Portuguese Sea and Atmosphere Institute

Abstract. Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly (Muñoz-Sabater, 2019a) and monthly (Muñoz-Sabater, 2019b) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.

Land surface temperature (LST) is one of the key parameters in the physics of land surface processes from local through global scales. The importance of LST is being increasingly recognized and there is a strong interest in developing methodologies to measure LST from space. However, retrieving LST is still a challenging task since the LST retrieval problem is ill-posed. This paper reviews the current status of selected remote sensing algorithms for estimating LST from thermal infrared (TIR) data. A brief theoretical background of the subject is presented along with a survey of the algorithms employed for obtaining LST from space-based TIR measurements. The discussion focuses on TIR data acquired from polar-orbiting satellites because of their widespread use, global applicability and higher spatial resolution compared to geostationary satellites. The theoretical framework and methodologies used to derive the LST from the data are reviewed followed by the methodologies for validating satellite-derived LST. Directions for future research to improve the accuracy of satellite-derived LST are then suggested.

Microplastics (MP) pollution has received increased attention over the last few years. However, while the number of studies documentating the ingestion of microplastics by fish has increased, fewer studies have addressed the toxicological effects derived from the ingestion of these small items in wild conditions. Here, MP contamination and effect biomarkers were investigated in three commercially important fish species from the North East Atlantic Ocean. From the 150 analysed fish (50 per species), 49 % had MP. In fish from the 3 species, MP in the gastrointestinal tract, gills and dorsal muscle were found. Fish with MP had significantly (p ≤ 0.05) higher lipid peroxidation levels in the brain, gills and dorsal muscle, and increased brain acetylcholinesterase activity than fish where no MP were found. These results suggest lipid oxidative damage in gills and muscle, and neurotoxicity through lipid oxidative damage and acetylcholinesterase induction in relation to MP and/or MP-associated chemicals exposure. From the 150 fish analysed, 32 % had MP in dorsal muscle, with a total mean (± SD) of 0.054 ± 0.099 MP items/g. Based on this mean and on EFSA recommendation for fish consumption by adults or the general population, human consumers of Dicentrachus labrax, Trachurus trachurus, Scomber colias may intake 842 MP items/year from fish consumption only. Based on the mean of MP in fish muscle and data (EUMOFA, NOAA) of fish consumption per capita in selected European and American countries, the estimated intake of microplastics through fish consumption ranged from 518 to 3078 MP items/year/capita. Considering that fish consumption is only one of the routes of human exposure to microplastics, this study and others in the literature emphasize the need for more research, risk assessment and adoption of measures to minimize human exposure to these particles. Thus, MP pollution and its effects should be further investigated and addressed according to the WHO 'One Health' approach.

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Land Surface Temperature (LST) is increasingly important for various studies assessing land surface conditions, e.g., studies of urban climate, evapotranspiration, and vegetation stress. The Landsat series of satellites have the potential to provide LST estimates at a high spatial resolution, which is particularly appropriate for local or small-scale studies. Numerous studies have proposed LST retrieval algorithms for the Landsat series, and some datasets are available online. However, those datasets generally require the users to be able to handle large volumes of data. Google Earth Engine (GEE) is an online platform created to allow remote sensing users to easily perform big data analyses without increasing the demand for local computing resources. However, high spatial resolution LST datasets are currently not available in GEE. Here we provide a code repository that allows computing LSTs from Landsat 4, 5, 7, and 8 within GEE. The code may be used freely by users for computing Landsat LST as part of any analysis within GEE.

In November 2004, a regional climate change workshop was held in Guatemala with the goal of analyzing how climate extremes had changed in the region. Scientists from Central America and northern South America brought long‐term daily temperature and precipitation time series from meteorological stations in their countries to the workshop. After undergoing careful quality control procedures and a homogeneity assessment, the data were used to calculate a suite of climate change indices over the 1961–2003 period. Analysis of these indices reveals a general warming trend in the region. The occurrence of extreme warm maximum and minimum temperatures has increased while extremely cold temperature events have decreased. Precipitation indices, despite the large and expected spatial variability, indicate that although no significant increases in the total amount are found, rainfall events are intensifying and the contribution of wet and very wet days are enlarging. Temperature and precipitation indices were correlated with northern and equatorial Atlantic and Pacific Ocean sea surface temperatures. However, those indices having the largest significant trends (percentage of warm days, precipitation intensity, and contribution from very wet days) have low correlations to El Niño–Southern Oscillation. Additionally, precipitation indices show a higher correlation with tropical Atlantic sea surface temperatures.

Abstract Food uptake follows rules defined by feeding behaviour that determines the kind and quantity of food ingested by fish larvae as well as how live prey and food particles are detected, captured and ingested. Feeding success depends on the progressive development of anatomical characteristics and physiological functions and on the availability of suitable food items throughout larval development. The fish larval stages present eco‐morpho‐physiological features very different from adults and differ from one species to another. The organoleptic properties, dimensions, detectability, movements characteristics and buoyancy of food items are all crucial features that should be considered, but is often ignored, in feeding regimes. Ontogenetic changes in digestive function lead to limitations in the ability to process certain feedstuffs. There is still a lack of knowledge about the digestion and absorption of various nutrients and about the ontogeny of basic physiological mechanisms in fish larvae, including how they are affected by genetic, dietary and environmental factors. The neural and hormonal regulation of the digestive process and of appetite is critical for optimizing digestion. These processes are still poorly described in fish larvae and attempts to develop optimal feeding regimes are often still on a ‘trial and error’ basis. A holistic understanding of feeding ecology and digestive functions is important for designing diets for fish larvae and the adaptation of rearing conditions to meet requirements for the best presentation of prey and microdiets, and their optimal ingestion, digestion and absorption. More research that targets gaps in our knowledge should advance larval rearing.

In support of the first Tropospheric Ozone Assessment Report (TOAR) a relational database of global surface ozone observations has been developed and populated with hourly measurement data and enhanced metadata. A comprehensive suite of ozone data products including standard statistics, health and vegetation impact metrics, and trend information, are made available through a common data portal and a web interface. These data form the basis of the TOAR analyses focusing on human health, vegetation, and climate relevant ozone issues, which are part of this special feature. Cooperation among many data centers and individual researchers worldwide made it possible to build the world’s largest collection of in-situ hourly surface ozone data covering the period from 1970 to 2015. By combining the data from almost 10,000 measurement sites around the world with global metadata information, new analyses of surface ozone have become possible, such as the first globally consistent characterisations of measurement sites as either urban or rural/remote. Exploitation of these global metadata allows for new insights into the global distribution, and seasonal and long-term changes of tropospheric ozone and they enable TOAR to perform the first, globally consistent analysis of present-day ozone concentrations and recent ozone changes with relevance to health, agriculture, and climate. Considerable effort was made to harmonize and synthesize data formats and metadata information from various networks and individual data submissions. Extensive quality control was applied to identify questionable and erroneous data, including changes in apparent instrument offsets or calibrations. Such data were excluded from TOAR data products. Limitations of a posteriori data quality assurance are discussed. As a result of the work presented here, global coverage of surface ozone data for scientific analysis has been significantly extended. Yet, large gaps remain in the surface observation network both in terms of regions without monitoring, and in terms of regions that have monitoring programs but no public access to the data archive. Therefore future improvements to the database will require not only improved data harmonization, but also expanded data sharing and increased monitoring in data-sparse regions.

Microalgae are very interesting and valuable natural sources of highly valuable bioactive compounds, such as vitamins, essential amino acids, polyunsaturated fatty acids, minerals, carotenoids, enzymes and fibre.

study area was trawled, and 86% was not trawled. Trawling activity was aggregated; the most intensively trawled areas accounting for 90% of activity comprised 77% of footprint on average. Regional swept area ratio (SAR; ratio of total swept area trawled annually to total area of region, a metric of trawling intensity) and footprint area were related, providing an approach to estimate regional trawling footprints when high-resolution spatial data are unavailable. If SAR was ≤0.1, as in 8 of 24 regions, there was >95% probability that >90% of seabed was not trawled. If SAR was 7.9, equal to the highest SAR recorded, there was >95% probability that >70% of seabed was trawled. Footprints were smaller and SAR was ≤0.25 in regions where fishing rates consistently met international sustainability benchmarks for fish stocks, implying collateral environmental benefits from sustainable fishing.

BACKGROUND: There is a growing interest in industry to replace synthetic chemicals by natural products with bioactive properties. Aromatic plants are excellent sources of bioactive compounds that can be extracted using several processes. As far as oregano is concerned, studies are lacking addressing the effect of extraction processes in bioactivity of extracts. This study aimed to characterise the in vitro antioxidant and antibacterial properties of oregano (Origanum vulgare) essential oil and extracts (in hot and cold water, and ethanol), and the chemical composition of its essential oil. RESULTS: The major components of oregano essential oil were carvacrol, β-fenchyl alcohol, thymol, and γ-terpinene. Hot water extract had the strongest antioxidant properties and the highest phenolic content. All extracts were ineffective in inhibiting the growth of the seven tested bacteria. In contrast, the essential oil inhibited the growth of all bacteria, causing greater reductions on both Listeria strains (L. monocytogenes and L. innocua). CONCLUSION: O. vulgare extracts and essential oil from Portuguese origin are strong candidates to replace synthetic chemicals used by the industry.

Abstract Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run‐up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits.

In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Abstract A grand challenge from the wind energy industry is to provide reliable forecasts on mountain winds several hours in advance at microscale (∼100 m) resolution. This requires better microscale wind-energy physics included in forecasting tools, for which field observations are imperative. While mesoscale (∼1 km) measurements abound, microscale processes are not monitored in practice nor do plentiful measurements exist at this scale. After a decade of preparation, a group of European and U.S. collaborators conducted a field campaign during 1 May–15 June 2017 in Vale Cobrão in central Portugal to delve into microscale processes in complex terrain. This valley is nestled within a parallel double ridge near the town of Perdigão with dominant wind climatology normal to the ridges, offering a nominally simple yet natural setting for fundamental studies. The dense instrument ensemble deployed covered a ∼4 km × 4 km swath horizontally and ∼10 km vertically, with measurement resolutions of tens of meters and seconds. Meteorological data were collected continuously, capturing multiscale flow interactions from synoptic to microscales, diurnal variability, thermal circulation, turbine wake and acoustics, waves, and turbulence. Particularly noteworthy are the extensiveness of the instrument array, space–time scales covered, use of leading-edge multiple-lidar technology alongside conventional tower and remote sensors, fruitful cross-Atlantic partnership, and adaptive management of the campaign. Preliminary data analysis uncovered interesting new phenomena. All data are being archived for public use.

DHA is a key nutritional n-3 PUFA and needs to be supplied by the human diet. DHA is found in significant amounts in the retinal and neuronal cell membranes due to its high fluidity. Indeed, DHA is selectively concentrated in the synaptic and retinal membranes. DHA is deemed to display anti-inflammatory properties and to reduce the risk of CVD. Consumption of larger amounts of DHA appears to reduce the risk of depression, bipolar disorder, schizophrenia and mood disorders. Conversely, it has been shown that loss of DHA from the nerve cell membrane leads to dysfunction of the central nervous system in the form of anxiety, irritability, susceptibility to stress, dyslexia, impaired memory and cognitive functions, and extended reaction times. DHA plays an important role in ensuring a healthy ageing, by thwarting macular degeneration, Alzheimer's disease, and other brain disorders at the same time as enhancing memory and strengthening neuroprotection in general. A reduced level of DHA is associated with cognitive decline during ageing. Different mechanisms for this fundamental DHA role have been put forward. Namely, neuroprotectin D1, a DHA derivative, may support brain cell survival and repair through neurotrophic, anti-apoptotic, and anti-inflammatory signalling. Many of the effects of DHA on the neurological system may be related to signalling connections, thus leading to the study of the related signalolipidomics. Therefore, the present review will focus on the influence of DHA deficiency upon ageing, with specific emphasis upon neurological disorders related to cognitive function and mental health.

Abstract. Planktonic foraminifera preserved in marine sediments archive the physical and chemical conditions under which they built their shells. To interpret the paleoceanographic information contained in fossil foraminifera, the recorded proxy signals have to be attributed to the habitat and life cycle characteristics of individual species. Much of our knowledge on habitat depth is based on indirect methods, which reconstruct the depth at which the largest portion of the shell has been calcified. However, habitat depth can be best studied by direct observations in stratified plankton nets. Here we present a synthesis of living planktonic foraminifera abundance data in vertically resolved plankton net hauls taken in the eastern North Atlantic during 12 oceanographic campaigns between 1995 and 2012. Live (cytoplasm-bearing) specimens were counted for each depth interval and the vertical habitat at each station was expressed as average living depth (ALD). This allows us to differentiate species showing an ALD consistently in the upper 100 m (e.g., Globigerinoides ruber white and pink), indicating a shallow habitat; species occurring from the surface to the subsurface (e.g., Globigerina bulloides, Globorotalia inflata, Globorotalia truncatulinoides); and species inhabiting the subsurface (e.g., Globorotalia scitula and Globorotalia hirsuta). For 17 species with variable ALD, we assessed whether their depth habitat at a given station could be predicted by mixed layer (ML) depth, temperature in the ML and chlorophyll a concentration in the ML. The influence of seasonal and lunar cycle on the depth habitat was also tested using periodic regression. In 11 out of the 17 tested species, ALD variation appears to have a predictable component. All of the tested parameters were significant in at least one case, with both seasonal and lunar cyclicity as well as the environmental parameters explaining up to > 50 % of the variance. Thus, G. truncatulinoides, G. hirsuta and G. scitula appear to descend in the water column towards the summer, whereas populations of Trilobatus sacculifer appear to descend in the water column towards the new moon. In all other species, properties of the mixed layer explained more of the observed variance than the periodic models. Chlorophyll a concentration seems least important for ALD, whilst shoaling of the habitat with deepening of the ML is observed most frequently. We observe both shoaling and deepening of species habitat with increasing temperature. Further, we observe that temperature and seawater density at the depth of the ALD were not equally variable among the studied species, and their variability showed no consistent relationship with depth habitat. According to our results, depth habitat of individual species changes in response to different environmental and ontogenetic factors and consequently planktonic foraminifera exhibit not only species-specific mean habitat depths but also species-specific changes in habitat depth.

Abstract Near-surface wind speed trends recorded at 67 land-based stations across Spain and Portugal for 1961–2011, also focusing on the 1979–2008 subperiod, were analyzed. Wind speed series were subjected to quality control, reconstruction, and homogenization using a novel procedure that incorporated the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5)-simulated series as reference. The resultant series show a slight downward trend for both 1961–2011 (−0.016 m s−1 decade−1) and 1979–2008 (−0.010 m s−1 decade−1). However, differences between seasons with declining values in winter and spring, and increasing trends in summer and autumn, were observed. Even though wind stilling affected 77.8% of the stations in winter and 66.7% in spring, only roughly 40% of the declining trends were statistically significant at the p < 0.10 level. On the contrary, increasing trends appeared in 51.9% of the stations in summer and 57.4% in autumn, with also around 40% of the positive trends statistically significant at the p < 0.10 level. In this article, the authors also investigated (i) the possible impact of three atmospheric indices on the observed trends and (ii) the role played by the urbanization growth in the observed decline. An accurate homogenization and assessment of the long-term trends of wind speed is crucial for many fields such as wind energy (e.g., power generation) and agriculture–hydrology (e.g., evaporative demand).

The Earth surface thermal infrared (TIR) radiation shows conspicuously an anisotropic behavior just like the bi-directional reflectance of visible and near infrared spectral domains. The importance of thermal radiation directionality (TRD) is being more and more widely recognized in the applications because of the magnitude of the effects generated. The effects of TRD were originally evidenced through experiments in 1962, showing that two sensors simultaneously measuring temperature of the same scene may get significantly different values when the viewing geometry is different. Such effect limits inter-comparison of measurement datasets and land surface temperature (LST) products acquired at different view angles, while raising the question of measurement reliability when used to characterize land surface processes. These early experiments fostered the development of modeling approaches to quantify TRD with the aim of developing a correction for Earth surface TIR radiation. Initiatives for pushing the analysis of TIR data through modeling have been lasted since 1970s. They were initially aimed at mimicking the observed TIR radiance with consideration of canopy structure, component emissivities and temperatures, and Earth surface energy exchange processes. Presently, observing the Earth surface TRD effect is still a challenging task because the TIR status changes rapidly. Firstly, a brief theoretical background and the basic radiative transfer equation are presented. Then, this paper reviews the historical development and current status of observing TRD in the laboratory, in-situ, from airborne and space-borne platforms. Accordingly, the TRD model development, including radiative transfer models, geometric models, hybrid models, 3D models, and parametric models are reviewed for surfaces of water, ice and sea, snow, barren lands, vegetation and urban landscapes, respectively. Next, we introduce three potential applications, including normalizing the LST products, estimating the hemispheric upward longwave radiation using multi-angular TIR observations and separating surface component temperatures. Finally, we give hints and directions for future research work. The last section summarizes the study and stresses three main conclusions.

The South Asian Monson (SAM) is one of the most intense climatic elements yet its initiation and variations are not well established. Dating the deposits of SAM wind-driven currents in IODP cores from the Maldives yields an age of 12. 9 Ma indicating an abrupt SAM onset, over a short period of 300 kyrs. This coincided with the Indian Ocean Oxygen Minimum Zone expansion as revealed by geochemical tracers and the onset of upwelling reflected by the sediment's content of particulate organic matter. A weaker 'proto-monsoon' existed between 12.9 and 25 Ma, as mirrored by the sedimentary signature of dust influx. Abrupt SAM initiation favors a strong influence of climate in addition to the tectonic control, and we propose that the post Miocene Climate Optimum cooling, together with increased continentalization and establishment of the bipolar ocean circulation, i.e. the beginning of the modern world, shifted the monsoon over a threshold towards the modern system.