Gradient in the climate change signal of European discharge predicted by a multi-model ensemble

In order to perform hydrological studies on the PRUDENCE regional climate model (RCM) simulations, a special focus was put on the discharge from large river catchments located in northern and central Europe. The discharge was simulated with a simplified land surface (SL) scheme and the Hydrological Discharge (HD) model. The daily fields of precipitation, 2 m temperature and evapotranspiration from the RCM simulations were used as forcing. Therefore the total catchment water balances are constrained by the hydrological cycle of the different RCMs. The validation of the simulated hydrological cycle from the control simulations shows that the multi-model ensemble mean is closer to the observations than each of the models, especially if different catchments and hydrological variables are considered. Therefore, the multi-model ensemble mean can be used to largely reduce the uncertainty that is introduced by a single RCM. This also provides more confidence in the future projections for the multi-model ensemble means. The scenario simulations predict a gradient in the climate change signal over Northern and Central Europe. Common features are the overall warming and the general increase of evapotranspiration. But while in the northern parts the warming will enhance the hydrological cycle leading to an increased discharge, the large warming, especially in the summer, will slow down the hydrological cycle caused by a drying in the central parts of Europe which is accompanied by a reduction of discharge. The comparison of the changes predicted by the multi-model ensemble mean to the changes predicted by the driving GCM indicates that the RCMs can compensate problems that a driving GCM may have with local scale processes or parameterizations.     

X‐ray fluorescence measurements of the surface elemental composition of asteroid 433 Eros

Abstract— We report major element ratios determined for the S‐class asteroid 433 Eros using remote‐sensing x‐ray fluorescence spectroscopy with the near‐Earth asteroid rendezvous Shoemaker x‐ray spectrometer (XRS). Data analysis techniques and systematic errors are described in detail. Data acquired during five solar flares and during two extended “quiet Sun” periods are presented; these results sample a representative portion of the asteroid's surface. Although systematic uncertainties are potentially large, the most internally consistent and plausible interpretation of the data is that Eros has primitive Mg/Si, Al/Si, Ca/Si and Fe/Si ratios, closely similar to H or R chondrites. Global differentiation of the asteroid is ruled out. The S/Si ratio is much lower than that of chondrites, probably reflecting impact‐induced volatilization and/or photo‐ or ion‐induced sputtering of sulfur at the surface of the asteroid. An alternative explanation for the low S/Si ratio is that it reflects a limited degree of melting with loss of an FeS‐rich partial melt. Size‐sorting processes could lead to segregation of Fe‐Ni metal from silicates within the regolith of Eros; this could indicate that the Fe/Si ratios determined by the x‐ray spectrometer are not representative of the bulk Eros composition.     

Integrated models,scenarios and dynamics of climate,land use and common birds

Reconciling food, fiber and energy production with biodiversity conservation is among the greatest challenges of the century, especially in the face of climate change. Model-based scenarios linking climate, land use and biodiversity can be exceptionally useful tools for decision support in this context. We present a modeling framework that links climate projections, private land use decisions including farming, forest and urban uses and the abundances of common birds as an indicator of biodiversity. Our major innovation is to simultaneously integrate the direct impacts of climate change and land use on biodiversity as well as indirect impacts mediated by climate change effects on land use, all at very fine spatial resolution. In addition, our framework can be used to evaluate incentive-based conservation policies in terms of land use and biodiversity over several decades. The results for our case study in France indicate that the projected effects of climate change dominate the effects of land use on bird abundances. As a conservation policy, implementing a spatially uniform payment for pastures has a positive effect in relatively few locations and only on the least vulnerable bird species.     

Water chemistry and hydrometeorology in a glacierized catchment in the Polar Urals,Russia

This study aims to determine the relationships between local meteorological conditions,proglacial river discharge and biogeochemical processes operating in a periglacial basin located in the Polar Ural mountain range, Russia. Fieldwork was conducted in the catchment of Obruchev Glacier(13 km2) during the summer peak flow period in 2008. River discharge was dominated by snowmelt and changed from 3300 l s-1 to less than 1000 l s-1. The mean daily air temperatures of stations situated in the mountain tundra and near Obruchev Glacier from July 11 th to August 1st 2008 were 14.4°C and 10.3°C, respectively. The glacial river had low total dissolved solids varying from 4.5 to 9 mg l-1 and coefficients of correlation between Na+ and Cl-, K+ and Cl-, as well as NH4+ and Cl- were 0.94, 0.90 and 0.84, respectively. Rainfall events affected the snowmelt initiation and provided an essential part of the discharge during the intense snowmelt period, which occurred from July 11 th to July 18 th 2008. Data showed that Na+ and K+ in the surface water derived from snowmelt rather than chemical weathering of silicates. Also, it was obtained that NO3- derived from the melting snowpack, whereas ammonification occurring under the snowpacks was the primary source for NH4+.     

Soil Loss Mapping for Sustainable Development and Management of Land Resources in Warora Tehsil of Chandrapur District of Maharashtra: An Integrated Approach Using Remote Sensing and GIS

The study area is characterized by low and fluctuating rainfall pattern, thin soil cover, predominantly rain-fed farming with low productivity coupled with intensive mining activities, urbanization, deforestation, wastelands and unwise utilization of natural resources causing human induced environmental degradation and ecological imbalances, that warrant sustainable development and optimum management of land resources. Spatial information related to existing geology, land use/land cover, physiography, slope and soils has been derived through remote sensing, collateral data and field survey and used as inputs in a widely used erosion model (Universal Soil Loss Equation) in India to compute soil loss (t/ha/yr) in GIS. The study area has been delineated into very slight (<5 t/ha/yr), slight (5–10 t/ha/yr), moderate (10–15 t/ha/yr), moderately severe (15–20 t/ha/yr), severe (20–40 t/ha/yr) and very severe (>40 t/ha/yr) soil erosion classes. The study indicate that 45.4 thousand ha. (13.7% of TGA) is under moderate, moderately severe, severe and very severe soil erosion categories. The physiographic unit wise analysis of soil loss in different landscapes have indicated the sensitive areas, that has helped to prioritize development and management plans for soil and water conservation measures and suitable interventions like afforestation, agro-forestry, agri-horticulture, silvipasture systems which will result in the improvement of productivity of these lands, protect the environment from further degradation and for the ecological sustenance.     

The role of the simulation setup in a long-term high-resolution climate change projection for the southern African region

High-resolution regional climate change simulations have proven to offer an added value compared to available global climate model simulations. However, over many regions of the globe, long-term high-resolution climate change projections are rather sparse. We present a transient high-resolution climate change projection with the regional climate model with the regional climate model REMO over the southern African region, following the SRES A1B emission scenario. The simulation was conducted at 18?km grid spacing for the period from 1960 to 2100, making it to the longest available climate change projection at such a high resolution for the region. In the first part of the study, we focus on the impact of the model setup on the simulated rainfall over the southern African region. In the standard setup, we used the output of the global climate model ECHAM5/MPIOM directly to force REMO. This setup led to a very strong wet bias over the region. Changing it to the double-nesting setup significantly reduced this bias, but a substantial wet bias still persists. The remaining bias could partly be attributed to a warm bias in the SST forcing over the southern Atlantic Ocean. Thus, we applied an SST correction based on the anomaly approach to the data, which led to a further improvement of the rainfall simulation. As the SST bias in the southern Atlantic is a common feature of all global climate models assessed by the IPCC, we recommend the chosen model setup, including the SST correction, as general procedure for dynamical downscaling studies over the southern African region. In the second part, we present the projected spatial and temporal changes of temperature and precipitation, including several rainfall characteristics, over the southern African region. Herby we compare the projections of the high-resolution REMO simulation to those of the forcing regional and global models. We generally find that for temperature the magnitude of the projected changes of the regional model only slightly differs from the GCM projection; however, the spatial patterns are much better resolved in the RCM projections. For precipitation, REMO shows a more intense drying toward the end of the twenty-first century than it is simulated by the global model. This can have a major influence when investigating the impacts of future climate change on a regional or even local scale. In combination with the improved spatial patterns, the application of high-resolution climate change information could therefore improve the results of such applications.