International Intercomparison of In Situ Chlorophyll-a Measurements for Data Quality Assurance of the Swedish Monitoring Program

Chlorophyll-a is an essential climate variable. Chlorophyll-a in situ measurements are usually used for the validation of satellite images. Previous intercomparisons have shown that there can be substantial differences between in situ laboratories. In order to shed light on these differences, we arranged international chlorophyll-a intercomparisons with eight participating laboratories during 1–2 July 2021. We performed two dedicated transects through Bråviken bay (NW Baltic proper) and sampled four stations in each transect along a chlorophyll-a gradient. We took three surface replicates per laboratory and per station, i.e., 24 samples per laboratory. The samples were filtered through Whatman GF/F filters, and filters were frozen in liquid nitrogen and distributed in dry ice to all laboratories together with chlorophyll-a standards. The results between labs compared quite well. The mean normalized bias (MNB) of the standard measurements ranged between −23% and +19% for all laboratories and −7% to +19% for the Baltic Sea laboratories compared to high-performance liquid chromatography. The MNB of the two Bråviken transects ranged between −23 and +17% for all laboratories (compared to the median of all spectrophotometric and fluorometric measurements) and between −2 and +17% for the Baltic Sea laboratories. On average, the chlorophyll-a concentrations measured by the fluorometric method were about 13% higher than those measured by spectrophotometry, and fluorometry samples tended to have more scatter. The largest uncertainties seem to be caused by variable storage and extraction methods and are not fully captured in this intercomparison. This is demonstrated by analyzing historical comparisons revealing very large uncertainties (root mean square difference (RMSD) up to 109% and bias up to 68%), possibly due to too low filtration volumes and due to different extraction and storage methods. Our recommendation is to flash-freeze samples in liquid nitrogen and store them at −80°C. After storage, they should be extracted and measured at room temperature within 6–24 h. Our results also indicate that ethanol is much more efficient in extracting Chl-a than acetone. Last but not least, we would like to point out that the uncertainties in measuring chlorophyll-a by satellite are now within the range of in situ data, as shown here by comparing the in situ results from this study with published remote sensing results from the literature.publishedVersio

Sensitivity Studies for the Exercise I-1 of the OECD/UAM Benchmark

OECD/NEA has initiated an international Uncertainty Analysis in Modeling (UAM) benchmark focused on uncertainties in modeling of Light Water Reactor (LWR). The first step of uncertainty propagation is to perform sensitivity to the input data affected by the numerical errors and physical models. The objective of the present paper is to study the effect of the numerical discretization error and the manufacturing tolerances on fuel pin lattice integral parameters (multiplication factor and macroscopic cross-sections) through sensitivity calculations. The two-dimensional deterministic codes NEWT and HELIOS were selected for this work. The NEWT code was used for analysis of the TMI-1, PB-2, and Kozloduy-6 test cases; the TMI-1 test case was investigated using the HELIOS code. The work has been performed within the framework of UAM Exercise I-1 "Cell Physics.

International Intercomparison of In Situ Chlorophyll-a Measurements for Data Quality Assurance of the Swedish Monitoring Program

Chlorophyll-a is an essential climate variable. Chlorophyll-a in situ measurements are usually used for the validation of satellite images. Previous intercomparisons have shown that there can be substantial differences between in situ laboratories. In order to shed light on these differences, we arranged international chlorophyll-a intercomparisons with eight participating laboratories during 1–2 July 2021. We performed two dedicated transects through Bråviken bay (NW Baltic proper) and sampled four stations in each transect along a chlorophyll-a gradient. We took three surface replicates per laboratory and per station, i.e., 24 samples per laboratory. The samples were filtered through Whatman GF/F filters, and filters were frozen in liquid nitrogen and distributed in dry ice to all laboratories together with chlorophyll-a standards. The results between labs compared quite well. The mean normalized bias (MNB) of the standard measurements ranged between −23% and +19% for all laboratories and −7% to +19% for the Baltic Sea laboratories compared to high-performance liquid chromatography. The MNB of the two Bråviken transects ranged between −23 and +17% for all laboratories (compared to the median of all spectrophotometric and fluorometric measurements) and between −2 and +17% for the Baltic Sea laboratories. On average, the chlorophyll-a concentrations measured by the fluorometric method were about 13% higher than those measured by spectrophotometry, and fluorometry samples tended to have more scatter. The largest uncertainties seem to be caused by variable storage and extraction methods and are not fully captured in this intercomparison. This is demonstrated by analyzing historical comparisons revealing very large uncertainties (root mean square difference (RMSD) up to 109% and bias up to 68%), possibly due to too low filtration volumes and due to different extraction and storage methods. Our recommendation is to flash-freeze samples in liquid nitrogen and store them at −80°C. After storage, they should be extracted and measured at room temperature within 6–24 h. Our results also indicate that ethanol is much more efficient in extracting Chl-a than acetone. Last but not least, we would like to point out that the uncertainties in measuring chlorophyll-a by satellite are now within the range of in situ data, as shown here by comparing the in situ results from this study with published remote sensing results from the literature

Molecular characterization and phylogenetic analysis of human influenza A viruses in three consecutive seasons with different epidemiological profiles

INTRODUCTION: Influenza activity and influenza virus circulation were observed in Lombardy (northern Italy) during three consecutive seasons and the molecular characteristics of circulating viruses analysed to control for introduction of new variants. METHODS: The molecular characterization of 38 isolates, namely 20 A/H3N2 and 18 A/H1N1 influenza strains from the 2005/06, 2006/07 and 2007/08 seasons, was performed by sequence analysis of the globular head region of the HA protein (HA1 subunit), specific for influenza virus A/H3 and A/H1. RESULTS AND DISCUSSION: The last three influenza seasons in the study region were characterized by medium-low activity. A typical co-circulation of several variants was shown for A/H3 viruses for approximately two years and were subsequently almost entirely substituted by new emerging variants. Vice versa, A/H1 viruses had a more homogeneous circulation with a single lineage clearly dominating each season. The HA sequences of the A/H3 and the A/H1 viruses isolated in the last three seasons fell into 4 and 3 principal phylogenetic groups, respectively. No evidence of positive or negative selection in the sequence alignments was observed. CONCLUSIONS: Molecular characterization of the influenza viruses in three consecutive seasons highlighted considerable heterogeneity in their HA sequences. A careful surveillance of genetic changes in the HA1 domain during seasonal influenza epidemics may reveal immune escape and provide early information on newly emerging strains with epidemiologic inference

Assessment of MERIS ocean color data products for European seas

The accuracy of marine data products from the Medium Resolution Imaging Spectrometer (MERIS) operated on board the Envisat platform is investigated with the aid of in situ geographically distributed measurements from different European seas. The assessment focuses on standard products from the 2012 data update commonly identified as 3rd Reprocessing. Results indicate atmospherically corrected data affected by a negative bias of several tens percent at the 413 nm center wavelength, significantly decreasing to a few percent at 560 nm and increasing again at 665 nm. Such an underestimate at the blue center wavelengths leads to an average overestimate of the algal-1 MERIS pigment index largely exceeding 100% for the considered European seas. A comparable overestimate is also observed for the algal-2 pigment index independently determined from top-of-atmosphere radiance through the application of neural networks

The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)

Ten international laboratories specializing in the determination of marine pigment concentrations using high performance liquid chromatography (HPLC) were intercompared using in situ samples and a mixed pigment sample. Although prior Sea-viewing Wide Field-of-view Sensor (SeaWiFS) High Performance Liquid Chromatography (HPLC) Round-Robin Experiment (SeaHARRE) activities conducted in open-ocean waters covered a wide dynamic range in productivity, and some of the samples were collected in the coastal zone, none of the activities involved exclusively coastal samples. Consequently, SeaHARRE-4 was organized and executed as a strictly coastal activity and the field samples were collected from primarily eutrophic waters within the coastal zone of Denmark. The more restrictive perspective limited the dynamic range in chlorophyll concentration to approximately one and a half orders of magnitude (previous activities covered more than two orders of magnitude). The method intercomparisons were used for the following objectives: a) estimate the uncertainties in quantitating individual pigments and higher-order variables formed from sums and ratios; b) confirm if the chlorophyll a accuracy requirements for ocean color validation activities (approximately 25%, although 15% would allow for algorithm refinement) can be met in coastal waters; c) establish the reduction in uncertainties as a result of applying QA procedures; d) show the importance of establishing a properly defined referencing system in the computation of uncertainties; e) quantify the analytical benefits of performance metrics, and f) demonstrate the utility of a laboratory mix in understanding method performance. In addition, the remote sensing requirements for the in situ determination of total chlorophyll a were investigated to determine whether or not the average uncertainty for this measurement is being satisfied