Mesoscale Variability Research Articles

Mesoscale neuronal granular trial variability in vivo illustrated by nonlinear recurrent network in silico.

Large-scale neural recording with single-neuron resolution has revealed the functional complexity of the neural systems. However, even under well-designed task conditions, the cortex-wide network exhibits highly dynamic trial variability, posing challenges to the conventional trial-averaged analysis. To study mesoscale trial variability, we conducted a comparative study between fluorescence imaging of layer-2/3 neurons in vivo and network simulation in silico. We imaged up to 40,000 cortical neurons' triggered responses by deep brain stimulus (DBS). And we build an in silico network to reproduce the biological phenomena we observed in vivo. We proved the existence of ineluctable trial variability and found it influenced by input amplitude and range. Moreover, we demonstrated that a spatially heterogeneous coding community accounts for more reliable inter-trial coding despite single-unit trial variability. A deeper understanding of trial variability from the perspective of a dynamical system may lead to uncovering intellectual abilities such as parallel coding and creativity.

Nested cross-validation Gaussian process to model dimethylsulfide mesoscale variations in warm oligotrophic Mediterranean seawater

The study proposes an approach to elucidate spatiotemporal mesoscale variations of seawater Dimethylsulfide (DMS) concentrations, the largest natural source of atmospheric sulfur aerosol, based on the Gaussian Process Regression (GPR) machine learning model. Presently, the GPR was trained and evaluated by nested cross-validation across the warm-oligotrophic Mediterranean Sea, a climate hot spot region, leveraging the high-resolution satellite measurements and Mediterranean physical reanalysis together with in-situ DMS observations. The end product is daily gridded fields with a spatial resolution of 0.083° × 0.083° (~9 km) that spans 23 years (1998–2020). Extensive observations of atmospheric methanesulfonic acid (MSA), a typical biogenic secondary aerosol component from DMS oxidation, are consistent with the parameterized high-resolution estimates of sea-to-air DMS flux (FDMS). This represents substantial progress over existing coarse-resolution DMS global maps which do not accurately depict the seasonal patterns of MSA in the Mediterranean atmospheric boundary layer.

Advancing the Seasonal Outlook of the Wet Seasons of Florida

Abstract In this study, we introduce an ensemble approach to provide a probabilistic seasonal outlook of the length and seasonal rainfall anomaly of the wet season over Florida using the observed variations of the onset date of the season at the granularity of ∼10-km grid resolution (which is the spatial resolution of the observed rainfall data used for this work). The time series of daily precipitation at the grid resolution of NASA’s Global Precipitation Mission is randomly perturbed 1000 times to account for the uncertainty of synoptic to mesoscale variations on the diagnosis of the onset and demise date of the wet season. The strong covariability of the onset date with the seasonal length and seasonal rainfall anomaly of the wet season is then leveraged to provide the seasonal outlooks by monitoring the onset date of the wet season. This simple seasonal outlook is effective in predicting extreme tercile and even extreme pentile anomalies across Florida. We suggest that the proposed approach to the seasonal outlook of the wet season of Florida provides a viable alternative in the absence of strong external forcing like ENSO or tropical Atlantic variability that potentially limits the predictability of numerical climate models used for seasonal prediction. Significance Statement Earlier studies have shown that the seasonal prediction from the numerical climate models even at zero lead time has very limited prediction skills over the summer in Florida, which also coincides with the wettest part of the year. Florida’s wet season exhibits significant interannual variations, which exert its influence on water management decisions for subsequent drier seasons of the year. Therefore, strategies to improve this skill are highly relevant. We propose in this study that by monitoring the onset of the wet season variations, we can usefully provide a probabilistic seasonal outlook of the season over Florida. This is done by leveraging the observed linear relationships between the onset date variations with the length and the seasonal rainfall anomaly of the season. Furthermore, the outlook is provided at the spatial resolution of the observed dataset, which in this case is at 10-km grid resolution.

Mesoscale Variations in the Number of Thunder Days Over the Japanese Archipelago During the Past Fifty‐Six Years

ABSTRACTThe spatial and temporal variations of cumulonimbus clouds (Cbs) that produce lightning have mesoscale characteristics due to the nature of Cbs and the influence of topography; however, previous studies have lacked a mesoscale perspective because historical lightning observations relied on human observation. In this study, mesoscale variations in the number of thunder days (TDs) over the Japanese Archipelago over a 56‐year period were investigated using manned observation data (Period 1: 1954–1963) and radio‐wave observation data (Period 2: 2010–2019). A comparison of the two periods of Period 1 and Period 2 revealed that the locations of mesoscale areas with high TDs did not change significantly; however, the number of TDs increased in most mesoscale areas and it was not possible to identify any mesoscale areas with a significant decreasing trend. The characteristics of mesoscale variation varied with the season as follows: (1) Winter (November–January): the number of TDs along the coastal lands of the Sea of Japan increased significantly. The variations in the synoptic‐scale winter pressure pattern with low stability were one of the factors contributing to the increasing trend of TDs. (2) In the first half of the Baiu season (June), the number of TDs increased in two regions: one region was the south of Japan associated with the Baiu front, while the second region was the northern area of Japan, where the influence of the Baiu front is limited. (3) Summer (August): the number of TDs in mountainous areas tended to increase significantly, and the variation in the water vapour content was significantly correlated with the variation in the number of TDs. The number of TDs in the foothills did not increase significantly. (4) Akisame season (September): the number of TDs along the Pacific Ocean coast significantly increased.

Dimethyl sulfide (DMS) climatologies, fluxes, and trends – Part 1: Differences between seawater DMS estimations

Abstract. Dimethyl sulfide (DMS) is a naturally emitted trace gas that can affect the Earth's radiative budget by changing cloud albedo. Most atmospheric models that represent aerosol processes depend on regional or global distributions of seawater DMS concentrations and sea–air flux parameterizations to estimate its emissions. In this study, we analyse the differences between three estimations of seawater DMS, one of which is an observation-based interpolation method following Hulswar et al. (2022) (hereafter referred to as H22) and two of which are proxy-based parameterization methods following Galí et al. (2018) (hereafter referred to as G18) and Wang et al. (2020a) (hereafter referred to as W20). The interpolation-based method depends on the distribution of observations and the methods used to fill data between observations, while the parameterization-based methods rely on establishing a relationship between DMS and environmental parameters such as chlorophyll a, mixed-layer depth, nutrients, sea surface temperature, etc., which can then be used to predict DMS concentrations. On average, the interpolation-based methods show higher DMS values compared to the parameterization-based methods. Even though the interpolation method shows higher values than the parameterization-based methods, it fails to capture mesoscale variability. The regression-based parameterization method (G18) shows the lowest values compared to other estimations, especially in the Southern Ocean, which is the high-DMS region in austral summer. The parameterization-based methods suggest positive long-term trends in seawater DMS (3.82±0.79 % per decade for G18 and 2.13±0.32 % per decade for W20). Since large differences, often more than 100 %, are observed between the different estimations of seawater DMS, the derived sea–air fluxes and, hence, the impact of DMS on the radiative budget are sensitive to the estimate used.

The role of mesoscale-driven connectivity patterns in coral recovery around Moorea and Tahiti, French Polynesia

Coral reefs are declining due to anthropogenic warming. Nonetheless, some have recovered quickly from repeated bleaching events. Coral recovery depends on adaptation capabilities, fishing pressure, overall number of stressors, reef conditions before the event, and degree of connectivity. Coral reefs that are connected to many others can receive viable larvae and regain coverage faster. Around Moorea and Tahiti, within the Society Islands of French Polynesia, coral cover has regained its previous levels rapidly, despite several mass bleaching events over the past three decades. Here it is explored whether the connectivity with distant reefs may support such recovery by modeling the transport of coral larvae around the islands over 28 years. Ocean currents enable connectivity with the Tuamotu Islands, ~ 250 km to the northeast, that act as sources to Moorea and Tahiti for pelagic larval durations of three weeks or longer. The circulation around Moorea and Tahiti is very dynamic; mesoscale eddies can also halt the connectivity with the Tuamotu Islands and sporadically transport larvae from reefs to the west and southeast instead. With many undisturbed coral reefs within a 300 km radius and strong mesoscale variability, a dynamic, long-range connectivity may explain the recovery of reefs around Moorea and Tahiti.

Mesoscale soil moisture measurements along the rover route using the mobile cosmic-ray neutron sensing in the eastern Tibetan Plateau

Water resources in the soil play an essential role in hydrological processes and ecosystem functions on the Tibetan Plateau. However, accurately measuring soil moisture distribution in this region presents challenges due to the diverse ecosystem types, complex terrain, and harsh environmental conditions. In this study, we introduce an approach for estimating mesoscale soil moisture in the Qilian Mountains (QLM) region of the eastern Tibetan Plateau using a cosmic-ray neutron rover. Soil moisture estimates derived from neutron count rates, newly adjusted by vegetation effects, demonstrated good agreement with soil moisture measurements obtained through soil sampling at 26 calibration sites across the region (RMSE = 0.025 g g−1). The calibration parameter N0_NDVI was 443 cpm in the QLM. Utilizing NDVI as vegetation correction method showed potential improvements in the accuracy of converting neutron counts to soil moisture across the diverse mountainous ecosystem types. The newly developed calibration equation provided a high-precision, high spatial resolution soil moisture transect across various landscapes measured by the rover. The average mesoscale soil moisture along the rover route varied by ecosystem types, with values of 0.10 g/g in deserts, 0.17 g/g in grasslands, 0.13 g/g in forests, 0.18 g/g in subalpine shrublands, and 0.20 g/g in croplands. Land cover types emerged as crucial determinants of mesoscale soil moisture variability in the QLM region. These findings offer valuable mesoscale soil moisture data and new insights into soil water information at the transect scale across diverse ecosystem types in the Tibetan Plateau.

Circumpolar Transport and Overturning Strength Inferred From Satellite Observables Using Deep Learning in an Eddying Southern Ocean Channel Model

AbstractThe Southern Ocean connects the ocean's major basins via the Antarctic Circumpolar Current (ACC), and closes the global meridional overturning circulation (MOC). Observing these transports is challenging because three‐dimensional mesoscale‐resolving measurements of currents, temperature, and salinity are required to calculate transport in density coordinates. Previous studies have proposed to circumvent these limitations by inferring subsurface transports from satellite measurements using data‐driven methods. However, it is unclear whether these approaches can identify the signatures of subsurface transport in the Southern Ocean, which exhibits an energetic mesoscale eddy field superposed on a highly heterogeneous mean stratification and circulation. This study employs Deep Learning techniques to link the transports of the ACC and the upper and lower branches of the MOC to sea surface height (SSH) and ocean bottom pressure (OBP), using an idealized channel model of the Southern Ocean as a test bed. A key result is that a convolutional neural network produces skillful predictions of the ACC transport and MOC strength (skill score of 0.74 and 0.44, respectively). The skill of these predictions is similar across timescales ranging from daily to decadal but decreases substantially if SSH or OBP is omitted as a predictor. Using a fully connected or linear neural network yields similarly accurate predictions of the ACC transport but substantially less skillful predictions of the MOC strength. Our results suggest that Deep Learning offers a route to linking the Southern Ocean's zonal transport and overturning circulation to remote measurements, even in the presence of pronounced mesoscale variability.

Gravity Wave Momentum Fluxes from 1 km Global ECMWF Integrated Forecast System

Progress in understanding the impact of mesoscale variability, including gravity waves (GWs), on atmospheric circulation is often limited by the availability of global fine-resolution observations and simulated data. This study presents momentum fluxes due to atmospheric GWs extracted from four months of an experimental “nature run", integrated at a 1 km resolution (XNR1K) using the Integrated Forecast System (IFS) model. Helmholtz decomposition is used to compute zonal and meridional flux of vertical momentum from ~1.5 petabytes of data; quantities often emulated by climate model parameterization of GWs. The fluxes are validated using ERA5 reanalysis, both during the first week after initialization and over the boreal winter period from November 2018 to February 2019. The agreement between reanalysis and IFS demonstrates its capability to generate reliable flux distributions and capture mesoscale dynamic variability in the atmosphere. The dataset could be valuable in advancing our understanding of GW-planetary wave interactions, GW evolution around atmospheric extremes, and as high-quality training data for machine learning (ML) simulation of GWs.

Formation of Eastern Boundary Undercurrents via Mesoscale Eddy Rectification

Abstract Eastern boundary upwelling systems (EBUSs) host equatorward wind-driven near-surface currents overlying poleward subsurface undercurrents. Various previous theories for these undercurrents have emphasized the role of poleward alongshore pressure gradient forces (APFs). Energetic mesoscale variability may also serve to accelerate undercurrents via mesoscale stirring of the potential vorticity gradient imposed by the continental slope. However, it remains unclear whether this eddy rectification mechanism contributes substantially to driving poleward undercurrents in EBUS. This study isolates the influence of eddy rectification on undercurrents via a suite of idealized simulations forced either by alongshore winds, with or without an APF, or by randomly generated mesoscale eddies. It is found that the simulations develop undercurrents with strengths comparable to those found in nature in both wind-forced and randomly forced experiments. Analysis of the momentum budget reveals that the along-isobath undercurrent flow is accelerated by isopycnal advective eddy momentum fluxes and the APF and retarded by frictional drag. The undercurrent acceleration may manifest as eddy momentum fluxes or as topographic form stress depending on the coordinate system used to compute the momentum budget, which reconciles these findings with previous work that linked eddy acceleration of the undercurrent to topographic form stress. The leading-order momentum balance motivates a scaling for the strength of the undercurrent that explains most of the variance across the simulations. These findings indicate that eddy rectification is of comparable importance to the APF in driving poleward undercurrents in EBUSs and motivate further work to diagnose this effect in high-resolution models and observations and to parameterize it in coarse-resolution ocean/climate models.

Mesoscale variability of phosphorus stocks, hydrological and biological processes in the mixed layer in the Eastern Mediterranean Sea in autumn and during an unusually dense winter phytoplankton bloom

We investigated spatiotemporal variations of nutrients, dissolved organic pools (C, N, P), phosphomonoesterase (PME) and phosphodiesterase (PDE) activities, heterotrophic prokaryotic production and planktonic microorganisms within the mixed layer (ML) in the Eastern Mediterranean Sea. We characterized two contrasted situations: autumn 2018 (highly stratified period, deep chlorophyll maximum within 100 m depth) and winter 2019 (including a bloom period). We compared the distribution of biogeochemical variables within the mixed layer and hydrological vertical structure between the different stations using a principal component analysis. Six groups of stations were identified (one group in autumn, 5 in winter), based on variable physical descriptors but also environmental biogeochemical conditions related to i) the seasonal aspect (for instance, all stations sampled within the Ierapetra anticyclone in autumn clustered in one, single group); ii) transitions between cyclonic and anticyclonic structures with a large range of ML depths (18–269 m) and indications of intense, preceding winter convection events: iii) progression of a high phytoplankton bloom during the winter cruise inferred from a series of observations: a strong nitrate drawdown, important growth of Synechococcus, pico and nano eukaryotes, accumulation of chlorophyll a (>60 mg m−2), primary production rates up to 509 mg C m−2 d−1, changes in the pigments’ diversity, increase in biomass-specific ectoenzymatic activities and of heterotrophic prokaryotic production, all in conjunction with the vicinity of the Rhodes gyre. Here, we studied the distribution of biological and biogeochemical properties within the mixed layer, in particular by employing sensitive methods for the detection of low phosphate concentrations and of the labile dissolved organic phosphorus pool. From this data set, we demonstrate that the surface mixed layer classically considered as a P-depleted and uniform layer in the Eastern Mediterranean Sea was highly biologically dynamic, and prone to rapid spatio-temporal changes in phosphatase activities and phytoplankton dynamics. Altogether, these data reveal a strong short-term population dynamics. The results highlight the role of mixing episodes in winter, which provide pulsed supplies of phosphate and/or nitrate from the deeper layer to the euphotic zone, triggering transient blooms that often go undetected by satellites.

Mesoscale and climate environmental variability drive krill community changes in the Humboldt Current System

Euphausiids (or “krill”) play a crucial role in the food webs of eastern boundary upwelling systems. Their inter-specific predatory interactions with ecologically and commercially important species highlights the importance of understanding krill variability at different temporal and spatial scales. In the Humboldt Current System (HCS), few studies have addressed the spatio-temporal variability of krill communities and their link with climate and local environmental drivers. We studied the patterns and variability of euphausiid diversity in the coastal area off northern Chile, using zooplankton and CTD-O data, and satellite environmental data from the falls and springs of 2010–2017. The community showed low diversity and evenness, with the endemic species Euphausia mucronata being the most abundant. The environmental variance showed 2 main modes of variability: (1) upwelling-associated changes in the depth of the oxygen minimum zone (OMZ) and in temperature, and (2) interannual variability in salinity, associated with ENSO-driven water-mass changes. The diversity indices and community structure showed large fluctuations in the cross-shore direction, and with latitude. The general pattern showed higher diversity offshore and southward, with few species in the low temperature, shallow OMZ conditions of the coastal band. During the 2013 and 2016 marine heatwaves and the 2015-2016 El Niño, the Subtropical Water Mass was advected southward, causing an increase in salinity and temperature, and a decrease in total krill abundance. However, ENSO variability did not significantly affect the species composition. The changes in community structure were caused by fluctuations in species abundance rather than species presence, as the most abundant species dominated the community throughout the study period. These results indicate that the krill communities of the HCS are highly resilient to climate perturbations, with upwelling-associated gradients being the primary source of variability for euphausiid populations in this ecosystem.

Global Ocean pCO2 Variation Regimes: Spatial Patterns and the Emergence of a Hybrid Regime

AbstractThe variability in ocean surface partial pressure of carbon dioxide (pCO2), driven by both physical and biological processes, substantially influences air‐sea carbon exchange. It is widely recognized that the pCO2 variation at a specific ocean location is primarily dominated by either thermal or nonthermal effects. However, the distinct pCO2 variation regimes, their global distribution, and the mechanisms underlying such patterns have yet to be fully determined due to a paucity of global observations. Through the use of observation‐based products and an eddy‐resolving ocean simulation, this study demonstrates the presence of three distinct regimes in the global ocean: one in which sea surface temperature (SST) is the dominant control on pCO2 variations; another in which dissolved inorganic carbon (DIC) is the primary control; and a third previously uncharacterized hybrid regime where pCO2 variations are governed by seasonally‐varying factors. This hybrid regime is generally located between SST‐ and DIC‐dominated regimes and occupies approximately 15% of the global ocean. The regimes broadly exist in zonal bands that are closely linked to the relative strengths of SST and DIC variances. Seasonally‐varying mixed‐layer depth, mesoscale variability (quantified in terms of eddy kinetic energy), and biological processes modulate local pCO2 variations and play significant roles in shaping the global pattern of regime distributions. Understanding the distribution of pCO2 regimes, including the hybrid regime revealed in this study, as well as their different oceanic drivers, is essential for future predictions of ocean carbon uptake in response to global warming.

How Variable Are Cold Pools?

AbstractCold pools formed by precipitating convective clouds are an important source of mesoscale temperature variability. However, their sub‐mesoscale (100 m–10 km) structure has not been quantified, impeding validation of numerical models and understanding of their atmospheric and societal impacts. We assess temperature variability in observed and simulated cold pools using variograms calculated from dense network observations collected during a field experiment and in high‐resolution case‐study and idealized simulations. The temperature variance in cold pools is enhanced for spatial scales between ∼5 and 15 km compared to pre‐cold pool conditions, but the magnitude varies strongly with cold pool evolution and environment. Simulations capture the overall cold pool variogram shape well but underestimate the magnitude of the variability, irrespective of model resolution. Temperature variograms outside of cold pool periods are represented by the range of simulations evaluated here, suggesting that models misrepresent cold pool formation and/or dissipation processes.

Submesoscale‐Permitting Physical/Biogeochemical Future Projections for the Main Hawaiian Islands

AbstractGlobal climate models provide useful tools to forecast large‐scale anthropogenic trends and the impacts on ocean physics and marine biology and chemistry. Due to coarse spatial resolution, they typically lack the ability to represent important regional processes while underestimating mesoscale variability and vertical mixing. This means they provide limited value when it comes to regional climate projections. We developed a regional submesoscale‐permitting physical/biogeochemical model to dynamically downscale the output of a CMIP6 Earth System Model for three different Socioeconomic Pathways for the main Hawaiian Islands. We describe the methodology for downscaling the CMIP6 ocean physics and biogeochemistry along with atmospheric conditions in order to offline nest a regional model. We expect the large‐scale spatial and temporal features of the global model to be retained by the regional model, while adding representation of the regional processes that are crucial to understanding climate change on a local scale. We compare the regional model representation against both observed data and a regional reanalysis over the first two decades of the century. We show that the regional model maintains the large‐scale trends and interannual variability provided by the CMIP6 model while well‐representing the regional dynamics that drive the short‐term variability. To better illustrate the benefit of the downscaling, we present preliminary analysis of the downscaled results to examine climate impacts on the island corals that are not resolved by the global models. This analysis reveals that coastal corals are likely to experience unprecedented ocean acidification and substantial warming over the course of the century.

Regional Controls on Climate and Weather Variability on the Southwest Coast of Peru

Southwestern Peru has an arid climate typical of subtropical west coasts bordering cold ocean currents. Mountain runoff is barely able to sustain urban needs and motivates this research. Using high-resolution satellite reanalysis products, the meso-scale climate and weather variability are explored via point-to-field regression. A time series spanning 1970–2022 of Tacna area (18 S, 70.2 W, 570 m) rainfall, potential evaporation, wind, and weather parameters were evaluated for thermodynamic and kinematic features. Although sea breezes draw marine air inland, they simultaneously generate low-level divergence and subsidence aloft. Potential evaporation in early summer causes water deficits that are rarely offset by late summer runoff from the Andes Mountains. Winter (May–September) showers from passing cold fronts are more frequent during El Niño. Warming of the tropical east Pacific accelerates subtropical westerly winds that lift over the coastal plains. Quasi-stationary Rossby wave patterns amplify transient troughs at 70 W, but the winter showers rarely exceed 4 mm/day due to low-level stability from negative heat fluxes over cool seawater offshore. Two winter wet spells were studied using satellite and surface data (July 2002, July 2009). Light showers were prominent in elevations from 400 to 900 m. An early summer dry spell was considered (November 2020), wherein southeast winds, coastal upwelling, and low dewpoint temperatures coincided with La Niña conditions. A rain-gauge transect showed that summer convection stays east of the Andes escarpment and seldom benefits the coastal plains. Thus, water resources in Tacna are strained beyond the carrying capacity.

Impact of Typhoon Nanmadol (2011) on the propagation of nonlinear internal waves in the South China Sea

In situ measurements from an array of pressure-equipped inverted echo sounders (PIESs), numerical simulation results using a non-hydrostatic model (SUNTANS) that does not account for mesoscale variability, and a ray-tracing method are used to investigate the behavior of nonlinear internal waves (NLIWs) in the South China Sea, focusing on period of Typhoon Nanmadol passage. Unusual significant differences in NLIWs arrival time occur between the PIES observation and SUNTANS simulation results after Typhoon Nanmadol passage; i.e., the observed NLIWs show a delay of 0.5–1.5 h at the westernmost PIES sites compared to the simulated ones in the SUNTANS. A data-assimilated ocean model outputs in addition to satellite altimetry reveal that the passage of Typhoon Nanmadol alters the oceanic environments remarkably, creating thermocline shoaling of ~80 m, which can slow down the wave propagation speed. We account for the delay of NLIWs using ray-tracing simulations. Our results demonstrate that typhoon-induced changes in mesoscale structure can significantly impact the fate of NLIWs in the South China Sea, which have potential on ocean mixing and biogeochemical systems.

An evaluation of the LLC4320 global-ocean simulation based on the submesoscale structure of modeled sea surface temperature fields

Abstract. We have assembled 2 851 702 nearly cloud-free cutout images (sized 144 km × 144 km) of sea surface temperature (SST) data from the entire 2012–2020 Level-2 Visible Infrared Imaging Radiometer Suite (VIIRS) dataset to perform a quantitative comparison to the ocean model output from the MIT General Circulation Model (MITgcm). Specifically, we evaluate outputs from the LLC4320 (LLC, latitude–longitude–polar cap) 148∘ global-ocean simulation for a 1-year period starting on 17 November 2011 but otherwise matched in geography and the day of the year to the VIIRS observations. In lieu of simple (e.g., mean, standard deviation) or complex (e.g., power spectrum) statistics, we analyze the cutouts of SST anomalies with an unsupervised probabilistic autoencoder (PAE) trained to learn the distribution of structures in SST anomaly (SSTa) on ∼ 10–80 km scales (i.e., submesoscale to mesoscale). A principal finding is that the LLC4320 simulation reproduces, over a large fraction of the ocean, the observed distribution of SSTa patterns well, both globally and regionally. Globally, the medians of the structure distributions match to within 2σ for 65 % of the ocean, despite a modest, latitude-dependent offset. Regionally, the model outputs reproduce mesoscale variations in SSTa patterns revealed by the PAE in the VIIRS data, including subtle features imprinted by variations in bathymetry. We also identify significant differences in the distribution of SSTa patterns in several regions: (1) in an equatorial band equatorward of 15∘; (2) in the Antarctic Circumpolar Current (ACC), especially in the eastern half of the Indian Ocean; and (3) in the vicinity of the point at which western boundary currents separate from the continental margin. It is clear that region 3 is a result of premature separation in the simulated western boundary currents. The model output in region 2, the southern Indian Ocean, tends to predict more structure than observed, perhaps arising from a misrepresentation of the mixed layer or of energy dissipation and stirring in the simulation. The differences in region 1, the equatorial band, are also likely due to model errors, perhaps arising from the shortness of the simulation or from the lack of high-frequency and/or wavenumber atmospheric forcing. Although we do not yet know the exact causes for these model–data SSTa differences, we expect that this type of comparison will help guide future developments of high-resolution global-ocean simulations.

The Pacific water flow branches in the eastern Chukchi Sea

The flow of Pacific-origin water across the Chukchi Sea shelf impacts the regional ecosystem in profound ways, yet the two current branches on the eastern shelf that carry the water from Bering Strait to Barrow Canyon – the Alaskan Coastal Current (ACC) and Central Channel (CC) Branch – have not been clearly distinguished or quantified. In this study we use an extensive collection of repeat hydrographic sections occupied at three locations on the Chukchi shelf, together with data from a climatology of shipboard velocity data, to accomplish this. The data were collected predominantly between 2010 and 2020 during the warm months of the year as part of the Distributed Biological Observatory and Arctic Observing Network. The mean sections show that mass is balanced for both currents at the three locations: Bering Strait, Point Hope, and Barrow Canyon. The overall mean ACC transport is 0.34 ± 0.04 Sv, and that of the CC Branch is 0.86 ± 0.11 Sv. The dominant hydrographic variability at Bering Strait is seasonal, but this becomes less evident to the north. At Barrow Canyon, the dominant hydrographic signal is associated with year-to-year variations in sea-ice melt. Farther south there is pronounced mesoscale variability: an empirical orthogonal function analysis at Bering Strait and Point Hope reveals a distinct ACC mode and CC Branch mode in hydrography and baroclinic transport, where the former is wind-driven. Finally, the northward evolution in properties of the two currents is investigated. The poleward increase in salinity of the ACC can be explained by lateral mixing alone, but solar heating together with wind mixing play a large role in the temperature evolution. This same atmospheric forcing also impacts the northward evolution of the CC Branch.

Opinion: A critical evaluation of the evidence for aerosol invigoration of deep convection

Abstract. Deep convective updraft invigoration via indirect effects of increased aerosol number concentration on cloud microphysics is frequently cited as a driver of correlations between aerosol and deep convection properties. Here, we critically evaluate the theoretical, modeling, and observational evidence for warm- and cold-phase invigoration pathways. Though warm-phase invigoration is plausible and theoretically supported via lowering of the supersaturation with increased cloud droplet concentration in polluted conditions, the significance of this effect depends on substantial supersaturation changes in real-world convective clouds that have not been observed. Much of the theoretical support for cold-phase invigoration depends on unrealistic assumptions of instantaneous freezing and unloading of condensate in growing, isolated updrafts. When applying more realistic assumptions, impacts on buoyancy from enhanced latent heating via fusion in polluted conditions are largely canceled by greater condensate loading. Many foundational observational studies supporting invigoration have several fundamental methodological flaws that render their findings incorrect or highly questionable. Thus, much of the evidence for invigoration has come from numerical modeling, but different models and setups have produced a vast range of results. Furthermore, modeled aerosol impacts on deep convection are rarely tested for robustness, and microphysical biases relative to observations persist, rendering many results unreliable for application to the real world. Without clear theoretical, modeling, or observational support, and given that enervation rather than invigoration may occur for some deep convective regimes and environments, it is entirely possible that the overall impact of cold-phase invigoration is negligible. Substantial mesoscale variability of dominant thermodynamic controls on convective updraft strength coupled with substantial updraft and aerosol variability in any given event are poorly quantified by observations and present further challenges to isolating aerosol effects. Observational isolation and quantification of convective invigoration by aerosols is also complicated by limitations of available cloud condensation nuclei and updraft speed proxies, aerosol correlations with meteorological conditions, and cloud impacts on aerosols. Furthermore, many cloud processes, such as entrainment and condensate fallout, modulate updraft strength and aerosol–cloud interactions, varying with cloud life cycle and organization, but these processes remain poorly characterized. Considering these challenges, recommendations for future observational and modeling research related to aerosol invigoration of deep convection are provided.