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- Author or Editor: Cathy Hohenegger x
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Abstract
In this study, we estimate bulk entrainment rates for deep convection in convection-permitting simulations, conducted over the tropical Atlantic Ocean, encompassing parts of Africa and South America. We find that, even though entrainment rates decrease with height in all regions, they are, when averaging between 600 and 800 hPa, generally higher over land than over ocean. This is so because, over Amazonia, shallow convection causes an increase of bulk entrainment rates at lower levels and because, over West Africa, where entrainment rates are highest, convection is organized in squall lines. These squall lines are associated with strong mesoscale convergence, causing more intense updrafts and stronger turbulence generation in the vicinity of updrafts, increasing the entrainment rates. With the exception of West Africa, entrainment rates differ less across regions than across different environments within the regions. In contrast to what is usually assumed in convective parameterizations, entrainment rates increase with environmental humidity. Furthermore, over ocean, they increase with static stability, while over land, they decrease. In addition, confirming the results of a recent idealized study, entrainment rates increase with convective aggregation, except in regions dominated by squall lines, like over West Africa.
Abstract
In this study, we estimate bulk entrainment rates for deep convection in convection-permitting simulations, conducted over the tropical Atlantic Ocean, encompassing parts of Africa and South America. We find that, even though entrainment rates decrease with height in all regions, they are, when averaging between 600 and 800 hPa, generally higher over land than over ocean. This is so because, over Amazonia, shallow convection causes an increase of bulk entrainment rates at lower levels and because, over West Africa, where entrainment rates are highest, convection is organized in squall lines. These squall lines are associated with strong mesoscale convergence, causing more intense updrafts and stronger turbulence generation in the vicinity of updrafts, increasing the entrainment rates. With the exception of West Africa, entrainment rates differ less across regions than across different environments within the regions. In contrast to what is usually assumed in convective parameterizations, entrainment rates increase with environmental humidity. Furthermore, over ocean, they increase with static stability, while over land, they decrease. In addition, confirming the results of a recent idealized study, entrainment rates increase with convective aggregation, except in regions dominated by squall lines, like over West Africa.
Abstract
The rapid amplification of small-amplitude perturbations by the chaotic nature of the atmospheric dynamics intrinsically limits the skill of deterministic weather forecasts. In this study, limited-area cloud-resolving numerical weather prediction (NWP) experiments are conducted to investigate the role of mesoscale processes in determining predictability. The focus is set on domain-internal error growth by integrating an ensemble of simulations using slightly modified initial conditions but identical lateral boundary conditions. It is found that the predictability of the three investigated cases taken from the Mesoscale Alpine Programme (MAP) differs tremendously. In terms of normalized precipitation spread, values between 0.05 (highly predictable) and 1 (virtually unpredictable) are obtained. Analysis of the derived ensemble spread demonstrates that the diabatic forcing associated with moist dynamics is the prime source of rapid error growth. However, in agreement with an earlier study it is found that the differentiation between convective and stratiform rain is unable to account for the distinctive precipitation spreads of the three cases. In particular, instability indices are demonstrated to be poor predictors of the predictability level. An alternate hypothesis is proposed and tested. It is inspired by the dynamical instability theory and states that significant loss of predictability only occurs over moist convectively unstable regions that are able to sustain propagation of energy against the mean flow. Using a linear analysis of gravity wave propagation, this hypothesis is shown to provide successful estimates of the predictability level for the three cases under consideration.
Abstract
The rapid amplification of small-amplitude perturbations by the chaotic nature of the atmospheric dynamics intrinsically limits the skill of deterministic weather forecasts. In this study, limited-area cloud-resolving numerical weather prediction (NWP) experiments are conducted to investigate the role of mesoscale processes in determining predictability. The focus is set on domain-internal error growth by integrating an ensemble of simulations using slightly modified initial conditions but identical lateral boundary conditions. It is found that the predictability of the three investigated cases taken from the Mesoscale Alpine Programme (MAP) differs tremendously. In terms of normalized precipitation spread, values between 0.05 (highly predictable) and 1 (virtually unpredictable) are obtained. Analysis of the derived ensemble spread demonstrates that the diabatic forcing associated with moist dynamics is the prime source of rapid error growth. However, in agreement with an earlier study it is found that the differentiation between convective and stratiform rain is unable to account for the distinctive precipitation spreads of the three cases. In particular, instability indices are demonstrated to be poor predictors of the predictability level. An alternate hypothesis is proposed and tested. It is inspired by the dynamical instability theory and states that significant loss of predictability only occurs over moist convectively unstable regions that are able to sustain propagation of energy against the mean flow. Using a linear analysis of gravity wave propagation, this hypothesis is shown to provide successful estimates of the predictability level for the three cases under consideration.
Abstract
Cold pools are mesoscale features that are key for understanding the organization of convection, but are insufficiently captured in conventional observations. This study conducts a statistical characterization of cold-pool passages observed at a 280-m-high boundary layer mast in Hamburg (Germany) and discusses factors controlling their signal strength. During 14 summer seasons 489 cold-pool events are identified from rapid temperature drops below −2 K associated with rainfall. The cold-pool activity exhibits distinct annual and diurnal cycles peaking in July and midafternoon, respectively. The median temperature perturbation is −3.3 K at 2-m height and weakens above. Also the increase in hydrostatic air pressure and specific humidity is largest near the surface. Extrapolation of the vertically weakening pressure signal suggests a characteristic cold-pool depth of about 750 m. Disturbances in the horizontal and vertical wind speed components document a lifting-induced circulation of air masses prior to the approaching cold-pool front. According to a correlation analysis, the near-surface temperature perturbation is more strongly controlled by the pre-event saturation deficit (r = −0.71) than by the event-accumulated rainfall amount (r = −0.35). Simulating the observed temperature drops as idealized wet-bulb processes suggests that evaporative cooling alone explains 64% of the variability in cold-pool strength. This number increases to 92% for cases that are not affected by advection of midtropospheric low-Θ e air masses under convective downdrafts.
Abstract
Cold pools are mesoscale features that are key for understanding the organization of convection, but are insufficiently captured in conventional observations. This study conducts a statistical characterization of cold-pool passages observed at a 280-m-high boundary layer mast in Hamburg (Germany) and discusses factors controlling their signal strength. During 14 summer seasons 489 cold-pool events are identified from rapid temperature drops below −2 K associated with rainfall. The cold-pool activity exhibits distinct annual and diurnal cycles peaking in July and midafternoon, respectively. The median temperature perturbation is −3.3 K at 2-m height and weakens above. Also the increase in hydrostatic air pressure and specific humidity is largest near the surface. Extrapolation of the vertically weakening pressure signal suggests a characteristic cold-pool depth of about 750 m. Disturbances in the horizontal and vertical wind speed components document a lifting-induced circulation of air masses prior to the approaching cold-pool front. According to a correlation analysis, the near-surface temperature perturbation is more strongly controlled by the pre-event saturation deficit (r = −0.71) than by the event-accumulated rainfall amount (r = −0.35). Simulating the observed temperature drops as idealized wet-bulb processes suggests that evaporative cooling alone explains 64% of the variability in cold-pool strength. This number increases to 92% for cases that are not affected by advection of midtropospheric low-Θ e air masses under convective downdrafts.
Abstract
This study analyzes the effects of land surface heterogeneities at various horizontal scales on the transition from shallow to deep convection and on the cloud size distribution. An idealized case of midlatitude summertime convection is simulated by means of large-eddy simulations coupled to an interactive land surface. The transition is accelerated over heterogeneous surfaces. The simulation with an intermediate patch size of 12.8 km exhibits the fastest transition with a transition time two-thirds that over a homogeneous surface. A similar timing is observed for the precipitation onset whereas the total accumulated rainfall tends to increase with patch size. The cloud size distribution can be approximated by a power law with a scale break. The exponent of the power law is independent of the heterogeneity scale, implying a similar cloud cover between the simulations. In contrast, the scale break varies with patch size. The size of the largest clouds does not scale with the boundary layer height, although their maximum size scales with the patch size. Finally, the idea that larger clouds grow faster, known from homogeneous surface conditions, is not fully valid over heterogeneous surfaces. These various aspects can be understood from the complex interplay between the characteristics of the triggered mesoscale circulations and a cloud development acting in response to the diurnal cycle in surface heating. The results also call for adequate representation of such effects in convective parameterizations.
Abstract
This study analyzes the effects of land surface heterogeneities at various horizontal scales on the transition from shallow to deep convection and on the cloud size distribution. An idealized case of midlatitude summertime convection is simulated by means of large-eddy simulations coupled to an interactive land surface. The transition is accelerated over heterogeneous surfaces. The simulation with an intermediate patch size of 12.8 km exhibits the fastest transition with a transition time two-thirds that over a homogeneous surface. A similar timing is observed for the precipitation onset whereas the total accumulated rainfall tends to increase with patch size. The cloud size distribution can be approximated by a power law with a scale break. The exponent of the power law is independent of the heterogeneity scale, implying a similar cloud cover between the simulations. In contrast, the scale break varies with patch size. The size of the largest clouds does not scale with the boundary layer height, although their maximum size scales with the patch size. Finally, the idea that larger clouds grow faster, known from homogeneous surface conditions, is not fully valid over heterogeneous surfaces. These various aspects can be understood from the complex interplay between the characteristics of the triggered mesoscale circulations and a cloud development acting in response to the diurnal cycle in surface heating. The results also call for adequate representation of such effects in convective parameterizations.
