2019 Vol. 25, No. 4
2019, 25(4): .
Abstract:
2019, 25(4): 421-436.
doi: 10.16555/j.1006-8775.2019.04.001
Abstract:
Considering the feature of tropical cyclones (TCs) that strong positive vorticity exists in the lower layers of troposphere, this study proposed to use vorticity at 850 hPa as cost function to find the conditional nonlinear optimal perturbation (CNOP), which was largely different from those previous studies using total energy of perturbed forecast variables. The CNOP was obtained by an ensemble-based approach. All of the sensitive areas determined by CNOP with vorticity at 850 hPa as cost function for the three cases were located over the TC core region and its vicinity. The impact of the CNOP-based adaptive observations on TC forecasts was evaluated with three cases via observational system simulation experiments (OSSEs). Results showed obvious improvements in TC intensity or track forecasts due to the CNOP-based adaptive observations, which were related to the main error source of the verification area, i.e., intensity error or location error.
Considering the feature of tropical cyclones (TCs) that strong positive vorticity exists in the lower layers of troposphere, this study proposed to use vorticity at 850 hPa as cost function to find the conditional nonlinear optimal perturbation (CNOP), which was largely different from those previous studies using total energy of perturbed forecast variables. The CNOP was obtained by an ensemble-based approach. All of the sensitive areas determined by CNOP with vorticity at 850 hPa as cost function for the three cases were located over the TC core region and its vicinity. The impact of the CNOP-based adaptive observations on TC forecasts was evaluated with three cases via observational system simulation experiments (OSSEs). Results showed obvious improvements in TC intensity or track forecasts due to the CNOP-based adaptive observations, which were related to the main error source of the verification area, i.e., intensity error or location error.
2019, 25(4): 437-447.
doi: 10.16555/j.1006-8775.2019.04.002
Abstract:
This study evaluates the performance of the regional climate model RegCM4 in simulating tropical cyclone (TC) activities over the Western North Pacific (WNP) and their landfalling in China. The model is driven by ERA-Interim boundary conditions at a grid spacing of 25 km, with the simulation period as 1991–C2010. Results show that RegCM4 performs well in capturing the main structural features of observed TCs, and in simulating the genesis number and annual cycle of the genesis. The model reproduces the general pattern of the observed TC tracks and occurrence frequency. However, significant underestimation of the occurrence frequency as well as the TC intensity is found. Number of the landfalling TCs over China is also much less than the observed. Bias of the model in reproducing the large-scale circulation pattern and steering flow may contribute to the underestimated landfalling TC numbers.
This study evaluates the performance of the regional climate model RegCM4 in simulating tropical cyclone (TC) activities over the Western North Pacific (WNP) and their landfalling in China. The model is driven by ERA-Interim boundary conditions at a grid spacing of 25 km, with the simulation period as 1991–C2010. Results show that RegCM4 performs well in capturing the main structural features of observed TCs, and in simulating the genesis number and annual cycle of the genesis. The model reproduces the general pattern of the observed TC tracks and occurrence frequency. However, significant underestimation of the occurrence frequency as well as the TC intensity is found. Number of the landfalling TCs over China is also much less than the observed. Bias of the model in reproducing the large-scale circulation pattern and steering flow may contribute to the underestimated landfalling TC numbers.
2019, 25(4): 448-461.
doi: 10.16555/j.1006-8775.2019.04.003
Abstract:
In this study, we investigate the variations of spring and autumn air temperatures in southern China (SC) and associated atmospheric circulation patterns. During the boreal spring, the SC air temperature is mainly influenced by tropical sea surface temperature anomalies (SSTAs). On the one hand, the El Niño SSTA pattern may induce a stronger-than-normal western Pacific subtropical high, which leads to warming in SC. On the other hand, the warm SSTAs in the tropical Indian Ocean may trigger anomalous Rossby wave trains, which propagate northeastward and result in anomalously high temperature in SC. During the boreal autumn, however, the SC temperature is more likely affected by mid-latitude atmospheric circulation, such as the wave trains forced by the North Atlantic SSTAs. The NCEP Climate Forecast System version 2 (CFSv2) is able to capture the climatology of SC air temperatures during both spring and autumn. For interannual variation, the CFSv2 shows a good skill for predicting the SC temperature in spring, due to the model’s good performance in capturing the associated atmospheric circulation anomalies as responses to tropical SSTAs, in spite of the overestimated relationship with the El Niño–CSouthern Oscillation (ENSO). However, the model has a poor skill for predicting the SC temperature in autumn, primarily due to the unrealistic prediction of its relationship with the ENSO.
In this study, we investigate the variations of spring and autumn air temperatures in southern China (SC) and associated atmospheric circulation patterns. During the boreal spring, the SC air temperature is mainly influenced by tropical sea surface temperature anomalies (SSTAs). On the one hand, the El Niño SSTA pattern may induce a stronger-than-normal western Pacific subtropical high, which leads to warming in SC. On the other hand, the warm SSTAs in the tropical Indian Ocean may trigger anomalous Rossby wave trains, which propagate northeastward and result in anomalously high temperature in SC. During the boreal autumn, however, the SC temperature is more likely affected by mid-latitude atmospheric circulation, such as the wave trains forced by the North Atlantic SSTAs. The NCEP Climate Forecast System version 2 (CFSv2) is able to capture the climatology of SC air temperatures during both spring and autumn. For interannual variation, the CFSv2 shows a good skill for predicting the SC temperature in spring, due to the model’s good performance in capturing the associated atmospheric circulation anomalies as responses to tropical SSTAs, in spite of the overestimated relationship with the El Niño–CSouthern Oscillation (ENSO). However, the model has a poor skill for predicting the SC temperature in autumn, primarily due to the unrealistic prediction of its relationship with the ENSO.
2019, 25(4): 462-470.
doi: 10.16555/j.1006-8775.2019.04.004
Abstract:
South China spring rainfall (SCSR) is a unique feature during the seasonal transition from the winter half-year to summer half-year. Abnormal SCSR has great impacts on crop harvests. Seeking previous predictability sources, particularly persistent precursors, is of practical importance in the seasonal prediction of SCSR. The present study investigates the relationship between SCSR and preceding-summer warm pool ocean heat content (WPHC). The SCSR-WPHC relationship is not stationary and has a remarkable interdecadal change around 1983. Before 1983, SCSR and preceding-summer WPHC have a close relationship, with a temporal correlation coefficient (TCC) of ?0.54. After 1983, the relationship disappears, with a TCC of ?0.18. It is further found that the WPHC-associated sea surface temperature anomaly (SSTA) pattern in the simultaneous spring during the two periods presents dissimilar evolutionary features. Before 1983, a La Niña-like SSTA presents a fast transition during the winter and alters to a developing El Niño during the following spring. The warm SSTA is confined to a limited region over the eastern Pacific. Therefore, the rainfall and circulation responses over the equatorial Maritime Continent are relatively weak. In turn, the Rossby wave response in terms of the cyclonic anomaly to the Maritime Continent diabatic heating is weak and confined to the South China Sea and Philippine Sea, which leads to high pressure and suppressed rainfall over south China, establishing an intimate SCSR–CWPHC relationship. However, after 1983, because the La Niña-like SSTA pattern can persist for more than a year, the rainfall diabatic heating over the Maritime Continent during springtime is enhanced, resulting in a much larger cyclonic response over East Asia but insignificant rainfall anomalies over south China. Therefore, the SCSR–CWPHC relationship becomes weak. Wavelet analysis suggests that the change in the dominant period of WPHC variation is probably responsible for the different SSTA evolutions and corresponding atmospheric responses.
South China spring rainfall (SCSR) is a unique feature during the seasonal transition from the winter half-year to summer half-year. Abnormal SCSR has great impacts on crop harvests. Seeking previous predictability sources, particularly persistent precursors, is of practical importance in the seasonal prediction of SCSR. The present study investigates the relationship between SCSR and preceding-summer warm pool ocean heat content (WPHC). The SCSR-WPHC relationship is not stationary and has a remarkable interdecadal change around 1983. Before 1983, SCSR and preceding-summer WPHC have a close relationship, with a temporal correlation coefficient (TCC) of ?0.54. After 1983, the relationship disappears, with a TCC of ?0.18. It is further found that the WPHC-associated sea surface temperature anomaly (SSTA) pattern in the simultaneous spring during the two periods presents dissimilar evolutionary features. Before 1983, a La Niña-like SSTA presents a fast transition during the winter and alters to a developing El Niño during the following spring. The warm SSTA is confined to a limited region over the eastern Pacific. Therefore, the rainfall and circulation responses over the equatorial Maritime Continent are relatively weak. In turn, the Rossby wave response in terms of the cyclonic anomaly to the Maritime Continent diabatic heating is weak and confined to the South China Sea and Philippine Sea, which leads to high pressure and suppressed rainfall over south China, establishing an intimate SCSR–CWPHC relationship. However, after 1983, because the La Niña-like SSTA pattern can persist for more than a year, the rainfall diabatic heating over the Maritime Continent during springtime is enhanced, resulting in a much larger cyclonic response over East Asia but insignificant rainfall anomalies over south China. Therefore, the SCSR–CWPHC relationship becomes weak. Wavelet analysis suggests that the change in the dominant period of WPHC variation is probably responsible for the different SSTA evolutions and corresponding atmospheric responses.
2019, 25(4): 471-482.
doi: 10.16555/j.1006-8775.2019.04.005
Abstract:
The climatological features and interannual variation of winter-to-spring transition over southern China and its surrounding areas, and its possible mechanisms are examined in this study. The climatological mean winter-to-spring transition is approximately in mid-March over southern China and the northern South China Sea. During the transition stage, anomalous southwest winds prevail at low-level over southern China and its nearby regions with enhanced convergence center over southern China, bringing more moisture from the Bay of Bengal (BOB) and the South China Sea (SCS) to southern China; meanwhile, the upper level is characterized by an obvious divergence wind pattern over southern China to the southwest part of Japan and enhanced upward motion. All the change of circulation is favorable to an increase of precipitation over southern China after seasonal transition. The winter-to-spring transition is predominantly on the interannual variation over southern China and the northern SCS. Early winter-to-spring transitions may induce more precipitation over southern China in spring, especially in March, while late cases will result in less precipitation. The interannual variability of the winter-to-spring transition and the related large-scale circulation are closely associated with the decaying phase of ENSO events. The warm ENSO events contribute to early winter-to-spring transitions and more precipitation over southern China.
The climatological features and interannual variation of winter-to-spring transition over southern China and its surrounding areas, and its possible mechanisms are examined in this study. The climatological mean winter-to-spring transition is approximately in mid-March over southern China and the northern South China Sea. During the transition stage, anomalous southwest winds prevail at low-level over southern China and its nearby regions with enhanced convergence center over southern China, bringing more moisture from the Bay of Bengal (BOB) and the South China Sea (SCS) to southern China; meanwhile, the upper level is characterized by an obvious divergence wind pattern over southern China to the southwest part of Japan and enhanced upward motion. All the change of circulation is favorable to an increase of precipitation over southern China after seasonal transition. The winter-to-spring transition is predominantly on the interannual variation over southern China and the northern SCS. Early winter-to-spring transitions may induce more precipitation over southern China in spring, especially in March, while late cases will result in less precipitation. The interannual variability of the winter-to-spring transition and the related large-scale circulation are closely associated with the decaying phase of ENSO events. The warm ENSO events contribute to early winter-to-spring transitions and more precipitation over southern China.
2019, 25(4): 483-497.
doi: 10.16555/j.1006-8775.2019.04.006
Abstract:
Due to the topography and local nonuniform distribution of heating, extratropical cyclones in the lower troposphere usually have complex shapes and structures, and there remain some uncertainties in identifying them. Using a modified cyclone area automatic objective recognition algorithm for cyclones, we investigated the patterns of spring cyclone activities affecting Changjiang River-Huaihe River valleys (CHV) of China during the previous 37 years. The results indicated that the algorithm performs well in reproducing the cyclogenesis, movement, and cyclolysis of cyclones in CHV. Three new perspectives were noted. (1) Most influential cyclones have relatively short travel distances and lifetimes, they are typically excluded when conducting synoptic-scale cyclone tracking. (2) The cyclogenesis location of influential cyclones in spring displays multi-source characteristics. In particular, the influential cyclones originated in northern China account for 43% with more marked mobility compared to the locally generated cyclones, although most of their centers do not enter CHV. (3) Multi-center cyclones appear mainly in Da Hinggan Mountains which is on the east side of the Mongolian Plateau and over the East China Sea. These cyclones are relatively large in horizontal scale and have relatively long lifetimes.
Due to the topography and local nonuniform distribution of heating, extratropical cyclones in the lower troposphere usually have complex shapes and structures, and there remain some uncertainties in identifying them. Using a modified cyclone area automatic objective recognition algorithm for cyclones, we investigated the patterns of spring cyclone activities affecting Changjiang River-Huaihe River valleys (CHV) of China during the previous 37 years. The results indicated that the algorithm performs well in reproducing the cyclogenesis, movement, and cyclolysis of cyclones in CHV. Three new perspectives were noted. (1) Most influential cyclones have relatively short travel distances and lifetimes, they are typically excluded when conducting synoptic-scale cyclone tracking. (2) The cyclogenesis location of influential cyclones in spring displays multi-source characteristics. In particular, the influential cyclones originated in northern China account for 43% with more marked mobility compared to the locally generated cyclones, although most of their centers do not enter CHV. (3) Multi-center cyclones appear mainly in Da Hinggan Mountains which is on the east side of the Mongolian Plateau and over the East China Sea. These cyclones are relatively large in horizontal scale and have relatively long lifetimes.
2019, 25(4): 498-518.
doi: 10.16555/j.1006-8775.2019.04.007
Abstract:
The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.
The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.
2019, 25(4): 519-527.
doi: 10.16555/j.1006-8775.2019.04.008
Abstract:
Based on the 74 circulation indexes provided by National Climate Center of China (hereinafter referred to as NCC) and the 24 indexes compiled by NOAA, the study used the C4.5 algorithm in data mining to establish a decision tree prediction model to predict whether the Spring Persistent Rains (hereinafter referred to as SPR) of 55 years (from 1961 to 2015) is more than the normal, and obtained 5 rules to determine whether the SPR is more than the normal. The accuracy rate of the test set, namely “whether the SPR is more than the normal”, is 98.18%. After evaluating the model by conducting ten 10-fold cross validations to take the average value, the test accuracy rate gained is 84%. There are differences between the three types of years with a SPR more than the normal when it comes to intensity and distribution. In spring, they have respective anomalous 850hPa monthly mean wind fields and water-vapor flux distribution, and 700hPa forms the zone where the vertical speed is anomalously negative. As indicated by the results, the SPR prediction model based on the C4.5 algorithm has a high prediction accuracy rate, the model is reasonably and effectively constructed, and the decision rules take comprehensive factors into consideration. The anomalous rainfall and circulation distribution characteristics obtained based on the decision classification results provide new ideas and methods for the climatic prediction of SPR.
Based on the 74 circulation indexes provided by National Climate Center of China (hereinafter referred to as NCC) and the 24 indexes compiled by NOAA, the study used the C4.5 algorithm in data mining to establish a decision tree prediction model to predict whether the Spring Persistent Rains (hereinafter referred to as SPR) of 55 years (from 1961 to 2015) is more than the normal, and obtained 5 rules to determine whether the SPR is more than the normal. The accuracy rate of the test set, namely “whether the SPR is more than the normal”, is 98.18%. After evaluating the model by conducting ten 10-fold cross validations to take the average value, the test accuracy rate gained is 84%. There are differences between the three types of years with a SPR more than the normal when it comes to intensity and distribution. In spring, they have respective anomalous 850hPa monthly mean wind fields and water-vapor flux distribution, and 700hPa forms the zone where the vertical speed is anomalously negative. As indicated by the results, the SPR prediction model based on the C4.5 algorithm has a high prediction accuracy rate, the model is reasonably and effectively constructed, and the decision rules take comprehensive factors into consideration. The anomalous rainfall and circulation distribution characteristics obtained based on the decision classification results provide new ideas and methods for the climatic prediction of SPR.
2019, 25(4): 528-541.
doi: 10.16555/j.1006-8775.2019.04.009
Abstract:
Data from the lightning mapping imager on board the Fengyun-4 meteorological satellite (FY-4) were used to study the assimilation of lightning data and its influence on precipitation predictions. We first conducted a quality control check on the events observed by the first Fengyun-4 satellite (FY-4A) lightning mapping imager, after which the noise points were removed from the lightning distribution. The subsequent distribution was more consistent with the spatial distribution and range of ground-based observations and precipitation. We selected the radar reflectivity, which was closely related to the lightning frequency, as the parameter to assimilate the lightning data and utilized a large sample of lightning frequency and radar reflectivity data from the eastern United States provided by Vaisala. Based on statistical analysis, we found the empirical relationship between the lightning frequency and radar reflectivity and established a look-up table between them. We converted the lightning event data into radar reflectivity data and found that the converted reflectivity and composite reflectivity of ground-based radar observations showed high consistency. We further assimilated the lightning data into the model, adjusted the model cloud analysis process and adjusted the model hydrometeor field by using the lightning data. A rainstorm weather process that occurred on August 8, 2017, in south China was used for the numerical forecast experiment, and three experiments were designed for comparison and analysis: a control experiment, an experiment without the assimilation of FY-4 lightning data (NoLig), and an experiment with the assimilation of FY-4 lightning data (Lig). The results show that after assimilating the FY-4A lightning data, the accuracies of the intensity, central location and range of the precipitation predicted by the Lig experiment were obviously superior to those predicted by the control and NoLig experiments, and the effect was especially obvious in the short-term (1–C2 hour) forecast. The studies in this paper highlight the application value and potential of FY-4 lightning data in precipitation predictions.
Data from the lightning mapping imager on board the Fengyun-4 meteorological satellite (FY-4) were used to study the assimilation of lightning data and its influence on precipitation predictions. We first conducted a quality control check on the events observed by the first Fengyun-4 satellite (FY-4A) lightning mapping imager, after which the noise points were removed from the lightning distribution. The subsequent distribution was more consistent with the spatial distribution and range of ground-based observations and precipitation. We selected the radar reflectivity, which was closely related to the lightning frequency, as the parameter to assimilate the lightning data and utilized a large sample of lightning frequency and radar reflectivity data from the eastern United States provided by Vaisala. Based on statistical analysis, we found the empirical relationship between the lightning frequency and radar reflectivity and established a look-up table between them. We converted the lightning event data into radar reflectivity data and found that the converted reflectivity and composite reflectivity of ground-based radar observations showed high consistency. We further assimilated the lightning data into the model, adjusted the model cloud analysis process and adjusted the model hydrometeor field by using the lightning data. A rainstorm weather process that occurred on August 8, 2017, in south China was used for the numerical forecast experiment, and three experiments were designed for comparison and analysis: a control experiment, an experiment without the assimilation of FY-4 lightning data (NoLig), and an experiment with the assimilation of FY-4 lightning data (Lig). The results show that after assimilating the FY-4A lightning data, the accuracies of the intensity, central location and range of the precipitation predicted by the Lig experiment were obviously superior to those predicted by the control and NoLig experiments, and the effect was especially obvious in the short-term (1–C2 hour) forecast. The studies in this paper highlight the application value and potential of FY-4 lightning data in precipitation predictions.
2019, 25(4): 542-552.
doi: 10.16555/j.1006-8775.2019.04.010
Abstract:
Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–C30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–C30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–C2016 indicate that EHRPs can be predicted 8–C24 d in advance, with an average period of validity of 16.7 d.
Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–C30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–C30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–C2016 indicate that EHRPs can be predicted 8–C24 d in advance, with an average period of validity of 16.7 d.
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