Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

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.

Large reorganizations in butterfly communities during an extreme weather event

Drought events are projected to increase in frequency and magnitude, which may alter the composition of ecological communities. Using a functional community metric that describes abundance, life history traits and conservation status, based upon Grime’s CSR (Competitive-Stress tolerant-Ruderal)¬ scheme, we investigated how British butterfly communities changed during an extreme drought in 1995. Throughout Britain, the total abundance of these insects had a significant tendency to increase, accompanied by substantial changes in community composition, particularly in more northerly, wetter sites. Communities tended to shift away from specialist, vulnerable species, and towards generalist, widespread species and, in the year following, communities had yet to return to equilibrium. Importantly, heterogeneity in surrounding landscapes mediated community responses to the drought event. Contrary to expectation, however, community shifts were more extreme in areas of greater topographic diversity, whilst land-cover diversity buffered community changes and limited declines in vulnerable specialist butterflies.

Extended time weather forecasts contributes to agricultural productivity estimates

Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Parana, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.

Weather conditions and moon phase influence on Tropical Screech Owl and Burrowing Owl detection by playback

Sampling owls in a reliable and standardized way is not easy given their nocturnal habits. Playback is a widely employed technique to survey owls. We assessed the influence of wind speed, temperature, air humidity, and moon phase on the response rate of the Tropical Screech Owl Megascops choliba and the Burrowing Owl Athene cunicularia in southeast Brazil. Tropical Screech Owl occurs in scrubland and wooded habitats, whereas the Burrowing Owl inhabits open grasslands to grassland savannah. Sixteen survey points were systematically distributed in four different landscape types, ranging from open grassland to woodland savannah. Field work was conducted in 2004 from June to December, the reproductive season of the two owl species. Our study design consisted of eight field expeditions of five nights each; four expeditions occurred under full moon and four under new moon conditions. At each survey station, we performed a broadcast/listening sequence involving several calls and vocalizations from each species, starting with Tropical Screech Owl (the smaller species). From 112 sample periods for each species within their respective preferred habitats, we obtained 54 responses from Tropical Screech Owl (48% response rate) and 30 responses (27% response rate) from Burrowing Owl. We found that the response rate of Tropical Screech Owl increased under conditions of higher temperature and air humidity, while the response rate of Burrowing Owl was higher during full moon nights.

Solar Energy assessment based on weather station data for direct site monitoring in Indonesia

This thesis evaluates different sites for a weather measurement system and a suitable PV- simulation for University of Surabaya (UBAYA) in Indonesia/Java. The weather station is able to monitor all common weather phenomena including solar insolation. It is planned to use the data for scientific and educational purposes in the renewable energy studies. During evaluation and installation it falls into place that official specifications from global meteorological organizations could not be meet for some sensors caused by the conditions of UBAYA campus. After arranging the hardware the weather at the site was monitored for period of time. A comparison with different official sources from ground based and satellite bases measurements showed differences in wind and solar radiation. In some cases the monthly average solar insolation was deviating 42 % for satellite-based measurements. For the ground based it was less than 10 %. The average wind speed has a difference of 33 % compared to a source, which evaluated the wind power in Surabaya. The wind direction shows instabilities towards east compared with data from local weather station at the airport. PSET has the chance to get some investments to investigate photovoltaic on there own roof. With several simulations a suitable roof direction and the yearly and monthly outputs are shown. With a 7.7 kWpeak PV installation with the latest crystalline technology on the market 8.82 MWh/year could be achieved with weather data from 2012. Thin film technology could increase the value up to 9.13 MWh/year. However, the roofs have enough area to install PV. Finally the low price of electricity in Indonesia makes it not worth to feed in the energy into the public grid.

Weather-based prediction of anthracnose severity using artificial neural network models

Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides. Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21.9% for the Australian and 22.1% for the South American model. of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development.

Preparedness for rain during sunny weather: Caribbean environmental sustainability in a nuclear age

Includes bibliography

Evaluation of weather influence on mechanical and viscoelastic properties of polyetherimide/carbon fiber composites

In order to investigate how environmental degradation affects the mechanical and thermal performance of polyetherimide/carbon fiber laminates, in this work different weathering were conducted. Additionally, dynamic mechanical analysis, interlaminar shear strength tests and non-destructive inspections were performed on this composite before and after being submitted to hygrothermal, UV radiation and thermal shock weathering. According to our results, hygrothermally aged samples had their glass transition temperature and elastic and storage moduli reduced by plasticization effect. Photooxidation, due to UV radiation exposure, occurred only on the surface of the laminates. Thermal shock induced a reversible stress on the composite's interface region. The results revealed that the mechanical behavior can vary during weather exposure but since this variation is only subtle, this thermoplastic laminate can be considered for high-performance applications, such as aerospace. © The Author(s) 2013.

Lightning and precipitation produced by severe weather systems over Belém, Brazil

Eventos de raios nuvem-solo registrados pela rede de detecção do SIPAM, integrada por 12 sensores VAISALA LPATS IV, distribuídos no leste da Amazônia, foram analisados durante 4 tempestades com ocorrência de precipitação intensa em Belém-PA-Brasil, em 2006-2007. Esses casos selecionados, correspondem a eventos de chuva com mais de 25 mm/hora ou 40 mm/ 2 horas, de precipitação registrada por um pluviômetro instalado em 1º 47' 53" and 48º 30' 16" O. Com centro nessa localização, um círculos de 30, 10 e 5 km de raio foram traçados através de um sistema de informação geográfica e os dados de eventos de raios nessas áreas foram separados para analise. Durante essas tempestades, os eventos de raios ocorreram de maneira quase aleatória, sobre a área maior que já havia sido previamente coberta por sistemas convectivos de mesoescala, em todos os casos. Esse trabalho também mostrou a grande influencia dos sistemas de larga escala nas condições de tempo que levaram às tempestades severas estudadas. Adicionalmente, foi observado que, quando existe interação entre sistemas de larga e meso escalas, tanto a precipitação como o numero de relâmpagos aumentaram significativamente e a atividade elétrica nos círculos maiores pode anteceder a chuva no ponto central.

Weather forecasting for Eastern Amazon with OLAM model

O modelo OLAM tem como característica a vantagem de representar simultaneamente os fenômenos meteorológicos de escala global e regional através de um esquema de refinamento de grades. Durante o projeto REMAM, o modelo foi aplicado para alguns estudos de caso com objetivo de avaliar o desempenho do modelo na previsão numérica de tempo para a região leste da Amazônia. Estudos de caso foram feitos para os doze meses do ano de 2009. Os resultados do modelo para estes casos foram comparados com dados observados na região de estudo. A análise dos dados de precipitação mostrou que o modelo consegue representar a distribuição média da precipitação acumulada e os aspectos da sazonalidade da ocorrência dos eventos, mas não consegue prever individualmente a acumulação de precipitação local. No entanto, avaliação individual de alguns casos mostrou que o modelo OLAM conseguiu representar dinamicamente e prever, com alguns dias de antecedência, o desenvolvimento de fenômenos meteorológicos costeiros como as linhas de instabilidade, que são um dos mais importantes sistemas precipitantes da Amazônia.

Tropical Healthcare Epidemiology: Weather Determinants of the Etiology of Bloodstream Infections in a Brazilian Hospital

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Weather variables, water balance, growth, and agro industrial yield of sugarcane

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)