《Climate Dynamics》2013,40(3-4):805-821

Regional climate models (RCMs) have been increasingly used for climate change studies at the watershed scale. However, their performance is strongly dependent upon their driving conditions, internal parameterizations and domain configurations. Also, the spatial resolution of RCMs often exceeds the scales of small watersheds. This study developed a two-step downscaling method to generate climate change projections for small watersheds through combining a weighted multi-RCM ensemble and a stochastic weather generator. The ensemble was built on a set of five model performance metrics and generated regional patterns of climate change as monthly shift terms. The stochastic weather generator then incorporated these shift terms into observed climate normals and produced synthetic future weather series at the watershed scale. This method was applied to the Assiniboia area in southern Saskatchewan, Canada. The ensemble led to reduced biases in temperature and precipitation projections through properly emphasizing models with good performance. Projection of precipitation occurrence was particularly improved through introducing a weight-based probability threshold. The ensemble-derived climate change scenario was well reproduced as local daily weather series by the stochastic weather generator. The proposed combination of dynamical downscaling and statistical downscaling can improve the reliability and resolution of future climate projection for small prairie watersheds. It is also an efficient solution to produce alternative series of daily weather conditions that are important inputs for examining watershed responses to climate change and associated uncertainties.  相似文献   

The activity of convectively coupled equatorial waves in CMIP3 global climate models     

Ping Huang  Chia Chou  Ronghui Huang 《Theoretical and Applied Climatology》2013,112(3-4):697-711

This study evaluates the convectively coupled equatorial waves in ten coupled general circulation models (GCMs) in the twentieth century experiment from the Coupled Model Intercomparison Project phase 3 of the World Climate Research Programme. The antisymmetric bands in all GCMs are weaker than in observations, and the mixed Rossby-gravity (MRG) wave seems to be a mixture of the equatorial Rossby (ER) and tropical depression-type (TD-type) waves rather than a mixture of the ER and inertiogravity waves found in observations. The simulated TD-type wave is more organized than in observations with a quasilinear wavenumber–frequency relationship. In most GCMs, the two observed activity centers of the MRG and TD-type waves over the southern Indian Ocean and the southwestern Pacific cannot be separated; only one wave activity center is found over the Maritime Continent. The observed northwestward propagation of the TD-type wave over the western North Pacific is also not well simulated in the GCMs. The simulated active season of the MRG and TD-type waves over the northern hemisphere during the boreal summer and fall is much shorter than in observations. The models from CCSR utilizing the Pan and Randall scheme with the convection suppression simulate the realistic Kelvin wave activity with the maximum activity near the equator, while the wave activities filtered for the Kelvin wave in the other GCMs are similar to the extratropical Rossby wave with the maximum activity at higher latitudes. Likewise, only these two models produce a realistic seasonal cycle of the Kelvin wave activity.  相似文献   

Balance characteristics of multivariate background error covariances and their impact on analyses and forecasts in tropical and Arctic regions   总被引：4，自引：0，他引：4  

Yaodeng Chen  Syed R. H. Rizvi  Xiang-Yu Huang  Jinzhong Min  Xin Zhang 《Meteorology and Atmospheric Physics》2013,121(1-2):79-98

For variational data assimilation, the background error covariance matrix plays a crucial role because it is strongly linked with the local meteorological features, and is especially dominated by error correlations between different analysis variables. Multivariate background error (MBE) statistics have been generated for two regions, namely the Tropics (covering Indonesia and its neighborhood) and the Arctic (covering high latitudes). Detailed investigation has been carried out for these MBE statistics to understand the physical processes leading to the balance (defined by the forecasts error correlations) characteristics between mass and wind fields for the low and high latitudes represented by these two regions. It is found that in tropical regions, the unbalanced (full balanced) part of the velocity potential (divergent part of wind) contributes more to the balanced part of the temperature, relative humidity, and surface pressure fields as compared with the stream function (rotational part of wind). However, the exact opposite happens in the Arctic. For both regions, the unbalanced part of the temperature field is the main contributor to the balanced part of the relative humidity field. Results of single observation tests and six-hourly data assimilation cycling experiments are consistent with the respective balance part contributions of different fields in the two regions. This study provides an understanding of the contrasting dynamical balance relationship that exists between the mass and wind fields in high- and low-latitude regions. The study also examines the impact of MBE on Weather Research and Forecasting model forecasts for the two regions.  相似文献   

Improved reliability of ENSO hindcasts with multi-ocean analyses ensemble initialization     

Jieshun Zhu  Bohua Huang  Magdalena A. Balmaseda  James L. Kinter III  Peitao Peng  Zeng-Zhen Hu  Lawrence Marx 《Climate Dynamics》2013,41(9-10):2785-2795

Currently, ensemble seasonal forecasts using a single model with multiple perturbed initial conditions generally suffer from an “overconfidence” problem, i.e., the ensemble evolves such that the spread among members is small, compared to the magnitude of the mean error. This has motivated the use of a multi-model ensemble (MME), a technique that aims at sampling the structural uncertainty in the forecasting system. Here we investigate how the structural uncertainty in the ocean initial conditions impacts the reliability in seasonal forecasts, by using a new ensemble generation method to be referred to as the multiple-ocean analysis ensemble (MAE) initialization. In the MAE method, multiple ocean analyses are used to build an ensemble of ocean initial states, thus sampling structural uncertainties in oceanic initial conditions (OIC) originating from errors in the ocean model, the forcing flux, and the measurements, especially in areas and times of insufficient observations, as well as from the dependence on data assimilation methods. The merit of MAE initialization is demonstrated by the improved El Niño and the Southern Oscillation (ENSO) forecasting reliability. In particular, compared with the atmospheric perturbation or lagged ensemble approaches, the MAE initialization more effectively enhances ensemble dispersion in ENSO forecasting. A quantitative probabilistic measure of reliability also indicates that the MAE method performs better in forecasting all three (warm, neutral and cold) categories of ENSO events. In addition to improving seasonal forecasts, the MAE strategy may be used to identify the characteristics of the current structural uncertainty and as guidance for improving the observational network and assimilation strategy. Moreover, although the MAE method is not expected to totally correct the overconfidence of seasonal forecasts, our results demonstrate that OIC uncertainty is one of the major sources of forecast overconfidence, and suggest that the MAE is an essential component of an MME system.  相似文献