ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 41,Issue 8,2015 Table of Contents
2015, 41(8):921-931.
DOI: 10.7519/j.issn.1000-0526.2015.08.001
Abstract:
This study develops a new cloud scheme of Global/Regional Assimilation and Prediction System (GRAPES) at 50 km spatial resolution, considering the impact of the detrainment process of shallow convection and boundarylayer clouds on hydrometeors water contents and cloud fraction. The purpose of this research is to improve the lowlevel cloud prediction of GRAPES model, simulate and compare the results before and after the improvement. Besides the results are compared with observational data of the Clouds and the Earth’s Radiant Energy System (CERES) and Year of Tropical Convection (YOTC). The results show that considering the detrainment process of shallow convection and boundarylayer clouds mainly increases the cloud fraction and liquid hydrometeor contents of lowlevel cloud below 700 hPa. The improved results are closer to observation. Boundarylayer stratocumulus clouds mainly affect the clouds near the top of boundary layer and the influenced thickness is less than 200 hPa. The impact magnitude of shallow convection detrainment process is equivalent to the one of boundarylayer clouds, but the impact thickness is more widely in the former. Shallow convection process will have a certain impact on the low clouds from surface to the height of 700 hPa. Further research shows that due to the improvement of lowlevel cloud prediction, forecast of cloud radiative forcing at surface and top of atmosphere could also be improved, the increasement of lowlevel clouds would directly enhance cloud radiative forcing at surface.
This study develops a new cloud scheme of Global/Regional Assimilation and Prediction System (GRAPES) at 50 km spatial resolution, considering the impact of the detrainment process of shallow convection and boundarylayer clouds on hydrometeors water contents and cloud fraction. The purpose of this research is to improve the lowlevel cloud prediction of GRAPES model, simulate and compare the results before and after the improvement. Besides the results are compared with observational data of the Clouds and the Earth’s Radiant Energy System (CERES) and Year of Tropical Convection (YOTC). The results show that considering the detrainment process of shallow convection and boundarylayer clouds mainly increases the cloud fraction and liquid hydrometeor contents of lowlevel cloud below 700 hPa. The improved results are closer to observation. Boundarylayer stratocumulus clouds mainly affect the clouds near the top of boundary layer and the influenced thickness is less than 200 hPa. The impact magnitude of shallow convection detrainment process is equivalent to the one of boundarylayer clouds, but the impact thickness is more widely in the former. Shallow convection process will have a certain impact on the low clouds from surface to the height of 700 hPa. Further research shows that due to the improvement of lowlevel cloud prediction, forecast of cloud radiative forcing at surface and top of atmosphere could also be improved, the increasement of lowlevel clouds would directly enhance cloud radiative forcing at surface.
2015, 41(8):932-941.
DOI: 10.7519/j.issn.1000-0526.2015.08.002
Abstract:
Based on the new generation numerical prediction model GRAPES_Meso, the numerical experiments were carried out to evaluate the two kinds of cumulus convective parameterization schemes, KainFritsch Eta scheme and BettsMillerJanjic scheme, for the winter (January) and summer (June-August) 2009. The results show that there is no obvious differences between the two schemes for winter, but some differences exist for the summer. The statistic characteristic of meteorological fields, such as wind, height and temperature, shows that BMJ performances slightly better than KFeta in the low atmospheric layer, but it does not do as well as KFeta in the middle and high layers. The results of TScore verification indicate that KFeta scheme has a higher score than BMJ scheme for precipitation forecast, especially in predicting moderate to heavy rains over southern China. The spatial distribution of the average contribution rate in total precipitation of the two schemes is different obviously in the lowlatitude ocean region, where the contribution rate of BMJ scheme is greater than KFeta scheme. In the drizzle level, the probability distribution of cumulus precipitation contribution rate in total precipitation looks like steep “U” shaped. With the increase of precipitation levels, the proportion of cumulus precipitation of KFeta becomes large. On the contrary, the higher of the precipitation level is, the lower proportion of the cumulus precipitation reaches by using the BMJ cumulus scheme.
Based on the new generation numerical prediction model GRAPES_Meso, the numerical experiments were carried out to evaluate the two kinds of cumulus convective parameterization schemes, KainFritsch Eta scheme and BettsMillerJanjic scheme, for the winter (January) and summer (June-August) 2009. The results show that there is no obvious differences between the two schemes for winter, but some differences exist for the summer. The statistic characteristic of meteorological fields, such as wind, height and temperature, shows that BMJ performances slightly better than KFeta in the low atmospheric layer, but it does not do as well as KFeta in the middle and high layers. The results of TScore verification indicate that KFeta scheme has a higher score than BMJ scheme for precipitation forecast, especially in predicting moderate to heavy rains over southern China. The spatial distribution of the average contribution rate in total precipitation of the two schemes is different obviously in the lowlatitude ocean region, where the contribution rate of BMJ scheme is greater than KFeta scheme. In the drizzle level, the probability distribution of cumulus precipitation contribution rate in total precipitation looks like steep “U” shaped. With the increase of precipitation levels, the proportion of cumulus precipitation of KFeta becomes large. On the contrary, the higher of the precipitation level is, the lower proportion of the cumulus precipitation reaches by using the BMJ cumulus scheme.
2015, 41(8):942-952.
DOI: 10.7519/j.issn.1000-0526.2015.08.003
Abstract:
Based on NCEP reanalysis data, conventional observations data, surface dense observation data and Doppler radar data, the environmental background of 10 tornadoes which occurred within spiral rain belt of typhoon and the evolution characteristics of echo structure of the tornadoes in F2 class and above were studied in detail. The results show that, firsthy typhoontornadoes occur in an environment with the weak convective available potential energy (200-1000 J·kg-1) and strong lowlevel vertical wind shear where the vertical wind shear between 0 and 1 km more than 10-2s-1. The storm relative helicity is very great and the typhoon tornado environment average bulk Richardson number is small, averagely below 40. Typhoontornadoes mostly occur on the right sides of the movingpaths of the typhoons where the 0-1 km vertical wind shear and storm relative helicity are greater.Typhoontornadoes are mainly generated in the spiral rainbands in the outsideregion of the typhoons. Before tornadoes come into being the convergence of wind direction and speed appears near the surface, but the temperature gradient is small. Secondly, the storms which produce typhoontornadoes are mini supercell storms, with cell centroid being about 2 km and stretching height about 5-7 km, accompanying the mesocyclones in horizontal scales about 2-4 km. The positive vertical vorticity is limited to below 4 km.
Based on NCEP reanalysis data, conventional observations data, surface dense observation data and Doppler radar data, the environmental background of 10 tornadoes which occurred within spiral rain belt of typhoon and the evolution characteristics of echo structure of the tornadoes in F2 class and above were studied in detail. The results show that, firsthy typhoontornadoes occur in an environment with the weak convective available potential energy (200-1000 J·kg-1) and strong lowlevel vertical wind shear where the vertical wind shear between 0 and 1 km more than 10-2s-1. The storm relative helicity is very great and the typhoon tornado environment average bulk Richardson number is small, averagely below 40. Typhoontornadoes mostly occur on the right sides of the movingpaths of the typhoons where the 0-1 km vertical wind shear and storm relative helicity are greater.Typhoontornadoes are mainly generated in the spiral rainbands in the outsideregion of the typhoons. Before tornadoes come into being the convergence of wind direction and speed appears near the surface, but the temperature gradient is small. Secondly, the storms which produce typhoontornadoes are mini supercell storms, with cell centroid being about 2 km and stretching height about 5-7 km, accompanying the mesocyclones in horizontal scales about 2-4 km. The positive vertical vorticity is limited to below 4 km.
2015, 41(8):953-963.
DOI: 10.7519/j.issn.1000-0526.2015.08.004
Abstract:
Based on NCEP/NCAR analysis data (1°×1°, 4timesaday) and various dense observation data, a typical shear and cold front type rainstorm process in Yunnan Province was diagnosed and its mesoscale characteristics were analyzed. The results show that the northwest air flow leads cold air and shear line to move south, location of surface cold front is consistent with shear line, warm air and cold air converge near shear line and cold front, leading to heavy rainfalls. Efficient and reasonable configuration of synoptic scale systems and their interaction provide the background for mesoscale convective systems. The distributions of high CAPE area and dense isoline area of Δθse (500-800) correspond to the convective systems. Mesoscale characteristics of the local and sudden rainstorm are closely related to surface mesosacle convergence systems. The location and movement of surface cold front and the overlaid intensive wind field convergence area could be used as important reference for the imminent forecast of shorttime severe precipitation. The intensity and location of rainfall are related to gradient of TBB isolines and the location of the largevalue zone of the gradient. The occurrence and development of CloudtoGround lightning could be one of criteria indicating occurrence and development of convective cloud cluster. There is a complex relationship between the time of lightning frequency peak value and the time of rainstorm peak value at different rainstorm sites in lowlatitude plateau because of various factors. The existence of the gale area, the second type mesoγ scale convergence area and “train effect” are the direct causes for local heavy rainfall. Boundary layer jet plays an important role in dynamic trigger and vapor transport in this process.
Based on NCEP/NCAR analysis data (1°×1°, 4timesaday) and various dense observation data, a typical shear and cold front type rainstorm process in Yunnan Province was diagnosed and its mesoscale characteristics were analyzed. The results show that the northwest air flow leads cold air and shear line to move south, location of surface cold front is consistent with shear line, warm air and cold air converge near shear line and cold front, leading to heavy rainfalls. Efficient and reasonable configuration of synoptic scale systems and their interaction provide the background for mesoscale convective systems. The distributions of high CAPE area and dense isoline area of Δθse (500-800) correspond to the convective systems. Mesoscale characteristics of the local and sudden rainstorm are closely related to surface mesosacle convergence systems. The location and movement of surface cold front and the overlaid intensive wind field convergence area could be used as important reference for the imminent forecast of shorttime severe precipitation. The intensity and location of rainfall are related to gradient of TBB isolines and the location of the largevalue zone of the gradient. The occurrence and development of CloudtoGround lightning could be one of criteria indicating occurrence and development of convective cloud cluster. There is a complex relationship between the time of lightning frequency peak value and the time of rainstorm peak value at different rainstorm sites in lowlatitude plateau because of various factors. The existence of the gale area, the second type mesoγ scale convergence area and “train effect” are the direct causes for local heavy rainfall. Boundary layer jet plays an important role in dynamic trigger and vapor transport in this process.
2015, 41(8):964-969.
DOI: 10.7519/j.issn.1000-0526.2015.08.005
Abstract:
The correlations between frost and temperature, surface temperature, vapor pressure, wind speed and other meteorological factors are discussed in this paper by using the observation data from Anhui Dangshan Weather Station in the winter halfyear (from October to April of the next year) from 2001 to 2013. Using stepwise discriminant analysis method, multiple sets of frost automatic discriminant models for the occurrence of frost are built based on Bayes discriminant method. The results show that: (1) The occurrence of frost is significantly correlated with daily minimum temperature, night temperature of different observation time and surface temperature. The lower the night temperature or the surface temperature is, the larger the possibility of the temperature is lower than the frost point and the greater the possibility of the frost occurrence. (2) Through the back calculation test and prediction test of independent samples, the average accuracy rate of unoccurred frost discriminated by the frost model is 86.5% based on Bayes discriminant method and the average accuracy rate of the seen frost is 92.7%. The three factor models based on the daily minimum temperature, the daily vapor pressure at 07:00 BT and the daily wind speed at 07:00 BT are optimal. The accuracy rate of discriminating the frost occurrence by the three factor models is more than 90%. Therefore, we can combine the Bayes frost discriminant model with image recognition technology, and apply the new technology to frost automatic observation.
The correlations between frost and temperature, surface temperature, vapor pressure, wind speed and other meteorological factors are discussed in this paper by using the observation data from Anhui Dangshan Weather Station in the winter halfyear (from October to April of the next year) from 2001 to 2013. Using stepwise discriminant analysis method, multiple sets of frost automatic discriminant models for the occurrence of frost are built based on Bayes discriminant method. The results show that: (1) The occurrence of frost is significantly correlated with daily minimum temperature, night temperature of different observation time and surface temperature. The lower the night temperature or the surface temperature is, the larger the possibility of the temperature is lower than the frost point and the greater the possibility of the frost occurrence. (2) Through the back calculation test and prediction test of independent samples, the average accuracy rate of unoccurred frost discriminated by the frost model is 86.5% based on Bayes discriminant method and the average accuracy rate of the seen frost is 92.7%. The three factor models based on the daily minimum temperature, the daily vapor pressure at 07:00 BT and the daily wind speed at 07:00 BT are optimal. The accuracy rate of discriminating the frost occurrence by the three factor models is more than 90%. Therefore, we can combine the Bayes frost discriminant model with image recognition technology, and apply the new technology to frost automatic observation.
2015, 41(8):970-979.
DOI: 10.7519/j.issn.1000-0526.2015.08.006
Abstract:
Using grided data from 2419 stations of National Meteorological Information Centre during 2012-2013 and the TRMM (3B40RT, 3B41RT, 3B42RT), CMORPH, GSMaP, HYDRO satellitederived rainfall data, this paper evaluated and discussed the validation of rainfall estimates from the six data with 0.25°×0.25° spatial resolution and the accuracy of the retrieved daily rainfall products over the whole China, Eastern China and Western China. Results show that the accuracy of satellitederived data is higher in spring, summer and autumn than in winter. The linear correlation coefficient, mean absolute error (MAE), root mean square error (RMSE), probability of detection (POD), and the false alarm ratio (FAR) change with seasons. Meanwhile, the index of each data is better in summer than in winter. The quantitative statistical metrics are obviously different, changing in monthly scale. The estimate ability of satellitederived rainfall is poor when estimating solid and smallamount precipitation. For the large range of precipitation events over China, all the 6 rainfall products have better result. The better quality is realized by merging multisources, and the worse quality results from singlesource microwave, infrared or visible light. The 3B42RT retrieves better falling area of rainfall, but extreme value is larger. The comprehensive evaluation of the CMORPH is better than others. The spatial distribution of accuracy of satellitederived rainfall is related to terrains of China.
Using grided data from 2419 stations of National Meteorological Information Centre during 2012-2013 and the TRMM (3B40RT, 3B41RT, 3B42RT), CMORPH, GSMaP, HYDRO satellitederived rainfall data, this paper evaluated and discussed the validation of rainfall estimates from the six data with 0.25°×0.25° spatial resolution and the accuracy of the retrieved daily rainfall products over the whole China, Eastern China and Western China. Results show that the accuracy of satellitederived data is higher in spring, summer and autumn than in winter. The linear correlation coefficient, mean absolute error (MAE), root mean square error (RMSE), probability of detection (POD), and the false alarm ratio (FAR) change with seasons. Meanwhile, the index of each data is better in summer than in winter. The quantitative statistical metrics are obviously different, changing in monthly scale. The estimate ability of satellitederived rainfall is poor when estimating solid and smallamount precipitation. For the large range of precipitation events over China, all the 6 rainfall products have better result. The better quality is realized by merging multisources, and the worse quality results from singlesource microwave, infrared or visible light. The 3B42RT retrieves better falling area of rainfall, but extreme value is larger. The comprehensive evaluation of the CMORPH is better than others. The spatial distribution of accuracy of satellitederived rainfall is related to terrains of China.
2015, 41(8):980-985.
DOI: 10.7519/j.issn.1000-0526.2015.08.007
Abstract:
Using thermal balance equation during the process of hail melting, the approximate relationship of 0℃ layer height (h0) and hail melting ability was obtained, and the influence of h0 to zero layer hail radius (r0) and ground hail radius (rg) was analyzed under the condition of small scale hail. The results show that rg changes with h0 and r0, so the hail cloud index setting such as radar echo height and center intensity is related to the change of h0, when h0 changes in the range of 2000-6000 m, the threshold of minimum zero layer hail radius changes between 0.32 cm to 1.08 cm, and the threshold of minimum updraft velocity changes from 11.5 m·s-1 to 21.2 m·s-1. The results show a general understanding on the change of 0℃ layer height to hail melting, which can provide a reference for hail forecast and hailsuppression operation, and reduce the false alarm rate of WSR88D enhanced HDA algorithm in hail size predication.
Using thermal balance equation during the process of hail melting, the approximate relationship of 0℃ layer height (h0) and hail melting ability was obtained, and the influence of h0 to zero layer hail radius (r0) and ground hail radius (rg) was analyzed under the condition of small scale hail. The results show that rg changes with h0 and r0, so the hail cloud index setting such as radar echo height and center intensity is related to the change of h0, when h0 changes in the range of 2000-6000 m, the threshold of minimum zero layer hail radius changes between 0.32 cm to 1.08 cm, and the threshold of minimum updraft velocity changes from 11.5 m·s-1 to 21.2 m·s-1. The results show a general understanding on the change of 0℃ layer height to hail melting, which can provide a reference for hail forecast and hailsuppression operation, and reduce the false alarm rate of WSR88D enhanced HDA algorithm in hail size predication.
2015, 41(8):986-996.
DOI: 10.7519/j.issn.1000-0526.2015.08.008
Abstract:
Main basic methods of analysis and assimilation for numerical weather prediction (NWP) has gone through the polynomial function fitting method, the successive correction method (SCM), the optimum interpolation (OI), the variational method (Var) and the ensemble Kalman filter (EnKF). This article tries to present a concise and true description with their basic ideas and implementation approaches based on original classical references to these methods. Then remarks on their distinct characteristics and innovative development are made, and it is highlighted, from these remarks, that we can see a stepbystep expansion of useful information and cutdown on limitations along the historical progress of atmospheric data assimilation, which is clearly endowed with a foreandaft connection and a cognitively simple internal logic of development. Also, an effort is taken to precisely understand the concept of “atmospheric data assimilation”, along its historical progress and on basis of some essential terms “subjective analysis” and “objective analysis”, “first guess field” and “background field”, “analysis” and “assimilation”, “update”, and “innovation”.
Main basic methods of analysis and assimilation for numerical weather prediction (NWP) has gone through the polynomial function fitting method, the successive correction method (SCM), the optimum interpolation (OI), the variational method (Var) and the ensemble Kalman filter (EnKF). This article tries to present a concise and true description with their basic ideas and implementation approaches based on original classical references to these methods. Then remarks on their distinct characteristics and innovative development are made, and it is highlighted, from these remarks, that we can see a stepbystep expansion of useful information and cutdown on limitations along the historical progress of atmospheric data assimilation, which is clearly endowed with a foreandaft connection and a cognitively simple internal logic of development. Also, an effort is taken to precisely understand the concept of “atmospheric data assimilation”, along its historical progress and on basis of some essential terms “subjective analysis” and “objective analysis”, “first guess field” and “background field”, “analysis” and “assimilation”, “update”, and “innovation”.
2015, 41(8):997-1006.
DOI: 10.7519/j.issn.1000-0526.2015.08.009
Abstract:
This article tries to summarize and synthetically remark several basic aspects and common inherent characteristics of atmospheric data assimilation. Such a logic line is highlighted from “what’s data assimilation problem”, to “how is data assimilated”, and to “what are the inherent requirements for the resulting analysis”. The logic correspondingly involves “inverse problem and a priori information”, “input, weight, propagation and smoothing of observation information”, and “requirements of accuracy and consistency for the analysis”. Also, we lay emphasis on some common inherent characteristics, including “equivalences between variational method and optimal interpolation method and between fourdimensional variational method and extended Kalman filter method”, “the dominant role of mathematics in assimilation methods”, “multidisciplinary knowledge connotated in assimilation methods” and “system engineering required in operational assimilation systems”.
This article tries to summarize and synthetically remark several basic aspects and common inherent characteristics of atmospheric data assimilation. Such a logic line is highlighted from “what’s data assimilation problem”, to “how is data assimilated”, and to “what are the inherent requirements for the resulting analysis”. The logic correspondingly involves “inverse problem and a priori information”, “input, weight, propagation and smoothing of observation information”, and “requirements of accuracy and consistency for the analysis”. Also, we lay emphasis on some common inherent characteristics, including “equivalences between variational method and optimal interpolation method and between fourdimensional variational method and extended Kalman filter method”, “the dominant role of mathematics in assimilation methods”, “multidisciplinary knowledge connotated in assimilation methods” and “system engineering required in operational assimilation systems”.
2015, 41(8):1007-1016.
DOI: 10.7519/j.issn.1000-0526.2015.08.010
Abstract:
Based on the parallel daily air temperature data of automatic and manual observations at 143 national benchmark stations from 2002 to 2010, systematic comparative analysis and objective evaluation of differences are made, especially focusing on the large differences and their causes. The impact of automatic observation on the homogeneity of temperature time series is evaluated using the penalized maximal t test (PMT) combined with the metadata of observation instrument changes. The results show that: (1) 51.29%, 54.14%, and 67.18% of daily average, highest, lowest temperatures obtained by AWS (automatic weather station) are greater than the values by manual observation and the percentage of difference between ±0.2℃ respectively accounts for 78.8%, 63.1%, and 60.9%. Average difference values of daily average, highest, lowest temperature are 0.05℃, 0.09℃ and 0.15℃, and the standard deviations are 0.14℃, 0.22℃ and 0.15℃, respectively. The difference, absolute difference value and standard deviation of all temperature elements have no apparent increasing or decreasing trend along with the observation time of AWS and their spatial distributions are different. (2) By the classification comparison and screening of the difference value, absolute difference value and standard deviation step by step, some differences are found greater at a few stations and the differences of the average, the highest and lowest temperatures collected from the same sensor are different as well. By the check of PMT, the inhomogeneous breakpoints are found in the monthly average temperature time series, monthly average maximum temperature time series of 35% station and monthly average minimum temperature time series of 25% stations among the 20 stations with largest absolute difference values of average, maximum and minimum temperatures. (3) The change of calibration error of temperature sensor is the important reason for difference jump between automatic and manual observations. The instrument failures, such as zero drift of electronic components of temperature sensor or data collector can lead temperature obtained by AWS to deviate greatly from the value of manual observation. The above two facts are the main causes for greater differences in temperature between automatic and manual observations, and also possible reasons for inhomogeneous breakpoints of temperature series because of observational instrument changes. Therefore, we suggest strengthening monitoring and quality control for automatic observation data, increasing the observation instrument calibration error correction and realizing the zero temperature compensation adopting methods of hardware and software compensation to reduce or eliminate the instrument error as much as possible and improve the accuracy of the automatic observation data.
Based on the parallel daily air temperature data of automatic and manual observations at 143 national benchmark stations from 2002 to 2010, systematic comparative analysis and objective evaluation of differences are made, especially focusing on the large differences and their causes. The impact of automatic observation on the homogeneity of temperature time series is evaluated using the penalized maximal t test (PMT) combined with the metadata of observation instrument changes. The results show that: (1) 51.29%, 54.14%, and 67.18% of daily average, highest, lowest temperatures obtained by AWS (automatic weather station) are greater than the values by manual observation and the percentage of difference between ±0.2℃ respectively accounts for 78.8%, 63.1%, and 60.9%. Average difference values of daily average, highest, lowest temperature are 0.05℃, 0.09℃ and 0.15℃, and the standard deviations are 0.14℃, 0.22℃ and 0.15℃, respectively. The difference, absolute difference value and standard deviation of all temperature elements have no apparent increasing or decreasing trend along with the observation time of AWS and their spatial distributions are different. (2) By the classification comparison and screening of the difference value, absolute difference value and standard deviation step by step, some differences are found greater at a few stations and the differences of the average, the highest and lowest temperatures collected from the same sensor are different as well. By the check of PMT, the inhomogeneous breakpoints are found in the monthly average temperature time series, monthly average maximum temperature time series of 35% station and monthly average minimum temperature time series of 25% stations among the 20 stations with largest absolute difference values of average, maximum and minimum temperatures. (3) The change of calibration error of temperature sensor is the important reason for difference jump between automatic and manual observations. The instrument failures, such as zero drift of electronic components of temperature sensor or data collector can lead temperature obtained by AWS to deviate greatly from the value of manual observation. The above two facts are the main causes for greater differences in temperature between automatic and manual observations, and also possible reasons for inhomogeneous breakpoints of temperature series because of observational instrument changes. Therefore, we suggest strengthening monitoring and quality control for automatic observation data, increasing the observation instrument calibration error correction and realizing the zero temperature compensation adopting methods of hardware and software compensation to reduce or eliminate the instrument error as much as possible and improve the accuracy of the automatic observation data.
2015, 41(8):1017-1022.
DOI: 10.7519/j.issn.1000-0526.2015.08.011
Abstract:
According to the automatic soil moisture monitoring data read from the database of National Meteorological Information Centre (NMIC), the soil bulk density, field capacity and wilting moisture of each station are calculated. In the operational practice, according to the soil maximum hygroscopicity, the lowest threshold of the relative soil moisture is set to be 6%. According to the saturated soil moisture, the top threshold of the relative soil moisture is set to be 190%. According to the diurnal variation characteristics of the soil moisture, the diurnal variation amplitude of the relative soil moisture of 10 cm and 20 cm soil layer is set to 0.1%. The variation range of relative soil moisture with time of representative stations is analyzed. The results show that in the increasing stage of soil moisture, the variation amplitude between hours should be less than the difference of the saturated soil moisture (%) with the previous monitoring data. When the relative soil moisture is larger than 100%, the decline range should be less than the saturated soil moisture (%) minus 95%. And when the relative soil moisture is less than 100%, the decline range should be less than 5%.
According to the automatic soil moisture monitoring data read from the database of National Meteorological Information Centre (NMIC), the soil bulk density, field capacity and wilting moisture of each station are calculated. In the operational practice, according to the soil maximum hygroscopicity, the lowest threshold of the relative soil moisture is set to be 6%. According to the saturated soil moisture, the top threshold of the relative soil moisture is set to be 190%. According to the diurnal variation characteristics of the soil moisture, the diurnal variation amplitude of the relative soil moisture of 10 cm and 20 cm soil layer is set to 0.1%. The variation range of relative soil moisture with time of representative stations is analyzed. The results show that in the increasing stage of soil moisture, the variation amplitude between hours should be less than the difference of the saturated soil moisture (%) with the previous monitoring data. When the relative soil moisture is larger than 100%, the decline range should be less than the saturated soil moisture (%) minus 95%. And when the relative soil moisture is less than 100%, the decline range should be less than 5%.
2015, 41(8):1023-1027.
DOI: 10.7519/j.issn.1000-0526.2015.08.012
Abstract:
This paper discusses two problems on calibration of windprofiling radar. Firstly, based on the calibration principle of echo intensity, it analyzes the effect of variations in transmitted power and receiver gain on measurement accuracy of echo intensity using weather radar equation. In addition, it puts forward a method to improve measurement accuracy of echo intensity by measuring sampled transmitted pulse and backscattered power at the output of digital receiver during each pulse repetition time. Secondly, according to calibration principle of velocity, it analyzes the image spectral component caused by imbalance in amplitude and phase of I/Q signals in velocity calibration. Moreover, it presents a correction method based on statistical characteristics of time domain signals. What’s more, simulation experiment is conducted using mathematic models for I/Q signals. And the result shows that this method can suppress the image spectral component effectively.
This paper discusses two problems on calibration of windprofiling radar. Firstly, based on the calibration principle of echo intensity, it analyzes the effect of variations in transmitted power and receiver gain on measurement accuracy of echo intensity using weather radar equation. In addition, it puts forward a method to improve measurement accuracy of echo intensity by measuring sampled transmitted pulse and backscattered power at the output of digital receiver during each pulse repetition time. Secondly, according to calibration principle of velocity, it analyzes the image spectral component caused by imbalance in amplitude and phase of I/Q signals in velocity calibration. Moreover, it presents a correction method based on statistical characteristics of time domain signals. What’s more, simulation experiment is conducted using mathematic models for I/Q signals. And the result shows that this method can suppress the image spectral component effectively.
2015, 41(8):1028-1035.
DOI: 10.7519/j.issn.1000-0526.2015.08.013
Abstract:
Data Fusion Effect and Advantage Analysis of MultiSensor Automatic Weather Station
Data Fusion Effect and Advantage Analysis of MultiSensor Automatic Weather Station
2015, 41(8):1036-1041.
DOI: 10.7519/j.issn.1000-0526.2015.08.014
Abstract:
The performances of mediumrange forecasts are verified and compared for T639, ECMWF (EC) and Japan models from March to May 2015. The results show that the three models have good performance on predicting the largescale circulation and 850 hPa temperature evolution and adjustment in Asian middle and high latitude areas. EC shows a better performance on westerly index and 850 hPa temperature than the other two models. Taking the sandstorm process from 31 March to 1 April as a case, it is found that all the three models have predicted the intensity and affected range of the major weather for sandstorm, but compared with observations some biases also exist.
The performances of mediumrange forecasts are verified and compared for T639, ECMWF (EC) and Japan models from March to May 2015. The results show that the three models have good performance on predicting the largescale circulation and 850 hPa temperature evolution and adjustment in Asian middle and high latitude areas. EC shows a better performance on westerly index and 850 hPa temperature than the other two models. Taking the sandstorm process from 31 March to 1 April as a case, it is found that all the three models have predicted the intensity and affected range of the major weather for sandstorm, but compared with observations some biases also exist.
2015, 41(8):1042-1048.
DOI: 10.7519/j.issn.1000-0526.2015.08.015
Abstract:
The performances of mediumrange forecasts are verified and compared for T639, ECMWF (EC) and Japan models from March to May 2015. The results show that the three models have good performance on predicting the largescale circulation and 850 hPa temperature evolution and adjustment in Asian middle and high latitude areas. EC shows a better performance on westerly index and 850 hPa temperature than the other two models. Taking the sandstorm process from 31 March to 1 April as a case, it is found that all the three models have predicted the intensity and affected range of the major weather for sandstorm, but compared with observations some biases also exist.
The performances of mediumrange forecasts are verified and compared for T639, ECMWF (EC) and Japan models from March to May 2015. The results show that the three models have good performance on predicting the largescale circulation and 850 hPa temperature evolution and adjustment in Asian middle and high latitude areas. EC shows a better performance on westerly index and 850 hPa temperature than the other two models. Taking the sandstorm process from 31 March to 1 April as a case, it is found that all the three models have predicted the intensity and affected range of the major weather for sandstorm, but compared with observations some biases also exist.
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ISSN:1000-0526 CN:11-2282/P