The holstein interglaciation: Time-stratigraphic position and correlation to stable-isotope stratigraphy of deep-sea sediments

Marine molluscan shells from para-type and other loclities of the Holsteinian interglaciation were dated by Th/U and the electron spin resonance (ESR) method to more than 350,000 and 370,000 yr B.P., beyond the limit of Th/U dating. The high age estimate is corroborated by a K/Ar age of 420,000 yr B.P. determined from volcanic ash near the base of the Ariendorf paleosol in the Middle Rhine valley believed to be a pedostratigraphic equivalent of the Holsteinian. Shells from the Herzeele marine unit III, an equivalent of the Wacken (Dömnitz) warm stage in northern France and subsequent to the Holsteinian, revealed ages between 300,000 and 350,000 yr B.P. A correlation of these two warm stages with marine oxygen-isotope stages 11 and 9 on the SPECMAP and CARTUNE time scales is suggested. From the benthic oxygen-isotope record one may infer that no exceptionally high global sea-level rise corresponds to the large transgressions of the Holstein Sea in northern Germany. Therefore, a significant proportion of the transgression was probably the result of an unusually large local glacial-isostatic depression caused by the extreme buildup of ice during the preceding Elster glaciation (stage 12). According to the deep-sea record, it lasted approximately 50% longer than the subsequent cold stage 10. The outstanding soil formation with Braunlehm and the well-developed thermal optimum of the Holsteinian are tentatively related to a phase of minimum sea-ice cover in the Norwegian-Greenland Sea, as deduced from long benthic carbon-isotope records from the central Atlantic.     

Regional climate modelling over complex terrain: an evaluation study of COSMO-CLM hindcast model runs for the Greater Alpine Region

In this study the results of the regional climate model COSMO-CLM (CCLM) covering the Greater Alpine Region (GAR, 4°–19°W and 43°–49°N) were evaluated against observational data. The simulation was carried out as a hindcast run driven by ERA-40 reanalysis data for the period 1961–2000. The spatial resolution of the model data presented is approx. 10 km per grid point. For the evaluation purposes a variety of observational datasets were used: CRU TS 2.1, E-OBS, GPCC4 and HISTALP. Simple statistics such as mean biases, correlations, trends and annual cycles of temperature and precipitation for different sub-regions were applied to verify the model performance. Furthermore, the altitude dependence of these statistical measures has been taken into account. Compared to the CRU and E-OBS datasets CCLM shows an annual mean cold bias of ?0.6 and ?0.7 °C, respectively. Seasonal precipitation sums are generally overestimated by +8 to +23 % depending on the observational dataset with large variations in space and season. Bias and correlation show a dependency on altitude especially in the winter and summer seasons. Temperature trends in CCLM contradict the signals from observations, showing negative trends in summer and autumn which are in contrast to CRU and E-OBS.     

Climate Suitability for Stable Malaria Transmission in Zimbabwe Under Different Climate Change Scenarios

Climate is one factor that determines the potential range of malaria. As such, climate change may work with or against efforts to bring malaria under control. We developed a model of future climate suitability for stable Plasmodium falciparum malaria transmission in Zimbabwe. Current climate suitability for stable malaria transmission was based on the MARA/ARMA model of climatic constraints on the survival and development of the Anopheles vector and the Plasmodium falciparum malaria parasite. We explored potential future geographic distributions of malaria using 16 projections of climate in 2100. The results suggest that, assuming no future human-imposed constraints on malaria transmission, changes in temperature and precipitation could alter the geographic distribution of malaria in Zimbabwe, with previously unsuitable areas of dense human population becoming suitable for transmission. Among all scenarios, the highlands become more suitable for transmission, while the lowveld and areas with low precipitation show varying degrees of change, depending on climate sensitivity and greenhouse gas emission stabilization scenarios, and depending on the general circulation model used. The methods employed can be used within or across other African countries.     

Evaluation of a Photosynthesis-Based Canopy Resistance Formulation in the Noah Land-Surface Model

Accurately representing complex land-surface processes balancing complexity and realism remains one challenge that the weather modelling community is facing nowadays. In this study, a photosynthesis-based Gas-exchange Evapotranspiration Model (GEM) is integrated into the Noah land-surface model replacing the traditional Jarvis scheme for estimating the canopy resistance and transpiration. Using 18-month simulations from the High Resolution Land Data Assimilation System (HRLDAS), the impact of the photosynthesis-based approach on the simulated canopy resistance, surface heat fluxes, soil moisture, and soil temperature over different vegetation types is evaluated using data from the Atmospheric Radiation Measurement (ARM) site, Oklahoma Mesonet, 2002 International H₂O Project (IHOP_2002), and three Ameriflux sites. Incorporation of GEM into Noah improves the surface energy fluxes as well as the associated diurnal cycle of soil moisture and soil temperature during both wet and dry periods. An analysis of midday, average canopy resistance shows similar day-to-day trends in the model fields as seen in observed patterns. Bias and standard deviation analyses for soil temperature and surface fluxes show that GEM responds somewhat better than the Jarvis scheme, mainly because the Jarvis approach relies on a parametrised minimum canopy resistance and meteorological variables such as air temperature and incident radiation. The analyses suggest that adding a photosynthesis-based transpiration scheme such as GEM improves the ability of the land-data assimilation system to simulate evaporation and transpiration under a range of soil and vegetation conditions.     

Multi-species chemical data assimilation with the Danish Eulerian hemispheric model: system description and verification

Satellite retrievals of atmospheric composition provide a wealth of data on a global scale. These complement results from atmospheric chemistry-transport models (CTMs), and can be combined using data assimilation. We present two assimilation schemes coupled to the Danish Eulerian Hemispheric Model (DEHM), a three-dimensional, off-line CTM with full photochemistry: a variant on the ensemble Kalman filter and the three-dimensional variational scheme. The aim of this paper is to describe the two schemes and present an initial assessment of their impacts on model skill. Retrievals of multiple atmospheric trace gases are assimilated, namely: NO₂ tropospheric column densities, CH₄ total column densities, and partial column concentrations of O₃, CO and CH₄; these data are retrieved from four satellite sensors. Data for each species are assimilated independently of one another, and other species are only adjusted indirectly via the model’s chemistry and dynamics. Assimilation results are compared with measurements from surface monitoring stations and other satellite retrievals, and preliminary validation results are presented.Reference simulations (without assimilation) grossly underestimate surface CO concentrations, and both assimilation schemes eliminate this large and systematic model bias. The assimilation improves the spatial correlation of modelled CO with surface observations, and improves the spatial correlation between forecasts and retrievals for CO, NO₂ and O₃. Results for CH₄ show a loss of skill due to a mismatch in model bias between two assimilated CH₄ data-sets. Finally, we discuss differences in methodology and results between this paper and a recent study on multi-species chemical data assimilation. Joint optimisation of initial conditions and emission rates offers a promising direction for improving modelled boundary-layer concentrations.     

Response of single benthic metrics and multi-metric methods to anthropogenic pressure gradients, in five distinct European coastal and transitional ecosystems

In recent times many benthic indices have been proposed to assess the ecological quality of marine waters worldwide. In this study we compared single metrics and multi-metric methods to assess coastal and transitional benthic status along human pressure gradients in five distinct environments across Europe: Varna bay and lake (Bulgaria), Lesina lagoon (Italy), Mondego estuary (Portugal), Basque coast (Spain) and Oslofjord (Norway). Hence, 13 single metrics (abundance, number of taxa, and several diversity and sensitivity indices) and eight of the most common indices used within the European Water Framework Directive (WFD) for benthic assessment were selected: index of size spectra (ISS), Benthic assessment tool (BAT), Norwegian quality index (NQI), Multivariate AMBI (M-AMBI), Benthic quality index (BQI), (Benthic ecosystem quality index (BEQI), Benthic index based on taxonomic sufficiency (BITS), and infaunal quality index (IQI). Within each system, sampling sites were ordered in an increasing pressure gradient according to a preliminary classification based on professional judgement. The different indices are largely consistent in their response to pressure gradient, except in some particular cases (i.e. BITS, in all cases, or ISS when a low number of individuals is present). Inconsistencies between indicator responses were most pronounced in transitional waters (i.e. IQI, BEQI), highlighting the difficulties of the generic application of indicators to all marine, estuarine and lagoonal environments. However, some of the single (i.e. ecological groups approach, diversity, richness) and multi-metric methods (i.e. BAT, M-AMBI, NQI) were able to detect such gradients both in transitional and coastal environments, being these multi-metric methods more consistent in the detection than single indices. This study highlights the importance of survey design and good reference conditions for some indicators. The agreement observed between different methodologies and their ability to detect quality trends across distinct environments constitutes a promising result for the implementation of the WFD’s monitoring plans. Moreover, these results have management implications, regarding the dangers of misclassification, uncertainty in the assessment, use of conflicting indices, and testing and validation of indices.     

Exploring the sensitivity of coastal inundation modelling to DEM vertical error

As sea level is projected to rise throughout the twenty-first century due to climate change, there is a need to ensure that sea level rise (SLR) models accurately and defensibly represent future flood inundation levels to allow for effective coastal zone management. Digital elevation models (DEMs) are integral to SLR modelling, but are subject to error, including in their vertical resolution. Error in DEMs leads to uncertainty in the output of SLR inundation models, which if not considered, may result in poor coastal management decisions. However, DEM error is not usually described in detail by DEM suppliers; commonly only the RMSE is reported. This research explores the impact of stated vertical error in delineating zones of inundation in two locations along the Devon, United Kingdom, coastline (Exe and Otter Estuaries). We explore the consequences of needing to make assumptions about the distribution of error in the absence of detailed error data using a 1 m, publically available composite DEM with a maximum RMSE of 0.15 m, typical of recent LiDAR-derived DEMs. We compare uncertainty using two methods (i) the NOAA inundation uncertainty mapping method which assumes a normal distribution of error and (ii) a hydrologically correct bathtub method where the DEM is uniformly perturbed between the upper and lower bounds of a 95% linear error in 500 Monte Carlo Simulations (HBM+MCS). The NOAA method produced a broader zone of uncertainty (an increase of 134.9% on the HBM+MCS method), which is particularly evident in the flatter topography of the upper estuaries. The HBM+MCS method generates a narrower band of uncertainty for these flatter areas, but very similar extents where shorelines are steeper. The differences in inundation extents produced by the methods relate to a number of underpinning assumptions, and particularly, how the stated RMSE is interpreted and used to represent error in a practical sense. Unlike the NOAA method, the HBM+MCS model is computationally intensive, depending on the areas under consideration and the number of iterations. We therefore used the HBM+ MCS method to derive a regression relationship between elevation and inundation probability for the Exe Estuary. We then apply this to the adjacent Otter Estuary and show that it can defensibly reproduce zones of inundation uncertainty, avoiding the computationally intensive step of the HBM+MCS. The equation-derived zone of uncertainty was 112.1% larger than the HBM+MCS method, compared to the NOAA method which produced an uncertain area 423.9% larger. Each approach has advantages and disadvantages and requires value judgements to be made. Their use underscores the need for transparency in assumptions and communications of outputs. We urge DEM publishers to move beyond provision of a generalised RMSE and provide more detailed estimates of spatial error and complete metadata, including locations of ground control points and associated land cover.     

Geomorphologic map of the 1<Superscript>st</Superscript> Mutnaya River,Southeastern Kamchatka,Russia

The Kamchatka Peninsula–situated in the Pacific “Ring of Fire”–has 29 active and over 400 extinct volcanoes. Since it is situated in the northeastern extremity of Russia, in subarctic climate, the volcanic landforms are overprinted by the 446 glaciers. This research focuses on the 1^stMutnaya catchment which drains the southern slopes of two active volcanoes: Avachinsky and Koryaksky. Those volcanoes are a permanent threat for the cities of Petropavlovsk and Elizovo, which are the 2 of 3 cities of the peninsula. Hence, most of the studies carried out in the area dealt with the natural hazards and only few focus on landscape evolution. Thus, the purpose of this study was to elaborate a cartographic approach which integrates classic geomorphology with state of the art GIS and remote sensing techniques. As result, different landforms and related processes have been analysed and included in the first general geomorphologic map of the 1^stMutnaya catchment.