Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a de...Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.展开更多
After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve we...After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.展开更多
A new Suboptimal Maximum Likelihood Estimation (SMLE) algorithm based on full-deramp model and its implementation in satellite-borne radar altimeter are presented, with emphasis on the influence of both the return flu...A new Suboptimal Maximum Likelihood Estimation (SMLE) algorithm based on full-deramp model and its implementation in satellite-borne radar altimeter are presented, with emphasis on the influence of both the return fluctuation and the receiver noise on height and slope estimation precision. Some conclusions are obtained and verified by computer simulation.展开更多
A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter,chaff,clear air echoes etc.In this study,a fuzzy logic algorithm f...A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter,chaff,clear air echoes etc.In this study,a fuzzy logic algorithm for the identification of non-meteorological echoes is developed using optimized membership functions and weights for the dual-polarization radar located at Mount Sobaek.For selected precipitation and non-meteorological events,the characteristics of the precipitation and non-meteorological echo are derived by the probability density functions of five fuzzy parameters as functions of reflectivity values.The membership functions and weights are then determined by these density functions.Finally,the nonmeteorological echoes are identified by combining the membership functions and weights.The performance is qualitatively evaluated by long-term rain accumulation.The detection accuracy of the fuzzy logic algorithm is calculated using the probability of detection（POD）,false alarm rate（FAR）,and clutter–signal ratio（CSR）.In addition,the issues in using filtered dual-polarization data are alleviated.展开更多
This study presents the radar-based characteristics and formation environment of supercells spawned by the tornadic landfalling Typhoon Mujigae(2015)in October 2015.More than 100 supercells were identified within a 24...This study presents the radar-based characteristics and formation environment of supercells spawned by the tornadic landfalling Typhoon Mujigae(2015)in October 2015.More than 100 supercells were identified within a 24-hour period around the time of the typhoon’s landfall,of which three were tornadic with a rotational intensity clearly stronger than those of non-tornadic supercells.The identified supercells were concentrated within a relatively small area in the northeast quadrant beyond 140 km from the typhoon center.These supercells were found more likely to form over flat topography and were difficult to maintain in mountainous regions.During the study period,more supercells formed offshore than onshore.The mesocyclones of the identified supercells were characterized by a small diameter generally less than 5 km and a shallow depth generally less than 4 km above ground level.An environmental analysis revealed that the northeast quadrant had the most favorable conditions for the genesis of supercell in this typhoon case.The nondimensional supercell composite parameter(SCP)and entraining-SCP(E-SCP)were effective in separating supercell from non-supercell environment.Even though the atmosphere in the typhoon’s northeast quadrant was characterized by an E-SCP/SCP value supportive of supercell organization,orography was an impeditive factor for the supercell development.These findings support the use of traditional parameters obtained from midlatitude supercells to assess the supercell potential in a tropical cyclone envelope.展开更多
基金supported by the China Ministry of Industry and Information Technology Foundation and Aeronautical Science Foundation of China(ASFC-201920007002)the National Key Research and Development Plan(2021YFB1600603)the Open Fund of Key Laboratory of Civil Aircraft Airworthiness Technology,Civil Aviation University of China.
文摘Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.
基金supported by the NOAA (Grant Nos. NA16AOR4320115 and NA11OAR4320072)NSF (Grant No. AGS-1341878)
文摘After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.
文摘A new Suboptimal Maximum Likelihood Estimation (SMLE) algorithm based on full-deramp model and its implementation in satellite-borne radar altimeter are presented, with emphasis on the influence of both the return fluctuation and the receiver noise on height and slope estimation precision. Some conclusions are obtained and verified by computer simulation.
基金supported by a grant(14AWMP-B079364-01) from Water Management Research Program funded by Ministry of Land,Infrastructure and Transport of Korean government
文摘A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter,chaff,clear air echoes etc.In this study,a fuzzy logic algorithm for the identification of non-meteorological echoes is developed using optimized membership functions and weights for the dual-polarization radar located at Mount Sobaek.For selected precipitation and non-meteorological events,the characteristics of the precipitation and non-meteorological echo are derived by the probability density functions of five fuzzy parameters as functions of reflectivity values.The membership functions and weights are then determined by these density functions.Finally,the nonmeteorological echoes are identified by combining the membership functions and weights.The performance is qualitatively evaluated by long-term rain accumulation.The detection accuracy of the fuzzy logic algorithm is calculated using the probability of detection（POD）,false alarm rate（FAR）,and clutter–signal ratio（CSR）.In addition,the issues in using filtered dual-polarization data are alleviated.
基金funded fun-ded by the National Natural Science Foundation of China(Grant Nos.41875051 and 41905043)the China Postdoctoral Sci-ence Foundation(Grant No.2019M653146)。
文摘This study presents the radar-based characteristics and formation environment of supercells spawned by the tornadic landfalling Typhoon Mujigae(2015)in October 2015.More than 100 supercells were identified within a 24-hour period around the time of the typhoon’s landfall,of which three were tornadic with a rotational intensity clearly stronger than those of non-tornadic supercells.The identified supercells were concentrated within a relatively small area in the northeast quadrant beyond 140 km from the typhoon center.These supercells were found more likely to form over flat topography and were difficult to maintain in mountainous regions.During the study period,more supercells formed offshore than onshore.The mesocyclones of the identified supercells were characterized by a small diameter generally less than 5 km and a shallow depth generally less than 4 km above ground level.An environmental analysis revealed that the northeast quadrant had the most favorable conditions for the genesis of supercell in this typhoon case.The nondimensional supercell composite parameter(SCP)and entraining-SCP(E-SCP)were effective in separating supercell from non-supercell environment.Even though the atmosphere in the typhoon’s northeast quadrant was characterized by an E-SCP/SCP value supportive of supercell organization,orography was an impeditive factor for the supercell development.These findings support the use of traditional parameters obtained from midlatitude supercells to assess the supercell potential in a tropical cyclone envelope.
