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An Intercomparison and Evaluation of Aircraft-Derived and Simulated CO from Seven Chemical Transport Models During the TRACE-P Experiment

Four global scale and three regional scale chemical transport models are intercompared and evaluated during NASA's TRACE-P experiment. Model simulated and measured CO are statistically analyzed along aircraft flight tracks. Results for the combination of eleven flights show an overall negative bias in simulated CO. Biases are most pronounced during large CO events. Statistical agreements vary greatly among the individual flights. Those flights with the greatest range of CO values tend to be the worst simulated. However, for each given flight, the models generally provide similar relative results. The models exhibit difficulties simulating intense CO plumes. CO error is found to be greatest in the lower troposphere. Convective mass flux is shown to be very important, particularly near emissions source regions. Occasionally meteorological lift associated with excessive model-calculated mass fluxes leads to an overestimation of mid- and upper- tropospheric mixing ratios. Planetary Boundary Layer (PBL) depth is found to play an important role in simulating intense CO plumes. PBL depth is shown to cap plumes, confining heavy pollution to the very lowest levels.

Kiley, C. M.↗

Differential Organic Carbon Mineralization Responses to Soil Moisture in Three Different Soil Orders Under Mixed Forested System: Supporting Data

This data contains data from 90-day long incubation study which aimed to look at the soil moisture-texture relationship on soil organic carbon (SOC) cycling. Soils were collected from three distinct soil textures from mixed forests in 2017: sandy (Georgia, 2017-05-01), loamy (Missouri, 2017-06-14) and clayey (Texas, December 2017) were incubated at different soil moisture levels (air-dried, 25% water holding capacity (WHC), 50% WHC, 100% WHC and 175% WHC) at room temperature for a period of 90 days. Files contain microbial respiration, active and slow SOC pools, and their respective mineralization rates, extractable organic carbon (C), and C-acquiring extracellular enzymes. Findings from these data were used in Singh et al. (2021). This study aimed to examine the interactive effect of soil moisture and texture on SOC mineralization. Soil samples of three distinct textures (sandy, loamy, and clayey) were collected from mixed forests of Georgia, Missouri, and Texas, respectively. Soil cores of 5 cm diameter were collected from numerous random locations at each site from 0-15 cm depth after scraping the litter layer and mixed thoroughly to obtain a composite sample per site. Three additional soil cores were collected to determine the WHC using pressure plate extractors. Soil samples were composited, and triplicate soil samples were incubated in mason jars for a period of 90 days at room temperature under different moisture regimes: air dried, 25% WHC, 50% WHC, at WHC and 100% saturation. Soil respiration was measured weekly, and destructive sampling was conducted at 1, 15, 60, and 90 days to determine extractable organic C, C acquiring enzyme activity, and active and slow SOC pools with their respective mineralization rates. The C acquiring enzyme activity was the total activity of α-glucosidase, β-glucosidase, cellobiohydrolase, and β-xylosidase enzymes. Gas samples for microbial respiration measurements were collected from headspace of incubation jars through the sampling ports on the lids and then analyzed using a Shimadzu Gas Chromatograph (GC-2014). Prior to sampling, the vials were evacuated. Blank correction was also done by collecting gas samples from empty incubation jars. Double pool exponential decay model was used in SigmaPlot to determine the active and slow SOC pools and their mineralization rates (Farrar et al., 2012; Jagadamma et al., 2014). The C-acquiring extracellular enzymes were measured using the microplate method by German et al., (2011). Microbial community structure was determined using the phospholipid fatty acid (PLFA) and neutral lipid fatty acid (NLFA) analyses (Buyer and Sasser, 2012). This dataset has seven data files provided in comma-separate (*.csv) format. Additional metadata are provided: seven data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

Carbon acquiring enzyme activity↗

Testing Extensions of Our Quantitative Daily of San Joaquin Wintertime Aerosols Using MAIAC and Meteorology Without Transport/Transformation Assumptions

The Western US and many regions globally present daunting difficulties in understanding and mapping PM2.5 episodes. We evaluate extensions of a method independent of source-description and transport/transformation. These regions suffer frequent few-day episodes due to shallow mixing; low satellite AOT and bright surfaces complicate the description. Nevertheless, we expect residual errors in our maps of less than 8 ug/m^3 in episodes reaching 60-100 ug/m^3; maps which detail pollution from Interstate 5. Our current success is due to use of physically meaningful functions of MODIS-MAIAC-derived AOD, afternoon mixed-layer height, and relative humidity for a basin in which the latter are correlated. A mixed-effects model then describes a daily AOT-to-PM2.5 relationship. (Note: in other published mixed-effects models, AOT contributes minimally. We seek to extend on these to develop useful estimation methods for similar situations. We evaluate existing but more spotty information on size distribution (AERONET, MISR, MAIA, CALIPSO, other remote sensing). We also describe the usefulness of an equivalent mixing depth for water vapor vs meteorological boundary layer height. Each has virtues and limitations. Finally, we begin to evaluate methods for removing the complications due to detached but polluted layers (which don't mix to the surface) using geographical, meteorological, and remotely sensed data.

Chatfield, Robert B.↗

Vertical Structure in Phytoplankton Growth and Productivity Inferred From Biogeochemical-Argo Floats and the Carbon-Based Productivity Model

Estimates of marine net primary production (NPP) commonly rely on limited in situ 14C incubations or satellite-based algorithms mainly constrained to the surface ocean. Here we combine data from biogeochemical Argo floats with a carbon-based productivity model (CbPM) to compute vertically-resolved estimates of NPP. Inferred NPP profiles derived by informing the CbPM with float-based, depth-resolved, bio-optical data are able to qualitatively reproduce the vertical structure in NPP inferred from in situ 14C incubations at various ocean regions. At station ALOHA, float-based estimates agree within uncertainty with productivity observations at depth, but underestimate surface NPP. We test the ability of the CbPM to infer the depth-resolved structure in NPP from bio-optical properties in the mixed layer, in similar fashion as how remote sensing algorithms of ocean productivity operate. In Southern Ocean waters, the depth-reconstructing implementation of the CbPM overestimates phytoplankton division rates and Chl:C below the mixed layer, resulting in artificially high subsurface NPP when compared with the fully float-informed implementation of the model. The CbPM subsurface extrapolation of phytoplankton Chl, Chl:C division rates, and NPP improves by accounting for deep nutrient (iron) stress impacts on photoacclimation in the Southern Ocean. This improvement is also observed in vertically- integrated NPP, where the mean bias between model implementations in depth-integrated productivity south of 30◦S is reduced by 62 % when account for deep iron limitation. Our results demonstrate that profiling data from biogeochemical Argo floats can serve to inform regional adjustments that lead to the improvement of marine productivity algorithms.

NPP↗

Atmospheric Aerosol and Thermal Structure in the Boundary Layer Over the Los Angeles Basin

A field study using a mobile lidar was recently conducted in the L. A. Basin, California, to (1) examine the relationship between the vertical aerosol and the thermal structure, and (2) map the vertical aerosol structure in the atmospheric boundary layer over the basin. These data are needed for use in the development of a mixing-depth submodel required for photochemical air Quality simulation models. Toward these ends, a series of lidar aerosol measurements in conjunction with balloon and aircraft temperature soundings were taken at a site in El Monte, and in a mobile mode along a 90-mile freeway loop between El Monte, Santa Monica, and Long Beach. The lidar data are presented in the form of time-height and distance-height cross sections. The results indicate that, although aerosol concentrations are frequently present above the base of the marine inversion, these are generally in stratified layers in contrast to the more uniform nature of the lower convective layer, permitting the mixing depth to be distinguished on this basis. The lidar-derived mixing depths are well correlated (within 100 m) with daytime temperature inversions. Other significant features shown by the lidar data include large Basin-wide mixing-depth variations, waves with amplitudes of 200-300 m and wavelengths of 1000-1500 m on the lower aerosol layer, and apparent aerosol "chimneys" with overrunning in the vicinity of convergence zones.

Johnson, Warren B.↗

A Melting Layer Model for Passive/Active Microwave Remote Sensing Applications: Model Formulation and Comparison with Observations - Part 1

In this study, a 1-D steady-state microphysical model which describes the vertical distribution of melting precipitation particles is developed. The model is driven by the ice-phase precipitation distributions just above the freezing level at applicable gridpoints of "parent" 3-D cloud-resolving model (CRM) simulations. It extends these simulations by providing the number density and meltwater fraction of each particle in finely separated size categories through the melting layer. The depth of the modeled melting layer is primarily determined by the initial material density of the ice-phase precipitation. The radiative properties of melting precipitation at microwave frequencies are calculated based upon different methods for describing the dielectric properties of mixed phase particles. Particle absorption and scattering efficiencies at the Tropical Rainfall Measuring Mission Microwave Imager frequencies (10.65 to 85.5 GHz) are enhanced greatly for relatively small (approx. 0.1) meltwater fractions. The relatively large number of partially-melted particles just below the freezing level in stratiform regions leads to significant microwave absorption, well-exceeding the absorption by rain at the base of the melting layer. Calculated precipitation backscatter efficiencies at the Precipitation Radar frequency (13.8 GHz) increase in proportion to the particle meltwater fraction, leading to a "bright-band" of enhanced radar reflectivities in agreement with previous studies. The radiative properties of the melting layer are determined by the choice of dielectric models and the initial water contents and material densities of the "seeding" ice-phase precipitation particles. Simulated melting layer profiles based upon snow described by the Fabry-Szyrmer core-shell dielectric model and graupel described by the Maxwell-Garnett water matrix dielectric model lead to reasonable agreement with radar-derived melting layer optical depth distributions. Moreover, control profiles that do not contain mixed-phase precipitation particles yield optical depths that are systematically lower than those observed. Therefore, the use of the melting layer model to extend 3-D CRM simulations appears justified, at least until more realistic spectral methods for describing melting precipitation in high-resolution, 3-D CRM's are implemented.

Olson, William S.↗

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗

On the rate of destruction of lithium in late-type main-sequence stars

It it shown that the rate of destruction of lithium by nuclear reactions in the outer mixed layers of late-type main-sequence stars depends on both the depth of the region where mixing occurs and the stratification within it. The mixed region includes and probably extends beneath the base of the convection zone. As the star evolves on the main sequence, the properties of the convection zone vary in a simple manner. If the mixed layer behaves similarly, then the mean destruction rate can easily be related to the present local value evaluated at the base of the mixed layer. In the case of the sun, it is found that if mixing is rapid compared with the nuclear destruction rate, then the mean destruction rate is approximately equal to one-half the present local value.

Christensen-Dalsgaard, J.↗

Penetration below a convective zone

Two-dimensional numerical simulations are used to investigate how fully compressible nonlinear convection penetrates into a stably stratified zone beneath a stellar convection zone. Estimates are obtained of the extent of penetration as the relative stability S of the stable to the unstable zone is varied over a broad range. The model deals with a perfect gas possessing a constant dynamic viscosity. The dynamics is dominated by downward-directed plumes which can extend far into the stable material and which can lead to the excitation of a broad spectrum of internal gravity waves in the lower stable zone. The convection is highly time dependent, with the close coupling between the lateral swaying of the plumes and the internal gravity waves they generate serving to modulate the strength of the convection. The depth of penetration delta, determined by the position where the time-averaged kinetic flux has its first zero in the stable layer, is controlled by a balance between the kinetic energy carried into the stable layer by the plumes and the buoyancy braking they experience there. A passive scalar is introduced into the unstable layer to evaluate the transport of chemical species downward. Such a tracer is effectively mixed within a few convective overturning times down to a depth of delta within the stable layer. Analytical estimates based on simple scaling laws are used to interpret the variation of delta with S, showing that it first involves an interval of adiabatic penetration if the local Peclet number of the convection exceeds unity, followed by a further thermal adjustment layer, the depths of each interval scaling in turn as S(exp -1) and S(exp -1/4). These estimates are in accord with the penetration results from the simulations.

Hurlburt, Neal E.↗

A large-eddy simulation exploration of the assumptions used in retrieving entrainment from a mixing diagram approach with ground-based remote sensors

Entrainment is a crucial component of the atmospheric boundary layer (BL) moisture and heat budget. While usually thought of as only entrainment flux, entrainment within the mixed layer budget equation is really composed of two terms: the flux of a property across the boundary separating the BL from the free troposphere and the change in the concentration of a property as the depth of the BL changes. In a recent study, Wakefield et al. (2023) used ground-based remote-sensing observations to estimate entrainment flux as the residual of a mixing diagram framework that was applied to the daytime convective boundary layer. This present work uses large-eddy simulation (LES) to examine how well this residual assumption for entrainment fluxes alone compares to the actual sum of those two entrainment terms derived from spatial averages of the LES output. We highlight the importance of the second entrainment term in closing the mixed layer budget and show that the residual assumption does not represent entrainment flux only but rather a total entrainment term when the boundary layer depth is changing.

Rosenberger, Tessa E. [Cleveland State Univ., Clev↗

Particle track record in Apollo 15 deep core from 54 to 80 cm depths.

Particle track measurements have been made in nearly 500 individual grains from 13 levels in the 54-80 cm depth range of the Apollo 15 deep core. They reveal a wide range of track densities at all depths and some systematic variations within layers, indicating that both predepositional mixing and subsequent layering are present and that separate sublayers exist within larger regions where no sublayers are visible. Minimum track densities are inferred to be useful measures of maximum residence times for undisturbed layers. Using the observed minimum track densities, we conclude that the average deposition rate in this section of soil column was greater than 0.4 cm/million years.

Fleischer, R. L.↗

Indications of a Decrease in the Depth of Deep Convective Cores with Increasing Aerosol Concentration during the CACTI Campaign

Abstract An aerosol indirect effect on deep convective cores (DCCs), by which increasing aerosol concentration increases cloud-top height via enhanced latent heating and updraft velocity, has been proposed in many studies. However, the magnitude of this effect remains uncertain due to aerosol measurement limitations, modulation of the effect by meteorological conditions, and difficulties untangling meteorological and aerosol effects on DCCs. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in 2018–19 produced concentrated aerosol and cloud observations in a location with frequent DCCs, providing an opportunity to examine the proposed aerosol indirect effect on DCC depth in a rigorous and robust manner. For periods throughout the campaign with well-mixed boundary layers, we analyze relationships that exist between aerosol variables (condensation nuclei concentration > 10 nm, 0.4% cloud condensation nuclei concentration, 55–1000-nm aerosol concentration, and aerosol optical depth) and meteorological variables [level of neutral buoyancy (LNB), convective available potential energy, midlevel relative humidity, and deep-layer vertical wind shear] with the maximum radar-echo-top height and cloud-top temperature (CTT) of DCCs. Meteorological variables such as LNB and deep-layer shear are strongly correlated with DCC depth. LNB is also highly correlated with three of the aerosol variables. After accounting for meteorological correlations, increasing values of the aerosol variables [with the exception of one formulation of aerosol optical depth (AOD)] are generally correlated at a statistically significant level with a warmer CTT of DCCs. Therefore, for the study region and period considered, increasing aerosol concentration is mostly associated with a decrease in DCC depth.

54 ENVIRONMENTAL SCIENCES↗

Observed Variability in Convective Cell Characteristics and Near-Storm Environments across the Sea- and Bay-Breeze Fronts in Southeast Texas

Abstract During the DOE Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) IOP spanning June–September 2022, two fixed ARM sites and a mobile team concurrently sampled the airmass heterogeneity across sea- and bay-breeze fronts around the greater Houston metropolitan region. Here, we quantify the spatiotemporal variability between maritime (coastal/bay side of breeze fronts) and continental (inland side of breeze fronts) air masses over 15 IOP days characterized by strong sea-breeze forcing. We analyze environmental profile data from 177 radiosondes and use S- and C-band radar data to track and quantify the variability in attributes of more than 2300 shallow and transitioning cells across different air masses. The composite analysis of environmental profiles indicates that during the early afternoon, the sea-breeze maritime air mass exhibits lower convective available potential energy (CAPE) than the bay-breeze maritime air mass. As the sea breeze advances inland with time, CAPE within the maritime air mass exceeds that of the continental air mass to the north of the breeze fronts. In general, maritime cells have a larger mean composite reflectivity and cell widths than continental cells; however, the response varies between shallow and transitioning cells. Mean composite 20-dB Z echo-top heights, however, are similar across air masses for both shallow and transitioning cells. The continental and maritime inflow air mass for transitioning cells has significantly different mean values for mixed-layer entrainment CAPE, lifted condensation level, level of free condensation, boundary layer depth, and diluted equilibrium level. For shallow cells, only total precipitable water shows a significant difference. Significance Statement The greater Houston metropolitan area is a natural laboratory for understanding the individual impacts of background meteorology and aerosols on convective clouds. Due to its proximity to the Gulf Coast and Galveston Bay, the Houston region experiences a diurnal precipitation cycle in the summer, driven by convection triggered from sea- and bay-breeze fronts. These fronts act as a boundary between air masses with distinct thermodynamic and environmental characteristics. Convergence along these fronts and interactions between storm outflow and the fronts facilitate convection initiation in different mesoscale air masses. This study quantifies the heterogeneity among these air masses while investigating their influence on cloud microphysics. We find that the effect of airmass heterogeneity is more pronounced for the bulk microphysical properties in shallow clouds.

Sharma, Milind↗

Mixing of the lunar regolith

A probabilistic model for mixing and turnover rates for the lunar regolith due to meteoritic impact is presented and evaluated using results from laboratory impact experiments and estimated meteoritic fluxes. The upper millimeter of the lunar surface is shown to be the primary mixing zone in the regolith and an important source for impact melts and vapors. Below this 'mixing layer' the rate of mixing and turnover decreases very rapidly with increasing depth, consistent with well-preserved stratigraphy and resident times deduced from deep drill core tube samples.

Gault, D. E.↗

Magneto-Stokes flow in a shallow free-surface annulus

In this study, we analyse ‘magneto-Stokes’ flow, a fundamental magnetohydrodynamic (MHD) flow that shares the cylindrical-annular geometry of the Taylor–Couette cell but uses applied electromagnetic forces to circulate a free-surface layer of electrolyte at low Reynolds numbers. The first complete, analytical solution for time-dependent magneto-Stokes flow is presented and validated with coupled laboratory and numerical experiments. Three regimes are distinguished (shallow-layer, transitional and deep-layer flow regimes), and their influence on the efficiency of microscale mixing is clarified. The solution in the shallow-layer limit belongs to a newly identified class of MHD potential flows, and thus induces mixing without the aid of axial vorticity. We show that these shallow-layer magneto-Stokes flows can still augment mixing in distinct Taylor dispersion and advection-dominated mixing regimes. The existence of enhanced mixing across all three distinguished flow regimes is predicted by asymptotic scaling laws and supported by three-dimensional numerical simulations. Mixing enhancement is initiated with the least electromagnetic forcing in channels with order-unity depth-to-gap-width ratios. If the strength of the electromagnetic forcing is not a constraint, then shallow-layer flows can still yield the shortest mixing times in the advection-dominated limit. Our robust description of momentum evolution and mixing of passive tracers makes the annular magneto-Stokes system fit for use as an MHD reference flow.

58 GEOSCIENCES↗

Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity from Landsat.

Alonzo, Michael↗

The Detection of Change in the Arctic Using Satellite and Buoy Data

The decade of the 1990s is the warmest decade of the last century while the year 1998 is the warmest year ever observed by modern techniques with 9 out of 12 months of the year being the warmest month. Since the Arctic is expected to provide early signals of a possible warming scenario, detailed examination of changes in the Arctic environment is important. In this study, we examined available satellite ice cover and surface temperature data, wind and pressure data, and ocean hydrographic data to gain insights into the warming phenomenon. The areas of open water in both western and eastern regions of the Arctic were found to follow a cyclical pattern with approximately decadal period but with a lag of about three years between the two regions. The pattern was interrupted by unusually large anomalies in open water area in the western region in 1993 and 1998 and in the eastern region in 1995. The big 1998 open water anomaly occurred at the same time when a large surface temperature anomaly was also occurring in the area and adjacent regions. The infrared temperature data show for the first time the complete spatial scope of the warming anomalies and it is apparent that despite the magnitude of the 1998 anomaly, it is basically confined to North America and the Western Arctic. The large increases in open water areas in the Western Sector form 1996 to 1998 were observed to be coherent with changing wind directions which was predominantly cyclonic in 1996 and anti-cyclonic in 1997 and 1998. Detailed hydrography measurements up to 500 m depth over the same general area in April 1996 and April 1997 also indicate significant freshening and warming in the upper part of the mixed layer suggesting increases in ice melt. Continuous ocean temperature and salinity data from ocean buoys confirm this result and show significant seasonal changes from 1996 to 1998, at depths of 8 m, 45 m, and 75 m. Long data records of temperature and hydrography were also examined and the potential impact of a warming, freshening, and the presence of abnormally large open areas on the state of the Arctic climate system are discussed.

Comiso, Josefino C.↗

Southern Ocean Heat Storage, Reemergence, and Winter Sea Ice Decline Induced by Summertime Winds

The observational record shows a substantial 40-yr upward trend in summertime westerly winds over the Southern Ocean, as characterized by the southern annular mode (SAM) index. Enhanced summertime westerly winds have been linked to cold summertime sea surface temperature (SST) anomalies. Previous studies have suggested that Ekman transport or upwelling is responsible for this seasonal cooling. Here, another process is presented in which enhanced vertical mixing, driven by summertime wind anomalies, moves heat downward, cooling the sea surface and simultaneously warming the subsurface waters. The anomalously cold SSTs draw heat from the atmosphere into the ocean, leading to increased depth-integrated ocean heat content. The subsurface heat is returned to the surface mixed layer during the autumn and winter as the mixed layer deepens, leading to anomalously warm SSTs and potentially reducing sea ice cover. Observational analyses and numerical experiments support our proposed mechanism, showing that enhanced vertical mixing produces subsurface warming and cools the surface mixed layer. Nevertheless, the dominant driver of surface cooling remains uncertain; the relative importance of advective and mixing contributions to the surface cooling is model dependent. Modeling results suggest that sea ice volume is more sensitive to summertime winds than sea ice extent, implying that enhanced summertime westerly winds may lead to thinner sea ice in the following winter, if not lesser ice extent. Thus, strong summertime winds could precondition the sea ice cover for a rapid retreat in the following melt season.

Southern Ocean↗