Abstract. Current estimates of the global ocean carbon sink based on measurements of CO2 fugacity are inconsistent with those obtained from global ocean biogeochemistry models. Here we investigate how this gap might change by more fully accounting for submonthly variability in observation-based estimates, a step closer to the roughly hourly frequencies used in models. While these data-based estimates use hourly to 6-hourly wind speeds to compute the air-sea CO2 flux, other input variables are available only at monthly resolution. Thus, they neglect high-frequency variability in key variables such as atmospheric pressure associated with synoptic events such as storms. To evaluate this error, we compare flux estimates from observational data sets with different temporal resolutions. Accounting for hourly variations in atmospheric pressure and daily variations in sea surface temperature, a data-based approach reduces the estimated global carbon uptake by 0.12 Pg C yr−1, closing 25 % of the average gap between observation-based and model estimates. This reduction results from proper accounting of the covariance between wind speed and atmospheric pressure, particularly in the southern extratropics.

Precipitation alters sea surface physical and biogeochemical properties locally. However, due to its high temporal and spatial variations, it has largely been overlooked in studies assessing global ocean carbon uptake. Air-sea CO2 flux is mainly due to the interfacial exchange of CO2 molecules between the liquid and gaseous phases media. Rain may impact this interfacial air-sea CO2 flux by (i) enhancing the turbulence at the air-sea interface and (ii) diluting the CO2 concentration near the ocean surface. At the same time, rain directly injects into the ocean CO2 absorbed by the raindrops during their fall. This latter component, known as wet deposition, contributes to the CO2 flux into the ocean. This study provides the first comprehensive global estimate of these effects and their combined influence on the global ocean carbon uptake during the period 2008-2018. We use different representations of the ocean surface response to rain and different rain products with different rain rate distributions (ERA5 and IMERG) to quantify the uncertainty of the global impact of rain on CO2 sink. We show that rain increases the global ocean carbon sink by +0.14 to +0.19 PgC yr-1 over 2008-2018, representing an increase of 5 to 7% of the global carbon uptake (2.66 PgC yr-1). Both interfacial flux and wet deposition have comparable orders of magnitude. Rain mainly increases the CO2 sink in the tropics, where strong rain rates and weak winds induce noticeable dilution at the ocean surface, in the storm track regions, and in the Southern ocean.

Rain alters local sea surface physical and biogeochemical properties but its spatiotemporal variability has led to its overlook in global ocean carbon uptake studies. Different physical and chemical processes in the gaseous and liquid phases control the transfer of carbon dioxide (CO2) between the atmosphere and ocean. Rain impacts the interfacial flux by (1) increasing turbulence in the ocean and (2) modulating the air-sea CO2 concentration gradient. Concurrently, raindrops inject CO2 absorbed during their fall into the ocean through wet deposition. Here this study presents a comprehensive estimate of these effects on the global ocean carbon uptake over 2008-2018 based on observational products (satellite and in situ) and reanalysis. Using various representations of the ocean surface response to rainfall and different rain products, we show that rain increases the ocean carbon sink by +0.14-0.19 PgC yr-1 over 2008-2018, representing an increase of 5-7% of the ocean carbon uptake (2.66 PgC yr-1). Rain-induced interfacial flux and wet deposition have comparable orders of magnitude. The former mainly increases the CO2 sink in the tropics because strong rain rates and weak winds induce noticeable salinity and CO2 dilution. The latter is important in the tropics, storm track regions and the Southern Ocean. About 6% of the total uptake of carbon dioxide by the ocean is due to rainfall, according to an analysis of satellite observations and ERA5 reanalysis data from 2008 to 2018.

Background: Climate change will make extreme weather events more frequent in the 21st century. Extreme ambient temperatures during the prenatal period have been associated with adverse pregnancy outcomes such as preterm birth. It is unclear, however, whether heat waves during pregnancy impact fetal growth in apparently healthy term newborns. Objectives: We aimed to investigate associations between heat wave during pregnancy and birth weight outcomes in term newborns from the PARIS birth cohort, and to explore meteorological conditions and air pollution as possible intermediate factors. Methods: We examined data on 3,359 newborns born between 37 and 42 weeks in Paris, France, between 2003 and 2006. Associations of maternal exposure to heat wave (during whole pregnancy and each trimester) with birth weight and small for gestational age (SGA) at term were studied using linear and logistic regression models adjusted for potential confounders. Maternal characteristics were investigated as possible modifiers. We explored the mediating role of ambient temperature, relative humidity, and air pollution levels in the relationship between heat wave during the first trimester and term SGA. Results: Mothers who were pregnant during the 2003 French heat wave (n = 506, 15 %) were more likely to have a term SGA baby (aOR = 2.70; 95 % CI: 1.38, 5.28) compared to mothers who did not experience heat wave during pregnancy. The association was stronger when heat wave occurred during the first trimester (aOR = 4.18; 95 % CI: 1.69, 10.35). Primiparous women were identified as more vulnerable than multiparous women. Average ambient temperature and air quality index explained about 36 % and 56 % of the association between heat wave during the first trimester and term SGA, respectively. Conclusions: This study suggests prenatal exposure to heat wave, especially during the first trimester, may adversely affect fetal growth of term newborns, which could be explained by both increasing ambient temperatures and worsening air quality.

The ocean skin is composed of thin interfacial microlayers of temperature and mass of less than 1 mm where heat and chemical exchanges are controlled by molecular diffusion. It is characterized by a cooling of similar to-0.2 K and an increase in salinity of similar to 0.1 g/kg (absolute salinity) relative to the water below. A surface observation-based air-sea CO2 flux estimate considering the variation of the CO2 concentration in these microlayers has been shown to lead to an increase in the global ocean sink of the anthropogenic CO2 by +0.4 PgC yr(-1) (15% of the global sink). This study analyzes this effect in more details using a 15-year (2000-2014) simulation from an Earth System Model (ESM) that incorporates a physical representation of the ocean surface layers (diurnal warm layer and rain lenses) and microlayers. Results show that considering the microlayers increases the simulated global ocean carbon sink by +0.26 to +0.37 PgC yr(-1) depending on assumptions on the chemical equilibrium. This is indeed about 15% of the global sink (2.04 PgC yr(-1)) simulated by the ESM. However, enabling the ocean skin adjustment to feedback on ocean carbon concentrations reduces this increase to only +0.13 (+/- 0.09) PgC y(-1). Coupled models underestimate the ocean carbon sink by similar to 5% if the ocean skin effect is not included. Plain Language Summary The ocean skin is a thin layer of less than a millimeter that is in contact with the atmosphere, where the heat and chemical exchanges are controlled by molecular diffusion. It typically corresponds to a temperature at the ocean interface that is cooler by -0.2 K than the water at a depth of a millimeter. It also corresponds to a salinity that is slightly higher at the interface. Taking into account these temperature and salinity changes in this thin layer can change calculations of the global ocean carbon sink substantially. We use a global Earth System Model including a representation of the ocean skin to study this impact. We found an increase of 15% in the simulated global ocean carbon sink. This is consistent with past studies. Enabling the flux to feedback on the ocean carbon concentration significantly reduces its impact. We conclude by discussing the uncertainties in the global ocean carbon sink associated with the formulation of the carbon flux and the representation of the ocean skin.

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the reliability of the dielectric constant model. Two new parametrizations were recently developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements by Boutin et al. (2021) (BV), and on the other hand, on new George Washington University laboratory measurements by Zhou et al. (2021) (GW2020). These two approaches are fully independent. For most SSS and Sea Surface Temperature (SST) conditions commonly observed over the open ocean, the relative variations of brightness temperatures Tb simulated through the BV and GW2020 parametrizations agree particularly well, and better than with earlier parametrizations previously used in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. Nevertheless, uncertainty remains, especially below 10 °C where a $\sim $ 0.1 K relative difference between the two models is observed. This motivates the development of a revised parameterization, BVZ, based on a methodology similar to that used to derive BV but using GW2020 instead of SMOS measurements. Compared to the GW2020 parameterization, BVZ is derived with a reduced number of degrees of freedom, it relies on the TEOS10 PSS78 conductivity-salinity relationship, and on the previously derived static permittivity of fresh water. One month per season of SMOS data have been reprocessed in 2018 using BV, GW2020, and BVZ. We find the best overall agreement between SMOS SSS and Argo SSS with BVZ parametrization, with noticeable improvement in the 5 °C–15 °C SST range.

We investigate the Chukchi and the Beaufort seas, where salty and warm Pacific Water flows in from the Bering Strait and interacts with the sea ice, contributing to its summer melt. For the first time, thanks to in-situ measurements recorded by two saildrones deployed during summer 2019 and refined sea ice filtering in satellite L-Band radiometric data, we demonstrate the ability of satellite Sea Surface Salinity (SSS) observed by SMOS and SMAP to capture very fresh SSS induced by sea ice melt, referred to as meltwater lenses (MWL). The largest MWL observed by the saildrones during this period occupied a large part of the Chukchi shelf, with a SSS decrease reaching 5 pss, and persisted for up to one month. Over this MWL, measured currents and wind speed illustrate the influence of induced low SSS pattern on the air-sea momentum transfer to the upper ocean by restricting its vertical extent. Combined with satellite-based Sea Surface Temperature, satellite SSS provides a monitoring of the different water masses encountered in the region during summer 2019. Using sea ice concentration and estimated Ekman transport, we analyse the spatial variability of sea surface properties after the sea ice edge retreat over the Chukchi and the Beaufort seas. The two MWL captured by both, the saildrones and the satellite measurements, result from different dynamics. Over the Beaufort Sea, the MWL evolution follows the meridional sea ice retreat, whereas in the Chukchi Sea, a large persisting MWL is generated by advection of a sea ice filament.

This study is performed in the frame of the European Space Agency (ESA) Climate Change Initiative (CCI+) for Sea Surface Salinity (SSS), which aims at generating global SSS fields from all available satellite L-band radiometer measurements over the longest possible period with a great stability. By combining SSS from the Soil Moisture and Ocean Salinity, SMOS, Aquarius and the Soil Moisture Active Passive, SMAP missions, CCI+SSS fields (Boutin et al. 2020) are the only one to provide a 10 year time series of satellite salinity with such quality: global rms difference of weekly 25x25km2 CCI+SSS with respect to in situ Argo SSS of 0.17 pss, correlation coefficient of 0.97 (see https://pimep.ifremer.fr/diffusion/analyses/mdb-database/GO/cci-l4-esa-merged-oi-v2.31-7dr/argo/report/pimep-mdb-report_GO_cci-l4-esa-merged-oi-v2.31-7dr_argo_20201215.pdf). Nevertheless, we found that some systematic biases remained. In this presentation, we will show how they will be reduced in the next CCI+SSS version. The key satellite mission ensuring the longest time period, since 2010, at global scale, is SMOS. We implemented a re-processing of the whole SMOS dataset by changing some key points. Firstly we replace the Klein and Swift (1977) dielectric constant parametrization by the new Boutin et al. (2020) one. Secondly we change the reference dataset used to perform a vicarious calibration over the south east Pacific Ocean (the so-called Ocean Target Transformation), by using Argo interpolated fields (ISAS, Gaillard et al. 2016) contemporaneous to the satellite measurements instead of the World Ocean Atlas climatology. And thirdly the auxiliary data (wind, SST, atmospheric parameters) used as priors in the retrieval scheme, which come in the original SMOS processing from the ECMWF forecast model were replaced by ERA5 reanalysis. Our results are showing a quantitative improvement in the stability of the SMOS CCI+SSS with respect to in situ measurements for all the period as well as a decrease of the spread of the difference between SMOS and in situ salinity measurements. Bibliography: J. Boutin et al. (2020), Correcting Sea Surface Temperature Spurious Effects in Salinity Retrieved From Spaceborne L-Band Radiometer Measurements, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2020.3030488. F. Gaillard et al. (2016), In Situ–Based Reanalysis of the Global Ocean Temperature and Salinity with ISAS: Variability of the Heat Content and Steric Height, Journal of Climate, vol. 29, no. 4, pp. 1305-1323, doi: 10.1175/JCLI-D-15-0028.1. L. Klein and C. Swift (1977), An improved model for the dielectric constant of sea water at microwave frequencies, IEEE Transactions on Antennas and Propagation, vol. 25, no. 1, pp. 104-111, doi: 10.1109/JOE.1977.1145319. Data reference: J. Boutin et al. (2020): ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product, v2.31, for 2010 to 2019. Centre for Environmental Data Analysis. https://catalogue.ceda.ac.uk/uuid/eacb7580e1b54afeaabb0fd2b0a53828

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the accuracy of the modelling of the dielectric constant (ε). Two new ε parametrizations have recently been developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements and on the other hand on new laboratory measurements. These two approaches are fully independent. These new ε parametrizations are compared with each other and with the ε models previously in use in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. The two new ε parametrizations are found to be in closer agreement than with earlier parametrizations for most common ocean conditions. We will further study to which extent the recent SMOS CCI+SSS v3 reprocessing confirms the above results and could help resolve remaining inconsistencies.

Sea Surface Salinity (SSS) are retrieved from SMOS and SMAP L-band radiometers at a spatial resolution of about 50km. Traditionally, satellite SSS products validation is based on comparisons with in-situ near surface salinity measurements. In-situ measurements are performed on moorings, argo floats and along ship tracks[JB1] , which provide punctual or one-dimensional (along ship tracks) estimations of the SSS. The sampling difference between one-dimensional or punctual in-situ measurements and two-dimensional satellite products results in a sampling error that must be separated from measurement errors for the validation of satellite products. We use a small-scale resolution field (1/12° Mercator Global Ocean Physics Analysis and Forecast) to estimate the expected sampling error of each kind of in-situ measurements, by comparing punctual, [JB2] one-dimensional and two-dimensional SSS variability. The better understanding of sampling errors allows a more accurate validation of satellite SSS and of the errors estimated by satellite retrieval algorithms. The improvement is quantified by considering the standard deviation of satellite minus in-situ salinities differences normalized by the sampling and retrieval errors. This quantity should be equal to one if all the error contributions are correctly considered. This methodology will be applied to SMOS SSS and to merged SMOS and SMAP SSS products.

Sea surface salinity is retrieved for more than 11 years from the Soil Moisture and Ocean Salinity (SMOS) satellite mission. This data set provides a unique monitoring of the Sea Surface Salinity (SSS) spatio-temporal variability at global scale. It is particularly useful to follow the surface ocean pathway of fresh river plumes water as illustrated here in the Bay of Bengal. A revised adjustment of the whole SMOS SSS time series (CATDS Expertise Center version 5, 2010–2020) leads to clear reduction of local biases in very variable regions and in very noisy regions. The robust std difference between SMOS CEC v5 (18-day, ~70km SSS) and Argo in situ SSS is 0.17 in regions warmer than 5°C. We will discuss how future CATDS products will be improved in view of two ongoing reprocessings, the CATDS L1/L2 v7 reprocessing and the ESA CCI+SSS L2 SMOS reprocessing.

The European Space Agency (ESA) Climate Change Initiative (CCI+) for Sea Surface Salinity (SSS) aims at generating global SSS fields from all available satellite L-band radiometer measurements over the longest possible period with a great stability (including Soil Moisture and Ocean Salinity, SMOS). Version 1 and 2 of CCI+SSS level 4 fields combine SSS form the three satellite L-Band radiometer missions and have been found to be in a very good agreement with in situ measurements (global rms difference of 0,16 pss). Nevertheless, some systematic differences still remain between CCI+SSS and in situ SSS. We study here to which extent some errors coming from the SMOS SSS processing are reduced, when making some key changes in the SMOS level 2 OS processing. Then, we discuss the contribution of each change in the preliminary results we obtain.

In coupled general circulation model, the accuracy of momentum and energy exchange at the air-sea interface is still a potential source of significant bias. In the framework of the COCOA project we investigate new methods (both mathematical and numerical) to have a more correct flux representation. One important source of error is the asynchronous coupling between oceanic and atmospheric model. Indeed, the time step of the coupling is generally longer than time steps used by either the atmospheric or the oceanic model. This introduces inconsistencies between the free evolution of the two models due to the exchange parameters that are held constant since the last coupling time step. In particular, non-synchronous exchange coefficients may lead to error in the diurnal evolution of the coupled system, or to bias in the ocean mixed layer temperature for period where surface fluxes increases or decrease linearly. In order to evaluate the potential amplitude of this error, and its regional and sea- sonal distribution, we use the hourly fluxes that are available in the new ECMWF ERA5 re-analyses. The error due to asynchronous coupling is first evaluated by inspecting the flux difference between two successive time-steps. Results show more important differences over the western boundary currents and the circumpolar current for all the fluxes except for the solar flux. We also observe larger differences in summer compared to winter in the respective hemisphere. By taking in account the geometrical variation of the solar flux we show how we can reduce the error for the solar flux. In a second time we are calculating the statistics for the linear increase and decrease of the flux for a fixed period (ig one day, two days...) over all the ocean for all the fluxes except the solar one. The results are showing coefficients that are decreasing as the period increase. We also use those coefficient in a simple mixed layer model to calculate the error made over the period of calcul. On the contrary we see the appearance of a plateau at two-three days on the impact of this linear bias. Finally, using the De Boyer de Montaigu climatology for the mixed layer height we show that the linear bias could lead to temperature change up to 0.1K.

Temperature and Salinity at the ocean interface can be substantially different than their bulk values in the ocean mixed layer at 5-10 meters depth. The main phenomena that account for these differences are (i) the interfacial millimeter scale diffusive microlayer usually cooler and saltier than below due to surface fluxes and (ii) diurnal warm layers of few tens of centimeters to few meters that form under weak wind condition due to solar absorption. Although characterized by small vertical scales, these tightly wind-related phenomena corresponds to coherent structures up to the large-scale where they can impact air-sea exchanges of heat, water and chemical species. Another phenomenon that can impact global air-sea exchanges is the freshwater lenses produced by rain. Rain freshens and cools the ocean surface, as raindrops temperature is usually lower than surface temperature. The induced negative salinity anomaly enables surface cold anomalies to be sustained and further cooled down by surface fluxes after rain has ceased. This study presents a first global estimate of basic statistics rain-induced ocean surface freshening and temperature changes and of their variations with seasons.

Despite the efforts reported in the literature to explain contrasting experimental observations, the evolution of seismic attributes (velocity and attenuation) of rocks across the saturation range remains ill understood. In a comparative study, we monitored the evolution of ultrasonic P wave attributes in a porous sandstone subjected to two experiments of moisture adsorption and water spontaneous imbibition. Both experiments highlighted a significant (i.e., by 1 order of magnitude) and similar drop in P waves amplitudes, although the maximum saturations reached in each experiment is very different (i.e., about 2% vs. 70%). However, only moisture adsorption leads to a dramatic elastic softening (velocity reduction). This difference might be explained by the coupling between two competing physical mechanisms taking place during water imbibition, namely, elastic softening driven by water adsorption at the grain contact and elastic stiffening driven by full saturation of the grain contacts, at the ultrasonic frequency of the measurement.

Rationale: Although the effects of traffic‐related air pollution on respiratory exacerbations have been well documented, its impact on lung function in childhood remains unclear. Objectives: Our aim was to investigate the associations of prenatal, early, and lifetime traffic‐related air pollution exposure with lung function at 8‐9 years studying possible effect modification by sex, sensitization at 8‐9 years, and early lower respiratory tract infections. Methods: We conducted this study among 788 children from the PARIS (Pollution and Asthma Risk: an Infant Study) birth cohort. Lung function tests were performed during the medical examination at 8‐9 years. Traffic‐related air pollution exposure during each trimester of pregnancy was estimated using nitrogen oxides background measurements. Postnatal traffic‐related air pollution exposure was assessed by a nitrogen oxides air dispersion model at both residential and daycare/school addresses. Associations between lung function and traffic‐related air pollution exposure were analyzed by multiple linear regression models. Results: Higher prenatal nitrogen oxides levels, especially during the second trimester of pregnancy, were associated with a lower forced expiratory flow at 25‐75% of the forced vital capacity, but there were no significant associations between prenatal nitrogen oxide levels and forced vital capacity, forced expiratory volume during 1 second, or the forced expiratory volume during 1 second/forced vital capacity ratio overall. Postnatal traffic‐related air pollution exposure was associated with lower lung function among children with early lower respiratory tract infections or sensitization at 8‐9 years, but not in the full cohort. In children with early repeated lower respiratory tract infections, an interquartile increase in lifetime nitrogen oxides exposure was associated with both a lower forced expiratory volume during 1 second (−62.6 ml; 95% confidence interval = −107.0 to −18.1) and forced vital capacity (−55.7 ml; 95% confidence interval = −109.5 to −1.8), but was not associated with the forced expiratory volume during 1 second/forced vital capacity ratio. There was an association between greater early postnatal nitrogen oxide exposure and a lower forced expiratory volume during 1 second/forced vital capacity ratio among sensitized children (−0.65%; 95% confidence interval = −1.25 to −0.05). Conclusions: This study sheds new light, suggesting associations between postnatal traffic‐related air pollution exposure and reduced lung function may be enhanced by early, repeated lower respiratory tract infections or allergic sensitization.