2021 Vol. 27, No. 3
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2021, 27(3): .
Abstract:
2021, 27(3): 191-200.
doi: 10.46267/j.1006-8775.2021.018
Abstract:
Previous studies showed that 4D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously, and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation, which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper.
Previous studies showed that 4D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously, and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation, which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper.
2021, 27(3): 201-217.
doi: 10.46267/j.1006-8775.2021.019
Abstract:
Tropical cyclone(TC) rainfall forecast has remained a challenge. To create initial conditions with high quality for simulation, the present study implemented a data assimilation scheme based on the EnKF method to ingest the satellite-retrieved cloud water path(Cw) and tested it in WRF. The scheme uses the vertical integration of forecasted cloud water content to transform control variables to the observation space, and creates the correlations between Cw and control variables in the flow-dependent background error covariance based on all the ensemble members, so that the observed cloud information can affect the background temperature and humidity. For two typhoons in 2018(Yagi and Rumiba), assimilating Cw significantly increases the simulated rainfalls and TC intensities. In terms of the average equitable threat score of daily moderate to heavy rainfall(5-120 mm), the improvements are over 130%, and the dry biases are cut by about 30%. Such improvements are traced down to the fact that Cw assimilation increases the moisture content, especially that further away from the TC center, which provides more precipitable water for the rainfall, strengthens the TC and broadens the TC size via latent heat release and internal wind field adjustment.
Tropical cyclone(TC) rainfall forecast has remained a challenge. To create initial conditions with high quality for simulation, the present study implemented a data assimilation scheme based on the EnKF method to ingest the satellite-retrieved cloud water path(Cw) and tested it in WRF. The scheme uses the vertical integration of forecasted cloud water content to transform control variables to the observation space, and creates the correlations between Cw and control variables in the flow-dependent background error covariance based on all the ensemble members, so that the observed cloud information can affect the background temperature and humidity. For two typhoons in 2018(Yagi and Rumiba), assimilating Cw significantly increases the simulated rainfalls and TC intensities. In terms of the average equitable threat score of daily moderate to heavy rainfall(5-120 mm), the improvements are over 130%, and the dry biases are cut by about 30%. Such improvements are traced down to the fact that Cw assimilation increases the moisture content, especially that further away from the TC center, which provides more precipitable water for the rainfall, strengthens the TC and broadens the TC size via latent heat release and internal wind field adjustment.
2021, 27(3): 218-231.
doi: 10.46267/j.1006-8775.2021.020
Abstract:
This study presented an evaluation of tropical cyclone (TC) intensity forecasts from five global ensemble prediction systems (EPSs) during 2015-2019 in the western North Pacific region. Notable error features include the underestimation of the TC intensity by ensemble mean forecast and the under-dispersion of the probability forecasts.The root mean square errors (brier scores) of the ensemble mean(probability forecasts) generally decrease consecutively at long lead times during the five years, but fluctuate between certain values at short lead times.Positive forecast skill appeared in the most recent two years (2018-2019) at 120 h or later as compared with the climatology forecasts. However, there is no obvious improvement for the intensity change forecasts during the 5-year period, with abrupt intensity change remaining a big challenge. The probability forecasts show no skill for strong TCs at all the lead times. Among the five EPSs, ECMWF-EPS ranks the best for the intensity forecast, while NCEPGEFS ranks the best for the intensity change forecast, according to the evaluation of ensemble mean and dispersion.As for the other probability forecast evaluation, ECMWF-EPS ranks the best at lead times shorter than 72 h, while NCEP-GEFS ranks the best later on.
This study presented an evaluation of tropical cyclone (TC) intensity forecasts from five global ensemble prediction systems (EPSs) during 2015-2019 in the western North Pacific region. Notable error features include the underestimation of the TC intensity by ensemble mean forecast and the under-dispersion of the probability forecasts.The root mean square errors (brier scores) of the ensemble mean(probability forecasts) generally decrease consecutively at long lead times during the five years, but fluctuate between certain values at short lead times.Positive forecast skill appeared in the most recent two years (2018-2019) at 120 h or later as compared with the climatology forecasts. However, there is no obvious improvement for the intensity change forecasts during the 5-year period, with abrupt intensity change remaining a big challenge. The probability forecasts show no skill for strong TCs at all the lead times. Among the five EPSs, ECMWF-EPS ranks the best for the intensity forecast, while NCEPGEFS ranks the best for the intensity change forecast, according to the evaluation of ensemble mean and dispersion.As for the other probability forecast evaluation, ECMWF-EPS ranks the best at lead times shorter than 72 h, while NCEP-GEFS ranks the best later on.
2021, 27(3): 232-245.
doi: 10.46267/j.1006-8775.2021.021
Abstract:
In this study, the Dynamical-Statistical-Analog Ensemble Forecast model(DSAEF_LTP model) for landfalling tropical cyclone(LTC) precipitation was employed to simulate the precipitation of 10 LTCs that occurred over China in 2018. With similarity region scheme(SRS) parameter values added and TC intensity introduced to the generalized initial value(GIV), four groups of precipitation simulation experiments were designed to verify the forecasting ability of the improved model for more TC samples. Results show that the simulation ability of the DSAEF_LTP model can be optimized regardless of whether adding SRS values only, or introducing TC intensity into GIV, while the experiment with both the two improvements shows a more prominent advantage in simulating the heavier precipitation of LTCs. Compared with four NWP models(i.e., ECMWF, GFS, GRAPES and SMS-WARMS), the overall forecasting performance of the DSAEF_LTP model achieves a better result in simulating precipitation at the thresholds over 250 mm and performs slightly better than NWP models at the thresholds over 100 mm.
In this study, the Dynamical-Statistical-Analog Ensemble Forecast model(DSAEF_LTP model) for landfalling tropical cyclone(LTC) precipitation was employed to simulate the precipitation of 10 LTCs that occurred over China in 2018. With similarity region scheme(SRS) parameter values added and TC intensity introduced to the generalized initial value(GIV), four groups of precipitation simulation experiments were designed to verify the forecasting ability of the improved model for more TC samples. Results show that the simulation ability of the DSAEF_LTP model can be optimized regardless of whether adding SRS values only, or introducing TC intensity into GIV, while the experiment with both the two improvements shows a more prominent advantage in simulating the heavier precipitation of LTCs. Compared with four NWP models(i.e., ECMWF, GFS, GRAPES and SMS-WARMS), the overall forecasting performance of the DSAEF_LTP model achieves a better result in simulating precipitation at the thresholds over 250 mm and performs slightly better than NWP models at the thresholds over 100 mm.
2021, 27(3): 246-258.
doi: 10.46267/j.1006-8775.2021.022
Abstract:
This paper applies statistical and synthetic analysis methods to study the characteristics of the three types of tropical cyclone(TC) that landed in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA) from 1981 to2018 and the reasons for the differences of TC-induced wind and precipitation. The results show that there are interdecadal changes in the frequency and intensity of the landfalling TCs in the GBA, with decreased frequency but increased intensity in the 2010 s. The TCs that landed in the west of the Pearl River Estuary(PRE) have the highest frequency and the strongest intensity during landing, which bring the strongest winds; the TCs that landed in the PRE have the lowest frequency and the shortest duration after landing, which cause the strongest precipitation; the TCs that landed in the east of the PRE have the longest duration on the land. This study shows that near the center of the TCs that landed in the PRE, there is a weak anomalous cyclonic shear compared with the ones that landed in the west of the PRE. It is a confluence area of anomalous north wind and anomalous southwest wind, with better water vapor convergence and dynamic rising conditions, which is conducive to the formation of heavy precipitation.Compared with the TCs that landed in the PRE and in its east, there is a closed positive anomalous center of pressure gradient in the northwest center of the TCs that landed in its west, resulting in higher wind speeds in the west of the PRE. The characteristics of the three types of TCs in the GBA are highly related to TC-induced damage.In the future, the GBA needs to focus on preparing for TCs landing in its west. Zhuhai, Jiangmen and Huizhou are key cities to guard against TCs. The results of this study provide foundations for effective management and reduction of TC disaster risks in the future development of the GBA.
This paper applies statistical and synthetic analysis methods to study the characteristics of the three types of tropical cyclone(TC) that landed in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA) from 1981 to2018 and the reasons for the differences of TC-induced wind and precipitation. The results show that there are interdecadal changes in the frequency and intensity of the landfalling TCs in the GBA, with decreased frequency but increased intensity in the 2010 s. The TCs that landed in the west of the Pearl River Estuary(PRE) have the highest frequency and the strongest intensity during landing, which bring the strongest winds; the TCs that landed in the PRE have the lowest frequency and the shortest duration after landing, which cause the strongest precipitation; the TCs that landed in the east of the PRE have the longest duration on the land. This study shows that near the center of the TCs that landed in the PRE, there is a weak anomalous cyclonic shear compared with the ones that landed in the west of the PRE. It is a confluence area of anomalous north wind and anomalous southwest wind, with better water vapor convergence and dynamic rising conditions, which is conducive to the formation of heavy precipitation.Compared with the TCs that landed in the PRE and in its east, there is a closed positive anomalous center of pressure gradient in the northwest center of the TCs that landed in its west, resulting in higher wind speeds in the west of the PRE. The characteristics of the three types of TCs in the GBA are highly related to TC-induced damage.In the future, the GBA needs to focus on preparing for TCs landing in its west. Zhuhai, Jiangmen and Huizhou are key cities to guard against TCs. The results of this study provide foundations for effective management and reduction of TC disaster risks in the future development of the GBA.
2021, 27(3): 259-271.
doi: 10.46267/j.1006-8775.2021.023
Abstract:
A single-column model(SCM) is developed in the regional climate model RegCM4. The evolution of a dry convection boundary layer(DCBL) is used to evaluate this SCM. Moreover, four planetary boundary layer(PBL)schemes, namely the Holtslag-Boville scheme(HB), Yonsei University scheme(YSU), and two University of Washington schemes(UW01, Grenier-Bretherton-McCaa scheme and UW09, Bretherton-Park scheme), are compared by using the SCM approach. A large-eddy simulation(LES) of the DCBL is performed as a benchmark to examine how well a PBL parameterization scheme reproduces the LES results, and several diagnostic outputs are compared to evaluate the schemes. The results show that the SCM is properly constructed. In general, with the DCBL case, the YSU scheme performs best for reproducing the LES results, which include well-mixed features and vertical sensible heat fluxes; the simulated wind speed, turbulent kinetic energy, entrainment flux, and height of the entrainment zone are all underestimated in the UW09; the UW01 has all those biases of the UW09 but larger, and the simulated potential temperature is not well mixed; the HB is the least skillful scheme, by which the PBL height, entrainment flux, height of the entrainment zone, and the vertical gradients within the mixed layer are all overestimated, and a inversion layer near the top of the surface layer is wrongly simulated. Although more cases and further testing are required, these simulations show encouraging results towards the use of this SCM framework for evaluating the simulated physical processes by the RegCM4.
A single-column model(SCM) is developed in the regional climate model RegCM4. The evolution of a dry convection boundary layer(DCBL) is used to evaluate this SCM. Moreover, four planetary boundary layer(PBL)schemes, namely the Holtslag-Boville scheme(HB), Yonsei University scheme(YSU), and two University of Washington schemes(UW01, Grenier-Bretherton-McCaa scheme and UW09, Bretherton-Park scheme), are compared by using the SCM approach. A large-eddy simulation(LES) of the DCBL is performed as a benchmark to examine how well a PBL parameterization scheme reproduces the LES results, and several diagnostic outputs are compared to evaluate the schemes. The results show that the SCM is properly constructed. In general, with the DCBL case, the YSU scheme performs best for reproducing the LES results, which include well-mixed features and vertical sensible heat fluxes; the simulated wind speed, turbulent kinetic energy, entrainment flux, and height of the entrainment zone are all underestimated in the UW09; the UW01 has all those biases of the UW09 but larger, and the simulated potential temperature is not well mixed; the HB is the least skillful scheme, by which the PBL height, entrainment flux, height of the entrainment zone, and the vertical gradients within the mixed layer are all overestimated, and a inversion layer near the top of the surface layer is wrongly simulated. Although more cases and further testing are required, these simulations show encouraging results towards the use of this SCM framework for evaluating the simulated physical processes by the RegCM4.
Direct Radiative Effect of Aerosols on Net Ecosystem Carbon Exchange in the Pearl River Delta Region
2021, 27(3): 272-281.
doi: 10.46267/j.1006-8775.2021.024
Abstract:
The environmental impact of aerosols is currently a hot issue that has received worldwide attention. Lacking simultaneous observations of aerosols and carbon flux, the understanding of the aerosol radiative effect of urban agglomeration on the net ecosystem carbon exchange (NEE) is restricted. In 2009-2010, an observation of the aerosol optical property and CO2 flux was carried out at the Dongguan Meteorological Bureau Station (DMBS) using a sun photometer and eddy covariance systems. The different components of photosynthetically active radiation (PAR), including global PAR (GPAR), direct PAR (DPAR), and scattered PAR (FPAR), were calculated using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. The effects of PAR on the NEE between land-atmosphere systems were investigated. The results demonstrated that during the study period the aerosol optical depth (AOD) reduced the DPAR by 519.28±232.89 μmol photons · m−2 s−1, but increased the FPAR by 324.93±169.85μmol photons · m−2 s−1, ultimately leading to 194.34±92.62 μmol photons·m−2 s−1 decrease in the GPAR. All the PARs (including GPAR, DPAR, and FPAR) resulted in increases in the NEE (improved carbon absorption), but the FPAR has the strongest effect with the light use efficiency (LUE) being 1.12 times the values for the DPAR. The absorption of DPAR by the vegetation exhibited photo-inhibition in the radiation intensity > 600 photons · m−2 s−1; in contrast, the absorptions of FPAR did not exhibit apparent photo-inhibition. Compared with the FPAR caused by aerosols, the DPAR was not the primary factor affecting the NEE. On the contrary, the increase in AOD significantly increased the FPAR, enhancing the LUE of vegetation ecosystems and finally promoting the photosynthetic CO2 absorption.
The environmental impact of aerosols is currently a hot issue that has received worldwide attention. Lacking simultaneous observations of aerosols and carbon flux, the understanding of the aerosol radiative effect of urban agglomeration on the net ecosystem carbon exchange (NEE) is restricted. In 2009-2010, an observation of the aerosol optical property and CO2 flux was carried out at the Dongguan Meteorological Bureau Station (DMBS) using a sun photometer and eddy covariance systems. The different components of photosynthetically active radiation (PAR), including global PAR (GPAR), direct PAR (DPAR), and scattered PAR (FPAR), were calculated using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. The effects of PAR on the NEE between land-atmosphere systems were investigated. The results demonstrated that during the study period the aerosol optical depth (AOD) reduced the DPAR by 519.28±232.89 μmol photons · m−2 s−1, but increased the FPAR by 324.93±169.85μmol photons · m−2 s−1, ultimately leading to 194.34±92.62 μmol photons·m−2 s−1 decrease in the GPAR. All the PARs (including GPAR, DPAR, and FPAR) resulted in increases in the NEE (improved carbon absorption), but the FPAR has the strongest effect with the light use efficiency (LUE) being 1.12 times the values for the DPAR. The absorption of DPAR by the vegetation exhibited photo-inhibition in the radiation intensity > 600 photons · m−2 s−1; in contrast, the absorptions of FPAR did not exhibit apparent photo-inhibition. Compared with the FPAR caused by aerosols, the DPAR was not the primary factor affecting the NEE. On the contrary, the increase in AOD significantly increased the FPAR, enhancing the LUE of vegetation ecosystems and finally promoting the photosynthetic CO2 absorption.
2021, 27(3): 282-290.
doi: 10.46267/j.1006-8775.2021.025
Abstract:
An analysis of the delay Doppler maps (DDMs) data from the CYGNSS satellites is implemented to derive the sea surface height (SSH). An SSH estimation algorithm, the leading edge derivation (LED) method which is applied to the delay waveforms, is applied to the DDMs, while the tropospheric delay methods, the Saastamoinen method (SM) and the numerical method (NM) are used. The results show that when the SSH from Jason-2 is referred to as the truth, if the tropospheric delay is corrected, the SSH bias can decrease. The resulted SSH bias from the Jason-2 SSH by the LED retrieval method is of order meter. The resulted SSH deviation from the truth by the NM scheme is half as small as that by the SM scheme. Since the SM scheme is not applicable to the nonhydrostatical condition, the resulted bias is larger. The work can be applied to the Beidou system in the future.
An analysis of the delay Doppler maps (DDMs) data from the CYGNSS satellites is implemented to derive the sea surface height (SSH). An SSH estimation algorithm, the leading edge derivation (LED) method which is applied to the delay waveforms, is applied to the DDMs, while the tropospheric delay methods, the Saastamoinen method (SM) and the numerical method (NM) are used. The results show that when the SSH from Jason-2 is referred to as the truth, if the tropospheric delay is corrected, the SSH bias can decrease. The resulted SSH bias from the Jason-2 SSH by the LED retrieval method is of order meter. The resulted SSH deviation from the truth by the NM scheme is half as small as that by the SM scheme. Since the SM scheme is not applicable to the nonhydrostatical condition, the resulted bias is larger. The work can be applied to the Beidou system in the future.
2021, 27(3): 291-302.
doi: 10.46267/j.1006-8775.2021.026
Abstract:
Rainfall is triggered and mainly dominated by atmospheric thermo-dynamics and rich water vapor.Nonetheless, turbulence is also considered as an important factor influencing the evolution of rainfall microphysical parameters. To study such an influence, the present study utilized boundary layer wind profiler radar measurements. The separation point of the radar power spectral density data was carefully selected to classify rainfall and turbulence signals; the turbulent dissipation rate ε and rainfall microphysical parameters can be retrieved to analyze the relationship betweenε and microphysical parameters. According to the retrievals of two rainfall periods in Beijing 2016, it was observed that(1) ε in the precipitation area ranged from 10-3.5 to 10-1 m2 s-3 and was positively correlated with the falling velocity spectrum width; (2) interactions between turbulence and raindrops showed that small raindrops got enlarge through collision and coalescence in weak turbulence, but large raindrops broke up into small drops under strong turbulence, and the separation value of ε being weak or strong varied with rainfall attributes; (3) the variation of rainfall microphysical parameters(characteristic diameters, number concentration, rainfall intensity, and water content) in the middle stage were stronger than those in the early and the later stages of rainfall event; (4) unlike the obvious impacts on raindrop size and number concentration, turbulence impacts on rain rate and LWC were not significant because turbulence did not cause too much water vapor and heat exchange.
Rainfall is triggered and mainly dominated by atmospheric thermo-dynamics and rich water vapor.Nonetheless, turbulence is also considered as an important factor influencing the evolution of rainfall microphysical parameters. To study such an influence, the present study utilized boundary layer wind profiler radar measurements. The separation point of the radar power spectral density data was carefully selected to classify rainfall and turbulence signals; the turbulent dissipation rate ε and rainfall microphysical parameters can be retrieved to analyze the relationship betweenε and microphysical parameters. According to the retrievals of two rainfall periods in Beijing 2016, it was observed that(1) ε in the precipitation area ranged from 10-3.5 to 10-1 m2 s-3 and was positively correlated with the falling velocity spectrum width; (2) interactions between turbulence and raindrops showed that small raindrops got enlarge through collision and coalescence in weak turbulence, but large raindrops broke up into small drops under strong turbulence, and the separation value of ε being weak or strong varied with rainfall attributes; (3) the variation of rainfall microphysical parameters(characteristic diameters, number concentration, rainfall intensity, and water content) in the middle stage were stronger than those in the early and the later stages of rainfall event; (4) unlike the obvious impacts on raindrop size and number concentration, turbulence impacts on rain rate and LWC were not significant because turbulence did not cause too much water vapor and heat exchange.
2021, 27(3): 303-318.
doi: 10.46267/j.1006-8775.2021.027
Abstract:
Wavelet analysis was applied to lidar observations to retrieve the planetary boundary layer height (PBLH) over Guangzhou from September 2013 to November 2014 over Guangzhou. Impact of the boundary effect and the wavelet scale factor on the accuracy of the retrieved PBLH has been explored thoroughly. In addition, the PBLH diurnal variations and the relationship between PM2.5 concentration and PBLH during polluted and clean episodes were studied. Results indicate that the most steady retrieved PBLH can be obtained when scale factor is chosen between 300-390 m. The retrieved maximum and minimum PBLH in the annual mean diurnal cycle were ~1100 m and ~650 m, respectively. The PBLH was significantly lower in the dry season than in the wet season, with the average highest PBLH in the dry season and the wet season being ~1050 m and ~1200 m respectively. Compared to the wet season, the development of PBLH in the dry season was delayed by at least one hour due to the seasonal cycle of solar radiation. Episode analysis indicated that the PBLH was ~50% higher during clean episodes than during haze episodes. The average highest PBLH in the haze episodes and clean episodes were ~800 m and ~1300 m, respectively. A significant negative correlation between PBLH and PM2.5 concentration(r=-0.55**) is discovered.According to China "Ambient Air Quality Standard", the PBLH values in good and slightly polluted conditions were 1/6-1/3 lower than that in excellent conditions, while the corresponding PM2.5 concentration were ~2-2.5 times higher.
Wavelet analysis was applied to lidar observations to retrieve the planetary boundary layer height (PBLH) over Guangzhou from September 2013 to November 2014 over Guangzhou. Impact of the boundary effect and the wavelet scale factor on the accuracy of the retrieved PBLH has been explored thoroughly. In addition, the PBLH diurnal variations and the relationship between PM2.5 concentration and PBLH during polluted and clean episodes were studied. Results indicate that the most steady retrieved PBLH can be obtained when scale factor is chosen between 300-390 m. The retrieved maximum and minimum PBLH in the annual mean diurnal cycle were ~1100 m and ~650 m, respectively. The PBLH was significantly lower in the dry season than in the wet season, with the average highest PBLH in the dry season and the wet season being ~1050 m and ~1200 m respectively. Compared to the wet season, the development of PBLH in the dry season was delayed by at least one hour due to the seasonal cycle of solar radiation. Episode analysis indicated that the PBLH was ~50% higher during clean episodes than during haze episodes. The average highest PBLH in the haze episodes and clean episodes were ~800 m and ~1300 m, respectively. A significant negative correlation between PBLH and PM2.5 concentration(r=-0.55**) is discovered.According to China "Ambient Air Quality Standard", the PBLH values in good and slightly polluted conditions were 1/6-1/3 lower than that in excellent conditions, while the corresponding PM2.5 concentration were ~2-2.5 times higher.
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