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- Author or Editor: U. Lohmann x
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Abstract
Observations by Borys, Lowenthal, Cohn, and Brown in midlatitude orographic clouds show that for a given supercooled liquid water content, both the riming and the snowfall rates are smaller if the supercooled cloud has more cloud droplets as, for example, caused by anthropogenic aerosols. The climatic implication of this effect was studied in global climate model simulations by replacing the constant riming efficiency with a size-dependent one appropriate for planar crystals and aggregates, respectively. In the model simulations that use a size-dependent riming collection efficiency, the pollution-induced decrease in cloud droplet size causes a decrease in the riming rate in stratiform clouds despite larger liquid water contents in polluted clouds. Contrary to the above-mentioned observations, in all model simulations the snowfall rate increases because of feedbacks in the climate system. Anthropogenic aerosol particles increase the aerosol and cloud optical thickness, which reduces the solar radiation at the top of the atmosphere and the surface. This in turn causes a cooling in Northern Hemisphere midlatitudes that favors precipitation formation via the ice phase.
Abstract
Observations by Borys, Lowenthal, Cohn, and Brown in midlatitude orographic clouds show that for a given supercooled liquid water content, both the riming and the snowfall rates are smaller if the supercooled cloud has more cloud droplets as, for example, caused by anthropogenic aerosols. The climatic implication of this effect was studied in global climate model simulations by replacing the constant riming efficiency with a size-dependent one appropriate for planar crystals and aggregates, respectively. In the model simulations that use a size-dependent riming collection efficiency, the pollution-induced decrease in cloud droplet size causes a decrease in the riming rate in stratiform clouds despite larger liquid water contents in polluted clouds. Contrary to the above-mentioned observations, in all model simulations the snowfall rate increases because of feedbacks in the climate system. Anthropogenic aerosol particles increase the aerosol and cloud optical thickness, which reduces the solar radiation at the top of the atmosphere and the surface. This in turn causes a cooling in Northern Hemisphere midlatitudes that favors precipitation formation via the ice phase.
Abstract
New parameterizations of contact freezing and immersion freezing in stratiform mixed-phase clouds (with temperatures between 0° and −35°C) for black carbon and mineral dust assumed to be composed of either kaolinite (simulation KAO) or montmorillonite (simulation MON) are introduced into the ECHAM4 general circulation model. The effectiveness of black carbon and dust as ice nuclei as a function of temperature is parameterized from a compilation of laboratory studies. This is the first time that freezing parameterizations take the chemical composition of ice nuclei into account. The rather subtle differences between these sensitivity simulations in the present-day climate have significant implications for the anthropogenic indirect aerosol effect. The decrease in net radiation in these sensitivity simulations at the top of the atmosphere varies from 1 ± 0.3 to 2.1 ± 0.1 W m−2 depending on whether dust is assumed to be composed of kaolinite or montmorillonite. In simulation KAO, black carbon has a higher relevancy as an ice nucleus than in simulation MON, because kaolinite is not freezing as effectively as montmorillonite. In simulation KAO, the addition of anthropogenic aerosols results in a larger ice water path, a slightly higher precipitation rate, and a reduced total cloud cover. On the contrary, in simulation MON the increase in ice water path is much smaller and globally the decrease in precipitation is dominated by the reduction in warm-phase precipitation due to the indirect cloud lifetime effect.
Abstract
New parameterizations of contact freezing and immersion freezing in stratiform mixed-phase clouds (with temperatures between 0° and −35°C) for black carbon and mineral dust assumed to be composed of either kaolinite (simulation KAO) or montmorillonite (simulation MON) are introduced into the ECHAM4 general circulation model. The effectiveness of black carbon and dust as ice nuclei as a function of temperature is parameterized from a compilation of laboratory studies. This is the first time that freezing parameterizations take the chemical composition of ice nuclei into account. The rather subtle differences between these sensitivity simulations in the present-day climate have significant implications for the anthropogenic indirect aerosol effect. The decrease in net radiation in these sensitivity simulations at the top of the atmosphere varies from 1 ± 0.3 to 2.1 ± 0.1 W m−2 depending on whether dust is assumed to be composed of kaolinite or montmorillonite. In simulation KAO, black carbon has a higher relevancy as an ice nucleus than in simulation MON, because kaolinite is not freezing as effectively as montmorillonite. In simulation KAO, the addition of anthropogenic aerosols results in a larger ice water path, a slightly higher precipitation rate, and a reduced total cloud cover. On the contrary, in simulation MON the increase in ice water path is much smaller and globally the decrease in precipitation is dominated by the reduction in warm-phase precipitation due to the indirect cloud lifetime effect.
Abstract
Tropical land mean surface air temperature and precipitation responses to the eruptions of El Chichón in 1982 and Pinatubo in 1991, as simulated by the atmosphere-only GCMs (AMIP) in phase 5 of the Coupled Model Intercomparison Project (CMIP5), are examined and compared to three observational datasets. The El Niño–Southern Oscillation (ENSO) signal was statistically separated from the volcanic signal in all time series. Focusing on the ENSO signal, it was found that the 17 investigated AMIP models successfully simulate the observed 4-month delay in the temperature responses to the ENSO phase but simulate somewhat too-fast precipitation responses during the El Niño onset stage. The observed correlation between temperature and ENSO phase (correlation coefficient of 0.75) is generally captured well by the models (simulated correlation of 0.71 and ensemble means of 0.61–0.83). For precipitation, mean correlations with the ENSO phase are −0.59 for observations and −0.53 for the models, with individual ensemble members having correlations as low as −0.26. Observed, ENSO-removed tropical land temperature and precipitation decrease by about 0.35 K and 0.25 mm day−1 after the Pinatubo eruption, while no significant decrease in either variable was observed after El Chichón. The AMIP models generally capture this behavior despite a tendency to overestimate the precipitation response to El Chichón. Scatter is substantial, both across models and across ensemble members of individual models. Natural variability thus may still play a prominent role despite the strong volcanic forcing.
Abstract
Tropical land mean surface air temperature and precipitation responses to the eruptions of El Chichón in 1982 and Pinatubo in 1991, as simulated by the atmosphere-only GCMs (AMIP) in phase 5 of the Coupled Model Intercomparison Project (CMIP5), are examined and compared to three observational datasets. The El Niño–Southern Oscillation (ENSO) signal was statistically separated from the volcanic signal in all time series. Focusing on the ENSO signal, it was found that the 17 investigated AMIP models successfully simulate the observed 4-month delay in the temperature responses to the ENSO phase but simulate somewhat too-fast precipitation responses during the El Niño onset stage. The observed correlation between temperature and ENSO phase (correlation coefficient of 0.75) is generally captured well by the models (simulated correlation of 0.71 and ensemble means of 0.61–0.83). For precipitation, mean correlations with the ENSO phase are −0.59 for observations and −0.53 for the models, with individual ensemble members having correlations as low as −0.26. Observed, ENSO-removed tropical land temperature and precipitation decrease by about 0.35 K and 0.25 mm day−1 after the Pinatubo eruption, while no significant decrease in either variable was observed after El Chichón. The AMIP models generally capture this behavior despite a tendency to overestimate the precipitation response to El Chichón. Scatter is substantial, both across models and across ensemble members of individual models. Natural variability thus may still play a prominent role despite the strong volcanic forcing.
Assessments of the influence of aerosol emissions from human activities on the radiation budget, in particular via the modification of cloud properties, have been a challenge. In light of the variability to both aerosol properties and environmental properties affected by aerosols, observational evidence alone cannot provide accurate and global answers, because detailed observations are locally limited and/or lack statistical significance. Thus, current understanding is predominantly derived from simulations with ancies to envelope (backward) modeling, however, suggest that many aerosol processes in global (forward) modeling are not properly considered. Using analytically derived parameterizations is recommended wherever possible. If an analytical method does not exist or is too demanding computationally, laboratory results augmented by field data are the second-best approach. For the constraint of so-derived parameterizations at the GCM scale, evaluating individual parameterizations using statistical relationships of satellite-retrieved quantities relevant to the process is recommended. The set of parameterizations may also be evaluated and improved using the data assimilation technique. To improve the quality of data references to modeling, there is a need to link available atmospheric data from all scales, and establish and support validation networks and experiments, and a commitment to fine-tune and improve satellite retrievals in an iterative process even beyond the anticipated period of the mission. Only then can more reliable estimates of the indirect aerosol effect be expected.
Assessments of the influence of aerosol emissions from human activities on the radiation budget, in particular via the modification of cloud properties, have been a challenge. In light of the variability to both aerosol properties and environmental properties affected by aerosols, observational evidence alone cannot provide accurate and global answers, because detailed observations are locally limited and/or lack statistical significance. Thus, current understanding is predominantly derived from simulations with ancies to envelope (backward) modeling, however, suggest that many aerosol processes in global (forward) modeling are not properly considered. Using analytically derived parameterizations is recommended wherever possible. If an analytical method does not exist or is too demanding computationally, laboratory results augmented by field data are the second-best approach. For the constraint of so-derived parameterizations at the GCM scale, evaluating individual parameterizations using statistical relationships of satellite-retrieved quantities relevant to the process is recommended. The set of parameterizations may also be evaluated and improved using the data assimilation technique. To improve the quality of data references to modeling, there is a need to link available atmospheric data from all scales, and establish and support validation networks and experiments, and a commitment to fine-tune and improve satellite retrievals in an iterative process even beyond the anticipated period of the mission. Only then can more reliable estimates of the indirect aerosol effect be expected.
Abstract
A transient shallow-convection scheme is implemented into the general circulation model ECHAM5 and the coupled aerosol model HAM, developed at the Max Planck Institute for Meteorology in Hamburg. The shallow-convection scheme is extended to take the ice phase into account. In addition, a detailed double-moment microphysics approach has been added. In this approach, the freezing processes and precipitation formation are dependent on aerosols. Furthermore, in the scheme, tracers are transported and scavenged consistently as in the rest of the model. Results of a single-column model simulation for the Barbados Oceanography and Meteorology Experiment (BOMEX) campaign are compared with previously published large-eddy simulation (LES) results. Compared to the standard version, the global ECHAM5-HAM simulations with the newly implemented scheme show a decreased frequency of shallow convection in better agreement with LES. Less shallow convection is compensated by more stratus and stratocumulus. Deep and especially midlevel convection are markedly affected by those changes, which in turn influence high-level clouds. Generally, a better agreement with the observations can be obtained. For a better understanding of the scheme’s impact and to test different setting parameters, sensitivity analyses are performed. The mixing properties, cloud-base vertical velocity, and launching layer of the test parcel, respectively, are varied. In this context, results from simulations without shallow convection are also presented.
Abstract
A transient shallow-convection scheme is implemented into the general circulation model ECHAM5 and the coupled aerosol model HAM, developed at the Max Planck Institute for Meteorology in Hamburg. The shallow-convection scheme is extended to take the ice phase into account. In addition, a detailed double-moment microphysics approach has been added. In this approach, the freezing processes and precipitation formation are dependent on aerosols. Furthermore, in the scheme, tracers are transported and scavenged consistently as in the rest of the model. Results of a single-column model simulation for the Barbados Oceanography and Meteorology Experiment (BOMEX) campaign are compared with previously published large-eddy simulation (LES) results. Compared to the standard version, the global ECHAM5-HAM simulations with the newly implemented scheme show a decreased frequency of shallow convection in better agreement with LES. Less shallow convection is compensated by more stratus and stratocumulus. Deep and especially midlevel convection are markedly affected by those changes, which in turn influence high-level clouds. Generally, a better agreement with the observations can be obtained. For a better understanding of the scheme’s impact and to test different setting parameters, sensitivity analyses are performed. The mixing properties, cloud-base vertical velocity, and launching layer of the test parcel, respectively, are varied. In this context, results from simulations without shallow convection are also presented.
Abstract
Cirrus clouds impact the planetary energy balance and upper-tropospheric water vapor transport and are therefore relevant for climate. In this study cirrus clouds at temperatures colder than −40°C simulated by the ECHAM–Hamburg Aerosol Module (ECHAM-HAM) general circulation model are compared to Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data. The model captures the general cloud cover pattern and reproduces the observed median ice water content within a factor of 2, while extinction is overestimated by about a factor of 3 as revealed by temperature-dependent frequency histograms. Two distinct types of cirrus clouds are found: in situ–formed cirrus dominating at temperatures colder than −55°C and liquid-origin cirrus dominating at temperatures warmer than −55°C. The latter cirrus form in anvils of deep convective clouds or by glaciation of mixed-phase clouds, leading to high ice crystal number concentrations. They are associated with extinction coefficients and ice water content of up to 1 km−1 and 0.1 g m−3, respectively, while the in situ–formed cirrus are associated with smaller extinction coefficients and ice water content. In situ–formed cirrus are nucleated either heterogeneously or homogeneously. The simulated homogeneous ice crystals are similar to liquid-origin cirrus, which are associated with high ice crystal number concentrations. On the contrary, heterogeneously nucleated ice crystals appear in smaller number concentrations. However, ice crystal aggregation and depositional growth smooth the differences between several formation mechanisms, making the attribution to a specific ice nucleation mechanism challenging.
Abstract
Cirrus clouds impact the planetary energy balance and upper-tropospheric water vapor transport and are therefore relevant for climate. In this study cirrus clouds at temperatures colder than −40°C simulated by the ECHAM–Hamburg Aerosol Module (ECHAM-HAM) general circulation model are compared to Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data. The model captures the general cloud cover pattern and reproduces the observed median ice water content within a factor of 2, while extinction is overestimated by about a factor of 3 as revealed by temperature-dependent frequency histograms. Two distinct types of cirrus clouds are found: in situ–formed cirrus dominating at temperatures colder than −55°C and liquid-origin cirrus dominating at temperatures warmer than −55°C. The latter cirrus form in anvils of deep convective clouds or by glaciation of mixed-phase clouds, leading to high ice crystal number concentrations. They are associated with extinction coefficients and ice water content of up to 1 km−1 and 0.1 g m−3, respectively, while the in situ–formed cirrus are associated with smaller extinction coefficients and ice water content. In situ–formed cirrus are nucleated either heterogeneously or homogeneously. The simulated homogeneous ice crystals are similar to liquid-origin cirrus, which are associated with high ice crystal number concentrations. On the contrary, heterogeneously nucleated ice crystals appear in smaller number concentrations. However, ice crystal aggregation and depositional growth smooth the differences between several formation mechanisms, making the attribution to a specific ice nucleation mechanism challenging.
Abstract
We investigate the circumstances under which the Saharan air layer (SAL) has a negative impact on the intensification of tropical cyclones (TCs) over the North Atlantic Ocean. Using hurricane tracking, aerosol optical depth (AOD) data, and meteorological analyses, we analyze the interaction of the SAL with 52 named TCs that formed over the east and central Atlantic south of the Cape Verde islands between 2004 and 2017. Following the categorization of negative SAL influences on TC intensification by Dunion and Velden, only 21% of the investigated storms can be classified (28% of all storms that encountered the SAL), and 21% of the storms continue to intensify despite the presence of the SAL. We show that among TCs that encounter the SAL, there is evidence supporting a weak negative correlation between the magnitude of TC intensification and the ambient AOD. However, above-average Saharan dust abundance in the vicinity of TCs is not a good independent indicator for storm nonintensification. To better understand the specific processes involved, a composite study is carried out, contrasting storms that intensify in the presence of the SAL against those that do not. We find that sheared air masses on the north side and drier air from the northeast of the storm early on during its lifetime, in addition to higher AOD, are associated with TC nonintensification in proximity to the SAL.
Abstract
We investigate the circumstances under which the Saharan air layer (SAL) has a negative impact on the intensification of tropical cyclones (TCs) over the North Atlantic Ocean. Using hurricane tracking, aerosol optical depth (AOD) data, and meteorological analyses, we analyze the interaction of the SAL with 52 named TCs that formed over the east and central Atlantic south of the Cape Verde islands between 2004 and 2017. Following the categorization of negative SAL influences on TC intensification by Dunion and Velden, only 21% of the investigated storms can be classified (28% of all storms that encountered the SAL), and 21% of the storms continue to intensify despite the presence of the SAL. We show that among TCs that encounter the SAL, there is evidence supporting a weak negative correlation between the magnitude of TC intensification and the ambient AOD. However, above-average Saharan dust abundance in the vicinity of TCs is not a good independent indicator for storm nonintensification. To better understand the specific processes involved, a composite study is carried out, contrasting storms that intensify in the presence of the SAL against those that do not. We find that sheared air masses on the north side and drier air from the northeast of the storm early on during its lifetime, in addition to higher AOD, are associated with TC nonintensification in proximity to the SAL.
Abstract
The Global Energy and Water Cycle Experiment has identified the poor representation of clouds in atmospheric general circulation models as one of the major impediments for the use of these models in reliably predicting future climate change. One of the most commonly encountered types of cloud system in midlatitudes is that associated with cyclones. The purpose of this study is to investigate the representation of frontal cloud systems in a hierarchy of models in order to identify their relative weaknesses. The hierarchy of models was classified according to the horizontal resolution: cloud-resolving models (5-km resolution), limited-area models (20-km resolution), coarse-grid single-column models (300 km), and an atmospheric general circulation model (>100 km). The models were evaluated using both in situ and satellite data.
The study shows, as expected, that the higher-resolution models give a more complete description of the front and capture many of the observed nonlinear features of the front. At the low resolution, the simulations are unable to capture the front accurately due to the lack of the nonlinear features seen in the high-resolution simulations. The model intercomparison identified problems in applying single-column models to rapidly advecting baroclinic systems. Mesoscale circulations driven by subgrid-scale dynamical, thermodynamical, and microphysical processes are identified as an important feedback mechanism linking the frontal circulations and the cloud field. Finally it is shown that the same techniques used to validate climatological studies with International Satellite Cloud Climatology Project data are also valid for case studies, thereby providing a methodology to generalize the single case studies to climatological studies.
Abstract
The Global Energy and Water Cycle Experiment has identified the poor representation of clouds in atmospheric general circulation models as one of the major impediments for the use of these models in reliably predicting future climate change. One of the most commonly encountered types of cloud system in midlatitudes is that associated with cyclones. The purpose of this study is to investigate the representation of frontal cloud systems in a hierarchy of models in order to identify their relative weaknesses. The hierarchy of models was classified according to the horizontal resolution: cloud-resolving models (5-km resolution), limited-area models (20-km resolution), coarse-grid single-column models (300 km), and an atmospheric general circulation model (>100 km). The models were evaluated using both in situ and satellite data.
The study shows, as expected, that the higher-resolution models give a more complete description of the front and capture many of the observed nonlinear features of the front. At the low resolution, the simulations are unable to capture the front accurately due to the lack of the nonlinear features seen in the high-resolution simulations. The model intercomparison identified problems in applying single-column models to rapidly advecting baroclinic systems. Mesoscale circulations driven by subgrid-scale dynamical, thermodynamical, and microphysical processes are identified as an important feedback mechanism linking the frontal circulations and the cloud field. Finally it is shown that the same techniques used to validate climatological studies with International Satellite Cloud Climatology Project data are also valid for case studies, thereby providing a methodology to generalize the single case studies to climatological studies.
A Global Land Data Assimilation System (GLDAS) has been developed. Its purpose is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes. GLDAS is unique in that it is an uncoupled land surface modeling system that drives multiple models, integrates a huge quantity of observation-based data, runs globally at high resolution (0.25°), and produces results in near–real time (typically within 48 h of the present). GLDAS is also a test bed for innovative modeling and assimilation capabilities. A vegetation-based “tiling” approach is used to simulate subgrid-scale variability, with a 1-km global vegetation dataset as its basis. Soil and elevation parameters are based on high-resolution global datasets. Observation-based precipitation and downward radiation and output fields from the best available global coupled atmospheric data assimilation systems are employed as forcing data. The high-quality, global land surface fields provided by GLDAS will be used to initialize weather and climate prediction models and will promote various hydrometeorological studies and applications. The ongoing GLDAS archive (started in 2001) of modeled and observed, global, surface meteorological data, parameter maps, and output is publicly available.
A Global Land Data Assimilation System (GLDAS) has been developed. Its purpose is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes. GLDAS is unique in that it is an uncoupled land surface modeling system that drives multiple models, integrates a huge quantity of observation-based data, runs globally at high resolution (0.25°), and produces results in near–real time (typically within 48 h of the present). GLDAS is also a test bed for innovative modeling and assimilation capabilities. A vegetation-based “tiling” approach is used to simulate subgrid-scale variability, with a 1-km global vegetation dataset as its basis. Soil and elevation parameters are based on high-resolution global datasets. Observation-based precipitation and downward radiation and output fields from the best available global coupled atmospheric data assimilation systems are employed as forcing data. The high-quality, global land surface fields provided by GLDAS will be used to initialize weather and climate prediction models and will promote various hydrometeorological studies and applications. The ongoing GLDAS archive (started in 2001) of modeled and observed, global, surface meteorological data, parameter maps, and output is publicly available.
Abstract
Mixed-phase clouds represent a three-phase colloidal system consisting of water vapor, ice particles, and coexisting supercooled liquid droplets. Mixed-phase clouds are ubiquitous in the troposphere, occurring at all latitudes from the polar regions to the tropics. Because of their widespread nature, mixed-phase processes play critical roles in the life cycle of clouds, precipitation formation, cloud electrification, and the radiative energy balance on both regional and global scales. Yet, in spite of many decades of observations and theoretical studies, our knowledge and understanding of mixed-phase cloud processes remains incomplete. Mixed-phase clouds are notoriously difficult to represent in numerical weather prediction and climate models, and their description in theoretical cloud physics still presents complicated challenges. In this chapter, the current status of our knowledge on mixed-phase clouds, obtained from theoretical studies and observations, is reviewed. Recent progress, along with a discussion of problems and gaps in understanding the mixed-phase environment is summarized. Specific steps to improve our knowledge of mixed-phase clouds and their role in the climate and weather system are proposed.
Abstract
Mixed-phase clouds represent a three-phase colloidal system consisting of water vapor, ice particles, and coexisting supercooled liquid droplets. Mixed-phase clouds are ubiquitous in the troposphere, occurring at all latitudes from the polar regions to the tropics. Because of their widespread nature, mixed-phase processes play critical roles in the life cycle of clouds, precipitation formation, cloud electrification, and the radiative energy balance on both regional and global scales. Yet, in spite of many decades of observations and theoretical studies, our knowledge and understanding of mixed-phase cloud processes remains incomplete. Mixed-phase clouds are notoriously difficult to represent in numerical weather prediction and climate models, and their description in theoretical cloud physics still presents complicated challenges. In this chapter, the current status of our knowledge on mixed-phase clouds, obtained from theoretical studies and observations, is reviewed. Recent progress, along with a discussion of problems and gaps in understanding the mixed-phase environment is summarized. Specific steps to improve our knowledge of mixed-phase clouds and their role in the climate and weather system are proposed.
