应用气象学报

2015, 26(5)

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Abstract:

A Particle Swarm Optimization-neural Network Ensemble Prediction Model for Persistent Freezing Rain and Snow Storm in Southern China

Lu Hong, Zhai Panmao, Qin Weijian, Jin Long, Xie Min, Qian Xi, Zhao Huasheng

2015, 26(5): 513-524. DOI: 10.11898/1001-7313.20150501

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Abstract:
Based on daily minimum temperature, maximum temperature and precipitation data of 756 stations in China, National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis data during 1951-2013 and NCEP 24 h forecast data, a nonlinear statistical ensemble prediction model based on the particle swarm optimization-neural network (PSONN-EPM) is developed for predicting and verifying the regional persistent freezing rain and snow storm process in southern China by analyzing and extracting significant predictors. Results show that model performance can be effectively improved when dividing low-temperature processes into the general process and severe process which are constructed based on cold extents, humidity and influence ranges of the freezing rain and snow storm processes. In 10-day independent forecast test, the average relative errors for the general process and the severe process are 2.04 and 0.6 using stepwise regression equation forecast method, while those are 1.33 and 0.30 by using PSONN-EPM technique. It means forecast errors are reduced by 0.71 and 0.3 as compared with the stepwise regression method. In addition, the predication result for the severe freezing rain and snow storm process is better than that for the general process. The PSONN-EPM integrates predictions of multiple ensemble members, thus the prediction accuracy and stability are higher than those of the traditional linear regression method. Furthermore, such method does not contain any tunable parameters, and is applicable for practical operational weather prediction.

Anomalous Moisture and Temperature Characteristics in Precipitation Process During January 2008 Heavy Snowstorm in China

Chen Hongxing, Chen Yun, Lu Er, Li Hui

2015, 26(5): 525-535. DOI: 10.11898/1001-7313.20150502

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Abstract:
The severe cryogenic freezing rain and snow disastrous weather occurrs in central-southern China from 10 Jan to 2 Feb in 2008, which lasts for nearly a month, causes huge social and economic impacts. The water vapor supply and the cold air surges of this disaster are investigated, and their effects on the formation of the heavy snowstorm are performed. The abnormality of the atmospheric circulation is that the blocking high remains stable in high latitudes of the Northern Hemisphere, the western Pacific subtropical high is more north than normal and the south branch trough is active. In this process, cold air continuously transports from north to central-southern China, forming a high isentropic potential vorticity center. At the same time, there is also strong water vapor continuously transports to north, the integrated water vapor is more than normal in the central-southern China, but at 850 hPa and levels below, the moisture is less. At different levels, anomalous temperature and moisture are different. From low layer to high layer, the air temperature change from abnormally low to abnormally high. The moisture increases and turns into more than normal at 700 hPa. Some methods are defined to examine whether moisture and temperature both play positive roles in this event. Results indicate that at 850 hPa and levels below, although warm and moist air transport from the south, dry and cold air transport from the north is very strong, so the abnormally low air temperature caused by the cold air surges dominates the abnormally high relative humility, and the precipitation is more than normal, resulting in less moisture is less than normal, but this negative effect is weaker than the positive effect of abnormally lower air temperature. On the contrary, at 600 hPa and levels above, although the dry cold air transport from north, the warm and wet air from south is very strong, the abnormally more water vapor dominates the heavy precipitation, the air temperature is warmer than normal, and it has a negative effect at 700 hPa, the result of the blend of the warm and moist air from the south with the dry and cold air from the north is that the air over the central-southern China is moister while colder than normal. They both have positive contributions to the heavy snowstorm. It shows from calculation that at this level, the moistness of the air contributes more than the coldness of the air.

The Influence of Sea Surface Temperature Anomaly on the East Asian Summer Monsoon Strength and Its Precursor

Ke Zongjian, Hua Lijuan, Zhong Linhao, Du Liangmin

2015, 26(5): 536-544. DOI: 10.11898/1001-7313.20150503

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Abstract:
The strength of the East Asian Summer Monsoon (EASM) is closely connected to the summer main rainfall belt in China. The precursor index defined by the difference of zonal wind anomaly at 200 hPa between the middle latitude in Asia and eastern Pacific in February is well indicative to the strength of EASM, which is an important predicting factors in flood season. The potential mechanism of precursor signal influencing the EASM is proposed by changing the surface characteristics in South Asia continent, but it is unclear whether the atmospheric circulation anomaly in February persists in the following seasons over middle latitude region.In addition, a further investigation is needed about the surface anomaly variation over South Asia in winter-spring seasons. ERA-Interim reanalysis data, NOAA sea surface data, gridded CMAP precipitation data and precipitation observations over China are used. By composite, correlation and regression analysis approaches, the difference of wind in middle latitude over Eurasia, sea surface temperature (SST) in tropics and thermal condition in South Asia continent in previous winter-spring seasons in various strength EASM years are analyzed. Results indicate that tropical SST is the physical connection of accordant variations between the strength of EASM and its precursor.Results show that the precursor signal of EASM captures the primary feature for the first mode of empirical orthogonal function (EOF1) of zonal wind anomaly at 200 hPa over the Asia and Pacific in February. The EOF1 mode is related to SST in the central and eastern Pacific. In the previous winter, the SST is below (above) normal in the central and eastern Pacific, which is conducive to a northward (southward) shift of westerly jet over the Asia in February. The zonal wind anomaly at 200 hPa exhibits meridional positive-negative-positive (negative-positive-negative) pattern, and the precursor index is stronger (weaker) than normal. In summer, the negative (positive) SST anomaly occurs in the vicinity of Indian Ocean and South China Sea, which results in an increasing (decreasing) difference between ocean and land and stronger (weaker) Indian Summer Monsoon. Meanwhile, the western Pacific subtropical high (WPSH) is weaker (stronger) than normal, and the EASM is stronger (weaker) than normal.The anomalous feature of zonal wind in the middle latitude of the Asia in February is hardly to persist in spring. The physical connection between EASM and its precursor mainly derives from the tropical ocean.

Spatiotemporal Variability of Heat Waves in Beijing-Tianjin-Hebei Region and Influencing Factors in Recent 54 Years

Li Shuangshuang, Yang Saini, Zhang Donghai, Liu Xianfeng

2015, 26(5): 545-554. DOI: 10.11898/1001-7313.20150504

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Abstract:

It indicates that hot summers will become more frequent in eastern China in the future. The region will face a great risk in the absence of any adaptation measures taken towards reducing its vulnerability to effects of extreme heat. Beijing-Tianjin-Hebei Region is identified as the biggest metropolitan in northern China. Rapid urbanization and the recent frequent occurrence of hot summers in the region raises questions about influencing factors at the regional scale and the spatiotemporal variability of heat waves. Using the newly developed Heatwave Index (HI), a statistical analysis is conducted on the temporal and spatial distribution characteristics of heat waves in Beijing-Tianjin-Hebei Region over a period from 1960 to 2013. More specifically, based on the history of relocations, the heat wave trends between Beijing and Fengning is compared to investigate the influence of urbanization, and also analyse the relationship between atmospheric circulation anomalies and observed heat wave trends. It shows that based on variations in heat wave trends, two distinct phases are identified in Beijing-Tianjin-Hebei Region. Owing to some abrupt changes in the mid-1970s, the frequency of heat waves decrease from 1960 to 1973, and then increase from 1974 to 2013. Heat waves show a decreasing trend in the southern part and an increasing trend in the northern part of Beijing-Tianjin-Hebei Region. A significant increasing trend is found in the northern and western biological conservation area, and decreasing trend in south-eastern plains. At the regional scale, urbanization and relocations affect the occurrence of slight to moderate rather than extreme heat waves. In the period of global warming and rapid urbanization, the frequency of heat waves in Beijing is higher than that of Fengning. In recent global warming hiatus, the frequency of heat waves in Beijing is lower than Fengning. Driving factors behind temporal and spatial patterns are deemed complicated. The inter-decadal variations are significantly and closely related to the offsetting of western Pacific subtropical high (WPSH) ridge and the anomalous anticyclone over the Tibetan Plateau (TPAI) in summer. In other words, there is a positive correlation between the number of heat wave days and WPSH and TPAI. Furthermore, the probability of a summer with a mega-heat wave would increase with the anomalies in WPSH and TPAI.

Impacts of Doppler Radar Data Assimilation on the Simulation of Severe Heavy Rainfall Events

Zhang Xinzhong, Chen Junming, Zhao Ping

2015, 26(5): 555-566. DOI: 10.11898/1001-7313.20150505

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Abstract:
The impact of Doppler weather radar (DWR) data on the simulation of a heavy rainfall event is examined. The quality control algorithm of DWR developed by Center for Analysis and Prediction of Storms is applied and the threshold for the raw S-band DWR radial velocity is decided. Several commonly seen non-meteorological returns can be removed effectively. The DWR reflectivity data are processed and the regional three-dimensional mosaic is generated using the CINRAD 3D Digital Mosaic System developed by State Key Laboratory of Severe Weather. Retrieval results match well with the observation. The Gridpoint Statistical Interpolation System (GSI) and the Weather Research and forecasting Model version 3.5.1 (WRF) are used to assimilate 46 S-band DWR data to simulate the severe heavy rain cases that occurred in Jun 2013. Numerical experiment results show that about 90% of the radial velocity data after quality control can be assimilated and generate reasonable analysis increments. Results also show that the assimilation of DWR data has a positive impact on the simulation of heavy rainfall. Assimilating radial velocity can enhance the information of mesoscale weather system in initial field and the simulated field, making the simulated wind fields and rainfall location more similar to the observation. Radar reflectivity data are used primarily in a cloud analysis that retrieves the amount of hydrometeors and adjusts in-cloud temperature and moisture. Assimilating radial velocity affects the zonal and vertical winds by adjusting the amount of hydrometers and moisture which have directly influence on generating precipitation. It changes the simulated rainfall intensity. Assimilating radial velocity and reflectivity at the same time can not only reflect the wind filed more reasonably, but also improve the simulation of rainfall intensity and area. In addition, improvements of the precipitation are most notable in the 12-36 h simulation when more effective radar data are available. Both ETS and HSS of experiment assimilating radar data are proved higher than CTRL experiment which only assimilates conventional data.

The Effect of Different Planetary Boundary Layer Schemes on the Simulation of Near Surface O₃ Vertical Distribution

Xu Jing, Ma Zhiqiang, Zhao Xiujuan, Zhang Xiaoling

2015, 26(5): 567-577. DOI: 10.11898/1001-7313.20150506

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Abstract:
Located at the base of the troposphere and affected strongly by ground surface, the planetary boundary layer (PBL) is the main passage of air-land interaction and air pollution. The PBL affects the momentum and heat exchange between the ground and atmosphere through the surface force and turbulence transport. The concentration of pollutants on the ground depends on the vertical mixing state of the atmosphere. Thus, the boundary layer parameterization scheme is not only the important part of numerical model for weather forecast, but also the important foundation of air pollution numerical model. A variety of boundary layer parameterization schemes of physical process are developed, which have different effects on the ground meteorological field and pollutant diffusion. To further understand how the boundary layer processes affect the mixing and transport of air pollutants, a sensitivity experiment is designed and the WRF-Chem model with different PBL schemes (MYJ, YSU and ACM2) is utilized to simulate the PBL structures and O₃ vertical distributions on a cloudless and steady day (26-27 Aug 2013). Simulations of temperature field and wind speed field using different PBL schemes are compared to observations. The analysis focuses on the difference of simulations of residual layer formation at night and O₃ vertical distribution after sunrise using different PBL schemes. Simulations are compared with the radiosonde data of ozone at Gucheng Station. Results show that the regional distribution characteristics and vertical structures of the temperature and wind speed can be well simulated by all these three PBL parameterization schemes, but the simulation of the ground temperature and wind speed are generally on the high side. The nighttime boundary layer height simulated by MYJ scheme is much higher than those simulated by YSU and ACM2 schemes, leading to the difference in near surface pollutants concentration. In the evolution process of the boundary layer structure from stable state in nighttime to slightly disturbance state after sunrise, the vertical temperature and wind structures simulated by YSU and ACM2 schemes are more consistent with observations. Simulations on effects of boundary layer process upon O₃ vertical distribution using YSU and ACM2 schemes also have obvious advantages over MYJ scheme. It should be noted that the simulation is only on a clear and steady weather case, and for complex weather conditions, effects of boundary layer schemes need further verification.

The Quality Control Method of Erroneous Radar Echo Data Generated by Hardware Fault

Zhao Ruijin, Liu Liping, Zhang Jin

2015, 26(5): 578-589. DOI: 10.11898/1001-7313.20150507

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Abstract:
Radar hardware fault affects data quality directly. Erroneous data not only affect local forecaster analyzing weather, but also have serious influence on the running of national operation system. So far, study on radar data quality control mainly aims at non-meteorological echoes, such as ground clutter, sea clutter, electromagnetic interference and so on. There isn't enough effective quality control method for erroneous data generated by hardware fault. Through analysis on the integrity of base data, position information and characteristic of hardware fault echoes, the correlation between erroneous data and fault category, and effects of different fault on data and echoes are studied. A quality control method is provided.Erroneous data generated by radar hardware fault affect integrity of base data, position and intensity information of echoes. There is some difference among different type hardware fault or part of radar. Transmitter and receiver system fault mainly affect the intensity information. Servo system fault mainly affect position information and the integrity of date. Through checking base data integrity and echoes position information, fault data generated by servo system can be identified.The radar intensity information affect image feature such as shape, range and intensity. The error intensity information data generated by radar hardware fault can be controlled through fuzzy-logical principle, and identified through comparing parameters such as radar echoes area, mean absolute difference of intensity, the degree of intensity change, and image correlation coefficient with neighboring normal data. There is some difference between different parts of radar or different kinds of hardware fault. It is impossible to identify all erroneous data only by one method. In the actual work, it is necessary to combine status and alarm information, and apply multiple means to check radar data step by step. Only in this way, erroneous data generated by hardware fault can be effectively and comprehensively controlled.A test on erroneous data generated by hardware fault of Shijiazhuang radar site from 2004 to 2013 is carried out, and the identification ratio is above 90%. It is supplement for the existing quality control methods which mainly aim at non-meteorological echoes when radar operate normally. The proposed algorithm is mainly based on the intensity and position information, and the quality control method on velocity and spectral width error generated by hardware fault should be further studied.

Data Auto-collection Based on Sound Level Characteristics for Weather Modification Operation by Ground-based Artillery Gun Shooting

Li Hongyu, Wang Hua, Jia Lijia, Hu Xiangfeng, Tao Yue, Wang Xiaobin

2015, 26(5): 590-599. DOI: 10.11898/1001-7313.20150508

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Abstract:
As an important task of weather service system, improving information technology on weather modification aircraft and ground operations and accurately collecting basic data from all kinds of operating equipment is an important element for operation management and decision making, as well as the basis for the scientific assessment of operating results. Currently, ground information management of weather modification operation generally follows earlier national rules of information collection and reporting. On one side, the collected information includes operating equipment, operating time, dosage and other basic information. A simple assessment is needed to evaluate the operation by combining comprehensive meteorological observations, making it difficult to ensure the timeliness of information reporting. On the other side, the operating information collected at ground enters the system typically by oral reports and hand typing, which limits the accuracy of the reported information. Thus it is difficult for the managing departments to know in-situ operating conditions, which directly limits operations of other services including security management. Improved data collecting methods are needed to overcome the bottleneck that data collection during weather modification operation relies on hand typing and the associated data security issues, and to improve the timeliness and accuracy of data collection. Based on mature technology, it is an effective way to collect operational data automatically through rebuilding operating instruments, and using in-situ operating sound, light or vibration features to trigger automatic responses of ground data operations. The way of using in-situ sound characteristics to trigger automatic responses to identify operating data from common-used artillery guns and rocket launchers also has a low cost and no security risk. In order to overcome the bottleneck, a new ground-level data acquisition and transmission device based on the acoustic technology are developed. Two experiments are carried out to collect sound level data of training shells and JD-07 type cloud seeding shells, respectively, which are shot from a 37 mm diameter, 65-type double-barreled artillery gun. This kind of artillery guns is widely used in weather modification throughout China. Results indicate that leading noise, sound level sharp jump and peak value yielded from the artillery gun shooting can act as a very effective index of data automatic collection during weather modification operation by artillery guns. Remarkable changes in the sound level of environmental noises inside the weather modification station can distinguish effectively the information on single or double-barreled and discontinuous or continuous gun shooting. Based on this, the shooting time and the shotted shells can be recorded automatically, accurately and in real time. The distance and position of the data acquisition and transmission device away from the artillery gun in the weather modification station have little effect on the accuracy of gun shooting data collection from sound level characteristics. As a significant mark of shell firing from the artillery gun, the leading noise recognition can be an important part of safe operation monitoring, playing an early warning role for major security incidents and their emergency treatment. Comparison of the sound level peak of each shell also helps to provide a visual reference for shell quality inspection. In addition, values of azimuth and elevation angles for each shell shooting can be calculated precisely based on the principle of time difference of arrival by arranging a sound sensing array. The accurate shooting position information can be collected automatically by integrating a GPS module.

Evaluation on the Random Error of Second Level Sounding Data

Yao Wen, Ma Ying

2015, 26(5): 600-609. DOI: 10.11898/1001-7313.20150509

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Abstract:
With the development of science and technology, the performance of sounding system, including the data acquisition rate, accuracy, reliability and automation are improved significantly. Comparison and statistical methods to estimate various errors are also needed to be improved. Relative system error and random error are concern variables of the sounding information users, errors evaluated by the reasonable method can reflect typical characteristics of error to same extent. So far, there have not a satisfactory standard radiosonde developed as a reference, relative system error and random error are obtained only through direct intercomparison simultaneously. The random error, it is not determined by dual-launching the same type of radiosondes because of the heavy workload. It is mainly used the indirect estimation method, that is the random error of the specify instrument used as a reference, and then the random error of unknown radiosonde is isolated from the variance between reference and unknown radiosondes. But whether the indirect calculation method of random error is suitable for the second level sounding data or not, the further discussion should be adopted. An overview of the random error is explained including the definition and determination method. And then two datasets are used to analyze the effect on the random error by different degree of data smoothing. One is the data of domestic GPS radiosondes comparison experiments in June 2007 and June-July 2008, the other dataset is the 8th WMO radiosonde comparison at Yangjiang China in 2010. The intercomparison analysis shows that the indirect calculation method of random error could not fully be applicable to the second level sounding data, especially for the estimation of random error of wind, temperature in stratospheric and relative humidity in tropospheric. The second level sounding data can detect the more detail caused by the swing of rising balloon, the raw data should be smoothed to reduce the impact of the above. If smoothing degrees of the original data compared are consistent, the indirect calculation method of random errors could be used suitably. The deviation is small, conversely, it might be problematical, which will produce large bias if it exists the difference in smoothing degree of the original data. In the scheme of direct intercomparision, in order to obtain the relative system error and random error of the different types of radiosonde systems, it is best to hang more than one of the same types of radiosonde in the same balloon to contrast synchronously, which can reduce the influence on evaluating the unknown radiosonde random error because of the own error of reference instrument. The more radiosondes of the same type are used, the more valid data could be obtained, the more accurate evaluation of random errors could be obtained.

The Application of Initiative Lightning Protection Technology Based on Lightning Nowcasting and Warning

Zeng Jinquan, Zhu Biao, Wang Yingbo, Zhang Yefang

2015, 26(5): 610-617. DOI: 10.11898/1001-7313.20150510

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Abstract:
Based on traditional passive lightning protection technology, an initiative of lightning protection technology is proposed on the basis of lightning nowcasting and warning system, considering features of electron system thunderbolt disaster. An application system is developed based on B/S framework. The system can automatically block lightning surge channel of protection when lightning is coming, and return to normal when the alarm is clear. Through the visualization of GIS, the process of lightning, the evolution of effective warning and the implementation of control terminal are shown dynamically. A survey is carried out on terrain conditions of four radio stations at Quanzhou, and the historical lightning environment and the main route of lighting wave invasion are analyzed in detail. The initiative lightning protection technology is used in the serious area of thunderbolt disaster by the way of key locations. Combining the electromagnetic field of the lightning current radiation and the anti-jam effect of electronic apparatus, the key location is determined within a 5-kilometer radius. In order to evaluate the effect, the response time of sub-closing and the advanced direction and time detecting (ADTD) of monitoring data of each terminal is analyzed. The efficiency of initiative lightning protection is tested by two methods in these four radio stations from August 2013 to August 2014. One method is to calculate the efficiency of thunderbolt disaster depending by counting the total number of lightning in range of key locations, the number of lightning when the warning level is at dangerous or too dangerous level. The forecast scoring method is also used to estimate the efficiency, giving the POD (probability of detection), FAR (false alarm rate) and TS (threat score).The result demonstrates that the initiative lightning protection technology is a better improvement and supplement for the passive lightning protection technology. In contrast with the quantity of lightning flashes, warning results of 4 radio stations is 69%, and with the forecast scoring method the probability of detection is 53%. The system gives better warning result in the area where lightning activities are centralized than that in the area where lightning activities is scattered.

Direction-finding Location Algorithm of Cloud Flashes

Liang Li, Ma Shuqing, Pang Wenjing, Pu Xiaohu

2015, 26(5): 618-625. DOI: 10.11898/1001-7313.20150511

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Abstract:
Cloud lightning location is achieved by excluding solution with large gross errors to optimize initial solution, and joint constrained optimization of weighted integration and Gauss-Newton iterative algorithm based on the multi-station direction-finding cross-algorithm. The lighting position of each group is used as initial positioning solution, which is achieved according to elevation and information of azimuth. Initial solution is optimized through removing the solution with large gross errors by testing function of T-distribution, and then more accurate location information is obtained utilizing the weighted arithmetic. Cloud lightning location information is obtained accurately finally using Gauss-Newton iterative algorithm for constraint calculation. The algorithm is evaluated with the Monte Carlo simulation method, and then the influence of locating result is analyzed. Assuming the error of site layout is 10 m, the error of angle finding is 1°, the position precision is significantly improved using the algorithm of removing gross errors in four-station network simulation. The position precision of three-dimensiond angle of arrival loction (3D-AOA) is higher than integration solution under the same simulation conditions, which shows that the position precision is improved effectively by utilizing the weighted arithmetic and Gauss-Newton iterative algorithm. It shows that the accuracy of position is effectively improved and the deviation of four-station network is less than 500 m when the direction-finding error is 1°, and more stations lead to higher positional precision, but considering the balance of economic cost and precision, four-or five-station network is suggested. As the accuracy of direction-finding increases, the positional precision also increases. Analysis of different station network distributed shows that uniform distributed mode is better than others, the position precision of stations within a station network is clearly higher than stations out of the network. The error symmetry is convenient for analyzing data in practical application. Longer baseline leads to higher positioning accuracy of station network when the station number, station network structure and the direction-finding are fixed. Due to the sensitivity of finding system to the positioning distance, the error curve becomes less symmetrical when the baseline length reaches 100 km. The analysis on different baseline length of the station network positioning accuracy is only the theoretical result in the ideal case, a variety of factors such as instrument performance, detecting network, and hardware testing should be taken into comprehensive consideration in actual application.

Retrieval of Atmospheric Boundary Layer Height from Ground-based Microwave Radiometer Measurements

Liu Sibo, He Wenying, Liu Hongyan, Chen Hongbin

2015, 26(5): 626-635. DOI: 10.11898/1001-7313.20150512

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Abstract:
Atmospheric boundary layer is a key parameter for boundary layer studies, including meteorology, air quality and climate. The atmospheric boundary layer height estimates are inferred from local radiosonde measurements or remote sensing observations from instruments like laser radar, wind profiling radar or sodar. Methods used to estimate atmospheric boundary layer height from radiosonde profiles are also used with atmospheric temperature and humidity profiles retrieved by microwave radiometers. An alternative approach to estimate atmospheric boundary layer height from microwave radiometer data is proposed based on microwave brightness temperatures, instead of retrieved profiles. Using the ground-based microwave radiometer and laser radar atmospheric boundary layer height obtained in 2013 at Xianghe Station, algorithms for retrieving atmospheric boundary layer height from 14-channel microwave brightness temperatures are developed based on the nonlinear neural network and multiple linear regression methods. The atmospheric boundary layer height is derived from laser radar backscattering data using the algorithm that retrieves the most significant gradients in profiles using gradient method. Root mean square errors (RMSEs) and correlation coefficient with two kinds of method are obtained to analyze which method is better through comparison. Retrieval results with the neural network method are compared in different periods of time and weather conditions. It shows that neural network algorithm is better than the multiple linear regression algorithm because results are more consistent with the observation. The correlation coefficient between the lidar-detected and neural network algorithm retrieved boundary layer height is 0.83, which is about 26% higher than the multiple linear regression algorithm retrieved result. Also, RMSEs of the neural network algorithm retrieved values (268.8 m) are less than the multiple linear regression algorithm retrieved values (365.1 m). For different time periods and weather conditions, retrievals in spring are best of four seasons, retrievals in the clear sky are better than those in the cloudy sky. But RMSEs in the cloud sky are less than those in the clear sky. Overall, correlation coefficients in four seasons are close to 0.80. It suggests that in order to improve the retrieval precision, specific retrievals under different conditions (such as different seasons and different skies) should be carried out.

Correction of TRMM PR Surface Rainfall Rates over the Tibetan Plateau

Li Jiarui, Lu Naimeng, Gu Songyan

2015, 26(5): 636-640. DOI: 10.11898/1001-7313.20150513

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Abstract:
In order to reveal and improve the accuracy of surface rainfall rates derived from precipitation radar (PR) on TRMM satellite over the Tibetan Plateau, TRMM PR 2A25 products and hourly rain gauge data from 2005 to 2007 are compared.Results show that PR has a relative error of-35% in stratiform rain and 42% in convective rain over the Tibetan Plateau.The applicability of Z-R relation is one of the cause for the bias of PR.Based on the analysis, the initial coefficients A and b in Z-R relations at 20℃ level are modified to 0.0288 and 0.6752 for stratiform rain, respectively, also modified to 0.0406 and 0.5809 for convective rain, thus the Z-R relation at different altitudes between 0℃ and 20℃ height are updated. Results suggest that the modified models can achieve better accuracy in estimating surface rainfall rates over the Tibetan Plateau.

Vol.26, NO.5, 2015