ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2022-10-06
    Description: Prominent excursions in the number of cosmogenic nuclides (e.g., 10Be) around 774 CE/775 document the most severe solar proton event (SPE) throughout the Holocene. Its manifestation in ice cores is valuable for geochronology, but also for solar‐terrestrial physics and climate modeling. Using the ECHAM/MESSy Atmospheric Chemistry (EMAC) climate model in combination with the Warning System for Aviation Exposure to SEP (WASAVIES), we investigate the transport, mixing, and deposition of the cosmogenic nuclide 10Be produced by the 774 CE/775 SPE. By comparing the model results to the reconstructed 10Be time series from four ice core records, we study the atmospheric pathways of 10Be from its stratospheric source to its sink at Earth's surface. The reconstructed post‐SPE evolution of the 10Be surface fluxes at the ice core sites is well captured by the model. The downward transport of the 10Be atoms is controlled by the Brewer‐Dobson circulation in the stratosphere and cross‐tropopause transport via tropopause folds or large‐scale sinking. Clear hemispheric differences in the transport and deposition processes are identified. In both polar regions the 10Be surface fluxes peak in summertime, with a larger influence of wet deposition on the seasonal 10Be surface flux in Greenland than in Antarctica. Differences in the peak 10Be surface flux following the 774 CE/775 SPE at the drilling sites are explained by specific meteorological conditions depending on the geographic locations of the sites.
    Description: Plain Language Summary: During large solar storms, high energy particles are hurled with enormous force toward Earth by the Sun. As these particles collide with atmospheric constituents (such as oxygen or nitrogen) unique nuclides of cosmogenic origin are formed in the higher atmosphere. From there they are transported downwards and finally precipitate at the surface due to different sink processes. Their imprints can be conserved over thousands of years within natural archives, such as ice cores or tree rings. Analysis of these natural archives around the globe indicates that the strongest solar storm over the last 10.000 years happened around 774 CE/775. This event is estimated to have been up to two orders of magnitude stronger, than the strongest known events documented for the satellite era. In this study, we model and analyze the transport and deposition of the cosmogenic nuclides produced by the extreme 774 CE/775 event, by applying a new experimental setup. Our results might help to interpret the fingerprints of historical extreme events with respect to the prevailing atmospheric conditions.
    Description: Key Points: The modeled transport and deposition of the cosmogenic nuclide10Be produced by the 774/775 solar proton event was compared to 10Be ice core records. Hemispheric differences in stratospheric and cross‐tropopause transport, and deposition were identified, with polar summertime maxima of 10Be surface flux. Differences in reconstructed10Be surface fluxes are explained by the local ratio of wet to dry deposition maximizing in the summertime.
    Description: MEXT Japan Society for the Promotion of Science http://dx.doi.org/10.13039/501100001691
    Keywords: ddc:551.5
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2022-09-22
    Description: February‐March 2020 was marked by highly anomalous large‐scale circulations in the Northern extratropical troposphere and stratosphere. The Atlantic jet reached extreme strength, linked to some of the strongest and most persistent positive values of the Arctic Oscillation index on record, which provided conditions for extreme windstorms hitting Europe. Likewise, the stratospheric polar vortex reached extreme strength that persisted for an unusually long period. Past research indicated that such circulation extremes occurring throughout the troposphere‐stratosphere system are dynamically coupled, although the nature of this coupling is still not fully understood and generally difficult to quantify. We employ sets of numerical ensemble simulations to statistically characterize the mutual coupling of the early 2020 extremes. We find the extreme vortex strength to be linked to the reflection of upward propagating planetary waves and the occurrence of this reflection to be sensitive to the details of the vortex structure. Our results show an overall robust coupling between tropospheric and stratospheric anomalies: ensemble members with polar vortex exceeding a certain strength tend to exhibit a stronger tropospheric jet and vice versa. Moreover, members exhibiting a breakdown of the stratospheric circulation (e.g., sudden stratospheric warming) tend to lack periods of persistently enhanced tropospheric circulation. Despite indications for vertical coupling, our simulations underline the role of internal variability within each atmospheric layer. The circulation extremes during early 2020 may be viewed as resulting from a fortuitous alignment of dynamical evolutions within the troposphere and stratosphere, aided by each layer's modification of the other layer's boundary condition.
    Description: Key Points Large‐ensemble simulations are needed to fully characterize coupled extremes in the polar vortex and tropospheric jet in early 2020. Details of the vortex structure play an important role in promoting either reflection or dissipation of upward propagating waves 1 and/or 2. Modulation of lowermost stratospheric circulation from above and below facilitates co‐evolution of tropospheric and stratospheric extremes.
    Description: Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659
    Description: https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5
    Description: https://doi.org/10.5282/ubm/data.281
    Description: https://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/ao.shtml
    Keywords: ddc:551.5
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2022-12-06
    Description: Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we use Variational Encoder Decoder structures (VED), a non‐linear dimensionality reduction technique, to learn and understand convective processes in an aquaplanet superparameterized climate model simulation, where deep convective processes are simulated explicitly. We show that similar to previous deep learning studies based on feed‐forward neural nets, the VED is capable of learning and accurately reproducing convective processes. In contrast to past work, we show this can be achieved by compressing the original information into only five latent nodes. As a result, the VED can be used to understand convective processes and delineate modes of convection through the exploration of its latent dimensions. A close investigation of the latent space enables the identification of different convective regimes: (a) stable conditions are clearly distinguished from deep convection with low outgoing longwave radiation and strong precipitation; (b) high optically thin cirrus‐like clouds are separated from low optically thick cumulus clouds; and (c) shallow convective processes are associated with large‐scale moisture content and surface diabatic heating. Our results demonstrate that VEDs can accurately represent convective processes in climate models, while enabling interpretability and better understanding of sub‐grid‐scale physical processes, paving the way to increasingly interpretable machine learning parameterizations with promising generative properties.
    Description: Plain Language Summary: Deep neural nets are hard to interpret due to their hundred thousand or million trainable parameters without further postprocessing. We demonstrate in this paper the usefulness of a network type that is designed to drastically reduce this high dimensional information in a lower‐dimensional space to enhance the interpretability of predictions compared to regular deep neural nets. Our approach is, on the one hand, able to reproduce small‐scale cloud related processes in the atmosphere learned from a physical model that simulates these processes skillfully. On the other hand, our network allows us to identify key features of different cloud types in the lower‐dimensional space. Additionally, the lower‐order manifold separates tropical samples from polar ones with a remarkable skill. Overall, our approach has the potential to boost our understanding of various complex processes in Earth System science.
    Description: Key Points: A Variational Encoder Decoder (VED) can predict sub‐grid‐scale thermodynamics from the coarse‐scale climate state. The VED's latent space can distinguish convective regimes, including shallow/deep/no convection. The VED's latent space reveals the main sources of convective predictability at different latitudes.
    Description: EC ERC HORIZON EUROPE European Research Council http://dx.doi.org/10.13039/100019180
    Description: Columbia sub‐award 1
    Description: Advanced Research Projects Agency - Energy http://dx.doi.org/10.13039/100006133
    Description: Deutsches Klimarechenzentrum http://dx.doi.org/10.13039/100018730
    Description: National Science Foundation Science and Technology Center Learning the Earth with Artificial intelligence and Physics
    Keywords: ddc:551.5 ; machine learning ; generative deep learning ; convection ; parameterization ; explainable artificial intelligence ; dimensionality reduction
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2023-01-19
    Description: Europe has been affected by record‐breaking heat waves in recent decades. Using station data and a gridded reanalysis as input, four commonly used heat wave indices, the heat wave magnitude index daily (HWMId), excess heat factor (EHF), wet‐bulb globe temperature (WBGT) and universal thermal climate index (UTCI), are computed. The extremeness of historical European heat waves between 1979 and 2019 using the four indices and different metrics is ranked. A normalisation to enable the comparison between the four indices is introduced. Additionally, a method to quantify the influence of the input parameters on heat wave magnitude is introduced. The spatio‐temporal behaviour of heat waves is assessed by spatial–temporal tracking. The areal extent, large‐scale intensity and duration are visualized using bubble plots. As expected, temperature explains the largest variance in all indices, but humidity is nearly as important in WBGT and wind speed plays a substantial role in UTCI. While the 2010 Russian heat wave is by far the most extreme event in duration and intensity in all normalized indices, the 2018 heat wave was comparable in size for EHF, WBGT and UTCI. Interestingly, the well‐known 2003 central European heat wave was only the fifth and tenth strongest in cumulative intensity in WBGT and UTCI, respectively. The June and July 2019 heat waves were very intense, but short‐lived, thus not belonging to the top heat waves in Europe when duration and areal extent are taken into account. Overall, the proposed normalized indices and the multi‐metric assessment of large‐scale heat waves allow for a more robust description of their extremeness and will be helpful to assess heat waves worldwide and in climate projections.
    Description: Europe has been affected by record‐breaking heat waves in recent decades. Using station data and a gridded reanalysis, the extremeness of European heat waves between 1979 and 2019 is ranked using four indices: heat wave magnitude index daily (HWMId), excess heat factor (EHF), wet‐bulb globe temperature (WBGT) and universal thermal climate index (UTCI). In order to assess heatwaves worldwide and in climate projections, the spatial extent, large‐scale intensity and duration of heatwaves are visualized using bubble plots.
    Description: AXA Research Fund http://dx.doi.org/10.13039/501100001961
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: Karlsruher Institut für Technologie http://dx.doi.org/10.13039/100009133
    Keywords: ddc:551.5 ; duration ; heat wave ; indices ; intensity ; large‐scale ; spatial extent
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2023-06-21
    Description: Surface windstress transfers energy to the surface mixed layer of the ocean, and this energy partly radiates as internal gravity waves with near-inertial frequencies into the stratified ocean below the mixed layer where it is available for mixing. Numerical and analytical models provide estimates of the energy transfer into the mixed layer and the fraction radiated into the interior, but with large uncertainties, which we aim to reduce in the present study. An analytical slab model of the mixed layer used before in several studies is extended by consistent physics of wave radiation into the interior. Rayleigh damping, controlling the physics of the original slab model, is absent in the extended model and the wave-induced pressure gradient is resolved. The extended model predicts the energy transfer rates, both in physical and wavenumber-frequency space, associated with the wind forcing, dissipation in the mixed layer, and wave radiation at the base as function of a few parameters: mixed layer depth, Coriolis frequency and Brunt-Väisälä frequency below the mixed layer, and parameters of the applied windstress spectrum. The results of the model are satisfactorily validated with a realistic numerical model of the North Atlantic Ocean.
    Description: Deutsche Forschungsgemeinschaft https://doi.org/10.13039/501100001659
    Keywords: ddc:551.5 ; Wind-driven internal gravity waves ; Wave radiation physics
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 6
    Publication Date: 2023-12-05
    Description: A promising approach to improve cloud parameterizations within climate models and thus climate projections is to use deep learning in combination with training data from storm‐resolving model (SRM) simulations. The ICOsahedral Non‐hydrostatic (ICON) modeling framework permits simulations ranging from numerical weather prediction to climate projections, making it an ideal target to develop neural network (NN) based parameterizations for sub‐grid scale processes. Within the ICON framework, we train NN based cloud cover parameterizations with coarse‐grained data based on realistic regional and global ICON SRM simulations. We set up three different types of NNs that differ in the degree of vertical locality they assume for diagnosing cloud cover from coarse‐grained atmospheric state variables. The NNs accurately estimate sub‐grid scale cloud cover from coarse‐grained data that has similar geographical characteristics as their training data. Additionally, globally trained NNs can reproduce sub‐grid scale cloud cover of the regional SRM simulation. Using the game‐theory based interpretability library SHapley Additive exPlanations, we identify an overemphasis on specific humidity and cloud ice as the reason why our column‐based NN cannot perfectly generalize from the global to the regional coarse‐grained SRM data. The interpretability tool also helps visualize similarities and differences in feature importance between regionally and globally trained column‐based NNs, and reveals a local relationship between their cloud cover predictions and the thermodynamic environment. Our results show the potential of deep learning to derive accurate yet interpretable cloud cover parameterizations from global SRMs, and suggest that neighborhood‐based models may be a good compromise between accuracy and generalizability.
    Description: Plain Language Summary: Climate models, such as the ICOsahedral Non‐hydrostatic climate model, operate on low‐resolution grids, making it computationally feasible to use them for climate projections. However, physical processes –especially those associated with clouds– that happen on a sub‐grid scale (inside a grid box) cannot be resolved, yet they are critical for the climate. In this study, we train neural networks that return the cloudy fraction of a grid box knowing only low‐resolution grid‐box averaged variables (such as temperature, pressure, etc.) as the climate model sees them. We find that the neural networks can reproduce the sub‐grid scale cloud fraction on data sets similar to the one they were trained on. The networks trained on global data also prove to be applicable on regional data coming from a model simulation with an entirely different setup. Since neural networks are often described as black boxes that are therefore difficult to trust, we peek inside the black box to reveal what input features the neural networks have learned to focus on and in what respect the networks differ. Overall, the neural networks prove to be accurate methods of reproducing sub‐grid scale cloudiness and could improve climate model projections when implemented in a climate model.
    Description: Key Points: Neural networks can accurately learn sub‐grid scale cloud cover from realistic regional and global storm‐resolving simulations. Three neural network types account for different degrees of vertical locality and differentiate between cloud volume and cloud area fraction. Using a game theory based library we find that the neural networks tend to learn local mappings and are able to explain model errors.
    Description: EC ERC HORIZON EUROPE European Research Council
    Description: Partnership for Advanced Computing in Europe (PRACE)
    Description: NSF Science and Technology Center, Center for Learning the Earth with Artificial Intelligence and Physics (LEAP)
    Description: Deutsches Klimarechenzentrum
    Description: Columbia sub‐award 1
    Description: https://github.com/agrundner24/iconml_clc
    Description: https://doi.org/10.5281/zenodo.5788873
    Description: https://code.mpimet.mpg.de/projects/iconpublic
    Keywords: ddc:551.5 ; cloud cover ; parameterization ; machine learning ; neural network ; explainable AI ; SHAP
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 7
    Publication Date: 2023-11-28
    Description: Horizontal gravity wave (GW) refraction was observed around the Andes and Drake Passage during the SouthTRAC campaign. GWs interact with the background wind through refraction and dissipation. This interaction helps to drive midatmospheric circulations and slows down the polar vortex by taking GW momentum flux (GWMF) from one location to another. The SouthTRAC campaign was composed to gain improved understanding of the propagation and dissipation of GWs. This study uses observational data from this campaign collected by the German High Altitude Long Range research aircraft on 12 September 2019. During the campaign a minor sudden stratospheric warming in the southern hemisphere occurred, which heavily influenced GW propagation and refraction and thus also the location and amount of GWMF deposition. Observations include measurements from below the aircraft by Gimballed Limb Observer for Radiance Imaging of the Atmosphere and above the aircraft by Airborne Lidar for the Middle Atmosphere. Refraction is identified in two different GW packets as low as ≈4 km and as high as 58 km. One GW packet of orographic origin and one of nonorographic origin is used to investigate refraction. Observations are supplemented by the Gravity‐wave Regional Or Global Ray Tracer, a simplified mountain wave model, ERA5 data and high‐resolution (3 km) WRF data. Contrary to some previous studies we find that refraction makes a noteworthy contribution in the amount and the location of GWMF deposition. This case study highlights the importance of refraction and provides compelling arguments that models should account for this.
    Description: Plain Language Summary: Gravity waves (GWs) are very important for models to reproduce a midatmospheric circulations. But the fact is that models oversimplify the GW physics which results in GWs being underrepresented in models. GW refraction is one of the processes not captured by the physics in model parameterization schemes. This article uses high‐resolution observations from the SouthTRAC campaign to show how GWs refract and highlight the importance there‐of. This case study shows a 25% increase in the GWMF during propagation. The increase in momentum flux is linked to refraction which results in a shortening in the GW horizontal wavelength. This article shows that refraction is important for the amount as well as the location of GWMF deposition. This case study highlights the importance of refraction and provides compelling arguments that models should account for this.
    Description: Key Points: A case study reveals that refraction results in a 25% increase in gravity wave momentum flux (GWMF). Including refraction dynamics affects the location of GWMF deposition. Refraction is prominent in strong wind gradients (i.e., displaced vortex conditions).
    Description: ANPCYT PICT
    Description: DFG
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: Instituto de Física de Buenos Aires
    Description: SNCAD MinCyT initiative
    Description: HALO‐SPP
    Description: ROMIC WASCLIM
    Description: https://doi.org/10.5281/zenodo.6997443
    Description: https://cds.climate.copernicus.eu/cdsapp%23%21/home
    Keywords: ddc:551.5 ; gravity wave ; mountain wave ; refraction ; Andes ; Drake Passage ; gravity wave momentum flux
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 8
    Publication Date: 2022-10-04
    Description: We use a global 5‐km resolution model to analyze the air‐sea interactions during a katabatic storm in the Irminger Sea originating from the Ammassalik valleys. Katabatic storms have not yet been resolved in global climate models, raising the question of whether and how they modify water masses in the Irminger Sea. Our results show that dense water forms along the boundary current and on the shelf during the katabatic storm due to the heat loss caused by the high wind speeds and the strong temperature contrast. The dense water contributes to the lightest upper North Atlantic Deep Water as upper Irminger Sea Intermediate Water and thus to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The katabatic storm triggers a polar low, which in turn amplifies the near‐surface wind speed due to the superimposed pressure gradient, in addition to acceleration from a breaking mountain wave. Overall, katabatic storms account for up to 25% of the total heat loss (20 January 2020 to 30 September 2021) over the Irminger shelf of the Ammassalik area. Resolving katabatic storms in global models is therefore important for the formation of dense water in the western boundary current of the Irminger Sea, which is relevant to the AMOC, and for the large‐scale atmospheric circulation by triggering polar lows.
    Description: Plain Language Summary: Katabatic storms are outbursts of cold air associated with strong winds from coastal valleys of Greenland, in particular from the Ammassalik valleys in southeast Greenland. These storms are not resolved in global climate models because of their small spatial extent. However, they are important for the formation of dense water on the Irminger Sea shelf, because they induce a substantial heat loss from the coastal water. In this study, we resolve katabatic storms for the first time in a global climate model and analyze the water transformation caused by a single storm before quantifying the importance of katabatic storms for the entire simulation period. We find that a water mass is formed during the katabatic storm that is dense enough to contribute to the cooling and sinking of the global conveyor belt in the subpolar North Atlantic. Overall, katabatic storms account for up to 25% of the heat loss over the Irminger shelf of the Ammassalik area.
    Description: Key Points: For the first time, the direct effect of a katabatic storm on the Irminger Sea has been simulated in a global climate model. The katabatic storm induces strong heat loss and dense water formation over the Irminger shelf (Sermilik Trough) and in the boundary current. Dense water forming in the western boundary current during katabatic storms contributes to the lightest upper North Atlantic Deep Water.
    Description: Collaborative Research Centre TRR181 funded by DFG
    Description: Max Planck Society for Advancement of Science
    Description: NextGEMS
    Description: European Union’s Horizon 2020
    Description: https://hdl.handle.net/21.11116/0000-0008-ECF1-E
    Description: https://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=DKRZ_LTA_033_ds00010
    Description: https://mpimet.mpg.de/en/science/modeling-with-icon/code-availability
    Keywords: ddc:551.5
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2022-10-06
    Description: Trade wind convection organises into a rich spectrum of spatial patterns, often in conjunction with precipitation development. Which role spatial organisation plays for precipitation and vice versa is not well understood. We analyse scenes of trade‐wind convection scanned by the C‐band radar Poldirad during the EUREC4A field campaign to investigate how trade‐wind precipitation fields are spatially organised, quantified by the cells' number, mean size, and spatial arrangement, and how this matters for precipitation characteristics. We find that the mean rain rate (i.e., the amount of precipitation in a scene) and the intensity of precipitation (mean conditional rain rate) relate differently to the spatial pattern of precipitation. Whereas the amount of precipitation increases with mean cell size or number, as it scales well with the precipitation fraction, the intensity increases predominantly with mean cell size. In dry scenes, the increase of precipitation intensity with mean cell size is stronger than in moist scenes. Dry scenes usually contain fewer cells with a higher degree of clustering than moist scenes do. High precipitation intensities hence typically occur in dry scenes with rather large, few, and strongly clustered cells, whereas high precipitation amounts typically occur in moist scenes with rather large, numerous, and weakly clustered cells. As cell size influences both the intensity and amount of precipitation, its importance is highlighted. Our analyses suggest that the cells' spatial arrangement, correlating mainly weakly with precipitation characteristics, is of second‐order importance for precipitation across all regimes, but it could be important for high precipitation intensities and to maintain precipitation amounts in dry environments.
    Description: We analyse scenes of trade‐wind convection scanned by the C‐band radar Poldirad during the EUREC4A field campaign to investigate how trade‐wind precipitation fields are spatially organised, quantified by the cells' number, mean size, and spatial arrangement, and how this matters for precipitation characteristics. We conclude that the cells' size is important for both the amount and intensity of precipitation, whereas the cells' spatial arrangement is of second‐order importance for precipitation across all regimes, but possibly important for precipitation in dry environments.
    Description: Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy—EXC 2037 'CLICCS—Climate, Climatic Change, and Society'
    Description: https://doi.org/10.25326/217
    Description: https://doi.org/10.25326/79
    Keywords: ddc:551.5
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 10
    Publication Date: 2023-01-14
    Description: High‐resolution flight data obtained from in situ measurements in the free atmosphere aboard the High Altitude and Long Range Research Aircraft (HALO) are used to determine eddy dissipation rates along extended flights during the recent Southern Hemisphere Transport, Dynamics, and Chemistry aircraft campaign (SOUTHTRAC) in the 2019 austral winter. These data are analyzed and correlated with quantities characterizing the ambient airflow and the magnitudes of vertical energy propagation through internal gravity waves. The observed turbulence events are strongly correlated with elevated shear values, and overturning gravity waves do not appear to play a role. A highlight of the analysis is the validation of a recently implemented Clear Air Turbulence (CAT) forecast index in the European Centre for Medium‐Range Weather Forecast integrated forecast system. Here we find a slightly better correlation of the CAT prediction with the HALO research aircraft observations compared to those of commercial aircraft. The observed turbulence during SOUTHTRAC was never stronger than moderate, as EDR values remained below 0.3 m2/3 s−1. In general, light and light‐to‐moderate turbulence events were extremely rare, occurring in only about 5% of the flight time, and stronger events in less than 0.2%. These results are also reflected in the local atmospheric conditions, which were dominated by a thermally very stable airflow with low vertical shear and large Richardson numbers.
    Description: Plain Language Summary: This study analyzes high‐resolution data of velocity components in the upper troposphere and lower stratosphere collected with the German research aircraft High Altitude and Long Range Research Aircraft during the Southern Hemisphere Transport, Dynamics, and Chemistry (SOUTHTRAC) campaign in September–November 2019. Flights were conducted predominantly over the southern part of South America, the Drake Passage, and the Antarctic Peninsula. The objective of the analysis was to determine the eddy dissipation rates during the 22 flights. The cubic root of eddy dissipation rates is a common measure used to characterize turbulent regions in the atmosphere. High quality observations with a very accurately calibrated sensor are rare, especially in the remote areas of the SOUTHTRAC campaign. Observed eddy dissipation rates have been correlated with gravity wave activity, but these correlations are very small. A much stronger dependence of the eddy dissipation rates exists on the vertical shear of the horizontal wind. Thus, mechanical generation of turbulence appears to dominate in the observed cases. Overall, the observed turbulence was never stronger than moderate. Turbulence events were extremely rare, occurring in only about 5% of the flight time, and stronger events less than 0.2%. Finally, the observed eddy dissipation rates were compared with weather model forecasts, demonstrating their reliability in predicting turbulent regions.
    Description: Key Points: Small eddy dissipation rates were observed in the free atmosphere along extended research flights during Southern Hemisphere Transport, Dynamics, and Chemistry in austral winter 2019. Stronger turbulence events are rare and are mostly correlated with enhanced vertical shear of the horizontal wind. EDR predictions of a 15‐member ensemble shows higher correlation with research aircraft observations than with those by commercial aircraft.
    Description: Federal Ministry for Education and Research
    Description: German Science Foundation
    Description: https://halo-db.pa.op.dlr.de/mission/116
    Description: https://halo-db.pa.op.dlr.de/dataset/8497
    Description: https://halo-db.pa.op.dlr.de/dataset/8496
    Description: https://apps.ecmwf.int/codes/grib/param-db/?id=260290
    Description: https://doi.org/10.21957/xbar-5611
    Description: https://halo-db.pa.op.dlr.de/dataset/8955
    Description: https://madis.ncep.noaa.gov/acars_variable_list.shtml
    Keywords: ddc:551.5 ; turbulence in the free atmosphere ; eddy dissipation rate ; clear‐air turbulence predictions ; ECMWF integrated forecast system
    Language: English
    Type: doc-type:article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...