Vol.26, NO.1, 2015

Display Method:
Advances in Impacts of Climate Change on Agricultural Production in China
Guo Jianping
2015, 26(1): 1-11. DOI: 10.11898/1001-7313.20150101
Climate change, the main feature of which is global warming, has become one of the important environmental problems in the world. Also, it is a matter of general concern by the scientific community, governments and the social public. Climate change has brought a series of problems that beyond the range of nature changes in the earth itself, which poses a serious threat to human survival and social economy. Agriculture, especially crop production and food security, is one of the largest and the most direct industry affected by climate change. Therefore, the impact of climate change on agricultural production is always one of the hottest issues in the field of climate change. The present situation and progress in the research field of climate change impact on agricultural production in China is summarized systematically, introducing research methods, the progress in the experiment of greenhouse gases concentration enrichment in the atmosphere impact on crops, impacts and future trends of climate change on agricultural climate resources, the possible impact of climate change on crop growth and yield, impacts and future trends of climate change on agricultural planting system and varieties distribution, impact of climate change on crop potential productivity, impact of measures of adapting to climate change to increase the utilization ratio of agricultural climate resources and so on. On the basis, current problems in the impact assessment of climate change on agriculture is proposed too. In order to improve the reliability and rationality of the impact assessment for climate change on agriculture, more attention needs to be paid to the research of uncertainty of future climate change scenarios, model prediction and evaluation method. In addition, further researches are also needed about the impact of extreme weather events under climate change on agricultural production, the impact of climate change on agricultural plant diseases and insect pests, impacts of climate change on cash crops, fruit, animal husbandry and farmland ecosystem.
A Modified Method to Correct the Measurement Error of TSI3563 Integrating Nephelometer
Ma Nan, Zhou Xiuji, Yan Peng, Zhao Chunsheng
2015, 26(1): 12-21. DOI: 10.11898/1001-7313.20150102
TSI3563 integrating nephelometer is designed for high-quality in-situ aerosol scattering measurement, which is widely used all over the world. However, the scattering coefficient measured by TSI3563 nephelometer contain two systematic errors: The truncation error (i.e., the geometrical blockage of near-forward/backward-scattered light) and the non-Lambertian error (i.e., the slightly non-cosine weighted intensity distribution of illumination light provided by the opal glass diffusor). These errors need to be corrected since they can typically cause a bias of about 10% in the measured scattering coefficient. Based on the aerosol properties measured in North China Plain during Hachi (Haze in China) Project, the correction factor is calculated with a traditional method and the Mie model (taken as reference) which requires aerosol number size distribution and refractive index as input. The traditional correction method is widely used all over the world since it requires only data from nephelometer itself. However, results show the traditional method cannot provide a good estimation of the correction factor. Due to the high concentration of submicron aerosol in PM10, aerosol number size distributions measured in North China Plain are different from those assumed in the traditional method. The traditional correction method is therefore inadequate for high-aerosol pollution region like North China Plain. It is found that the correction factor is sensitive on the volume fraction of supermicron aerosol in PM10. Higher volume fractions would lead to higher correction factors. A modified correction method is proposed. The volume fraction of supermicron aerosol which can be obtained from PM1 and PM10 measurement is used in the new method. For different volume fractions, different parameters are chosen for the calculation of correction factors. Testing with aerosol properties measured in North China Plain, the modified method provided a good estimation of the correction factors. 80% of correction factors calculated with the modified method are with a bias less than 1% and 100% are with a bias less than 3%. Compared with the traditional method, a distinct improvement is found in correction results. It suggests that to estimate the correction factor for TSI3563 nephelometer measurement, the Mie model should be the first choice if a real-time measurement of aerosol number size distribution is available. Otherwise, the modified method proposed should be used if a real-time PM1 and PM10 measurement is available. Without those parallel measurements, the traditional method can be the last choice to estimate the correction factor.
Identifying the Interference of Spaceborne Microwave Radiometer over Large Water Area
Guan Li, Xia Shichang, Zhang Sibo
2015, 26(1): 22-31. DOI: 10.11898/1001-7313.20150103
The phenomenon of satellite-measured passive microwave thermal emission from natural surface and atmosphere being mixed with signals from active sensors is referred as radio-frequency interference (RFI). Due to increasing conflicts between scientific and commercial users of the radio spectrum, RFI is an increasing serious problem for microwave active and passive remote sensing. RFI greatly affects the quality of data and retrieval products from space-borne microwave radiometry, as the C-band and X-band of spaceborne microwave radiometer operate in unprotected frequency bands. Interference signals over land come dominantly from lower frequency active microwave transmitters, including radar, air traffic control, cell phone, garage door remote control, GPS signal on highway, defense tracking and vehicle speed detection for law enforcement. The signal emanating from geostationary communication and television satellites that reflect off the ocean surface is the major interference source over ocean of spaceborne passive microwave imagers. RFI detection and correction of low-frequency radiances over large water area is extremely important before these data being used for either geophysical retrievals or data assimilation in numerical weather prediction models.RFI over ocean and inland large water area of North America, as well as over the coastline of China are identified and analyzed based on Advanced Microwave Scanning Radiometer (AMSR-E) observations using double principal component analysis (DPCA) algorithm. The AMSR-E instrument is primarily designed to enhance cloud and surface sensing capabilities. The DPCA method takes advantage of the multi-channel correlation for natural surface radiations, as well as the de-correlation between different RFI contaminated frequencies. Results show that the DPCA method works well in detecting the location and intensity of RFI over ocean and large water area. The AMSR-E observation over the ocean of America at 18.7 GHz is mainly interfered by geostationary television satellites DirecTV. The RFI location and intensity from the ocean reflection of downlink radiation highly depends upon the relative geometry between the geostationary satellite and the measuring passive sensor. Only the field of views with smaller glint angle (defined as the angle between the geostationary specular reflection vector and the AMSR-E line-of-sight vector) is easily affected by RFI. The stronger RFI distribute near the Great Lakes of America, and the RFI magnitude of East and West Coast is stronger than south coast. AMSR-E observations of 6.925 GHz are contaminated by RFI along the coastline of China, while observations of 18.7 GHz are not affected.
Application of Latent Heat Nudging Method to Assimilating Surface Precipitation Observations
Wu Yali, Chen Dehui
2015, 26(1): 32-44. DOI: 10.11898/1001-7313.20150104
For the spin-up problem in initial integration of meso-scale numerical weather prediction model, especially the time lags in the prediction of rain belt, latent heat nudging method is applied to assimilate the intensified automatic weather station (AWS) precipitation observations, so that it can effectively improve the performance of model in the very short-term forecasts. Based on GRAPES_Meso model with high resolution developed by China Meteorological Administration, three groups of latent heat nudging experiments are designed for generating different initial conditions, including the control run, the traditional cold-latent heat nudging (C-LHN) assimilation and the revised warm-latent heat nudging (W-LHN) assimilation. The last one consists of W6-LHN and W12-LHN with 6 h and 12 h warm-start period before nudging, respectively.Batch tests are carried out from 0000 UTC 20 June to 0000 UTC 20 July in 2013, preliminary conclusions can be drawn as follows. Firstly, initial temperature profiles are significantly modified due to the adjustment of forecasted latent heat profiles, according to analyzed differences between observations and forecasts in the pre-forecast period. And initial distributions of specific humidity and wind vectors are modified indirectly that convergence and divergence of water vapor increase at lower and middle levels. Thus the convective instability in the heavy rain area is strengthened. Secondly, compared with the control run without any initial precipitation information, the application of latent heat nudging method in GRAPES_Meso model can reduce the spin-up time, precipitation is triggered quickly in the first 3 hours, which is important for the very short-term forecast and nowcasting in particular. Therefore, the location and intensity are much closer to observations, and enhancing forecast skills of 3 h, 6 h and 12 h accumulated precipitation such as TS, ETS and Bias scores. In addition, when comparing the warm and cold latent heat nudging methods, both of them has its advantages and disadvantages, performances differ with forecast length and precipitation magnitudes divided into light, moderate, heavy, hard and torrential rainfall, but 3 h, 6 h and 12 h light and moderate precipitations are always better predicted by W-LHN. Finally, W6-LHN experiments achieve more favorable rainfall forecasts, but W12-LHN experiments tend to overestimate the heavy and torrential rain.All in all, application of latent heat nudging method in assimilating the observed precipitation for very short-term forecast is operationally prospective, with advantages of lower cost but higher performance, thus it is easy to meet the operational demand for being available to public very soon. However, the impact on improving precipitation forecasts cannot last long because meso-and micro-scale characteristics fade away with the increasing forecast length. In the near future, it is expected that three dimensional variational analysis will be incorporated for an extended prediction.
Effects of Assimilating Radar Rainfall Rate Estimation on Torrential Rain Forecast
Gao Yudong, Wan Qilin, Xue Jishan, Ding Weiyu, Li Haorui, Zhang Chengzhong, Huang Yanyan
2015, 26(1): 45-56. DOI: 10.11898/1001-7313.20150105
Meso-scale weather system, such as torrential rain, is neither easily detected nor effectively simulated. Main causes consist of the insufficient observation and the inaccurate initial filed, which are prepared for the routine weather prediction and the hazardous weather simulation. To solve these problems, high resolution rainfall rate data estimated by doppler radar Z-I relationship is calibrated with AWS data by variational method. The forecast experiment on a torrential rain case captured by the radar in Guangzhou indicates that the east center of precipitation omitted in the original Z-I estimation is forecasted after the calibration. Even though the minor amount of rainfall rate is inclined to be overestimated, relative errors of calibration significantly decline as the increase of rain rate value. As a result, high resolution datasets of calibration rain rate are demonstrated to possess a more accurate single point value than the estimation of Z-I relationship and a more reasonable gradient than AWS data. Meanwhile, according to the distribution of instantaneous precipitation, calibration rainfall rate datasets imply lots of information on the atmospheric dynamic and moisture, which are the major factors to arouse a convective rainstorm.To verify various advantages of mixed characteristics, a set of experiments are performed using FSU (Florida State University) cumulus parameterization scheme as the observational operator, based on GRAPES (Global/Regional Analysis and Prediction System) Regional Three Dimensional Variation System. Compared with NCEP (National Centers for Environmental Prediction) global analysis data, the convergence in lower level and the divergence in higher level after assimilation are conspicuously strengthened, which sequentially lead the unstable energy in atmosphere to be elevated. Showalter index and K index diagnose indicate a heavy rain in the dense data region as well. In addition, the vertical transportation of moisture forced by the convergence sustains a strong convection and ameliorates the cumulative precipitation. The storm path prediction is obviously improved. Results of simulation experiment express that not only the hourly distribution and center of precipitation are similar to the observation, also, the meso-scale convective system development and demise are impressively depicted.
Doppler Radar Features of Severe Hailstorms in Guangdong Province
Hu Sheng, Luo Cong, Zhang Yu, Li Huaiyu, He Ruyi
2015, 26(1): 57-65. DOI: 10.11898/1001-7313.20150106
Doppler weather radar features of 12 severe hailstorms in Guangdong Province are studied.Firstly, radar echo characteristics including the maximum reflectivity, maximum reflectivityheight, the echo top, 45 dBZ echo height, the vertically integrated liquid (VIL) water, the VIL density and the vertical gradient of reflectivity are calculated. The maximum reflectivity of these 12 hailstorms are mostly over 65 dBZ with the highest value of 73 dBZ. The maximum echo heights are over 5 km with the highest being 9.2 km. Besides, all of 45 dBZ echo heights reach 9.7 km. The maximum VIL is 91 kg·m-2 and only one storm's maximum VIL is less than 50 kg·m-2. The average vertical gradient of reflectivity is 2.4 dB·km-1, and the minimum vertical gradient of reflectivity is 0.5 dB·km-1.Secondly, three body scatter spike (TBSS) features, side-lobe echoes, and reflectivity distribution features in 0℃ and-20℃ environmental temperature layers of 12 sever hailstorms are analyzed. Side-lobe echoes and TBSS features are observed in 3 and 6 hailstorms, respectively, but they are found simultaneously only in one severe hailstorm. Severe hails occur within 0-40 minutes after the first TBSS feather or the side-lobe echo appears, and the average forecast lead time is about 14 minutes. Average heights of the 0℃ and-20℃ environmental temperature layers around 12 severe hailstorms are 4502 m and 7682 m. All the maximum echoes of 12 severe hailstorms in 0℃ and-20℃ layers are over 54 dBZ, and the maximum values are 67 dBZ and 66 dBZ in different layers.Finally, vertical reflectivity profiles between severe hailstorms and non-hail storms are compared. For severe hailstorms, most of the maximum echoes exceed 65 dBZ, and their heights are between 5 km and 10 km. Radar echoes in hailstorms below 10 km are over 40 dBZ, and 30 dBZ echoes can extend to 15 km or higher. For non-hail storms in hailstorm days, the maximum echoes are about 60 dBZ, and corresponding heights are lower, located at 2-5 km levels. 40 dBZ echoes in storms are rarely above 10 km. It shows that these storms in hailstorm days can't generate large hail because of their weaker vertical updraft and weaker, reflectivity. For storms in non-hailstorm days, the maximum echoes vary from 55 dBZ to 68 dBZ, and heights of most of them are about 5 km. 40 dBZ echoes in some storms can extend to 10 km or higher, however, large hails don't occur for these strong storms due to different environmental conditions.
A Method to Suppress the Precipitation Interference on Horizontal Wind of Wind Profile Radar
Lin Xiaomeng, He Ping, Huang Xingyou
2015, 26(1): 66-75. DOI: 10.11898/1001-7313.20150107
Wind profile radar (WPR) is a kind of clear air radar, which takes atmospheric turbulence as the main detecting object. In the past few decades, WPR spectral data processing mainly focus on the wind spectrum estimation. In recent years, with the use of WPR data expansion, there are increasingly high demands for WPR data accuracy. However, ground clutter, external noise, flying objects, presence of disturbances such as precipitation and limitations of Fourier Transform often lead multiple peaks overlapping phenomenon, which makes it difficult to judge spectral moments, resulting in large error detection products. Especially in the case of precipitation, wind speed measurement may be even completely wrong. Therefore, the radar power spectrum data need further processing under different weather conditions especially for turbulence and precipitation to establish an effective spectral extraction programs and enhance the wind profile accuracy of radar detection.WPR has a large dynamic reception range, so it can receive the echo of scattering of atmosphere turbulence and scattering of precipitation particles simultaneously during precipitation. In this case, spectrum of atmosphere turbulence and spectrum of precipitation are superimposed. It requires uniform wind-field on horizon when calculating the horizontal wind, but the spatial variability of precipitation will bring distorted horizontal wind-field if the superimposed spectrum data. To avoid this problem, the radar power spectrum data are processed with three steps. First, the original radar power spectrum is processed by interpolation and moving average, judging whether it is affected by precipitation according to the number of maximum points. Second, in the case that the radar power spectrum is affected by precipitation, spectrums of atmosphere turbulence and precipitation are separated by two methods in accordance with spectrum of atmosphere turbulence and spectrum of precipitation's tending to symmetry. And then the horizontal wind-field is derived utilizing the separated spectrum of atmosphere turbulence. Case analysis shows that the consistency of derived wind-field has significant improvement using the spectrum of atmosphere turbulence instead of the original spectrum.
Effects of Radiosonde System Changing to L-band Radar Digital Radiosonde on Humidity Measurements in China
Wang Ying, Xiong Anyuan
2015, 26(1): 76-86. DOI: 10.11898/1001-7313.20150108
The radiosonde sounding is a major tool for measuring the vertical structure of atmospheric variables. Accurate monitoring of water vapor is vital for numerical weather prediction and climatic change assessment. The radiosonde sounding system in China begins upgrading to L-band radar digital radiosonde system from 59-701 system since 2002 and completes in 2011, and the sensor for humidity measurement is changed from goldbeater's skin to a carbon hygristor. These changes may result in discontinuity of radiosonde observation series.In order to determine the observational bias brought by the upgrade, comparative analysis of relative humidity (RH) measurement between pre-change and post-change of the system is made using radiosonde humidity observations. 98 radiosonde stations out of 120 stations in China are selected to analyze differences between 3 pre-change years and 3 post-change years. Results show that RH after changing the sensor has a significant dry bias. There are statistically significant dry bias in almost all selected stations at 200 hPa, and in 75% and 54% stations at 500 hPa and 850 hPa, respectively. RH dry biases increase with height in troposphere, with values of 14.6%, 8.3% and 5.3% at 200 hPa, 500 hPa and 850 hPa, respectively. There are more dry biases during daytime than nighttime due to impacts of solar radiation. The probability distribution of relative humidity after the system upgrading has a significant shift comparing to pre-upgrading. The occurrence frequency of RH with the value less than 20% after system change is much higher than that during pre-change, which are 53% vs 10% at 200 hPa. The frequency of RH with the value less than or equal to 3% are 16.2%, 9.9% and 2.2% on 200 hPa, 500 hPa and 850 hPa after system upgrading, but that is nearly 0 at three levels before upgrading. Causes of these dry biases and biases between actual value and the observation will be further studied. Also, methods for correcting the bias should be developed.
Statistical Characteristics of Magnetic Field Produced by Tall-Object Lightning in Guangzhou During 2011-2012
Wang Zhimin, Lü Weitao, Chen Lüwen, Qi Qi, Yang Xinyi, Zhang Yang, Ma Ying, Chen Shaodong
2015, 26(1): 87-94. DOI: 10.11898/1001-7313.20150109
With the development of society and economy, more and more tall objects, such as tall towers, skyscrapers and other kinds of high buildings are erected in China. It is a commonly used method to study physical mechanisms of lightning discharge by measuring the electromagnetic fields produced by the lightning occurring on tall objects. Characteristics of electromagnetic fields and the influence on the electromagnetic environment induced by lightning flashes occurring on or around the tall objects are also widely studied. Since 2009, a field experiment is conducted to study the physics process of lightning flashes striking on tall objects in Guangzhou. The Tall-Object Lightning Observatory in Guangzhou (TOLOG) is established on the top of a building with a height of approximately 100 m that belongs to Guangdong Provincial Meteorological Bureau to observe lightning flashes striking on tall objects with different heights in Guangzhou. In this experiment, the height of observed lightning striking point is found to be within 90-600 m, while the distance between the lightning striking points and the observation point is within 140 m-3.3 km. Magnetic field data for 40 negative lightning flashes obtained during 2011-2012 are analyzed. Statistical results show that tall objects have an enhancing effect on the magnetic field induced by the lightning flashes striking on them. The taller the object is, the larger the enhancing effect will be. The geometric mean (GM) value of the magnetic field peak values induced by the lightning flashes to the objects taller than 200 m is 2.4 times of that induced by lightning flashes to the objects lower than 200 m. Waveforms of the lightning magnetic field always exhibit multi-peak behavior. Regarding the magnetic field waveforms of the first return stroke, 13 out of 20 cases in which the lightning flashes strikes objects lower than 200 m have the subsequent peak value that is greater than the initial peak value; 8 out of 14 cases in which lightning flashes that strike tall objects higher than 200 m exhibit the same characteristics. The GM value of inter-stroke intervals of all of 135 return strokes is 69.1 ms. Among them, the GM value is 65.0 ms for the inter-stroke intervals of the 53 return strokes occurring on the objects taller than 200 m, and 71.5 ms for the inter-stroke intervals of the 82 return strokes occurring on the objects lower than 200 m. In addition, 10 lightning flashes (45%) among 22 multi-stroke negative lightning flashes are found that the magnetic field peak value induced by subsequent return stroke is greater than that induced by the first return stroke.
National Solar Radiation Measurement Standards and Quality Control
Yang Yun, Quan Jimei, Ding Lei, Bian Zeqiang
2015, 26(1): 95-102. DOI: 10.11898/1001-7313.20150110
In order to ensure the accuracy of national solar radiation measurements and the world radiometric reference (WRR) transfer, quality control is carried out on the solar radiation measurement standards. There is a full set of sound management system and quality guarantee measure over many years' improvement, including the measurement standard of value transfer and traceability, the selection and validation of calibration method, calibration process and data quality control, staffed and personnel skill requirements and so on. It also passes the measurement standard reexamination organized by General Administration of Quality Supervision, Inspection and Quarantine (AQSIQ).The radiation value is directly traceable to the WRR every five years through attending the World Meteorological Organization (WMO) International Pyrheliometer Comparisons (IPC), and then the metrological verification or calibration method is adopted for the standard radiation instrument value transfer, to ensure the accuracy of WRR in China and neighboring countries. China national solar radiation measuring standard is directly compared with the WRR for 3 times in 15 years, and comparison results of the uncertainty is 0.17%, surpassing requirements of WMO.In order to ensure measurement standards between the international cycle comparison interval, and keep them in good confidence calibration status, the repeatability and stability of solar radiation measurement standards should be checked every year to determine standards in original state. In fact, there should be more times of checking if conditions allow to reduce the uncertainty introduced by the repeatability of measurement error. Mean value control chart is used to judge whether the measurement process is affected by uncontrolled system bias, and graphics memory way is used to achieve continuous and long-term statistical quality control. Period verification shows the solar radiation measurement repeatability and years of stability is no more than 0.1% and less than 0.25%, within the control limits and taking a random distribution state. That ensures the measuring process in a stable controlled status, meeting the standard requirements.Above all, the WRR international comparison itself cannot ensure the national solar radiation measurement standards fully meet the quality assurance requirements, a lot of collaborative international comparison and period verification should be carried out to ensure that the measurement uncertainty is controlled within the allowable range of 0.25%.
A Comparative Study on Dynamic Forecasting of Early Rice Yield by Using Different Methods in Hunan Province
Shuai Xiqiang, Lu Kuidong, Huang Wanhua
2015, 26(1): 103-111. DOI: 10.11898/1001-7313.20150111
The crop yield forecasting is one of the most important aspects of meteorological services for agricultural production. In order to improve the prediction accuracy, different forecasting methods are compared, and dynamic forecasting models of early rice yield are established based on climatic suitability, key meteorological factors and crop growth simulation model. Daily mean, maximum and minimum temperatures, precipitation, sunshine duration, wind velocity and vapor pressure data of 15 representative meteorological stations are used, as well as the early rice growth and yield data of 12 representative agricultural meteorological stations in Hunan Province from 1962 to 2002. Fitting test is performed by constraining the margin of error less than 5%. Extrapolation test is performed using data from 2003 to 2012, showing the accuracy of three methods are similar, all higher than 93.8%, and the dynamic forecasting models practically pass the test of 0.02 level, except for failing the test of 0.10 level on 30 April. Forecasting models from rifeness tiller to elongating stage pass the test of 0.01 level, and forecasting models at reproductive stage pass the test of 0.001 level too. The method based on climatic suitability improves the accuracy by 4%-6% comparing to that based on key meteorological factors and is 8%-10% more accurate than that based on crop growth simulation model. In quantitative forecast, the method based on crop growth simulation model is optimum, leading to obviously more samples whose margin of error is less than 5%. According to the analysis, the better method of early rice yield forecasting is screened out for Hunan Province. The method based on climatic suitability is chosen to carry out trend prediction of early rice yield, and the method based on crop growth simulation model is used to make quantitative forecast. It also provides reference for dynamic forecasting method research of early rice yield in other areas of China.
Characteristics of Raindrop Size Distribution in Chengdu
Liu Chenzhong, Zhou Yunjun, Gu Juan, Huang Lei, Xiang Gang
2015, 26(1): 112-121. DOI: 10.11898/1001-7313.20150112
Based on raindrop data derived from LNM laser spectrometer from 2009 to 2011, raindrop size distribution (RSD) characteristics of Chengdu are discussed, and evolutions of microphysical parameters of 175 precipitation processes including cumulus type, cumulus-stratus mixed cloud type and stratus type are analyzed. Meanwhile, three typical cases are chosen to investigate the microphysical structure parameters. Conclusions are as follows.The cumulus precipitation and cumulus-stratus mixed cloud precipitation are wider than stratus precipitation in RSD and larger than stratus precipitation in raindrop density, especially in sections of big raindrops and very small raindrops. It reveals different ways raindrop growth. The curve of RSD in three types of precipitation has more than two peaks, indicating that most of the precipitation process is unstable. The advantage diameter and the median volume diameter are well correlated with rainfall intensity, Dp and Dn values in three types of precipitation are significantly different, the advantage diameter and the median volume diameter of stratus precipitation is less than half of cumulus precipitation. In general, four kinds of characteristic diameters of the cumulus precipitation are the largest ones in three types of precipitation, and the ones of the cumulus-stratus mixed cloud precipitation are larger than those of the stratus precipitation. But results are not completely in accordance with facts. Because of the complexity of the precipitation process, four characteristics of diameter cannot be the classification standard of precipitation patterns. Small raindrops make the main contribution to the rainfall intensity of stratus precipitation, while big raindrops make the main contribution to the cumulus precipitation and cumulus-stratus mixed cloud precipitation over Chengdu Area. In different rainfall process, raindrop is in the majority, the deviation of contribution rate is small, and the number proportion is stable. Although the number of big raindrops is very small, the deviation of raindrop density ratio becomes large and the proportion of number is not stable, and it is the main cause for heavy rainfall process. The rainfall intensity depends on the quantity of big raindrops, however, the contribution of small raindrops to the rainfall intensity is negative. The median volume diameter can indicate the change of rainfall intensity, because the median volume diameter always increases earlier than rainfall intensity. Raindrop proportion increases firstly, then the raindrop density increases, finally, numbers of the small raindrops increase with big raindrops, strengthening the rainfall intensity. The study on RSD is helpful to further understand the mechanism and microphysical characteristics of the precipitation over Chengdu, and can also accumulate basic data and experience for the precipitation numerical prediction.
Design and Implementation of NWP Data Service Platform Based on Hadoop Framework
Li Yongsheng, Zeng Qin, Xu Meihong, Shi Xiaoying
2015, 26(1): 122-128. DOI: 10.11898/1001-7313.20150113
As the numerical weather prediction (NWP) products increase in huge amounts every day, traditional relational database has the problem of low efficiency in archiving capacity and management, while file based storage faces performance challenges in long-time-series data accessing and massive computation of spatial-temporal data. Therefore, a three-tier software framework is designed, which implements distributed data storage model, parallel data access service and distributed computation for frequently used statistical algorithms based on Hadoop framework. Meteorological big data such as NWP products, radar 3D mosaic and satellite remote sensing are designed to be composed of metadata and data entity, which both are stored in Hbase data tables, and managed with HDFS file system. Metadata are defined by variable name, dimension, latitude, longitude, altitude and lead time etc., and data entity consists of row key, time stamp and column family to store the value at each grid point. A Rest (representational state transfer) Web Service is setup for direct NWP data acquisition, field data clipping and location based time-series accessing. File download services in "MICAPS", "surfer" and "json" format are also ready for the third-party meteorological software. System testing for data access of CHAF model shows that it costs only 12 seconds to write in 1000 NWP data fields each with 82503 grid points, and less than 4 seconds to read out the same amount of data from the distributed databases.Map-reduce scheme are implemented for computation of meteorological algorithms, e.g., Kalman filter and successive regression. Most of meteorological statistical algorithms are time independent, which make it possible that a task is divided into small sub-tasks according to data slicing on time series, and assigned to different computational nodes in map programs. Reduce programs are to gather and summarize the result of sub-task computation. With data amount and users increasing, Hadoop framework deployed on several X86 PC servers demonstrates performance advantage over single IBM power system. And flexible hardware architecture from 3 computational nodes to 9 nodes show steady and better data access efficiency with good speed-up ratio, which brings more confidence for practical use in weather forecast.Operational trial in multi-user environment further shows advantages of this cloud-like computing service over the traditional client-server model in meteorological data mining, such as NWP interpretation and model evaluation.