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Marine stratocumuli are the most dominant cloud type by area coverage in the Southern Ocean (SO). They can be divided into different self-organized cellular morphological regimes known as open and closed mesoscale-cellular convective (MCC) clouds. Open and closed cells are the two most frequent types of organizational regimes in the SO. Using the liDAR-raDAR (DARDAR) version 2 retrievals, we quantify 59 % of all MCC clouds in this region as mixed-phase clouds (MPCs) during a 4-year time period from 2007 to 2010. The net radiative effect of SO MCC clouds is governed by changes in cloud albedo. Both cloud morphology and phase have previously been shown to impact cloud albedo individually, but their interactions and their combined impact on cloud albedo remain unclear.
Here, we investigate the relationships between cloud phase, organizational patterns, and their differences regarding their cloud radiative properties in the SO. The mixed-phase fraction, which is defined as the number of MPCs divided by the sum of MPC and supercooled liquid cloud (SLC) pixels, of all MCC clouds at a given cloud-top temperature (CTT) varies considerably between austral summer and winter. We further find that seasonal changes in cloud phase at a given CTT across all latitudes are largely independent of cloud morphology and are thus seemingly constrained by other external factors. Overall, our results show a stronger dependence of cloud phase on cloud-top height (CTH) than CTT for clouds below 2.5 km in altitude.
Preconditioning through ice-phase processes in MPCs has been observed to accelerate individual closed-to-open cell transitions in extratropical stratocumuli. The hypothesis of preconditioning has been further substantiated in large-eddy simulations of open and closed MPCs. In this study, we do not find preconditioning to primarily impact climatological cloud morphology statistics in the SO. Meanwhile, in-cloud albedo analysis reveals stronger changes in open and closed cell albedo in SLCs than in MPCs. In particular, few optically thick (cloud optical thickness >10) open cell stratocumuli are characterized as ice-free SLCs. These differences in in-cloud albedo are found to alter the cloud radiative effect in the SO by 21 to 39 W m−2 depending on season and cloud phase.
Seismic arrays provide tools for the localization of events without clear phases or events outside the network, where the station coverage prohibits classical localization techniques. Beam forming allows the determination of the direction (back azimuth) and horizontal (apparent) velocity of an incoming wavefront. Here we combine multiple arrays to retrieve event epicentres from the area of intersecting beams without the need to specify a velocity model. The analysis is performed in the time domain, which allows selecting a relatively narrow time window around the phase of interest while preserving frequency bandwidth. This technique is applied to earthquakes and hybrid events in the region of Fogo and Brava, two islands of the southern chain of the Cape Verde archipelago. The results show that the earthquakes mainly originate near Brava, whereas the hybrid events are located on Fogo. By multiple-event beam stacking we are able to further constrain the epicentral locations of the hybrid events in the northwestern part of the collapse scar of Fogo. In previous studies, these events were attributed to shallow hydrothermal processes. However, we obtain relatively high apparent velocities at the arrays, pointing to either deeper sources or complex ray paths. For a better understanding of possible errors of the multi-array analysis, we also compare slowness values obtained from the array analysis with those derived from earthquake locations from classical (local network) localizations. In general, the results agree well. Nevertheless, some systematic deviations of the array-derived back-azimuth and slowness values occur that can be quantified for certain event locations.
Seismic arrays provide tools for the localization of events without clear phases or events outside the network, where the station coverage prohibits classical localization techniques. Beam forming allows the determination of the direction (back azimuth) and horizontal (apparent) velocity of an incoming wavefront. Here we combine multiple arrays to retrieve event epicentres from the area of intersecting beams without the need to specify a velocity model. The analysis is performed in the time domain, which allows selecting a relatively narrow time window around the phase of interest while preserving frequency bandwidth. This technique is applied to earthquakes and hybrid events in the region of Fogo and Brava, two islands of the southern chain of the Cape Verde archipelago. The results show that the earthquakes mainly originate near Brava, whereas the hybrid events are located on Fogo. By multiple-event beam stacking we are able to further constrain the epicentral locations of the hybrid events in the northwestern part of the collapse scar of Fogo. In previous studies, these events were attributed to shallow hydrothermal processes. However, we obtain relatively high apparent velocities at the arrays, pointing to either deeper sources or complex ray paths. For a better understanding of possible errors of the multi-array analysis, we also compare slowness values obtained from the array analysis with those derived from earthquake locations from classical (local network) localizations. In general, the results agree well. Nevertheless, some systematic deviations of the array-derived back-azimuth and slowness values occur that can be quantified for certain event locations.
We evaluate the influence of a forest parametrization on the simulation of the boundary layer flow over moderate complex terrain in the context of the Perdigão 2017 field campaign. The numerical simulations are performed using the Weather Research and Forecasting model in large eddy simulation mode (WRF-LES). The short-term, high-resolution (40 m horizontal grid spacing) and long-term (200 m horizontal grid spacing) WRF-LES are evaluated for an integration time of 12 h and 1.5 months, respectively, with and without forest parameterization. The short-term simulations focus on low-level jet events over the valley, while the long-term simulations cover the whole intensive observation period (IOP) of the field campaign. The results are validated using lidar and meteorological tower observations. The mean diurnal cycle during the IOP shows a significant improvement of the along-valley wind speed and the wind direction when using the forest parametrization. However, the drag imposed by the parametrization results in an underestimation of the cross-valley wind speed, which can be attributed to a poor representation of the land surface characteristics. The evaluation of the high-resolution WRF-LES shows a positive influence of the forest parametrization on the simulated winds in the first 500 m above the surface.
We evaluate the influence of a forest parametrization on the simulation of the boundary layer flow over moderate complex terrain in the context of the Perdigão 2017 field campaign. The numerical simulations are performed using the Weather Research and Forecasting model in large eddy simulation mode (WRF-LES). The short-term, high-resolution (40 m horizontal grid spacing) and long-term (200 m horizontal grid spacing) WRF-LES are evaluated for an integration time of 12 h and 1.5 months, respectively, with and without forest parameterization. The short-term simulations focus on low-level jet events over the valley, while the long-term simulations cover the whole intensive observation period (IOP) of the field campaign. The results are validated using lidar and meteorological tower observations. The mean diurnal cycle during the IOP shows a significant improvement of the along-valley wind speed and the wind direction when using the forest parametrization. However, the drag imposed by the parametrization results in an underestimation of the cross-valley wind speed, which can be attributed to a poor representation of the land surface characteristics. The evaluation of the high-resolution WRF-LES shows a positive influence of the forest parametrization on the simulated winds in the first 500 m above the surface.
Marine stratocumuli are the most dominant cloud type by area coverage in the Southern Ocean (SO). They can be divided into different self-organized cellular morphological regimes known as open and closed mesoscale-cellular convective (MCC) clouds. Open and closed cells are the two most frequent types of organizational regimes in the SO. Using the liDAR-raDAR (DARDAR) version 2 retrievals, we quantify 59 % of all MCC clouds in this region as mixed-phase clouds (MPCs) during a 4-year time period from 2007 to 2010. The net radiative effect of SO MCC clouds is governed by changes in cloud albedo. Both cloud morphology and phase have previously been shown to impact cloud albedo individually, but their interactions and their combined impact on cloud albedo remain unclear.
Here, we investigate the relationships between cloud phase, organizational patterns, and their differences regarding their cloud radiative properties in the SO. The mixed-phase fraction, which is defined as the number of MPCs divided by the sum of MPC and supercooled liquid cloud (SLC) pixels, of all MCC clouds at a given cloud-top temperature (CTT) varies considerably between austral summer and winter. We further find that seasonal changes in cloud phase at a given CTT across all latitudes are largely independent of cloud morphology and are thus seemingly constrained by other external factors. Overall, our results show a stronger dependence of cloud phase on cloud-top height (CTH) than CTT for clouds below 2.5 km in altitude.
Preconditioning through ice-phase processes in MPCs has been observed to accelerate individual closed-to-open cell transitions in extratropical stratocumuli. The hypothesis of preconditioning has been further substantiated in large-eddy simulations of open and closed MPCs. In this study, we do not find preconditioning to primarily impact climatological cloud morphology statistics in the SO. Meanwhile, in-cloud albedo analysis reveals stronger changes in open and closed cell albedo in SLCs than in MPCs. In particular, few optically thick (cloud optical thickness >10) open cell stratocumuli are characterized as ice-free SLCs. These differences in in-cloud albedo are found to alter the cloud radiative effect in the SO by 21 to 39 W m−2 depending on season and cloud phase.
Bilder stellen auf vielfältige Weise Bezüge zu Räumen und raumbezogenen Praktiken her. Als humangeographische Forschungsmethode fragt die Bildanalyse nach der Wirklichkeit und der Wirkungsweise von Bildern im Verhältnis von Gesellschaft und Raum. Der Beitrag führt fachlich und methodisch in die humangeographische Bildanalyse ein und diskutiert ihren Beitrag zur geographischen Bildungsforschung im Hinblick auf die Vermittlung von Bild(lese)kompetenz und den mündigen Umgang mit medialer Bildlichkeit. Als Unterrichtsbeispiel wird eine Analyse visuellen Materials für eine differenzierte Auseinandersetzung mit dem Problem Müll vorgestellt.
Surface temperature is a fundamental parameter of Earth’s climate. Its evolution through time is commonly reconstructed using the oxygen isotope and the clumped isotope compositions of carbonate archives. However, reaction kinetics involved in the precipitation of carbonates can introduce inaccuracies in the derived temperatures. Here, we show that dual clumped isotope analyses, i.e., simultaneous ∆47 and ∆48 measurements on the single carbonate phase, can identify the origin and quantify the extent of these kinetic biases. Our results verify theoretical predictions and evidence that the isotopic disequilibrium commonly observed in speleothems and scleractinian coral skeletons is inherited from the dissolved inorganic carbon pool of their parent solutions. Further, we show that dual clumped isotope thermometry can achieve reliable palaeotemperature reconstructions, devoid of kinetic bias. Analysis of a belemnite rostrum implies that it precipitated near isotopic equilibrium and confirms the warmer-than-present temperatures during the Early Cretaceous at southern high latitudes.
Particulate matter (PM) largely consists of secondary organic aerosol (SOA) that is formed via oxidation of biogenic and anthropogenic volatile organic compounds (VOCs). Unambiguous identification of SOA molecules and their assignment to their precursor vapors is a challenge that has so far only succeeded for a few SOA marker compounds, which are now well characterized and (partly) available as authentic standards. In this work, we resolve the complex composition of SOA by a top-down approach based on a newly created aerosolomics database, which is fed by non-target analysis results of filter samples from oxidation flow reactor experiments. We investigated the oxidation products from the five biogenic VOCs α-pinene, β-pinene, limonene, 3-carene, and trans-caryophyllene and from the four anthropogenic VOCs toluene, o-xylene, 1,2,4-trimethylbenzene, and naphthalene. Using ultra-high performance liquid chromatography coupled to a high-resolution (Orbitrap) mass spectrometer, we determine the molecular formula of 596 chromatographically separated compounds based on exact mass and isotopic pattern. We utilize retention time and fragmentation mass spectra as a basis for unambiguous attribution of the oxidation products to their parent VOCs. Based on the molecular-resolved application of the database, we are able to assign roughly half of the total signal of oxygenated hydrocarbons in ambient suburban PM2.5 to one of the nine studied VOCs. The application of the database enabled us to interpret the appearance of diurnal compound clusters that are formed by different oxidation processes. Furthermore, the application of a hierarchical cluster analysis (HCA) on the same set of filter samples enabled us to identify compound clusters that depend on sulfur dioxide mixing ratio and temperature. This study demonstrates how aerosolomics tools (database and HCA) applied on PM filter samples can improve our understanding of SOA sources, their formation pathways, and temperature-driven partitioning of SOA compounds.
Particulate matter (PM) largely consists of secondary organic aerosol (SOA) that is formed via oxidation of biogenic and anthropogenic volatile organic compounds (VOCs). Unambiguous identification of SOA molecules and their assignment to their precursor vapors are challenges that have so far only succeeded for a few SOA marker compounds, which are now well characterized and (partly) available as authentic standards. In this work, we resolve the complex composition of SOA by means of a top-down approach based on the newly created Aerosolomics database, which is fed by non-target analysis results of filter samples from oxidation flow reactor experiments. We investigated the oxidation products from the five biogenic VOCs α-pinene, β-pinene, limonene, 3-carene, and trans-caryophyllene and from the four anthropogenic VOCs toluene, o-xylene, 1,2,4-trimethylbenzene, and naphthalene. Using ultrahigh-performance liquid chromatography coupled to a high-resolution (Orbitrap) mass spectrometer, we determine the molecular formula of 596 chromatographically separated compounds based on exact mass and isotopic pattern. We utilize retention time and fragmentation mass spectra as a basis for unambiguous attribution of the oxidation products to their parent VOCs. Based on the molecular-resolved application of the database, we are able to assign roughly half of the total signal of oxygenated hydrocarbons in ambient suburban PM2.5 to one of the nine studied VOCs. The application of the database enabled us to interpret the appearance of diurnal compound clusters that are formed by different oxidation processes. Furthermore, by performing a hierarchical cluster analysis (HCA) on the same set of filter samples, we identified compound clusters that depend on sulfur dioxide mixing ratio and temperature. This study demonstrates how Aerosolomics tools (database and HCA) applied to PM filter samples can improve our understanding of SOA sources, their formation pathways, and temperature-driven partitioning of SOA compounds.