Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT - Elsa Breton; Nicolas Savoye; Peggy Rimmelin-Maury; Benoit Sautour; Eric Goberville; Arnaud Lheureux; Thierry Cariou; Sophie Ferreira; Hélène Agogué; Samir Alliouane; Fabien Aubert; Sébastien Aubin; et al. (Frontiers in Marine Science, 2023)
Introduction While crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented. Methods With a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (<20 laboratories) and multivariate datasets. Finally, the expanded uncertainty of measurement for 20 environmental variables routinely measured by SOMLIT from discrete sampling—including Essential Ocean Variables—is provided. Results, Discussion, Conclusion The examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.

Seasonal circulation regimes in the North Atlantic: Towards a new seasonality - Florentin Breton; Mathieu Vrac; Pascal Yiou; Pradeebane Vaittinada Ayar; Aglaé Jézéquel (International Journal of Climatology, 2022)
European climate variability is shaped by atmospheric dynamics over the North Atlantic and local processes. Better understanding their future seasonality is essential to anticipate changes in weather conditions for human and natural systems. We explore atmospheric seasonality over 1979–2017 and 1979–2100 with seasonal circulation regimes (SCRs), by clustering year‐round daily fields of Z500 from the ERA‐Interim reanalysis and 12 Coupled Model Intercomparison Project phase 5 (CMIP5) climate models (historical and RCP8.5 runs). The spatial and temporal variability of SCR structures and associated patterns of surface air temperature are investigated. Climate models have biases but reproduce structures and evolutions of SCRs similar to the reanalysis over 1979–2017: decreasing frequency of winter conditions (starting later and ending earlier in the year) and the opposite for summer conditions. These changes are stronger over 1979–2100 than over 1979–2017, associated with a large increase of North Atlantic seasonal mean Z500 and temperature. When using more SCRs (more freedom in definition of seasonality), the changes over 1979–2100 correspond to a long‐term swap between SCRs, resulting in similar structures (annual cycle and spatial patterns) relative to the evolution of seasonal mean Z500 and temperature. To understand whether the evolution of SCRs is linked to uniform warming, or to changes in circulation patterns, we remove the calendar trend in the Z500 regional average to define SCRs based on detrended data (d‐SCRs). The temporal properties of d‐SCRs appear almost constant whereas their spatial patterns change, indicating that the calendar Z500 regional trend drives the evolutions of SCRs, and that changing spatial patterns in d‐SCRs account for the heterogeneity of this trend. Our study suggests that historical winter conditions will continue to decrease in the future while historical summer conditions continue to increase. However, it also suggests that the spatial and temporal patterns of SCRs would remain similar, relatively to the year‐round Z500 increase.

Molecular Mechanisms of the Adsorption of a Model Protein (Human Serum Albumin) on Poly(Methylidene Malonate 2.1.2) Nanoparticles - Yoléne Bousquet; Pieter J. Swart; Nathalie Schmitt-Colin; Florence Velge-Roussel; Mirjam E. Kuipers; Dirk K. F. Meijer; Nicole Bru; Johan Hoebeke; Pascal Breton (Pharmaceutical Research, 1999)