Search results for "PAT"

Plio-Pleistocene Dust Traps on Paleokarst Surfaces: A Case Study From the Carpathian Basin

2020

Plio-Pleistocene silt/clay-rich deposits and paleo-karst fissure sediments from sites of the northern and southern parts of the Carpathian Basin were investigated. These materials were supposed to be mixed during transport before being captured in karstified fissures. Evidence that the eolian fissure sediments of Plio-Pleistocene age in the older Triassic–Cretaceous limestones are derived from eolian silt and clay includes compositional and textural matches, especially decreasing grain-size trends observed downwards from the paleo-surface of the former landscape. Various environmental factors could be recognized by the statistical evaluation of grain-size distribution curves of fissure fill…

Strategies for Disease Prevention and Health Promotion in Urban Areas: The Erice 50 Charter

2018

A review of mental health and wellbeing under climate change in small island developing states (SIDS)

2021

AbstractSmall island developing states (SIDS) are often at the forefront of climate change impacts, including those related to health, but information on mental health and wellbeing is typically underreported. To help address this research lacuna, this paper reviews research about mental health and wellbeing under climate change in SIDS. Due to major differences in the literature’s methodologies, results, and analyses, the method is an overview and qualitative evidence synthesis of peer-reviewed publications. The findings show that mental health and wellbeing in the context of climate change have yet to feature prominently and systematically in research covering SIDS. It seems likely that m…

Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

2021

The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (altitude, slope degree, profile curvature, distance to river, aspect, plan curvature, distance to road, distance to fault, rainfall, geology and land-sue) to construct a geospatial database and divided the data into the training and the testing dataset. We then d…

Modified climate with long term memory in tree ring proxies

2015

ABSTRACT : A contribution to the PAGES Asia2k Working Group. ABSTRACT: Long term memory (LTM) scaling behavior in worldwide tree ring proxies and subsequent climate reconstructions is analyzed for and compared with the memory structure inherent to instrumental temperature and precipitation data. Detrended fluctuation analysis is employed to detect LTM and its scaling exponent a is used to evaluate LTM. The results show that temperature and precipitation reconstructions based on ring width measurements (mean \alpha =0.8) contain more memory than records based on maximum latewood density (mean \alpha =0.7). Both exceed the memory inherent to regional instrumental data (\alpha =0.6 for tempera…

2016

The spatial context is criticalwhen assessing present-day climate anomalies, attributing them to potential forcings and making statements regarding their frequency and severity in a long-term perspective. Recent international initiatives have expanded the number of high-quality proxy-records and developed new statistical reconstruction methods. These advances allow more rigorous regional past temperature reconstructions and, in turn, the possibility of evaluating climate models on policy-relevant, spatiotemporal scales. Here we provide a new proxy-based, annually-resolved, spatial reconstruction of the European summer (June-August) temperature fields back to 755 CE based on Bayesian hierarc…

Radiance-based NIRv as a proxy for GPP of corn and soybean

2020

Abstract Substantial uncertainty exists in daily and sub-daily gross primary production (GPP) estimation, which dampens accurate monitoring of the global carbon cycle. Here we find that near-infrared radiance of vegetation (NIRv,Rad), defined as the product of observed NIR radiance and normalized difference vegetation index, can accurately estimate corn and soybean GPP at daily and half-hourly time scales, benchmarked with multi-year tower-based GPP at three sites with different environmental and irrigation conditions. Overall, NIRv,Rad explains 84% and 78% variations of half-hourly GPP for corn and soybean, respectively, outperforming NIR reflectance of vegetation (NIRv,Ref), enhanced vege…

Spatial variability of the relationships of runoff and sediment yield with weather types throughout the Mediterranean basin

2019

Este artículo contiene 16 páginas, 6 figuras, 2 tablas.

Testing simple scaling in soil erosion processes at plot scale

2018

Abstract Explaining scale effects for runoff and erosion improves our understanding and simulation ability of hydrological and erosion processes. In this paper, plot scale effects on event runoff per unit area (Qe), sediment concentration (Ce) and soil loss per unit area (SLe) were checked at El Teularet-Sierra de Enguera experimental site in Eastern Spain. The measurements were carried out for 31 events occurring in the years 2005 and 2007 in bare ploughed plots ranging from 1 to 48 m2. The analysis established the scaling relationship by dimensional analysis and self-similarity theory, and tested this relationship at different temporal scales ranging from event to annual scale. The dimens…

PHYSICS-based retrieval of scattering albedo and vegetation optical depth using multi-sensor data integration

2017

Vegetation optical depth and scattering albedo are crucial parameters within the widely used τ-ω model for passive microwave remote sensing of vegetation and soil. A multi-sensor data integration approach using ICESat lidar vegetation heights and SMAP radar as well as radiometer data enables a direct retrieval of the two parameters on a physics-derived basis. The crucial step within the retrieval methodology is the calculus of the vegetation scattering coefficient KS, where one exact and three approximated solutions are provided. It is shown that, when using the assumption of a randomly oriented volume, the backscatter measurements of the radar provide a sufficient first order estimate and …