2021 Vol. 27, No. 1
2021, 27(1): .
Abstract:
2021, 27(1): 1-9.
doi: 10.46267/j.1006-8775.2021.001
Abstract:
In the present study, the performance of the GRAPES model in wind simulation over south China was assessed. The simulations were evaluated by using surface observations and two sounding stations in south China. The results show that the GRAPES model could provide a reliable simulation of the distribution and diurnal variation of the wind. It showed a generally overestimated southerly wind speed especially over the Pearl River Delta region and the south of Jiangxi Province as well as the coastal region over south China. GRAPES also exhibited a large number of stations with the opposite surface wind directions over the east of Guangxi and the south of Jiangxi during the nocturnal-to-morning period, as well as an overall overestimation of surface wind over the coastal regions during the afternoon. Although GRAPES could simulate the general evolutional characteristics of vertical wind profile, it underestimated wind speed above 900 hPa and overestimated wind speed below 900 hPa. Though the parameterization scheme of gravity wave drag proved to be an effective method to alleviate the systematic deviation of wind simulation, GRAPES still exhibited large errors in wind simulation, especially in the lower and upper troposphere.
In the present study, the performance of the GRAPES model in wind simulation over south China was assessed. The simulations were evaluated by using surface observations and two sounding stations in south China. The results show that the GRAPES model could provide a reliable simulation of the distribution and diurnal variation of the wind. It showed a generally overestimated southerly wind speed especially over the Pearl River Delta region and the south of Jiangxi Province as well as the coastal region over south China. GRAPES also exhibited a large number of stations with the opposite surface wind directions over the east of Guangxi and the south of Jiangxi during the nocturnal-to-morning period, as well as an overall overestimation of surface wind over the coastal regions during the afternoon. Although GRAPES could simulate the general evolutional characteristics of vertical wind profile, it underestimated wind speed above 900 hPa and overestimated wind speed below 900 hPa. Though the parameterization scheme of gravity wave drag proved to be an effective method to alleviate the systematic deviation of wind simulation, GRAPES still exhibited large errors in wind simulation, especially in the lower and upper troposphere.
2021, 27(1): 10-23.
doi: 10.46267/j.1006-8775.2021.002
Abstract:
We set four sets of simulation experiments to explore the impacts of horizontal resolution (HR) and vertical resolution (VR) on the microphysical structure and boundary layer fluxes of tropical cyclone (TC) Hato (2017). The study shows that higher HR tends to strengthen TC. Increasing VR in the upper layers tends to weaken TC, while increasing VR in the lower layers tends to strengthen TC. Simulated amounts of all hydrometeors were larger with higher HR. Increasing VR at the upper level enhanced the mixing ratios of cloud ice and cloud snow, while increasing VR at the lower level elevated the mixing ratios of graupel and rainwater. HR has greater impact on the distributions of hydrometeors. Higher HR has a more complete ring structure of the eyewall and more concentrated hydrometeors along the cloud wall. Increasing VR at the lower level has little impact on the distribution of TC hydrometeors, while increasing VR at the upper level enhances the cloud thickness of the eyewall area. Surface latent heat flux (SLHF) is influenced greatly by resolution. Higher HR leads to larger water vapor fluxes and larger latent heat, which would result in a stronger TC. A large amount of false latent heat was generated when HR was too high, leading to an extremely strong TC, VR has a smaller impact on SLHF than HR. But increasing VR at the upper-level reduces the SLHF and weakens TC, and elevating VR at the lower-level increases the SLHF and strengthens TC. The changes in surface water vapor flux and SLHF were practically identical and the simulation results were improved when HR and VR were more coordinated. The friction velocity was greater with higher VR. Enhancing VR at the lower level increased the friction velocity, while increasing VR at the upper level reduced it.
We set four sets of simulation experiments to explore the impacts of horizontal resolution (HR) and vertical resolution (VR) on the microphysical structure and boundary layer fluxes of tropical cyclone (TC) Hato (2017). The study shows that higher HR tends to strengthen TC. Increasing VR in the upper layers tends to weaken TC, while increasing VR in the lower layers tends to strengthen TC. Simulated amounts of all hydrometeors were larger with higher HR. Increasing VR at the upper level enhanced the mixing ratios of cloud ice and cloud snow, while increasing VR at the lower level elevated the mixing ratios of graupel and rainwater. HR has greater impact on the distributions of hydrometeors. Higher HR has a more complete ring structure of the eyewall and more concentrated hydrometeors along the cloud wall. Increasing VR at the lower level has little impact on the distribution of TC hydrometeors, while increasing VR at the upper level enhances the cloud thickness of the eyewall area. Surface latent heat flux (SLHF) is influenced greatly by resolution. Higher HR leads to larger water vapor fluxes and larger latent heat, which would result in a stronger TC. A large amount of false latent heat was generated when HR was too high, leading to an extremely strong TC, VR has a smaller impact on SLHF than HR. But increasing VR at the upper-level reduces the SLHF and weakens TC, and elevating VR at the lower-level increases the SLHF and strengthens TC. The changes in surface water vapor flux and SLHF were practically identical and the simulation results were improved when HR and VR were more coordinated. The friction velocity was greater with higher VR. Enhancing VR at the lower level increased the friction velocity, while increasing VR at the upper level reduced it.
2021, 27(1): 24-33.
doi: 10.46267/j.1006-8775.2021.003
Abstract:
Traditional precipitation skill scores are affected by the well-known"double penalty"problem caused by the slight spatial or temporal mismatches between forecasts and observations. The fuzzy (neighborhood) method has been proposed for deterministic simulations and shown some ability to solve this problem. The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts. We developed an ensemble precipitation verification skill score, i. e., the Spatial Continuous Ranked Probability Score (SCRPS), and used it to extend spatial verification from deterministic into ensemble forecasts. The SCRPS is a spatial technique based on the Continuous Ranked Probability Score (CRPS) and the fuzzy method. A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency, which were then used in the reference score to calculate the skill score of the SCRPS. The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained. The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used.
Traditional precipitation skill scores are affected by the well-known"double penalty"problem caused by the slight spatial or temporal mismatches between forecasts and observations. The fuzzy (neighborhood) method has been proposed for deterministic simulations and shown some ability to solve this problem. The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts. We developed an ensemble precipitation verification skill score, i. e., the Spatial Continuous Ranked Probability Score (SCRPS), and used it to extend spatial verification from deterministic into ensemble forecasts. The SCRPS is a spatial technique based on the Continuous Ranked Probability Score (CRPS) and the fuzzy method. A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency, which were then used in the reference score to calculate the skill score of the SCRPS. The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained. The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used.
2021, 27(1): 34-47.
doi: 10.46267/j.1006-8775.2021.004
Abstract:
In this study, the Weather Research and Forecasting (WRF) model and meteorological observation data were used to research the long-distance moisture transport supply source of the extreme rainfall event that occurred on July 21, 2012 in Beijing. Recording a maximum rainfall amount of 460 mm in 24 h, this rainstorm event had two dominant moisture transport channels. In the early stage of the rainstorm, the first channel comprised southwesterly monsoonal moisture from the Bay of Bengal (BOB) that was directly transported to north China along the eastern edge of Tibetan Plateau (TP) by orographic uplift. During the rainstorm, the southwesterly moisture transport was weakened by the transfer of Typhoon Vicente. Moreover, the southeasterly moisture transport between the typhoon and western Pacific subtropical high (WPSH) became another dominant moisture transport channel. The moisture in the lower troposphere was mainly associated with the southeasterly moisture transport from the South China Sea and the East China Sea, and the moisture in the middle troposphere was mainly transported from the BOB and Indian Ocean. The control experiment well reproduced the distribution and intensity of rainfall and moisture transport. By comparing the control and three sensitivity experiments, we found that the moisture transported from Typhoon Vicente and a tropical cyclone in the BOB both significantly affected this extreme rainfall event. After Typhoon Vicente was removed in a sensitivity experiment, the maximum 24-h accumulated rainfall in north China was reduced by approximately 50% compared with that of the control experiment, while the rainfall after removing the tropical cyclone was reduced by 30%. When both the typhoon and tropical cyclone were removed, the southwesterly moisture transport was enhanced. Moreover, the sensitivity experiment of removing Typhoon Vicente also weakened the tropical cyclone in the BOB. Thus, the moisture pump driven by Typhoon Vicente played an important role in maintaining and strengthening the tropical cyclone in the BOB through its westerly airflow. Typhoon Vicente was not only the moisture transfer source for the southwesterly monsoonal moisture but also affected the tropical cyclone in the BOB, which was a key supply source of long-distance moisture transport for the extreme rainfall event on July 21, 2012 in Beijing.
In this study, the Weather Research and Forecasting (WRF) model and meteorological observation data were used to research the long-distance moisture transport supply source of the extreme rainfall event that occurred on July 21, 2012 in Beijing. Recording a maximum rainfall amount of 460 mm in 24 h, this rainstorm event had two dominant moisture transport channels. In the early stage of the rainstorm, the first channel comprised southwesterly monsoonal moisture from the Bay of Bengal (BOB) that was directly transported to north China along the eastern edge of Tibetan Plateau (TP) by orographic uplift. During the rainstorm, the southwesterly moisture transport was weakened by the transfer of Typhoon Vicente. Moreover, the southeasterly moisture transport between the typhoon and western Pacific subtropical high (WPSH) became another dominant moisture transport channel. The moisture in the lower troposphere was mainly associated with the southeasterly moisture transport from the South China Sea and the East China Sea, and the moisture in the middle troposphere was mainly transported from the BOB and Indian Ocean. The control experiment well reproduced the distribution and intensity of rainfall and moisture transport. By comparing the control and three sensitivity experiments, we found that the moisture transported from Typhoon Vicente and a tropical cyclone in the BOB both significantly affected this extreme rainfall event. After Typhoon Vicente was removed in a sensitivity experiment, the maximum 24-h accumulated rainfall in north China was reduced by approximately 50% compared with that of the control experiment, while the rainfall after removing the tropical cyclone was reduced by 30%. When both the typhoon and tropical cyclone were removed, the southwesterly moisture transport was enhanced. Moreover, the sensitivity experiment of removing Typhoon Vicente also weakened the tropical cyclone in the BOB. Thus, the moisture pump driven by Typhoon Vicente played an important role in maintaining and strengthening the tropical cyclone in the BOB through its westerly airflow. Typhoon Vicente was not only the moisture transfer source for the southwesterly monsoonal moisture but also affected the tropical cyclone in the BOB, which was a key supply source of long-distance moisture transport for the extreme rainfall event on July 21, 2012 in Beijing.
2021, 27(1): 48-61.
doi: 10.46267/j.1006-8775.2021.005
Abstract:
This study uses rain gauge observations to assess the performance of different radar estimators R(ZH), R(KDP) and R(A) in estimating precipitation based on the observations of an S-band polarimetric radar over southern China during a typical convective storm and an extremely severe typhoon, i. e., Typhoon Manghkut. These radar estimators were derived from observations of a local autonomous particle size and velocity (Parsivel) unit (APU) disdrometer. A key parameter, alpha (α), which is the ratio of specific attenuation A to specific differential phase KDP with three fixed values (α=0.015 dB deg-1, α=0.0185 dB deg-1 and α=0.03 dB deg-1) was examined to test the sensitivity of the R(A) rain retrievals. The results show that: (1) All radar estimators can capture the spatio-temporal patterns of two precipitation events, R(A) with α=0.0185 dB deg-1 is well correlated with gauge measurement via higher Pearson's correlation coefficient (CC) of 0.87, lower relative bias (RB) of 16%, and lower root mean square error (RMSE) of 17.09 mm in the convective storm while it underestimates the typhoon event with RB of 35%; (2) R(A) with α=0.03 dB deg-1 shows the best statistical scores with the highest CC (0.92), lowest RB (7%) and RMSE (25.74mm) corresponding to Typhoon Manghkut; (3) R(A) estimates are more efficient in mitigating the impact of partial beam blockage. The results indicate that α is remarkably influenced by the variation of drop size distribution. Thus, more work is needed to establish an automated and optimized α for the R(A) relation during different rainfall events over different regions.
This study uses rain gauge observations to assess the performance of different radar estimators R(ZH), R(KDP) and R(A) in estimating precipitation based on the observations of an S-band polarimetric radar over southern China during a typical convective storm and an extremely severe typhoon, i. e., Typhoon Manghkut. These radar estimators were derived from observations of a local autonomous particle size and velocity (Parsivel) unit (APU) disdrometer. A key parameter, alpha (α), which is the ratio of specific attenuation A to specific differential phase KDP with three fixed values (α=0.015 dB deg-1, α=0.0185 dB deg-1 and α=0.03 dB deg-1) was examined to test the sensitivity of the R(A) rain retrievals. The results show that: (1) All radar estimators can capture the spatio-temporal patterns of two precipitation events, R(A) with α=0.0185 dB deg-1 is well correlated with gauge measurement via higher Pearson's correlation coefficient (CC) of 0.87, lower relative bias (RB) of 16%, and lower root mean square error (RMSE) of 17.09 mm in the convective storm while it underestimates the typhoon event with RB of 35%; (2) R(A) with α=0.03 dB deg-1 shows the best statistical scores with the highest CC (0.92), lowest RB (7%) and RMSE (25.74mm) corresponding to Typhoon Manghkut; (3) R(A) estimates are more efficient in mitigating the impact of partial beam blockage. The results indicate that α is remarkably influenced by the variation of drop size distribution. Thus, more work is needed to establish an automated and optimized α for the R(A) relation during different rainfall events over different regions.
2021, 27(1): 62-69.
doi: 10.46267/j.1006-8775.2021.006
Abstract:
One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles. In this paper, we propose a multiple linear regression method to retrieve sea surface wind speed at an incidence angle between 0°~65°. We assume that a one-dimensional synthetic aperture microwave radiometer operates at frequencies of 6.9, 10.65, 18.7, 23.8 and 36.5 GHz. Then, the microwave radiative transfer forward model is used to simulate the measured brightness temperatures. The sensitivity of the brightness temperatures at 0°~65° to the sea surface wind speed is calculated. Then, vertical polarization channels (VR), horizontal polarization channels (HR) and all channels (AR) are used to retrieve the sea surface wind speed via a multiple linear regression algorithm at 0°~65°, and the relationship between the retrieval error and incidence angle is obtained. The results are as follows: (1) The sensitivity of the vertical polarization brightness temperature to the sea surface wind speed is smaller than that of the horizontal polarization. (2) The retrieval error increases with Gaussian noise. The retrieval error of VR first increases and then decreases with increasing incidence angle, the retrieval error of HR gradually decreases with increasing incidence angle, and the retrieval error of AR first decreases and then increases with increasing incidence angle. (3) The retrieval error of AR is the lowest and it is necessary to retrieve the sea surface wind speed at a larger incidence angle for AR.
One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles. In this paper, we propose a multiple linear regression method to retrieve sea surface wind speed at an incidence angle between 0°~65°. We assume that a one-dimensional synthetic aperture microwave radiometer operates at frequencies of 6.9, 10.65, 18.7, 23.8 and 36.5 GHz. Then, the microwave radiative transfer forward model is used to simulate the measured brightness temperatures. The sensitivity of the brightness temperatures at 0°~65° to the sea surface wind speed is calculated. Then, vertical polarization channels (VR), horizontal polarization channels (HR) and all channels (AR) are used to retrieve the sea surface wind speed via a multiple linear regression algorithm at 0°~65°, and the relationship between the retrieval error and incidence angle is obtained. The results are as follows: (1) The sensitivity of the vertical polarization brightness temperature to the sea surface wind speed is smaller than that of the horizontal polarization. (2) The retrieval error increases with Gaussian noise. The retrieval error of VR first increases and then decreases with increasing incidence angle, the retrieval error of HR gradually decreases with increasing incidence angle, and the retrieval error of AR first decreases and then increases with increasing incidence angle. (3) The retrieval error of AR is the lowest and it is necessary to retrieve the sea surface wind speed at a larger incidence angle for AR.
2021, 27(1): 70-80.
doi: 10.46267/j.1006-8775.2021.007
Abstract:
Investigating the temporal and spatial distributions of the atmospheric heat sources (AHS) over the Tibetan Plateau-Tropical Indian Ocean (TP-TIO) region is of great importance for the understanding of the evolution and development of the South Asian summer monsoon (SASM). This study used the Japanese 55-year Reanalysis (JRA-55) data from 1979 to 2016 and adopted statistical methods to study the characteristics of the AHS between the TP and TIO, and theirs link to the SASM on an interannual scale. The results indicated that the monthly variations of the AHS in the two regions were basically anti-phase, and that the summer AHS in the TP was obviously stronger than that in the TIO. There were strong AHS and atmospheric moisture sink (AMS) centers in both the eastern and western TP in summer. The AHS center in the east was stronger than that in the west, and the AMS centers showed the opposite pattern. In the TIO, a strong AHS center in the northwest-southeast direction was located near 10°S, 90°E. Trend analysis showed that summer AHS in the TIO was increasing significantly, especially before 1998, whereas there was a weakening trend in the TP. The difference of the summer AHS between the TP and TIO (hereafter IQ) was used to measure the thermal contrast between the TP and the TIO. The IQ showed an obvious decreasing trend. After 1998, there was a weak thermal contrast between the TP and the TIO, which mainly resulted from the enhanced AHS in the TIO. The land-sea thermal contrast, the TIO Hadley circulation in the southern hemisphere and the SASM circulation all weakened, resulting in abnormal circulation and abnormal precipitation in the Bay of Bengal (BOB).
Investigating the temporal and spatial distributions of the atmospheric heat sources (AHS) over the Tibetan Plateau-Tropical Indian Ocean (TP-TIO) region is of great importance for the understanding of the evolution and development of the South Asian summer monsoon (SASM). This study used the Japanese 55-year Reanalysis (JRA-55) data from 1979 to 2016 and adopted statistical methods to study the characteristics of the AHS between the TP and TIO, and theirs link to the SASM on an interannual scale. The results indicated that the monthly variations of the AHS in the two regions were basically anti-phase, and that the summer AHS in the TP was obviously stronger than that in the TIO. There were strong AHS and atmospheric moisture sink (AMS) centers in both the eastern and western TP in summer. The AHS center in the east was stronger than that in the west, and the AMS centers showed the opposite pattern. In the TIO, a strong AHS center in the northwest-southeast direction was located near 10°S, 90°E. Trend analysis showed that summer AHS in the TIO was increasing significantly, especially before 1998, whereas there was a weakening trend in the TP. The difference of the summer AHS between the TP and TIO (hereafter IQ) was used to measure the thermal contrast between the TP and the TIO. The IQ showed an obvious decreasing trend. After 1998, there was a weak thermal contrast between the TP and the TIO, which mainly resulted from the enhanced AHS in the TIO. The land-sea thermal contrast, the TIO Hadley circulation in the southern hemisphere and the SASM circulation all weakened, resulting in abnormal circulation and abnormal precipitation in the Bay of Bengal (BOB).
2021, 27(1): 81-86.
doi: 10.46267/j.1006-8775.2021.008
Abstract:
The strong destructive winds during tornadoes can greatly threaten human life and destroy property. The increasing availability of visual and remote observations, especially by Doppler weather radars, is of great value in understanding tornado formation and issuing warnings to the public. In this study, we present the first documented tornado over water detected by a state-of-the-art dual-polarization phased-array radar (dual-PAR) in China. In contrast to new-generation weather radars, the dual-PAR shows great advantages in tornado detection for its high spatial resolution, reliable polarimetric variables, and rapid-scan strategy. The polarimetric signature of copolar cross-correlation coefficient with anomalously low magnitude appears to be effective for verifying a tornado and thus is helpful for issuing tornado warnings. The Guangdong Meteorological Service has been developing an experimental X-band dual-PAR network in the Pearl River Delta with the goal of deploying at least 40 advanced dual-PARs and other dual-polarization weather radars before 2035. This network is the first quasi-operational X-band dual-PAR network with unprecedented high coverage in the globe. With such high-performance close-range PARs, efficient operational nowcasting and warning services for small-scale, rapidly evolving, and damaging weather (e.g., tornadoes, localized heavy rainfall, microbursts, and hail) can be expected.
The strong destructive winds during tornadoes can greatly threaten human life and destroy property. The increasing availability of visual and remote observations, especially by Doppler weather radars, is of great value in understanding tornado formation and issuing warnings to the public. In this study, we present the first documented tornado over water detected by a state-of-the-art dual-polarization phased-array radar (dual-PAR) in China. In contrast to new-generation weather radars, the dual-PAR shows great advantages in tornado detection for its high spatial resolution, reliable polarimetric variables, and rapid-scan strategy. The polarimetric signature of copolar cross-correlation coefficient with anomalously low magnitude appears to be effective for verifying a tornado and thus is helpful for issuing tornado warnings. The Guangdong Meteorological Service has been developing an experimental X-band dual-PAR network in the Pearl River Delta with the goal of deploying at least 40 advanced dual-PARs and other dual-polarization weather radars before 2035. This network is the first quasi-operational X-band dual-PAR network with unprecedented high coverage in the globe. With such high-performance close-range PARs, efficient operational nowcasting and warning services for small-scale, rapidly evolving, and damaging weather (e.g., tornadoes, localized heavy rainfall, microbursts, and hail) can be expected.
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