2019 Vol. 36, No. 1
Display Method:
2019, 36(1): 1-14.
doi: 10.1007/s00376-018-8075-9
Abstract:
Aerosol optical depth (AOD) is the most basic parameter that describes the optical properties of atmospheric aerosols, and it can be used to indicate aerosol content. In this study, we assimilated AOD data from the Fengyun-3A (FY-3A) and MODIS meteorological satellite using the Gridpoint Statistical Interpolation three-dimensional variational data assimilation system. Experiments were conducted for a dust storm over East Asia in April 2011. Each 0600 UTC analysis initialized a 24-h Weather Research and Forecasting with Chemistry model forecast. The results generally showed that the assimilation of satellite AOD observational data can significantly improve model aerosol mass prediction skills. The AOD distribution of the analysis field was closer to the observations of the satellite after assimilation of satellite AOD data. In addition, the analysis resulting from the experiment assimilating both FY-3A/MERSI (Medium-resolution Spectral Imager) AOD data and MODIS AOD data had closer agreement with the ground-based values than the individual assimilation of the two datasets for the dust storm over East Asia. These results suggest that the Chinese FY-3A satellite aerosol products can be effectively applied to numerical models and dust weather analysis.
Aerosol optical depth (AOD) is the most basic parameter that describes the optical properties of atmospheric aerosols, and it can be used to indicate aerosol content. In this study, we assimilated AOD data from the Fengyun-3A (FY-3A) and MODIS meteorological satellite using the Gridpoint Statistical Interpolation three-dimensional variational data assimilation system. Experiments were conducted for a dust storm over East Asia in April 2011. Each 0600 UTC analysis initialized a 24-h Weather Research and Forecasting with Chemistry model forecast. The results generally showed that the assimilation of satellite AOD observational data can significantly improve model aerosol mass prediction skills. The AOD distribution of the analysis field was closer to the observations of the satellite after assimilation of satellite AOD data. In addition, the analysis resulting from the experiment assimilating both FY-3A/MERSI (Medium-resolution Spectral Imager) AOD data and MODIS AOD data had closer agreement with the ground-based values than the individual assimilation of the two datasets for the dust storm over East Asia. These results suggest that the Chinese FY-3A satellite aerosol products can be effectively applied to numerical models and dust weather analysis.
2019, 36(1): 15-28.
doi: 10.1007/s00376-018-8095-5
Abstract:
The diurnal variation of precipitation over the Dabie Mountains (DBM) in eastern China during the 2013 mei-yu season is investigated with forecasts of a regional convection-permitting model. Simulated precipitation is verified against surface rain-gauge observations. The observed morning precipitation peak on the windward (relative to the prevailing synoptic-scale wind) side of the DBM is reproduced with good spatial and temporal accuracy. The interaction between the DBM and a nocturnal boundary layer low-level jet (BLJ) due to the inertial oscillation mechanism is shown to be responsible for this precipitation peak. The BLJ is aligned with the lower-level southwesterly synoptic-scale flow that carries abundant moisture. The BLJ core is established at around 0200 LST upwind of the mountains. It moves towards the DBM and reaches maximum intensity at about 70 km ahead of the mountains. When the BLJ impinges upon the windward side of the DBM in the early morning, mechanical lifting of moist air leads to condensation and subsequent precipitation.
The diurnal variation of precipitation over the Dabie Mountains (DBM) in eastern China during the 2013 mei-yu season is investigated with forecasts of a regional convection-permitting model. Simulated precipitation is verified against surface rain-gauge observations. The observed morning precipitation peak on the windward (relative to the prevailing synoptic-scale wind) side of the DBM is reproduced with good spatial and temporal accuracy. The interaction between the DBM and a nocturnal boundary layer low-level jet (BLJ) due to the inertial oscillation mechanism is shown to be responsible for this precipitation peak. The BLJ is aligned with the lower-level southwesterly synoptic-scale flow that carries abundant moisture. The BLJ core is established at around 0200 LST upwind of the mountains. It moves towards the DBM and reaches maximum intensity at about 70 km ahead of the mountains. When the BLJ impinges upon the windward side of the DBM in the early morning, mechanical lifting of moist air leads to condensation and subsequent precipitation.
2019, 36(1): 29-40.
doi: 10.1007/s00376-018-8017-6
Abstract:
A fog monitor, hotplate total precipitation sensor, weather identifier and visibility sensor, ultrasonic wind speed meter, an icing gradient observation frame, and an automated weather station were involved in the observations at the Lushan Meteorological Bureau of Jiangxi Province, China. In this study, for the icing process under a cold surge from 20-25 January 2016, the duration, frequency, and spectrum distribution of agglomerate fog were analyzed. The effects of rain, snow, and supercooled fog on icing growth were studied and the icing and meteorological conditions at two heights (10 m and 1.5 m) were compared. There were 218 agglomerate fogs in this icing process, of which agglomerate fogs with durations less than and greater than 10 min accounted for 91.3% and 8.7%, respectively. The average time interval was 10.3 min. The fog droplet number concentration for sizes 2-15 μm and 30-50 μm increased during rainfall, and that for 2-27 μm decreased during snowfall. Icing grew rapidly (1.3 mm h-1) in the freezing rain phase but slowly (0.1 mm h-1) during the dry snow phase. Intensive supercooled fog, lower temperatures and increased wind speed all favored icing growth during dry snow (0.5 mm h-1). There were significant differences in the thickness, duration, density, and growth mechanism of icing at the heights of 10 m and 1.5 m. Differences in temperature and wind speed between the two heights were the main reasons for the differences in icing conditions, which indicated that icing was strongly affected by height.
A fog monitor, hotplate total precipitation sensor, weather identifier and visibility sensor, ultrasonic wind speed meter, an icing gradient observation frame, and an automated weather station were involved in the observations at the Lushan Meteorological Bureau of Jiangxi Province, China. In this study, for the icing process under a cold surge from 20-25 January 2016, the duration, frequency, and spectrum distribution of agglomerate fog were analyzed. The effects of rain, snow, and supercooled fog on icing growth were studied and the icing and meteorological conditions at two heights (10 m and 1.5 m) were compared. There were 218 agglomerate fogs in this icing process, of which agglomerate fogs with durations less than and greater than 10 min accounted for 91.3% and 8.7%, respectively. The average time interval was 10.3 min. The fog droplet number concentration for sizes 2-15 μm and 30-50 μm increased during rainfall, and that for 2-27 μm decreased during snowfall. Icing grew rapidly (1.3 mm h-1) in the freezing rain phase but slowly (0.1 mm h-1) during the dry snow phase. Intensive supercooled fog, lower temperatures and increased wind speed all favored icing growth during dry snow (0.5 mm h-1). There were significant differences in the thickness, duration, density, and growth mechanism of icing at the heights of 10 m and 1.5 m. Differences in temperature and wind speed between the two heights were the main reasons for the differences in icing conditions, which indicated that icing was strongly affected by height.
2019, 36(1): 41-54.
doi: 10.1007/s00376-018-8032-7
Abstract:
The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant overestimation in quantitative precipitation estimation (QPE) based on the Z-R (reflectivity factor-rain rate) relationship. The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity (VPR) correction. In this study, we applied bright-band correction algorithms to evaluate three different bands (S-, C- and X-band) of dual-polarized radars and to reduce overestimation errors in Z-R relationship-based QPEs. After the reflectivity was corrected by the algorithms using average VPR (AVPR) alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient (AVPR+CC), the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gauge observations, separately. The overestimation of Z-R relationship-based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE (root-mean-square error), RMAE (relative mean absolute error) and RMB (relative mean bias) of QPEs, averaged over all eight cases, the AVPR method improved from 2.28, 0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR+CC method improved to 1.44, 0.55 and 0.30, respectively. The QPEs after AVPR+CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.
The bright band, a layer of enhanced radar reflectivity associated with melting ice particles, is a major source of significant overestimation in quantitative precipitation estimation (QPE) based on the Z-R (reflectivity factor-rain rate) relationship. The effects of the bright band on radar-based QPE can be eliminated by vertical profile of reflectivity (VPR) correction. In this study, we applied bright-band correction algorithms to evaluate three different bands (S-, C- and X-band) of dual-polarized radars and to reduce overestimation errors in Z-R relationship-based QPEs. After the reflectivity was corrected by the algorithms using average VPR (AVPR) alone and a combination of average VPR and the vertical profile of the copolar correlation coefficient (AVPR+CC), the QPEs were derived. The bright-band correction and resulting QPEs were evaluated in eight precipitation events by comparing to the uncorrected reflectivity and rain-gauge observations, separately. The overestimation of Z-R relationship-based QPEs associated with the bright band was reduced after correction by the two schemes for which hourly rainfall was less than 5 mm. For the verification metrics of RMSE (root-mean-square error), RMAE (relative mean absolute error) and RMB (relative mean bias) of QPEs, averaged over all eight cases, the AVPR method improved from 2.28, 0.94 and 0.78 to 1.55, 0.60 and 0.40, respectively, while the AVPR+CC method improved to 1.44, 0.55 and 0.30, respectively. The QPEs after AVPR+CC correction had less overestimation than those after AVPR correction, and similar conclusions were drawn for all three different bands of dual-polarized radars.
2019, 36(1): 55-64.
doi: 10.1007/s00376-018-8072-z
Abstract:
This study documents the first two principal modes of interannual variability of midsummer precipitation over Northeast China (NEC) and their associated atmospheric circulation anomalies. It is shown that the first principal mode exhibits the largest amount of variability in precipitation over the south of NEC (referred to as the south mode), whereas the second principal mode behaves with the greatest precipitation anomaly over the north of NEC (referred to as the north mode). Further findings reveal that, through modulating moisture transportation and upper- and lower-troposphere divergence circulation as well as vertical movement over NEC, the anomalous northwestern Pacific anticyclone and the anticyclone centered over northern NEC exert the dominant influence on the south and north modes, respectively. Additionally, it is quantitatively estimated that water vapor across the southern boundary of NEC dominates the moisture budget for the south mode, while the north mode has a close connection with moisture through NEC's northern and western boundaries. Furthermore, the north (south) mode is strongly related to the intensity (meridional shift) of the East Asian westerly jet.
This study documents the first two principal modes of interannual variability of midsummer precipitation over Northeast China (NEC) and their associated atmospheric circulation anomalies. It is shown that the first principal mode exhibits the largest amount of variability in precipitation over the south of NEC (referred to as the south mode), whereas the second principal mode behaves with the greatest precipitation anomaly over the north of NEC (referred to as the north mode). Further findings reveal that, through modulating moisture transportation and upper- and lower-troposphere divergence circulation as well as vertical movement over NEC, the anomalous northwestern Pacific anticyclone and the anticyclone centered over northern NEC exert the dominant influence on the south and north modes, respectively. Additionally, it is quantitatively estimated that water vapor across the southern boundary of NEC dominates the moisture budget for the south mode, while the north mode has a close connection with moisture through NEC's northern and western boundaries. Furthermore, the north (south) mode is strongly related to the intensity (meridional shift) of the East Asian westerly jet.
2019, 36(1): 65-78.
doi: 10.1007/s00376-018-7234-3
Abstract:
In this study, a three-dimensional mesoscale model was used to numerically simulate the well-known "98.7" heavy rainfall event that affected the Yangtze Valley in July 1998. Two experiments were conducted to analyze the impact of moist processes on the development of meso-β scale vortices (MβV) and their triggering by mesoscale wind perturbation (MWP). In the experiment in which the latent heat feedback (LHF) scheme was switched off, a stable low-level col field (i.e., saddle field——a region between two lows and two highs in the isobaric surface) formed, and the MWP triggered a weak MβV. However, when the LHF scheme was switched on as the MWP was introduced into the model, the MβV developed quickly and intense rainfall and a mesoscale low-level jet (mLLJ) were generated. The thickness of the air column and average temperature between 400 and 700 hPa decreased without the feedback of latent heat, whereas they increased quickly when the LHF scheme was switched on, with the air pressure falling at low levels but rising at upper levels. A schematic representation of the positive feedbacks among the mesoscale vortex, rainfall, and mLLJ shows that in the initial stage of the MβV, the MWP triggers light rainfall and the latent heat occurs at low levels, which leads to weak convergence and ageostrophic winds. In the mature stage of the MβV, convection extends to the middle-to-upper levels, resulting in an increase in the average temperature and a stretching of the air column. A low-level cyclonic circulation forms under the effect of Coriolis torque, and the mLLJ forms to the southeast of the MβV.
In this study, a three-dimensional mesoscale model was used to numerically simulate the well-known "98.7" heavy rainfall event that affected the Yangtze Valley in July 1998. Two experiments were conducted to analyze the impact of moist processes on the development of meso-β scale vortices (MβV) and their triggering by mesoscale wind perturbation (MWP). In the experiment in which the latent heat feedback (LHF) scheme was switched off, a stable low-level col field (i.e., saddle field——a region between two lows and two highs in the isobaric surface) formed, and the MWP triggered a weak MβV. However, when the LHF scheme was switched on as the MWP was introduced into the model, the MβV developed quickly and intense rainfall and a mesoscale low-level jet (mLLJ) were generated. The thickness of the air column and average temperature between 400 and 700 hPa decreased without the feedback of latent heat, whereas they increased quickly when the LHF scheme was switched on, with the air pressure falling at low levels but rising at upper levels. A schematic representation of the positive feedbacks among the mesoscale vortex, rainfall, and mLLJ shows that in the initial stage of the MβV, the MWP triggers light rainfall and the latent heat occurs at low levels, which leads to weak convergence and ageostrophic winds. In the mature stage of the MβV, convection extends to the middle-to-upper levels, resulting in an increase in the average temperature and a stretching of the air column. A low-level cyclonic circulation forms under the effect of Coriolis torque, and the mLLJ forms to the southeast of the MβV.
2019, 36(1): 79-92.
doi: 10.1007/s00376-018-8035-4
Abstract:
The land surface processes of the Noah-MP and Noah models are evaluated over four typical landscapes in the Haihe River Basin (HRB) using in-situ observations. The simulated soil temperature and moisture in the two land surface models (LSMs) is consistent with the observation, especially in the rainy season. The models reproduce the mean values and seasonality of the energy fluxes of the croplands, despite the obvious underestimated total evaporation. Noah shows the lower deep soil temperature. The net radiation is well simulated for the diurnal time scale. The daytime latent heat fluxes are always underestimated, while the sensible heat fluxes are overestimated to some degree. Compared with Noah, Noah-MP has improved daily average soil heat flux with diurnal variations. Generally, Noah-MP performs fairly well for different landscapes of the HRB. The simulated cold bias in soil temperature is possibly linked with the parameterized partition of the energy into surface fluxes. Thus, further improvement of these LSMs remains a major challenge.
The land surface processes of the Noah-MP and Noah models are evaluated over four typical landscapes in the Haihe River Basin (HRB) using in-situ observations. The simulated soil temperature and moisture in the two land surface models (LSMs) is consistent with the observation, especially in the rainy season. The models reproduce the mean values and seasonality of the energy fluxes of the croplands, despite the obvious underestimated total evaporation. Noah shows the lower deep soil temperature. The net radiation is well simulated for the diurnal time scale. The daytime latent heat fluxes are always underestimated, while the sensible heat fluxes are overestimated to some degree. Compared with Noah, Noah-MP has improved daily average soil heat flux with diurnal variations. Generally, Noah-MP performs fairly well for different landscapes of the HRB. The simulated cold bias in soil temperature is possibly linked with the parameterized partition of the energy into surface fluxes. Thus, further improvement of these LSMs remains a major challenge.
2019, 36(1): 93-103.
doi: 10.1007/s00376-018-7296-2
Abstract:
Variation in the location of the South Asian High (SAH) in early boreal summer is strongly influenced by elevated surface heating from the Tibetan Plateau (TP) and the Iranian Plateau (IP). Based on observational and ERA-Interim data, diagnostic analyses reveal that the interannual northwestward-southeastward (NW-SE) shift of the SAH in June is more closely correlated with the synergistic effect of concurrent surface thermal anomalies over the TP and IP than with each single surface thermal anomaly over either plateau from the preceding May. Concurrent surface thermal anomalies over these two plateaus in May are characterized by a negative correlation between sensible heat flux over most parts of the TP (TPSH) and IP (IPSH). This anomaly pattern can persist till June and influences the NW-SE shift of the SAH in June through the release of latent heat (LH) over northeastern India. When the IPSH is stronger (weaker) and the TPSH is weaker (stronger) than normal in May, an anomalous cyclone (anticyclone) appears over northern India at 850 hPa, which is accompanied by the ascent (descent) of air and anomalous convergence (divergence) of moisture flux in May and June. Therefore, the LH release over northeastern India is strengthened (weakened) and the vertical gradient of apparent heat source is decreased (increased) in the upper troposphere, which is responsible for the northwestward (southeastward) shift of the SAH in June.
Variation in the location of the South Asian High (SAH) in early boreal summer is strongly influenced by elevated surface heating from the Tibetan Plateau (TP) and the Iranian Plateau (IP). Based on observational and ERA-Interim data, diagnostic analyses reveal that the interannual northwestward-southeastward (NW-SE) shift of the SAH in June is more closely correlated with the synergistic effect of concurrent surface thermal anomalies over the TP and IP than with each single surface thermal anomaly over either plateau from the preceding May. Concurrent surface thermal anomalies over these two plateaus in May are characterized by a negative correlation between sensible heat flux over most parts of the TP (TPSH) and IP (IPSH). This anomaly pattern can persist till June and influences the NW-SE shift of the SAH in June through the release of latent heat (LH) over northeastern India. When the IPSH is stronger (weaker) and the TPSH is weaker (stronger) than normal in May, an anomalous cyclone (anticyclone) appears over northern India at 850 hPa, which is accompanied by the ascent (descent) of air and anomalous convergence (divergence) of moisture flux in May and June. Therefore, the LH release over northeastern India is strengthened (weakened) and the vertical gradient of apparent heat source is decreased (increased) in the upper troposphere, which is responsible for the northwestward (southeastward) shift of the SAH in June.
2019, 36(1): 104-118.
doi: 10.1007/s00376-018-7242-3
Abstract:
In this study, we evaluate the forecast skill of the subseasonal-to-seasonal (S2S) prediction model of the Beijing Climate Center (BCC) for the boreal summer intraseasonal oscillation (BSISO). We also discuss the key factors that inhibit the BSISO forecast skill in this model. Based on the bivariate anomaly correlation coefficient (ACC) of the BSISO index, defined by the first two EOF modes of outgoing longwave radiation and 850-hPa zonal wind anomalies over the Asian monsoon region, we found that the hindcast skill degraded as the lead time increased. The ACC dropped to below 0.5 for lead times of 11 days and longer when the predicted BSISO showed weakened strength and insignificant northward propagation. To identify what causes the weakened forecast skill of BSISO at the forecast lead time of 11 days, we diagnosed the main mechanisms responsible for the BSISO northward propagation. The same analysis was also carried out using the observations and the outputs of the four-day forecast lead that successfully predicted the observed northward-propagating BSISO. We found that the lack of northward propagation at the 11-day forecast lead was due to insufficient increases in low-level cyclonic vorticity, moistening and warm temperature anomalies to the north of the convection, which were induced by the interaction between background mean flows and BSISO-related anomalous fields. The BCC S2S model can predict the background monsoon circulations, such as the low-level southerly and the northerly and easterly vertical shears, but has limited capability in forecasting the distributions of circulation and moisture anomalies.
In this study, we evaluate the forecast skill of the subseasonal-to-seasonal (S2S) prediction model of the Beijing Climate Center (BCC) for the boreal summer intraseasonal oscillation (BSISO). We also discuss the key factors that inhibit the BSISO forecast skill in this model. Based on the bivariate anomaly correlation coefficient (ACC) of the BSISO index, defined by the first two EOF modes of outgoing longwave radiation and 850-hPa zonal wind anomalies over the Asian monsoon region, we found that the hindcast skill degraded as the lead time increased. The ACC dropped to below 0.5 for lead times of 11 days and longer when the predicted BSISO showed weakened strength and insignificant northward propagation. To identify what causes the weakened forecast skill of BSISO at the forecast lead time of 11 days, we diagnosed the main mechanisms responsible for the BSISO northward propagation. The same analysis was also carried out using the observations and the outputs of the four-day forecast lead that successfully predicted the observed northward-propagating BSISO. We found that the lack of northward propagation at the 11-day forecast lead was due to insufficient increases in low-level cyclonic vorticity, moistening and warm temperature anomalies to the north of the convection, which were induced by the interaction between background mean flows and BSISO-related anomalous fields. The BCC S2S model can predict the background monsoon circulations, such as the low-level southerly and the northerly and easterly vertical shears, but has limited capability in forecasting the distributions of circulation and moisture anomalies.
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