Explore the vast range of titles available.

Changes in winter and spring temperatures have been widely used to explain the diverse responses of spring phenology to climate change. However, few studies have quantified their respective effects. Using 386,320 in situ observations of leaf unfolding date (LUD) of six tree species in Europe, we show that accelerated spring thermal accumulation and changes in winter chilling explain, on average, 61% and 39%, respectively, of the advancement in LUD for the period 1951–2019. We find that winter warming may not have delayed bud dormancy release, but rather it has increased the thermal requirement in reaching leaf unfolding. This increase in thermal requirement and the decreased efficiency of spring warming for thermal accumulation partly explain the weakening response of leaf unfolding to warming. Our study stresses the need to better assess the antagonistic and heterogeneous effects of winter and spring warming on leaf phenology, which is key to projecting future vegetation–climate feedbacks.The authors use central European observations of leaf unfolding date (LUD) for six tree species. They demonstrate antagonistic and heterogenous effects of winter chilling and spring thermal accumulation on leaf phenology, with the latter having greater explanation (61% versus 39%) for LUD advancement.

It has been speculated that the partial pressure of carbon dioxide ( p CO 2 ) in shelf waters may lag the rise in atmospheric CO 2 . Here, we show that this is the case across many shelf regions, implying a tendency for enhanced shelf uptake of atmospheric CO 2 . This result is based on analysis of long-term trends in the air–sea p CO 2 gradient (Δ p CO 2 ) using a global surface ocean p CO 2 database spanning a period of up to 35 years. Using wintertime data only, we find that Δ p CO 2 increased in 653 of the 825 0.5° cells for which a trend could be calculated, with 325 of these cells showing a significant increase in excess of +0.5 μatm yr −1 ( p  < 0.05). Although noisier, the deseasonalized annual data suggest similar results. If this were a global trend, it would support the idea that shelves might have switched from a source to a sink of CO 2 during the last century. It remains unclear whether surface water partial pressure of CO 2 ( p CO 2 ) in continental shelves tracks with increasing atmospheric p CO 2 . Here, the authors show that p CO 2 in shelf waters lags behind rising atmospheric CO 2 in a number of shelf regions, suggesting shelf uptake of atmospheric CO 2 .

Rivers are pivotal in the global carbon cycle, transporting terrestrial carbon to the ocean while emitting significant amount of CO2${\\mathrm{C}\\mathrm{O}}_{2}$to the atmosphere. However, the partitioning of fluvial inorganic carbon (IC) between downstream transport and atmospheric evasion remains uncertain due to intricate hydrodynamic and biogeochemical processes. Inspired by Budyko's hydrological work, this study introduces a dimensionless framework to identify critical factors in fluvial IC partitioning: the IC fraction in equilibrium with the atmosphere and the ratio of advection to evasion timescales. River catchment analyses and modeling reveal that the equilibrium ratio determines the fraction of IC stably transported downstream. The hydrodynamic‐driven timescale ratio determines the fate of out‐of‐equilibrium IC, with low‐order streams favoring atmospheric evasion and higher‐order streams promoting downstream transport. This framework provides a simple yet robust approach to predicting river carbon dynamics, with implications for land‐to‐ocean transport, fluvial emissions, and climate mitigation strategies such as enhanced weathering. Plain Language Summary Rivers contain large amounts of dissolved inorganic carbon originating from the decomposition of organic matter and soil water fluxes. This carbon is partly transported downstream across the river network to the ocean and partly emitted as CO2${\\mathrm{C}\\mathrm{O}}_{2}$to the atmosphere. Quantifying the partitioning between these fluxes is crucial for accurate carbon budgets from the local to the global scale, but the complex interplay of biogeophysical processes makes it challenging. Inspired by Budyko's seminal work in hydrology, we present a framework that determines the main chemical and physical processes governing the fluvial inorganic carbon partitioning. We identify two dimensionless numbers (or indexes) that can be defined with only a few parameters and provide quantitative and robust predictions on fluvial carbon fate. These numbers are linked to water turbulence and chemistry, and their values change across the river network. Key Points Rivers partition inorganic carbon between downstream transport and CO2${\\mathrm{C}\\mathrm{O}}_{2}$emissions to the atmosphere Incorporating key hydrodynamic and biogeochemical processes, we identify the dimensionless numbers that govern the inorganic carbon partitioning Water hydrodynamics plays a critical role in the fate of the carbon that is out of equilibrium with the atmosphere

In this study, we present the first combined open- and coastal-ocean pCO2 mapped monthly climatology (, 10.25921/qb25-f418, https://www.nodc.noaa.gov/ocads/oceans/MPI-ULB-SOM_FFN_clim.html, last access: 8 April 2020) constructed from observations collected between 1998 and 2015 extracted from the Surface Ocean CO2 Atlas (SOCAT) database. We combine two neural network-based pCO2 products, one from the open ocean and the other from the coastal ocean, and investigate their consistency along their common overlap areas. While the difference between open- and coastal-ocean estimates along the overlap area increases with latitude, it remains close to 0 µatm globally. Stronger discrepancies, however, exist on the regional level resulting in differences that exceed 10 % of the climatological mean pCO2, or an order of magnitude larger than the uncertainty from state-of-the-art measurements. This also illustrates the potential of such an analysis to highlight where we lack a good representation of the aquatic continuum and future research should be dedicated. A regional analysis further shows that the seasonal carbon dynamics at the coast–open interface are well represented in our climatology. While our combined product is only a first step towards a true representation of both the open-ocean and the coastal-ocean air–sea CO2 flux in marine carbon budgets, we show it is a feasible task and the present data product already constitutes a valuable tool to investigate and quantify the dynamics of the air–sea CO2 exchange consistently for oceanic regions regardless of its distance to the coast.

In spite of the recent strong increase in the number of measurements of the partial pressure of CO2 in the surface ocean (pCO2), the air–sea CO2 balance of the continental shelf seas remains poorly quantified. This is a consequence of these regions remaining strongly under-sampled in both time and space and of surface pCO2 exhibiting much higher temporal and spatial variability in these regions compared to the open ocean. Here, we use a modified version of a two-step artificial neural network method (SOM-FFN; Landschützer et al., 2013) to interpolate the pCO2 data along the continental margins with a spatial resolution of 0.25∘ and with monthly resolution from 1998 to 2015. The most important modifications compared to the original SOM-FFN method are (i) the much higher spatial resolution and (ii) the inclusion of sea ice and wind speed as predictors of pCO2. The SOM-FFN is first trained withpCO2 measurements extracted from the SOCATv4 database. Then, the validity of our interpolation, in both space and time, is assessed by comparing the generated pCO2 field with independent data extracted from the LDVEO2015 database. The new coastal pCO2 product confirms a previously suggested general meridional trend of the annual mean pCO2 in all the continental shelves with high values in the tropics and dropping to values beneath those of the atmosphere at higher latitudes. The monthly resolution of our data product permits us to reveal significant differences in the seasonality of pCO2 across the ocean basins. The shelves of the western and northern Pacific, as well as the shelves in the temperate northern Atlantic, display particularly pronounced seasonal variations in pCO2, while the shelves in the southeastern Atlantic and in the southern Pacific reveal a much smaller seasonality. The calculation of temperature normalizedpCO2 for several latitudes in different oceanic basins confirms that the seasonality in shelf pCO2 cannot solely be explained by temperature-induced changes in solubility but are also the result of seasonal changes in circulation, mixing and biological productivity. Our results also reveal that the amplitudes of both thermal and nonthermal seasonal variations in pCO2 are significantly larger at high latitudes. Finally, because this product's spatial extent includes parts of the open ocean as well, it can be readily merged with existing global open-ocean products to produce a true global perspective of the spatial and temporal variability of surface ocean pCO2.

In recent years, advancements in machine learning based interpolation methods have enabled the production of high-resolution maps of sea surface partial pressure of CO2 (pCO2) derived from observations extracted from databases such as the Surface Ocean CO2 Atlas (SOCAT). These pCO2-products now allow quantifying the oceanic air–sea CO2 exchange based on observations. However, most of them do not yet explicitly include the coastal ocean. Instead, they simply extend the open ocean values onto the nearshore shallow waters, or their spatial resolution is simply so coarse that they do not accurately capture the highly heterogeneous spatiotemporal pCO2 dynamics of coastal zones. Until today, only one global pCO2-product has been specifically designed for the coastal ocean (Laruelle et al., 2017). This product, however, has shortcomings because it only provides a climatology covering a relatively short period (1998–2015), thus hindering its application to the evaluation of the interannual variability, decadal changes and the long-term trends of the coastal air–sea CO2 exchange, a temporal evolution that is still poorly understood and highly debated. Here we aim at closing this knowledge gap and update the coastal product of Laruelle et al. (2017) to investigate the longest global monthly time series available for the coastal ocean from 1982 to 2020. The method remains based on a two-step Self-Organizing Maps and Feed-Forward Network method adapted for coastal regions, but we include additional environmental predictors and use a larger pool of training and validation data with ∼18 million direct observations extracted from the latest release of the SOCAT database. Our study reveals that the coastal ocean has been acting as an atmospheric CO2 sink of -0.40 Pg C yr-1 (-0.18 Pg C yr-1 with a narrower coastal domain) on average since 1982, and the intensity of this sink has increased at a rate of 0.06 Pg C yr-1 decade-1 (0.02 Pg C yr-1 decade-1 with a narrower coastal domain) over time. Our results also show that the temporal changes in the air–sea pCO2 gradient plays a significant role in the long-term evolution of the coastal CO2 sink, along with wind speed and sea-ice coverage changes that can also play an important role in some regions, particularly at high latitudes. This new reconstructed coastal pCO2-product (10.25921/4sde-p068; Roobaert et al., 2023) allows us to establish regional carbon budgets requiring high-resolution coastal flux estimates and provides new constraints for closing the global carbon cycle.

The calculation of the air–water CO2 exchange (FCO2) in the ocean not only depends on the gradient in CO2 partial pressure at the air–water interface but also on the parameterization of the gas exchange transfer velocity (k) and the choice of wind product. Here, we present regional and global-scale quantifications of the uncertainty in FCO2 induced by several widely used k formulations and four wind speed data products (CCMP, ERA, NCEP1 and NCEP2). The analysis is performed at a 1∘ × 1∘ resolution using the sea surfacepCO2 climatology generated by Landschützer et al. (2015a) for the 1991–2011 period, while the regional assessment relies on the segmentation proposed by the Regional Carbon Cycle Assessment and Processes (RECCAP) project. First, we use k formulations derived from the global 14C inventory relying on a quadratic relationship between k and wind speed (k=c⋅U102; Sweeney et al., 2007; Takahashi et al., 2009; Wanninkhof, 2014), where c is a calibration coefficient and U10 is the wind speed measured 10 m above the surface. Our results show that the range of global FCO2, calculated with these k relationships, diverge by 12 % when using CCMP, ERA or NCEP1. Due to differences in the regional wind patterns, regional discrepancies in FCO2 are more pronounced than global. These global and regional differences significantly increase when using NCEP2 or other k formulations which include earlier relationships (i.e., Wanninkhof, 1992; Wanninkhof et al., 2009) as well as numerous local and regional parameterizations derived experimentally. To minimize uncertainties associated with the choice of wind product, it is possible to recalculate the coefficient c globally (hereafter called c∗) for a given wind product and its spatio-temporal resolution, in order to match the last evaluation of the global k value. We thus performed these recalculations for each wind product at the resolution and time period of our study but the resulting global FCO2 estimates still diverge by 10 %. These results also reveal that the Equatorial Pacific, the North Atlantic and the Southern Ocean are the regions in which the choice of wind product will most strongly affect the estimation of the FCO2, even when using c∗.