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Abstract
A model for the radar reflectivity of boundary layer water clouds is constructed using cloud droplet spectra fitted to a truncated gamma distribution. The spectra were derived from several recent field experiments. Realistic space-based radar returns are simulated that take into account the pulse shape, digitization interval, averaging volume, and variations in droplet concentration, cloud depth, and cloud-top height. The results show that the long pulse length of the proposed radar is responsible for smearing out the real reflectivity spatially so that the space-based detected clouds occupy a volume far exceeding that of the “observed” cloud. However, the effect of smearing is reduced by the limited receiver sensitivity. Cloud volume of boundary layer clouds is overestimated by between 30% and 100% using proposed radar parameters. Even if clouds are detected, the radar reflectivity convoluted by the pulse shape is sufficiently different from the originally observed reflectivity to seriously impede the retrieval of accurate cloud liquid water content.
Abstract
A model for the radar reflectivity of boundary layer water clouds is constructed using cloud droplet spectra fitted to a truncated gamma distribution. The spectra were derived from several recent field experiments. Realistic space-based radar returns are simulated that take into account the pulse shape, digitization interval, averaging volume, and variations in droplet concentration, cloud depth, and cloud-top height. The results show that the long pulse length of the proposed radar is responsible for smearing out the real reflectivity spatially so that the space-based detected clouds occupy a volume far exceeding that of the “observed” cloud. However, the effect of smearing is reduced by the limited receiver sensitivity. Cloud volume of boundary layer clouds is overestimated by between 30% and 100% using proposed radar parameters. Even if clouds are detected, the radar reflectivity convoluted by the pulse shape is sufficiently different from the originally observed reflectivity to seriously impede the retrieval of accurate cloud liquid water content.
Abstract
Errors in cloud optical depth retrieved from pyranometer irradiances are estimated using a fractal model of cloud inhomogeneity. The cloud field is constructed from a two-dimensional array of pixels. For each of the pixels, which are 200 × 200 m2 in size, the radiative transfer is calculated using the independent pixel approximation. If cloud cover is 100%, the retrieval bias can be positive or negative for individual 10-min averaged transmittances, depending on the position of cloud inhomogeneities with respect to the pyranometer. The mean bias is always negative. Increasing the averaging time to 40 min reduces the scatter in the bias, although the mean bias remains −1.0, a value that depends on the choice of fractal model. If cloud cover is less than 100%, but there is no independent means to omit partly cloudy periods from the irradiance records, the negative retrieval bias will increase with reduced cloud cover and optical depth. Below optical depths of 5, the retrieval errors are so large that no meaningful results are obtained despite the fact that retrievals may appear to be reasonable. The simulations herein cannot take account of three-dimensional photon transport. The results of this study demonstrate that it is essential to measure cloud fraction and the variability of the cloud structure if optical depth is to be retrieved from pyranometer observations. Extra instruments recommended for ground-based remote sensing of cloud optical depth are a cloud lidar, powerful enough to probe the entire troposphere, and a microwave radiometer to measure the total column liquid water.
Abstract
Errors in cloud optical depth retrieved from pyranometer irradiances are estimated using a fractal model of cloud inhomogeneity. The cloud field is constructed from a two-dimensional array of pixels. For each of the pixels, which are 200 × 200 m2 in size, the radiative transfer is calculated using the independent pixel approximation. If cloud cover is 100%, the retrieval bias can be positive or negative for individual 10-min averaged transmittances, depending on the position of cloud inhomogeneities with respect to the pyranometer. The mean bias is always negative. Increasing the averaging time to 40 min reduces the scatter in the bias, although the mean bias remains −1.0, a value that depends on the choice of fractal model. If cloud cover is less than 100%, but there is no independent means to omit partly cloudy periods from the irradiance records, the negative retrieval bias will increase with reduced cloud cover and optical depth. Below optical depths of 5, the retrieval errors are so large that no meaningful results are obtained despite the fact that retrievals may appear to be reasonable. The simulations herein cannot take account of three-dimensional photon transport. The results of this study demonstrate that it is essential to measure cloud fraction and the variability of the cloud structure if optical depth is to be retrieved from pyranometer observations. Extra instruments recommended for ground-based remote sensing of cloud optical depth are a cloud lidar, powerful enough to probe the entire troposphere, and a microwave radiometer to measure the total column liquid water.
Abstract
Ground based lidar measurements of the atmospheric mixed layer depth, the entrainment zone depth and the wind speed and wind direction were used to test various parameterized entrainment models of mixed layer growth rate. Six case studies under clear air convective conditions over flat terrain in central Illinois are presented. It is shown that surface heating alone accounts for a major portion of the rise of the mixed layer on all days. A new set of entrainment model constants was determined which optimized height predictions for the dataset. Under convective conditions, the shape of the mixed layer height prediction curves closely resembled the observed shapes. Under conditions when significant wind shear was present, the shape of the height prediction curve departed from the data suggesting deficiencies in the parameterization of shear production. Development of small cumulus clouds on top of the layer is shown to affect mixed layer depths in the afternoon growth phase.
Abstract
Ground based lidar measurements of the atmospheric mixed layer depth, the entrainment zone depth and the wind speed and wind direction were used to test various parameterized entrainment models of mixed layer growth rate. Six case studies under clear air convective conditions over flat terrain in central Illinois are presented. It is shown that surface heating alone accounts for a major portion of the rise of the mixed layer on all days. A new set of entrainment model constants was determined which optimized height predictions for the dataset. Under convective conditions, the shape of the mixed layer height prediction curves closely resembled the observed shapes. Under conditions when significant wind shear was present, the shape of the height prediction curve departed from the data suggesting deficiencies in the parameterization of shear production. Development of small cumulus clouds on top of the layer is shown to affect mixed layer depths in the afternoon growth phase.
Abstract
Maine stratus clouds were simultaneously observed by nadir Nd:YAG lidar measurements and in situ cloud physics measurements. A procedure was applied to derive the two-dimensional vertical cross section of the liquid water from within the cloud top lidar observations. A comparison to direct in-cloud liquid water observations gave good results. The liquid water retrieval was limited to an effective optical of 1.5. The true cloud optical thickness was also obtained from the retrieval procedure to a corresponding limit of 3.8. The optical thickness of the observed marine stratus clouds was predominantly below 3.0.
Abstract
Maine stratus clouds were simultaneously observed by nadir Nd:YAG lidar measurements and in situ cloud physics measurements. A procedure was applied to derive the two-dimensional vertical cross section of the liquid water from within the cloud top lidar observations. A comparison to direct in-cloud liquid water observations gave good results. The liquid water retrieval was limited to an effective optical of 1.5. The true cloud optical thickness was also obtained from the retrieval procedure to a corresponding limit of 3.8. The optical thickness of the observed marine stratus clouds was predominantly below 3.0.
Abstract
North Atlantic (NA) deep-water formation and the resulting Atlantic meridional overturning cell is generally regarded as the primary feature of the global overturning circulation and is believed to be a result of the geometry of the continents. Here, instead, the overturning is viewed as a global energy–driven system and the robustness of NA dominance is investigated within this framework. Using an idealized geometry ocean general circulation model coupled to an energy moisture balance model, various climatic forcings are tested for their effect on the strength and structure of the overturning circulation. Without winds or a high vertical diffusivity, the ocean does not support deep convection. A supply of mechanical energy through winds or mixing (purposefully included or due to numerical diffusion) starts the deep-water formation. Once deep convection and overturning set in, the distribution of convection centers is determined by the relative strength of the thermal and haline buoyancy forcing. In the most thermally dominant state (i.e., negligible salinity gradients), strong convection is shared among the NA, North Pacific (NP), and Southern Ocean (SO), while near the haline limit, convection is restricted to the NA. The effect of a more vigorous hydrological cycle is to produce stronger salinity gradients, favoring the haline state of NA dominance. In contrast, a higher mean ocean temperature will increase the importance of temperature gradients because the thermal expansion coefficient is higher in a warm ocean, leading to the thermally dominated state. An increase in SO winds or global winds tends to weaken the salinity gradients, also pushing the ocean to the thermal state. Paleoobservations of more distributed sinking in warmer climates in the past suggest that mean ocean temperature and winds play a more important role than the hydrological cycle in the overturning circulation over long time scales.
Abstract
North Atlantic (NA) deep-water formation and the resulting Atlantic meridional overturning cell is generally regarded as the primary feature of the global overturning circulation and is believed to be a result of the geometry of the continents. Here, instead, the overturning is viewed as a global energy–driven system and the robustness of NA dominance is investigated within this framework. Using an idealized geometry ocean general circulation model coupled to an energy moisture balance model, various climatic forcings are tested for their effect on the strength and structure of the overturning circulation. Without winds or a high vertical diffusivity, the ocean does not support deep convection. A supply of mechanical energy through winds or mixing (purposefully included or due to numerical diffusion) starts the deep-water formation. Once deep convection and overturning set in, the distribution of convection centers is determined by the relative strength of the thermal and haline buoyancy forcing. In the most thermally dominant state (i.e., negligible salinity gradients), strong convection is shared among the NA, North Pacific (NP), and Southern Ocean (SO), while near the haline limit, convection is restricted to the NA. The effect of a more vigorous hydrological cycle is to produce stronger salinity gradients, favoring the haline state of NA dominance. In contrast, a higher mean ocean temperature will increase the importance of temperature gradients because the thermal expansion coefficient is higher in a warm ocean, leading to the thermally dominated state. An increase in SO winds or global winds tends to weaken the salinity gradients, also pushing the ocean to the thermal state. Paleoobservations of more distributed sinking in warmer climates in the past suggest that mean ocean temperature and winds play a more important role than the hydrological cycle in the overturning circulation over long time scales.
Abstract
Changes in radiative heating and cooling rates due to both the near Infrared and 15μbands of CO2 are computed for changes in CO2 concentration from 320 to 600 and 1000 ppmv. An increase in CO2 concentration leads to a smaller net change at the in the troposphere, little net change at the tropopause, and increased cooling in the stratosphere. The 15μ and near infrared effects act in the same sense in the tropopause but tend to compensate in the stratosphere, although the near infrared contribution is generally small when compared with that due to the 15μ band. Possible effects of the changes on the generation of zonal available potential energy are suggested.
Abstract
Changes in radiative heating and cooling rates due to both the near Infrared and 15μbands of CO2 are computed for changes in CO2 concentration from 320 to 600 and 1000 ppmv. An increase in CO2 concentration leads to a smaller net change at the in the troposphere, little net change at the tropopause, and increased cooling in the stratosphere. The 15μ and near infrared effects act in the same sense in the tropopause but tend to compensate in the stratosphere, although the near infrared contribution is generally small when compared with that due to the 15μ band. Possible effects of the changes on the generation of zonal available potential energy are suggested.
Abstract
A method is presented to obtain droplet concentration for water clouds from ground-based remote sensing observations. It relies on observations of cloud thickness, liquid water path, and optical extinction near the cloud base. The method was tested for two case studies (19 April 1996 and 4 September 1996) during the Clouds And Radiation experiment (CLARA). The CLARA experiment was designed to observe clouds using a variety of remote sensing instruments near the city of Delft in the western part of the Netherlands. The measurement of cloud thickness is dependent on the detection of cloud base by lidar and cloud top by radar. It is shown that during CLARA it was possible to detect cloud base with an uncertainty of less than 30 m using current lidar techniques. The agreement between in situ and remote sensing observations of droplet concentration was reasonable. An error analysis indicates that this method is most sensitive to uncertainties in liquid water path and the unknown effects of multiple scattering on lidar signal returns. When the liquid water path is very small the relative error of the liquid water path increases to unacceptable levels, so that the retrieval of droplet concentration becomes very difficult. The estimated uncertainty in the strength of multiple scattering can explain differences between observations and retrievals of droplet concentration on one day, but not the other.
Abstract
A method is presented to obtain droplet concentration for water clouds from ground-based remote sensing observations. It relies on observations of cloud thickness, liquid water path, and optical extinction near the cloud base. The method was tested for two case studies (19 April 1996 and 4 September 1996) during the Clouds And Radiation experiment (CLARA). The CLARA experiment was designed to observe clouds using a variety of remote sensing instruments near the city of Delft in the western part of the Netherlands. The measurement of cloud thickness is dependent on the detection of cloud base by lidar and cloud top by radar. It is shown that during CLARA it was possible to detect cloud base with an uncertainty of less than 30 m using current lidar techniques. The agreement between in situ and remote sensing observations of droplet concentration was reasonable. An error analysis indicates that this method is most sensitive to uncertainties in liquid water path and the unknown effects of multiple scattering on lidar signal returns. When the liquid water path is very small the relative error of the liquid water path increases to unacceptable levels, so that the retrieval of droplet concentration becomes very difficult. The estimated uncertainty in the strength of multiple scattering can explain differences between observations and retrievals of droplet concentration on one day, but not the other.
Abstract
The development of a radiation fog layer at the Cabauw Experimental Site for Atmospheric Research (51.97°N, 4.93°E) on 23 March 2011 was observed with ground-based in situ and remote sensing observations to investigate the relationship between visibility and radar reflectivity. The fog layer thickness was less than 200 m. Radar reflectivity values did not exceed −25 dBZ even with visibilities less than 100 m. The onset and evaporation of fog produce different radar reflectivity–visibility relationships. The evolution of the fog layer was modeled with a droplet activation model that used the aerosol size distribution observed at the 60-m altitude tower level as input. Radar reflectivity and visibility were calculated from model drop size spectra using Mie scattering theory. Since radiative cooling rates are small in comparison with cooling rates due to adiabatic lift of aerosol-laden air, the modeled supersaturation remains low so that few aerosol particles are activated to cloud droplets. The modeling results suggest that the different radar reflectivity–visibility relationships are the result of differences in the interplay between water vapor and cloud droplets during formation and evaporation of the fog. During droplet activation, only a few large cloud droplets remain after successfully competing for water vapor with the smaller activated droplets. These small droplets eventually evaporate (deactivate) again. In the fog dissolution/evaporation stage, only these large droplet need to be evaporated. Therefore, to convert radar reflectivity to visibility for traffic safety products, knowledge of the state of local fog evolution is necessary.
Abstract
The development of a radiation fog layer at the Cabauw Experimental Site for Atmospheric Research (51.97°N, 4.93°E) on 23 March 2011 was observed with ground-based in situ and remote sensing observations to investigate the relationship between visibility and radar reflectivity. The fog layer thickness was less than 200 m. Radar reflectivity values did not exceed −25 dBZ even with visibilities less than 100 m. The onset and evaporation of fog produce different radar reflectivity–visibility relationships. The evolution of the fog layer was modeled with a droplet activation model that used the aerosol size distribution observed at the 60-m altitude tower level as input. Radar reflectivity and visibility were calculated from model drop size spectra using Mie scattering theory. Since radiative cooling rates are small in comparison with cooling rates due to adiabatic lift of aerosol-laden air, the modeled supersaturation remains low so that few aerosol particles are activated to cloud droplets. The modeling results suggest that the different radar reflectivity–visibility relationships are the result of differences in the interplay between water vapor and cloud droplets during formation and evaporation of the fog. During droplet activation, only a few large cloud droplets remain after successfully competing for water vapor with the smaller activated droplets. These small droplets eventually evaporate (deactivate) again. In the fog dissolution/evaporation stage, only these large droplet need to be evaporated. Therefore, to convert radar reflectivity to visibility for traffic safety products, knowledge of the state of local fog evolution is necessary.
Abstract
A wide body of modeling and theoretical scaling studies support the concept that changes to the Atlantic meridional overturning circulation (AMOC), whether forced by winds or buoyancy fluxes, can be understood in terms of a simple causative relation between the AMOC and an appropriately defined meridional density gradient (MDG). The MDG is supposed to translate directly into a meridional pressure gradient. Here two sets of experiments are performed using a modular ocean model coupled to an energy–moisture balance model in which the positive AMOC–MDG relation breaks down. In the first suite of seven model integrations it is found that increasing winds in the Southern Ocean cause an increase in overturning while the surface density difference between the equator and North Atlantic drops. In the second suite of eight model integrations the equation of state is manipulated so that the density is calculated at the model temperature plus an artificial increment ΔT that ranges from −3° to 9°C. (An increase in ΔT results in increased sensitivity of density to temperature gradients.) The AMOC in these model integrations drops as the MDG increases regardless of whether the density difference is computed at the surface or averaged over the upper ocean. Traditional scaling analysis can only produce this weaker AMOC if the scale depth decreases enough to compensate for the stronger MDG. Five estimates of the depth scale are evaluated and it is found that the changes in the AMOC can be derived from scaling analysis when using the depth of the maximum overturning circulation or estimates thereof but not from the pycnocline depth. These two depth scales are commonly assumed to be the same in theoretical models of the AMOC. It is suggested that the correlation between the MDG and AMOC breaks down in these model integrations because the depth and strength of the AMOC is influenced strongly by remote forcing such as Southern Ocean winds and Antarctic Bottom Water formation.
Abstract
A wide body of modeling and theoretical scaling studies support the concept that changes to the Atlantic meridional overturning circulation (AMOC), whether forced by winds or buoyancy fluxes, can be understood in terms of a simple causative relation between the AMOC and an appropriately defined meridional density gradient (MDG). The MDG is supposed to translate directly into a meridional pressure gradient. Here two sets of experiments are performed using a modular ocean model coupled to an energy–moisture balance model in which the positive AMOC–MDG relation breaks down. In the first suite of seven model integrations it is found that increasing winds in the Southern Ocean cause an increase in overturning while the surface density difference between the equator and North Atlantic drops. In the second suite of eight model integrations the equation of state is manipulated so that the density is calculated at the model temperature plus an artificial increment ΔT that ranges from −3° to 9°C. (An increase in ΔT results in increased sensitivity of density to temperature gradients.) The AMOC in these model integrations drops as the MDG increases regardless of whether the density difference is computed at the surface or averaged over the upper ocean. Traditional scaling analysis can only produce this weaker AMOC if the scale depth decreases enough to compensate for the stronger MDG. Five estimates of the depth scale are evaluated and it is found that the changes in the AMOC can be derived from scaling analysis when using the depth of the maximum overturning circulation or estimates thereof but not from the pycnocline depth. These two depth scales are commonly assumed to be the same in theoretical models of the AMOC. It is suggested that the correlation between the MDG and AMOC breaks down in these model integrations because the depth and strength of the AMOC is influenced strongly by remote forcing such as Southern Ocean winds and Antarctic Bottom Water formation.
Abstract
This paper presents a detailed analysis of convection-permitting cloud simulations, aimed at increasing the understanding of the role of parameterized cloud microphysics in the simulation of mesoscale convective systems (MCSs) in the tropical western Pacific (TWP). Simulations with three commonly used bulk microphysics parameterizations with varying complexity have been compared against satellite-retrieved cloud properties. An MCS identification and tracking algorithm was applied to the observations and the simulations to evaluate the number, spatial extent, and microphysical properties of individual cloud systems. Different from many previous studies, these individual cloud systems could be tracked over larger distances because of the large TWP domain studied.
The analysis demonstrates that the simulation of MCSs is very sensitive to the parameterization of microphysical processes. The most crucial element was found to be the fall velocity of frozen condensate. Differences in this fall velocity between the experiments were more related to differences in particle number concentrations than to fall speed parameterization. Microphysics schemes that exhibit slow sedimentation rates for ice aloft experience a larger buildup of condensate in the upper troposphere. This leads to more numerous and/or larger MCSs with larger anvils. Mean surface precipitation was found to be overestimated and insensitive to the microphysical schemes employed in this study. In terms of the investigated properties, the performances of complex two-moment schemes were not superior to the simpler one-moment schemes, since explicit prediction of number concentration does not necessarily improve processes such as ice nucleation, the aggregation of ice crystals into snowflakes, and their sedimentation characteristics.
Abstract
This paper presents a detailed analysis of convection-permitting cloud simulations, aimed at increasing the understanding of the role of parameterized cloud microphysics in the simulation of mesoscale convective systems (MCSs) in the tropical western Pacific (TWP). Simulations with three commonly used bulk microphysics parameterizations with varying complexity have been compared against satellite-retrieved cloud properties. An MCS identification and tracking algorithm was applied to the observations and the simulations to evaluate the number, spatial extent, and microphysical properties of individual cloud systems. Different from many previous studies, these individual cloud systems could be tracked over larger distances because of the large TWP domain studied.
The analysis demonstrates that the simulation of MCSs is very sensitive to the parameterization of microphysical processes. The most crucial element was found to be the fall velocity of frozen condensate. Differences in this fall velocity between the experiments were more related to differences in particle number concentrations than to fall speed parameterization. Microphysics schemes that exhibit slow sedimentation rates for ice aloft experience a larger buildup of condensate in the upper troposphere. This leads to more numerous and/or larger MCSs with larger anvils. Mean surface precipitation was found to be overestimated and insensitive to the microphysical schemes employed in this study. In terms of the investigated properties, the performances of complex two-moment schemes were not superior to the simpler one-moment schemes, since explicit prediction of number concentration does not necessarily improve processes such as ice nucleation, the aggregation of ice crystals into snowflakes, and their sedimentation characteristics.
