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- ItemModelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing(Katlenburg-Lindau : Copernicus, 2023) Heinke, Jens; Rolinski, Susanne; Müller, ChristophTo represent the impact of grazing livestock on carbon (C) and nitrogen (N) dynamics in grasslands, we implement a livestock module into LPJmL5.0-tillage, a global vegetation and crop model with explicit representation of managed grasslands and pastures, forming LPJmL5.0-grazing. The livestock module uses lactating dairy cows as a generic representation of grazing livestock. The new module explicitly accounts for forage quality in terms of dry-matter intake and digestibility using relationships derived from compositional analyses for different forages. Partitioning of N into milk, feces, and urine as simulated by the new livestock module shows very good agreement with observation-based relationships reported in the literature. Modelled C and N dynamics depend on forage quality (C:N ratios in grazed biomass), forage quantity, livestock densities, manure or fertilizer inputs, soil, atmospheric CO2 concentrations, and climate conditions. Due to the many interacting relationships, C sequestration, GHG emissions, N losses, and livestock productivity show substantial variation in space and across livestock densities. The improved LPJmL5.0-grazing model can now assess the effects of livestock grazing on C and N stocks and fluxes in grasslands. It can also provide insights about the spatio-temporal variability of grassland productivity and about the trade-offs between livestock production and environmental impacts.
- ItemA method to derive Fourier-wavelet spectra for the characterization of global-scale waves in the mesosphere and lower thermosphere and its MATLAB and Python software (fourierwavelet v1.1)(Katlenburg-Lindau : Copernicus, 2023) Yamazaki, YosukeThis paper describes a simple method for characterizing global-scale waves in the mesosphere and lower thermosphere (MLT), such as tides and traveling planetary waves, using uniformly gridded two-dimensional longitude-Time data. The technique involves two steps. In the first step, the Fourier transform is performed in space (longitude), and then the time series of the space Fourier coefficients are derived. In the second step, the wavelet transform is performed on these time series, and wavelet coefficients are derived. A Fourier-wavelet spectrum can be obtained from these wavelet coefficients, which gives the amplitude and phase of the wave as a function of time and wave period. It can be used to identify wave activity that is localized in time, similar to a wavelet spectrum, but the Fourier-wavelet spectrum can be obtained separately for eastward-and westward-propagating components and for different zonal wavenumbers. The Fourier-wavelet analysis can be easily implemented using existing Fourier and wavelet software. MATLAB and Python scripts are created and made available at https://igit.iap-kborn.de/yamazaki/fourierwavelet (last access: 18 August 2023) that compute Fourier-wavelet spectra using the wavelet software provided by . Some application examples are presented using MLT data from atmospheric models.
- ItemCloud top heights and aerosol layer properties from EarthCARE lidar observations: The A-CTH and A-ALD products(Katlenburg-Lindau : Copernicus, 2023) Wandinger, Ulla; Haarig, Moritz; Baars, Holger; Donovan, David; van Zadelhoff, Gerd-JanThe high-spectral-resolution Atmospheric Lidar (ATLID) on the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) provides vertically resolved information on aerosols and clouds with unprecedented accuracy. Together with the Cloud Profiling Radar (CPR), the Multi-Spectral Imager (MSI), and the Broad-Band Radiometer (BBR) on the same platform, it allows for a new synergistic view on atmospheric processes related to the interaction of aerosols, clouds, precipitation, and radiation at the global scale. This paper describes the algorithms for the determination of cloud top height and aerosol layer information from ATLID Level 1b (L1b) and Level 2a (L2a) input data. The ATLID L2a Cloud Top Height (A-CTH) and Aerosol Layer Descriptor (A-ALD) products are developed to ensure the provision of atmospheric layer products in continuation of the heritage from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Moreover, the products serve as input for synergistic algorithms that make use of data from ATLID and MSI. Therefore, the products are provided on the EarthCARE joint standard grid (JSG). A wavelet covariance transform (WCT) method with flexible thresholds is applied to determine layer boundaries from the ATLID Mie co-polar signal. Strong features detected with a horizontal resolution of 1 JSG pixel (approximately 1ĝ€¯km) or 11 JSG pixels are classified as thick or thin clouds, respectively. The top height of the uppermost cloud layer together with information on cloud layering are stored in the A-CTH product for further use in the generation of the ATLID-MSI Cloud Top Height (AM-CTH) synergy product. Aerosol layers are detected as weaker features at a resolution of 11 JSG pixels. Layer-mean optical properties are calculated from the ATLID L2a Extinction, Backscatter and Depolarization (A-EBD) product and stored in the A-ALD product, which also contains the aerosol optical thickness (AOT) of each layer, the stratospheric AOT, and the AOT of the entire atmospheric column. The latter parameter is used to produce the synergistic ATLID-MSI Aerosol Column Descriptor (AM-ACD) later in the processing chain. Several quality criteria are applied in the generation of A-CTH and A-ALD, and respective information is stored in the products. The functionality and performance of the algorithms are demonstrated by applying them to common EarthCARE test scenes. Conclusions are drawn for the application to real-world data and the validation of the products after the launch of EarthCARE.
- ItemCloud mask algorithm from the EarthCARE Multi-Spectral Imager: the M-CM products(Katlenburg-Lindau : Copernicus, 2023) Hünerbein, Anja; Bley, Sebastian; Horn, Stefan; Deneke, Hartwig; Walther, AndiThe EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) satellite mission will provide new insights into aerosol-cloud-radiation interactions by means of synergistic observations of the Earth's atmosphere from a collection of active and passive remote sensing instruments, flying on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross-track direction with a 150km swath and a pixel sampling at 500m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask algorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential inputs to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol optical properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end-to-end simulator and satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simulated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algorithm. Some discrepancies are found, however, for the detection of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available.
- ItemNext-generation ice-nucleating particle sampling on board aircraft: characterization of the High-volume flow aERosol particle filter sAmpler (HERA)(Katlenburg-Lindau : Copernicus, 2023) Grawe, Sarah; Jentzsch, Conrad; Schaefer, Jonas; Wex, Heike; Mertes, Stephan; Stratmann, FrankAtmospheric ice-nucleating particle (INP) concentration data from the free troposphere are sparse but urgently needed to understand vertical transport processes of INPs and their influence on cloud formation and properties. Here, we introduce the new High-volume flow aERosol particle filter sAmpler (HERA) which was specially developed for installation on research aircraft and subsequent offline INP analysis. HERA is a modular system consisting of a sampling unit and a powerful pump unit, and it has several features which were integrated specifically for INP sampling. Firstly, the pump unit enables sampling at flow rates exceeding 100 L min-1, which is well above typical flow rates of aircraft INP sampling systems described in the literature (∼ 10 L min-1). Consequently, required sampling times to capture rare, high-temperature INPs (≥ -15 C) are reduced in comparison to other systems, and potential source regions of INPs can be confined more precisely. Secondly, the sampling unit is designed as a seven-way valve, enabling switching between six filter holders and a bypass with one filter being sampled at a time. In contrast to other aircraft INP sampling systems, the valve position is remote-controlled via software so that manual filter changes during flight are eliminated and the potential for sample contamination is decreased. This design is compatible with a high degree of automation, i.e., triggering filter changes depending on parameters like flight altitude, geographical location, temperature, or time. In addition to presenting the design and principle of operation of HERA, this paper describes laboratory characterization experiments with size-selected test substances, i.e., SNOMAX® and Arizona Test Dust. The particles were sampled on filters with HERA, varying either particle diameter (300 to 800 nm) or flow rate (10 to 100 L min-1) between experiments. The subsequent offline INP analysis showed good agreement with literature data and comparable sampling efficiencies for all investigated particle sizes and flow rates. Furthermore, the collection efficiency of atmospheric INPs in HERA was compared to a straightforward filter sampler and good agreement was found. Finally, results from the first campaign of HERA on the High Altitude and LOng range research aircraft (HALO) demonstrate the functionality of the new system in the context of aircraft application.
- ItemLandInG 1.0: a toolbox to derive input datasets for terrestrial ecosystem modelling at variable resolutions from heterogeneous sources(Katlenburg-Lindau : Copernicus, 2023) Ostberg, Sebastian; Müller, Christoph; Heinke, Jens; Schaphoff, SibyllWe present the Land Input Generator (LandInG) version 1.0, a new toolbox for generating input datasets for terrestrial ecosystem models (TEMs) from diverse and partially conflicting data sources. While LandInG 1.0 is applicable to process data for any TEM, it is developed specifically for the open-source dynamic global vegetation, hydrology, and crop growth model LPJmL (Lund-Potsdam-Jena with managed Land). The toolbox documents the sources and processing of data to model inputs and allows for easy changes to the spatial resolution. It is designed to make inconsistencies between different sources of data transparent so that users can make their own decisions on how to resolve these should they not be content with the default assumptions made here. As an example, we use the toolbox to create input datasets at 5 and 30 arcmin spatial resolution covering land, country, and region masks, soil, river networks, freshwater reservoirs, irrigation water distribution networks, crop-specific annual land use, fertilizer, and manure application. We focus on the toolbox describing the data processing rather than only publishing the datasets as users may want to make different choices for reconciling inconsistencies, aggregation, spatial extent, or similar. Also, new data sources or new versions of existing data become available continuously, and the toolbox approach allows for incorporating new data to stay up to date.
- ItemThe Earth system model CLIMBER-X v1.0 - Part 2: The global carbon cycle(Katlenburg-Lindau : Copernicus, 2023) Willeit, Matteo; Ilyina, Tatiana; Liu, Bo; Heinze, Christoph; Perrette, Mahé; Heinemann, Malte; Dalmonech, Daniela; Brovkin, Victor; Munhoven, Guy; Börker, Janine; Hartmann, Jens; Romero-Mujalli, Gibran; Ganopolski, AndreyThe carbon cycle component of the newly developed Earth system model of intermediate complexity CLIMBER-X is presented. The model represents the cycling of carbon through the atmosphere, vegetation, soils, seawater and marine sediments. Exchanges of carbon with geological reservoirs occur through sediment burial, rock weathering and volcanic degassing. The state-of-the-art HAMOCC6 model is employed to simulate ocean biogeochemistry and marine sediment processes. The land model PALADYN simulates the processes related to vegetation and soil carbon dynamics, including permafrost and peatlands. The dust cycle in the model allows for an interactive determination of the input of the micro-nutrient iron into the ocean. A rock weathering scheme is implemented in the model, with the weathering rate depending on lithology, runoff and soil temperature. CLIMBER-X includes a simple representation of the methane cycle, with explicitly modelled natural emissions from land and the assumption of a constant residence time of CH4 in the atmosphere. Carbon isotopes 13C and 14C are tracked through all model compartments and provide a useful diagnostic for model-data comparison. A comprehensive evaluation of the model performance for the present day and the historical period shows that CLIMBER-X is capable of realistically reproducing the historical evolution of atmospheric CO2 and CH4 but also the spatial distribution of carbon on land and the 3D structure of biogeochemical ocean tracers. The analysis of model performance is complemented by an assessment of carbon cycle feedbacks and model sensitivities compared to state-of-the-art Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Enabling an interactive carbon cycle in CLIMBER-X results in a relatively minor slow-down of model computational performance by ∼ 20 % compared to a throughput of ∼ 10 000 simulation years per day on a single node with 16 CPUs on a high-performance computer in a climate-only model set-up. CLIMBER-X is therefore well suited to investigating the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to >100000 years.
- ItemEffects of extreme melt events on ice flow and sea level rise of the Greenland Ice Sheet(Katlenburg-Lindau : Copernicus, 2023) Beckmann, Johanna; Winkelmann, RicardaOver the past decade, Greenland has experienced several extreme melt events, the most pronounced ones in the years 2010, 2012 and 2019. With progressing climate change, such extreme melt events can be expected to occur more frequently and potentially become more severe and persistent. So far, however, projections of ice loss and sea level change from Greenland typically rely on scenarios which only take gradual changes in the climate into account. Using the Parallel Ice Sheet Model (PISM), we investigate the effect of extreme melt events on the overall mass balance of the Greenland Ice Sheet and the changes in ice flow, invoked by the altered surface topography. As a first constraint, this study estimates the overall effect of extreme melt events on the cumulative mass loss of the Greenland Ice Sheet. We find that the sea level contribution from Greenland might increase by 2 to 45 cm (0.2 % to 14 %) by the year 2300 if extreme events occur more frequently in the future under a Representative Concentration Pathway 8.5 (RCP8.5) scenario, and the ice sheet area might be reduced by an additional 6000 to 26 000 km2 by 2300 in comparison to future warming scenarios without extremes. In conclusion, projecting the future sea level contribution from the Greenland Ice Sheet requires consideration of the changes in both the frequency and intensity of extreme events. It is crucial to individually address these extremes at a monthly resolution as temperature forcing with the same excess temperature but evenly distributed over longer timescales (e.g., seasonal) leads to less sea level rise than for the simulations of the resolved extremes. Extremes lead to additional mass loss and thinning. This, in turn, reduces the driving stress and surface velocities, ultimately dampening the ice loss attributed to ice flow and discharge. Overall, we find that the surface elevation feedback largely amplifies melting for scenarios with and without extremes, with additional mass loss attributed to this feedback having the greatest impact on projected sea level.