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search.filters.applied.f.access: openAccess × Type: Text × Publisher: Göttingen : Copernicus GmbH × Subject: algorithm ×

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Now showing 1 - 6 of 6
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    PeakTree: A framework for structure-preserving radar Doppler spectra analysis
    (Göttingen : Copernicus GmbH, 2019) Radenz, M.; Bühl, J.; Seifert, P.; Griesche, H.; Engelmann, R.
    Clouds are frequently composed of more than one particle population even at the smallest scales. Cloud radar observations frequently contain information on multiple particle species in the observation volume when there are distinct peaks in the Doppler spectrum. Multi-peaked situations are not taken into account by established algorithms, which only use moments of the Doppler spectrum. In this study, we propose a new algorithm that recursively represents the subpeaks as nodes in a binary tree. Using this tree data structure to represent the peaks of a Doppler spectrum, it is possible to drop all a priori assumptions on the number and arrangement of subpeaks. The approach is rigid, unambiguous and can provide a basis for advanced analysis methods. The applicability is briefly demonstrated in two case studies, in which the tree structure was used to investigate particle populations in Arctic multilayered mixed-phase clouds, which were observed during the research vessel Polarstern expedition PS106 and the Atmospheric Radiation Measurement Program BAECC campaign.
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    Reconstruction of global gridded monthly sectoral water withdrawals for 1971-2010 and analysis of their spatiotemporal patterns
    (Göttingen : Copernicus GmbH, 2018) Huang, Z.; Hejazi, M.; Li, X.; Tang, Q.; Vernon, C.; Leng, G.; Liu, Y.; Döll, P.; Eisner, S.; Gerten, D.; Hanasaki, N.; Wada, Y.
    Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5°) sectoral water withdrawal dataset for the period 1971-2010, which distinguishes six water use sectors, i.e., irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971-2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. The reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.
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    Retrieving horizontally resolved wind fields using multi-static meteor radar observations
    (Göttingen : Copernicus GmbH, 2018) Stober, G.; Chau, J.L.; Vierinen, J.; Jacobi, C.; Wilhelm, S.
    Recently, the MMARIA (Multi-static, Multi-frequency Agile Radar for Investigations of the Atmosphere) concept of a multi-static VHF meteor radar network to derive horizontally resolved wind fields in the mesosphere-lower thermosphere was introduced. Here we present preliminary results of the MMARIA network above Eastern Germany using two transmitters located at Juliusruh and Collm, and five receiving links: two monostatic and three multi-static. The observations are complemented during a one-week campaign, with a couple of addition continuous-wave coded transmitters, making a total of seven multi-static links. In order to access the kinematic properties of non-homogenous wind fields, we developed a wind retrieval algorithm that applies regularization to determine the non-linear wind field in the altitude range of 82-98 km. The potential of such observations and the new retrieval to investigate gravity waves with horizontal scales between 50-200 km is presented and discussed. In particular, it is demonstrated that horizonal wavelength spectra of gravity waves can be obtained from the new data set. © Author(s) 2018.
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    Combining cloud radar and radar wind profiler for a value added estimate of vertical air motion and particle terminal velocity within clouds
    (Göttingen : Copernicus GmbH, 2018) Radenz, M.; Bühl, J.; Lehmann, V.; Görsdorf, U.; Leinweber, R.
    Vertical-stare observations from a 482MHz radar wind profiler and a 35GHz cloud radar are combined on the level of individual Doppler spectra to measure vertical air motions in clear air, clouds and precipitation. For this purpose, a separation algorithm is proposed to remove the influence of falling particles from the wind profiler Doppler spectra and to calculate the terminal fall velocity of hydrometeors. The remaining error of both vertical air motion and terminal fall velocity is estimated to be better than 0.1ms-1 using numerical simulations. This combination of instruments allows direct measurements of in-cloud vertical air velocity and particle terminal fall velocity by means of ground-based remote sensing. The possibility of providing a profile every 10s with a height resolution of < 100m allows further insight into the process scale of in-cloud dynamics. The results of the separation algorithm are illustrated by two case studies, the first covering a deep frontal cloud and the second featuring a shallow mixed-phase cloud.
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    Accounting for environmental flow requirements in global water assessments
    (Göttingen : Copernicus GmbH, 2014) Pastor, A.V.; Ludwig, F.; Biemans, H.; Hoff, H.; Kabat, P.
    As the water requirement for food production and other human needs grows, quantification of environmental flow requirements (EFRs) is necessary to assess the amount of water needed to sustain freshwater ecosystems. EFRs are the result of the quantification of water necessary to sustain the riverine ecosystem, which is calculated from the mean of an environmental flow (EF) method. In this study, five EF methods for calculating EFRs were compared with 11 case studies of locally assessed EFRs. We used three existing methods (Smakhtin, Tennant, and Tessmann) and two newly developed methods (the variable monthly flow method (VMF) and the Q90-Q50 method). All methods were compared globally and validated at local scales while mimicking the natural flow regime. The VMF and the Tessmann methods use algorithms to classify the flow regime into high, intermediate, and low-flow months and they take into account intra-annual variability by allocating EFRs with a percentage of mean monthly flow (MMF). The Q90-Q50 method allocates annual flow quantiles (Q90 and Q50) depending on the flow season. The results showed that, on average, 37% of annual discharge was required to sustain environmental flow requirement. More water is needed for environmental flows during low-flow periods (46-71% of average low-flows) compared to high-flow periods (17-45% of average high-flows). Environmental flow requirements estimates from the Tennant, Q90-Q50, and Smakhtin methods were higher than the locally calculated EFRs for river systems with relatively stable flows and were lower than the locally calculated EFRs for rivers with variable flows. The VMF and Tessmann methods showed the highest correlation with the locally calculated EFRs (R2 = 0.91). The main difference between the Tessmann and VMF methods is that the Tessmann method allocates all water to EFRs in low-flow periods while the VMF method allocates 60% of the flow in low-flow periods. Thus, other water sectors such as irrigation can withdraw up to 40% of the flow during the low-flow season and freshwater ecosystems can still be kept in reasonable ecological condition. The global applicability of the five methods was tested using the global vegetation and the Lund-Potsdam-Jena managed land (LPJmL) hydrological model. The calculated global annual EFRs for fair ecological conditions represent between 25 and 46% of mean annual flow (MAF). Variable flow regimes, such as the Nile, have lower EFRs (ranging from 12 to 48% of MAF) than stable tropical regimes such as the Amazon (which has EFRs ranging from 30 to 67% of MAF).
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    A matrix clustering method to explore patterns of land-cover transitions in satellite-derived maps of the Brazilian Amazon
    (Göttingen : Copernicus GmbH, 2017) Müller-Hansen, F.; Cardoso, M.F.; Dalla-Nora, E.L.; Donges, J.F.; Heitzig, J.; Kurths, J.; Thonicke, K.
    Changes in land-use systems in tropical regions, including deforestation, are a key challenge for global sustainability because of their huge impacts on green-house gas emissions, local climate and biodiversity. However, the dynamics of land-use and land-cover change in regions of frontier expansion such as the Brazilian Amazon are not yet well understood because of the complex interplay of ecological and socioeconomic drivers. In this paper, we combine Markov chain analysis and complex network methods to identify regimes of land-cover dynamics from land-cover maps (TerraClass) derived from high-resolution (30ĝ€m) satellite imagery. We estimate regional transition probabilities between different land-cover types and use clustering analysis and community detection algorithms on similarity networks to explore patterns of dominant land-cover transitions. We find that land-cover transition probabilities in the Brazilian Amazon are heterogeneous in space, and adjacent subregions tend to be assigned to the same clusters. When focusing on transitions from single land-cover types, we uncover patterns that reflect major regional differences in land-cover dynamics. Our method is able to summarize regional patterns and thus complements studies performed at the local scale.