2016 Vol. 33, No. 10
Display Method:
2016, 33(10): 1106-1119.
doi: 10.1007/s00376-016-5290-0
Abstract:
This paper examines how assimilating surface observations can improve the analysis and forecast ability of a four-dimensional Variational Doppler Radar Analysis System (VDRAS). Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational (4DVAR) data assimilation system. A squall-line case observed during a field campaign is selected to investigate the performance of the technique. A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions. The surface-based cold pool, divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation. Three experiments——assimilating radar data only, assimilating radar data with surface data blended in a mesoscale background, and assimilating both radar and surface observations with a 4DVAR cost function——are conducted to examine the impact of the surface data assimilation. Independent surface and wind profiler observations are used for verification. The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations. It is also shown that the additional surface data can help improve the analysis and forecast at low levels. Surface and low-level features of the squall line——including the surface warm inflow, cold pool, gust front, and low-level wind——are much closer to the observations after assimilating the surface data in VDRAS.
This paper examines how assimilating surface observations can improve the analysis and forecast ability of a four-dimensional Variational Doppler Radar Analysis System (VDRAS). Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational (4DVAR) data assimilation system. A squall-line case observed during a field campaign is selected to investigate the performance of the technique. A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions. The surface-based cold pool, divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation. Three experiments——assimilating radar data only, assimilating radar data with surface data blended in a mesoscale background, and assimilating both radar and surface observations with a 4DVAR cost function——are conducted to examine the impact of the surface data assimilation. Independent surface and wind profiler observations are used for verification. The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations. It is also shown that the additional surface data can help improve the analysis and forecast at low levels. Surface and low-level features of the squall line——including the surface warm inflow, cold pool, gust front, and low-level wind——are much closer to the observations after assimilating the surface data in VDRAS.
2016, 33(10): 1120-1136.
doi: 10.1007/s00376-016-6024-z
Abstract:
The initiation of convective cells in the late morning of 24 June 2010 along the eastward extending ridge of the Dabie Mountains in the Anhui region, China, is studied through numerical simulations that include local data assimilation. A primary convergence line is found over the ridge of the Dabie Mountains, and along the ridge line several locally enhanced convergence centers preferentially initiate convection. Three processes responsible for creating the overall convergence pattern are identified. First, thermally-driven upslope winds induce convergence zones over the main mountain peaks along the ridge, which are shifted slightly downwind in location by the moderate low-level easterly flow found on the north side of a Mei-yu front. Second, flows around the main mountain peaks along the ridge create further convergence on the lee side of the peaks. Third, upslope winds develop along the roughly north-south oriented valleys on both sides of the ridge due to thermal and dynamic channeling effects, and create additional convergence between the peaks along the ridge. The superposition of the above convergence features creates the primary convergence line along the ridge line of the Dabie Mountains. Locally enhanced convergence centers on the primary line cause the initiation of the first convection cells along the ridge. These conclusions are supported by two sensitivity experiments in which the environmental wind (dynamic forcing) or radiative and land surface thermal forcing are removed, respectively. Overall, the thermal forcing effects are stronger than dynamic forcing given the relatively weak environmental flow.
The initiation of convective cells in the late morning of 24 June 2010 along the eastward extending ridge of the Dabie Mountains in the Anhui region, China, is studied through numerical simulations that include local data assimilation. A primary convergence line is found over the ridge of the Dabie Mountains, and along the ridge line several locally enhanced convergence centers preferentially initiate convection. Three processes responsible for creating the overall convergence pattern are identified. First, thermally-driven upslope winds induce convergence zones over the main mountain peaks along the ridge, which are shifted slightly downwind in location by the moderate low-level easterly flow found on the north side of a Mei-yu front. Second, flows around the main mountain peaks along the ridge create further convergence on the lee side of the peaks. Third, upslope winds develop along the roughly north-south oriented valleys on both sides of the ridge due to thermal and dynamic channeling effects, and create additional convergence between the peaks along the ridge. The superposition of the above convergence features creates the primary convergence line along the ridge line of the Dabie Mountains. Locally enhanced convergence centers on the primary line cause the initiation of the first convection cells along the ridge. These conclusions are supported by two sensitivity experiments in which the environmental wind (dynamic forcing) or radiative and land surface thermal forcing are removed, respectively. Overall, the thermal forcing effects are stronger than dynamic forcing given the relatively weak environmental flow.
2016, 33(10): 1137-1142.
doi: 10.1007/s00376-016-5218-8
Abstract:
The precipitation responses to the radiative effects of ice clouds are investigated through analysis of five-day and horizontally averaged data from 2D cumulus ensemble model experiments of a pre-summer torrential precipitation event. The exclusion of the radiative effects of ice clouds lowered the precipitation rate through a substantial reduction in the decrease of hydrometeors when the radiative effects of water clouds were switched on, whereas it increased the precipitation rate through hydrometeor change from an increase to a decrease when the radiative effects of ice clouds were turned off. The weakened hydrometeor decrease was associated with the enhanced longwave radiative cooling mainly through the decreases in the melting of non-precipitating ice to non-precipitating water. The hydrometeor change from an increase to a decrease corresponded to the strengthened longwave radiative cooling in the upper troposphere through the weakened collection of non-precipitating water by precipitation water.
The precipitation responses to the radiative effects of ice clouds are investigated through analysis of five-day and horizontally averaged data from 2D cumulus ensemble model experiments of a pre-summer torrential precipitation event. The exclusion of the radiative effects of ice clouds lowered the precipitation rate through a substantial reduction in the decrease of hydrometeors when the radiative effects of water clouds were switched on, whereas it increased the precipitation rate through hydrometeor change from an increase to a decrease when the radiative effects of ice clouds were turned off. The weakened hydrometeor decrease was associated with the enhanced longwave radiative cooling mainly through the decreases in the melting of non-precipitating ice to non-precipitating water. The hydrometeor change from an increase to a decrease corresponded to the strengthened longwave radiative cooling in the upper troposphere through the weakened collection of non-precipitating water by precipitation water.
2016, 33(10): 1143-1157.
doi: 10.1007/s00376-016-5255-3
Abstract:
Different choices of control variables in variational assimilation can bring about different influences on the analyzed atmospheric state. Based on the WRF model's three-dimensional variational assimilation system, this study compares the behavior of two momentum control variable options——streamfunction velocity potential (ψ-χ) and horizontal wind components (U-V)——in radar wind data assimilation for a squall line case that occurred in Jiangsu Province on 24 August 2014. The wind increment from the single observation test shows that the ψ-χ control variable scheme produces negative increments in the neighborhood around the observation point because streamfunction and velocity potential preserve integrals of velocity. On the contrary, the U-V control variable scheme objectively reflects the information of the observation itself. Furthermore, radial velocity data from 17 Doppler radars in eastern China are assimilated. As compared to the impact of conventional observation, the assimilation of radar radial velocity based on the U-V control variable scheme significantly improves the mesoscale dynamic field in the initial condition. The enhanced low-level jet stream, water vapor convergence and low-level wind shear result in better squall line forecasting. However, the ψ-χ control variable scheme generates a discontinuous wind field and unrealistic convergence/divergence in the analyzed field, which lead to a degraded precipitation forecast.
Different choices of control variables in variational assimilation can bring about different influences on the analyzed atmospheric state. Based on the WRF model's three-dimensional variational assimilation system, this study compares the behavior of two momentum control variable options——streamfunction velocity potential (ψ-χ) and horizontal wind components (U-V)——in radar wind data assimilation for a squall line case that occurred in Jiangsu Province on 24 August 2014. The wind increment from the single observation test shows that the ψ-χ control variable scheme produces negative increments in the neighborhood around the observation point because streamfunction and velocity potential preserve integrals of velocity. On the contrary, the U-V control variable scheme objectively reflects the information of the observation itself. Furthermore, radial velocity data from 17 Doppler radars in eastern China are assimilated. As compared to the impact of conventional observation, the assimilation of radar radial velocity based on the U-V control variable scheme significantly improves the mesoscale dynamic field in the initial condition. The enhanced low-level jet stream, water vapor convergence and low-level wind shear result in better squall line forecasting. However, the ψ-χ control variable scheme generates a discontinuous wind field and unrealistic convergence/divergence in the analyzed field, which lead to a degraded precipitation forecast.
2016, 33(10): 1158-1170.
doi: 10.1007/s00376-016-6004-3
Abstract:
Hydrometeor variables (cloud water and cloud ice mixing ratios) are added into the WRF three-dimensional variational assimilation system as additional control variables to directly analyze hydrometeors by assimilating cloud observations. In addition, the background error covariance matrix of hydrometeors is modeled through a control variable transform, and its characteristics discussed in detail. A suite of experiments using four microphysics schemes (LIN, SBU-YLIN, WDM6 and WSM6) are performed with and without assimilating satellite cloud liquid/ice water path. We find analysis of hydrometeors with cloud assimilation to be significantly improved, and the increment and distribution of hydrometeors are consistent with the characteristics of background error covariance. Diagnostic results suggest that the forecast with cloud assimilation represents a significant improvement, especially the ability to forecast precipitation in the first seven hours. It is also found that the largest improvement occurs in the experiment using the WDM6 scheme, since the assimilated cloud information can sustain for longer in this scheme. The least improvement, meanwhile, appears in the experiment using the SBU-YLIN scheme.
Hydrometeor variables (cloud water and cloud ice mixing ratios) are added into the WRF three-dimensional variational assimilation system as additional control variables to directly analyze hydrometeors by assimilating cloud observations. In addition, the background error covariance matrix of hydrometeors is modeled through a control variable transform, and its characteristics discussed in detail. A suite of experiments using four microphysics schemes (LIN, SBU-YLIN, WDM6 and WSM6) are performed with and without assimilating satellite cloud liquid/ice water path. We find analysis of hydrometeors with cloud assimilation to be significantly improved, and the increment and distribution of hydrometeors are consistent with the characteristics of background error covariance. Diagnostic results suggest that the forecast with cloud assimilation represents a significant improvement, especially the ability to forecast precipitation in the first seven hours. It is also found that the largest improvement occurs in the experiment using the WDM6 scheme, since the assimilated cloud information can sustain for longer in this scheme. The least improvement, meanwhile, appears in the experiment using the SBU-YLIN scheme.
2016, 33(10): 1171-1184.
doi: 10.1007/s00376-016-5208-x
Abstract:
The entrainment flux ratio A e and the inversion layer (IL) thickness are two key parameters in a mixed layer model. A e is defined as the ratio of the entrainment heat flux at the mixed layer top to the surface heat flux. The IL is the layer between the mixed layer and the free atmosphere. In this study, a parameterization of A e is derived from the TKE budget in the first-order model for a well-developed CBL under the condition of linearly sheared geostrophic velocity with a zero value at the surface. It is also appropriate for a CBL under the condition of geostrophic velocity remaining constant with height. LESs are conducted under the above two conditions to determine the coefficients in the parameterization scheme. Results suggest that about 43% of the shear-produced TKE in the IL is available for entrainment, while the shear-produced TKE in the mixed layer and surface layer have little effect on entrainment. Based on this scheme, a new scale of convective turbulence velocity is proposed and applied to parameterize the IL thickness. The LES outputs for the CBLs under the condition of linearly sheared geostrophic velocity with a non-zero surface value are used to verify the performance of the parameterization scheme. It is found that the parameterized A e and IL thickness agree well with the LES outputs.
The entrainment flux ratio A e and the inversion layer (IL) thickness are two key parameters in a mixed layer model. A e is defined as the ratio of the entrainment heat flux at the mixed layer top to the surface heat flux. The IL is the layer between the mixed layer and the free atmosphere. In this study, a parameterization of A e is derived from the TKE budget in the first-order model for a well-developed CBL under the condition of linearly sheared geostrophic velocity with a zero value at the surface. It is also appropriate for a CBL under the condition of geostrophic velocity remaining constant with height. LESs are conducted under the above two conditions to determine the coefficients in the parameterization scheme. Results suggest that about 43% of the shear-produced TKE in the IL is available for entrainment, while the shear-produced TKE in the mixed layer and surface layer have little effect on entrainment. Based on this scheme, a new scale of convective turbulence velocity is proposed and applied to parameterize the IL thickness. The LES outputs for the CBLs under the condition of linearly sheared geostrophic velocity with a non-zero surface value are used to verify the performance of the parameterization scheme. It is found that the parameterized A e and IL thickness agree well with the LES outputs.
2016, 33(10): 1185-1198.
doi: 10.1007/s00376-016-5209-9
Abstract:
Following the parameterization of sheared entrainment obtained in the companion paper, Liu et al.(2016), the present study aims to further investigate the characteristics of entrainment, and develop a simple model for predicting the growth rate of a well-developed and sheared CBL. The relative stratification, defined as the ratio of the stratification in the free atmosphere to that in the entrainment zone, is found to be a function of entrainment flux ratio (A e). This leads to a simple expression of the entrainment rate, in which A e needs to be parameterized. According to the results in Liu et al.(2016), A e can be simply expressed as the ratio of the convective velocity scale in the sheared CBL to that in the shear-free CBL. The parameterization of the convective velocity scale in the sheared CBL is obtained by analytically solving the bulk model with several assumptions and approximations. Results indicate that the entrainment process is influenced by the dynamic effect, the interaction between mean shear and environmental stratification, and one other term that includes the Coriolis effect. These three parameterizations constitute a simple model for predicting the growth rate of a well-developed and sheared CBL. This model is validated by outputs of LESs, and the results show that it performs satisfactorily. Compared with bulk models, this model does not need to solve a set of equations for the CBL. It is more convenient to apply in numerical models.
Following the parameterization of sheared entrainment obtained in the companion paper, Liu et al.(2016), the present study aims to further investigate the characteristics of entrainment, and develop a simple model for predicting the growth rate of a well-developed and sheared CBL. The relative stratification, defined as the ratio of the stratification in the free atmosphere to that in the entrainment zone, is found to be a function of entrainment flux ratio (A e). This leads to a simple expression of the entrainment rate, in which A e needs to be parameterized. According to the results in Liu et al.(2016), A e can be simply expressed as the ratio of the convective velocity scale in the sheared CBL to that in the shear-free CBL. The parameterization of the convective velocity scale in the sheared CBL is obtained by analytically solving the bulk model with several assumptions and approximations. Results indicate that the entrainment process is influenced by the dynamic effect, the interaction between mean shear and environmental stratification, and one other term that includes the Coriolis effect. These three parameterizations constitute a simple model for predicting the growth rate of a well-developed and sheared CBL. This model is validated by outputs of LESs, and the results show that it performs satisfactorily. Compared with bulk models, this model does not need to solve a set of equations for the CBL. It is more convenient to apply in numerical models.
2016, 33(10): 1199-1208.
doi: 10.1007/s00376-016-6036-8
Abstract:
Atmospheric variability is driven not only by internal dynamics, but also by external forcing, such as soil states, SST, snow, sea-ice cover, and so on. To investigate the forecast uncertainties and effects of land surface processes on numerical weather prediction, we added modules to perturb soil moisture and soil temperature into NCEP's Global Ensemble Forecast System (GEFS), and compared the results of a set of experiments involving different configurations of land surface and atmospheric perturbation. It was found that uncertainties in different soil layers varied due to the multiple timescales of interactions between land surface and atmospheric processes. Perturbations of the soil moisture and soil temperature at the land surface changed sensible and latent heat flux obviously, as compared to the less or indirect land surface perturbation experiment from the day-to-day forecasts. Soil state perturbations led to greater variation in surface heat fluxes that transferred to the upper troposphere, thus reflecting interactions and the response to atmospheric external forcing. Various verification scores were calculated in this study. The results indicated that taking the uncertainties of land surface processes into account in GEFS could contribute a slight improvement in forecast skill in terms of resolution and reliability, a noticeable reduction in forecast error, as well as an increase in ensemble spread in an under-dispersive system. This paper provides a preliminary evaluation of the effects of land surface processes on predictability. Further research using more complex and suitable methods is needed to fully explore our understanding in this area.
Atmospheric variability is driven not only by internal dynamics, but also by external forcing, such as soil states, SST, snow, sea-ice cover, and so on. To investigate the forecast uncertainties and effects of land surface processes on numerical weather prediction, we added modules to perturb soil moisture and soil temperature into NCEP's Global Ensemble Forecast System (GEFS), and compared the results of a set of experiments involving different configurations of land surface and atmospheric perturbation. It was found that uncertainties in different soil layers varied due to the multiple timescales of interactions between land surface and atmospheric processes. Perturbations of the soil moisture and soil temperature at the land surface changed sensible and latent heat flux obviously, as compared to the less or indirect land surface perturbation experiment from the day-to-day forecasts. Soil state perturbations led to greater variation in surface heat fluxes that transferred to the upper troposphere, thus reflecting interactions and the response to atmospheric external forcing. Various verification scores were calculated in this study. The results indicated that taking the uncertainties of land surface processes into account in GEFS could contribute a slight improvement in forecast skill in terms of resolution and reliability, a noticeable reduction in forecast error, as well as an increase in ensemble spread in an under-dispersive system. This paper provides a preliminary evaluation of the effects of land surface processes on predictability. Further research using more complex and suitable methods is needed to fully explore our understanding in this area.
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