Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll- a data

In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll-a (Chla) data and to assess the fitness-for-purpose of multi-mission Chla products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t-test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chla data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012–2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chla data can be used for multi-annual time series analysis (including trend detection), but with some caution required if recent years are included, particularly in the central tropical Pacific. The study also recalls the challenges associated with creating a multi-mission ocean color data record suitable for climate research

Нетипичная локализация нейробластомы средостения у ребенка раннего возраста

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Satellite Ocean Colour: Current Status and Future Perspective

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and interannual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided

Cell-based screen for altered nuclear phenotypes reveals senescence progression in polyploid cells after Aurora kinase B inhibition.

Cellular senescence is a widespread stress response and is widely considered to be an alternative cancer therapeutic goal. Unlike apoptosis, senescence is composed of a diverse set of subphenotypes, depending on which of its associated effector programs are engaged. Here we establish a simple and sensitive cell-based prosenescence screen with detailed validation assays. We characterize the screen using a focused tool compound kinase inhibitor library. We identify a series of compounds that induce different types of senescence, including a unique phenotype associated with irregularly shaped nuclei and the progressive accumulation of G1 tetraploidy in human diploid fibroblasts. Downstream analyses show that all of the compounds that induce tetraploid senescence inhibit Aurora kinase B (AURKB). AURKB is the catalytic component of the chromosome passenger complex, which is involved in correct chromosome alignment and segregation, the spindle assembly checkpoint, and cytokinesis. Although aberrant mitosis and senescence have been linked, a specific characterization of AURKB in the context of senescence is still required. This proof-of-principle study suggests that our protocol is capable of amplifying tetraploid senescence, which can be observed in only a small population of oncogenic RAS-induced senescence, and provides additional justification for AURKB as a cancer therapeutic target.This work was supported by the University of Cambridge, Cancer Research UK, Hutchison Whampoa; Cancer Research UK grants A6691 and A9892 (M.N., N.K., C.J.T., D.C.B., C.J.C., L.S.G, and M.S.); a fellowship from the Uehara Memorial Foundation (M.S.).This is the author accepted manuscript. The final version is available from the American Society for Cell Biology via http://dx.doi.org/10.1091/mbc.E15-01-000

Inside and out: the activities of senescence in cancer.

The core aspect of the senescent phenotype is a stable state of cell cycle arrest. However, this is a disguise that conceals a highly active metabolic cell state with diverse functionality. Both the cell-autonomous and the non-cell-autonomous activities of senescent cells create spatiotemporally dynamic and context-dependent tissue reactions. For example, the senescence-associated secretory phenotype (SASP) provokes not only tumour-suppressive but also tumour-promoting responses. Senescence is now increasingly considered to be an integrated and widespread component that is potentially important for tumour development, tumour suppression and the response to therapy.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/nrc377

A compilation of global bio-optical in situ data for ocean colour satellite applications – version three

A global in situ data set for validation of ocean colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented. This version of the compilation, starting in 1997, now extends to 2021, which is important for the validation of the most recent satellite optical sensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprises in situ observations of the following variables: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient, and total suspended matter. Data were obtained from multi-project archives acquired via open internet services or from individual projects acquired directly from data providers. Methodologies were implemented for homogenization, quality control, and merging of all data. Minimal changes were made on the original data, other than conversion to a standard format, elimination of some points, after quality control and averaging of observations that were close in time and space. The result is a merged table available in text format. Overall, the size of the data set grew with 148 432 rows, with each row representing a unique station in space and time (cf. 136 250 rows in previous version; Valente et al., 2019). Observations of remote-sensing reflectance increased to 68 641 (cf. 59 781 in previous version; Valente et al., 2019). There was also a near tenfold increase in chlorophyll data since 2016. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) are included in the final table. By making the metadata available, provenance is better documented and it is also possible to analyse each set of data separately. The compiled data are available at https://doi.org/10.1594/PANGAEA.941318 (Valente et al., 2022)

Convoluted double square: single layer FSS with close band spacings

A novel element provides reflection band ratios as low as 1.1. It is derived from the double square but is less demanding on printing definition. Together, the two elements offer increased flexibility in Frequency selective surface design for close band applications. Substrate loss effects are also discussed

On the temporal consistency of chlorophyll products derived from three ocean-colour sensors

Satellite ocean-colour sensors have life spans lasting typically five-to-ten years. Detection of long-term trends in chlorophyll-a concentration (Chl-a) using satellite ocean colour thus requires the combination of different ocean-colour missions with sufficient overlap to allow for cross-calibration. A further requirement is that the different sensors perform at a sufficient standard to capture seasonal and inter-annual fluctuations in ocean colour. For over eight years, the SeaWiFS, MODIS-Aqua and MERIS ocean-colour sensors operated in parallel. In this paper, we evaluate the temporal consistency in the monthly Chl-a time-series and in monthly inter-annual variations in Chl-a among these three sensors over the 2002–2010 time period. By subsampling the monthly Chl-a data from the three sensors consistently, we found that the Chl-a time-series and Chl-a anomalies among sensors were significantly correlated for >90% of the global ocean. These correlations were also relatively insensitive to the choice of three Chl-a algorithms and two atmospheric-correction algorithms. Furthermore, on the subsampled time-series, correlations between Chl-a and time, and correlations between Chl-a and physical variables (sea-surface temperature and sea-surface height) were not significantly different for >92% of the global ocean. The correlations in Chl-a and physical variables observed for all three sensors also reflect previous theories on coupling between physical processes and phytoplankton biomass. The results support the combining of Chl-a data from SeaWiFS, MODIS-Aqua and MERIS sensors, for use in long-term Chl-a trend analysis, and highlight the importance of accounting for differences in spatial sampling among sensors when combining ocean-colour observations