Comprehensive evaluation of the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis against independent observations: Reactive gases

The Copernicus Atmosphere Monitoring Service (CAMS) is operationally providing forecast and reanalysis products of air quality and atmospheric composition. In this article, we present an extended evaluation of the CAMS global reanalysis data set of four reactive gases, namely, ozone (O-3), carbon monoxide (CO), nitrogen dioxide (NO2), and formaldehyde (HCHO), using multiple independent observations. Our results show that the CAMS model system mostly provides a stable and accurate representation of the global distribution of reactive gases over time. Our findings highlight the crucial impact of satellite data assimilation and emissions, investigated through comparison with a model run without assimilated data. Stratospheric and tropospheric O-3 are mostly well constrained by the data assimilation, except over Antarctica after 2012/2013 due to changes in the assimilated data. Challenges remain for O-3 in the Tropics and high-latitude regions during winter and spring. At the surface and for short-lived species (NO2), data assimilation is less effective. Total column CO in the CAMS reanalysis is well constrained by the assimilated satellite data. The control run, however, shows large overestimations of total column CO in the Southern Hemisphere and larger year-to-year variability in all regions. Concerning the long-term stability of the CAMS model, we note drifts in the time series of biases for surface O-3 and CO in the Northern midlatitudes and Tropics and for NO2 over East Asia, which point to biased emissions. Compared to the previous Monitoring Atmospheric Composition and Climate reanalysis, changes in the CAMS chemistry module and assimilation system helped to reduce biases and enhance the long-term temporal consistency of model results for the CAMS reanalysis

Some challenges of middle atmosphere data assimilation

The assimilation of measurements from the stratosphere and mesosphere is becoming increasingly common as the lids of weather prediction and climate models rise into the mesosphere and thermosphere. However, the dynamics of the middle atmosphere pose specific challenges to the assimilation of measurements from this region. Forecast-error variances can be very large in the mesosphere and this can render assimilation schemes very sensitive to the details of the specification of forecast error correlations. An example is shown where observations in the stratosphere are able to produce increments in the mesosphere. Such sensitivity of the assimilation scheme to misspecification of covariances can also amplify any existing biases in measurements or forecasts. Since both models and measurements of the middle atmosphere are known to have biases, the separation of these sources of bias remains a issue. Finally, well-known deficiencies of assimilation schemes, such as the production of imbalanced states or the assumption of zero bias, are proposed explanations for the inaccurate transport resulting from assimilated winds. The inability of assimilated winds to accurately transport constituents in the middle atmosphere remains a fundamental issue limiting the use of assimilated products for applications involving longer time-scales

Absence of diabetic retinopathy in a patient who has had diabetes mellitus for 69 years, and inadequate glycemic control: case presentation

The main risk factors for the development and progression of diabetic retinopathy (DR) are chronic hyperglycemia, disease duration and systemic blood pressure. So far chronic hyperglycemia is the strongest evidence concerning the risk of developing DR. However there are some patients with poor metabolic control who never develop this diabetic complication. We present a case of a 73-year-old woman with type 1 diabetes mellitus, diagnosed 69 years ago. The patient is 73 years old, with no evidence of DR, despite poor glycemic control and several risk factors for DR. This case suggests the presence of a possible protection factor, which could be genetic

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring

Impact of Spectral Resolution on Quantifying Cyanobacteria in Lakes and Reservoirs: A Machine-Learning Assessment

Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters. These blooms can be detected using optical radiometers due to the presence of phycocyanin (PC) pigments. The spectral resolution of best-available multispectral sensors limits their ability to diagnostically detect PC in the presence of other photosynthetic pigments. To assess the role of spectral resolution in the determination of PC, a large ( N=905 ) database of colocated in situ radiometric spectra and PC are employed. We first examine the performance of selected widely used machine-learning (ML) models against that of benchmark algorithms for hyperspectral remote sensing reflectance ( Rrs ) spectra resampled to the spectral configuration of the Hyperspectral Imager for the Coastal Ocean (HICO) with a full-width at half-maximum (FWHM) of < 6 nm. Results show that the multilayer perceptron (MLP) neural network applied to HICO spectral configurations (median errors < 65%) outperforms other ML models. This model is subsequently applied to Rrs spectra resampled to the band configuration of existing satellite instruments and of the one proposed for the next Landsat sensor. These results confirm that employing MLP models to estimate PC from hyperspectral data delivers tangible improvements compared with retrievals from multispectral data and benchmark algorithms (with median errors between ∼73 % and 126%) and shows promise for developing a globally applicable cyanobacteria measurement approach

Osmotic stress does not trigger brevetoxin production in the dinoflagellate Karenia brevis

With the global proliferation of toxic Harmful Algal Bloom (HAB) species, there is a need to identify the environmental and biological factors that regulate toxin production. One such species, Karenia brevis, forms nearly annual blooms that threaten coastal regions throughout the Gulf of Mexico. This dinoflagellate produces brevetoxins, potent neurotoxins that cause neurotoxic shellfish poisoning and respiratory illness in humans, as well as massive fish kills. A recent publication reported that a rapid decrease in salinity increased cellular toxin quotas in K. brevis and hypothesized that brevetoxins serve a role in osmoregulation. This finding implied that salinity shifts could significantly alter the toxic impacts of blooms. We repeated the original experiments separately in three different laboratories and found no evidence for increased brevetoxin production in response to low-salinity stress in any of the eight K. brevis strains we tested, including three used in the original study. Thus, we find no support for an osmoregulatory function of brevetoxins. The original publication also stated that there was no known cellular function for brevetoxins. However, there is increasing evidence that brevetoxins promote survival of the dinoflagellates by deterring grazing by zooplankton. Whether they have other as yet unidentified cellular functions is currently unknown

Variable expressivity of osteogenesis imperfecta in a Brazilian family due to p.G1079S mutation in the COL1A1 gene

Osteogenesis imperfecta (OI) is a Mendelian disease with genetic heterogeneity characterized by bone fragility, recurrent fractures, blue sclerae, and short stature, caused mostly by mutations in COL1A1 or COL1A2 genes, which encode the pro-alpha 1(I) and pro-alpha 2(I) chains of type I collagen, respectively. A Brazilian family that showed variable expression of autosomal dominant OI was identified and characterized. Scanning for mutations was carried out using SSCP and DNA sequence analysis. The missense mutation c.3235G&gt;A was identified within exon 45 of the COL1A1 gene in a 16-year-old girl diagnosed as having OI type I; it resulted in substitution of a glycine residue (G) by a serine (S) at codon 1079 (p.G1079S). The proband's mother had the disease signs, but without bone fractures, as did five of nine uncles and aunts of the patient. All of them carried the mutation, which was excluded in four healthy brothers of the patient's mother. This is the first description in a Brazilian family with OI showing variable expression; only one among seven carriers for the c.3235G&gt;A mutation developed bone fractures, the most striking clinical feature of this disease. This finding has a significant implication for prenatal diagnosis in OI disease.Brazilian institutions ArcelorMittal TubaraoBrazilian institutions ArcelorMittal TubaraoFundacao de Apoio ao Hospital Universitario Cassiano Antonio MoraesFundacao de Apoio ao Hospital Universitario Cassiano Antonio MoraesConselho Nacional de Desenvolvimento Cientifico e TecnologicoConselho Nacional de Desenvolvimento Cientifico e TecnologicoFundo de Apoio a Ciencia e Tecnologia de VitoriaFundo de Apoio a Ciencia e Tecnologia de VitoriaFundacao de Amparo a Pesquisa do Espirito SantoFundacao de Amparo a Pesquisa do Espirito Sant

CAIRT - The changing-atmosphere infra-red tomography explorer

Optics InfoBase Conference Papers2021 Article number FTh4G.6. Fourier Transform Spectroscopy, FTS 2021 - Part of OSA Optical Sensors and Sensing Congress 2021Virtual, Online19 July 2021 through 23 July 2021Code 174136CAIRT, a candidate for ESA’s Earth Explorer 11 mission, will observe the Earth’s limb with an imaging Fourier-transform spectrometer. It will provide global observations of ozone, temperature, water vapour and key halogen and nitrogen compounds.With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709Peer reviewe