Alpine snow cover in a changing climate: a regional climate model perspective

An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951–2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971–2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000 m and overestimate snow above 1,500 m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500 m, amounting to 40–80 % by mid century relative to 1971–2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000–2,500 m, SWE reductions amount to 10–60 % by mid century and to 30–80 % by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800 m by mid century, and at elevations below about 2,000 m by the end of the century.     

The MEMIN research unit: Scaling impact cratering experiments in porous sandstones

Abstract– The MEMIN research unit (Multidisciplinary Experimental and Modeling Impact research Network) is focused on analyzing experimental impact craters and experimental cratering processes in geological materials. MEMIN is interested in understanding how porosity and pore space saturation influence the cratering process. Here, we present results of a series of impact experiments into porous wet and dry sandstone targets. Steel, iron meteorite, and aluminum projectiles ranging in size from 2.5 to 12 mm were accelerated to velocities of 2.5–7.8 km s^?1, yielding craters with diameters between 3.9 and 40 cm. Results show that the target’s porosity reduces crater volumes and cratering efficiency relative to nonporous rocks. Saturation of pore space with water to 50% and 90% increasingly counteracts the effects of porosity, leading to larger but flatter craters. Spallation becomes more dominant in larger‐scale experiments and leads to an increase in cratering efficiency with increasing projectile size for constant impact velocities. The volume of spalled material is estimated using parabolic fits to the crater morphology, yielding approximations of the transient crater volume. For impacts at the same velocity these transient craters show a constant cratering efficiency that is not affected by projectile size.     

Detection of the Kuiper bands in the spectrum of Titan

3ew spectra of Titan centered at 7500 Å, at resolutions of 4 and 1 Å are presented. Weak absorptions coincident with features observed in the spectra of Uranus and Neptune are found. This observation suggests methane abundances in excess of 1 km-am, thereby emphasizing the complexity of line formation in Titan's atmosphere. The question of the total atmospheric pressure of Titan must be reexamined.     

气候变化背景下欧洲中部水资源供给的不稳定性评估——以易北河流域为例

 欧洲中部的易北河流域是典型的湿润半湿润地区。夏季的水资源供给是限制农业生产的因素之一,特别是在具有较高农业生产力水平,而年降水量只有500 mm的黄土地区。通过总结气候变化与水文循环（GLOWA-Elbe）项目第一阶段的成果,根据气候和土地利用变化的各种情景并考虑其不确定性,对未来50 a德国易北河流域水资源供给稳定性作出综合评估。研究表明,欧洲中部必须从自然和社会角度应对未来气候变化情景下产生水资源供给短缺的可能情况。     

Generation and evaluation of multitemporal digital terrain models of the Mt. Everest area from different optical sensors

Multitemporal digital terrain models (DTM) are an important source for many purposes such as the detection of areas, which are susceptible to natural hazards such as landslides and glacial lake outburst floods, or for the examination of changes in glacier thickness. To exploit the potential of stereo satellite and aerial imagery for time series analysis, the employed methodology and software can be critical. A statistical analysis based on quartiles is presented to eliminate the influence of registration and elevation errors in DTMs. For our analysis, we used multi-temporal airborne and spaceborne stereoscopic images. The oldest images were recorded in the 1960s by the US American reconnaissance satellite Corona, while the most recent imagery are 2007 Cartosat-1 stereo scenes, along with one ASTER stereo pair. Complex panoramic distortion and limited spatial resolution resulted in the Corona and ASTER DTMs having the highest RMSEz. Due to differing acquisition techniques, applied software packages and temporal differences DTMs will never be identical. Therefore, we propose a relative vertical accuracy assessment with a master DTM. We chose the Cartosat-1 DTM as it showed the highest absolute accuracy. Inaccuracies between the master and the slave DTMs were adjusted by means of trend surfaces and outliers were successfully eliminated applying the interquartile range.     

Multi-source spatial data-based invasion risk modeling of Striga (Striga asiatica) in Zimbabwe

ABSTRACT

Monitoring of destructive invasive weeds such as those from the genus Striga requires accurate, near real-time predictions and integrated assessment techniques to enable better surveillance and consistent assessment initiatives. Thus, in this study, we predicted the potential ecological niche of Striga (Striga asiatica) weed in Zimbabwe, to identify and understand its propagation and map potentially vulnerable cropping areas. Vegetation phenology from remote sensing, bioclimatic and other environmental variables (i.e. cropping system, edaphic, land surface temperature, and terrain) were used as predictors. Six machine learning modeling techniques and the ensemble model were evaluated on their suitability to predict current and future Striga weed distributional patterns. The mentioned predictors (n = 40) were integrated into six models with “presence-only” training and evaluation data, collected in Zimbabwe over the period between the 12^th and 28^th of March 2018. The area under the curve (AUC) and true skill statistic (TSS) were used to measure the performance of the Striga modeling framework. The results showed that the ensemble model had the strongest Striga occurrence predictive power (AUC = 0.98; TSS = 0.93) when compared to the other modeling algorithms. Temperature seasonality (Bio4), the maximum temperature of the warmest month (Bio5) and precipitation seasonality (Bio15) were determined to be the most dominant bioclimatic variables influencing Striga occurrence. “Start of the season” and “season minimum value” of the “Enhanced Vegetation Index base value” were the most relevant remote sensing-based variables. Based on projected climate change scenarios, the study showed that up to 2050, the suitable area for Striga propagation will increase by ~ 0.73% in Zimbabwe. The present work demonstrated the importance of integrating multi-source data in predicting possible crop production restraints due to weed propagation. The results can enhance national preparedness and management strategies, specifically, if the current and future risk areas can be identified for early intervention and containment     

Simulations of VLBI observations of a geodetic satellite providing co-location in space

We performed Monte Carlo simulations of very-long-baseline interferometry (VLBI) observations of Earth-orbiting satellites incorporating co-located space-geodetic instruments in order to study how well the VLBI frame and the spacecraft frame can be tied using such measurements. We simulated observations of spacecraft by VLBI observations, time-of-flight (TOF) measurements using a time-encoded signal in the spacecraft transmission, similar in concept to precise point positioning, and differential VLBI (D-VLBI) observations using angularly nearby quasar calibrators to compare their relative performance. We used the proposed European Geodetic Reference Antenna in Space (E-GRASP) mission as an initial test case for our software. We found that the standard VLBI technique is limited, in part, by the present lack of knowledge of the absolute offset of VLBI time to Coordinated Universal Time at the level of microseconds. TOF measurements are better able to overcome this problem and provide frame ties with uncertainties in translation and scale nearly a factor of three smaller than those yielded from VLBI measurements. If the absolute time offset issue can be resolved by external means, the VLBI results can be significantly improved and can come close to providing 1 mm accuracy in the frame tie parameters. D-VLBI observations with optimum performance assumptions provide roughly a factor of two higher uncertainties for the E-GRASP orbit. We additionally simulated how station and spacecraft position offsets affect the frame tie performance.     

Land cover mapping in the Upper Shire River catchment in Malawi using Landsat satellite data

Land cover mapping forms a reference base for resource managers in their decision-making processes to guide rural/urban growth and management of natural resources. The aim of this study was to map land cover dynamics within the Upper Shire River catchment, Malawi. The article promotes innovation of automated land cover mapping based on remote sensing information to generate data products that are both appropriate to, and usable within different scientific applications in developing countries such as Malawi. To determine land cover dynamics, 1989 and 2002 Landsat images were used. Image bands were combined in transformations and indices with physical meaning; together with spatial data, to enhance classification accuracy. A maximum likelihood classification for each image was computed for identification of land cover variables. The results showed that the combination of spatial and digital data enhanced classification accuracy and the ability to categorise land cover features, which are relatively inhomogeneous.     

Troposphere delays from space geodetic techniques, water vapor radiometers, and numerical weather models over a series of continuous VLBI campaigns

Continuous, very long baseline interferometry (VLBI) campaigns over 2 weeks have been carried out repeatedly, i.e., CONT02 in October 2002, CONT05 in September 2005, CONT08 in August 2008, and CONT11 in September 2011, to demonstrate the highest accuracy the current VLBI was capable at that time. In this study, we have compared zenith total delays (ZTD) and troposphere gradients as consistently estimated from the observations of VLBI, Global Navigation Satellite Systems (GNSS), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) at VLBI sites participating in the CONT campaigns. We analyzed the CONT campaigns using the state-of-the-art software following common processing strategies as closely as possible. In parallel, ZTD and gradients were derived from numerical weather models, i.e., from the global European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields, the High Resolution Limited Area Model (European sites), the Japan Meteorological Agency-Operational Meso-Analysis Field (MANAL, over Japan), and the Cloud Resolving Storm Simulator (Tsukuba, Japan). Finally, zenith wet delays were estimated from the observations of water vapor radiometers (WVR) at sites where the WVR observables are available during the CONT sessions. The best ZTD agreement, interpreted as the smallest standard deviation, was found between GNSS and VLBI techniques to be about 5–6 mm at most of the co-located sites and CONT campaigns. We did not detect any significant improvement in the ZTD agreement between various techniques over time, except for DORIS and MANAL. On the other hand, the agreement and thus the accuracy of the troposphere parameters mainly depend on the amount of humidity in the atmosphere.