Three decades of landslide activity in western Nepal: new insights into trends and climate drivers

In recent decades, landslide disasters in the Himalayas, as in other mountain regions, are widely reported to have increased. While some studies have suggested a link to increasing heavy rainfall under a warmer climate, others pointed to anthropogenic influences on slope stability, and increasing exposure of people and assets located in harm’s way. A lack of sufficiently high-resolution regional landslide inventories, both spatially and temporally, has prevented any robust consensus so far. Focusing on Far-Western Nepal, we draw on remote sensing techniques to create a regional inventory of 26,350 single landslide events, of which 8778 date to the period 1992–2018. These events serve as a basis for the analyses of landslide frequency relationships and trends in relation to precipitation and temperature datasets. Results show a strong correlation between the annual number of shallow landslides and the accumulated monsoon precipitation (r = 0.74). Furthermore, warm and dry monsoons followed by especially rainy monsoons produce the highest incidence of shallow landslides (r = 0.77). However, we find strong spatial variability in the strength of these relationships, which is linked to recent demographic development in the region. This highlights the role of anthropogenic drivers, and in particular road cutting and land-use change, in amplifying the seasonal monsoon influence on slope stability. In parallel, the absence of any long-term trends in landslide activity, despite widely reported increase in landslide disasters, points strongly to increasing exposure of people and infrastructure as the main driver of landslide disasters in this region of Nepal. By contrast, no climate change signal is evident from the data.

     

On the use of logistic regression for stellar classification

We are totally immersed in the Big Data era and reliable algorithms and methods for data classification are instrumental for astronomical research. Random Forest and Support Vector Machines algorithms have become popular over the last few years and they are widely used for different stellar classification problems. In this article, we explore an alternative supervised classification method scarcely exploited in astronomy, Logistic Regression, that has been applied successfully in other scientific areas, particularly biostatistics. We have applied this method in order to derive membership probabilities for potential T Tauri star candidates from ultraviolet-infrared colour-colour diagrams.     

Metallic Mineral Resources in the Twenty-First Century. I. Historical Extraction Trends and Expected Demand

Industrial, technological, and economic developments depend on the availability of metallic raw materials. As a greater fraction of the Earth’s population has become part of developed economies and as developed societies have become more affluent, the demand on metallic mineral resources has increased. Yet metallic minerals are non-renewable natural resources, the supply of which, even if unknown and potentially large, is finite. An analysis of historical extraction trends for eighteen metals, going back to the year 1900, demonstrates that demand of metallic raw materials has increased as a result of both increase in world population and increase in per-capita consumption. These eighteen metals can be arranged into four distinct groups, for each of which it is possible to identify a consistent pattern of per-capita demand as a function of time. These patterns can, in turn, be explained in terms of the industrial and technological applications, and in some cases conventional uses as well, of the metals in each group. Under the assumption that these patterns will continue into the future, and that world population will grow by no more than about 50% by the year 2100, one can estimate the amount of metallic raw materials that will be required to sustain the world’s economy throughout the twenty-first century. From the present until the year 2100, the world can be expected to require about one order of magnitude more metal than the total amount of metal that fueled technological and economic growth between the age of steam and the present day. For most of the metals considered here, this corresponds to 5–10 times the amount of metal contained in proven ore reserves. The two chief driving factors of this expected demand are growth in per-capita consumption and present-day absolute population numbers. World population is already so large that additional population growth makes only a small contribution to the expected future demand of metallic raw materials. It is not known whether or not the amount of metal required to sustain the world’s economy throughout this century exists in exploitable mineral resources. In the accompanying paper, I show that it is nevertheless possible to make statistical inferences about the size distribution of the mineral deposits that will need to be discovered and developed in order to satisfy the expected demand. Those results neither prove nor disprove that the needed resources exist but can be used to improve our understanding of the challenges facing future supply of metallic raw materials.     

A method for checking the quality of geographic metadata based on ISO 19157

With recent advances in remote sensing, location-based services and other related technologies, the production of geospatial information has exponentially increased in the last decades. Furthermore, to facilitate discovery and efficient access to such information, spatial data infrastructures were promoted and standardized, with a consideration that metadata are essential to describing data and services. Standardization bodies such as the International Organization for Standardization have defined well-known metadata models such as ISO 19115. However, current metadata assets exhibit heterogeneous quality levels because they are created by different producers with different perspectives. To address quality-related concerns, several initiatives attempted to define a common framework and test the suitability of metadata through automatic controls. Nevertheless, these controls are focused on interoperability by testing the format of metadata and a set of controlled elements. In this paper, we propose a methodology of testing the quality of metadata by considering aspects other than interoperability. The proposal adapts ISO 19157 to the metadata case and has been applied to a corpus of the Spanish Spatial Data Infrastructure. The results demonstrate that our quality check helps determine different types of errors for all metadata elements and can be almost completely automated to enhance the significance of metadata.     

A paleoenvironmental reconstruction of Laguna Babícora, Chihuahua, Mexico based on ostracode paleoecology and trace element shell chemistry

Paleoecology of Laguna Babícora, Chihuahua, Mexico was reconstructed using ostracode faunal assemblages and shell chemistry. The paleolimnological record is used to show the magnitude of paleoclimatic changes in the area from 25,000 years to the present.Faunal assemblages consist of four species of the genus Limnocythere: L. sappaensis, L. ceriotuberosa, L. bradburyi and L. platyforma, all associated with Candona caudata, Candona patzcuaro and Cypridopsis vidua. A paleosalinity index developed from these assemblages indicates that the lake's salinity fluctuated frequently from oligo- to meso-haline conditions during the last 25,000 years. This pattern and low salinity range are in good agreement with modern TDS (here used as an indicator of salinity) values recorded from 26 wells and one spring from the area (258–975 mg l^–1). To estimate paleotemperature we examined the trace element content (Mg/Ca ratios) from individual valves of L. ceriotuberosa and L. platyforma, the two species most commonly recorded in Laguna Babícora.Shell Mg/Ca ratios of 204 specimens of these two species were used to estimate water temperature (Mg/Ca) by means of experimental standard coefficients. Our data show that paleowater temperature ranged from 5.6–21.3 °C (with 2 values ranging from 0.2–4.8 °C), which suggest a close correlation with atmospheric temperatures around the lake. These results are in good agreement with a modern mean winter temperature (3.5 °C) and mean summer temperature (20 °C) recorded in the area between 1970 and 1980.     

Spatial and temporal changes in dry-snow line altitude on the Antarctic Peninsula

Drastic changes were detected in glacial systems of the Antarctic Peninsula in the last decades. The observed phenomena comprise the disintegration of ice shelves, acceleration and thinning of glaciers, and retreat of glacier fronts. However, due to the lack of consistent systematic observations in particular of the higher parts of the glacial systems, it is difficult to predict further responses of the Antarctic Peninsula glaciers to climatic change. The present paper analyses spatial and temporal variations of changes in the dry-snow line altitude on the Antarctic Peninsula as extracted from a time series (1992–2005) of ERS-1/2 SAR and Envisat ASAR data. Upward changes in dry-snow line altitude were observed in general, and are attributed to extreme high-temperature events impacting the central plateaus of the Antarctic Peninsula and the increasing duration of warming periods. A mean decrease in dry-snow line altitude was detected on the west side of the peninsula and is identified as a response to recorded increase in precipitation and accumulation. These results validate the capability of SAR data for deriving superficial parameters of glaciers to be used as indicators of climatic changes in high-latitude regions where operational restrictions limit conventional meteorological observations.     

Analysis of the precipitation and cloudiness associated with COLs occurrence in the Iberian Peninsula

Summary The Iberian Peninsula is one of the regions in the world with higher occurrence of cut-off low systems (COL). The aim of this paper is to analyse the weather events (rainfall and cloudiness layer) associated to COLs in the Iberian Peninsula with tools not previously used: (a) the use of the new multidecadal COLs database developed by Nieto et al (2005) that permit us to study a 41 years period (1958–1998), (b) the checking of the expected weather events (rainfall and cloudiness layer) associated with COLs in a conceptual model (Winkler et al, 2005) and (c) the extensive use of radiosoundings to analyse convective instability in areas inside and close to the COL. Two points of view are used to make the analysis: (1) a source oriented method, when a particular COL is followed and its associated precipitation and cloudiness is analysed over four quadrants in which Iberia was divided and (2) a receptor oriented method, when the precipitation associated to COLs is analysed in given areas, defined by patterns of precipitation. Results reveal that the precipitation and cloudiness patterns associated to COLs in the conceptual model reproduce quite well the main characteristics found over the Iberian Peninsula. The generalized idea that most of the COLs produce intense convective rainfall is show to be misleading. Convective phenomena are important usually when the centre of the COL is located on the Mediterranean region. Most of the rainfall associated with COLs comes from the baroclinic shield; specially in cases located over the west half of the Iberian Peninsula. It is shown that nearly 30% of COLs do not induce any rainfall; most of them located in the southern half of the Peninsula, and mainly during autumn. Only 30% of COLs produce generalized rainfall over the whole analysed territory, being most of them (about 90%) located over the western half of the Iberian Peninsula.     

Analysis of uncertainties in future climate projections for South America: comparison of WCRP-CMIP3 and WCRP-CMIP5 models

This paper identifies two sources of uncertainties in model projections of temperature and precipitation: internal and inter-model variability. Eight models of WCRP-CMIP3 and WCRP-CMIP5 were compared to identify improvements in the reliability of projections from new generation models. While no significant differences are observed between both datasets, some improvements were found in the new generation models. For example, in summer CMIP5 inter-model variability of temperature was lower over northeastern Argentina, Paraguay and northern Brazil, in the last decades of the 21st century. Reliability of temperature projections from both sets of models is high, with signal to noise ratio greater than 1 over most of the study region. Although no major differences were observed in both precipitation datasets, CMIP5 inter-model variability was lower over northern and eastern Brazil in summer (especially at the end of the 21st century). Reliability of precipitation projections was low in both datasets. However, the signal to noise ratio in new generation models was close to 1, and even greater than 1 over eastern Argentina, Uruguay and southern Brazil in some seasons.