Defining and predicting heat waves in Bangladesh

This paper proposes a heat-wave definition for Bangladesh that could be used to trigger preparedness measures in a heat early warning system (HEWS) and explores the climate mechanisms associated with heat waves. A HEWS requires a definition of heat waves that is both related to human health outcomes and forecastable. No such definition has been developed for Bangladesh. Using a generalized additive regression model, a heat-wave definition is proposed that requires elevated minimum and maximum daily temperatures over the 95th percentile for 3 consecutive days, confirming the importance of nighttime conditions for health impacts. By this definition, death rates increase by about 20% during heat waves; this result can be used as an argument for public-health interventions to prevent heat-related deaths. Furthermore, predictability of these heat waves exists from weather to seasonal time scales, offering opportunities for a range of preparedness measures. Heat waves are associated with an absence of normal premonsoonal rainfall brought about by anomalously strong low-level westerly winds and weak southerlies, detectable up to approximately 10 days in advance. This circulation pattern occurs over a background of drier-than-normal conditions, with below-average soil moisture and precipitation throughout the heat-wave season from April to June. Low soil moisture increases the odds of heat-wave occurrence for 10–30 days, indicating that subseasonal forecasts of heat-wave risk may be possible by monitoring soil-moisture conditions

Should seasonal rainfall forecasts be used for flood preparedness?

In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary drivers of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in wet climates, even a perfect tercile forecast of seasonal total rainfall would provide little to no indication of the seasonal likelihood of flooding. The number of extreme events within a season shows the highest correlations with floodiness consistently across regions. Otherwise, results vary across climate regimes: floodiness in arid regions in Southern and Eastern Africa shows the strongest correlations with seasonal average soil moisture and seasonal total rainfall. Floodiness in wetter climates of West and Central Africa and Madagascar shows the strongest relationship with measures of the intensity of seasonal rainfall. Measures of rainfall patterns, such as the length of dry spells, are least related to seasonal floodiness across the continent. Ultimately, identifying the drivers of seasonal flooding can be used to improve forecast information for flood preparedness, and avoid misleading decision-makers

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers

Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin

Extreme flooding impacts millions of people that live within the Amazon floodplain. Global hydrological models (GHMs) are frequently used to assess and inform the management of flood risk, but knowledge on the skill of available models is required to inform their use and development. This paper presents an intercomparison of eight different GHMs freely available from collaborators of the Global Flood Partnership (GFP) for simulating floods in the Amazon basin. To gain insight into the strengths and shortcomings of each model, we assess their ability to reproduce daily and annual peak river flows against gauged observations at 75 hydrological stations over a 19-year period (1997–2015). As well as highlighting regional variability in the accuracy of simulated streamflow, these results indicate that (a) the meteorological input is the dominant control on the accuracy of both daily and annual maximum river flows, and (b) groundwater and routing calibration of Lisflood based on daily river flows has no impact on the ability to simulate flood peaks for the chosen river basin. These findings have important relevance for applications of large-scale hydrological models, including analysis of the impact of climate variability, assessment of the influence of long-term changes such as land-use and anthropogenic climate change, the assessment of flood likelihood, and for flood forecasting systems

Genome-wide analysis reveals no evidence of trans chromosomal regulation of mammalian immune development.

It has been proposed that interactions between mammalian chromosomes, or transchromosomal interactions (also known as kissing chromosomes), regulate gene expression and cell fate determination. Here we aimed to identify novel transchromosomal interactions in immune cells by high-resolution genome-wide chromosome conformation capture. Although we readily identified stable interactions in cis, and also between centromeres and telomeres on different chromosomes, surprisingly we identified no gene regulatory transchromosomal interactions in either mouse or human cells, including previously described interactions. We suggest that advances in the chromosome conformation capture technique and the unbiased nature of this approach allow more reliable capture of interactions between chromosomes than previous methods. Overall our findings suggest that stable transchromosomal interactions that regulate gene expression are not present in mammalian immune cells and that lineage identity is governed by cis, not trans chromosomal interactions

Beyond El Niño: unsung climate modes drive African floods

The El Niño Southern Oscillation (ENSO) dominates the conversation about predictability of climate extremes and early warning and preparedness for floods and droughts, but in Africa other modes of climate variability are also known to influence rainfall anomalies. In this study, we compare the role of ENSO in driving flood hazard over sub-Saharan Africa with modes of climate variability in the Indian and Atlantic Oceans. This is achieved by applying flood frequency approaches to a hydrological reanalysis dataset and streamflow observations for different phases of the ENSO, Indian Ocean Dipole and Tropical South Atlantic climate modes. Our results highlight that Indian and Atlantic Ocean modes of climate variability are equally as important as ENSO for driving changes in the frequency of impactful floods across Africa. We propose that in many parts of Africa a larger consideration of these unsung climate modes could provide improved seasonal predictions of associated flood hazard and better inform adaptation to the changing climate

Variation of Sidewall Passivation on Sub-um Selectively Grown Ge-on-Si Devices Towards Single Photon Avalanche Detectors

Developing single photon avalanche diodes (SPADs) at short-wave infrared (SWIR) wavelengths beyond 1000 nm has attracted interest lately. Numerous quantum technology applications such as light detection and ranging (LIDAR), imaging through obscurants and quantum communications require sensitivity in this region. In quantum communications, operation at the telecoms wavelengths of 1310 nm and 1550 nm is essential. Ge-on-Si SPADs offer potential for lower afterpulsing and higher single photon detection efficiencies in the SWIR in comparison with InGaAs/InP SPADs, at a lower cost due to Si foundry compatibility. In this study, Ge-on-Si devices are fabricated on silicon-on-insulator (SOI) substrates, with a separate absorption, charge and multiplication layer (SACM) geometry and a lateral Si multiplication region. This Si foundry compatible process will allow for future integration with Si waveguides and optical fibres. The Ge is selectively grown inside sub-μm wide SiO2 trenches, reducing the threading dislocation in comparison with bulk Ge; a typical process for integrated Ge detectors. Here we deliberately exposed Ge sidewalls with an etch-back technique, to allow a passivation comparison not normally carried out in selectively grown devices planarised by chemical-mechanical polishing. Reduced dark currents are demonstrated using thermal GeO2 passivation in comparison to plasma-enhanced chemical-vapourdeposition SiO2. The improved passivation performance of GeO2 is verified by activation energy extraction and density of interface trap (Dit) calculations obtained from temperature-dependent capacitance-voltage (CV) and conductance-voltage (GV) measurements. This highlights the benefit of optimal surface passivation on sub-μm wide selectively grown Ge-on-SOI photodetector devices, potentially critical for waveguide integrated SPADs

Mobile assistive technologies for the visually impaired

There are around 285 million visually impaired people worldwide, and around 370,000 people are registered as blind or partially sighted in the UK. Ongoing advances in information technology (IT) are increasing the scope for IT-based mobile assistive technologies to facilitate the independence, safety, and improved quality of life of the visually impaired. Research is being directed at making mobile phones and other handheld devices accessible via our haptic (touch) and audio sensory channels. We review research and innovation within the field of mobile assistive technology for the visually impaired and, in so doing, highlight the need for successful collaboration between clinical expertise, computer science, and domain users to realize fully the potential benefits of such technologies. We initially reflect on research that has been conducted to make mobile phones more accessible to people with vision loss. We then discuss innovative assistive applications designed for the visually impaired that are either delivered via mainstream devices and can be used while in motion (e.g., mobile phones) or are embedded within an environment that may be in motion (e.g., public transport) or within which the user may be in motion (e.g., smart homes)

Decoupling the dark count rate contributions in Ge-on-Si single photon avalanche diodes

Single Photon Avalanche Diodes (SPADs) are semiconductor devices capable of accurately timing the arrival of single photons of light. Previously, we have demonstrated a pseudo-planar Ge-on-Si SPAD that operates in the short-wave infrared, which can be compatible with Si foundry processing. Here, we investigate the pseudo-planar design with simulation and experiment to establish the spatial contributions to the dark-count rate, which will ultimately facilitate optimisation towards operation at temperatures compatible with Peltier cooler technologies

Simulation and Design Optimization of Germanium-on-Silicon Single Photon Avalanche Diodes

Single photon avalanche diodes (SPADs) are semiconductor photodiode detectors capable of detecting individual photons, typically with sub-ns precision timing. We have previously demonstrated novel pseudo-planar germanium-on-silicon SPADs with absorption into the short-wave infrared, which promise lower costs and potentially easier CMOS integration compared to III-V SPADs. Here we have simulated the dark count rate of these devices, using a custom solver for McIntyre’s avalanche model and a trap assisted tunnelling generation model. Calibration and fitting have been performed using experimental data and the results have highlighted areas in which the technology can be optimised