Revisão das Técnicas para a Assimilação do Espectro Direcional Bi-Dimensional em Modelos de Ondas

Several meteorological centers are investigating methods on how to use the new information retrieved from spaceborn Synthetic Aperture Radar (SAR) measurements in order to improve the wave forecasting. With this picture in mind, and focusing mainly on the problem of the full directional spectrum, the theory of wave data assimilation techniques is reviewed. The present work aims as well to describe in some detail the three techniques used so far in the assimilation of the two dimensional spectrum, that is the Optimal Interpolation Scheme, the Adjoint Technique and the Green’s Function Method

SENSIBILIDADE DE ESPECTROS DE ONDAS OCEÂNICAS RECUPERADOS POR RADAR DE ABERTURA SINTÉTICA

SAR (Synthetic Aperture Radar ou Radar de Abertura Sintética) é o único sensor transportado por satélites capaz de medir o espectro direcional de ondas. Sua elevada cobertura espacial e temporal permite caracterizar o estado de mar, especialmente a região de baixa frequência do espectro de energia, que vem sendo assimilada em modelos numéricos de previsão de ondas em diversos centros operacionais espalhados pelo globo. Contudo, a extração do espectro de ondas de uma imagem SAR é um procedimento complexo. Alguns modos de operação não permitem o emprego de imagens sequenciais para resolver a ambiguidade direcional de propagação das ondas, o que requer informações adicionais, geralmente obtidas de um modelo de ondas. A dependência destas informações adicionais é investigada aplicando-se a inversão clássica de Hasselmann a alguns estados de mar teóricos. Esta abordagem é baseada na transformação analítica do espectro direcional de ondas sobre o espectro de imagem SAR correspondente. A solução deste problema inverso é determinada por um algoritmo numérico que minimiza um funcional não linear. Apesar de amplamente utilizado por diversos centros operacionais de previsão, este método não foi extensivamente testado em cenários experimentais bem definidos. Os resultados mostram que a dependência investigada é bastante significativa, sobretudo no que diz respeito à direção de propagação das ondas, levantando questionamentos sobre a acurácia da técnica

IMPACTOS ASSOCIADOS À RESOLUÇÃO DOS MODELOS ATMOSFÉRICOS EM MODELOS DE PROGNÓSTICOS DE ONDAS

Neste trabalho são avaliados os impactos que as diferentes resoluções temporais e espaciais do campo de vento provocam nos resultados de altura significativa do modelo prognóstico de onda. Com esse objetivo, três eventos meteorológicos que geraram ondulações na Bacia de Campos foram simulados com alta resolução utilizando o modelo de mesoescala Brazilian Regional Atmospheric Modeling System (BRAMS) e os resultados empregados no WAVEWATCH (WW3)para as seguintes resoluções espaciais 20, 60, 100, 300 e 600 km, com resoluções temporais de 1,3 e 6 h. Dois dos eventos selecionados estavam associados à formação de ciclones no Atlântico Sul que se propagaram com velocidades acima da média e geraram pistas com grande extensão.No terceiro caso, as ondas estavam associadas a pistas de pequenas dimensões espaciais geradas pelo Anticiclone Subtropical do Atlântico Sul (ASAS). A seleção destes casos com diferentes características físicas proporcionou uma melhor avaliação das discrepâncias que as resoluções espaciais e temporais ocasionariam. Tendo em vista os resultados encontrados, sugere-se que, para diminuir os erros, sejam utilizados campos de ventos com espaçamento de até 60 km e, quanto à resolução temporal, destaca-se que os três intervalos resolveram bem os casos selecionados

SEASTAR: a mission to study ocean submesoscale dynamics and small-scale atmosphere-ocean processes in coastal, shelf and polar seas

High-resolution satellite images of ocean color and sea surface temperature reveal an abundance of ocean fronts, vortices and filaments at scales below 10 km but measurements of ocean surface dynamics at these scales are rare. There is increasing recognition of the role played by small scale ocean processes in ocean-atmosphere coupling, upper-ocean mixing and ocean vertical transports, with advanced numerical models and in situ observations highlighting fundamental changes in dynamics when scales reach 1 km. Numerous scientific publications highlight the global impact of small oceanic scales on marine ecosystems, operational forecasts and long-term climate projections through strong ageostrophic circulations, large vertical ocean velocities and mixed layer re-stratification. Small-scale processes particularly dominate in coastal, shelf and polar seas where they mediate important exchanges between land, ocean, atmosphere and the cryosphere, e.g., freshwater, pollutants. As numerical models continue to evolve toward finer spatial resolution and increasingly complex coupled atmosphere-wave-ice-ocean systems, modern observing capability lags behind, unable to deliver the high-resolution synoptic measurements of total currents, wind vectors and waves needed to advance understanding, develop better parameterizations and improve model validations, forecasts and projections. SEASTAR is a satellite mission concept that proposes to directly address this critical observational gap with synoptic two-dimensional imaging of total ocean surface current vectors and wind vectors at 1 km resolution and coincident directional wave spectra. Based on major recent advances in squinted along-track Synthetic Aperture Radar interferometry, SEASTAR is an innovative, mature concept with unique demonstrated capabilities, seeking to proceed toward spaceborne implementation within Europe and beyond

The burden of injury in Central, Eastern, and Western European sub-region : a systematic analysis from the Global Burden of Disease 2019 Study

Background Injury remains a major concern to public health in the European region. Previous iterations of the Global Burden of Disease (GBD) study showed wide variation in injury death and disability adjusted life year (DALY) rates across Europe, indicating injury inequality gaps between sub-regions and countries. The objectives of this study were to: 1) compare GBD 2019 estimates on injury mortality and DALYs across European sub-regions and countries by cause-of-injury category and sex; 2) examine changes in injury DALY rates over a 20 year-period by cause-of-injury category, sub-region and country; and 3) assess inequalities in injury mortality and DALY rates across the countries. Methods We performed a secondary database descriptive study using the GBD 2019 results on injuries in 44 European countries from 2000 to 2019. Inequality in DALY rates between these countries was assessed by calculating the DALY rate ratio between the highest-ranking country and lowest-ranking country in each year. Results In 2019, in Eastern Europe 80 [95% uncertainty interval (UI): 71 to 89] people per 100,000 died from injuries; twice as high compared to Central Europe (38 injury deaths per 100,000; 95% UI 34 to 42) and three times as high compared to Western Europe (27 injury deaths per 100,000; 95%UI 25 to 28). The injury DALY rates showed less pronounced differences between Eastern (5129 DALYs per 100,000; 95% UI: 4547 to 5864), Central (2940 DALYs per 100,000; 95% UI: 2452 to 3546) and Western Europe (1782 DALYs per 100,000; 95% UI: 1523 to 2115). Injury DALY rate was lowest in Italy (1489 DALYs per 100,000) and highest in Ukraine (5553 DALYs per 100,000). The difference in injury DALY rates by country was larger for males compared to females. The DALY rate ratio was highest in 2005, with DALY rate in the lowest-ranking country (Russian Federation) 6.0 times higher compared to the highest-ranking country (Malta). After 2005, the DALY rate ratio between the lowest- and the highest-ranking country gradually decreased to 3.7 in 2019. Conclusions Injury mortality and DALY rates were highest in Eastern Europe and lowest in Western Europe, although differences in injury DALY rates declined rapidly, particularly in the past decade. The injury DALY rate ratio of highest- and lowest-ranking country declined from 2005 onwards, indicating declining inequalities in injuries between European countries.Peer reviewe

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : an analysis of data from the Global Burden of Disease Study 2019

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2.5 originating from ambient and household air pollution.Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2.5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure-response curve from the extracted relative risk estimates using the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2.5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2.5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals.Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2.5 exposure, with an estimated 3.78 (95% uncertainty interval 2.68-4.83) deaths per 100 000 population and 167 (117-223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13.4% (9.49-17.5) of deaths and 13.6% (9.73-17.9) of DALYs due to type 2 diabetes were contributed by ambient PM2.5, and 6.50% (4.22-9.53) of deaths and 5.92% (3.81-8.64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2.5.Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2.5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.Peer reviewe

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : An analysis of data from the Global Burden of Disease Study 2019

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes