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- Author or Editor: Nicolas Rochetin x
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Abstract
A new method is developed to detect cold pools from atmospheric soundings over tropical oceans and applied to sounding data from the Elucidating the Role of Cloud–Circulation Coupling in Climate (EUREC4A) field campaign, which took place south and east of Barbados in January–February 2020. The proposed method uses soundings to discriminate cold pools from their surroundings: cold pools are defined as regions where the mixed-layer height is smaller than 400 m. The method is first tested against 2D surface temperature and precipitation fields in a realistic high-resolution simulation over the western tropical Atlantic Ocean. Then, the method is applied to a dataset of 1068 atmospheric profiles from dropsondes (launched from two aircraft) and 1105 from radiosondes (launched from an array of four ships and the Barbados Cloud Observatory). We show that 7% of the EUREC4A soundings fell into cold pools. Cold-pool soundings coincide with (i) mesoscale cloud arcs and (ii) temperature drops of ∼1 K relative to the environment, along with moisture increases of ∼1 g kg−1. Furthermore, cold-pool moisture profiles exhibit a “moist layer” close to the surface, topped by a “dry layer” until the cloud base level, and followed by another moist layer in the cloud layer. In the presence of wind shear, the spreading of cold pools is favored downshear, suggesting downward momentum transport by unsaturated downdrafts. The results support the robustness of our detection method in diverse environmental conditions and its simplicity makes the method a promising tool for the characterization of cold pools, including their vertical structure. The applicability of the method to other regions and convective regimes is discussed.
Abstract
A new method is developed to detect cold pools from atmospheric soundings over tropical oceans and applied to sounding data from the Elucidating the Role of Cloud–Circulation Coupling in Climate (EUREC4A) field campaign, which took place south and east of Barbados in January–February 2020. The proposed method uses soundings to discriminate cold pools from their surroundings: cold pools are defined as regions where the mixed-layer height is smaller than 400 m. The method is first tested against 2D surface temperature and precipitation fields in a realistic high-resolution simulation over the western tropical Atlantic Ocean. Then, the method is applied to a dataset of 1068 atmospheric profiles from dropsondes (launched from two aircraft) and 1105 from radiosondes (launched from an array of four ships and the Barbados Cloud Observatory). We show that 7% of the EUREC4A soundings fell into cold pools. Cold-pool soundings coincide with (i) mesoscale cloud arcs and (ii) temperature drops of ∼1 K relative to the environment, along with moisture increases of ∼1 g kg−1. Furthermore, cold-pool moisture profiles exhibit a “moist layer” close to the surface, topped by a “dry layer” until the cloud base level, and followed by another moist layer in the cloud layer. In the presence of wind shear, the spreading of cold pools is favored downshear, suggesting downward momentum transport by unsaturated downdrafts. The results support the robustness of our detection method in diverse environmental conditions and its simplicity makes the method a promising tool for the characterization of cold pools, including their vertical structure. The applicability of the method to other regions and convective regimes is discussed.
Abstract
This paper presents a stochastic triggering parameterization for deep convection and its implementation in the latest standard version of the Laboratoire de Météorologie Dynamique–Zoom (LMDZ) general circulation model: LMDZ5B. The derivation of the formulation of this parameterization and the justification, based on large-eddy simulation results, for the main hypothesis was proposed in Part I of this study.
Whereas the standard triggering formulation in LMDZ5B relies on the maximum vertical velocity within a mean bulk thermal, the new formulation presented here (i) considers a thermal size distribution instead of a bulk thermal, (ii) provides a statistical lifting energy at cloud base, (iii) proposes a three-step trigger (appearance of clouds, inhibition crossing, and exceeding of a cross-section threshold), and (iv) includes a stochastic component.
Here the complete implementation is presented, with its coupling to the thermal model used to treat shallow convection in LMDZ5B. The parameterization is tested over various cases in a single-column model framework. A sensitivity study to each parameter introduced is also carried out. The impact of the new triggering is then evaluated in the single-column version of LMDZ on several case studies and in full 3D simulations.
It is found that the new triggering (i) delays deep convection triggering, (ii) suppresses it over oceanic trade wind cumulus zones, (iii) increases the low-level cloudiness, and (iv) increases the convective variability. The scale-aware nature of this parameterization is also discussed.
Abstract
This paper presents a stochastic triggering parameterization for deep convection and its implementation in the latest standard version of the Laboratoire de Météorologie Dynamique–Zoom (LMDZ) general circulation model: LMDZ5B. The derivation of the formulation of this parameterization and the justification, based on large-eddy simulation results, for the main hypothesis was proposed in Part I of this study.
Whereas the standard triggering formulation in LMDZ5B relies on the maximum vertical velocity within a mean bulk thermal, the new formulation presented here (i) considers a thermal size distribution instead of a bulk thermal, (ii) provides a statistical lifting energy at cloud base, (iii) proposes a three-step trigger (appearance of clouds, inhibition crossing, and exceeding of a cross-section threshold), and (iv) includes a stochastic component.
Here the complete implementation is presented, with its coupling to the thermal model used to treat shallow convection in LMDZ5B. The parameterization is tested over various cases in a single-column model framework. A sensitivity study to each parameter introduced is also carried out. The impact of the new triggering is then evaluated in the single-column version of LMDZ on several case studies and in full 3D simulations.
It is found that the new triggering (i) delays deep convection triggering, (ii) suppresses it over oceanic trade wind cumulus zones, (iii) increases the low-level cloudiness, and (iv) increases the convective variability. The scale-aware nature of this parameterization is also discussed.
Abstract
This paper proposes a new formulation of the deep convection triggering for general circulation model convective parameterizations. This triggering is driven by evolving properties of the strongest boundary layer thermals. To investigate this, a statistical analysis of large-eddy simulation cloud fields in a case of transition from shallow to deep convection over a semiarid land is carried out at different stages of the transition from shallow to deep convection. Based on the dynamical and geometrical properties at cloud base, a new computation of the triggering is first proposed. The analysis of the distribution law of the maximum size of the thermals suggests that, in addition to this necessary condition, another triggering condition is required, that is, that this maximum horizontal size should exceed a certain threshold. This is explicitly represented stochastically. Therefore, the new formulation integrates the whole transition process from the first cloud to the first deep convective cell and can be decomposed into three steps: (i) the appearance of clouds, (ii) crossing of the inhibition layer, and (iii) deep convection triggering.
Abstract
This paper proposes a new formulation of the deep convection triggering for general circulation model convective parameterizations. This triggering is driven by evolving properties of the strongest boundary layer thermals. To investigate this, a statistical analysis of large-eddy simulation cloud fields in a case of transition from shallow to deep convection over a semiarid land is carried out at different stages of the transition from shallow to deep convection. Based on the dynamical and geometrical properties at cloud base, a new computation of the triggering is first proposed. The analysis of the distribution law of the maximum size of the thermals suggests that, in addition to this necessary condition, another triggering condition is required, that is, that this maximum horizontal size should exceed a certain threshold. This is explicitly represented stochastically. Therefore, the new formulation integrates the whole transition process from the first cloud to the first deep convective cell and can be decomposed into three steps: (i) the appearance of clouds, (ii) crossing of the inhibition layer, and (iii) deep convection triggering.
Abstract
Radiative–convective equilibrium (RCE) describes an idealized state of the atmosphere in which the vertical temperature profile is determined by a balance between radiative and convective fluxes. While RCE has been applied extensively over oceans, its application over the land surface has been limited. The present study explores the properties of RCE over land using an atmospheric single-column model (SCM) from the Laboratoire de Météorologie Dynamique–Zoom, version 5B (LMDZ5B) general circulation model coupled in temperature and moisture to a land surface model using a simplified bucket model with finite moisture capacity. Given the presence of a large-amplitude diurnal heat flux cycle, the resultant RCE exhibits multiple equilibria when conditions are neither strictly water nor energy limited. By varying top-of-atmosphere insolation (through changes in latitude), total system water content, and initial temperature conditions the sensitivity of the land RCE states is assessed, with particular emphasis on the role of clouds. Based on this analysis, it appears that a necessary condition for the model to exhibit multiple equilibria is the presence of low-level clouds coupled to the diurnal cycle of radiation. In addition the simulated surface precipitation rate varies nonmonotonically with latitude as a result of a tradeoff between in-cloud rain rate and subcloud rain reevaporation, thus underscoring the importance of subcloud layer processes and unsaturated downdrafts. It is shown that clouds, especially at low levels, are key elements of the internal variability of the coupled land–atmosphere system through their feedback on radiation.
Abstract
Radiative–convective equilibrium (RCE) describes an idealized state of the atmosphere in which the vertical temperature profile is determined by a balance between radiative and convective fluxes. While RCE has been applied extensively over oceans, its application over the land surface has been limited. The present study explores the properties of RCE over land using an atmospheric single-column model (SCM) from the Laboratoire de Météorologie Dynamique–Zoom, version 5B (LMDZ5B) general circulation model coupled in temperature and moisture to a land surface model using a simplified bucket model with finite moisture capacity. Given the presence of a large-amplitude diurnal heat flux cycle, the resultant RCE exhibits multiple equilibria when conditions are neither strictly water nor energy limited. By varying top-of-atmosphere insolation (through changes in latitude), total system water content, and initial temperature conditions the sensitivity of the land RCE states is assessed, with particular emphasis on the role of clouds. Based on this analysis, it appears that a necessary condition for the model to exhibit multiple equilibria is the presence of low-level clouds coupled to the diurnal cycle of radiation. In addition the simulated surface precipitation rate varies nonmonotonically with latitude as a result of a tradeoff between in-cloud rain rate and subcloud rain reevaporation, thus underscoring the importance of subcloud layer processes and unsaturated downdrafts. It is shown that clouds, especially at low levels, are key elements of the internal variability of the coupled land–atmosphere system through their feedback on radiation.
