检索结果-南通市图书馆

Comprehensive Marine Observing Experiment Based on High-Altitude Large Unmanned Aerial Vehicle(South china Sea Experiment2020 of the “Petrel project”)

在线全文

学校读者我要写书评

暂无评论

Advances in Atmospheric Sciences 2021年第4期38卷 531-537页

作者： Xuefen ZHANG Liangxu LI Rongkang YANG Ran GUO Xia SUN Jianping LUO Hongbin CHEN Daxin LIU Kebing TANG Wenwu PENG Xiaodong HAN Qiyun GUO Xiaoxia LI Xikun FEI meteorological Observation Center of the china meteorological administration Beijing 10081China AVIC Chengdou Aircraft Industry(Group)Co. Ltd.Chengdou 610092China Hainan Provincial meteorological Bureau of the china meteorological administration Hainan 570203China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Beijing Institute of Radio Measurement China Aerospace Science and IndustryCorporationBeijing 100854China AVIC Leihua Electric technology Research Institute Wuxi 421063China

In collaboration with 12 other institutions, the meteorological Observation Center of the china meteorological administration undertook a comprehensive marine observation experiment in the South china Sea using the Yilong-10 high-altitude large unmanned aerial vehicle(UAV). The Yilong-10 UAV carried a self-developed dropsonde system and a millimeter-wave cloud radar system. In addition, a solar-powered unmanned surface vessel and two drifting buoys were used. The experiment was further supported by an intelligent, reciprocating horizontal drifting radiosonde system that was deployed from the Sansha meteorological Observing Station, with the intent of producing a stereoscopic observation over the South china Sea. Comprehensive three-dimensional observations were collected using the system from 31 July to2 August, 2020. This information was used to investigate the formation and development processes of Typhoon Sinlaku(2020). The data contain measurements of 21 oceanic and meteorological parameters acquired by the five devices, along with video footage from the UAV. The data proved very helpful in determining the actual location and intensity of Typhoon Sinlaku(2020). The experiment demonstrates the feasibility of using a high-altitude, large UAV to fill in the gaps between operational meteorological observations of marine areas and typhoons near china, and marks a milestone for the use of such data for analyzing the structure and impact of a typhoon in the South china Sea. It also demonstrates the potential for establishing operational UAV meteorological observing systems in the future, and the assimilation of such data into numerical weather prediction models.

关键词： high-altitude large UAV marine typhoon unmanned surface vessel horizontal drifting radiosonde drifting buoy

High-Resolution Mesoscale Analysis Data from the South china Heavy Rainfall Experiment （SCHeREX）： Data Generation and Quality Evaluation

在线全文

学校读者我要写书评

暂无评论

Acta meteorologica Sinica 2011年第4期25卷 478-493页

作者： NI Yunqi CUI Chunguang LI Hongli PENG Juxiang QIU Xuexing ZHANG Yanxia XU Xiaolin GAO Mei JIE Lianshu ZHANG Wenhua Chinese Academy of meteorological Sciences China Meteorological Administration （CMA） Beijing 100081 Wuhan Institute of Heavy Rain CMA Wuhan 430074 Guangzhou Institute of Tropical and Marine Meteorology CMA Guangzhou 510080 Anhui meteorological Observatory Hefei 230031 Shanghai Typhoon Institute CMA Shanghai 230030

In this study, the observational data acquired in the South china Heavy Rainfall Experiment （SCHeREX） from May to July 2008 and 2009 were integrated and assimilated with the US National Oceanic and Atmospheric administration＇s （NOAA） Local Analysis and Prediction System （LAPS; information available online at http：//***）. A high-resolution mesoscale analysis dataset was then generated at a spatial resolution of 5 km and a temporal resolution of 3 h in four observational areas： South china, Central china, Jianghuai area, and Yangtze River Delta area. The quality of this dataset was evaluated as follows. First, the dataset was qualitatively compared with radar reflectivity and TBB image for specific heavy rainfall events so as to examine its capability in reproduction of mesoscale systems. The results show that the SCHeREX analysis dataset has a strong capability in capturing severe mesoscale convective systems. Second, the mean deviation and root mean square error of the SCHeREX mesoscale analysis fields were analyzed and compared with radiosonde data. The results reveal that the errors of geopotential height, temperature, relative humidity, and wind of the SCHeREX analysis were within the acceptable range of observation errors. In particular, the average error was 45 m for geopotential height between 700 and 925 hPa, 1.0-1.1°C for temperature, less than 20% for relative humidity, 1.5-2.0 m s-1 for wind speed, and 20-25° for wind direction. The above results clearly indicate that the SCHeREX mesoscale analysis dataset is of high quality and sufficient reliability, and it is applicable to refined mesoscale weather studies.

关键词： diagnostic analysis integration and assimilation applicability quality evaluation

A STUDY ON THE IMPACTS OF LATENT HEAT PARAMETERIZATION SCHEME ON PREDICTION SKILL OF ENSO WITH A SIMPLE OCEAN-ATMOSPHERE COUPLED MODEL

在线全文

学校读者我要写书评

暂无评论

Journal of Tropical Meteorology 2010年第1期16卷 10-19页

作者：岳彩军陆维松李小凡 Shanghai Typhoon Institute of the china meteorological administration Laboratory of Typhoon Forecast Technique/CMA School of Atmospheric Sciences Nanjing University of Information Science and Technology Joint Center for Satellite Data Assimilation and NOAA/NESDIS/Center for Satellite Applications and Research Camp Springs

This study revises Weare＇s latent heat parameterization scheme and conducts an associated theoretic analysis. The revised Weare＇s scheme is found to present potentially better results than Zebiak＇s scheme. The Zebiak-Cane coupled ocean-atmosphere model, initialized by the National Centers for Environmental Prediction and the National Center for Atmospheric Research （NCEP/NCAR） reanalysis of wind stress anomaly at 925 hPa, is referred to as the ZCW coupled model. The atmosphere models of the ZCW coupled model that use Zebiak＇s scheme and the revised Weare＇s scheme are referred to as the ZCW0 and ZCWN atmosphere models, respectively. The coupled ocean-atmosphere models that use Zebiak＇s scheme and the revised Weare＇s scheme are referred to as the ZCWoand ZCWN coupled models, respectively. The simulations between the ZCW0 and ZCWN atmosphere models and between the ZCW0 and ZCWN coupled models are analyzed. The results include：（1） The evolution of heat, meridional wind and divergence anomalies simulated by similar ZCW0 and ZCWN atmosphere models, although the magnitudes of the former are larger than those of the latter; （2） The prediction skill of the Nino3 index from 1982 to 1999 by the ZCWN coupled model shows improvement compared with those by the ZCW0 coupled model; （3） The analysis of E1 Nino events in 1982/1983, 1986/1987, and 1997/1998 and La Nifia events in 1984/1985, 1988/1989, and 1998/2000 suggests that the ZCWN coupled model is better than the ZCW0 coupled model in predicting warm event evolution and cold event generation. The results also show the disadvantage of the ZCWN coupled model for predicting E1 Nino.

关键词： Zebiak-Cane ocean-atmosphere coupled model ENSO latent heat parameterization scheme

NUMERICAL MODELING STUDY OF EFFECTS OF EASTERN PACIFIC WARM POOL ON ENSO

在线全文

学校读者我要写书评

暂无评论

Journal of Tropical Meteorology 2010年第4期16卷 355-362页

In this study, sensitivity experiments were conducted with the Zebiak-Cane ocean-atmosphere coupled model forced by the wind stress anomaly from the U.S. National Centers for Environmental Prediction/National Center for Atmospheric Research （NCEP/NCAR） reanalysis data to study the impacts of eastern Pacific warm pool on the formation and development of ENSO events. The effects of climatological mean sea surface temperature of the warm pool on forecast skill during the ENSO events of 1982-1999 are more considerable that those of climatological mean meridional winds and ocean currents. The forecast skill for the 1997/1998 E1 Nifio event is characterized by sensitivity to climatological mean sea surface temperature and anomalies of northerly winds and currents. The forecast skill is found insensitive to climatological mean northerly meridional winds and currents.

关键词： eastern Pacific warm pool ENSO event Zebiak-Cane ocean-atmosphere coupled model sensitivity experiments

Regional Integrated meteorological Forecasting and Warning Model for Geological Hazards Based on Logistic Regression

在线全文

学校读者我要写书评

暂无评论

Wuhan University Journal of Natural Sciences 2007年第4期12卷 638-644页

作者： XU Jing YANG Chi ZHANG Guoping Chinese Academy of meteorological Sciences Beijing 100081 China National meteorological Centre China Meteorological Administration Beijing 100081 China College of Water Sciences Beijing Normal University Beijing 100875 China

Information model is adopted to integrate factors of various geosciences to estimate the susceptibility of geological hazards. Further combining the dynamic rainfall observations, Logistic regression is used for modeling the probabilities of geological hazard occurrences, upon which hierarchical warnings for rainfall-induced geological hazards are produced. The forecasting and warning model takes numerical precipitation forecasts on grid points as its dynamic input, forecasts the probabilities of geological hazard occurrences on the same grid, and translates the results into likelihoods in the form of a 5-level hierarchy. Validation of the model with observational data for the year 2004 shows that 80% of the geological hazards of the year have been identified as ＂likely enough to release warning messages＂. The model can satisfy the requirements of an operational warning system, thus is an effective way to improve the meteorological warnings for geological hazards.

关键词： geological hazard information model Logistic regression rainfall spatial analysis

Ensemble Prediction of Monsoon Index with a Genetic Neural Network Model

在线全文

学校读者我要写书评

暂无评论

Acta meteorologica Sinica 2009年第6期23卷 701-712页

作者：姚才金龙赵华生 Department of Atmospheric Sciences School of PhysicsPeking University Guangxi meteorological administration Guangxi Climate Center

After the consideration of the nonlinear nature changes of monsoon index,and the subjective determination of network structure in traditional artificial neural network prediction modeling,monthly and seasonal monsoon intensity index prediction is studied in this paper by using nonlinear genetic neural network ensemble prediction（GNNEP）*** differs from traditional prediction modeling in the following aspects：（1）Input factors of the GNNEP model of monsoon index were selected from a large quantity of preceding period high correlation factors,such as monthly sea temperature fields,monthly 500-hPa air temperature fields,monthly 200-hPa geopotential height fields,etc.,and they were also highly information-condensed and system dimensionality-reduced by using the empirical orthogonal function（EOF）method,which effectively condensed the useful information of predictors and therefore controlled the size of network structure of the GNNEP model.（2）In the input design of the GNNEP model,a mean generating function（MGF）series of predictand（monsoon index）was added as an input factor;the contrast analysis of results of predic- tion experiments by a physical variable predictor-predictand MGF GNNEP model and a physical variable predictor GNNEP model shows that the incorporation of the periodical variation of predictand（monsoon index）is very effective in improving the prediction of monsoon index.（3）Different from the traditional neural network modeling,the GNNEP modeling is able to objectively determine the network structure of the GNNNEP model,and the model constructed has a better generalization *** the case of identical predictors,prediction modeling samples,and independent prediction samples,the prediction accuracy of our GNNEP model combined with the system dimensionality reduction technique of predictors is clearly higher than that of the traditional stepwise regression model using the traditional treatment technique of predictors,suggesting that the GNNEP model

关键词： monsoon index ensemble prediction genetic algorithm neural network mean generating function

A STUDY OF PARTITIONING Q VECTOR ON BACKGROUND CONDITIONS OF A TORRENTIAL RAINFALL OVER SHANGHAI,china ON 25 AUGUST 2008

在线全文

学校读者我要写书评

暂无评论

Journal of Tropical Meteorology 2011年第3期17卷 231-247页

作者：岳彩军鲁小琴李小凡宗志平 Shanghai Typhoon Institute of the china meteorological administration Laboratory of Typhoon Forecast Technique/CMA Joint Center for Satellite Data Assimilation and NOAA/NESDIS/Center for Satellite Applications and Research Camp Springs National meteorological Center of CMA

A rainfall that occurred during 0200–1400 Beijing Standard Time(BST)25 August 2008 shows the rapid development of a convective system,a short life span,and a record rate of 117.5 mm h-1for Xujiahui station since *** study this torrential rainfall process,the partitioning method of Q vector is developed,in which a moist Q vector is first separated into a dry ageostrophic Q vector(DQ)and a diabatic-heating *** dry ageostrophic Q vector is further partitioned along isothermal lines in the natural coordinate to identify different scale forcing in adiabatic atmosphere,and the large-scale and convective condensational heating in non-uniform saturated atmosphere,convective condensational heating, and Laplace of diabatic heating that includes radiative heating and other heating and cooling processes,are calculated to study the forcing from diabatic *** effects of the environmental conditions on the development of the rainfall processes are diagnosed by performing the partitioning of Q vector based on 6-hourly NCEP/NCAR Final Analysis(FNL)data with the horizontal resolution of 1°×1°.The results include the following:(1)a low-pressure inverted trough associated with the landfall of Typhoon Nuri (2008),a strong southwesterly jet along the western side of the subtropical high,and an eastward-propagating westerly low-pressure trough provide favorable synoptic conditions for the development of torrential rainfall;(2)the analysis of DQ vector showed that the upward motions forced by the convergence of DQ vector in the lower troposphere(1000–600 hPa)favor the development of torrential *** DQ vector converges in the upper troposphere(500–100 hPa),upward motions in the whole air column intensify significantly to accelerate the development of torrential rainfall;(3)the partitioning analysis of DQ vector reveals that large-scale forcing persistently favors the development of torrential rainfall whereas the mesoscale forcing speeds up the torrential rainf

关键词： background conditions of torrential rainfall partitioning of Q vector dry ageostrophic Q vector diabatic heating

china land soil moisture EnKF data assimilation based on satellite remote sensing data

在线全文

学校读者我要写书评

暂无评论

Science china Earth Sciences 2011年第9期54卷 1430-1440页

作者： SHI ChunXiang XIE ZhengHui QIAN Hui LIANG MiaoLing YANG XiaoChun National Satellite meteorological Center China Meteorological Administration Beijing 100081 China Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China Institute of Geology Chinese Academy of Geological Sciences Key Geodynamics Laboratory the Ministry of Land and Resources Beijing 100037 China National meteorological Center China Meteorological Administration Beijing 100081 China

Soil moisture plays an important role in land-atmosphere interactions. It is an important geophysical parameter in research on climate, hydrology, agriculture, and forestry. Soil moisture has important climatic effects by influencing ground evapotranspi ration, runoff, surface reflectivity, surface emissivity, surface sensible heat and latent heat flux. At the global scale, the extent of its influence on the atmosphere is second only to that of sea surface temperature. At the terrestrial scale, its influence is even greater than that of sea surface temperatures. This paper presents a china Land Soil Moisture Data Assimilation System (CLSMDAS) based on EnKF and land process models, and results of the application of this system in the china Land Soil Moisture Data Assimilation tests. CLSMDAS is comprised of the following components: 1) A land process mo del—Community Land Model Version 3.0 (CLM3.0)—developed by the US National Center for Atmospheric Research (NCAR); 2) Precipitation of atmospheric forcing data and surface-incident solar radiation data come from hourly outputs of the FY2 geostationary meteorological satellite; 3) EnKF (Ensemble Kalman Filter) land data assimilation method; and 4) Observa tion data including satellite-inverted soil moisture outputs of the AMSR-E satellite and soil moisture observation data. Results of soil moisture assimilation tests from June to September 2006 were analyzed with CLSMDAS. Both simulation and assimila tion results of the land model reflected reasonably the temporal-spatial distribution of soil moisture. The assimilated soil mois ture distribution matches very well with severe summer droughts in Chongqing and Sichuan Province in August 2006, the worst since the foundation of the People’s Republic of china in 1949. It also matches drought regions that occurred in eastern Hubei and southern Guangxi in September.

关键词： EnKF land data assimilation AMSR-E soil moisture FY2C geostationary satellite high-resolution precipitation surface incident solar radiation

IAP's Solar-Powered Unmanned Surface Vehicle Actively Passes through the Center of typhoon Sinlaku(2020)

在线全文

学校读者我要写书评

暂无评论

Advances in Atmospheric Sciences 2021年第4期38卷 538-545页

作者： Hongbin CHEN Jun LI Wenying HE Shuqing MA Yingzhi WEI Jidong PAN Yu ZHAO Xuefen ZHANG Shuzhen HU Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric PhysicChinese Academy of SciencesBeijing 100029China The School of Earth Science Chinese Academy of Science UniversityBeijing 100049China Collaborative Innovation Center on Forecast and Evaluation of meteorological Disasters Nanjing University of Information Science and TechnologyNanjing 210044China meteorological Observation Center of the china meteorological administration Beijing 100081China Xiamen meteorological Service Xiamen 361013China

The solar-powered marine unmanned surface vehicle(USV) developed by the USV team of the Institute of Atmospheric Physics is a rugged, long-duration, and autonomous navigation vessel designed for the collection of longrange, continuous, real-time, meteorological and oceanographic measurements, especially under extreme sea conditions(sea state 6–7). These solar-powered USVs completed a long-term continuous navigation observation test over 26 *** this time, they coordinated double-USV observations and actively navigated into the path of Typhoon Sinlaku(2020) before collecting data very close to its center during the 2020 USV South china Sea Typhoon Observation Experiment. Detailed high temporal resolution(1 min) real-time observations collected by the USV on the typhoon were used for operational typhoon forecasting and warning for the first time. As a mobile meteorological and oceanographic observation station capable of reliable, automated deployment, data collection, and transmission, such solar-powered USVs can replace traditional observation platforms to provide valuable real-time data for research, forecasting, and early warnings for potential marine meteorological disasters.

关键词： solar-powered unmanned surface vehicle typhoon meteorological and oceanographic observation