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Barriereinseln und Außensände, geformt durch eine Kombination aus Wind, Wellen, Strömung und Küstenlängstransport gelten als morphologisch hoch aktive Küstenbereiche und variieren häufig in Ursprung, Genese und Entwicklung. Sie besitzen durch ihre dissipative Wirkungsweise eine bedeutende Schutzfunktion für rückwärtige Inseln, Halligen und Festlandbereiche und bilden vor der Küste Nordfrieslands die westliche Außengrenze des Wattenmeeres.
Ziel der nachfolgenden Studie ist es, anhand hochauflösender Georadarmessungen und sedimentologischer Daten aus Bohrungen die Landschaftsgeschichte an der Westküste Amrums sowie die Entstehung und interne sedimentäre Architektur des der Insel westlich angelagerten Kniepsandes zu untersuchen und die Prozesse, die zur Genese geführt haben, durch Datierungen zeitlich einzuordnen. Auf Grundlage der gewonnenen Daten wurden zwei stratigraphische Modelle entwickelt, welche die geologisch-geomorphologischen Prozesse und Sedimentationsbedingungen im Westküstenvorfeld erklären.
Ein Modell zeigt die Landschaftsentwicklung an der Westküste Amrums und beschreibt die Sedimentationsbedingungen, die im Vorfeld der Westküste herrschten, bevor der Kniepsand an die Insel heranwanderte. Auf der Landoberfläche des ertrinkenden saaleeiszeitlichen Geestkerns wurden zu Beginn der Flandrischen Transgression feinkörnige Sedimente eines Mischund Schlickwatts abgelagert. Es ist davon auszugehen, dass der damals noch weit vor der Küste Amrums liegende Kniepsand eine Barriere bildete und so an der heute hochenergetischen Westküste für strömungsberuhigte Sedimentationsbedingungen sorgte. Durch Erosion am Geestkern bildeten sich in unterschiedlichen Höhenpositionen fossile Kliffs, die dem damaligen Meeresspiegelstand entsprechen.
Ein weiteres Modell beschreibt den Andockmechanismus des Kniepsandes an die Insel Amrum. Durch die Anlagerung des ehemaligen Außensandes und den damit einhergehenden Sedimentinput wurden die Bedingungen für eine großflächige Dünenbildung geschaffen.
Comparing projections of future changes in runoff from hydrological and biome models in ISI-MIP
(2013)
Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Intercomparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981–2010) to the future (2070–2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies.
The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well-reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness-of-fit for broadleaved forests. N limitation associated with low N mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N-limitation associated with low N mineralisation rates of colder soils reduces CO2-enhancement of NPP for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by c. 10 %; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions not only in studies of global terrestrial C cycling, but to understand underlying mechanisms on local scales and in different regional contexts.
Fire is the primary disturbance factor in many terrestrial ecosystems. Wildfire alters vegetation structure and composition, affects carbon storage and biogeochemical cycling, and results in the release of climatically relevant trace gases including CO2, CO, CH4, NOx, and aerosols. One way of assessing the impacts of global wildfire on centennial to multi-millennial timescales is to use process-based fire models linked to dynamic global vegetation models (DGVMs). Here we present an update to the LPJ-DGVM and a new fire module based on SPITFIRE that includes several improvements to the way in which fire occurrence, behaviour, and the effects of fire on vegetation are simulated. The new LPJ-LMfire model includes explicit calculation of natural ignitions, the representation of multi-day burning and coalescence of fires, and the calculation of rates of spread in different vegetation types. We describe a new representation of anthropogenic biomass burning under preindustrial conditions that distinguishes the different relationships between humans and fire among hunter-gatherers, pastoralists, and farmers. We evaluate our model simulations against remote-sensing-based estimates of burned area at regional and global scale. While wildfire in much of the modern world is largely influenced by anthropogenic suppression and ignitions, in those parts of the world where natural fire is still the dominant process (e.g. in remote areas of the boreal forest and subarctic), our results demonstrate a significant improvement in simulated burned area over the original SPITFIRE. The new fire model we present here is particularly suited for the investigation of climate–human–fire relationships on multi-millennial timescales prior to the Industrial Revolution.
Funded by the German Ministry for Education and Research (BMBF) a major research project called MiKlip (Mittelfristige Klimaprognose, Decadal Climate Prediction) was launched and global as well as regional predictive ensemble hindcasts have been generated. The aim of the project is to demonstrate for past climate change whether predictive models have the capability of predicting climate on time scales of decades. This includes the development of a decadal forecast system, on the one hand to support decision making for economy, politics and society for decadal time spans. On the other hand, the scientific aspect is to explore the feasibility and prospects of global and regional forecasts on decadal time scales. The focus of this paper lies on the description of the regional hindcast ensemble for Europe generated by COSMO-CLM and on the assessment of the decadal variability and predictability against observations. To measure decadal variability we remove the long term bias as well as the long term linear trend from the data. Further, we applied low pass filters to the original data to separate the decadal climate signal from high frequency noise. The decadal variability and predictability assessment is applied to temperature and precipitation data for the summer and winter half-year averages/sums. The best results have been found for the prediction of decadal temperature anomalies, i.e. we have detected a distinct predictive skill and reasonable reliability. Hence it is possible to predict regional temperature variability on decadal timescales, However, the situation is less satisfactory for precipitation. Here we have found regions showing good predictability, but also regions without any predictive skill.
Global climate change is one of the major driving forces for adaptive shifts in migration and breeding phenology and possibly impacts demographic changes if a species fails to adapt sufficiently. In Western Europe, pied flycatchers (Ficedula hypoleuca) have insufficiently adapted their breeding phenology to the ongoing advance of food peaks within their breeding area and consequently suffered local population declines. We address the question whether this population decline led to a loss of genetic variation, using two neutral marker sets (mitochondrial control region and microsatellites), and one potentially selectively non-neutral marker (avian Clock gene). We report temporal changes in genetic diversity in extant populations and biological archives over more than a century, using samples from sites differing in the extent of climate change. Comparing genetic differentiation over this period revealed that only the recent Dutch population, which underwent population declines, showed slightly lower genetic variation than the historic Dutch population. As that loss of variation was only moderate and not observed in all markers, current gene flow across Western and Central European populations might have compensated local loss of variation over the last decades. A comparison of genetic differentiation in neutral loci versus the Clock gene locus provided evidence for stabilizing selection. Furthermore, in all genetic markers, we found a greater genetic differentiation in space than in time. This pattern suggests that local adaptation or historic processes might have a stronger effect on the population structure and genetic variation in the pied flycatcher than recent global climate changes.
In this study we show how size-resolved measurements of aerosol particles and cloud condensation nuclei (CCN) can be used to characterize the supersaturation of water vapor in a cloud. The method was developed and applied for the investigation of a cloud event during the ACRIDICON-Zugspitze campaign (17 September to 4 October 2012) at the high-alpine research station Schneefernerhaus (German Alps, 2650 m a.s.l.). Number size distributions of total and interstitial aerosol particles were measured with a scanning mobility particle sizer (SMPS), and size-resolved CCN efficiency spectra were recorded with a CCN counter system operated at different supersaturation levels.
During the evolution of a cloud, aerosol particles are exposed to different supersaturation levels. We outline and compare different estimates for the lower and upper bounds (Slow, Shigh) and the average value (Savg) of peak supersaturation encountered by the particles in the cloud. For the investigated cloud event, we derived Slow ≈ 0.19–0.25%, Shigh ≈ 0.90–1.64% and Savg ≈ 0.38–0.84%. Estimates of Slow, Shigh and Savg based on aerosol size distribution data require specific knowledge or assumptions of aerosol hygroscopicity, which are not required for the derivation of Slow and Savg from the size-resolved CCN efficiency spectra.
This study presents a method for adjusting long-term climate data records (CDRs) for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS). Recently, a 23-year long (1983–2005) continuous SIS CDR has been generated based on the visible channel (0.45–1 μm) of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005) and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards) were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present) was applied that combines the Standard Normal Homogeneity Test (SNHT) and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN) and about 50 stations of the Global Energy Balance Archive (GEBA) over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of any segment between two break points to the last segment (2006–present). Corrections are applied to the most significant breaks that can be related to satellite changes. This study focuses on the European region, but the methods can be generalized to other regions. To account for seasonal dependence of the mean-shifts the correction was performed independently for each calendar month. In comparison to the ground-based reference the homogenised data record shows an improvement over the original data record in terms of anomaly correlation and bias. In general the method can also be applied for the adjustment of satellite datasets addressing other variables to bridge the gap between CDRs and near-real-time data.
State-of-the-art general circulation models (GCMs) are tested and challenged by the ability to reproduce paleoclimate key intervals. In order to account for climate changes associated with soil dynamics we have developed a soil scheme, which is asynchronously coupled to a state-of-the-art atmosphere ocean GCM with dynamic vegetation. We test the scheme for conditions representative of a warmer (mid-Holocene, 6 kyr before present, BP) and colder (Last Glacial Maximum, 21 kyr BP) than pre-industrial climate. The computed change of physical soil properties (i.e. albedo, water storage capacity, and soil texture) for these different climates leads to amplified global climate anomalies. Especially regions like the transition zone of desert/savannah and taiga/tundra, exhibit an increased response as a result of the modified soil treatment. In comparison to earlier studies, the inclusion of the soil feedback pushes our model simulations towards the warmer end in the range of mid-Holocene studies and beyond current estimates of global cooling during the Last Glacial Maximum based on PMIP2 (Paleoclimate Modelling Intercomparison Project 2) studies. The main impact of the interactive soil scheme on the climate response is governed by positive feedbacks, including dynamics of vegetation, snow, sea ice, local water recycling, which might amplify forcing factors ranging from orbital to tectonic timescales.
When studying new particle formation, the uncertainty in determining the "true" nucleation rate is considerably reduced when using condensation particle counters (CPCs) capable of measuring concentrations of aerosol particles at sizes close to or even at the critical cluster size (1–2 nm). Recently, CPCs able to reliably detect particles below 2 nm in size and even close to 1 nm became available. Using these instruments, the corrections needed for calculating nucleation rates are substantially reduced compared to scaling the observed formation rate to the nucleation rate at the critical cluster size. However, this improved instrumentation requires a careful characterization of their cut-off size and the shape of the detection efficiency curve because relatively small shifts in the cut-off size can translate into larger relative errors when measuring particles close to the cut-off size.
Here we describe the development of two continuous-flow CPCs using diethylene glycol (DEG) as the working fluid. The design is based on two TSI 3776 counters. Several sets of measurements to characterize their performance at different temperature settings were carried out. Furthermore, two mixing-type particle size magnifiers (PSM) A09 from Airmodus were characterized in parallel. One PSM was operated at the highest mixing ratio (1 L min−1 saturator flow), and the other was operated in a scanning mode, where the mixing ratios are changed periodically, resulting in a range of cut-off sizes. The mixing ratios are determined by varying the saturator flow, where the aerosol flow stays constant at 2.5 L min−1. Different test aerosols were generated using a nano-differential mobility analyser (nano-DMA) or a high-resolution DMA, to obtain detection efficiency curves for all four CPCs. One calibration setup included a high-resolution mass spectrometer (APi-TOF) for the determination of the chemical composition of the generated clusters. The lowest cut-off sizes were achieved with negatively charged ammonium sulfate clusters, resulting in cut-offs of 1.4 nm for the laminar flow CPCs and 1.2 and 1.1 nm for the PSMs. A comparison of one of the laminar-flow CPCs and one of the PSMs measuring ambient and laboratory air showed good agreement between the instruments.