Natural fractionation of uranium isotopes
- Das Thema dieser Arbeit war die Untersuchung der natürlichen Variationen von den zwei primordialen Uranisotopen (238U und 235U) mit einem Schwerpunkt auf Proben, die (1) die kontinentale Kruste und ihre Verwitterungsprodukte (d.h. Granite, Shales und Flusswasser) repräsentieren, (2) Produkte der hydrothermalen Alteration vom mittelozeanischen Rücken widerspiegeln (d.h. alterierte Basalte, Karbonatgänge und hydrothermales Wasser) und (3) aus abgegrenzten euxinischen Becken (d.h. Proben aus der Wassersäule und den dazugehörigen Sedimenten) stammen. Das allgemeine Ziel war das Verständnis, unter welchen Bedingungen und Mechanismen eine Fraktionierung der zwei häufigsten Uranisotope (238U und 235U) in der Natur erfolgt, zu verbessern.
Die untersuchten Haupt- und Nebenflüsse unterscheiden sich sowohl in Ihrer Urankonzentration (c(U)) als auch in Ihrer Uranisotopenzusammensetzung (δ238U), wobei die Nebenflüsse eine geringere Urankonzentration (0.87 nmol/kg bis 3.08 nmol/kg) und eine schwerere Uranisotopenzusammensetzung aufweisen (-0.29 ‰ bis +0.01 ‰ im δ238U) im Vergleich zu den Hauptflüssen (c(U) = 5.19 nmol/kg bis 11.69 nmol/kg und d238U = -0.31 ‰ bis +0.13 ‰) aufweisen. Die untersuchten Gesteinsproben fallen alle in einen recht schmalen Bereich von δ238U, zwischen -0.45 ‰ und -0.21 ‰, mit einem Durchschnittswert von -0.30 ‰ ± 0.04 ‰ (doppelte Standardabweichung). Deren Uranisotopenvariationen sind unabhängig von der Urankonzentration (11.8 µg/g bis 1.3 µg/g), dem Alter (3.80 Ga bis 328 Ma), der Probenlokalität und Grad der Differenzierung. Basierend auf den Ergebnissen der Hauptflüsse, die die Uranhauptquelle für den Ozean darstellen, schlagen wir für zukünftige Berechnungen in der Massenbilanz des Urans einen neuen Wert als beste Abschätzung für die Quelle des Urans im Ozean vor, δ238U = -0.23 ‰.
Die Produkte der hydrothermalen Alteration, alterierte Basalte und Kalziumkarbonatgänge, zeigten etwas stärkere Isotopenvariationen (δ238U zwischen -0.63 ‰ und +0.27 ‰) als erwartet und die hydrothermalen Fluide wiesen eine etwas leichtere Uranisotopenzusammensetzung als Meerwasser ((-0.43 ± 0.25) ‰ vs. (-0.37 ± 0.03) ‰) auf. Diese Ergebnisse sind in Übereinstimmung mit einem Modell, dass annimmt, dass die beobachtete Isotopenfraktionierung hauptsächlich ein Ergebnis von Redoxprozessen ist, z.B. die partielle Reduktion von löslichem UVI aus dem Meerwasser während der hydrothermalen Alteration, was zu einer Anreicherung der schweren Uranisotope in der reduzierten Uranspezies (UIV) führt und 2) das bevorzugte Entfernen von UIV aus den hydrothermalen Fluid und der Einbau in die alterierte ozeanische Kruste. Durch diesen Prozess wird das hydrothermale Fluid an schweren Uranisotopen verarmt und somit würden auch die alterierten Basalte und Karbonate ein niedriges δ238U aufweisen, wenn sie mit dem isotopisch leichten hydrothermalen Fluid in Kontakt gekommen sind.
Die Untersuchung von Wasser- und Sedimentproben aus der Ostsee und dem anoxischen Kyllaren Fjord (Norwegen) auf deren Uran- und Mo-Isotopenzusammensetzung zeigte, dass die Uranisotopenzusammensetzung der Sedimente abhängt von (1) dem Ausmaß des Uranaustrags aus der Wassersäule (in einer ähnlichen Art und Weise wie bei den Molybdänisotopen) und (2) der Sedimentationsrate, d.h. der Fraktion von authigenem- relativ zum dedritischen Uran in den Sedimenten. Aufgrund der hohen Sedimentationsrate zeigen die Sedimente aus dem Kyllaren Fjord nur eine moderate authigene Urananreicherung und eine leichtere Uranisotopenzusammensetzung als Sedimente aus dem Schwarzen Meer. In den anoxischen Becken der Ostsee erfolgt dagegen eine starke Mo- und schwache U-Isotopenfraktionierung zwischen Wasser und Sediment. Durch die regelmäßigen auftretenden Spülereignisse mit sauerstoffreichem Wasser wurden vermutlich die ursprünglichen anoxischen Mo- und U-Isotopensignaturen der Sedimente verändert. Demzufolge müssen die Sedimente durchgehend anoxischen Bedingungen ausgesetzt sein, um eine Mo- und U-Isotopensignatur von den Redoxbedingungen während der Ablagerungen zu speichern.
Der Vergleich zwischen Molybdän- und Uranisotopen in der Ostsee und dem anoxischen Kyllaren Fjord zeigte, dass sich Uran- und Molybdänisotope in stark euxinischen Wassersäulen (c(H2S) > 11 µmol/L) entgegengesetzt verhalten. Dementsprechend ergänzen sich die beiden Isotopensysteme und können genutzt werden, um die Ablagerungsbedingungen in abgeschlossenen Becken und die Redoxentwicklung des Paläoozeans zu untersuchen.
The re-greening of the Sahel: natural cyclicity or human-induced change?
- The Sahel has been the focus of scientific interest in environmental-human dynamics and interactions. The objective of the present study is to contribute to the recent debate on the re-greening of Sahel. The paper examines the dynamics of barren land in the Sahel of Burkina Faso through analysis of remotely-sensed and rainfall data from 1975–2011. Discussions with farmers and land management staff have helped to understand the anthropogenic efforts toward soil restoration to enable the subsistence farming agriculture. Results showed that area of barren land has been fluctuating during the study period with approximately 10-year cyclicity. Similarly, rainfall, both at national and local levels has followed the same trends. The trends of the area of barren land and rainfall variability suggest that when rainfall increases, the area of barren land decreases and barren land increases when rainfall decreases. This implies that rainfall is one of the main factors driving the change in area of barren land. In addition, humans have contributed positively and negatively to the change by restoring barren lands for agriculture using locally known techniques and by accelerating land degradation through intensive and inappropriate land use practices.
Soil water retention curves for the major soil types of the Kruger National Park
Steven I. Higgins
- Soil water potential is crucial to plant transpiration and thus to carbon cycling and biosphere–atmosphere interactions, yet it is difficult to measure in the field. Volumetric and gravimetric water contents are easy and cheap to measure in the field, but can be a poor proxy of plant-available water. Soil water content can be transformed to water potential using soil moisture retention curves. We provide empirically derived soil moisture retention curves for seven soil types in the Kruger National Park, South Africa. Site-specific curves produced excellent estimates of soil water potential from soil water content values. Curves from soils derived from the same geological substrate were similar, potentially allowing for the use of one curve for basalt soils and another for granite soils. It is anticipated that this dataset will help hydrologists and ecophysiologists understand water dynamics, carbon cycling and biosphere–atmosphere interactions under current and changing climatic conditions in the region.
Sensitivity of simulated global-scale freshwater fluxes and storages to input data, hydrological model structure, human water use and calibration
Hannes Müller Schmied
Felix Theodor Portmann
- Global-scale assessments of freshwater fluxes and storages by hydrological models under historic climate conditions are subject to a variety of uncertainties. Using the global hydrological model WaterGAP 2.2, we investigated the sensitivity of simulated freshwater fluxes and water storage variations to five major sources of uncertainty: climate forcing, land cover input, model structure, consideration of human water use and calibration (or no calibration). In a modelling experiment, five variants of the standard version of WaterGAP 2.2 were generated that differed from the standard version only regarding the investigated source of uncertainty. Sensitivity was analyzed by comparing water fluxes and water storage variations computed by the variants to those of the standard version, considering both global averages and grid cell values for the time period 1971–2000. The basin-specific calibration approach for WaterGAP, which forces simulated mean annual river discharge to be equal to observed values at 1319 gauging stations (representing 54% of global land area except Antarctica and Greenland), has the highest effect on modelled water fluxes and leads to the best fit of modelled to observed monthly and seasonal river discharge. Alternative state-of-the-art climate forcings rank second regarding the impact on grid cell specific fluxes and water storage variations, and their impact is ubiquitous and stronger than that of alternative land cover inputs. The diverse model refinements during the last decade lead to an improved fit to observed discharge, and affect globally averaged fluxes and storage values (the latter mainly due to modelling of groundwater depletion) but only affect a relatively small number of grid cells. Considering human water use is important for the global water storage trend (in particular in the groundwater compartment) but impacts on water fluxes are rather local and only important where water use is high. The best fit to observed time series of monthly river discharge (Nash–Sutcliffe criterion) or discharge seasonality is obtained with the standard WaterGAP 2.2 model version which is calibrated and driven by a sequence of two time series of daily observation-based climate forcings, WFD/WFDEI. Discharge computed by a calibrated model version using monthly CRU 3.2 and GPCC v6 climate input reduced the fit to observed discharge for most stations. Taking into account the investigated uncertainties of climate and land cover data, we estimate that the global 1971–2000 discharge into oceans and inland sinks is between 40 000 and 42 000 km3 yr−1. The range is mainly due differences in precipitation data that affect discharge in uncalibrated river basins. Actual evapotranspiration, with approximately 70 000 km3 yr−1, is rather unaffected by climate and land cover in global sum but differs spatially. Human water use is calculated to reduce river discharge by approximately 1000 km3 yr−1. Thus, global renewable water resources are estimated to range between 41 000 and 43 000 km3 yr−1. The climate data sets WFD (available until 2001) and WFDEI (starting in 1979) were found to be inconsistent with respect to short wave radiation data, resulting in strongly different potential evapotranspiration. Global assessments of freshwater fluxes and storages would therefore benefit from the development of a global data set of consistent daily climate forcing from 1900 to current.
Knowledge, Attitude and Practice Regarding Dengue Fever among the Healthy Population of Highland and Lowland Communities in Central Nepal
Krishna Kumar Aryal
Mandira Lamichhane Dhimal
Shanker Pratap Singh
Chop Lal Bhusal
- BACKGROUND: Dengue fever (DF) is the most rapidly spreading mosquito-borne viral disease in the world. In this decade it has expanded to new countries and from urban to rural areas. Nepal was regarded DF free until 2004. Since then dengue virus (DENV) has rapidly expanded its range even in mountain regions of Nepal, and major outbreaks occurred in 2006 and 2010. However, no data on the local knowledge, attitude and practice (KAP) of DF in Nepal exist although such information is required for prevention and control measures.
METHODS: We conducted a community based cross-sectional survey in five districts of central Nepal between September 2011 and February 2012. We collected information on the socio-demographic characteristics of the participants and their knowledge, attitude and practice regarding DF using a structured questionnaire. We then statistically compared highland and lowland communities to identify possible causes of observed differences.
PRINCIPAL FINDINGS: Out of 589 individuals interviewed, 77% had heard of DF. Only 12% of the sample had good knowledge of DF. Those living in the lowlands were five times more likely to possess good knowledge than highlanders (P<0.001). Despite low knowledge levels, 83% of the people had good attitude and 37% reported good practice. We found a significantly positive correlation among knowledge, attitude and practice (P<0.001). Among the socio-demographic variables, the education level of the participants was an independent predictor of practice level (P<0.05), and education level and interaction between the sex and age group of the participants were independent predictors of attitude level (P<0.05).
CONCLUSION: Despite the rapid expansion of DENV in Nepal, the knowledge of people about DF was very low. Therefore, massive awareness programmes are urgently required to protect the health of people from DF and to limit its further spread in this country.
Medicanes in an ocean–atmosphere coupled regional climate model
- So-called medicanes (Mediterranean hurricanes) are meso-scale, marine, and warm-core Mediterranean cyclones that exhibit some similarities to tropical cyclones. The strong cyclonic winds associated with medicanes threaten the highly populated coastal areas around the Mediterranean basin. To reduce the risk of casualties and overall negative impacts, it is important to improve the understanding of medicanes with the use of numerical models. In this study, we employ an atmospheric limited-area model (COSMO-CLM) coupled with a one-dimensional ocean model (1-D NEMO-MED12) to simulate medicanes. The aim of this study is to assess the robustness of the coupled model in simulating these extreme events. For this purpose, 11 historical medicane events are simulated using the atmosphere-only model, COSMO-CLM, and coupled model, with different setups (horizontal atmospheric grid-spacings of 0.44°, 0.22°, and 0.08°; with/without spectral nudging, and an ocean grid-spacing of 1/12°). The results show that at high-resolution, the coupled model is able to not only simulate most of medicane events but also improve the track length, core temperature, and wind speed of simulated medicanes compared to the atmosphere-only simulations. The results suggest that the coupled model is more proficient for systemic and detailed studies of historical medicane events, and that this model can be an effective tool for future projections.
Progress in DGVMs: a comment on "Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis" by Verheijen et al. (2013)
Steven I. Higgins
Deriving an atmospheric budget of total organic bromine using airborne in-situ measurements from the Western Pacific during SHIVA
Dave E. Oram
- During the SHIVA (Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere) project an extensive dataset of all halogen species relevant for the atmospheric budget of total organic bromine has been collected in the West Pacific region using the FALCON aircraft operated by the German Aerospace agency DLR (Deutsches Zentrum für Luft- und Raumfahrt) covering a vertical range from the planetary boundary layer up to the ceiling altitude of the aircraft of 13 km. In total, more than 700 measurements were performed with the newly developed fully-automated in-situ instrument GHOST-MS (Gas cHromatograph for the Observation of Tracers – coupled with a Mass Spectrometer) by the Goethe University of Frankfurt (GUF) and with the onboard whole-air sampler WASP with subsequent ground based state-of-the-art GC/MS analysis by the University of East Anglia (UEA). Both instruments yield good agreement for all major (CHBr3 and CH2Br2) and minor (CHBrCl, CHBrCl2 and CHBr2Cl) VSLS (very short-lived substances), at least at the level of their 2 σ measurement uncertainties. In contrast to the suggestion that the Western Pacific could be a major source region for VSLS (Pyle et al., 2011), we found only slightly enhanced mixing ratios of brominated halogen source gases relative to the levels reported in Montzka et al. (2011) for other tropical regions. A budget for total organic bromine, including all four halons,CH3Br and the VSLS, is derived for the upper troposphere, the input region for the TTL and thus also for the stratosphere, compiled from the SHIVA dataset. With exception of the two minor VSLS CHBrCl2 and CHBr2Cl, excellent agreement with the values reported in Montzka et al. (2011) is found, while being slightly higher than previous studies from our group based on balloon-borne measurements.
Gridding of station observations by means of hybrid interpolation
- Gridded maps of meteorological variables are needed for the evaluation of weather and climate models and for climate change monitoring. In order to produce them, values at locations where no observing stations are available need to be estimated from point-wise observations. For the interpolation of meteorological observations deterministic and stochastic methods are often combined. Deterministic methods can account for ancillary information such as elevation, continentality or satellite observations. Stochastic methods such as kriging reproduce observed values at the station locations and also account for spatial variability. In the first two studies of this thesis, a flexible interpolation method for the gridding of locally observed daily extreme temperatures is developed that also provides an optimal estimate of the interpolation ncertainty. In the third study, an observational dataset is created using this interpolation method and then applied to evaluate a climate simulation for Africa.
In the first study, the Regression-Kriging-Kriging (RKK) method is tested for the interpolation of daily minimum and maximum temperatures (Tmin and Tmax) in different regions in Europe. RKK accounts for elevation, continentality index and zonal mean temperature and is applicable in regions of differing station density and climate. The accuracy of RKK is compared to Inverse Distance Weighting, a common deterministic interpolation method, and to Ordinary Kriging, a common stochastic interpolation method. The first step in RKK is to use regression kriging, in which multiple linear regression accounts for topographical effects on the temperature field and kriging minimizes the regression error, to interpolate climatological means. In the second step daily deviations from the monthly climatology are interpolated using simple kriging. Owing to the large climatological differences across the investigation area the interpolation is performed in homogeneous subregions defined according to the Köppen-Geiger climate classification. Cross validation demonstrates the superiority of RKK over the simpler algorithms in terms of accuracy and preservation of spatial variability. The interpolation performance however strongly varies across Europe, being considerably higher over Central Europe (highest station density) than over Greenland (few stations along the coast line). This illustrates the strong impact of the station density on the accuracy of the interpolation result. Satellites provide comprehensive observations of climate variables such as land surface temperature (LST) and cloud cover (CC). However, LST is associated with high uncertainty (standard error ~ 1-2°C), preventing its direct application in meteorology and climatology. The second study investigates the usefulness of LST and CC as predictors for the gridding of daily Tmin and Tmax. The RKK algorithm is compared with similar interpolation methods that apply LST and CC in addition to the predictors used with the RKK algorithm. The investigation is conducted in two regions, Central Europe and the Iberian Peninsula, which differ strongly in average cloud cover (Central Europe is approximately 30% cloud free and the Iberian Peninsula approximately 60 % cloud free). RKKLST (in which monthly mean LST is used as an additional predictor) yields for Central Europe no clear improvement over RKK, yet it reduces the interpolation error over the Iberian Peninsula. This finding can be explained by the higher percentage of cloud free pixels over that region in summer which enables a more robust determination of monthly mean LST. Adding a regression step for daily anomalies (using the predictor CC) yields the RKRK method and improves the preservation of spatial variability over the Iberian Peninsula. Moreover, a successive reduction of the station number (from 140 to 10 stations) reveals an increasing superiority of RKKLST and RKRK over RKK in both regions.
The application of a gridded observational dataset for climate monitoring or climate model validation requires knowledge of the uncertainties associated with the dataset. The estimation of the interpolation uncertainty, here the inter quartile range is the used uncertainty measure, is therefore an important issue within the frame of this thesis. By means of cross validation it is shown that the largest uncertainties occur in regions of low station density (e.g. Greenland), in mountainous regions and along coastlines (in these regions model evaluation results should be interpreted carefully). The magnitude of the interpolation error mainly depends on the station density, while the complexity of terrain has substantially less influence. On average over all regions and investigation days the target precision of the uncertainty estimate is reached. However, on local scales and for single days it can be clearly over- or underestimated. The application of satellite-derived predictors (LST and CC) yields no noteworthy improvement of the uncertainty estimate.
In the last study two regional climate simulations for Africa using the ERA-Interim driven COSMO-CLM (CCLM) model at two different horizontal resolutions (0.22° and 0.44°) are validated. It is assessed whether observed patterns and statistical properties of daily Tmin and Tmax are correctly represented in the model. The ERA-Interim reanalysis and a specially created observational dataset are used as reference. The observational dataset is generated by applying the RKRK algorithm (developed within the second study). The investigations show an occasionally large bias in Tmin and Tmax. The hemispheric summers are generally too warm and the temporal variability in temperature is too high, particularly over extra tropical Africa. The diurnal temperature range is overestimated by about 2°C in the northern subtropics but underestimated by about 2°C over large parts of the African tropics. CCLM reproduces the observed frequency distribution of daily Tmin and Tmax in all African climate regions, and the extreme values in the lower percentiles (5, 10, 20%) for Tmin are well simulated. The higher percentiles (80, 90, 95%) for Tmax are however overestimated by 2-5°C. For both Tmin and Tmax the 0.22° simulation is on average 0.5°C warmer than the 0.44° simulation. Additionally, the higher percentiles are about 1°C warmer for both Tmin and Tmax in the higher resolution run, while the lower percentiles in both runs match very well. Although the temperature pattern is represented in more detail along the coastlines and in topographically complex regions, the higher resolution simulation yields no qualitative improvement.
To summarize, the choice of the appropriate algorithm mainly depends on the interpolation conditions. In cases where the station density is high across the target region and the predictor space is adequately covered by observing stations, the computationally less demanding RK algorithm should be preferred. In regions where the station density is low the more robust RKRK algorithm should be the first choice. Due to the strong physical relation of both CC and LST to Tmin and Tmax the missing information is at least partially compensated for. The estimation of the interpolation uncertainty could be improved by applying a normal score transformation to the data prior to a kriging step. This is because the kriging assumption that the increments of the variable of interest are second order stationary can be approximately met by a normal score transformation.
A Satellite-Based Surface Radiation Climatology Derived by Combining Climate Data Records and Near-Real-Time Data
- 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.