THE VARIABILITY OF AEROSOL OPTICAL THICKNESS IN MOUNTAINOUS AND FOOTHILL AREAS OF THE NORTH OSSETIA ACCORDING TO SATELLITE MEASUREMENTS

Atmospheric aerosol is one of the indicators of air quality that affects the environmental situation. The aerosol optical thickness (AOT) of the atmosphere is studied in the mountainous, foothill, and plain regions of Republic of North Ossetia-Alania (Russian Federation) based on satellite data EOS Terra, Aqua. Several geographical locations at different heights were selected for the analysis. Daily series of AOT, air temperature and precipitation data were obtained on period over 20 years for each point. The results of statistical analysis of long-term values of AOT, temperature and precipitation are shown. There is a statistically significant relationship between the averaged values, and there is also a dependence on the height of the location and the proximity of mountains. Long-term average dependencies provide a basis for predicting the AOT value based on the measured temperature at height of 2 m for territories located in a complex landscape at different altitudes.

Análise da Variação Sazonal e de Tendências na Precipitação Pluviométrica no Município de Juazeiro-BA

A cidade de Juazeiro-BA destaca-se por ser um importante polo de desenvolvimento agrícola em bases irrigadas no Nordeste, no qual a distribuição sazonal da precipitação pluviométrica tem influência decisiva no contexto da relação saúde e saneamento em áreas urbanizadas, na agricultura familiar, no abastecimento de água de famílias isoladas e na economia dessa região. Assim, essa pesquisa tem como objetivo avaliar a distribuição das chuvas no município de Juazeiro-BA, analisando uma série diária de 32 anos de dados pluviométricos, calculando os valores anuais e sazonais do Índice de Concentração da Precipitação (ICP) e realizando um estudo de tendência da precipitação pluviométrica, a partir do método de Mann-Kendall. Os resultados revelaram que, em Juazeiro, o período chuvoso é bem definido, com os maiores índices de precipitação entre os meses de dezembro e março. O ICP anual tem o valor de 28,48 %, indicando alta irregularidade na distribuição das chuvas anuais, possibilitando a ocorrência de eventos extremos, tanto de inundações quanto de escassez hídrica. O teste de Mann-Kendall, para o período em estudo, apresentou tendência de diminuição da média pluviométrica anual em 7,51 mm, o que pode aumentar o déficit hídrico na região.Palavras-chave: Chuvas; Séries Climáticas; Concentração Pluviométrica; Mann-Kendall. Seasonal Variation and Trend in Rainfall in the Municipality of Juazeiro-BA A B S T R A C TThe city of Juazeiro-BA stands out for being an important agricultural development hub on irrigated bases in the Northeast, in which the seasonal distribution of pluviometric precipitation has a decisive influence in the context of the health and sanitation relationship in urbanized areas, in family agriculture, in water supplying of isolated families and the economy of that region. Thus, this research aims to assess the distribution of rainfall in the municipality of Juazeiro-BA, analyzing a daily series of 32 years of rainfall data, calculating the annual and seasonal values of the Precipitation Concentration Index (PCI) and conducting a rainfall trend study, using the Mann-Kendall method. The results revealed that, in Juazeiro, the rainy period is well defined, with the highest levels of precipitation between the months of December and March. The annual PCI has a value of 28.48 %, indicating a high irregularity in the distribution of annual rainfall, enabling the occurrence of extreme events, both floods and water scarcity. The Mann-Kendall test, for the period under study, presented tendency decrease of the annual rainfall average by 7.51 mm, which may increase the water deficit in the region.Keywords: Rainfall; Climate Series; Rain Concentration; Mann-Kendall.

Estimating the Risk of COVID-19 Death during the Course of the Outbreak in Korea, February–May 2020

Background: In Korea, a total of 10,840 confirmed cases of COVID-19 including 256 deaths have been recorded as of May 9, 2020. The time-delay adjusted case fatality risk (CFR) of COVID-19 in Korea is yet to be estimated. Methods: We obtained the daily series of confirmed cases and deaths in Korea reported prior to May 9, 2020. Using statistical methods, we estimated the time-delay adjusted risk for death from COVID-19 in Daegu, Gyeongsangbuk-do, other regions in Korea, as well as the entire country. Results: Our model-based crude CFR fitted the observed data well throughout the course of the epidemic except for the very early stage in Gyeongsangbuk-do; this was partially due to the reporting delay. Our estimates of the risk of death in Gyeongsangbuk-do reached 25.9% (95% Credible Interval (CrI): 19.6%–33.6%), 20.8% (95% CrI: 18.1%–24.0%) in Daegu, and 1.7% (95% CrI: 1.1%–2.5%) in other regions, whereas the national estimate was 10.2% (95% CrI: 9.0%–11.5%). Conclusions: The latest estimates of CFR of COVID-19 in Korea are considerably high, even with the early implementation of public health interventions including widespread testing, social distancing, and delayed school openings. Geographic differences in the CFR are likely influenced by clusters tied to hospitals and nursing homes.

Remote Sensing and Bio-Geochemical Modeling of Forest Carbon Storage in Spain

This study simulates annual net primary production (NPP) of forests over peninsular Spain during the years 2005–2012. The modeling strategy consists of a linked production efficiency model based on the Monteith approach and the bio-geochemical model Biome-BGC. Recently produced databases and data layers over the study area including meteorological daily series, ecophysiological parameters, and maps containing information about forest type, rooting depth, and growing stock volume (GSV), were employed. The models, which simulate forest processes assuming equilibrium conditions, were previously optimized for the study area. The production efficiency model was used to estimate daily gross primary production (GPP), while Biome-BGC was used to simulate growth (RG) and maintenance (RM) respirations. To account for actual forest conditions, GPP, RG, and RM were corrected using the ratio of the remotely-sensed derived actual to potential GSV as an indicator of the actual state of forests. The obtained results were evaluated against current annual increment observations from the Third Spanish Forest Inventory. Coefficients of determination ranged from 0.46 to 0.74 depending on the forest type. A simplified dataset was produced by applying regular increments in air temperature and reductions in precipitation to the original 2005–2012 daily series with the goal of covering the range of variation of the climate projections corresponding to the different climate change scenarios reported in the literature. The modified meteorological series were used to simulate new GPP, RG, and RM through Biome-BGC and corrected using GSV. Precipitation was confirmed as the main limiting factor in the study area. In the regions where precipitation was already a limiting factor during 2005–2012, both the increment in air temperature and the reduction in precipitation contributed to a reduction of NPP. In the regions where precipitation was not a limiting factor during 2005–2012, the increment in air temperature led to an increment of NPP. This study is therefore relevant to characterize the growth of Spanish forests both in current and expected climate conditions.

Estimating the risk of COVID-19 death during the course of the outbreak in Korea, February-March, 2020

BackgroundIn Korea, a total of 8,799 confirmed cases of COVID-19 including 102 deaths have been recorded as of Mar 21, 2020. The time-delay adjusted case fatality risk of COVID-19 in Korea is yet to be estimated.MethodsWe obtained the daily series of confirmed cases and deaths in Korea reported prior to March 21, 2020. Using statistical methods, we estimated the time-delay adjusted risk for death from COVID-19 in the city of Daegu, Gyeongsangbuk-do, other regions in Korea, as well as for the entire country.ResultsOur model-based crude CFR fitted the observed data well throughout the course of the epidemic except for the very early stage in Gyeongsangbuk-do, partially due to the reporting delay. Our estimates of the risk for death in Gyeongsangbuk-do reached 2.4% (95% CrI: 1.6-3.4%), 1.3% (95% CrI: 1.0-1.6%) in Daegu and 0.7% (95% CrI: 0.3-1.4%) in other regions, whereas the national estimate of the risk for death was estimated at 1.4% (95% CrI: 1.2-1.7%) in Korea.ConclusionsThe relatively low CFRs are associated with the early implementation of public health interventions including widespread testing, social distancing, and delayed school openings in Korea. Geographic differences in CFR are likely influenced by clusters of nosocomial transmission.

Transmissibility of 2019 Novel Coronavirus: zoonotic vs. human to human transmission, China, 2019-2020

ObjectivesThe novel coronavirus (2019-nCoV) originating from Wuhan has rapidly spread throughout China. While the origin of the outbreak remains uncertain, accumulating evidence links a wet market in Wuhan for the early spread of 2019-nCoV. Similarly, the influence of the marketplace on the early transmission dynamics is yet to be investigated.MethodsUsing the daily series of 2019-nCov incidenceincluding contact history with the market, we have conducted quantitative modeling analyses to estimate the reproduction numbers (R) for the market-to-human and human-to-human transmission together with the reporting probability and the early effects of public health interventions.ResultsOur mean R estimates for China in 2019-2020 are estimated at 0.37 (95%CrI: 0.02-1.78) for market-to-human transmission, and 3.87 (95%CrI: 3.18-4.78) for human-to-human transmission, respectively. Moreover we estimated that the reporting rate cases stemming from market-to-human transmission was 3-31 fold higher than that for cases stemming from human-to-human transmission, suggesting that contact history with the wet market played a key role in identifying 2019-nCov cases.ConclusionsOur findings suggest that the proportions of asymptomatic and subclinical patients constitute a substantial component of the epidemic’s magnitude. Findings suggest that the development of rapid diagnostic tests could help bring the epidemic more rapidly under control.

Estimation of ionospheric reflection height using long wave propagation

Phase height measurements of low frequency radio waves are used to study the long-term variability of the mesosphere over Europe. Phase height measurements use a characteristic pattern in field strength registration of radio waves interpreted as phase relations between sky wave and surface wave to obtain the apparent height of the reflection point, the Standard Phase Height (SPH). Based on this SPH-method a homogenized daily series was generated since 1959 at Kühlungsborn. Improvements of the measuring method show that the signal is significantly influenced by lower atmospheric layers. Mesospheric reflection is not the exclusive source of the measured behavior. Tropospheric influence can not be neglected. Taking this into account one has to conclude that the strong coherency of the SPH data to mesospheric heights is not as significant as previously assumed.

Variability of the Lake Onega ice coverage in the period 2000-2018 according to the satellite data

Studying of characteristics of the Lake Onega ice regime and investigating of the climate influence on the formation and destruction of the ice cover requires a continuous chronological series of data on the Lake ice coverage. Ice cover is the percentage of the ice area to the total area of the lake. In 1955–1990, calculations of the ice coverage of the Lake were based on the use of the results of airborne ice reconnaissance. On average for this period, from 5 to 15 values were annually obtained, which was not enough for a comprehensive analysis of the ice coverage variability. In this paper, for the frst time, a daily series of values of the ice coverage of the Lake Onega for the period 2000–2018 had been formed basing on the results of a combined analysis of the following satellite data sets: NSIDC, NOAA NESDIS, corrected by data of the satellite MODIS sensor. Values from November to May were grouped from the above data sets without regards for years of observations, and then the regression analysis of these values made possible to create a model (a polynomial of the 8th degree) of the chronological course of the ice coverage during the period of the ice phenomena existence on the Lake Onega. Te coefcient of determination of the model is 0.74, and the error in determining the ice coverage is 21%. Te average dates of the beginning, end, and duration of periods of the formation (from November 25th to January 19th), the destruction (from April 13th to May 17th) of the ice cover, as well as the total freeze-up time (from January 20th to April 12th) on the Lake Onega for the period 2000–2018 was determined. Te period of ice phenomena on the Lake Onega on average lasts for almost half a year (175 days), of which a signifcant part of the time is a complete freeze-up (84 days). It was found that the rate of formation of the ice cover (1.76% per day) on the Lake Onega is 1.65 times smaller than the rate of its destruction (2.90% per day), which approximately corresponds to similar results obtained for the Lake Ladoga (1.5 times).