2019 Vol. 25, No. 3
2019, 25(3): 293-303.
doi: 10.16555/j.1006-8775.2019.03.001
Abstract:
This paper comprehensively analyzes the characteristics and cause of the inshore intensification of super typhoon "Hato", the 13th super typhoon in 2017. The aspects of typhoon structure, evolution of large-scale circulation and physical quantity field are analyzed using observation data from the Guangdong Automatic Station, Shenzhen Doppler Radar data, NCEP 1°×1° reanalysis data, NCEP 0.25°×0.25° sea surface temperature (SST) data, etc. Additionally, in order to investigate the influence of SST change on the intensity of "Hato", the WRF model and ECMWF 0.125°×0.125° reanalysis data are combined to conduct 3 sensitivity tests on "Hato". The results show that the favorable conditions for inshore intensification of "Hato" included: the strengthening and westward extension of the subtropical high, continuous increase of low level moisture transport, an anomalous warm SST area north of 20°N in the South China Sea, an extreme divergence value in the northern South China Sea exceeding 6×10-5s-1, and vertical environmental wind shear between 1.1m/s-4.8m/s. The intensity of "Hato" was very sensitive to changes in SST. When the SST rose or dropped by 2°C, the minimum central pressure of the typhoon changed by about 13hPa or 11hPa, respectively. SST indirectly influenced the intensity of the typhoon through affecting latent heat transport and sensible heat transport.
This paper comprehensively analyzes the characteristics and cause of the inshore intensification of super typhoon "Hato", the 13th super typhoon in 2017. The aspects of typhoon structure, evolution of large-scale circulation and physical quantity field are analyzed using observation data from the Guangdong Automatic Station, Shenzhen Doppler Radar data, NCEP 1°×1° reanalysis data, NCEP 0.25°×0.25° sea surface temperature (SST) data, etc. Additionally, in order to investigate the influence of SST change on the intensity of "Hato", the WRF model and ECMWF 0.125°×0.125° reanalysis data are combined to conduct 3 sensitivity tests on "Hato". The results show that the favorable conditions for inshore intensification of "Hato" included: the strengthening and westward extension of the subtropical high, continuous increase of low level moisture transport, an anomalous warm SST area north of 20°N in the South China Sea, an extreme divergence value in the northern South China Sea exceeding 6×10-5s-1, and vertical environmental wind shear between 1.1m/s-4.8m/s. The intensity of "Hato" was very sensitive to changes in SST. When the SST rose or dropped by 2°C, the minimum central pressure of the typhoon changed by about 13hPa or 11hPa, respectively. SST indirectly influenced the intensity of the typhoon through affecting latent heat transport and sensible heat transport.
2019, 25(3): 304-311.
doi: 10.16555/j.1006-8775.2019.03.002
Abstract:
As the risk of storm surge on coastal plains increases, the research on disaster risk assessment is fundamental for disaster management. Disaster risk assessment tends to develop towards the direction of refinement and it gradually plays a more important role. As regards the characteristics of storm tide disaster in coastal plain, the paper uses refined floodplain numerical model which combines typhoon, flood, astronomical tide and waves. The model also considers influencing factors of dike-breaking, micro-topography and buildings. Precise calculation is executed for the range and the submerged depth caused by floodplain flow in coastal plain. Based on 3S technology, disaster-bearing bodies are subdivided into the smallest unit of the ground object, and the vulnerability of these units is evaluated. Refined risk assessment of storm surge disaster for the coastal plain is obtained, and the detailed distribution of risk areas at different risk levels is achieved. These results can be widely applied in many fields, such as disaster prevention and mitigation, urban planning, industrial arrangement, disaster insurance and so on.
As the risk of storm surge on coastal plains increases, the research on disaster risk assessment is fundamental for disaster management. Disaster risk assessment tends to develop towards the direction of refinement and it gradually plays a more important role. As regards the characteristics of storm tide disaster in coastal plain, the paper uses refined floodplain numerical model which combines typhoon, flood, astronomical tide and waves. The model also considers influencing factors of dike-breaking, micro-topography and buildings. Precise calculation is executed for the range and the submerged depth caused by floodplain flow in coastal plain. Based on 3S technology, disaster-bearing bodies are subdivided into the smallest unit of the ground object, and the vulnerability of these units is evaluated. Refined risk assessment of storm surge disaster for the coastal plain is obtained, and the detailed distribution of risk areas at different risk levels is achieved. These results can be widely applied in many fields, such as disaster prevention and mitigation, urban planning, industrial arrangement, disaster insurance and so on.
2019, 25(3): 312-323.
doi: 10.16555/j.1006-8775.2019.03.003
Abstract:
An ensemble Kalman filter based on the Weather Research and Forecasting Model (WRF-EnKF) is used to explore the effectiveness of the assimilation of surface observation data in an extreme local rainstorm over the Pearl River Delta region on 7 May 2017. Before the occurrence of rainstorm, the signals of weather forecasts in this case are too weak to be predicted by numerical weather model, but the surface temperature over the urban area are high. The results of this study show that the wind field, temperature, and water vapor are obviously adjusted by assimilating surface data of 10-m wind, 2-m temperature, and 2-m water vapor mixing ratio at 2300 BST 6 May, especially below the height of 2 km. The southerly wind over the Pearl River Delta region is enhanced, and the convergence of wind over the northern Guangzhou city is also enhanced. Additionally, temperature, water vapor mixing ratio and pseudoequivalent potential temperature are obviously increased over the urban region, providing favorable conditions for the occurrence of heavy precipitation. After assimilation, the predictions of 12-h rainfall amount, temperature, and relative humidity are significantly improved, and the rainfall intensity and distribution in this case can be successfully reproduced. Moreover, sensitivity tests suggest that the assimilation of 2-m temperature is the key to predict this extreme rainfall and just assimilating data of surface wind or water vapor is not workable, implying that urban heat island effect may be an important factor in this extreme rainstorm.
An ensemble Kalman filter based on the Weather Research and Forecasting Model (WRF-EnKF) is used to explore the effectiveness of the assimilation of surface observation data in an extreme local rainstorm over the Pearl River Delta region on 7 May 2017. Before the occurrence of rainstorm, the signals of weather forecasts in this case are too weak to be predicted by numerical weather model, but the surface temperature over the urban area are high. The results of this study show that the wind field, temperature, and water vapor are obviously adjusted by assimilating surface data of 10-m wind, 2-m temperature, and 2-m water vapor mixing ratio at 2300 BST 6 May, especially below the height of 2 km. The southerly wind over the Pearl River Delta region is enhanced, and the convergence of wind over the northern Guangzhou city is also enhanced. Additionally, temperature, water vapor mixing ratio and pseudoequivalent potential temperature are obviously increased over the urban region, providing favorable conditions for the occurrence of heavy precipitation. After assimilation, the predictions of 12-h rainfall amount, temperature, and relative humidity are significantly improved, and the rainfall intensity and distribution in this case can be successfully reproduced. Moreover, sensitivity tests suggest that the assimilation of 2-m temperature is the key to predict this extreme rainfall and just assimilating data of surface wind or water vapor is not workable, implying that urban heat island effect may be an important factor in this extreme rainstorm.
2019, 25(3): 324-335.
doi: 10.16555/j.1006-8775.2019.03.004
Abstract:
The diurnal cycles of precipitation over north China during summer in four strong rainfall years are examined using two-dimensional cloud-resolving modeling data. The diurnal signals are analyzed in terms of precipitation budget, fractional rainfall coverage and rain intensity over convective and stratiform rainfall area. The analysis of precipitation budget shows that the diurnal cycles of convective and stratiform precipitation mainly correspond respectively to those of water vapor convergence and transport of hydrometeor from convective rainfall area to stratiform rainfall area in 1964, 1994 and 1995, whereas they mainly correspond to those of water vapor convergence in 2013. The diurnal cycles of convective and stratiform precipitation are mainly associated with those of rain intensity in 1964, 1994 and 1995. In 2013, the diurnal cycle of stratiform precipitation is mainly related to that of fractional rainfall coverage over stratiform rainfall area. The multiple peaks of convective precipitation mainly correspond to the rain intensity maxima associated with strong water vapor convergence.
The diurnal cycles of precipitation over north China during summer in four strong rainfall years are examined using two-dimensional cloud-resolving modeling data. The diurnal signals are analyzed in terms of precipitation budget, fractional rainfall coverage and rain intensity over convective and stratiform rainfall area. The analysis of precipitation budget shows that the diurnal cycles of convective and stratiform precipitation mainly correspond respectively to those of water vapor convergence and transport of hydrometeor from convective rainfall area to stratiform rainfall area in 1964, 1994 and 1995, whereas they mainly correspond to those of water vapor convergence in 2013. The diurnal cycles of convective and stratiform precipitation are mainly associated with those of rain intensity in 1964, 1994 and 1995. In 2013, the diurnal cycle of stratiform precipitation is mainly related to that of fractional rainfall coverage over stratiform rainfall area. The multiple peaks of convective precipitation mainly correspond to the rain intensity maxima associated with strong water vapor convergence.
2019, 25(3): 336-343.
doi: 10.16555/j.1006-8775.2019.03.005
Abstract:
Hurricane intensity and track are strongly affected by air-sea interactions. Classified as following swells, crossing swells, and opposing swells, the observed wave height was parameterized by using the 10-m wind speed collected on 5 buoys by the National Buoy Data Center during 13 hurricane events. The path information of these 13 hurricanes was obtained from the National Hurricane Center Best Track (NHC-BT). Results show that the wave height increases exponentially with the 10-m wind speed, and the wave height reaches the maximum value, 11.2 m (8.1 m), when 10-m wind speed is 40 m s-1 under the following and crossing (opposing) swell conditions. We find that the wave steepness (the ratio of wave height to wave length) is proportional to the -2/3 power of the wave age (the ratio of wave phase velocity to 10-m wind speed). The parameterizations of friction velocity and drag coefficient are tested using the buoy data collected in moderate to high wind under following, crossing and opposing swell conditions. A wave age dependent equation for drag coefficient is found more accurate and suggested for future usage in numerical models. Further, these algorithms also suggest that wind-swell orientation needs to be considered to retrieve accurate surface drag under high winds and strong swells.
Hurricane intensity and track are strongly affected by air-sea interactions. Classified as following swells, crossing swells, and opposing swells, the observed wave height was parameterized by using the 10-m wind speed collected on 5 buoys by the National Buoy Data Center during 13 hurricane events. The path information of these 13 hurricanes was obtained from the National Hurricane Center Best Track (NHC-BT). Results show that the wave height increases exponentially with the 10-m wind speed, and the wave height reaches the maximum value, 11.2 m (8.1 m), when 10-m wind speed is 40 m s-1 under the following and crossing (opposing) swell conditions. We find that the wave steepness (the ratio of wave height to wave length) is proportional to the -2/3 power of the wave age (the ratio of wave phase velocity to 10-m wind speed). The parameterizations of friction velocity and drag coefficient are tested using the buoy data collected in moderate to high wind under following, crossing and opposing swell conditions. A wave age dependent equation for drag coefficient is found more accurate and suggested for future usage in numerical models. Further, these algorithms also suggest that wind-swell orientation needs to be considered to retrieve accurate surface drag under high winds and strong swells.
2019, 25(3): 344-352.
doi: 10.16555/j.1006-8775.2019.03.006
Abstract:
Traditional skill scores (e.g., the threat score) used in the high-resolution verification of precipitation are affected by a “double penalty” caused by slight spatial or temporal displacements, which can lead to misleading evaluations. The fractions skill score (FSS) is a popular spatial verificaiton measure that can be used to solve these problems. It can determine useful and skillful scores by neighborhood analysis, which can be used to monitor the performance of operational forecasts. However, the FSS provides different scores at each spatial scale and it is difficult to obtain a definite score for the assessment of precipitation to analyze the temporal variabilities of daily forecasts. We previously reported a modified FSS assessment method and showed that a particular analysis scale had a significant advantage in the verification of operational forecasts of precipitation. To compensate for the lack of artificial definition in the analysis scale, we report here a new integrated score that satisfies a Gaussian weight function to average the FSS over all scales. We describe the advantages of the new score in the verification of forecasts of daily and hourly precipitation, taking forecast products from the GRAPES regional model and quantitative precipitation estimation products from the National Meteorological Information Center during June and July 2017 and investigating the differences between these results and those obtained with the traditional category score. We found that a value of 0.5 can be used as a standard for the skillful FSS in the forecast of heavy rainfall. The integrated score can maintain all the advantages seen in previous studies in the verification of daily and hourly precipitation and show excellent application prospects. The long-term verification including different seasons also find that the score can effectively improve the identification characteristics of the assessment.
Traditional skill scores (e.g., the threat score) used in the high-resolution verification of precipitation are affected by a “double penalty” caused by slight spatial or temporal displacements, which can lead to misleading evaluations. The fractions skill score (FSS) is a popular spatial verificaiton measure that can be used to solve these problems. It can determine useful and skillful scores by neighborhood analysis, which can be used to monitor the performance of operational forecasts. However, the FSS provides different scores at each spatial scale and it is difficult to obtain a definite score for the assessment of precipitation to analyze the temporal variabilities of daily forecasts. We previously reported a modified FSS assessment method and showed that a particular analysis scale had a significant advantage in the verification of operational forecasts of precipitation. To compensate for the lack of artificial definition in the analysis scale, we report here a new integrated score that satisfies a Gaussian weight function to average the FSS over all scales. We describe the advantages of the new score in the verification of forecasts of daily and hourly precipitation, taking forecast products from the GRAPES regional model and quantitative precipitation estimation products from the National Meteorological Information Center during June and July 2017 and investigating the differences between these results and those obtained with the traditional category score. We found that a value of 0.5 can be used as a standard for the skillful FSS in the forecast of heavy rainfall. The integrated score can maintain all the advantages seen in previous studies in the verification of daily and hourly precipitation and show excellent application prospects. The long-term verification including different seasons also find that the score can effectively improve the identification characteristics of the assessment.
2019, 25(3): 353-364.
doi: 10.16555/j.1006-8775.2019.03.007
Abstract:
Sensitivities of parameterization schemes were conducted based on the Global/Regional Assimilation and Prediction System (GRAPES) model. Surface observations were used to evaluate the simulations and to improve the model’s ability to simulate the extreme precipitation over southern China on 20 July 2016. The results showed that GRAPES captured the large-scale precipitation over southern China but failed to predict the extreme precipitation over Xinyi. The model showed a systematic cold biases by adopting different parameterization schemes. In particular, the ECMWF analyses data showed a strong cold bias over Guangdong province and Guangxi Region. Observational nudging results showed that the surface temperature could largely help to alleviate the cold bias. The alleviation in the warm sector accounted for main improvement by the nudging scheme, and the RMSE was reduced by 1.56 degree from 3.25 degree to 1.69 degree by 1-h simulation and with 1.3 degree alleviation by 2-h simulation. Sensitivities using different parameterizations and the nudging scheme showed that the model’s underestimation of the precipitation was still present despite improvements in the predictions of surface temperature.
Sensitivities of parameterization schemes were conducted based on the Global/Regional Assimilation and Prediction System (GRAPES) model. Surface observations were used to evaluate the simulations and to improve the model’s ability to simulate the extreme precipitation over southern China on 20 July 2016. The results showed that GRAPES captured the large-scale precipitation over southern China but failed to predict the extreme precipitation over Xinyi. The model showed a systematic cold biases by adopting different parameterization schemes. In particular, the ECMWF analyses data showed a strong cold bias over Guangdong province and Guangxi Region. Observational nudging results showed that the surface temperature could largely help to alleviate the cold bias. The alleviation in the warm sector accounted for main improvement by the nudging scheme, and the RMSE was reduced by 1.56 degree from 3.25 degree to 1.69 degree by 1-h simulation and with 1.3 degree alleviation by 2-h simulation. Sensitivities using different parameterizations and the nudging scheme showed that the model’s underestimation of the precipitation was still present despite improvements in the predictions of surface temperature.
2019, 25(3): 365-372.
doi: 10.16555/j.1006-8775.2019.03.008
Abstract:
An ensemble of satellite measurements, statistic data from government and meteorological diagnosis in regional background site (Haikou, China) has revealed the spatial and temporal characteristics of NO2 and associated synoptic transport patterns over southern China from January 2013 to February 2014. The result shows that: (1) Ozone Monitoring Instrument (OMI) satellite products had a good correlation with observation NO2 in Haikou. The correlation coefficients between Observation NO2 and tropospheric column NO2 and ratio of TroNO2/ TotNO2(tropospheric column NO2/ total column NO2) had all passed the confidence level of 99.9% test. (2) TroNO2 over southern China has an obvious seasonal variation, which is closely coupled with regional meteorology in each season. (3) NO2 concentration in Haikou revealed three pollution periods during December 2013 and January 2014. The variation of NO2 concentration in Haikou is related to the meteorological elements closely. (4) Compared to the monthly mean meteorological fields of the pollution periods, the results indicate that NO2 pollution event in Haikou is directly related to the exogenous transportation from PRD region. An ensemble analysis of meteorological dynamic factors, wind vectors and backward trajectories during the pollution periods further verified this conclusion.
An ensemble of satellite measurements, statistic data from government and meteorological diagnosis in regional background site (Haikou, China) has revealed the spatial and temporal characteristics of NO2 and associated synoptic transport patterns over southern China from January 2013 to February 2014. The result shows that: (1) Ozone Monitoring Instrument (OMI) satellite products had a good correlation with observation NO2 in Haikou. The correlation coefficients between Observation NO2 and tropospheric column NO2 and ratio of TroNO2/ TotNO2(tropospheric column NO2/ total column NO2) had all passed the confidence level of 99.9% test. (2) TroNO2 over southern China has an obvious seasonal variation, which is closely coupled with regional meteorology in each season. (3) NO2 concentration in Haikou revealed three pollution periods during December 2013 and January 2014. The variation of NO2 concentration in Haikou is related to the meteorological elements closely. (4) Compared to the monthly mean meteorological fields of the pollution periods, the results indicate that NO2 pollution event in Haikou is directly related to the exogenous transportation from PRD region. An ensemble analysis of meteorological dynamic factors, wind vectors and backward trajectories during the pollution periods further verified this conclusion.
2019, 25(3): 373-384.
doi: 10.16555/j.1006-8775.2019.03.009
Abstract:
Designed for grid point systems, the traditional semi-Lagrangian semi-implicit scheme is not mass-conserving and can lead to significant solution errors. In the present study, a finite-volume semi-Lagrangian semi-implicit scheme (hereafter “FVSLSI”) is designed for the Yin-Yang mesh and tested in a barotropic shallow water model in the spherical coordinate system. Three test cases, i.e. the advection of a solid body, a steady state nonlinear zonal geostrophic flow and the deformation flow, are simulated to compare the performance of the FVSLSI with that of the traditional semi-Lagrangian scheme (hereafter “SL”) from perspectives of shape preservation, mass conservation, normalized bias, and convergence rate. Results indicate that the FVSLSI performs better than the SL in mass conservation and shape preservation. The bias by the FVSLSI is smaller than that by the SL, while the rate of convergence by the FVSLSI is larger than that by the SL. The FVSLSI also allows large time step. Therefore, the FVSLSI is suggested to be distributed to communities that are developing atmospheric/oceanic models.
Designed for grid point systems, the traditional semi-Lagrangian semi-implicit scheme is not mass-conserving and can lead to significant solution errors. In the present study, a finite-volume semi-Lagrangian semi-implicit scheme (hereafter “FVSLSI”) is designed for the Yin-Yang mesh and tested in a barotropic shallow water model in the spherical coordinate system. Three test cases, i.e. the advection of a solid body, a steady state nonlinear zonal geostrophic flow and the deformation flow, are simulated to compare the performance of the FVSLSI with that of the traditional semi-Lagrangian scheme (hereafter “SL”) from perspectives of shape preservation, mass conservation, normalized bias, and convergence rate. Results indicate that the FVSLSI performs better than the SL in mass conservation and shape preservation. The bias by the FVSLSI is smaller than that by the SL, while the rate of convergence by the FVSLSI is larger than that by the SL. The FVSLSI also allows large time step. Therefore, the FVSLSI is suggested to be distributed to communities that are developing atmospheric/oceanic models.
<p>PARTITION OF SEASON BASED ON MULTIELEMENTS AND THE DECADAL CHANGE OF SEASON DURATION IN CHINA</p>
2019, 25(3): 385-398.
doi: 10.16555/j.1006-8775.2019.03.010
Abstract:
<p>Using the multielements similarity measurement method and 1950–C2017 NCEP/NCAR gridded daily reanalysis datasets, we analyzed season duration in China during 1950–C2016, and we defined the element with maximum absolute sensitivity as the key impact element at each point using the sensitivity analysis method. The decadal change of season duration and its key impact element before and after 1980 were studied. The results indicated obvious meridional and zonal differences in the distribution of season duration for the 67-year average, and that the key impact element has the same distribution characteristics as season duration. In addition, complementary relationships were found between the durations of spring and summer, autumn and winter, and the cold and warm seasons. Of those, the complementary relationship between the durations of spring and summer was strongest and the regions of complementarity were numerous. The complementary regions of autumn and winter durations were found mainly in western China. In the cold and warm seasons, the complementary regions were widespread and the complementary relationship was generally weak. Comparison of the periods before and after 1980 revealed an east–Cwest difference in the interdecadal variation of season duration. Interdecadal variation in spring and summer was found concentrated in northern and western regions, while that in autumn and winter was concentrated in the western region. Areas of significant interdecadal variation of the key elements were found concentrated in northern and western regions, corresponding well with the areas of significant interdecadal variation of season duration.</p>
<p>Using the multielements similarity measurement method and 1950–C2017 NCEP/NCAR gridded daily reanalysis datasets, we analyzed season duration in China during 1950–C2016, and we defined the element with maximum absolute sensitivity as the key impact element at each point using the sensitivity analysis method. The decadal change of season duration and its key impact element before and after 1980 were studied. The results indicated obvious meridional and zonal differences in the distribution of season duration for the 67-year average, and that the key impact element has the same distribution characteristics as season duration. In addition, complementary relationships were found between the durations of spring and summer, autumn and winter, and the cold and warm seasons. Of those, the complementary relationship between the durations of spring and summer was strongest and the regions of complementarity were numerous. The complementary regions of autumn and winter durations were found mainly in western China. In the cold and warm seasons, the complementary regions were widespread and the complementary relationship was generally weak. Comparison of the periods before and after 1980 revealed an east–Cwest difference in the interdecadal variation of season duration. Interdecadal variation in spring and summer was found concentrated in northern and western regions, while that in autumn and winter was concentrated in the western region. Areas of significant interdecadal variation of the key elements were found concentrated in northern and western regions, corresponding well with the areas of significant interdecadal variation of season duration.</p>
2019, 25(3): 399-413.
doi: 10.16555/j.1006-8775.2019.03.011
Abstract:
This study investigated the relationships between sea surface temperature (SST) and weather phenomena in different seasons in the Bohai region (China). Five categories of weather phenomena were screened (i.e., fine, cloudy, foggy, rainy and windy conditions) and their relationships with the difference between air temperature and SST observed at Oil Platform A during 2003–C2010 were analyzed statistically. The effects of the difference between air temperature and SST in different weather phenomena were examined using the flux method of the atmospheric boundary layer and a formula for the difference between air temperature and SST. The results revealed diurnal variation of the difference between air temperature and SST of ?1.0 to +1.0 °C, i.e., air temperature above the sea surface is subtracted from the SST in corresponding weather phenomena in different seasons in the Bohai region. Moreover, according to the formula for the difference between air temperature and SST, wind and shortwave radiation are the most important factors in terms of the effects of SST on weather processes. In conclusion, the effects of SST on weather phenomena are manifest via the exchange of momentum and energy from sea to air. When the air temperature above the sea surface is lower than the SST, the SST helps develop mesoscale convection systems within the synoptic system through moisture and sensible heat fluxes. When the air temperature above the sea surface is greater than the SST, synoptic systems transfer heat energy into the sea through heat flux, which affects SST variation. Moreover, a mesoscale convection system will weaken if the synoptic system passes over a colder underlying surface.
This study investigated the relationships between sea surface temperature (SST) and weather phenomena in different seasons in the Bohai region (China). Five categories of weather phenomena were screened (i.e., fine, cloudy, foggy, rainy and windy conditions) and their relationships with the difference between air temperature and SST observed at Oil Platform A during 2003–C2010 were analyzed statistically. The effects of the difference between air temperature and SST in different weather phenomena were examined using the flux method of the atmospheric boundary layer and a formula for the difference between air temperature and SST. The results revealed diurnal variation of the difference between air temperature and SST of ?1.0 to +1.0 °C, i.e., air temperature above the sea surface is subtracted from the SST in corresponding weather phenomena in different seasons in the Bohai region. Moreover, according to the formula for the difference between air temperature and SST, wind and shortwave radiation are the most important factors in terms of the effects of SST on weather processes. In conclusion, the effects of SST on weather phenomena are manifest via the exchange of momentum and energy from sea to air. When the air temperature above the sea surface is lower than the SST, the SST helps develop mesoscale convection systems within the synoptic system through moisture and sensible heat fluxes. When the air temperature above the sea surface is greater than the SST, synoptic systems transfer heat energy into the sea through heat flux, which affects SST variation. Moreover, a mesoscale convection system will weaken if the synoptic system passes over a colder underlying surface.
2019, 25(3): 414-420.
doi: 10.16555/j.1006-8775.2019.03.012
Abstract:
This paper investigates the diurnal variations of summer precipitation in Shanghai by using the city's hourly precipitation data over a span of 35 years. The result shows that the precipitation peaks twice, in the morning and in the afternoon. Precipitation in the morning is characterized by light to moderate rain, and that in the afternoon by heavy to super heavy rain. The peak of short-duration precipitation is mostly found in the afternoon and at dusk, and that of long-duration precipitation in the morning. Most of the precipitation events in Shanghai are of a short duration of 2-3 hours. Basically, the precipitation is spatially distributed in three areas: the eastern coastal and central urban area, where the precipitation peaks mostly in the afternoon, the southern coastal area, where the precipitation peaks both in the afternoon and during the night, and the western area, where long-duration precipitation accounts for a much larger proportion than the other two areas.
This paper investigates the diurnal variations of summer precipitation in Shanghai by using the city's hourly precipitation data over a span of 35 years. The result shows that the precipitation peaks twice, in the morning and in the afternoon. Precipitation in the morning is characterized by light to moderate rain, and that in the afternoon by heavy to super heavy rain. The peak of short-duration precipitation is mostly found in the afternoon and at dusk, and that of long-duration precipitation in the morning. Most of the precipitation events in Shanghai are of a short duration of 2-3 hours. Basically, the precipitation is spatially distributed in three areas: the eastern coastal and central urban area, where the precipitation peaks mostly in the afternoon, the southern coastal area, where the precipitation peaks both in the afternoon and during the night, and the western area, where long-duration precipitation accounts for a much larger proportion than the other two areas.
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