The nearly four-decades-long quasi-continuous daily measurements of the Florida Current (FC) volume transport at 27ºN represents the longest climate record of a boundary current in existence. Given the extremely high utility of this submarine cable-collected time series for monitoring the Atlantic meridional overturning circulation, as well as for improving understanding and prediction of the regional weather, climate phenomena, coastal sea-level, and ecosystem dynamics, efforts are underway to establish a suitable backup observing system in case the cable becomes inoperable in the future. This study explores the utility of along-track satellite altimetry measurements since 1993 as a potential cable backup by establishing the relationship between the cross-stream sea surface height gradients and the FC volume transport derived from cable measurements and ship sections. We find that despite the lower temporal resolution, satellite altimetry can indeed serve as a decent but limited backup observing system. The FC transport inferred from satellite altimetry captures about 60% of the variability observed in the concurrent cable estimates, and the estimated error bars for the altimetry-derived transport are larger than those of the cable transport (2.1 Sv versus 1.5 Sv). We nevertheless demonstrate that satellite altimetry reproduces the seasonal, intra-seasonal, and inter-annual variability of the FC transport fairly well, as well as large transport anomalies during extreme weather events, such as tropical storms and hurricanes. The altimetry-derived transport can be provided in near-real time and serve the need to fill in data gaps in the cable record and assess its quality over time.

Although observations and modelling studies show that heavy rainfall is increasing in many regions, how changes will manifest themselves on sub-daily timescales remains highly uncertain. Here, for the first time, we combine observational analysis and high-resolution modelling results to examine changes to extreme rainfall intensities in urbanized Kuala Lumpur, Malaysia. We find that hourly intensities of extreme rainfall have increased by ~35% over the last three decades, nearly three times more than in surrounding rural areas, with daily intensities showing much weaker increases. Our modelling results confirm that the urban heat island effect creates a more unstable atmosphere, increased vertical uplift and moisture convergence. This, combined with weak surface winds in the Tropics, causes intensification of rainfall extremes over the city, with reduced rainfall in the surrounding region.

Hourly precipitation extremes can intensify with temperature at higher rates than expected from thermodynamic increases explained by the Clausius-Clapeyron (CC) relationship (~6.5%/K), but local scaling with surface air temperature is highly variable. Here we use daily dewpoint temperature, a direct proxy of absolute humidity, to estimate at-gauge local scaling across six macro-regions for a global dataset of over 7000 hourly precipitation gauges. We find scaling rates from CC to 2xCC at more than 60% of gauges, peaking in the tropics at a median rate of ~1.5CC. Moreover, regional scaling rates show surprisingly universal behaviour at around CC, with higher scaling in Europe. Importantly for impacts, hourly scaling is persistently higher than scaling for daily extreme precipitation. Our results indicate greater consistency in global scaling than previous work, usually at or above CC, with positive scaling in the (sub)tropics. This demonstrates the relevance of dewpoint temperature scaling to understanding future changes.

Remobilization and deformation of surficial subaqueous slope sediments create turbidites and soft sediment deformation structures (SSDS), which are common features in many depositional records. Paleoseismic studies have used seismically-induced turbidites and SSDS preserved in sedimentary sequences to reconstruct recurrence patterns and—in some cases—allow quantifying rupture location and magnitude of past earthquakes. However, our understanding of earthquake-triggered remobilization and deformation lacks studies targeting where these processes take place, the subaqueous slope, and involving direct comparison of sedimentary fingerprint with well-documented historical earthquakes. Here we investigate the sedimentary imprint of six megathrust earthquakes in 17 slope sediment cores from two Chilean lakes, Riñihue and Calafquén, and link it to magnitude, seismic intensity, peak ground acceleration (PGA) and Arias Intensity (Ia). Centimeter-scale stratigraphic gaps—caused by remobilization of surficial slope sediment—were identified using high-resolution multi-proxy core correlation of slope to basin cores and six types of SSDS using high-resolution 3D X-ray computed tomography data. Centimeter-scale gaps occur at the studied sites when Ia and moment magnitude (Mw) exceed 3.85 m/s and 8.8, respectively. Total remobilization depth correlates best with Ia and is highest in both lakes for the strongest earthquakes (Mw ~9.5). In lake Riñihue, SSDS thickness and type correlates best with PGA providing first field-based evidence of progressive SSDS development with increasing PGA for SSDS caused by Kelvin-Helmholtz instability (KHI). Stratigraphic gaps occur on slope angles of ≥2.3°, whereas deformation already occurs from slope angle 0.2°. The thickness of both stratigraphic gaps and SSDS increases with slope angle suggesting that increased slope angle—and thereby gravitational shear stress—promotes both remobilization and deformation. Seismic shaking is the dominant trigger for remobilization and deformation at our studied lakes. We propose that long duration and low frequency content of seismic shaking facilitates surficial remobilization, whereas ground motion amplitude controls KHI-related SSDS development.

Turbulent motions regulate vertical transport of momentum, heat, moisture and pollutants in the atmospheric boundary layer. From a numerical perspective, modeling such motions becomes challenging at kilometer and sub-kilometer resolutions, as the horizontal grid spacing of the model approaches the size of the most energetic convective eddies in the boundary layer. In this range of resolutions, typically termed ‘terra incognita’ or ‘gray zone’, partially resolved convective structures are grid-dependent and neither traditional 1D mesoscale parametrizations nor 3D closures typical of Large Eddy Simulations are theoretically appropriate. However, accurate numerical modeling at gray zone resolutions is a key aspect in several practical applications, such as proper coupling of mesoscale and microscale simulations. While some progress has been achieved in recent years through idealized simulations and theoretical considerations, the evaluation of different approaches in real convective boundary layers (CBL) is still very limited. Leveraging on a new set of one-way nested, full-physics multiscale numerical experiments, we quantify the magnitude of the errors introduced at gray zone resolutions and provide new perspectives on recently proposed modeling approaches. The new set of experiments is forced by real time-varying boundary conditions, spans a wide range of scales and includes traditional 1D schemes, 3D closures, scale-aware parametrizations and strategies to suppress resolved convection at gray zone resolutions. The study area is Riyadh (Saudi Arabia), where deep CBLs develop owing to strong convective conditions. Detailed analyses of our experiments, including validation with radiosonde data, calculations of spectral characteristics and partitioning of turbulent fluxes between resolved and subgrid scales, show that (i) grid-dependent convective structures entail minor impacts on first order statistics of the flow due to some degree of ‘implicit scale-awareness’ of 1D parametrizations and (ii) 3D closures outperform traditional and scale-aware 1D schemes especially in the surface layer, among other findings. The new simulation suite provides a benchmark of real simulations that can be extended to assess how new techniques for simulations at gray zone resolutions perform.

In order to improve access to the data and models of the Heliophysics System Observatory (HSO) and NASA-funded research projects, the NASA Heliophysics archive and modeling groups are collaborating to create a Heliophysics Digital Resources Library (HDRL) for improved cross-mission and observation-model comparison, machine learning and other large-scale and collaborative analysis, increased discoverability and usability of data and model results, software and services, and more complete metadata and provenance and quality control. Observational data are archived and served by the Solar Data Analysis Center (SDAC) and the Space Physics Data Facility (SPDF). The Community Coordinated Modeling Center (CCMC) provides empirical and first-principles simulations and analysis and display tools. A number of largely cross-cutting registry, access, and analysis standards and tools are provided by the Heliophysics Data and Model Consortium (HDMC). As part of this effort, SPDF, as the active and final archive for non-solar NASA Heliophysics data, works with current operating missions and the Heliophysics community to ingest, preserve and serve a wide range of past and current public science-quality data from the mesosphere into the furthest reach of deep-space exploration. SPDF facilitates scientific analysis of multi-instrument and multi-mission datasets to enhance the science return of the many missions. SPDF develops and maintains the Common Data Format (CDF) and the associated ISTP/SPDF metadata guidelines. SPDF services include CDAWeb, which supports both survey and burst mode data with graphics, listings and data superset/subset functions. SPDF is currently receiving and serving data from missions including Parker Solar Probe, Solar Orbiter, MMS, Van Allen Probes, THEMIS/ARTEMIS, GOLD, ICON, ACE, Cluster, IBEX, Voyager, Geotail, Wind and many others, and >120 Ground-Based investigations. SPDF also operates the multi-mission orbit displays and query services of SSCWeb and 4D Orbit Viewer, as well as the Heliophysics Data Portal (HDP) discipline-wide data inventory and access service, and OMNIWeb and COHOWeb for near-Earth and deep-space solar wind plasma, magnetic field, and energetic particle database, respectively.

Fire emissions are an important component of global models, which help to understand the influence of sources, transport and chemistry on atmospheric composition. Global fire emission inventories can vary substantially due to the assumptions made in the emission creation process, including the defined vegetation type, fire detection, fuel loading, fraction of vegetation burned and emissions factors. Here, we focus on the uncertainty in emission factors and the resulting impact on modeled composition. Our study uses the Community Atmosphere Model with chemistry (CAM-chem) to model atmospheric composition for 2014, a year chosen for the relatively quiet El Niño Southern Oscillation activity. We focus on carbon monoxide (CO), a trace gas emitted from incomplete combustion and also produced from secondary oxidation of volatile organic compounds (VOCs). Fire is a major source of atmospheric CO and VOCs. Modeled CO from four fire emission inventories (CMIP6/GFED4s, QFED2.5, GFAS1.2 and FINN1.5) are compared after being implemented in CAM-chem. Multiple sensitivity tests are performed based on CO and VOC emission factor uncertainties. We compare model output in the 14 basis regions defined by the Global Fire Emissions Database (GFED) team and evaluate against CO observations from the Measurements of Pollution in the Troposphere (MOPITT) satellite-based instrument. For some regions, emission factor uncertainty spans the results found by using different inventories. Finally, we use modeled ozone (O3) to briefly investigate how emission factor uncertainty influences the atmospheric oxidative environment. Overall, accounting for emission factor uncertainty when modeling atmospheric chemistry can lend a range of uncertainty to simulated results.

Data standardization can enable data reuse by streamlining the way data are collected, providing descriptive metadata, and enabling machine readability. Standardized open-source data can be more readily reused in interdisciplinary research that requires large amounts of data, such as climate modeling. Despite the importance given to both FAIR (Findable, Accessible, Interoperable, Reusable) data practices and the need for open-source data, a remaining question is how community data standards and open-source data can be adopted by research data providers and ultimately achieve FAIR data practices. In an attempt to answer this question, we used newly created water quality community data reporting formats and applied them to open-source water quality data. The development of this water quality data format was curated with several other related formats (e.g., CSV, Sample metadata reporting formats), aimed at targeting the research community that have historically published water quality data in a variety of formats. The water quality community data format aims to standardize how these types of data are stored in the data repository, ESS-DIVE (Environmental Systems Science Data Infrastructure for a Virtual Ecosystem). Adoption of these formats will also follow FAIR practices, increase machine readability, and increase the reuse of this data. We applied this community format to open-source water quality data produced by the Watershed Function Scientific Focus Area (WFSFA), a large watershed study in the East River Colorado, which involves many national laboratories, institutions, scientists, and disciplines. In this presentation, we provide a demonstration of a relatively efficient process for converting open-source water quality data into a format that adheres to a community data standard. We created examples of water quality data translated to the reporting formats that demonstrated the functionality of these data standards; descriptive metadata and sample names, streamlined data entries, and increased machine readability were products of this translation. As the community data standards are integrated within the WFSFA data collection processes, and ultimately all data providers of ESS-DIVE, these steps may enable interdisciplinary data discovery, increase reuse, and follow FAIR data practices.

Land-use decisions, particularly in an agricultural setting, lie at the nexus of the colliding challenges of climate change and food insecurity. Understanding and guiding these decisions at the regional scale is a key strategy in the development of natural climate solutions and sustainable food production systems. These issues come together in a particularly high-stakes context in the Massachusetts cranberry industry, which occupies a position of significant economic and sociocultural importance in the region, but faces a number of challenges in the form of heightened competition, unstable prices, an aging farmer population, and changing ecological conditions. Many farmers are looking either for ways to become profitable, or to exit the industry in a financially sustainable way. One option is to sell their land to developers; another option, which is exciting to scientists and environmental advocates, is undergoing an active habitat rehabilitation to restore the beneficial ecosystem services of a functioning wetland environment. Integrating satellite data and in-situ sensor data collected over the past decade, we aim to conduct a systems analysis that unites the viewpoints of cranberry industry stakeholders and clarifies the trade-offs between environmental, economic, and social factors in the region. We propose to address this aim via three core research efforts: a contextual analysis of the industry; a valuation and mapping of key ecological, economic, and social factors; and an integrated modeling approach that models interactions and trade-offs between these factors. In particular, this presentation will focus on the progress we have made valuing and mapping key environmental and economic factors using publicly available satellite imagery and census data. This work demonstrates how these factors align with existing features of the natural and built environment, supports conservation organizations and municipalities in their restoration and conservation advocacy, and provides a foundation for future scenario mapping that will analyze trade-offs in different land use cases.

On January 6, 2019, OSIRIS-REx first observed particles ejecting from the surface of near-Earth asteroid (101955) Bennu. This ejection event was unexpected and was only captured by chance in a pair of optical navigation images taken by the OSIRIS-REx NavCam 1 imager. With this limited dataset of only two observations per ejected particle, traditional orbit determination to reconstruct the particles’ trajectories was not possible. Therefore, a new technique was developed for reconstruction of the ejection event based on some simplifying assumptions that the particles all ejected from the same location at the same time and that their velocities remained constant after ejection (a reasonable approximation for fast-moving particles given Bennu’s weak gravity). This technique was then applied to reconstruct those particle events observed by the OSIRIS-REx spacecraft at Bennu from January 2019 through June 2019 by Pelgrift et al. (2020). We present a follow-on to that work that applies the same technique to reconstruct the particle ejection events observed in the latter half of OSIRIS-REx proximity operations at Bennu, covering the time span from July 2019 through July 2020. We reconstructed 8 additional events, bringing the total number of Bennu particle ejection events reconstructed using this technique to 19. The new dataset includes the largest event observed to-date, with over 350 individual tracked particles. The new events have particle ejection velocities similar to the previous events, ranging from 5 cm/s to 1.8 m/s. In the full dataset of 19 events, we observed the same trend noted in the original work where the majority of events were estimated to have occurred at mid-latitudes and afternoon local solar times (LST). Reference: Pelgrift, J. Y., Lessac-Chenen, E. J., Adam, C. D., Leonard, J. M., Nelson, D. S., McCarthy, L., et al. (2020). Reconstruction of Bennu particle events from sparse data. Earth and Space Science. 7, e2019EA000938. https://doi.org/10.1029/2019EA000938

This paper represents the first national-level (United States) estimate of the economic impacts of vibriosis cases as exacerbated by climate change. Vibriosis is an illness contracted through foodborne and waterborne exposures to various Vibrio species (e.g., non-V. cholerae O1 and O139 serotypes) found in estuarine and marine environments, including within aquatic life such as shellfish and finfish. Objectives The objective of this study was to project climate-induced changes in vibriosis related to sea surface temperatures (SSTs) and associated economic impacts in the U.S. Methods Our analysis constructed three logistic regression models by Vibrio species, using vibriosis data sourced from the Cholera and Other Vibrio Illness Surveillance (COVIS) system and using historical SSTs. We relied on previous estimates of the cost-per-case of vibriosis to estimate future total annual medical costs, lost income from productivity loss, and mortality-related indirect costs throughout the U.S. We separately report results for V. parahaemolyticus, V. vulnificus, V. alginolyticus, and “V. spp” given the different associated health burden of each. Results By 2090, increases in SST are estimated to result in a 51 percent increase in cases annually relative to the baseline era (1995) under Representative Concentration Pathway (RCP) 4.5 and a 108 percent increase under RCP8.5. The cost of these illnesses is projected to reach over $5.2 billion annually under RCP4.5 and $7.3 billion annually under RCP8.5, relative to $2.2 billion in the baseline (2018 dollars), equivalent to 140 percent and 234 percent increases respectively. Discussion Vibriosis incidence is likely to increase in the U.S. under moderate and unmitigated climate change scenarios through increases in SST, resulting in a substantial burden of morbidity and mortality, and costing millions of dollars. These costs are mostly attributable to deaths, primarily from exposure to V. vulnificus. Evidence suggests that other factors, including sea surface salinity, may contribute to further increases in vibriosis cases in some regions of the U.S. and should be investigated.

The work of Monin and Obukhov has enabled a description of turbulent processes in the Atmospheric Boundary Layer using flux-variance similarity functions. These functions, also called Integral Turbulence Characteristics (ITC), are used to characterize the state of turbulence at all frequencies. However, due to the non-universality of ITC models, more investigations are necessary, especially in tropical regions where low wind conditions frequently occur. This study aims at investigating whether these normalized standard deviations obey the Monin-Obukhov Similarity Theory (MOST) above a forest site in the Sudanian climate, and at identifying the appropriate ITC models for this ecosystem. Data were collected from a 18m tower equipped with an Eddy Covariance system, above the clear forest at Bellefoungou’s village, Northwest of Benin, West Africa. The turbulence intensity parameters calculated for five years and half, were analyzed according to wind speed, stability conditions and seasons. From their relationships with the stability parameter, data driven models were then obtained by the nonlinear least squares. The results showed that, all similarity functions follow MOST with a 1/3 power law whatever the stratification of the atmosphere during all the seasons excepted the temperature which had a parabolic shape in near neutral condition (-0.05 < ζ < 0.1). A seasonal dependence of all ITCs was evidenced under stable conditions. Indeed, roughness length and strong winds which dominating especially in the dry season favored more efficient turbulent exchange at the site. We also showed that the heat transfer is relatively more efficient than H2O transfer under both stability conditions. The established temperature and CO2 similarity models are found to be closer, and for some given stratification conditions, to those already existing in literature. But a noteworthy finding is that the models often used to assign a quality criterion to turbulent fluxes showed an overestimation relatively to those established ‘locally’ for u and w through all atmospheric stratification.

The thermal structure of the subduction interface changes drastically within the first few million years following subduction initiation (i.e. subduction infancy), resulting in changing metamorphic conditions and degree of mechanical coupling. Metamorphic soles beneath ophiolites record snapshots of subduction infancy. Beneath the Samail Ophiolite (Oman), the sole comprises structurally higher high-temperature (HT) and lower low-temperature (LT) units. This apparent inverted metamorphic gradient has been attributed to metamorphism under different Pressure-Temperature (P-T) conditions along the interface. However, peak P-T and timing of LT sole subduction are poorly constrained. Samples from Oman Drilling Project core BT-1B (104 m of metamorphic rocks) reveal that the LT sole subducted to similar peak P as the HT sole, but experienced ~300˚C lower peak T. Prograde fabrics in meta-sedimentary and meta-mafic rocks record Si-in-phengite values and amphibole chemistries consistent with peak P-T of ~8-12 kbar and ~450-550˚C in the epidote-amphibolite facies. Retrograde fabrics record a transition from near pervasive ductile to localized brittle strain under greenschist facies conditions. Titanite U-Pb ages (two samples) constrain timing of peak LT sole subduction to 95.7 ± 1.1 Ma, which may post-date the HT sole by ~6-8 Myr. In light of previous HT sole thermobarometry and geochronology, these new results support a model of protracted subduction and accretion while the infant subduction zone cooled at rates of ~100˚C/Myr for ~1-5 Myr. Temporal overlap of LT sole metamorphism and ophiolite crust formation suggests that underthrusting and cooling may lead to interface weakening, facilitating upper plate extension and forearc spreading.

A relatively simple design of a segmented flow meter (SF meter) is presented for measuring in situ plasma flow velocities and other space plasma parameters. The response of the flow meter to space environment is simulated for plasma conditions representative of the ionosphere at mid and low latitudes using a Particle In Cell (PIC) code. A synthetic data set consisting of ion currents collected by several segments of the flow meter, and the physical parameters for which they were calculated, is then used to construct a solution library from which inference models can be constructed, using radial basis function (RBF) and neural network regressions. Simulation results show that with such a flow meter, it should be possible to infer plasma flow velocities in the direction perpendicular to the ram direction, with uncertainties of 45 m/s or less. Models can also be constructed to infer plasma densities, with a relative error of 23 %. This work is presented as a first assessment and proof of concept for an original design of a simple and robust flow meter.

The ever-increasing amount of SAR data motivates the development of automatic processing chains to fully exploit the opportunities offered by these large databases. The InSAR Mass processing Toolbox for Multidimensional time series (MasTer) is an optimized tool to automatically download SAR data, select the interferometric pairs, perform the interferometric mass processing, compute the geocoded deformation maps, invert and display the velocity maps and the 2D time series on a web page updated incrementally as soon as a new image is available. New challenges relate to data management and processing load. We address them through methodological improvements dedicated to optimizing the InSAR pair selection. The proposed algorithm narrows the classical selection based on the shortest temporal and spatial baselines thanks to a coherence proxy and balances the use of each image as Primary and Secondary images thanks to graph theory methods. We apply the processing to three volcanic areas characterized with different climate, vegetation and deformation characteristics: the Virunga Volcanic Province (DR Congo), the Reunion Island (France) and the Domuyo and Laguna del Maule area (Chile-Argentina border). Compared to pair selection based solely on baseline criteria, this new tool produces similar velocity maps while reducing the total number of computed differential InSAR interferograms by up to 75\%, which drastically reduces the computation time. The optimization also allows to reduce the influence of DEM errors and atmospheric phase screen, which increase the signal-to-noise ratio of the inverted displacement time series.

This contribution highlights part of training events designed to collect, analyze, and manage water and water-related data (e.g., climate, weather, land, soils) and information products for the purposes of reducing water-related risks, and improving regional responses to environmental emergencies in the Mekong region. In this work, we discuss multiple tools and applications developed by National Aeronautics and Space Administration (NASA) scientists to lower technical barriers through current web technologies and leveraging data sharing capabilities among existing programs and institutions within different parts of the Mekong region. The aim of this training contribution is to leverage a well-established suite of tools that include but are not limited to remote sensing precipitation data adjustment techniques, i.e., the SWATOnline visualization and modeling system, and the NASAaccess data toolkit. The collaborative training events, which this contribution is part of, are administered by the United States Department of State (DOS) and the Ministry of Foreign Affairs - Republic of Korea under the Mekong-US Partnership and its Mekong Water Data Initiative facilitated by Sustainable Infrastructure Partnership (SIP) program. The Mekong Water Data is a DOS Initiative consists of multiple efforts and programs with an overarching objective of building the capacity of Mekong riparian countries and the Mekong River Commission Secretariat (MRCS), National Mekong Committees and line agencies in the Lower Mekong countries to improve the management of the Mekong River.

Thunderstorms exhibiting anomalous charge structures (ACSs, i.e., anomalous storms) are comprised by more riming ice carrying net positive versus negative charge, thought to result from increased mixed-phase cloud liquid water content (LWC). Anomalous storms are rarely observed in the United States (US) outside of the Great Plains (GP) region, where environmental conditions that suppress warm precipitation efficiency and support robust updrafts are thought to favor increased mixed-phase LWC. Two rare anomalous supercells in the Southeastern (SE) US exhibited similar charge structure characteristics as observed in GP anomalous storms, including a deep positive (negative) charge layer associated with riming (non-riming) ice in the lower (upper) mixed-phase region. However, most characteristics associated with SE anomalous environments were not consistent with those in the GP. A more rigorous evaluation of hypotheses concerning ACS development and their observation in the SE compared electrical, kinematic, microphysical, and environmental properties between the two anomalous and two SE normal supercells (i.e., exhibiting normal charge structures). Similar metrics of warm precipitation efficiency were observed in each. However, lower relative humidity in the charging region of the SE anomalous storms uniquely matched environmental characteristics in GP anomalous storms and differentiated SE anomalous from normal environments, suggesting the relative importance of saturation ratio alongside LWC in positive charging of riming ice. Differences were also observed in charge region characteristics and flash locations between a SE anomalous and normal storm. As riming ice increased in the negative charge region of the ACS, flash initiation locations were increasingly observed in stronger updrafts and updraft gradients compared with the normal storm. The evolution of microphysical characteristics of the negative charge region in the anomalous storm suggested an increase in normal alongside anomalous charging, indicating that variability in charging polarity may impact spatial flash relationships with the updraft. Further work is needed to diagnose whether particle-scale charging variability influences flash rate relationships with convective parameters such as updraft or graupel volume.

It is widely accepted that the signature of anticyclonic (cyclonic) eddies on the sea surface temperature corresponds to a warm (cold) core anomaly. Nevertheless, this statement has been put to question by recent regional studies showing the existence of inverse eddy SST anomalies: cold-core anticyclones and respectively warm-core cyclones. This study shows that the emergence of these inverse signatures is a seasonal phenomenon that affects the life cycle of mesoscale eddies in the Mediterranean Sea. We use remote-sensing observations and in-situ data to analyse the eddy-induced SST anomaly over a 2 years period (2016-2018). We build an eddy core surface temperature index to quantify the amount of Cold Core Anticyclones and Warm Core Cyclones all over the year and especially during the spring re-stratification period. We find that these inverse eddy signatures could reach a peak of 70 % in May and June, both for cyclones and anticyclones. Besides, in order to understand the underlying dynamical processes, we construct a simple vertical column model to study the impact of the seasonal air-sea fluxes on the surface stratification inside and outside eddies. It is only by taking into account a differential diapycnal eddy mixing - increased in anticyclones and reduced in cyclones - that we reproduce correctly, in agreement with the observations, the surface temperature inversion in the eddy core. This simplified model, suggests that vertical mixing modulation by mesoscale eddies might be the key mechanism that leads to the eddy-SSTA seasonal inversion in the ocean.