Advances in the stochastic modelling of satellite-derived rainfall estimates using a sparse calibration dataset

As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration

Hydrological modelling using ensemble satellite rainfall estimates in a sparsely gauged river basin: The need for whole-ensemble calibration

The potential for satellite rainfall estimates to drive hydrological models has been long understood, but at the high spatial and temporal resolutions often required by these models the uncertainties in satellite rainfall inputs are both significant in magnitude and spatiotemporally autocorrelated. Conditional stochastic modelling of ensemble observed fields provides one possible approach to representing this uncertainty in a form suitable for hydrological modelling. Previous studies have concentrated on the uncertainty within the satellite rainfall estimates themselves, sometimes applying ensemble inputs to a pre-calibrated hydrological model. This approach does not account for the interaction between input uncertainty and model uncertainty and in particular the impact of input uncertainty on model calibration. Moreover, it may not be appropriate to use deterministic inputs to calibrate a model that is intended to be driven by using an ensemble. A novel whole-ensemble calibration approach has been developed to overcome some of these issues. This study used ensemble rainfall inputs produced by a conditional satellite-driven stochastic rainfall generator (TAMSIM) to drive a version of the Pitman rainfall-runoff model, calibrated using the whole-ensemble approach. Simulated ensemble discharge outputs were assessed using metrics adapted from ensemble forecast verification, showing that the ensemble outputs produced using the whole-ensemble calibrated Pitman model outperformed equivalent ensemble outputs created using a Pitman model calibrated against either the ensemble mean or a theoretical infinite-ensemble expected value. Overall, for the verification period the whole-ensemble calibration provided a mean RMSE of 61.7% of the mean wet season discharge, compared to 83.6% using a calibration based on the daily mean of the ensemble estimates. Using a Brier’s Skill Score to assess the performance of the ensemble against a climatic estimate, the whole-ensemble calibration provided a positive score for the main range of discharge events. The equivalent score for calibration against the ensemble mean was negative, indicating it showed no skill versus the climatic estimate

The use of remotely sensed rainfall for managing drought risk: a case study of weather index insurance in Zambia

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere

A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa

Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets

Towards in cellulo virus crystallography

Viruses are a significant threat to both human health and the economy, and there is an urgent need for novel anti-viral drugs and vaccines. High-resolution viral structures inform our understanding of the virosphere, and inspire novel therapies. Here we present a method of obtaining such structural information that avoids potentially disruptive handling, by collecting diffraction data from intact infected cells. We identify a suitable combination of cell type and virus to accumulate particles in the cells, establish a suitable time point where most cells contain virus condensates and use electron microscopy to demonstrate that these are ordered crystalline arrays of empty capsids. We then use an X-ray free electron laser to provide extremely bright illumination of sub-micron intracellular condensates of bacteriophage phiX174 inside living Escherichia coli at room temperature. We have been able to collect low resolution diffraction data. Despite the limited resolution and completeness of these initial data, due to a far from optimal experimental setup, we have used novel methodology to determine a putative space group, unit cell dimensions, particle packing and likely maturation state of the particles.Peer reviewe

Ringing up about breastfeeding: a randomised controlled trial exploring early telephone peer support for breastfeeding (RUBY) - trial protocol

BACKGROUND: The risks of not breastfeeding for mother and infant are well established, yet in Australia, although most women initiate breastfeeding many discontinue breastfeeding altogether and few women exclusively breastfeed to six months as recommended by the World Health Organization and Australian health authorities. We aim to determine whether proactive telephone peer support during the postnatal period increases the proportion of infants who are breastfed at six months, replicating a trial previously found to be effective in Canada. DESIGN/METHODS: A two arm randomised controlled trial will be conducted, recruiting primiparous women who have recently given birth to a live baby, are proficient in English and are breastfeeding or intending to breastfeed. Women will be recruited in the postnatal wards of three hospitals in Melbourne, Australia and will be randomised to peer support or to 'usual' care. All women recruited to the trial will receive usual hospital postnatal care and infant feeding support. For the intervention group, peers will make two telephone calls within the first ten days postpartum, then weekly telephone calls until week twelve, with continued contact until six months postpartum. Primary aim: to determine whether postnatal telephone peer support increases the proportion of infants who are breastfed for at least six months. HYPOTHESIS: that telephone peer support in the postnatal period will increase the proportion of infants receiving any breast milk at six months by 10% compared with usual care (from 46% to 56%).Outcome data will be analysed by intention to treat. A supplementary multivariate analysis will be undertaken if there are any baseline differences in the characteristics of women in the two groups which might be associated with the primary outcomes. DISCUSSION: The costs and health burdens of not breastfeeding fall disproportionately and increasingly on disadvantaged groups. We have therefore deliberately chosen trial sites which have a high proportion of women from disadvantaged backgrounds. This will be the first Australian randomised controlled trial to test the effectiveness and cost effectiveness of proactive peer telephone support for breastfeeding. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12612001024831

Measuring children\u27s sodium and potassium intakes in NZ: a pilot study

Low sodium and high potassium intakes in childhood protect against rises in blood pressure (BP) and risk of cardiovascular disease (CVD) later in life. Our aim was to pilot methods for collection of 24-h urine samples (gold standard) and diet recalls to assess sodium and potassium intakes and their food sources in 30 children aged 8⁻11 years at one New Zealand primary school. A diverse sample (n = 27) was recruited over a two-week period. All children provided a urine sample (71% complete) and interviewer-assisted 24-h diet recall (Intake24 software). Median (range) sodium intake was 2191 (1087 to 4786) mg/day (salt equivalent 5.5 g), potassium intake was 1776 (800⁻2981) mg/day, BP was 105 (84⁻129)/62 (53⁻89) mmHg, and sodium to potassium molar ratio was 2.0 (1.1⁻4.8). Frequent use of discretionary salt was uncommon. Major food sources of sodium were bread, pies and pastries, and bread and pasta-based dishes, and potassium were sauces and condiments, dairy products, and non-alcoholic beverages. Most participants provided adequate data and enjoyed taking part. A larger survey is warranted to confirm findings and inform a potential intervention(s). Small improvements to study procedures and resources should improve completeness of urine samples and quality of 24-h diet recall data