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Improving the forecasts of the intensity of tropical cyclones (TCs) remains a major challenge. One possibility for improvement is consideration of the effects that aerosols have on tropical clouds and cyclones. The authors have been pursuing this under the Hurricane Aerosol and Microphysics Program, supported by the U.S. Department of Homeland Security. This was done through observations of aerosols and resulting cloud microphysical structure within tropical cyclones and simulating their effects using high-resolution TC models that treat cloud internal processes explicitly. In addition to atmospheric aerosols, special attention was given also to the impact of the intense sea-spray-generated aerosols and convective rolls in the hurricane boundary layer (BL) under hurricane- force winds.
The results of simulations and observations show that TC ingestion of aerosols that serve as cloud condensation nuclei can lead to significant reductions in their intensities. This is caused by redistribution of the precipitation and latent heating to more vigorous convection in the storm periphery that cools the low levels and interferes with the inflow of energy to the eyewall, hence making the eye larger and the maximum winds weaker. The microphysical effects of the pollution and dust aerosols occur mainly at the peripheral clouds. Closer to the circulation center, the hurricane-force winds raise intense sea spray that is lifted efficiently in the roll vortices that form in the BL and coalesce into rain of mostly seawater already at cloud base, which dominates the microstructure and affects the dynamics of the inner convective cloud bands.
Improving the forecasts of the intensity of tropical cyclones (TCs) remains a major challenge. One possibility for improvement is consideration of the effects that aerosols have on tropical clouds and cyclones. The authors have been pursuing this under the Hurricane Aerosol and Microphysics Program, supported by the U.S. Department of Homeland Security. This was done through observations of aerosols and resulting cloud microphysical structure within tropical cyclones and simulating their effects using high-resolution TC models that treat cloud internal processes explicitly. In addition to atmospheric aerosols, special attention was given also to the impact of the intense sea-spray-generated aerosols and convective rolls in the hurricane boundary layer (BL) under hurricane- force winds.
The results of simulations and observations show that TC ingestion of aerosols that serve as cloud condensation nuclei can lead to significant reductions in their intensities. This is caused by redistribution of the precipitation and latent heating to more vigorous convection in the storm periphery that cools the low levels and interferes with the inflow of energy to the eyewall, hence making the eye larger and the maximum winds weaker. The microphysical effects of the pollution and dust aerosols occur mainly at the peripheral clouds. Closer to the circulation center, the hurricane-force winds raise intense sea spray that is lifted efficiently in the roll vortices that form in the BL and coalesce into rain of mostly seawater already at cloud base, which dominates the microstructure and affects the dynamics of the inner convective cloud bands.
Abstract
A key to parameterization of subgrid-scale processes is the probability density function (PDF) of conserved scalars. If the appropriate PDF is known, then grid box average cloud fraction, liquid water content, temperature, and autoconversion can be diagnosed. Despite the fundamental role of PDFs in parameterization, there have been few observational studies of conserved-scalar PDFs in clouds. The present work analyzes PDFs from boundary layers containing stratocumulus, cumulus, and cumulus-rising-into-stratocumulus clouds.
Using observational aircraft data, the authors test eight different parameterizations of PDFs, including double delta function, gamma function, Gaussian, and double Gaussian shapes. The Gaussian parameterization, which depends on two parameters, fits most observed PDFs well but fails for large-scale PDFs of cumulus legs. In contrast, three-parameter parameterizations appear to be sufficiently general to model PDFs from a variety of cloudy boundary layers.
If a numerical model ignores subgrid variability, the model has biases in diagnoses of grid box average liquid water content, temperature, and Kessler autoconversion, relative to the values it would obtain if subgrid variability were taken into account. The magnitude of such biases is assessed using observational data. The biases can be largely eliminated by three-parameter PDF parameterizations.
Prior authors have suggested that boundary layer PDFs from short segments are approximately Gaussian. The present authors find that the hypothesis that PDFs of total specific water content are Gaussian can almost always be rejected for segments as small as 1 km.
Abstract
A key to parameterization of subgrid-scale processes is the probability density function (PDF) of conserved scalars. If the appropriate PDF is known, then grid box average cloud fraction, liquid water content, temperature, and autoconversion can be diagnosed. Despite the fundamental role of PDFs in parameterization, there have been few observational studies of conserved-scalar PDFs in clouds. The present work analyzes PDFs from boundary layers containing stratocumulus, cumulus, and cumulus-rising-into-stratocumulus clouds.
Using observational aircraft data, the authors test eight different parameterizations of PDFs, including double delta function, gamma function, Gaussian, and double Gaussian shapes. The Gaussian parameterization, which depends on two parameters, fits most observed PDFs well but fails for large-scale PDFs of cumulus legs. In contrast, three-parameter parameterizations appear to be sufficiently general to model PDFs from a variety of cloudy boundary layers.
If a numerical model ignores subgrid variability, the model has biases in diagnoses of grid box average liquid water content, temperature, and Kessler autoconversion, relative to the values it would obtain if subgrid variability were taken into account. The magnitude of such biases is assessed using observational data. The biases can be largely eliminated by three-parameter PDF parameterizations.
Prior authors have suggested that boundary layer PDFs from short segments are approximately Gaussian. The present authors find that the hypothesis that PDFs of total specific water content are Gaussian can almost always be rejected for segments as small as 1 km.
Abstract
The desire to improve the forecasting skill of the intensity and size of tropical cyclones has prompted the investigation into numerous physical processes that can impact these quantities. The modification of cloud properties via aerosols injected into a tropical cyclone can initiate interactions between cloud microphysics and storm dynamics that ultimately lead to appreciable changes in the large-scale features of the storm. In this modeling study it is shown that the introduction of aerosols at the periphery of an idealized tropical cyclone can impact both the intensity and size of the storm. In general, the storm intensity increases and the storm size decreases with increasing aerosol number concentration. Results from a sensitivity study to the aerosol number concentration in a source located at the storm periphery reveal that the storm intensity is increased up to 17%, and the storm size is reduced up to roughly 16% for aerosol concentrations ranging from 100 to 2000 cm−3. The storm response is approximately a monotonic function of the aerosol concentration amounts. Despite the increase in storm intensity for the heavily polluted case, the overall destructive potential of this case is reduced due to the significant decrease in the storm size.
Abstract
The desire to improve the forecasting skill of the intensity and size of tropical cyclones has prompted the investigation into numerous physical processes that can impact these quantities. The modification of cloud properties via aerosols injected into a tropical cyclone can initiate interactions between cloud microphysics and storm dynamics that ultimately lead to appreciable changes in the large-scale features of the storm. In this modeling study it is shown that the introduction of aerosols at the periphery of an idealized tropical cyclone can impact both the intensity and size of the storm. In general, the storm intensity increases and the storm size decreases with increasing aerosol number concentration. Results from a sensitivity study to the aerosol number concentration in a source located at the storm periphery reveal that the storm intensity is increased up to 17%, and the storm size is reduced up to roughly 16% for aerosol concentrations ranging from 100 to 2000 cm−3. The storm response is approximately a monotonic function of the aerosol concentration amounts. Despite the increase in storm intensity for the heavily polluted case, the overall destructive potential of this case is reduced due to the significant decrease in the storm size.
Abstract
A grid box in a numerical model that ignores subgrid variability has biases in certain microphysical and thermodynamic quantities relative to the values that would be obtained if subgrid-scale variability were taken into account. The biases are important because they are systematic and hence have cumulative effects. Several types of biases are discussed in this paper. Namely, numerical models that employ convex autoconversion formulas underpredict (or, more precisely, never overpredict) autoconversion rates, and numerical models that use convex functions to diagnose specific liquid water content and temperature underpredict these latter quantities. One may call these biases the “grid box average autoconversion bias,” “grid box average liquid water content bias,” and “grid box average temperature bias,” respectively, because the biases arise when grid box average values are substituted into formulas valid at a point, not over an extended volume. The existence of these biases can be derived from Jensen’s inequality.
To assess the magnitude of the biases, the authors analyze observations of boundary layer clouds. Often the biases are small, but the observations demonstrate that the biases can be large in important cases.
In addition, the authors prove that the average liquid water content and temperature of an isolated, partly cloudy, constant-pressure volume of air cannot increase, even temporarily. The proof assumes that liquid water content can be written as a convex function of conserved variables with equal diffusivities. The temperature decrease is due to evaporative cooling as cloudy and clear air mix. More generally, the authors prove that if an isolated volume of fluid contains conserved scalars with equal diffusivities, then the average of any convex, twice-differentiable function of the conserved scalars cannot increase.
Abstract
A grid box in a numerical model that ignores subgrid variability has biases in certain microphysical and thermodynamic quantities relative to the values that would be obtained if subgrid-scale variability were taken into account. The biases are important because they are systematic and hence have cumulative effects. Several types of biases are discussed in this paper. Namely, numerical models that employ convex autoconversion formulas underpredict (or, more precisely, never overpredict) autoconversion rates, and numerical models that use convex functions to diagnose specific liquid water content and temperature underpredict these latter quantities. One may call these biases the “grid box average autoconversion bias,” “grid box average liquid water content bias,” and “grid box average temperature bias,” respectively, because the biases arise when grid box average values are substituted into formulas valid at a point, not over an extended volume. The existence of these biases can be derived from Jensen’s inequality.
To assess the magnitude of the biases, the authors analyze observations of boundary layer clouds. Often the biases are small, but the observations demonstrate that the biases can be large in important cases.
In addition, the authors prove that the average liquid water content and temperature of an isolated, partly cloudy, constant-pressure volume of air cannot increase, even temporarily. The proof assumes that liquid water content can be written as a convex function of conserved variables with equal diffusivities. The temperature decrease is due to evaporative cooling as cloudy and clear air mix. More generally, the authors prove that if an isolated volume of fluid contains conserved scalars with equal diffusivities, then the average of any convex, twice-differentiable function of the conserved scalars cannot increase.
Abstract
Toward the end of the Cirrus Regional Study of Tropical Anvils and Cirrus Layer–Florida Area Cirrus Experiment (CRYSTAL–FACE) field campaign held during July 2002, high concentrations of Saharan dust, which can serve as cloud condensation nuclei (CCN), giant CCN (GCCN), and ice-forming nuclei (IFN) were observed over the peninsula of Florida. To investigate the impacts of enhanced aerosol concentrations on the characteristics of convective storms and their subsequent anvil development, sensitivity tests are conducted using the Regional Atmospheric Modeling System (RAMS) model, in which the initialization profiles of CCN, GCCN, and IFN concentrations are varied. These variations are found to have significant effects on the storm dynamics and microphysical processes, as well as on the surface precipitation. Updrafts are consistently stronger as the aerosol concentrations are increased. The anvils cover a smaller area but are better organized and have larger condensate mixing ratio maxima in the cases with greater aerosol concentrations. Cloud water mass tends to increase with increasing aerosol concentrations, with enhanced GCCN concentrations having the most significant influence. Increasing either the GCCN or IFN concentrations produces the most rainfall at the surface whereas enhanced CCN concentrations reduce surface rainfall. Higher IFN concentrations produce ice at warmer temperatures and deeper anvils, but simultaneously increasing the concentrations of CCN and GCCN leads to more supercooled liquid water available for freezing and greater ice mixing ratios. Graupel mixing ratios decrease and hail mixing ratios increase with increasing aerosol concentrations. Higher concentrations of GCCN and IFN result in greater accumulated surface precipitation initially. By the end of the simulation period, however, the accumulated precipitation is the greatest for the case in which the aerosol concentrations are lowest. Such changes in the dynamical and microphysical characteristics of convective storms as a result of the variations in aerosol concentrations have potential climate consequences, both through cloud radiative effects and the hydrological cycle. The impacts of varying CCN, GCCN, and IFN concentrations on the anvils will be discussed more fully in Part II.
Abstract
Toward the end of the Cirrus Regional Study of Tropical Anvils and Cirrus Layer–Florida Area Cirrus Experiment (CRYSTAL–FACE) field campaign held during July 2002, high concentrations of Saharan dust, which can serve as cloud condensation nuclei (CCN), giant CCN (GCCN), and ice-forming nuclei (IFN) were observed over the peninsula of Florida. To investigate the impacts of enhanced aerosol concentrations on the characteristics of convective storms and their subsequent anvil development, sensitivity tests are conducted using the Regional Atmospheric Modeling System (RAMS) model, in which the initialization profiles of CCN, GCCN, and IFN concentrations are varied. These variations are found to have significant effects on the storm dynamics and microphysical processes, as well as on the surface precipitation. Updrafts are consistently stronger as the aerosol concentrations are increased. The anvils cover a smaller area but are better organized and have larger condensate mixing ratio maxima in the cases with greater aerosol concentrations. Cloud water mass tends to increase with increasing aerosol concentrations, with enhanced GCCN concentrations having the most significant influence. Increasing either the GCCN or IFN concentrations produces the most rainfall at the surface whereas enhanced CCN concentrations reduce surface rainfall. Higher IFN concentrations produce ice at warmer temperatures and deeper anvils, but simultaneously increasing the concentrations of CCN and GCCN leads to more supercooled liquid water available for freezing and greater ice mixing ratios. Graupel mixing ratios decrease and hail mixing ratios increase with increasing aerosol concentrations. Higher concentrations of GCCN and IFN result in greater accumulated surface precipitation initially. By the end of the simulation period, however, the accumulated precipitation is the greatest for the case in which the aerosol concentrations are lowest. Such changes in the dynamical and microphysical characteristics of convective storms as a result of the variations in aerosol concentrations have potential climate consequences, both through cloud radiative effects and the hydrological cycle. The impacts of varying CCN, GCCN, and IFN concentrations on the anvils will be discussed more fully in Part II.
