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- Author or Editor: Christian Jakob x
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Abstract
Previous work has shown that the sharp fall in winter rainfall over coastal southwestern Australia in the 1970s was mainly due to a fall in the frequency of fronts; the gradual reduction in rainfall since the late 1990s was due to a reduction in the number of light-rain days; and the increased inland summer rainfall in the 1970s was due to an increased number of easterly troughs. The current paper extends this earlier work by identifying the rainfall patterns in the region in 14 CMIP5 models for the period 1980–2005 and by calculating how these patterns are projected to change in the twenty-first century. The patterns are identified using k-means clustering of the rainfall, which are validated against observed rainfall clusters. Although the agreement between the models and the observation is generally good, the models underestimate the frequency of raining fronts. In both representative concentration pathway 4.5 and 8.5 (RCP4.5 and RCP8.5) scenarios the number of dry days increases significantly at the expense of light-rain days and frontal rainfall. However, these trends are twice as large in the RCP8.5 scenario as in the RCP4.5 scenario. The reduction in the rainfall from the historical period to the second half of the twenty-first century is produced mainly by a reduction in both the frequency and intensity of light rain and a reduction in the frequency of fronts in the westerlies.
Abstract
Previous work has shown that the sharp fall in winter rainfall over coastal southwestern Australia in the 1970s was mainly due to a fall in the frequency of fronts; the gradual reduction in rainfall since the late 1990s was due to a reduction in the number of light-rain days; and the increased inland summer rainfall in the 1970s was due to an increased number of easterly troughs. The current paper extends this earlier work by identifying the rainfall patterns in the region in 14 CMIP5 models for the period 1980–2005 and by calculating how these patterns are projected to change in the twenty-first century. The patterns are identified using k-means clustering of the rainfall, which are validated against observed rainfall clusters. Although the agreement between the models and the observation is generally good, the models underestimate the frequency of raining fronts. In both representative concentration pathway 4.5 and 8.5 (RCP4.5 and RCP8.5) scenarios the number of dry days increases significantly at the expense of light-rain days and frontal rainfall. However, these trends are twice as large in the RCP8.5 scenario as in the RCP4.5 scenario. The reduction in the rainfall from the historical period to the second half of the twenty-first century is produced mainly by a reduction in both the frequency and intensity of light rain and a reduction in the frequency of fronts in the westerlies.
Abstract
The simulation of northern Australian wet season rainfall bursts by coupled climate models is evaluated. Individual models produce vastly different amounts of precipitation over the north of Australia during the wet season, and this is found to be related to the number of bursts they produce. The seasonal cycle of bursts is found to be poor in most of the models evaluated. It is known that northern Australian wet season bursts are often associated with midlatitude Rossby wave packets and their surface signature as they are refracted toward the tropics. The relationship between midlatitude waves and the initiation of wet season bursts is simulated well by the models evaluated. Another well-documented influence on the initiation of northern Australian wet season bursts is the Madden–Julian oscillation (MJO). No model adequately simulated the tropical outgoing longwave radiation temporal–spatial patterns seen in the reanalysis-derived OLR. This result suggests that the connection between the MJO and the initiation of northern Australian wet season bursts in models is poor.
Abstract
The simulation of northern Australian wet season rainfall bursts by coupled climate models is evaluated. Individual models produce vastly different amounts of precipitation over the north of Australia during the wet season, and this is found to be related to the number of bursts they produce. The seasonal cycle of bursts is found to be poor in most of the models evaluated. It is known that northern Australian wet season bursts are often associated with midlatitude Rossby wave packets and their surface signature as they are refracted toward the tropics. The relationship between midlatitude waves and the initiation of wet season bursts is simulated well by the models evaluated. Another well-documented influence on the initiation of northern Australian wet season bursts is the Madden–Julian oscillation (MJO). No model adequately simulated the tropical outgoing longwave radiation temporal–spatial patterns seen in the reanalysis-derived OLR. This result suggests that the connection between the MJO and the initiation of northern Australian wet season bursts in models is poor.
Abstract
The initiation of northern Australian monsoon rainfall bursts is accompanied by an increase in cyclonic circulation in the monsoon region. This study shows that the change in circulation at the start of the composite rainfall burst is predominantly influenced by midlatitude frontlike features. By exploiting the relationship between circulation tendency and the convergence of absolute vorticity flux, the circulation changes accompanying the initiation of Australian monsoon bursts is investigated. Moisture flux convergence is found to be proportional to the circulation changes in the monsoon region. Using a composite analysis it is shown that absolute vorticity fluxes through the southern boundary are by far the most important influence on monsoon burst circulation changes, with only one-third of events more closely related to other influences including the Madden–Julian oscillation. This is shown to be true throughout the wet season.
Abstract
The initiation of northern Australian monsoon rainfall bursts is accompanied by an increase in cyclonic circulation in the monsoon region. This study shows that the change in circulation at the start of the composite rainfall burst is predominantly influenced by midlatitude frontlike features. By exploiting the relationship between circulation tendency and the convergence of absolute vorticity flux, the circulation changes accompanying the initiation of Australian monsoon bursts is investigated. Moisture flux convergence is found to be proportional to the circulation changes in the monsoon region. Using a composite analysis it is shown that absolute vorticity fluxes through the southern boundary are by far the most important influence on monsoon burst circulation changes, with only one-third of events more closely related to other influences including the Madden–Julian oscillation. This is shown to be true throughout the wet season.
Abstract
Precipitation is often organized along coherent lines of low-level convergence, which at longer time and space scales form well-known convergence zones over the world’s oceans. Here, an automated, objective method is used to identify instantaneous low-level convergence lines in reanalysis data and calculate their frequency for the period 1979–2013. Identified convergence lines are combined with precipitation observations to assess the extent to which precipitation around the globe is associated with convergence lines in the lower troposphere. It is shown that a large percentage of precipitation (between 65% and 90%) over the tropical oceans is associated with such convergence lines, with large regional variations of up to 30% throughout the year, especially in the eastern Pacific and Atlantic Oceans. Over land, the annual-mean proportion of precipitation associated with convergence lines ranges between 30% and 60%, and the lowest proportions (less than 15%) associated with convergence lines occur on the eastern flank of the subtropical highs. Overall, much greater precipitation is associated with long coherent lines (greater than 300 km in length) than with shorter fragmented lines (less than 300 km), and the majority of precipitation associated with shorter lines occurs over land. The proportion of precipitation not associated with any convergence line primarily occurs where both precipitation and frequency of convergence lines are low. The high temporal and spatial resolution of the climatology constructed also enables an examination of the diurnal cycle in the relationship between convergence lines and precipitation. Here an example is provided over the tropical Maritime Continent region.
Abstract
Precipitation is often organized along coherent lines of low-level convergence, which at longer time and space scales form well-known convergence zones over the world’s oceans. Here, an automated, objective method is used to identify instantaneous low-level convergence lines in reanalysis data and calculate their frequency for the period 1979–2013. Identified convergence lines are combined with precipitation observations to assess the extent to which precipitation around the globe is associated with convergence lines in the lower troposphere. It is shown that a large percentage of precipitation (between 65% and 90%) over the tropical oceans is associated with such convergence lines, with large regional variations of up to 30% throughout the year, especially in the eastern Pacific and Atlantic Oceans. Over land, the annual-mean proportion of precipitation associated with convergence lines ranges between 30% and 60%, and the lowest proportions (less than 15%) associated with convergence lines occur on the eastern flank of the subtropical highs. Overall, much greater precipitation is associated with long coherent lines (greater than 300 km in length) than with shorter fragmented lines (less than 300 km), and the majority of precipitation associated with shorter lines occurs over land. The proportion of precipitation not associated with any convergence line primarily occurs where both precipitation and frequency of convergence lines are low. The high temporal and spatial resolution of the climatology constructed also enables an examination of the diurnal cycle in the relationship between convergence lines and precipitation. Here an example is provided over the tropical Maritime Continent region.
Abstract
Observational data of rainfall from a rain radar in Darwin, Australia, are combined with data defining the large-scale dynamic and thermodynamic state of the atmosphere around Darwin to develop a multicloud model based on a stochastic method using conditional Markov chains. The authors assign the radar data to clear sky, moderate congestus, strong congestus, deep convective, or stratiform clouds and estimate transition probabilities used by Markov chains that switch between the cloud types and yield cloud-type area fractions. Cross-correlation analysis shows that the mean vertical velocity is an important indicator of deep convection. Further, it is shown that, if conditioned on the mean vertical velocity, the Markov chains produce fractions comparable to the observations. The stochastic nature of the approach turns out to be essential for the correct production of area fractions. The stochastic multicloud model can easily be coupled to existing moist convection parameterization schemes used in general circulation models.
Abstract
Observational data of rainfall from a rain radar in Darwin, Australia, are combined with data defining the large-scale dynamic and thermodynamic state of the atmosphere around Darwin to develop a multicloud model based on a stochastic method using conditional Markov chains. The authors assign the radar data to clear sky, moderate congestus, strong congestus, deep convective, or stratiform clouds and estimate transition probabilities used by Markov chains that switch between the cloud types and yield cloud-type area fractions. Cross-correlation analysis shows that the mean vertical velocity is an important indicator of deep convection. Further, it is shown that, if conditioned on the mean vertical velocity, the Markov chains produce fractions comparable to the observations. The stochastic nature of the approach turns out to be essential for the correct production of area fractions. The stochastic multicloud model can easily be coupled to existing moist convection parameterization schemes used in general circulation models.
Abstract
Cumulus parameterizations in weather and climate models frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by convection in a model grid box and the vertical velocity in cumulus clouds. However, vertical velocities are difficult to observe on GCM scales, making the evaluation of mass-flux schemes difficult. Here, the authors combine high-temporal-resolution observations of in-cloud vertical velocities derived from a pair of wind profilers over two wet seasons at Darwin with physical properties of precipitating clouds [cloud-top heights (CTH), convective–stratiform classification] derived from the Darwin C-band polarimetric radar to provide estimates of cumulus mass flux and its constituents. The length of this dataset allows for investigations of the contributions from different cumulus cloud types—namely, congestus, deep, and overshooting convection—to the overall mass flux and of the influence of large-scale conditions on mass flux. The authors found that mass flux was dominated by updrafts and, in particular, the updraft area fraction, with updraft vertical velocity playing a secondary role. The updraft vertical velocities peaked above 10 km where both the updraft area fractions and air densities were small, resulting in a marginal effect on mass-flux values. Downdraft area fractions are much smaller and velocities are much weaker than those in updrafts. The area fraction responded strongly to changes in midlevel large-scale vertical motion and convective inhibition (CIN). In contrast, changes in the lower-tropospheric relative humidity and convective available potential energy (CAPE) strongly modulate in-cloud vertical velocities but have moderate impacts on area fractions. Although average mass flux is found to increase with increasing CTH, it is the environmental conditions that seem to dictate the magnitude of mass flux produced by convection through a combination of effects on area fraction and velocity.
Abstract
Cumulus parameterizations in weather and climate models frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by convection in a model grid box and the vertical velocity in cumulus clouds. However, vertical velocities are difficult to observe on GCM scales, making the evaluation of mass-flux schemes difficult. Here, the authors combine high-temporal-resolution observations of in-cloud vertical velocities derived from a pair of wind profilers over two wet seasons at Darwin with physical properties of precipitating clouds [cloud-top heights (CTH), convective–stratiform classification] derived from the Darwin C-band polarimetric radar to provide estimates of cumulus mass flux and its constituents. The length of this dataset allows for investigations of the contributions from different cumulus cloud types—namely, congestus, deep, and overshooting convection—to the overall mass flux and of the influence of large-scale conditions on mass flux. The authors found that mass flux was dominated by updrafts and, in particular, the updraft area fraction, with updraft vertical velocity playing a secondary role. The updraft vertical velocities peaked above 10 km where both the updraft area fractions and air densities were small, resulting in a marginal effect on mass-flux values. Downdraft area fractions are much smaller and velocities are much weaker than those in updrafts. The area fraction responded strongly to changes in midlevel large-scale vertical motion and convective inhibition (CIN). In contrast, changes in the lower-tropospheric relative humidity and convective available potential energy (CAPE) strongly modulate in-cloud vertical velocities but have moderate impacts on area fractions. Although average mass flux is found to increase with increasing CTH, it is the environmental conditions that seem to dictate the magnitude of mass flux produced by convection through a combination of effects on area fraction and velocity.
Abstract
A deficit of shortwave cloud forcing over the Southern Ocean is persistent in many global climate models. Cloud regimes have been widely used in model evaluation studies to make a process-oriented diagnosis of cloud parameterization errors, but cloud regimes have some limitations in resolving both observed and simulated cloud behavior. A hybrid methodology is developed for identifying cloud regimes from observed and simulated cloud simultaneously.
Through this methodology, 11 hybrid cloud regimes are identified in the ACCESS1.3 model for the high-latitude Southern Ocean. The hybrid cloud regimes resolve the features of observed cloud and characterize cloud errors in the model. The simulated properties of the hybrid cloud regimes, and their occurrence over the Southern Ocean and in the context of extratropical cyclones, are evaluated, and their contributions to the shortwave radiation errors are quantified.
Three errors are identified: an overall deficit of cloud fraction, a tendency toward optically thin low and midtopped cloud, and an absence of a shallow frontal-type cloud at high latitudes and in the warm fronts of extratropical cyclones.
To demonstrate the utility of the hybrid cloud regimes for the evaluation of changes to the model, the effects of selected changes to the model microphysics are investigated.
Abstract
A deficit of shortwave cloud forcing over the Southern Ocean is persistent in many global climate models. Cloud regimes have been widely used in model evaluation studies to make a process-oriented diagnosis of cloud parameterization errors, but cloud regimes have some limitations in resolving both observed and simulated cloud behavior. A hybrid methodology is developed for identifying cloud regimes from observed and simulated cloud simultaneously.
Through this methodology, 11 hybrid cloud regimes are identified in the ACCESS1.3 model for the high-latitude Southern Ocean. The hybrid cloud regimes resolve the features of observed cloud and characterize cloud errors in the model. The simulated properties of the hybrid cloud regimes, and their occurrence over the Southern Ocean and in the context of extratropical cyclones, are evaluated, and their contributions to the shortwave radiation errors are quantified.
Three errors are identified: an overall deficit of cloud fraction, a tendency toward optically thin low and midtopped cloud, and an absence of a shallow frontal-type cloud at high latitudes and in the warm fronts of extratropical cyclones.
To demonstrate the utility of the hybrid cloud regimes for the evaluation of changes to the model, the effects of selected changes to the model microphysics are investigated.
Abstract
Clouds over the Southern Ocean are often poorly represented by climate models, but they make a significant contribution to the top-of-atmosphere (TOA) radiation balance, particularly in the shortwave portion of the energy spectrum. This study seeks to better quantify the organization and structure of Southern Hemisphere midlatitude clouds by combining measurements from active and passive satellite-based datasets. Geostationary and polar-orbiter satellite data from the International Satellite Cloud Climatology Project (ISCCP) are used to quantify large-scale, recurring modes of cloudiness, and active observations from CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to examine vertical structure, radiative heating rates, and precipitation associated with these clouds. It is found that cloud systems are organized into eight distinct regimes and that ISCCP overestimates the midlevel cloudiness of these regimes. All regimes contain a relatively high occurrence of low cloud, with 79% of all cloud layers observed having tops below 3 km, but multiple-layered clouds systems are present in approximately 34% of observed cloud profiles. The spatial distribution of regimes varies according to season, with cloud systems being geometrically thicker, on average, during the austral winter. Those regimes found to be most closely associated with midlatitude cyclones produce precipitation the most frequently, although drizzle is extremely common in low-cloud regimes. The regimes associated with cyclones have the highest in-regime shortwave cloud radiative effect at the TOA, but the low-cloud regimes, by virtue of their high frequency of occurrence over the oceans, dominate both TOA and surface shortwave effects in this region as a whole.
Abstract
Clouds over the Southern Ocean are often poorly represented by climate models, but they make a significant contribution to the top-of-atmosphere (TOA) radiation balance, particularly in the shortwave portion of the energy spectrum. This study seeks to better quantify the organization and structure of Southern Hemisphere midlatitude clouds by combining measurements from active and passive satellite-based datasets. Geostationary and polar-orbiter satellite data from the International Satellite Cloud Climatology Project (ISCCP) are used to quantify large-scale, recurring modes of cloudiness, and active observations from CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to examine vertical structure, radiative heating rates, and precipitation associated with these clouds. It is found that cloud systems are organized into eight distinct regimes and that ISCCP overestimates the midlevel cloudiness of these regimes. All regimes contain a relatively high occurrence of low cloud, with 79% of all cloud layers observed having tops below 3 km, but multiple-layered clouds systems are present in approximately 34% of observed cloud profiles. The spatial distribution of regimes varies according to season, with cloud systems being geometrically thicker, on average, during the austral winter. Those regimes found to be most closely associated with midlatitude cyclones produce precipitation the most frequently, although drizzle is extremely common in low-cloud regimes. The regimes associated with cyclones have the highest in-regime shortwave cloud radiative effect at the TOA, but the low-cloud regimes, by virtue of their high frequency of occurrence over the oceans, dominate both TOA and surface shortwave effects in this region as a whole.
Abstract
A robust and computationally efficient object tracking algorithm is developed by incorporating various tracking techniques. Physical properties of the objects, such as brightness temperature or reflectivity, are not considered. Therefore, the algorithm is adaptable for tracking convection-like features in simulated data and remotely sensed two-dimensional images. In this algorithm, a first guess of the motion, estimated using the Fourier phase shift, is used to predict the candidates for matching. A disparity score is computed for each target–candidate pair. The disparity also incorporates overlapping criteria in the case of large objects. Then the Hungarian method is applied to identify the best pairs by minimizing the global disparity. The high-disparity pairs are unmatched, and their target and candidate are declared expired and newly initiated objects, respectively. They are tested for merger and split on the basis of their size and overlap with the other objects. The sensitivity of track duration is shown for different disparity and size thresholds. The paper highlights the algorithm’s ability to study convective life cycles using radar and simulated data over Darwin, Australia. The algorithm skillfully tracks individual convective cells (a few pixels in size) and large convective systems. The duration of tracks and cell size are found to be lognormally distributed over Darwin. The evolution of size and precipitation types of isolated convective cells is presented in the Lagrangian perspective. This algorithm is part of a vision for a modular platform [viz., TINT is not TITAN (TINT) and Tracking and Object-Based Analysis of Clouds (tobac)] that will evolve into a sustainable choice to analyze atmospheric features.
Abstract
A robust and computationally efficient object tracking algorithm is developed by incorporating various tracking techniques. Physical properties of the objects, such as brightness temperature or reflectivity, are not considered. Therefore, the algorithm is adaptable for tracking convection-like features in simulated data and remotely sensed two-dimensional images. In this algorithm, a first guess of the motion, estimated using the Fourier phase shift, is used to predict the candidates for matching. A disparity score is computed for each target–candidate pair. The disparity also incorporates overlapping criteria in the case of large objects. Then the Hungarian method is applied to identify the best pairs by minimizing the global disparity. The high-disparity pairs are unmatched, and their target and candidate are declared expired and newly initiated objects, respectively. They are tested for merger and split on the basis of their size and overlap with the other objects. The sensitivity of track duration is shown for different disparity and size thresholds. The paper highlights the algorithm’s ability to study convective life cycles using radar and simulated data over Darwin, Australia. The algorithm skillfully tracks individual convective cells (a few pixels in size) and large convective systems. The duration of tracks and cell size are found to be lognormally distributed over Darwin. The evolution of size and precipitation types of isolated convective cells is presented in the Lagrangian perspective. This algorithm is part of a vision for a modular platform [viz., TINT is not TITAN (TINT) and Tracking and Object-Based Analysis of Clouds (tobac)] that will evolve into a sustainable choice to analyze atmospheric features.
Abstract
A clustering methodology is applied to cloud optical depth (τ)–cloud top pressure (TAU-PC) histograms from the new 1° resolution ISCCP-H dataset to derive an updated global weather state (WS) dataset. Then, TAU-PC histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties to evaluate model cloud, radiation, and precipitation properties in the context of the weather states. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower-resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H weather states shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.
Abstract
A clustering methodology is applied to cloud optical depth (τ)–cloud top pressure (TAU-PC) histograms from the new 1° resolution ISCCP-H dataset to derive an updated global weather state (WS) dataset. Then, TAU-PC histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties to evaluate model cloud, radiation, and precipitation properties in the context of the weather states. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower-resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H weather states shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.
