Panicle architecture is closely related to yield formation. The qPE9-1 gene has been proved to be widely used in high-yield rice cultivar developments, conferring erect panicle character in japonica rice. Recently, qP...Panicle architecture is closely related to yield formation. The qPE9-1 gene has been proved to be widely used in high-yield rice cultivar developments, conferring erect panicle character in japonica rice. Recently, qPE9-1 has been successfully cloned; however, the genetic effect on grain yield per plant of the erect panicle allele qPE9-1 is controversial yet. In the present study, a drooping panicle parent Nongken 57, carrying qpe9-1 allele, was used as recurrent parent to successively backcross to a typical erect panicle line from the double haploid （DH） population （Wuyunjing 8/Nongken 57）, which was previously shown to carry qPE9-1 allele. Thus a pair of near-isogenic lines （NILs） was developed. The comparison of agronomic traits between the NILs showed that, when qpe9-1 was replaced by qPE9-1, the panicle architecture was changed from drooping to erect; moreover, the panicle length, plant height, 1000-grain weight and the tillers were significantly decreased, consequently resulting in the dramatic decrease of grain yield per plant by 30%. Therefore, we concluded that the qPE9-1 was a major factor controlling panicle architecture, and qPE9-1 had pleiotropic nature, with negative effects on grain yield per plant. This result strongly suggests that the erect panicle allele qPEg-1 should be used together with other favorable genes in the high-yield breeding practice. In addition, the effect of qPE9-1 on eating and cooking quality was also discussed in the present study.展开更多
The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of signifi- cant overestimation in quantitative precipitation estimation （QPE） based on the Z-R （refl...The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of signifi- cant overestimation in quantitative precipitation estimation （QPE） based on the Z-R （reflectivity factor-rain rate） relationship. The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity （VPR） correction. In this study, we applied bright-band correction algorithms to evaluate three different bands （S-, C- and X-band） of dual-polarized radars and to reduce overestimation errors in Z-R relationship-based QPEs. After the reflectivity was corrected by the algo- rithms using average VPR （AVPR） alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient （AVPR＋CC）, the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gange observations, separately. The overestimation of Z-R relationship-based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE （root-mean-square error）, RMAE （relative mean absolute error） and RMB （relative mean bias） of QPEs, averaged over all eight cases, the AVPR method improved from 2.28, 0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR＋CC method improved to 1.44, 0.55 and 0.30, respectively. The QPEs after AVPR＋CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.展开更多
As an emerging meteorological detection tool,X-band dual polarization radar has gradually become an important means of radar quantitative precipitation estimation(QPE)due to its high spatial resolution and sensitivity...As an emerging meteorological detection tool,X-band dual polarization radar has gradually become an important means of radar quantitative precipitation estimation(QPE)due to its high spatial resolution and sensitivity.In this paper,utilizing the advantages of polarization parameters of dual polarization radar,the QPE product of Guigang X-band radar was optimized,and the optimized algorithm results were compared with the QPE products of surrounding Nanning and Yulin S-band radars.The results showed that the optimized method using polarization parameters of horizontal reflectance factor(Z H)and differential reflectivity(Z DR)had higher consistency between the QPE product of Guigang X-band radar and the measured precipitation of automatic weather stations.In terms of quantitative precipitation estimation,Guigang X-band radar was slightly inferior to Nanning and Yulin S-band radars.展开更多
In this study,a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is employed to investigate the temporal-spatial variability of raindrop size distributions(DSDs)in the Zhengzhou ex...In this study,a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is employed to investigate the temporal-spatial variability of raindrop size distributions(DSDs)in the Zhengzhou extreme rainfall event on 20 July 2021.The rain rates observed by disdrometers and rain gauges from six operational sites are in good agreement,despite significant site-to-site variations of 24-h accumulated rainfall ranging from 198.3 to 624.1 mm.The Parsivel OTT observations show prominent temporal-spatial variations of DSDs,and the most drastic change was registered at Zhengzhou Station where the record-breaking hourly rainfall of 201.9 mm over 1500-1600 LST(local standard time)was reported.This hourly rainfall is characterized by fairly high concentrations of large raindrops,and the mass-weighted raindrop diameter generally increases with the rain rate before reaching the equilibrium state of DSDs with the rain rate of about 50 mm h^(−1).Besides,polarimetric radar observations show the highest differential phase shift(K_(dp))and differential reflectivity(Z_(dr))near surface over Zhengzhou Station from 1500 to 1600 LST.In light of the remarkable temporal-spatial variability of DSDs,a reflectivity-grouped fitting approach is proposed to optimize the reflectivity-rain rate(Z-R)parameterization for radar quantitative precipitation estimation(QPE),and the rain gauge measurements are used for validation.The results show an increase of mean bias ratio from 0.57 to 0.79 and a decrease of root-mean-square error from 23.69 to 18.36 for the rainfall intensity above 20.0 mm h^(−1),as compared with the fixed Z-R parameterization.This study reveals the drastic temporal-spatial variations of rain microphysics during the Zhengzhou extreme rainfall event and warrants the promise of using reflectivity-grouped fitting Z-R relationships for radar QPE of such events.展开更多
Long-term rainfall data are crucial for flood simulations and forecasting in karst regions.However,in karst areas,there is often a lack of suitable precipitation data available to build distributed hydrological models...Long-term rainfall data are crucial for flood simulations and forecasting in karst regions.However,in karst areas,there is often a lack of suitable precipitation data available to build distributed hydrological models to forecast karst floods.Quantitative precipitation forecasts(QPFs)and estimates(QPEs)could provide rational methods to acquire the available precipitation data for karst areas.Furthermore,coupling a physically based hydrological model with QPFs and QPEs could greatly enhance the performance and extend the lead time of flood forecasting in karst areas.This study served two main purposes.One purpose was to compare the performance of the Weather Research and Forecasting(WRF)QPFs with that of the Precipitation Estimations through Remotely Sensed Information based on the Artificial Neural Network-Cloud Classification System(PERSIANN-CCS)QPEs in rainfall forecasting in karst river basins.The other purpose was to test the feasibility and effective application of karst flood simulation and forecasting by coupling the WRF and PERSIANN models with the Karst-Liuxihe model.The rainfall forecasting results showed that the precipitation distributions of the 2 weather models were very similar to the observed rainfall results.However,the precipitation amounts forecasted by WRF QPF were larger than those measured by the rain gauges,while the quantities forecasted by the PERSIANN-CCS QPEs were smaller.A postprocessing algorithm was proposed in this paper to correct the rainfall estimates produced by the two weather models.The flood simulations achieved based on the postprocessed WRF QPF and PERSIANN-CCS QPEs coupled with the Karst-Liuxihe model were much improved over previous results.In particular,coupling the postprocessed WRF QPF with the Karst-Liuxihe model could greatly extend the lead time of flood forecasting,and a maximum lead time of 96 h is adequate for flood warnings and emergency responses,which is extremely important in flood simulations and forecasting.展开更多
基金supported by the Ministry of Science and Technology(Grant No.2006AA10Z118)National Natural Science Foundation(Grant No.30771323 and 30871501)the Jiangsu Province Government of China(Grant No.08KJA210002)
文摘Panicle architecture is closely related to yield formation. The qPE9-1 gene has been proved to be widely used in high-yield rice cultivar developments, conferring erect panicle character in japonica rice. Recently, qPE9-1 has been successfully cloned; however, the genetic effect on grain yield per plant of the erect panicle allele qPE9-1 is controversial yet. In the present study, a drooping panicle parent Nongken 57, carrying qpe9-1 allele, was used as recurrent parent to successively backcross to a typical erect panicle line from the double haploid （DH） population （Wuyunjing 8/Nongken 57）, which was previously shown to carry qPE9-1 allele. Thus a pair of near-isogenic lines （NILs） was developed. The comparison of agronomic traits between the NILs showed that, when qpe9-1 was replaced by qPE9-1, the panicle architecture was changed from drooping to erect; moreover, the panicle length, plant height, 1000-grain weight and the tillers were significantly decreased, consequently resulting in the dramatic decrease of grain yield per plant by 30%. Therefore, we concluded that the qPE9-1 was a major factor controlling panicle architecture, and qPE9-1 had pleiotropic nature, with negative effects on grain yield per plant. This result strongly suggests that the erect panicle allele qPEg-1 should be used together with other favorable genes in the high-yield breeding practice. In addition, the effect of qPE9-1 on eating and cooking quality was also discussed in the present study.
基金funded by a China National 973 Program on Key Basic Research project (Grant No.2014CB441401)the Beijing Municipal Natural Science Foundation (Grant No.8141002)the Public Welfare Industry (Meteorology) of China (Grant No.GYHY201106046)
文摘The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of signifi- cant overestimation in quantitative precipitation estimation （QPE） based on the Z-R （reflectivity factor-rain rate） relationship. The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity （VPR） correction. In this study, we applied bright-band correction algorithms to evaluate three different bands （S-, C- and X-band） of dual-polarized radars and to reduce overestimation errors in Z-R relationship-based QPEs. After the reflectivity was corrected by the algo- rithms using average VPR （AVPR） alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient （AVPR＋CC）, the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gange observations, separately. The overestimation of Z-R relationship-based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE （root-mean-square error）, RMAE （relative mean absolute error） and RMB （relative mean bias） of QPEs, averaged over all eight cases, the AVPR method improved from 2.28, 0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR＋CC method improved to 1.44, 0.55 and 0.30, respectively. The QPEs after AVPR＋CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.
基金Supported by Guangxi Meteorological Research Program Project(GUIQIKE 2023M28,GUIQIKE 2023M27,GUIQIKE 2023QN16).
文摘As an emerging meteorological detection tool,X-band dual polarization radar has gradually become an important means of radar quantitative precipitation estimation(QPE)due to its high spatial resolution and sensitivity.In this paper,utilizing the advantages of polarization parameters of dual polarization radar,the QPE product of Guigang X-band radar was optimized,and the optimized algorithm results were compared with the QPE products of surrounding Nanning and Yulin S-band radars.The results showed that the optimized method using polarization parameters of horizontal reflectance factor(Z H)and differential reflectivity(Z DR)had higher consistency between the QPE product of Guigang X-band radar and the measured precipitation of automatic weather stations.In terms of quantitative precipitation estimation,Guigang X-band radar was slightly inferior to Nanning and Yulin S-band radars.
基金Supported by the National Key Research and Development Program of China(2022YFC3003901)National Natural Science Foundation of China(42305087 and 42105141)+2 种基金Science and Technology Innovation Project for Ecosystem Construction of Zhengzhou Supercomputing Center in Henan Province(201400210800)Meteorological Joint Project of Henan Provincial Science and Technology(222103810094 and 232103810091)Basic Research Fund of Chinese Academy of Meteorological Sciences(451490 and 2023Z008).
文摘In this study,a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is employed to investigate the temporal-spatial variability of raindrop size distributions(DSDs)in the Zhengzhou extreme rainfall event on 20 July 2021.The rain rates observed by disdrometers and rain gauges from six operational sites are in good agreement,despite significant site-to-site variations of 24-h accumulated rainfall ranging from 198.3 to 624.1 mm.The Parsivel OTT observations show prominent temporal-spatial variations of DSDs,and the most drastic change was registered at Zhengzhou Station where the record-breaking hourly rainfall of 201.9 mm over 1500-1600 LST(local standard time)was reported.This hourly rainfall is characterized by fairly high concentrations of large raindrops,and the mass-weighted raindrop diameter generally increases with the rain rate before reaching the equilibrium state of DSDs with the rain rate of about 50 mm h^(−1).Besides,polarimetric radar observations show the highest differential phase shift(K_(dp))and differential reflectivity(Z_(dr))near surface over Zhengzhou Station from 1500 to 1600 LST.In light of the remarkable temporal-spatial variability of DSDs,a reflectivity-grouped fitting approach is proposed to optimize the reflectivity-rain rate(Z-R)parameterization for radar quantitative precipitation estimation(QPE),and the rain gauge measurements are used for validation.The results show an increase of mean bias ratio from 0.57 to 0.79 and a decrease of root-mean-square error from 23.69 to 18.36 for the rainfall intensity above 20.0 mm h^(−1),as compared with the fixed Z-R parameterization.This study reveals the drastic temporal-spatial variations of rain microphysics during the Zhengzhou extreme rainfall event and warrants the promise of using reflectivity-grouped fitting Z-R relationships for radar QPE of such events.
基金This study was supported by the National Science Foundation for Young Scientists of China(No.42101031)Chongqing Natural Science Foundation(No.cstc2021jcyj-msxm0007)+1 种基金the Open Project Program of Guangxi Key Science and Technology Innovation Base on Karst Dynamics(KDL&Guangxi 202009,KDL&Guangxi 202012)the National Natural Science Foundation of China(Grant No.41830648).
文摘Long-term rainfall data are crucial for flood simulations and forecasting in karst regions.However,in karst areas,there is often a lack of suitable precipitation data available to build distributed hydrological models to forecast karst floods.Quantitative precipitation forecasts(QPFs)and estimates(QPEs)could provide rational methods to acquire the available precipitation data for karst areas.Furthermore,coupling a physically based hydrological model with QPFs and QPEs could greatly enhance the performance and extend the lead time of flood forecasting in karst areas.This study served two main purposes.One purpose was to compare the performance of the Weather Research and Forecasting(WRF)QPFs with that of the Precipitation Estimations through Remotely Sensed Information based on the Artificial Neural Network-Cloud Classification System(PERSIANN-CCS)QPEs in rainfall forecasting in karst river basins.The other purpose was to test the feasibility and effective application of karst flood simulation and forecasting by coupling the WRF and PERSIANN models with the Karst-Liuxihe model.The rainfall forecasting results showed that the precipitation distributions of the 2 weather models were very similar to the observed rainfall results.However,the precipitation amounts forecasted by WRF QPF were larger than those measured by the rain gauges,while the quantities forecasted by the PERSIANN-CCS QPEs were smaller.A postprocessing algorithm was proposed in this paper to correct the rainfall estimates produced by the two weather models.The flood simulations achieved based on the postprocessed WRF QPF and PERSIANN-CCS QPEs coupled with the Karst-Liuxihe model were much improved over previous results.In particular,coupling the postprocessed WRF QPF with the Karst-Liuxihe model could greatly extend the lead time of flood forecasting,and a maximum lead time of 96 h is adequate for flood warnings and emergency responses,which is extremely important in flood simulations and forecasting.
