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Large rivers play an important role in transferring water and all of its constituents including carbon in its various forms from the land to the ocean, but the seasonal and inter-annual variations in these riverine flows remain unclear. Satellite Earth observation datasets and reanalysis products can now be used to observe synoptic-scale spatial and temporal variations in the carbonate system within large river outflows. Here we present the OceanSODA-UNEXE time series, a dataset of the full carbonate system in the surface water outflows of the Amazon (2010-2020) and Congo Rivers (2002-2016). Optimal empirical approaches were used to generate gridded Total alkalinity (TA) and dissolved inorganic carbon (DIC) fields in the outflow regions. These combinations were determined by equitably evaluating all combinations of algorithms and inputs against a matchup database of in situ observations. Gridded TA and DIC along with gridded temperature and salinity data enable the calculation of the full carbonate system in the surface ocean. The algorithm evaluation constitutes a Type A uncertainty evaluation for TA and DIC where model, input and sampling uncertainties are considered. Total combined uncertainties for TA and DIC were propagated through the carbonate system calculation allowing all variables to be provided with an associated uncertainty estimate. In the Amazon outflow, the total combined uncertainty for TA was identified as 36 µmol kg-1 (weighted RMSD 35 µmol kg-1 and weighted bias 8 µmol kg-1 for n=82) and for DIC was 44 µmol kg-1 (weighted RMSD 44 µmol kg-1 and weighted bias -6 µmol kg-1 for n=70). The spatially averaged propagated uncertainties for the partial pressure of carbon dioxide (pCO2) and pH are 85 µatm and 0.08 respectively, where the pH uncertainty is relative to an average pH of 8.19. In the Congo outflow, the combined uncertainty for TA was identified as 29 µmol kg-1 (weighted RMSD 28 µmol kg-1 and weighted bias 6 µmol kg-1 for n=102) and for DIC was 40 µmol kg-1 (weighted RMSD 37 µmol kg-1and weighted bias -16 µmol kg-1 for n=77). The spatially averaged propagated uncertainties for pCO2 and pH are 74 µatm and 0.08 respectively, where the pH uncertainty is relative to an average pH of 8.21. The combined uncertainties in TA and DIC in the Amazon and Congo outflows are lower than the natural variability their respective regions allowing the time varying regional variability to be evaluated. Potential uses of these data would be for assessing the spatial and temporal flow of carbon from the Amazon and Congo rivers into the Atlantic and for assessing the riverine driven carbonate system variations experienced by tropical reefs within the outflow regions. [ABSTRACT FROM AUTHOR]

In recent years, large datasets of in situ marine carbonate system parameters (partial pressure of CO2 (pCO2), total alkalinity, dissolved inorganic carbon and pH) have been collated, quality controlled and made publicly available. These carbonate system datasets have highly variable data density in both space and time, especially in the case of pCO2, which is routinely measured at high frequency using underway measuring systems. This variation in data density can create biases when the data are used, for example for algorithm assessment, favouring datasets or regions with high data density. A common way to overcome data density issues is to bin the data into cells of equal latitude and longitude extent. This leads to bins with spatial areas that are latitude and projection dependent (e. g. become smaller and more elongated as the poles are approached). Additionally, as bin boundaries are defined without reference to the spatial distribution of the data or to geographical features, data clusters may be divided sub-optimally (e. g. a bin covering a region with a strong gradient). To overcome these problems and to provide a tool for matching surface in situ data with satellite, model and climatological data, which often have very different spatiotemporal scales both from the in situ data and from each other, a methodology has been created to group in situ data into 'regions of interest': spatiotemporal cylinders consisting of circles on the Earth's surface extending over a period of time. These regions of interest are optimally adjusted to contain as many in situ measurements as possible. All surface in situ measurements of the same parameter contained in a region of interest are collated, including estimated uncertainties and regional summary statistics. The same grouping is applied to each of the nonin situ datasets in turn, producing a dataset of coincident matchups that are consistent in space and time. About 35 million in situ data points were matched with data from five satellite sources and five model and re-analysis datasets to produce a global matchup dataset of carbonate system data, consisting of ~286,000 regions of interest spanning 54 years from 1957 to 2020. Each region of interest is 100 km in diameter and 10 days in duration. An example application, the reparameterisation of a global total alkalinity algorithm, is shown. This matchup dataset can be updated as and when in situ and other datasets are updated, and similar datasets at finer spatiotemporal scale can be constructed, for example to enable regional studies. The matchup dataset provides users with a large multi-parameter carbonate system dataset containing data from different sources, in one consistent, collated and standardised format suitable for model-data intercomparisons and model evaluations. The OceanSODA-MDB data can be downloaded from https://doi.org/10.12770/0dc16d62-05f6-4bbe-9dc4-6d47825a5931 (Land and Piollé, 2022). [ABSTRACT FROM AUTHOR]

Surface ocean CO2 measurements are used to compute the oceanic air-sea CO2 flux. The CO2 flux component from rivers and estuaries is uncertain. Estuarine and coastal water carbon dioxide (CO2) observations are relatively few compared to observations in the open ocean. The contribution of these regions to the global air-sea CO2 flux remains uncertain due to systematic under-sampling. Existing high-quality CO2 instrumentation predominantly utilise showerhead and percolating style equilibrators optimised for open ocean observations. The intervals between measurements made with such instrumentation make it difficult to resolve the fine-scale spatial variability of surface water CO2 at timescales relevant to the high frequency variability in estuarine and coastal environments. Here we present a novel dataset with unprecedented frequency and spatial resolution transects made at the Western Channel Observatory in the south west of the UK from June to September 2016, using a fast response seawater CO2 system. Novel observations were made along the estuarine-coastal continuum at different stages of the tide and reveal distinct spatial patterns in the surface water CO2 fugacity (fCO2) at different stages of the tidal cycle. Changes in salinity and fCO2 were closely correlated at all stages of the tidal cycle and suggest that the mixing of oceanic and riverine end members determines the variations in fCO2. The observations demonstrate the complex dynamics determining spatial and temporal patterns of salinity and fCO2 in the region. Spatial variations in observed surface salinity were used to validate the output of a regional high resolution hydrodynamic model. The model enables a novel estimate of the air-sea CO2 flux in the estuarine-coastal zone. Air-sea CO2 flux variability in the estuarine-coastal boundary region is dominated by the state of the tide because of strong CO2 outgassing from the river plume. The observations and model output demonstrate that undersampling the complex tidal and mixing processes characteristic of estuarine and coastal environment bias quantification of air-sea CO2 fluxes in coastal waters. The results provide a mechanism to support critical national and regional policy implementation by reducing uncertainty in carbon budgets. [ABSTRACT FROM AUTHOR]

The alliance between Japan and France is not possible because neither government wants an alliance. France wants a simple military understanding whereby the deployment of Japanese troops in Korea would be coordinated with French operations in Taiwan and south China. For most of the 1883-1885 period, all that Japan stood to gain from France was indirect military and diplomatic support against China.

Summary Whether or not age by itself increases susceptibility to pneumococcal infections separate from the effects of chronic disease is controversial. To address this issue, data collected for a retrospective [...]