Developing Intensity-Duration-Frequency (IDF) Curves From Satellite-Based Precipitation: Methodology and Evaluation

Given the continuous advancement in the retrieval of precipitation from satellites, it is important to develop methods that incorporate satellite-based precipitation data sets in the design and planning of infrastructure. This is because in many regions around the world, in situ rainfall observations are sparse and have insufficient record length. A handful of studies examined the use of satellite-based precipitation to develop intensity-duration-frequency (IDF) curves; however, they have mostly focused on small spatial domains and relied on combining satellite-based with ground-based precipitation data sets. In this study, we explore this issue by providing a methodological framework with the potential to be applied in ungauged regions. This framework is based on accounting for the characteristics of satellite-based precipitation products, namely, adjustment of bias and transformation of areal to point rainfall. The latter method is based on previous studies on the reverse transformation (point to areal) commonly used to obtain catchment-scale IDF curves. The paper proceeds by applying this framework to develop IDF curves over the contiguous United States (CONUS); the data set used is Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR). IDFs are then evaluated against National Oceanic and Atmospheric Administration (NOAA) Atlas 14 to provide a quantitative estimate of their accuracy. Results show that median errors are in the range of (17–22%), (6–12%), and (3–8%) for one-day, two-day and three-day IDFs, respectively, and return periods in the range (2–100) years. Furthermore, a considerable percentage of satellite-based IDFs lie within the confidence interval of NOAA Atlas 14

Porosity measurements of interstellar ice mixtures using optical laser interference and extended effective medium approximations

Aims. This article aims to provide an alternative method of measuring the porosity of multi-phase composite ices from their refractive indices and of characterising how the abundance of a premixed contaminant (e.g., CO2) affects the porosity of water-rich ice mixtures during omni-directional deposition. Methods. We combine optical laser interference and extended effective medium approximations (EMAs) to measure the porosity of three astrophysically relevant ice mixtures: H2O:CO2=10:1, 4:1, and 2:1. Infrared spectroscopy is used as a benchmarking test of this new laboratory-based method. Results. By independently monitoring the O-H dangling modes of the different water-rich ice mixtures, we confirm the porosities predicted by the extended EMAs. We also demonstrate that CO2 premixed with water in the gas phase does not significantly affect the ice morphology during omni-directional deposition, as long as the physical conditions favourable to segregation are not reached. We propose a mechanism in which CO2 molecules diffuse on the surface of the growing ice sample prior to being incorporated into the bulk and then fill the pores partly or completely, depending on the relative abundance and the growth temperature.Comment: 9 pages, 6 figures, 1 table. Accepted for publication in A&

Reconfiguration and regulation of supply chains and HRM in times of economic crisis

This chapter reviews existing evidence on the reconfiguration and regulation of supply chains and employment relations during times of economic crisis. On the one hand, literature has highlighted pressures towards a degradation of standards as firms seek short-term cost advantages. This view is informed by various perspectives from organization studies to political economy but is united by the idea that structural changes in global capitalism drive how firms relate to their suppliers. On the other hand, it has been argued that counter-pressures range from consumer backlashes to the extension of formal and informal regulation across national boundaries. This undeniably heterogeneous literature has common themes suggesting that global forces may be mediated by existing embedded institutional arrangements at transnational, national and local level, and that there are still open-ended possibilities for social action. This chapter synthesizes and evaluates these two streams and identifies agendas for future research

Adaptive Interaction of Persistent Robots to User Temporal Preferences

Abstract. We look at the problem of enabling a mobile service robot to autonomously adapt to user preferences over repeated interactions in a long-term time frame, where the user provides feedback on every interaction in the form of a rating. We assume that the robot has a discrete and finite set of interaction options from which it has to choose one at every encounter with a given user. We first present three models of users which span the spectrum of possible preference profiles and their dynamics, incorporating aspects such as boredom and taste for change or surprise. Second, given the model to which the user belongs to, we present a learning algorithm which is able to successfully learn the model parameters. We show the applicability of our framework to personalizing light animations on our mobile service robot, CoBot.

Cryopreservation of a soil microbiome using a Stirling 1 cycle approach - a genomic assessment

Soil microbiomes are dynamic systems that respond to biotic and abiotic environmental factors such as those presented at seasonal scales or due to long-term anthropogenic regime shifts. These can affect the composition and function of microbiomes. Investigation of microbiomes can uncover hidden microbial roles in health and disease and discover microbiome-based interventions. Collections of soil samples are kept by various institutions in either a refrigerated or occasionally frozen state, but conditions are not optimised to ensure the integrity of soil microbiome. In this manuscript, we describe cryopreservation with a controlled rate cooler and estimate the genomic content of an exemplar soil sample before and after cryopreservation. The first hypothesis was to test the genomic integrity of the microbiome. We also enriched the soil sample with a liquid medium to estimate the growth of bacteria and compared their growth before and after cryopreservation. Sequence-based rRNA metabarcoding was used to demonstrate that the controlled rate cooler maintains intact the DNA content of the microbiome. Two methods of cryopreservation were applied and compared with control aliquots of soil. An optimised cryopreservation of soil samples is essential for the development of microbiome research in order to retain stable, functionally intact microbiomes. Our results showed that metabarcoding of 16S and ITS rRNA were useful methods to estimate successful cryopreservation. The soil microbiome after enrichment with liquid medium exhibited a similar response of cryopreserved soil and this was estimated with the comparison of the ten most abundant bacterial taxa. These findings support a successful process of cryopreservation and are promising for future use of this technology. To the best of our knowledge, this study is the first report of cryopreservation of soil using a Stirling cycle cooling approach

Environmental DNA illuminates the dark diversity of sharks

In the era of “Anthropocene defaunation,” large species are often no longer detected in habitats where they formerly occurred. However, it is unclear whether this apparent missing, or “dark,” diversity of megafauna results from local species extirpations or from failure to detect elusive remaining individuals. We find that despite two orders of magnitude less sampling effort, environmental DNA (eDNA) detects 44% more shark species than traditional underwater visual censuses and baited videos across the New Caledonian archipelago (south-western Pacific). Furthermore, eDNA analysis reveals the presence of previously unobserved shark species in human-impacted areas. Overall, our results highlight a greater prevalence of sharks than described by traditional survey methods in both impacted and wilderness areas. This indicates an urgent need for large-scale eDNA assessments to improve monitoring of threatened and elusive megafauna. Finally, our findings emphasize the need for conservation efforts specifically geared toward the protection of elusive, residual populations

The UK Crop Microbiome Cryobank: a utility and model for supporting Phytobiomes research

Plant microbiomes are the microbial communities essential to the functioning of the phytobiome—the system that consist of plants, their environment, and their associated communities of organisms. A healthy, functional phytobiome is critical to crop health, improved yields and quality food. However, crop microbiomes are relatively under-researched, and this is associated with a fundamental need to underpin phytobiome research through the provision of a supporting infrastructure. The UK Crop Microbiome Cryobank (UKCMC) project is developing a unique, integrated and open-access resource to enable the development of solutions to improve soil and crop health. Six economically important crops (Barley, Fava Bean, Oats, Oil Seed Rape, Sugar Beet and Wheat) are targeted, and the methods as well as data outputs will underpin research activity both in the UK and internationally. This manuscript describes the approaches being taken, from characterisation, cryopreservation and analysis of the crop microbiome through to potential applications. We believe that the model research framework proposed is transferable to different crop and soil systems, acting not only as a mechanism to conserve biodiversity, but as a potential facilitator of sustainable agriculture systems