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ABSTRACTThe Pan-Eurasian Experiment Modelling Platform (PEEX-MP) is one of the key blocks of the PEEX Research Programme. The PEEX MP has more than 30 models and is directed towards seamless environmental prediction. The main focus area is the Arctic-boreal regions and China. The models used in PEEX-MP cover several main components of the Earth’s system, such as the atmosphere, hydrosphere, pedosphere and biosphere, and resolve the physical-chemical-biological processes at different spatial and temporal scales and resolutions. This paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system, online integrated, forward/inverse, and socioeconomical modelling, and other approaches with a particular focus on applications in the PEEX geographical domain. The employed high-performance computing facilities, capabilities, and PEEX dataflow for modelling results are described. Several virtual research platforms (PEEX-View, Virtual Research Environment, Web-based Atlas) for handling PEEX modelling and observational results are introduced. The overall approach allows us to understand better physical-chemical-biological processes, Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks, impact, consequences, etc. for population, environment and climate in the PEEX domain. This work was also one of the last projects of Prof. Sergej Zilitinkevich, who passed away on 15 February 2021. Since the finalization took time, the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.

Abstract Background Little attention has been paid to the pathophysiological changes in the natural history of chronic obstructive pulmonary disease (COPD). The destructions of the small airways were visualized on thoracic micro-computed tomography scan. We investigated whether small airway inflammation (SAI) was the risk for the development of COPD. Methods A total of 1062 patients were enrolled and analyzed in the study. The partitioned airway inflammation was determined by exhaled nitric oxide (NO) of FnNO, FeNO50, FeNO200, and calculated CaNOdual. Both FeNO200 and CaNOdual were compared to detect the promising predictor for peripheral airway/alveolar inflammation in COPD. The correlation between exhaled NO and white cell classification was evaluated to determine the inflammation type during the development of COPD. Results Exhaled NO levels (FnNO, FeNO50, FeNO200, and CaNOdual) were the highest in the COPD group compared with all other groups. Furthermore, compared with controls, exhaled NO levels (FeNO50, FeNO200, and CaNOdual) were also significantly higher in the emphysema, chronic bronchitis, and smoking groups. FeNO200 was found to be a promising predictor for peripheral airway/alveolar inflammation (area under the curve [AUC] of the receiver operating characteristic [ROC] curve, area under the curve [AUC] = 0.841) compared with CaNOdual (AUC ROC = 0.707) in COPD. FeNO200 was the main risk factor (adjusted odds ratio, 2.191; 95% CI, 1.797–2.671; p = 0.002) for the development of COPD. The blood eosinophil and basophil levels were correlated with FeNO50 and FeNO200. Conclusion The complete airway inflammations were shown in COPD, whereas SAI was the main risk factor for the development of COPD, which might relate to eosinophil and basophil levels.

Abstract Background Acute respiratory distress syndrome (ARDS) is a disease with high mortality and morbidity. Regulator of G protein signaling protein 6 (RGS6), identified as a tumor suppressor gene, has received increasing attention owing to its close relationship with oxidative stress and inflammation. However, the association between ARDS and RGS6 has not been reported. Methods Congruously regulated G protein-coupled receptor (GPCR)-related genes and differentially expressed genes (DEGs) in an acute lung injury (ALI) model were identified, and functional enrichment analysis was conducted. In an in vivo study, the effects of RGS6 knockout were studied in a mouse model of ALI induced by lipopolysaccharide (LPS). HE staining, ELISA, and immunohistochemistry were used to evaluate pathological changes and the degree of inflammation. In vitro, qRT‒PCR, immunofluorescence staining, and western blotting were used to determine the dynamic changes in RGS6 expression in cells. The RGS6 overexpression plasmid was constructed for transfection. qRT‒PCR was used to assess proinflammatory factors transcription. Western blotting and flow cytometry were used to evaluate apoptosis and reactive oxygen species (ROS) production. Organoid culture was used to assess the stemness and self-renewal capacity of alveolar epithelial type II cells (AEC2s). Results A total of 110 congruously regulated genes (61 congruously upregulated and 49 congruously downregulated genes) were identified among GPCR-related genes and DEGs in the ALI model. RGS6 was downregulated in vivo and in vitro in the ALI model. RGS6 was expressed in the cytoplasm and accumulated in the nucleus after LPS stimulation. Compared with the control group, we found higher mortality, more pronounced body weight changes, more serious pulmonary edema and pathological damage, and more neutrophil infiltration in the RGS6 knockout group upon LPS stimulation in vivo. Moreover, AEC2s loss was significantly increased upon RGS6 knockout. Organoid culture assays showed slower alveolar organoid formation, fewer alveolar organoids, and impaired development of new structures after passaging upon RGS6 knockout. In addition, RGS6 overexpression decreased ROS production as well as proinflammatory factor transcription in macrophages and decreased apoptosis in epithelial cells. Conclusions RGS6 plays a protective role in ALI not only in early inflammatory responses but also in endogenous lung stem cell regeneration. Graphical Abstract

Abstract Background Data that guide selection of differing anticoagulant regimens for specific cancer-associated venous thromboembolism (VTE) are lacking. We aimed to compare the efficacy and safety of rivaroxaban and low-molecular-weight heparin (LMWH) against nonhigh-risk pulmonary embolism (PE) in Chinese lung cancer patients. Methods Four hundred forty-six Chinese lung cancer patients with nonhigh-risk PE who initiated treatment with rivaroxaban or LMWH were identified from Zhongshan Hospital database from 2016 to 2020. The primary outcomes were the composite event of VTE recurrence or major bleeding, and all-cause mortality. The secondary outcomes were VTE recurrence, major bleeding and clinically relevant non-major bleeding (CRNMB). Propensity score matching was used to balance baseline covariates. We conducted sensitivity analysis by stabilized inverse probability of treatment weighting and competing risk analysis by a Fine and Gray subdistribution hazard model. Results In propensity score-matched cohorts, rivaroxaban was similar to LMWH in the risks of the composite outcome (hazard ratio (HR), 0.73; 95% confidence interval (CI), 0.45–1.21; P = 0.22), VTE recurrence (HR, 0.69; 95% CI, 0.36–1.34; P = 0.28), major bleeding (HR, 0.79; 95% CI, 0.37–1.68; P = 0.54) and CRNMB (HR, 1.13; 95% CI, 0.62–2.09; P = 0.69). All-cause mortality was significantly lower in rivaroxaban group than LMWH group (HR, 0.52; 95% CI, 0.36–0.75; P

The EuroGOOS Coastal working group examines the entire coastal value chain from coastal observations to services for coastal users. The main objective of the working group is to review the status quo, identify gaps and future steps needed to secure and improve the sustainability of the European coastal service provision. Within this framework, our white paper defines a EuroGOOS roadmap for sustained “community coastal downstream service” provision, provided by a broad EuroGOOS community with focus on the national and local scale services. After defining the coastal services in this context, we describe the main components of coastal service provision and explore community benefits and requirements through sectoral examples (aquaculture, coastal tourism, renewable energy, port, cross-sectoral) together with the main challenges and barriers to user uptake. Technology integration challenges are outlined with respect to multiparameter observations, multi-platform observations, the land-coast-ocean continuum, and multidisciplinary data integration. Finally, the technological, financial, and institutional sustainability of coastal observing and coastal service provision are discussed. The paper gives special attention to the delineation of upstream and downstream services, public-private partnerships and the important role of Copernicus in better covering the coastal zone. Therefore, our white paper is a policy and practice review providing a comprehensive overview, in-depth discussion and actionable recommendations (according to key short-term or medium-term priorities) on the envisaged elements of a roadmap for sustained coastal service provision. EuroGOOS, as an entity that unites European national operational oceanography centres, research institutes and scientists across various domains within the broader field of operational oceanography, offers to be the engine and intermediary for the knowledge transfer and communication of experiences, best practices and information, not only amongst its members, but also amongst the different (research) infrastructures, institutes and agencies that have interests in coastal oceanography in Europe.

Abstract Coronavirus disease 2019 (COVID‐19), the highly contagious viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has spread worldwide with millions of cases and more than 5 million deaths to date. SARS‐CoV‐2 has caused serious damage all over the world with many countries experiencing the third or the fourth wave of the viral disease outbreaks, mainly due to the emergence of mutant variants. Those who unvaccinated remain most vulnerable to COVID‐19 and its variants. COVID‐19 vaccination, along with prevention strategies, is a critical measure to defense against the disease. COVID‐19 vaccination can reduce the spread of virus and help protect susceptible population. Although herd immunity might not be realized solely by vaccination, COVID‐19 vaccines have been proved to be effective in reducing the risk of severe disease, hospitalization, and even death. It is recommended that people get vaccinated as soon as they are eligible. This review summarizes the recent SARS‐CoV‐2 variants that brought challenges for vaccination and herd immunity and discusses promising management strategies.

We simulated the spatial distribution and dynamics of macro plastic in the Baltic Sea, using a new Lagrangian approach called the dynamical renormalization resampling scheme (DRRS). This approach extends the super-individual simulation technique, so the weight-per-individual is dynamic rather than fixed. The simulations were based on a mapping of the macro plastic sources along the Baltic coast line, and a five year time series of realistic wind, wave and current data to resolve time-variability in the transport and spatial distribution of macro plastics in the Baltic Sea. The model setup has been validated against beach litter observations and was able to reproduce some major spatial trends in macroplastic distributions. We also simulated plastic dispersal using Green’s functions (pollution plumes) for individual sources. e.g. rivers, and found a significant variation in the spatial range of Green’s functions corresponding to different pollution sources. We determined a significant temporal variability (up to 7 times the average) in the plastic concentration locally, which needs to be taken into account when assessing the ecological impact of marine litter. Accumulation patterns and litter wave formation were observed to be driven by an interplay between positive buoyancy, coastal boundaries and varying directions of physical forcing. Finally we determined the range of wind drag coefficients for floating plastic, where the dynamics is mostly directly wind driven, as opposed to indirectly by surface currents and waves. This study suggests that patterns of litter sorting by transport processes should be observable in many coastal and off-shore environments.

Offshore wind energy installations in coastal areas have grown massively over the last decade. This development comes with a large number of technological, environmental, economic, and scientific challenges, which need to be addressed to make the use of offshore wind energy sustainable. One important component in these optimization activities is suitable information from observations and numerical models. The purpose of this study is to analyze the gaps that exist in the present monitoring systems and their respective integration with models. This paper is the second part of two manuscripts and uses results from the first part about the requirements for different application fields. The present solutions to provide measurements for the required information products are described for several European countries with growing offshore wind operations. The gaps are then identified and discussed in different contexts, like technology evolution, trans-European monitoring and modeling initiatives, legal aspects, and cooperation between industry and science. The monitoring gaps are further quantified in terms of missing observed quantities, spatial coverage, accuracy, and continuity. Strategies to fill the gaps are discussed, and respective recommendations are provided. The study shows that there are significant information deficiencies that need to be addressed to ensure the economical and environmentally friendly growth of the offshore wind farm sector. It was also found that many of these gaps are related to insufficient information about connectivities, e.g., concerning the interactions of wind farms from different countries or the coupling between physical and biological processes.

The rapid expansion of offshore wind farms (OWFs) in European seas is accompanied by many challenges, including efficient and safe operation and maintenance, environmental protection, and biodiversity conservation. Effective decision-making for industry and environmental agencies relies on timely, multi-disciplinary marine data to assess the current state and predict the future state of the marine system. Due to high connectivity in space (land–estuarial–coastal sea), socioeconomic (multi-sectoral and cross-board), and environmental and ecological processes in sea areas containing OWFs, marine observations should be fit for purpose in relation to multiple OWF applications. This study represents an effort to map the major observation requirements (Part-I), identify observation gaps, and recommend solutions to fill those gaps (Part-II) in order to address multi-dimension challenges for the OWF industry. In Part-I, six targeted areas are selected, including OWF operation and maintenance, protection of submarine cables, wake and lee effects, transport and security, contamination, and ecological impact assessments. For each application area, key information products are identified, and integrated modeling–monitoring solutions for generating the information products are proposed based on current state-of-the-art methods. The observation requirements for these solutions, in terms of variables and spatial and temporal sampling needs, are therefore identified.

Marine plastic litter has been recognized as a growing problem and a threat to the marine environment and ecosystems, although its impacts on the marine life are still largely unknown. Marine protection and conservation actions require a detailed knowledge of the marine pathways, sources, and sinks of land-emitted plastic pollution. Model-based assessments provide a systematic way to map the occurrence of microplastics in the marine environment and to link the coastal sources to the accumulation zones in the sea. New modeling capacities have been developed, which include relevant key processes, i.e., current- and wave-induced horizontal and vertical transport, biofilm growth on the particle surface, sinking, and sedimentation. The core engine is the HIROMB-BOOS ocean circulation model, which has been set up for the Baltic Sea in a high, eddy-permitting resolution of approximately 900 m. We introduce the three-dimensional modeling tool for microplastics and demonstrate its ability to reproduce the drift pattern of microplastics in the Baltic Sea. The results of a multiyear run 2014–2019 provide the basis for an extensive validation study, which allows the evaluation of the model quality. The assessments focus on three types of microplastics, from car tires and household products, with different densities and particle sizes, which cover a broad range of land-emitted microplastic pollution. We show that the model is applicable to the task of identifying high concentration zones in the Baltic Sea and that it can be a useful tool to support the study of the environmental impacts of microplastics in the Baltic Sea. Our results suggest that microplastic concentrations in coastal regions close to major sources reach values above 0.0001 g/m3 near the surface, dependent on the buoyancy of the plastic material and the amount of discharge. The comparison with observations shows that the model is able to reproduce the average concentrations of measured microplastics in the size class of 300 μm with statistical significance, but it underestimates the very high concentrations associated either with flooding or high river-runoff events or generated by sub-mesoscale transport. The model is able to reproduce the seasonal dynamic in Latvian and Estonian waters, except for October, when the increase of modelled microplastics in the ocean is too slow. But the general spatial patterns are sufficiently well reproduced, which makes the developed model a tool sufficient for the assessment of microplastic transport and accumulation pattern.

This paper aims to quantify data uncertainties in marine microplastic measurements, including spatiotemporal sampling error and sample volume estimation error, identify impacts of varying mesh sizes, sampling and analysis methods, and evaluate consistency in multiple microplastic observation datasets. Twenty-seven datasets on surface marine microplastics with particle size >100 µm in the Baltic Sea are compiled. Results show that the trawl datasets have a spatiotemporal sampling error of 25% for microlitter concentration, 36% for microplastic fiber concentrations and 40-56% for microplastic particle concentration. By taking surface currents and wave-induced Stokes drift into account, the sample volume of the trawl measurements is corrected, leading to a mean microplastic concentration correction of 12%. The differences of microplastic concentration between datasets with varying mesh sizes from 100 – 500 µm are not statistically significant. Analysis methods, however, can lead to significant differences in microplastic datasets. The dataset consistency is further examined among the three dataset categories using trawl, pump and bulk sampling techniques. It is found that an individual dataset is often self-consistent. Most of the datasets within one monitoring category are more consistent than those from different categories. More than 70% of the datasets within individual categories are consistent, which have mean microplastic concentration significantly smaller than the rest of the datasets. Significant inconsistencies are identified between different data categories. Six out of eight highest relative standard deviations are found in the pump and bulk datasets. The median value of the mean microplastic concentration from the 10 pump datasets is about 4.5 times as much as that of the 14 trawl datasets, both for fiber and non-fiber particles. Significant differences are also identified on microplastic fiber fraction in different dataset categories. Two thirds of the 13 bulk and pump datasets have a microplastic fiber fraction >85% while the 14 trawl datasets show much lower microplastic fiber fractions between 45-70%. In addition, the particle collection efficiency, potential leakage of particles with irregular shapes, clogging, the false zero samples and related lower limit of the detectable microplastic concentration for given sampling methods and water environment, are also discussed.

The direct-lit LED backlight is a key component in large-area LCD displays. The existing methods which rely on point source assumption and irradiance feedback are less effective in compact designs in near field, and designing thin and high-quality back-lit LED backlights still remains a challenging issue. In this paper, we develop a direct method for designing thin and high-quality back-lit LED backlight systems. The étendue of LED light sources is considered in the numerical calculation of the lens profiles without cumbersome Monte Carlo ray tracing, which allows us to obtain compact LED lighting modules and achieve accurate control of the near-field irradiance distribution of the backlight system. Two examples are presented to demonstrate the elegance of this method in designing thin and high-quality back-lit LED backlights.

Experiments exploring the propagation of heat waves within cylindrical CH foams were performed on the Shenguang-III prototype laser facility in 2012. In this paper, the radiation fluxes out of CH foam cylinders at different angles are analyzed theoretically using the two-dimensional radiation hydrodynamics code LARED-R. Owing to the difficulty in validating opacity and equation of state (EOS) data for high-Z plasmas, and to uncertainties in the measured radiation temperature Tr and the original foam density ρ0, multipliers are introduced to adjust the Au material parameters, Tr, and ρ0 in our simulations to better explain the measurements. The dependences of the peak radiation flux Fmax and the breakout time of the heat wave thalf (defined as the time corresponding to the radiation flux at half-maximum) on the radiation source, opacity, EOS, and ρ0 scaling factors (ηsrc, ηop, ηeos, and ηρ) are investigated via numerical simulations combined with fitting. Then, with the uncertainties in the measured Tr and ρ0 fixed at 3.6% and 3.1%, respectively, experimental data are exploited as fiducial values to determine the ranges of ηop and ηeos. It is found that the ranges of ηop and ηeos fixed by this experiment overlap partially with those found in our previous work [Meng et al., Phys. Plasmas 20, 092704 (2013)]. Based on the scaled opacity and EOS parameters, the values of Fmax and thalf obtained via simulations are in good agreement with the measurements, with maximum errors ∼9.5% and within 100 ps, respectively.

Litter cleanup and disposal management in the marine environment are increasingly subject to public scrutiny, government regulation and stakeholder initiatives. In practice, ongoing efforts and new investment decisions, for example in new cleanup technologies, are constrained by financial and economic resources. Given budgetary restrictions, it is important to optimize decision-making using a scientific framework that takes into account the various effects of investments by combining multiple scientific perspectives and integrating these in a consistent and coherent way. Identifying optimal levels of marine litter cleanup is a challenge, because of its cross-disciplinary nature, involving physics, environmental engineering, science, and economics. In this paper, we propose a bridge-building, spatial cost-benefit optimization framework that allows prioritizing where to apply limited cleanup efforts within a regional spatial network of marine litter sources, using input from the maturing field of marine litter transport modeling. The framework also includes ecosystem functioning in relation to variable litter concentrations, as well as the potentially non-linear cost-efficiency of cleanup technologies. From these three components (transport modeling, ecosystem functioning, cleanup-effectiveness), along with litter source mapping, we outline the optimal cleanup solution at any given ecological target or economic constraint, as well as determine the cleanup feasibility. We illustrate our framework in a Baltic and Mediterranean Sea case study, using real data for litter transport and cleanup technology. Our study shows that including pollution Green's functions is essential to assess the feasibility of cleanup and determine optimal deployment of cleanup investments, where the presented framework combines physical, economical, technological and biological data consistently to compare and rank alternatives.

Abstract An ongoing outbreak of 2019-nCoV pneumonia was first identified in Wuhan, Hubei province, China at the end of 2019. With the spread of the new coronavirus accelerating, person-to-person transmission in family homes or hospitals, and intercity spread of 2019-nCoV occurred. At least 40,261 cases confirmed, 23,589 cases suspected, 909 cases death and 3444 cases cured in China and worldwide 24 countries confirmed 383 cases being diagnosed, 1 case death in February 10th, 2020. At present, the mortality of 2019-nCoV in China is 2.3%, compared with 9.6% of SARS and 34.4% of MERS reported by WHO. It seems the new virus is not as fatal as many people thought. Chinese authorities improved surveillance network, made the laboratory be able to recognize the outbreak within a few weeks and announced the virus genome that provide efficient epidemiological control. More comprehensive information is required to understand 2019-nCoV feature, the epidemiology of origin and spreading, and the clinical phenomina. According to the current status, blocking transmission, isolation, protection, and alternative medication are the urgent management strategies against 2019-nCoV.

A powerful forward error correction (FEC) scheme based on the serial concatenation of Bose-Chaudhuri-Hocquenghen (BCH) and low-density parity-check (LDPC) codes has been adopted by the second generation digital video broadcast (DVB-S2) standard due to their near Shannon limit performance. This paper proposes an efficient FEC encoder core to support different DVB-S2 codes for variable coding modulation (VCM) schemes of low earth orbit (LEO) satellite-ground communications. By exploring the properties of different concatenated BCH-LDPC codes and reusing the computation units and memories, the compatibility is achieved and the utilization of hardware resources is improved. Besides, parallel computing is performed to speed up the acquisition of check bits, which allows the encoding throughput to be increased. Hardware architecture implementation on Xilinx XC7K325t field programmable gate array (FPGA) shows that the encoding throughput rate of the proposed FEC encoder core can reach 1.19 Gb/s. And the overall data throughput is improved by 30.9% compared with the constant coding modulation (CCM) schemes.

Coastal zones are among the most variable environments. As such, they require adaptive water management to ensure the balance of economic and social interests with environmental concerns. High quality marine data of hydrographic conditions e.g., sea level, temperature, salinity, and currents are needed to provide a sound foundation for the decision making process. Operational models with sufficiently high forecasting quality and resolution can be used for a further extension of the marine service toward the coastal-estuary areas. The Limfjord is a large and shallow water body in Northern Jutland, connecting the North Sea in the West and the Kattegat in the East. It is currently not covered by the CMEMS service, despite its importance for sea shipping, aquaculture and mussel fisheries. In this study, we use the operational HIROMB-BOOS Model (HBM) to resolve the full Baltic-Limfjord-North Sea system with a horizontal resolution of 185.2 m in the Limfjord. The study shows several factors that are essential for successfully modeling the coastal-estuary system: (a) high computational efficiency and flexible grids to allow high resolution in the fjord, (b) an improved short wave radiation scheme to model the thermodynamics and the diurnal variability of the temperature in very shallow waters, (c) high resolution atmospheric forcing, (d) adequate river forcing, and (e) accurate bathymetry in the narrow straits. With properly resolving these issues, the system is able to provide high quality sea level forecast for storm surge warning and hydrography forecasts: temperature, salinity and currents with sufficiently good quality for ecosystem-based management. The model is able to simulate the complex spatial and temporal pattern of sea level, salinity and temperature in the Limfjord and to reproduce their diurnal, seasonal and interannual variability and stratification rather well. Its high computational efficiency makes it possible to model the transition from the basin-scales to coastal- and estuary-scales seamlessly. In total, The HBM model has been successfully extended, to include the complex estuary system of the Limfjord, and shows an adequate model performance with regards to sea level, salinity and temperature predictions, suitable for storm surge warning applications and coastal management applications.

Background. Limited information exists about the nature of late-onset asthma (LOA) without medication intervention when compared to early-onset asthma (EOA). Our goal was to understand how EOA and LOA affect clinical and pathophysiological features. Methods. A population-based cross-sectional study was carried out in Zhongshan Hospital (Shanghai, China). EOA and LOA were based on age of diagnosis (before and after age 40 years, respectively). Clinical variables were collected with an emphasis on allergic features, analyzed, related, and compared using one-way ANOVA or Kruskal-Wallis test. Correlations between blood basophils and clinical data were evaluated by Spearman’s rank test. Statistical analyses were conducted with SPSS v24.0. Results. Of a total of 12,760 adults with cough, sputum, or chest tightness, 90 subjects with EOA (mean age ± standard deviation (SD):28.73 ± 5.89), 111 with LOA (mean age ± SD: 60.25 ± 9.85), and 106 with chronic obstructive pulmonary disease (COPD) (mean age ± SD: 61.58 ± 10.95) were selected. FEV1/FVC (%), FEV1% predicted, and FVC% predicted were all significantly lower in LOA compared to EOA p

A novel, experimental massive channel matrix model for indoor scenarios is proposed. In this model, the hand-held effects of smartphone users are taken into consideration, as well as the correlation and coupling at transmitters and receivers in the conventional models. Hence, the proposed model is more applicable in real environments. Measurements at 3.5 GHz are carried out in a typical indoor scenario with a massive multiple-input multiple-output (MIMO) testbed to serve as a base station and an eight-antenna handset to mimic a smartphone. Channel performance predicted by the proposed model is in good agreement with the measurement results. It is highlighted that the proposed model is more accurate than the traditional massive MIMO channel matrix models.

An overview of the current European capacity in terms of operational modeling of marine and coastal systems is presented. This overview is compiled from a survey conducted in 2018–2019 among members of EuroGOOS and its related network of Regional Operational Oceanographic Systems, addressing the purposes, context and technical specificities of operational modeling systems. Contributions to the survey were received from 49 organizations around Europe, which represent 104 operational model systems simulating mostly hydrodynamics, biogeochemistry and sea waves. The analysis of contributions highlights the strengths and weaknesses of the current capacity from an operational point of view, and leads to the formulation of recommendations toward the improvement of marine operational modeling services in Europe. In particular, this study highlights the heterogeneity of the European operational modeling capacity in terms of atmospheric and land boundary conditions, its limited deployment for biogeochemical phenomena, and a restricted use of data assimilation methods. In order to improve the accuracy of their simulations, model operators aim toward a further refinement of spatial resolution, and identify the quality and accessibility of forcing data and the suitability of observations for data assimilation as restricting factors. The described issues call for institutional integration efforts and promotion of good practices to homogenize operational marine model implementations, and to ensure that external forcing datasets, observation networks and process formulations and parameterizations are adequately developed to enable the deployment of high-level operational marine and coastal modeling services across Europe.

Two important communities related to oceanography in the Baltic Sea are those working on operational oceanography and Earth system science, with focusing on the same water body but different temporal scales. They have been coordinated through two organizations/programs: the Baltic Sea Operational Oceanographic System (BOOS) and the Baltic Sea Experiment (BALTEX) and its successor, the Baltic Earth Program (Earth system science for the Baltic Sea region), respectively. Although the two communities have archived significant progresses in their own fields since early 1990s, there were few interactions between the communities. Rapid advancements of operational oceanography on ocean monitoring, data sharing, modeling, and historical ocean state reconstruction in the last decade have provided a wide range of data, products and modeling tools which may be used in Earth system and climate change research. This is especially true when operational oceanography in the Baltic Sea is in a transition to a seamless service, i.e., from basin to local scales, from synoptic to climate scales and from physical to biogeochemical and biological systems. On the other hand, the Baltic Sea Earth system research can help to improve operational oceanography by contributing research observations and transferring their research achievements to the operational system. Based on a review of state-of-the-art of BOOS monitoring and modeling capabilities and on-going BOOS research, this paper will highlight topics and areas which are related to the Baltic Earth Grand Challenges, i.e., salinity dynamics, land-sea biogeochemical linkages, natural hazards and extreme events, sea level dynamics, coastal morphology and erosion, regional variability of water and energy exchanges, and multi-drivers of regional Earth system changes. Potential win-win cooperation and interaction between the BOOS and the Baltic Earth communities are also proposed and discussed.

A method for reconstruction of gridded fields of sea surface variables from time-dependent observations, using sub-regional EOF (Empirical Orthogonal Functions) patterns from models, is presented and tested. Covariance fields, calculated from the model results over long enough time span, are used to find EOF modes. The gravest “observational” amplitudes and their first temporal derivatives are determined from the least-square minimization of fitting errors in relation to the observed values. The field is reconstructed by superposition of continuous model-based mode patterns multiplied by observational amplitudes that meet adopted statistical limits. If the observational amplitude exceeds the limits, gridded fields for this and higher modes are not produced. We applied the method in the northeastern Baltic over the model time series 2010–2015. Daily averages of sea surface temperature (SST) and salinity (SSS) from the high-resolution (grid step 0.5 nautical miles) sub-regional HBM model were spatially averaged over bins of 5 × 5 nautical miles. Three first modes cover 99% of variance of temperature and 61.4% of salinity. As shown by experiments with pseudo-observations (model values at these points reconstructed to the model grid and then compared with the original model data), reconstruction performance depends on the configuration of the observation points in the model domain. Still, a few first modes usually produce acceptable results. When removing the SST seasonal cycle prior to EOF analysis, spatial patterns of leading modes remained practically unchanged, share of variance of the three first modes was reduced to 88.6% and reconstruction errors were reduced by about 25%. Sufficient spatial data coverage of the larger basin with ship-born observations usually takes quite long time – of the order of month; therefore, time correction of the amplitudes using the found temporal derivatives improves the accuracy of reconstruction. The method is compared with the Optimal Interpolation (OI) by using the pseudo-observations. Results show that, for SST reconstruction, the OI method is significantly worse than the EOF method. For SSS, OI is slightly better than EOF. The superiority of EOF is that the remote correlation patterns can be used in the reconstruction, which is important when the observations are sparse.

2D sea level trend and variability fields of the Baltic Sea were reconstructed based on statistical modeling of monthly tide gauge observations, and model reanalysis as a reference. The reconstruction included both absolute and relative sea level (RSL) in 11 km resolution over the period 1900–2014. The reconstructed monthly sea level had an average correlation of 96% and root mean square error of 3.8 cm with 56 tide gauges independent of the statistical model. The statistical reconstruction of sea level was based on multiple linear regression and took land deformation information into account. An assessment of the quality of an open ocean altimetry product (ESA Sea Level CCI ECV, hereafter “the CCI”) in this regional sea was performed by validating the variability against the reconstruction as an independent source of sea level information. The validation allowed us to determine how close to the coast the CCI can be considered reliable. The CCI matched reconstructed sea level variability with correlation above 90% and root-mean-square (RMS) difference below 6 cm in the southern and open part of the Baltic Proper. However, areas with seasonal sea ice and areas of high natural variability need special treatment. The reconstructed RSL change, which is important for coastal communities, was found to be dominated by isostatic land movements. This pattern was confirmed by independent observations and the values were provided along the entire coastline of the Baltic Sea. The area averaged absolute sea level change for the Baltic Sea was 1.3 ± 0.3 mm/yr for the 20th century, which was slightly below the global mean for the same period. Considering the relative shortness of the satellite era, natural variability made trend estimation sensitive to the selected data period, but the linear trends derived from the reconstruction (3.4 ± 0.7 mm/yr for 1993–2014) fitted with those of the CCI (4.0 ± 1.4 mm/yr for 1993–2015) and with global mean estimates within the limits of uncertainty.

Maritime economy, ecosystem-based management and climate change adaptation and mitigation raise emerging needs on coastal ocean and biological observations. Integrated ocean observing aims at optimizing sampling strategies and cost-efficiency, sharing data and best practices, and maximizing the value of the observations for multiple purposes. Recently developed cost-effective, near real time technology such as gliders, radars, ferrybox, and shallow water Argo floats, should be used operationally to generate operational coastal sea observations and analysis. Furthermore, value of disparate coastal ocean observations can be unlocked with multi-dimensional integration on fitness-for-the-purpose, parameter and instrumental. Integration of operational monitoring with offline monitoring programs, such as those for research, ecosystem-based management and commercial purposes, is necessary to fill the gaps. Such integration should lead to a system of networks which can deliver data for all kinds of purposes. Detailed integration activities are identified which should enhance the coastal ocean and biological observing capacity. Ultimately a program is required which integrates physical, biogeochemical and biological observation of the ocean, from coastal to deep-sea environments, bringing together global, regional, and local observation efforts.

Marine data are needed for many purposes: for acquiring a better scientific understanding of the marine environment, but also, increasingly, as marine knowledge for decision making as well as developing products and services supporting economic growth. Data must be of sufficient quality to meet the specific users' needs. It must also be accessible in a timely manner. And yet, despite being critical, this timely access to known-quality data proves challenging. Europe's marine data have traditionally been collected by a myriad of entities with the result that much of our data are scattered throughout unconnected databases and repositories. Even when data are available, they are often not compatible, making the sharing of the information and data aggregation particularly challenging. In this paper, we present how the European Marine Observation and Data network (EMODnet) has developed over the last decade to tackle these issues. Today, EMODnet is comprised of more than 150 organizations which gather marine data, metadata, and data products and make them more easily accessible for a wider range of users. EMODnet currently consists of seven sub-portals: bathymetry, geology, physics, chemistry, biology, seabed habitats, and human activities. In addition, Sea-basin Checkpoints have been established to assess the observation capacity in the North Sea, Mediterranean, Atlantic, Baltic, Artic, and Black Sea. The Checkpoints identify whether the observation infrastructure in Europe meets the needs of users by undertaking a number of challenges. To complement this, a Data Ingestion Service has been set up to tackle the problem of the wealth of marine data that remain unavailable, by reaching out to data holders, explaining the benefits of sharing their data and offering a support service to assist them in releasing their data and making them available through EMODnet. The EMODnet Central Portal (www.emodnet.eu) provides a single point of access to these services, which are free to access and use. The strategic vision of EMODnet in the next decade is also presented, together with key focal areas toward a more user-oriented service, including EMODnet for business, internationalization for global users, and stakeholder engagement to connect the diverse communities across the marine knowledge value chain.

The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical and biogeochemical ocean and sea-ice state for the global ocean and the European regional seas. CMEMS serves a wide range of users (more than 15,000 users are now registered to the service) and applications. Observations are a fundamental pillar of the CMEMS value-added chain that goes from observation to information and users. Observations are used by CMEMS Thematic Assembly Centres (TACs) to derive high-level data products and by CMEMS Monitoring and Forecasting Centres (MFCs) to validate and constrain their global and regional ocean analysis and forecasting systems. This paper presents an overview of CMEMS, its evolution, and how the value of in situ and satellite observations is increased through the generation of high-level products ready to be used by downstream applications and services. The complementary nature of satellite and in situ observations is highlighted. Long-term perspectives for the development of CMEMS are described and implications for the evolution of the in situ and satellite observing systems are outlined. Results from Observing System Evaluations (OSEs) and Observing System Simulation Experiments (OSSEs) illustrate the high dependencies of CMEMS systems on observations. Finally future CMEMS requirements for both satellite and in situ observations are detailed.

To investigate the characteristics and survival of lung cancer patients with additional malignant primary cancers.Records of lung cancer patients newly diagnosed in Shanghai Pulmonary Hospital between January 2000 and January 2010 were retrospectively reviewed. Patients with second primary lung cancer and those with lung cancer only were included for detailed analysis.Of 27642 newly diagnosed lung cancer patients, 283 patients (1.02%) suffered previous additional primary cancers. Compared with single primary lung cancer, patients with secondary lung cancer associated other primary cancers were more often women (female to male ratio 1:1.72 vs 1:2.58, P = 0.018), older (64.2 vs 60.5 years old, P

We configured a coupled model system, comprising a regional climate model (RCM) and a regional ocean model, for the North Sea and Baltic Sea region at 6 nm resolution. A two-way nested fine-grid (1 nm) ocean domain is for the first time included for the Danish coastal waters in coupled RCMs to resolve the water exchange between the two regional seas. Here, we (1) assess the sensitivity of the near-surface atmosphere to prescribed sea surface temperatures (SSTs) from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim (ERAI) reanalysis and those modelled by the coupled system, and (2) examine different ocean responses in coarse and fine grids to atmospheric forcing. The experiments were performed covering the years 1990–2010, both using ERAI lateral boundary conditions. ERAI SSTs generally agree well with satellite SSTs in summer with differences within 1°C, but the ERAI overestimates the ice extent by 72% in winter due to the coarse resolution in the Baltic Sea. The atmosphere in the Baltic land–sea transition was more sensitive to high-resolution modelled SSTs with a significant improvement in winter, but it also provided a cold bias in summer as a combination of errors from both atmospheric and ocean models. Overall, the coupled simulation without observational constraints showed only minor deviations in the air–sea interface in the Baltic coastal region compared to the prescribed simulation, with seasonal mean differences within 2°C in 2 m air temperatures and 1°C in SSTs. An exception was in the Danish water, where the fine-grid ocean model yielded a better agreement with SST measurements and showed a smaller difference between the two simulations than the coarse-grid ocean model did. In turn, the modification on the atmosphere induced by modelled SSTs was negligible. The atmospheric–ocean–ice model in this configuration was found capable of reproducing the observed interannual variability of SST and ice extent in the Baltic Sea as well as the monthly extreme wind speeds and sea levels on a local scale for Denmark during the period 1990–2010. This article provides the first results in an attempt to resolve the Danish coasts with this accuracy in an RCM as a first step towards a fully coupled system for the region of interest.

Abstract Background Among the neurological complications of influenza in children, the most severe is acute necrotizing encephalopathy (ANE), with a high mortality rate and neurological sequelae. ANE is characterized by rapid progression to death within 1–2 days from onset. However, the knowledge about the early diagnosis of ANE is limited, which is often misdiagnosed as simple seizures/convulsions or mild acute influenza-associated encephalopathy (IAE). Objective To develop and validate an early prediction model to discriminate the ANE from two common neurological complications, seizures/convulsions and mild IAE in children with influenza. Methods This retrospective case-control study included patients with ANE (median age 3.8 (2.3,5.4) years), seizures/convulsions alone (median age 2.6 (1.7,4.3) years), or mild IAE (median age 2.8 (1.5,6.1) years) at a tertiary pediatric medical center in China between November 2012 to January 2020. The random forest algorithm was used to screen the characteristics and construct a prediction model. Results Of the 433 patients, 278 (64.2%) had seizures/convulsions alone, 106 (24.5%) had mild IAE, and 49 (11.3%) had ANE. The discrimination performance of the model was satisfactory, with an accuracy above 0.80 from both model development (84.2%) and internal validation (88.2%). Seizures/convulsions were less likely to be wrongly classified (3.7%, 2/54), but mild IAE (22.7%, 5/22) was prone to be misdiagnosed as seizures/convulsions, and a small proportion (4.5%, 1/22) of them was prone to be misdiagnosed as ANE. Of the children with ANE, 22.2% (2/9) were misdiagnosed as mild IAE, and none were misdiagnosed as seizures/convulsions. Conclusion This model can distinguish the ANE from seizures/convulsions with high accuracy and from mild IAE close to 80% accuracy, providing valuable information for the early management of children with influenza.