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Abstract
Mesoscale convective systems (MCSs) that are clustered in time and space can have a broader impact on flooding because they have larger area coverage than that of individual MCSs. The goal of this study is to understand the flood likelihood associated with MCS clusters. To achieve this, floods in the Storm Events Database in April–August of 2007–17 are matched with clustered MCSs identified from a high-resolution MCS dataset and terrestrial conditions in a land surface dataset over the central-eastern United States. Our analysis indicates that clustered MCSs preferentially occurring in April–June are more effective at producing floods, which also last longer due to the greater rainfall per area and wetter initial soil conditions and, hence, produce greater runoff per area than nonclustered MCSs. Similar increases of flood occurrence with cluster-total rainfall size and wetter soils are also observed for each MCS cluster, especially for the overlapping rainfall areas within each cluster. These areas receive rainfall from multiple MCSs that progressively wet the soils and are therefore associated with higher flood likelihood. This study underscores the importance to understand clustered MCSs to better understand flood risks and their future changes.
Abstract
Mesoscale convective systems (MCSs) that are clustered in time and space can have a broader impact on flooding because they have larger area coverage than that of individual MCSs. The goal of this study is to understand the flood likelihood associated with MCS clusters. To achieve this, floods in the Storm Events Database in April–August of 2007–17 are matched with clustered MCSs identified from a high-resolution MCS dataset and terrestrial conditions in a land surface dataset over the central-eastern United States. Our analysis indicates that clustered MCSs preferentially occurring in April–June are more effective at producing floods, which also last longer due to the greater rainfall per area and wetter initial soil conditions and, hence, produce greater runoff per area than nonclustered MCSs. Similar increases of flood occurrence with cluster-total rainfall size and wetter soils are also observed for each MCS cluster, especially for the overlapping rainfall areas within each cluster. These areas receive rainfall from multiple MCSs that progressively wet the soils and are therefore associated with higher flood likelihood. This study underscores the importance to understand clustered MCSs to better understand flood risks and their future changes.
Regional Downscaling for Air Quality Assessment
A Reasonable Proposition?
Assessing future changes in air quality using downscaled climate scenarios is a relatively new application of the dynamical downscaling technique. This article compares and evaluates two downscaled simulations for the United States made using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model with the goal of understanding how errors in the downscaled climate simulations may introduce uncertainty in air quality assessment. The two downscaled simulations were driven by boundary conditions from the NCEP–NCAR global reanalysis and a global climate simulation generated by the Goddard Institute for Space Studies global circulation model, respectively. Comparisons of the model runs are made against the boundary layer and circulation characteristics of the North American Regional Reanalysis, and also against observed precipitation. The relative dependence of different simulated quantities on regional forcing, model parameterizations, and large-scale circulation provides a framework to understand similarities and differences between model simulations. Results show significant improvements in the downscaled diurnal wind patterns, in response to the complex orography, that are important for air quality assessment. Evaluation of downscaled boundary layer depth and winds, precipitation, and large-scale circulation shows larger biases related to model physics and biases in the GCM large-scale conditions. Based on the comparisons, recommendations are made to improve the utility of downscaled scenarios for air quality assessment.
Assessing future changes in air quality using downscaled climate scenarios is a relatively new application of the dynamical downscaling technique. This article compares and evaluates two downscaled simulations for the United States made using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model with the goal of understanding how errors in the downscaled climate simulations may introduce uncertainty in air quality assessment. The two downscaled simulations were driven by boundary conditions from the NCEP–NCAR global reanalysis and a global climate simulation generated by the Goddard Institute for Space Studies global circulation model, respectively. Comparisons of the model runs are made against the boundary layer and circulation characteristics of the North American Regional Reanalysis, and also against observed precipitation. The relative dependence of different simulated quantities on regional forcing, model parameterizations, and large-scale circulation provides a framework to understand similarities and differences between model simulations. Results show significant improvements in the downscaled diurnal wind patterns, in response to the complex orography, that are important for air quality assessment. Evaluation of downscaled boundary layer depth and winds, precipitation, and large-scale circulation shows larger biases related to model physics and biases in the GCM large-scale conditions. Based on the comparisons, recommendations are made to improve the utility of downscaled scenarios for air quality assessment.
Abstract
The regional climate of the western United States shows clear footprints of interaction between atmospheric circulation and orography. The unique features of this diverse climate regime challenges climate modeling. This paper provides detailed analyses of observations and regional climate simulations to improve our understanding and modeling of the climate of this region. The primary data used in this study are the 1/8° gridded temperature and precipitation based on station observations and the NCEP–NCAR global reanalyses. These data were used to evaluate a 20-yr regional climate simulation performed using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (Penn State–NCAR) Mesoscale Model (MM5) driven by large-scale conditions of the NCEP–NCAR reanalyses. Regional climate features examined include seasonal mean and extreme precipitation; distribution of precipitation rates; and precipitation intensity, frequency, and seasonality. The relationships between precipitation and surface temperature are also analyzed as a means to evaluate how well regional climate simulations can be used to simulate surface hydrology, and relationships between precipitation and elevation are analyzed as diagnostics of the impacts of surface topography and spatial resolution. The latter was performed at five east–west transects that cut across various topographic features in the western United States.
These analyses suggest that the regional simulation realistically captures many regional climate features. The simulated seasonal mean and extreme precipitation are comparable to observations. The regional simulation produces precipitation over a wide range of precipitation rates comparable to observations. Obvious biases in the simulation include the oversimulation of precipitation in the basins and intermountain West during the cold season, and the undersimulation in the Southwest in the warm season. There is a tendency of reduced precipitation frequency rather than intensity in the simulation during the summer in the Northwest and Southwest, which leads to the insufficient summer mean precipitation in those areas. Because of the general warm biases in the simulation, there is also a tendency for more precipitation events to be associated with warmer temperatures, which can affect the simulation of snowpack and runoff.
Abstract
The regional climate of the western United States shows clear footprints of interaction between atmospheric circulation and orography. The unique features of this diverse climate regime challenges climate modeling. This paper provides detailed analyses of observations and regional climate simulations to improve our understanding and modeling of the climate of this region. The primary data used in this study are the 1/8° gridded temperature and precipitation based on station observations and the NCEP–NCAR global reanalyses. These data were used to evaluate a 20-yr regional climate simulation performed using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (Penn State–NCAR) Mesoscale Model (MM5) driven by large-scale conditions of the NCEP–NCAR reanalyses. Regional climate features examined include seasonal mean and extreme precipitation; distribution of precipitation rates; and precipitation intensity, frequency, and seasonality. The relationships between precipitation and surface temperature are also analyzed as a means to evaluate how well regional climate simulations can be used to simulate surface hydrology, and relationships between precipitation and elevation are analyzed as diagnostics of the impacts of surface topography and spatial resolution. The latter was performed at five east–west transects that cut across various topographic features in the western United States.
These analyses suggest that the regional simulation realistically captures many regional climate features. The simulated seasonal mean and extreme precipitation are comparable to observations. The regional simulation produces precipitation over a wide range of precipitation rates comparable to observations. Obvious biases in the simulation include the oversimulation of precipitation in the basins and intermountain West during the cold season, and the undersimulation in the Southwest in the warm season. There is a tendency of reduced precipitation frequency rather than intensity in the simulation during the summer in the Northwest and Southwest, which leads to the insufficient summer mean precipitation in those areas. Because of the general warm biases in the simulation, there is also a tendency for more precipitation events to be associated with warmer temperatures, which can affect the simulation of snowpack and runoff.
Abstract
This study investigates the North Atlantic atmospheric rivers (ARs) making landfall over western Europe in the present and future climate from the multimodel ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Overall, CMIP5 captures the seasonal and spatial variations of historical landfalling AR days, with the large intermodel variability strongly correlated with the intermodel spread of historical near-surface westerly jet position. Under representative concentration pathway 8.5 (RCP8.5), AR frequency is projected to increase significantly by the end of this century, with 127%–275% increase at peak AR frequency regions (45°–55°N). While thermodynamics plays a dominant role in the future increase of ARs, wind changes associated with the midlatitude jet shifts also significantly contribute to AR changes, resulting in dipole change patterns in all seasons. In the North Atlantic, the model-projected jet shifts are strongly correlated with the simulated historical jet position. As models exhibit predominantly equatorward biases in the historical jet position, the large poleward jet shifts reduce AR days south of the historical mean jet position through the dynamical connections between the jet positions and AR days. Using the observed historical jet position as an emergent constraint, dynamical effects further increase future AR days over the equatorward flank above the increases from thermodynamical effects. Compared to the present, both total and extreme precipitation induced by ARs in the future contribute more to the seasonal mean and extreme precipitation, primarily because of the increase in AR frequency. While AR precipitation intensity generally increases more relative to the increase in integrated vapor transport, AR extreme precipitation intensity increases much less.
Abstract
This study investigates the North Atlantic atmospheric rivers (ARs) making landfall over western Europe in the present and future climate from the multimodel ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Overall, CMIP5 captures the seasonal and spatial variations of historical landfalling AR days, with the large intermodel variability strongly correlated with the intermodel spread of historical near-surface westerly jet position. Under representative concentration pathway 8.5 (RCP8.5), AR frequency is projected to increase significantly by the end of this century, with 127%–275% increase at peak AR frequency regions (45°–55°N). While thermodynamics plays a dominant role in the future increase of ARs, wind changes associated with the midlatitude jet shifts also significantly contribute to AR changes, resulting in dipole change patterns in all seasons. In the North Atlantic, the model-projected jet shifts are strongly correlated with the simulated historical jet position. As models exhibit predominantly equatorward biases in the historical jet position, the large poleward jet shifts reduce AR days south of the historical mean jet position through the dynamical connections between the jet positions and AR days. Using the observed historical jet position as an emergent constraint, dynamical effects further increase future AR days over the equatorward flank above the increases from thermodynamical effects. Compared to the present, both total and extreme precipitation induced by ARs in the future contribute more to the seasonal mean and extreme precipitation, primarily because of the increase in AR frequency. While AR precipitation intensity generally increases more relative to the increase in integrated vapor transport, AR extreme precipitation intensity increases much less.
Abstract
Parallel simulations of clouds and radiation fields by a single-column model (SCM), a regional circulation model, and a global circulation model (GCM), each using the same treatment of all physical processes and approximately the same spatial resolution, are compared with observations at the Atmopheric Radiation Measurement Clouds and Radiation Testbed in the southern Great Plains. Significant differences between model simulations are evident for individual cloud systems, but these differences are not systematic, varying from cloud system to cloud system. Several systematic differences between model simulations and observations are identified. These biases are about the same for each model and are much larger than differences between model simulations, suggesting that for some purposes one model can serve as a testbed for parameterizations developed for another.
The role of nudging in the simulations is explored by driving the SCM with large-scale forcing from a GCM simulation. The authors find that nudging of SCM temperature and humidity toward the GCM simulation, using the inverse of the advective timescale for the nudging coefficient, reduces errors in the SCM simulation when artificial errors in the forcing are introduced. The authors also find that nudging of temperature and humidity hides physics errors introduced in the SCM, but only if the physics errors involve processes that directly influence temperature or humidity. Thus, errors in the treatment of nucleation, collision–coalescence, collection, and gravitational settling would not be hidden by nudging, but errors in the treatment of radiative heating, condensation/vapor deposition, evaporation/sublimation, melting, cumulus convection, and subgrid or resolved transport of heat and moisture would be hidden by nudging.
Abstract
Parallel simulations of clouds and radiation fields by a single-column model (SCM), a regional circulation model, and a global circulation model (GCM), each using the same treatment of all physical processes and approximately the same spatial resolution, are compared with observations at the Atmopheric Radiation Measurement Clouds and Radiation Testbed in the southern Great Plains. Significant differences between model simulations are evident for individual cloud systems, but these differences are not systematic, varying from cloud system to cloud system. Several systematic differences between model simulations and observations are identified. These biases are about the same for each model and are much larger than differences between model simulations, suggesting that for some purposes one model can serve as a testbed for parameterizations developed for another.
The role of nudging in the simulations is explored by driving the SCM with large-scale forcing from a GCM simulation. The authors find that nudging of SCM temperature and humidity toward the GCM simulation, using the inverse of the advective timescale for the nudging coefficient, reduces errors in the SCM simulation when artificial errors in the forcing are introduced. The authors also find that nudging of temperature and humidity hides physics errors introduced in the SCM, but only if the physics errors involve processes that directly influence temperature or humidity. Thus, errors in the treatment of nucleation, collision–coalescence, collection, and gravitational settling would not be hidden by nudging, but errors in the treatment of radiative heating, condensation/vapor deposition, evaporation/sublimation, melting, cumulus convection, and subgrid or resolved transport of heat and moisture would be hidden by nudging.
Abstract
Estimating water budgets of river basins in the western United States is a challenge because of the effects of complex terrain and lack of comprehensive observational datasets. This study aims at comparing different estimates of cold season water budgets of the Columbia River (CRB) and Sacramento–San Joaquin River (SSJ) basins. An intercomparison was performed based on the NCEP–NCAR reanalysis I (NRA1), NCEP–Department of Energy (DOE) reanalysis II (NRA2), ECMWF reanalyses (ERA), regional climate simulations produced by the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) and NCEP Regional Spectral Model (RSM) driven by the reanalyses, and two precipitation datasets gridded at 2.5° and ⅛° for 7 yr between 1986 and 1993. The purpose of the intercomparison was to understand the effects of spatial resolution, model configuration and associated parameterizations, and large-scale conditions on basin-scale water budgets.
Overall, the regional simulations were superior to the global reanalyses in terms of the spatial distribution of mean precipitation and precipitation anomalies. However, cold season precipitation was generally amplified in the regional models. Basin mean precipitation was typically higher than observed in the regional models and less than observed in the reanalyses. The amplification was the largest in the RSM simulation driven by NRA2, which had the biggest difference between the reanalyzed and regional simulation of basin mean precipitation. ERA and the MM5 simulations driven by ERA provided the best basin mean precipitation estimates when compared to the ⅛° observational dataset.
Large differences remain in estimating the water budgets of western river basins, such as CRB and SSJ. In terms of atmospheric moisture flux, there was a 15%–20% difference between the global reanalyses. In terms of basin mean precipitation, differences among the reanalyses, regional simulations, and observations were as large as 100% of the overall mean. There were large differences in spatial distribution of precipitation between the RSM and MM5 simulations because of terrain representations and other factors. Runoff and snowpack showed the most sensitivity to model differences in spatial resolution, physics parameterizations, and model representations. Better simulations of basin mean precipitation did not necessarily imply superior simulations of runoff or snowpack.
Abstract
Estimating water budgets of river basins in the western United States is a challenge because of the effects of complex terrain and lack of comprehensive observational datasets. This study aims at comparing different estimates of cold season water budgets of the Columbia River (CRB) and Sacramento–San Joaquin River (SSJ) basins. An intercomparison was performed based on the NCEP–NCAR reanalysis I (NRA1), NCEP–Department of Energy (DOE) reanalysis II (NRA2), ECMWF reanalyses (ERA), regional climate simulations produced by the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) and NCEP Regional Spectral Model (RSM) driven by the reanalyses, and two precipitation datasets gridded at 2.5° and ⅛° for 7 yr between 1986 and 1993. The purpose of the intercomparison was to understand the effects of spatial resolution, model configuration and associated parameterizations, and large-scale conditions on basin-scale water budgets.
Overall, the regional simulations were superior to the global reanalyses in terms of the spatial distribution of mean precipitation and precipitation anomalies. However, cold season precipitation was generally amplified in the regional models. Basin mean precipitation was typically higher than observed in the regional models and less than observed in the reanalyses. The amplification was the largest in the RSM simulation driven by NRA2, which had the biggest difference between the reanalyzed and regional simulation of basin mean precipitation. ERA and the MM5 simulations driven by ERA provided the best basin mean precipitation estimates when compared to the ⅛° observational dataset.
Large differences remain in estimating the water budgets of western river basins, such as CRB and SSJ. In terms of atmospheric moisture flux, there was a 15%–20% difference between the global reanalyses. In terms of basin mean precipitation, differences among the reanalyses, regional simulations, and observations were as large as 100% of the overall mean. There were large differences in spatial distribution of precipitation between the RSM and MM5 simulations because of terrain representations and other factors. Runoff and snowpack showed the most sensitivity to model differences in spatial resolution, physics parameterizations, and model representations. Better simulations of basin mean precipitation did not necessarily imply superior simulations of runoff or snowpack.
Abstract
The Lower Mississippi River basin (LMRB) has experienced significant changes in land cover and is one of the most vulnerable regions to hurricanes in the United States. Here, we study the impacts of land-cover change on the hydrologic response to Hurricane Ida in LMRB. By using an integrated surface–subsurface hydrologic model, Energy Exascale Earth System Model (E3SM) Land Model coupled with the three-dimensional ParFlow subsurface flow model (ELM-ParFlow), we simulate the effects of land-cover change on the flood volume and peak timing induced by rainfall from Hurricane Ida. The results show that land-cover changes from 1850 to 2015, which resulted in a smoother surface and less vegetation, exacerbated both flood peak time and volume induced by Hurricane Ida. The effects of land-cover changes can be decomposed into two mechanisms: a smoother surface routes more water faster to a watershed outlet and less vegetation allows more water to contribute to surface runoff. By comparing scenarios in which the two mechanisms were isolated, we found that changes in soil moisture due to vegetation cover change have more dominant effects on floods in the southern part and changes in Manning’s coefficient have the largest effect on floods in the northern part of the LMRB. The study provides important insights into the complex relationship between land-use, land-cover, and hydrologic processes in coastal regions.
Abstract
The Lower Mississippi River basin (LMRB) has experienced significant changes in land cover and is one of the most vulnerable regions to hurricanes in the United States. Here, we study the impacts of land-cover change on the hydrologic response to Hurricane Ida in LMRB. By using an integrated surface–subsurface hydrologic model, Energy Exascale Earth System Model (E3SM) Land Model coupled with the three-dimensional ParFlow subsurface flow model (ELM-ParFlow), we simulate the effects of land-cover change on the flood volume and peak timing induced by rainfall from Hurricane Ida. The results show that land-cover changes from 1850 to 2015, which resulted in a smoother surface and less vegetation, exacerbated both flood peak time and volume induced by Hurricane Ida. The effects of land-cover changes can be decomposed into two mechanisms: a smoother surface routes more water faster to a watershed outlet and less vegetation allows more water to contribute to surface runoff. By comparing scenarios in which the two mechanisms were isolated, we found that changes in soil moisture due to vegetation cover change have more dominant effects on floods in the southern part and changes in Manning’s coefficient have the largest effect on floods in the northern part of the LMRB. The study provides important insights into the complex relationship between land-use, land-cover, and hydrologic processes in coastal regions.
Abstract
Mesoscale convective systems (MCSs) bring large amounts of rainfall and strong wind gusts to the midlatitude land regions, with significant impacts on local weather and hydrologic cycle. However, weather and climate models face a huge challenge in accurately modeling the MCS life cycle and the associated precipitation, highlighting an urgent need for a better understanding of the underlying mechanisms of MCS initiation and propagation. From a theoretical perspective, a suitable model to capture the realistic properties of MCSs and isolate the bare-bones mechanisms for their initiation, intensification, and eastward propagation is still lacking. To simulate midlatitude MCSs over land, we develop a simple moist potential vorticity (PV) model that readily describes the interactions among PV perturbations, air moisture, and soil moisture. Multiple experiments with or without various environmental factors and external forcing are used to investigate their impacts on MCS dynamics and mesoscale circulation vertical structures. The result shows that mechanical forcing can induce lower-level updraft and cooling, providing favorable conditions for MCS initiation. A positive feedback among surface winds, evaporation rate, and air moisture similar to the wind-induced surface heat exchange over tropical ocean is found to support MCS intensification. Both background surface westerlies and vertical westerly wind shear are shown to provide favorable conditions for the eastward propagation of MCSs. Last, our result highlights the crucial role of stratiform heating in shaping mesoscale circulation response. The model should serve as a useful tool for understanding the fundamental mechanisms of MCS dynamics.
Abstract
Mesoscale convective systems (MCSs) bring large amounts of rainfall and strong wind gusts to the midlatitude land regions, with significant impacts on local weather and hydrologic cycle. However, weather and climate models face a huge challenge in accurately modeling the MCS life cycle and the associated precipitation, highlighting an urgent need for a better understanding of the underlying mechanisms of MCS initiation and propagation. From a theoretical perspective, a suitable model to capture the realistic properties of MCSs and isolate the bare-bones mechanisms for their initiation, intensification, and eastward propagation is still lacking. To simulate midlatitude MCSs over land, we develop a simple moist potential vorticity (PV) model that readily describes the interactions among PV perturbations, air moisture, and soil moisture. Multiple experiments with or without various environmental factors and external forcing are used to investigate their impacts on MCS dynamics and mesoscale circulation vertical structures. The result shows that mechanical forcing can induce lower-level updraft and cooling, providing favorable conditions for MCS initiation. A positive feedback among surface winds, evaporation rate, and air moisture similar to the wind-induced surface heat exchange over tropical ocean is found to support MCS intensification. Both background surface westerlies and vertical westerly wind shear are shown to provide favorable conditions for the eastward propagation of MCSs. Last, our result highlights the crucial role of stratiform heating in shaping mesoscale circulation response. The model should serve as a useful tool for understanding the fundamental mechanisms of MCS dynamics.
Abstract
Moisture recycling, the contribution of local evapotranspiration (ET) to precipitation, has been studied using bulk models assuming a well-mixed atmosphere. The latter is inconsistent with a climatologically stratified atmosphere that slants across latitudes. Reconciling the two views requires an understanding of overturning associated with different weather systems. In this study, we aim to better understand moisture recycling associated with mesoscale convective systems (MCSs). Using a convection-permitting WRF simulation equipped with water vapor tracers (WRF-WVT), we tag moisture from terrestrial ET in the U.S. Southern Great Plains during May 2015, when more than 20 MCS events occurred and produced significant precipitation and flooding. Water budget analysis reveals that approximately 76% of terrestrial ET is advected away from the region while the remaining 24% of terrestrial ET is “pumped” upward within the region, accounting for 12% of precipitation. Moisture recycling peaks during early night hours (1800–2400 LT) due to the mixing of the daytime accumulated ET by active convection. By focusing on five “diurnally driven” MCSs with less large-scale circulation influence than other MCSs during the same period, we find an upright pumping of terrestrial ET at the MCS initiation and development stages, which diverges into two branches during the MCS mature and decaying stages. One branch in the upper level advects the ET-sourced moisture downstream, while the other branch in the mid-to-upper level contributes to the trailing precipitation upstream. Overall, our analysis depicts a pumping mechanism associated with MCSs that mixes local ET vertically, highlighting its specific contributions to enhancing convective precipitation processes.
Abstract
Moisture recycling, the contribution of local evapotranspiration (ET) to precipitation, has been studied using bulk models assuming a well-mixed atmosphere. The latter is inconsistent with a climatologically stratified atmosphere that slants across latitudes. Reconciling the two views requires an understanding of overturning associated with different weather systems. In this study, we aim to better understand moisture recycling associated with mesoscale convective systems (MCSs). Using a convection-permitting WRF simulation equipped with water vapor tracers (WRF-WVT), we tag moisture from terrestrial ET in the U.S. Southern Great Plains during May 2015, when more than 20 MCS events occurred and produced significant precipitation and flooding. Water budget analysis reveals that approximately 76% of terrestrial ET is advected away from the region while the remaining 24% of terrestrial ET is “pumped” upward within the region, accounting for 12% of precipitation. Moisture recycling peaks during early night hours (1800–2400 LT) due to the mixing of the daytime accumulated ET by active convection. By focusing on five “diurnally driven” MCSs with less large-scale circulation influence than other MCSs during the same period, we find an upright pumping of terrestrial ET at the MCS initiation and development stages, which diverges into two branches during the MCS mature and decaying stages. One branch in the upper level advects the ET-sourced moisture downstream, while the other branch in the mid-to-upper level contributes to the trailing precipitation upstream. Overall, our analysis depicts a pumping mechanism associated with MCSs that mixes local ET vertically, highlighting its specific contributions to enhancing convective precipitation processes.
Abstract
By applying a cloud-tracking algorithm to tropical convective systems in a regional high-resolution model simulation, this study documents the environmental conditions before and after convective systems are initiated over ocean and land by following them during their lifetime. The comparative roles of various mechanisms of convection–environment interaction on the longevity of convective systems are quantified. The statistics of lifetime, maximum area, and propagation speed of the simulated deep convection agree well with geostationary satellite observations.
Among the environmental variables considered, lifetime of convective systems is found to be most related to midtropospheric moisture before as well as after the initiation of convection. Over ocean, convective systems enhance surface fluxes through the associated cooling and drying of the boundary layer as well as increased wind gusts. This process appears to play a minor positive role in the longevity of systems. For systems of equal lifetime, those over land tend to be more intense than those over ocean especially during the early stages of their life cycle. Both over ocean and land, convection is found to transport momentum vertically to increase low-level shear and decrease upper-level shear, but no discernible effect of shear on the lifetime of the convective systems is found.
Abstract
By applying a cloud-tracking algorithm to tropical convective systems in a regional high-resolution model simulation, this study documents the environmental conditions before and after convective systems are initiated over ocean and land by following them during their lifetime. The comparative roles of various mechanisms of convection–environment interaction on the longevity of convective systems are quantified. The statistics of lifetime, maximum area, and propagation speed of the simulated deep convection agree well with geostationary satellite observations.
Among the environmental variables considered, lifetime of convective systems is found to be most related to midtropospheric moisture before as well as after the initiation of convection. Over ocean, convective systems enhance surface fluxes through the associated cooling and drying of the boundary layer as well as increased wind gusts. This process appears to play a minor positive role in the longevity of systems. For systems of equal lifetime, those over land tend to be more intense than those over ocean especially during the early stages of their life cycle. Both over ocean and land, convection is found to transport momentum vertically to increase low-level shear and decrease upper-level shear, but no discernible effect of shear on the lifetime of the convective systems is found.
