Surface Fluxes Research Articles

Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output

Abstract. Land–atmosphere (L–A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centered climate anomalies. Local L–A coupling (LoCo) metrics capture relevant L–A processes, highlighting the impact of soil and vegetation states on surface flux partitioning and the impact of surface fluxes on boundary layer (BL) growth and development and the entrainment of air above the BL. A primary goal of the Climate Process Team in the Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) project is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional Earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L–A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land–atmosphere interactions span timescales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability in behavioral regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here, we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyze, and better understand L–A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behavior. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant timescales, (ii) enable demonstration of inter-model spread in L–A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.

New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4

Abstract. The South China Sea throughflow (SCSTF) connects the South China Sea (SCS) with neighboring seas and oceans, transferring surface water of the global thermohaline circulation between the Pacific and Indian oceans. A configuration of the SYMPHONIE ocean model at high resolution (4 km) and including an explicit representation of tides is implemented over this region, and a simulation is analyzed over 2010–2018. Comparisons with in situ and satellite data and other available simulations at coarser resolution show the good performance of the model and the relevance of the high resolution for reproducing the spatial and temporal variability of the characteristics of surface dynamics and water masses over the SCS. The added value of an online computation of each term of the water, heat, and salt SCS budgets (surface, lateral oceanic and river fluxes, and internal variations) is also quantitatively demonstrated: important discards are obtained with offline computation, with relative biases of ∼40 % for lateral oceanic inflows and outflows. The SCS water volume budget, including the SCSTF, is analyzed at climatological and seasonal scales. The SCS receives on average a 4.5 Sv yearly water volume input, mainly from the Luzon Strait. It laterally releases this water to neighboring seas, mainly to the Sulu Sea through Mindoro Strait (49 %), to the East China Sea via Taiwan Strait (28 %), and to the Java Sea through Karimata Strait (22 %). The seasonal variability of this water volume budget is driven by lateral interocean exchanges. Surface interocean exchanges, especially at Luzon Strait, are all driven by monsoon winds that favor winter southwestward flows and summer northeastward surface flows. Exchanges through Luzon Strait deep layers show a stable sandwiched structure with vertically alternating inflows and outflows. Last, differences in flux estimates induced by the use of a high-resolution model vs. a low-resolution model are quantified.

Self‐consistent transport simulation of boron dust particle injection in the peripheral plasma in Large Helical Device

AbstractThe trajectories and the ablation positions of boron dust particles dropped from an impurity powder dropper in the peripheral plasma in the Large Helical Device (LHD) were calculated using a three‐dimensional edge plasma simulation code (EMC3‐EIRENE) and a dust transport simulation code (DUSTT). The simulation shows that the trajectory of the boron dust particles is deflected at the upper divertor leg due to the effect of the hydrogen plasma flow, and the ablation positions of the dust particles in an ergodic layer change toward the outboard side of the torus for higher plasma densities. The effect of the boron ion flow in the divertor leg on the deflection is investigated by coupling the two codes self‐consistently. The simulation predicts that the boron ions in the divertor leg, which are produced by sputtering on the divertor plates, which do not affect the change in the ablation positions. It also shows that the ablation positions move toward the inboard side and approach the Last Closed Flux Surface (LCFS) in case of increased boron dust drop rates, which is caused by the lowered plasma flow in the upper divertor leg due to the lowered electron temperature by radiation cooling by the dropped dust particles.

Multi-decadal pacemaker simulations with an intermediate-complexity climate model

Abstract. In this paper, we first describe the main features of a new version of the International Centre for Theoretical Physics global atmospheric model (SPEEDY) with improved simulation of surface fluxes and the formulation of a three-layer thermodynamic ocean model (TOM3) suitable to explore the coupled extratropical response to tropical ocean variability. Then, we present results on the atmospheric model climatology, highlighting the impact of the modifications introduced in the model code, and show how important features of interdecadal and interannual variability are simulated in a “pacemaker” coupled ensemble of 70-year runs, where portions of the tropical Indo-Pacific are constrained to follow the observed variability. Despite the very basic representation of variations in greenhouse forcing and heat transport to the deep ocean (below the 300 m domain of the TOM3 model), the coupled ensemble reproduces the variations in surface temperature over land and sea with very good accuracy, confirming the role of the Indo-Pacific as a “pacemaker” for the natural fluctuations of global-mean surface temperatures found in earlier studies. Atmospheric zonal-mean temperature trends over 50 years are also realistically simulated in the extratropical lower troposphere and up to 100 hPa in the tropics. On the interannual scale, sea-surface temperature (SST) variability in sub-tropical and tropical regions not affected by SST relaxation is underestimated (mostly because of the absence of dynamically induced variability), while extratropical SST variability during the cold seasons is comparable to that observed. Atmospheric teleconnection patterns and their connections with SST are reproduced with high fidelity, although with local differences in the amplitude of regional features (such as a larger-than-observed response of extratropical SST to North Atlantic Oscillation variability). The SPEEDY-TOM3 model also reproduces the observed connection between averages of surface heat fluxes over the oceans and land surface air temperature in the wintertime northern extratropics. Overall, as in earlier versions of SPEEDY, the fidelity of the simulations (both in terms of climatological means and variability) is higher near the surface and in the lower troposphere, while the negative impacts of the coarse vertical resolution and simplified parameterizations are mostly felt in the stratosphere. However, the improved simulation of surface heat fluxes and their impact on extratropical SST variability in this model version (obtained at a very modest computational cost) make the SPEEDY-TOM3 model a suitable tool to investigate the coupled response of the extratropical circulation to interannual and inter-decadal changes of tropical SST in ensemble experiments.

Distinctive approach for MHD natural bioconvection flow of Reiner–Rivlin nano-liquid due to an isothermal sphere

The analysis of heat excess through non-Newtonian fluid is noticed proper and promising arena for biomedical technological applications than Newtonian liquid. Herein, a type of non-Newtonian (Reiner–Rivlin) nanomaterial has been scrutinized with gyrotactic microorganisms around an isothermal sphere with surface of zero mass flux. Being mindful of that the model of Buongiorno’s nanofluid is utilized. Non-dimensional formulas for the basic dimensional partial differential equation system are obtained using appropriate non-similarity transformations. MATLAB function bvp4c code is adopted to get the non-similar solutions. The computations disclosed that the velocity of Reiner–Rivlin nanofluid and its gradient accelerate away from the surface of sphere to infinity and reduces in proximity to the sphere surface for higher values of Reiner–Rivlin factor K. The rate of surface density transport, rate of surface heat transport, and gradient of velocity diminish as the stream wise coordinate boosts. As the problem is subjected to special circumstances, there is a remarkable agreement between the acquired and prior numerical calculations resulting from the comparison.

Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3

Abstract. We describe the development of the tangent linear (TL) and adjoint models of the Model for Prediction Across Scales (MPAS)-CO2 transport model, which is a global online chemical transport model developed upon the non-hydrostatic Model for Prediction Across Scales – Atmosphere (MPAS-A). The primary goal is to make the model system a valuable research tool for investigating atmospheric carbon transport and inverse modeling. First, we develop the TL code, encompassing all CO2 transport processes within the MPAS-CO2 forward model. Then, we construct the adjoint model using a combined strategy involving re-calculation and storage of the essential meteorological variables needed for CO2 transport. This strategy allows the adjoint model to undertake a long-period integration with moderate memory demands. To ensure accuracy, the TL and adjoint models undergo vigorous verifications through a series of standard tests. The adjoint model, through backward-in-time integration, calculates the sensitivity of atmospheric CO2 observations to surface CO2 fluxes and the initial atmospheric CO2 mixing ratio. To demonstrate the utility of the newly developed adjoint model, we conduct simulations for two types of atmospheric CO2 observations, namely the tower-based in situ CO2 mixing ratio and satellite-derived column-averaged CO2 mixing ratio (XCO2). A comparison between the sensitivity to surface flux calculated by the MPAS-CO2 adjoint model with its counterpart from CarbonTracker–Lagrange (CT-L) reveals a spatial agreement but notable magnitude differences. These differences, particularly evident for XCO2, might be attributed to the two model systems' differences in the simulation configuration, spatial resolution, and treatment of vertical mixing processes. Moreover, this comparison highlights the substantial loss of information in the atmospheric CO2 observations due to CT-L's spatial domain limitation. Furthermore, the adjoint sensitivity analysis demonstrates that the sensitivities to both surface flux and initial CO2 conditions spread out throughout the entire Northern Hemisphere within a month. MPAS-CO2 forward, TL, and adjoint models stand out for their calculation efficiency and variable-resolution capability, making them competitive in computational cost. In conclusion, the successful development of the MPAS-CO2 TL and adjoint models, and their integration into the MPAS-CO2 system, establish the possibility of using MPAS's unique features in atmospheric CO2 transport sensitivity studies and in inverse modeling with advanced methods such as variational data assimilation.

A quality-assured dataset of nine radiation components observed at the Shangdianzi regional GAW station in China (2013–2022)

Abstract. The New Baseline Surface Radiation (NBSR) system was established at the Shangdianzi (SDZ) regional Global Atmosphere Watch (GAW) station in 2013 to observe nine broadband radiation components, i.e. the global, direct, diffuse, and upwelling shortwave irradiance (GSWI, DSWI, DifSWI, and UpSWI); the photosynthetically active radiation (PAR); the ultraviolet irradiance (UVAI and UVBI); and the down- and upwelling longwave irradiance (DnLWI and UpLWI). To test the 1 min raw radiometric data, a Hybrid Algorithm for Radiation Data Quality Control (HARDQC) is presented in this study based on well-established methods, together with the solar irradiance dataset and the spectral features of the instrument bands. Subsequently, a NBSR dataset, which consists of radiation data at multiple timescales (i.e. 1 min, hourly, daily, monthly, monthly average hourly, and monthly average daily) over 2013–2022, is established and evaluated. Results show that more than 98.7 % of all radiation components passed the physical possibility test. The percentages of those that passed the extremely rare test are greater than 98.6 % for all radiation components except for the DnLWI (97.1 %). The percentages of those that passed the comparison test are greater than 83.3 % (GSWI), 78.3 % (DSWI), 81.7 % (DifSWI), 93.1 % (UpSWI), 88.9 % (PAR), 95.6 % (UVAI), 96.3 % (UVBI), 99.8 % (DnLWI), and 99.7 % (UpLWI), respectively. Due to data logger faults, removal of the instruments for calibration, and lightning strikes, some apparent data gaps in the upwelling radiation components (January 2015–August 2017) and all radiation components (December 2018; July to September 2021) were detected. Despite the existence of a few imperfections in the NBSR dataset, it is still reliable to apply it in many fields such as the validation of satellite products and numerical models, the investigation of relationships between radiation and atmospheric composition, and the detection of changes in the surface fluxes. The dataset described in this paper is available at https://doi.org/10.1594/PANGAEA.963330 (Quan et al., 2023b).

Mixed Convection in an Idealized Coastal Urban Environment With Momentum and Thermal Surface Heterogeneities

AbstractCoastal marine heatwaves (MHWs) modulate coastal climate through ocean‐land‐atmosphere interactions, but little is known about how coastal MHWs interact with coastal cities and modify urban thermal environment. In this study, a representative urban coastal environment under MHWs is simplified to a mixed convection problem. Fourteen large‐eddy simulations (LESs) are conducted to investigate how coastal cities interact with MHWs. We consider the simulations by simple urban roughness setup (Set A) as well as explicit urban roughness representation (Set B). Besides, different MHW intensities, synoptic wind speeds, surface fluxes of urban and sea patches are considered. Results suggest that increasing MHW intensity alters streamwise potential temperature gradient and vertical velocity direction. The magnitude of vertical velocity and urban heat island (UHI) intensity decrease with increasing synoptic wind speed. Changing urban or sea surface heat flux also leads to important differences in flow and temperature fields. Comparison between Set A and B reveals a significant increase of vertical velocity magnitude and UHI intensity. To further understand this phenomenon, a canopy layer UHI model is proposed to show the relationship between UHI intensity and urban canopy, thermal heterogeneity and mean advection. The effect of urban canopy is considered in terms of an additional vertical velocity scale that facilitates heat transport from the heated surface and therefore increases UHI intensity. The model can well explain the trend of the simulated results and implies that overlooking the effect of urban canopy underestimates canopy UHI in urban coastal environment.

Appraisal of Visible/IR and microwave datasets for land surface fluxes estimation using machine learning techniques

Land surface fluxes such as Soil Moisture (SM) and Soil Temperature (ST) are very important variables for many applications that includes agriculture water management, weather and climate prediction, natural disasters etc. Further, they are important for understanding soil processes, hydrological balances as well as changes in microbial population. Mapping of the soil moisture content at various depth is crucial for the sustenance of water resources and also to understand about the development of crops in forms of quality and yield. With changing environmental conditions, there is a need of approaches for estimating SM and ST in various climatic and geographic situations. Towards this, Earth Observation datasets at higher resolutions from satellites such as Sentinel 1 and 2, could play an important role in the monitoring of SM and ST over the larger areas. For estimation of SM and ST, machine learning approaches could be effective. This research looked into the possibilities of using Earth Observation (EO) data of Sentinel-1 (S1) and Sentinel-2 (S2) simultaneously to estimate SM and ST by using the machine learning methods such as random forest (RF) and Support Vector Machines (SVM). The coefficient of correlation (r), root mean square error (RMSE), and Bias are utilized in model enactment for accuracy and comparative analysis of the models used. The overall analysis indicates that the SVM model (r = 0.85, RMSE = 2.54, Bias = −0.05) is the second most appropriate after the RF model (r = 0.89, RMSE = 2.34, Bias = 0) for estimating land surface fluxes (SM and ST).

Effect of hyper-resistivity on ballooning modes with resonant magnetic perturbations

The impact of hyper-resistivity on non-ideal ballooning modes (BMs) is studied in the presence of resonant magnetic perturbation (RMP) through considering the hyper-resistivity, resistivity and diamagnetic effect in the BM model with an equilibrium distorted by RMP, which is stable for ideal BMs. Similar to the resistivity, the hyper-resistivity is also destabilizing for the BMs, but RMPs make the mode spectrum of the BMs destabilized by the hyper-resistivity move towards the low toroidal mode number side on the flux surface with a safety factor slightly larger than the RMP resonance safety factor, where the growth rates of the BMs destabilized by the resistivity decrease due to RMP. When both the hyper-resistivity and the resistivity are considered, there is a sort of competitive relationship between them in determining the properties of BMs. If either of the hyper-resistivity term and the resistivity term is much larger than the other one, the instability of BMs is mainly determined by the larger one, and the effect of the smaller one is masked. The destabilizing mechanisms of the hyper-resistivity and the resistivity on BMs are similar, namely, the diffusion and dissipation of current and magnetic field weaken the stabilizing effect of magnetic field line bending. The research results may be important for understanding the enhancement of plasma transport and the mechanism of small edge localized mode (ELM) during ELM control with RMP.

Interannual Variability in the Onset Time Distribution of the Open Water in the Kara Sea

Abstract Open water in ice-covered oceans is an essential condition for shipping and resource exploitation. We investigate the interannual and spatial variations of the open water onset time in the Kara Sea (KS) and the underlying mechanisms through analyzing satellite-based observations and model simulation results. The empirical orthogonal function (EOF) analysis on the satellite sea ice concentration during 1979–2020 reveals two primary spatial distribution patterns of the open water onset time. The first mode EOF1 shows the coherent advance or delay of the open water onset time within the KS, which is consistent with the multiyear-averaged state. The second mode EOF2 exhibits a seesaw pattern between the southwest and middle regions, which represents the regional difference of the open water onset time within the KS. In 1997 with significant anomaly in EOF2, analysis of the model simulation reveals that the strong easterly wind-induced ice transport is the main reason for the earlier opening in the middle region and delayed opening in the southwestern region. When compared with the multiyear-averaged state, this dynamic process causes a noticeable redistribution of local sea ice in the early melting season (May to June), with much more ice in the southwestern region, thence influences the regional onset time of open water. A similar situation also occurred in the years 1985, 2001, and 2004, as these years presented stronger easterly wind energy accumulated over May to June, which cause earlier opening in the middle region and later opening in the southwestern region. Significance Statement Variability of the open water in the Arctic Ocean has a significant impact on climate and ecosystem variability and also human activities. This study focuses on understanding why the onset time of open water was asynchronous over the Kara Sea. Generally, the open water first forms in the western region of the Kara Sea under the influences of warm inflow from the Barents Sea and river runoff. However, when strong easterly winds prevail across the whole region at the beginning of the melting season, sea ice is transported from east to west, resulting in the advanced opening in the middle and delayed opening in the southwest regions. This finding points out that wind can combine with surface and lateral heat fluxes to influence the interannual variability in the distribution of the open water onset time in the Kara Sea.

Retrieval of Surface Energy Fluxes Considering Vegetation Changes and Aerosol Effects

The exchange of moisture and energy between the land and the atmosphere plays a crucial role in terrestrial hydrological cycle and climate change. However, existing studies on the retrieval of surface water and heat flux tend to overlook the dynamic changes in surface vegetation and atmospheric aerosols, which directly affect surface energy and indirectly alter various meteorological factors, including cloud, precipitation, and temperature. In this study, we assess the machine-learning retrieval method for surface fluxes that takes into account vegetation changes and aerosol effects, using FLUXNET observations and remote sensing data to retrieve latent heat flux (LE) and sensible heat flux (H). We constructed four sets of deep neural network models: (a) The first set considers only meteorological factors, (b) the second set considers meteorological factors and aerosols, (c) the third set considers meteorological factors and vegetation changes, and (d) the fourth set comprehensively considers meteorological factors, aerosols, and vegetation changes. All model performances were evaluated using statistical indicators. ERA5 reanalysis and remote sensing data were used to drive the models and retrieve daily H and LE. The retrieved results were validated against ground observation sites that were not involved in model training or the FLUXCOM product. The results show that the model that considers meteorological factors, aerosols, and vegetation changes has the smallest errors and highest correlation for retrieving H and LE (RH = 0.85, RMSEH = 24.88; RLE = 0.88, RMSELE = 22.25). The ability of the four models varies under different vegetation types. In terms of seasons, the models that consider meteorological factors and vegetation changes, as well as those that comprehensively consider meteorological factors, aerosols, and vegetation changes, perform well in retrieving the surface fluxes. As for spatial distribution, when atmospheric aerosols are present in the region, the model that considers both meteorological factors and aerosols retrieves higher values of H compared to the model that considers only meteorological factors, while the LE values are relatively lower. The model that considers meteorological factors and vegetation changes, as well as the model that comprehensively considers meteorological factors, aerosols, and vegetation changes, retrieves lower values in most regions. Through the validation of independent observation sites and FLUXCOM products, we found that the model, considering meteorological factors, aerosols, and vegetation changes, was generally more accurate in the retrieval of surface fluxes. This study contributes to improving the retrieval and future prediction accuracy of surface fluxes in a changing environment.

Complete and robust magnetic field confinement by superconductors in fusion magnets

The fusion created by magnetically confined plasma is a promising clean and essentially unlimited future energy source. However, there are important problems hindering controlled fusion like the imperfect magnetic confinement and the associated plasma instabilities. We theoretically demonstrate how to create a fully confined magnetic field with the precise three-dimensional shape required by fusion theory, using a bulk superconducting toroid with a toroidal cavity. The vacuum field in the cavity consists of nested flux surfaces. The coils creating the field, embedded in the superconducting bulk, can be chosen with very simple shapes, in contrast with the cumbersome arrangements in current experiments, and can be spared from large magnetic forces between them. Because of the superconductor properties, the system will tend to maintain the optimum field distribution in response to instabilities in the plasma. We numerically demonstrate how a fully-confined magnetic field with the three-dimensional spatial distribution required in two of the most advanced stellarators, Large Helical Device and Wendelstein 7-X, can be exactly generated, using simple round coils as magnetic sources. Current high-temperature superconductors can be employed to construct the bulk superconducting toroid. This can lead to optimized robust magnetic confinement and largely simplified configurations in future fusion experiments.

An Entropy Stable Discontinuous Galerkin Method for the Two-Layer Shallow Water Equations on Curvilinear Meshes

We present an entropy stable nodal discontinuous Galerkin spectral element method (DGSEM) for the two-layer shallow water equations on two dimensional curvilinear meshes. We mimic the continuous entropy analysis on the semi-discrete level with the DGSEM constructed on Legendre–Gauss–Lobatto (LGL) nodes. The use of LGL nodes endows the collocated nodal DGSEM with the summation-by-parts property that is key in the discrete analysis. The approximation exploits an equivalent flux differencing formulation for the volume contributions, which generate an entropy conservative split-form of the governing equations. A specific combination of a numerical surface flux and discretization of the nonconservative terms is then applied to obtain a high-order path-conservative scheme that is entropy conservative. Furthermore, we find that this combination yields an analogous discretization for the pressure and nonconservative terms such that the numerical method is well-balanced for discontinuous bathymetry on curvilinear domains. Dissipation is added at the interfaces to create an entropy stable approximation that satisfies the second law of thermodynamics in the discrete case, while maintaining the well-balanced property. We conclude with verification of the theoretical findings through numerical tests and demonstrate results about convergence, entropy stability and well-balancedness of the scheme.

Linking Gulf Stream air–sea interactions to the exceptional blocking episode in February 2019: a Lagrangian perspective

Abstract. The development of atmospheric blocks over the North Atlantic–European region can lead to extreme weather events like heat waves or cold air outbreaks. Despite their potential severe impact on surface weather, the correct prediction of blocking lifecycles remains a key challenge in current numerical weather prediction (NWP) models. Increasing evidence suggests that latent heat release in cyclones, the advection of cold air (cold air outbreaks, CAOs) from the Arctic over the North Atlantic, and associated air–sea interactions over the Gulf Stream are key processes contributing to the onset, maintenance, and persistence of such flow regimes. To better understand the mechanism connecting air–sea interactions over the Gulf Stream with changes in the large-scale flow, we focus on an episode between 20 and 27 February 2019, when a quasi-stationary upper-level ridge was established over western Europe accompanied by an intensified storm track in the northwestern North Atlantic. During that time, a record-breaking winter warm spell occurred over western Europe bringing temperatures above 20 ∘C to the United Kingdom, the Netherlands, and northern France. The event was preceded and accompanied by the development of several rapidly intensifying cyclones that originated in the Gulf Stream region and traversed the North Atlantic. To explore the mechanistic linkage between the formation of this block and air–sea interactions over the Gulf Stream, we adopt a Lagrangian perspective, using kinematic trajectories. This allows us to study the pathways and transformations of air masses that form the upper-level potential vorticity anomaly and interact with the ocean front. We establish that more than one-fifth of these air masses interact with the Gulf Stream in the lower troposphere, experiencing intense heating and moistening over the region due to the frequent occurrence of CAOs behind the cold front of the cyclones. Trajectories moistened by the advection of cold air over a warm ocean by one cyclone later ascend into the upper troposphere with the ascending airstream of a subsequent cyclone, fueled by the strong surface fluxes. These findings highlight the importance of CAOs in the Gulf Stream region, indicating that their intense coupling between the ocean and atmosphere plays a role in block development. Additionally, they provide a mechanistic pathway linking air–sea interactions in the lower troposphere and the upper-level flow.

Quantifying the Contribution of Ocean Advection and Surface Flux to the Upper‐Ocean Salinity Variability Resolved by Climate Model Simulations

AbstractThis study examines the impact of ocean advection and surface freshwater flux on the non‐seasonal, upper‐ocean salinity variability in two climate model simulations with eddy‐resolving and eddy‐parameterized ocean components (HR and LR, respectively). We assess the realism of each simulation by comparing their sea surface salinity (SSS) variance with satellite and Argo float estimates. In the extratropics, the HR variance is about five times larger than that in LR and agrees with Argo. In turn, the extratropical satellite SSS variance is smaller than that from HR and Argo by about a factor of two, potentially caused by the insufficient resolution of radiometers to capture mesoscale features and their low sensitivity to SSS in cold waters. Using a simplified salinity conservation equation for the upper‐50‐m ocean, we find that the advection‐driven variance in HR is, on average, 10 times larger than the surface flux‐driven variance, reflecting the action of mesoscale processes.

Oceanic Frontal Turbulence

Abstract Upper-ocean turbulence results from a complex set of interactions between submesoscale turbulence and local boundary layer processes. The interaction between larger-scale currents and turbulent fluctuations is two-way: large-scale shearing motions generate turbulence, and the resulting coherent turbulent fluxes of momentum and buoyancy feed back onto the larger flow. Here we examine the evolution and role of turbulence in the intensification, instability, arrest, and decay (i.e., the life cycle) of a dense filament undergoing frontogenesis in the upper-ocean boundary layer, i.e., cold filament frontogenesis (CFF). This phenomenon is examined in large-eddy simulations (LES) with resolved turbulent motions in large horizontal domains using 109 grid points. The boundary layer turbulence is generated by surface buoyancy loss (cooling flux) and is allowed to freely interact with an initially imposed cold filament, and the evolution is followed through the frontal life cycle. Two control parameters are explored: the initial frontal strength M2 = ∂xb and the surface flux . The former is more consequent: initially weaker fronts sharpen more slowly and become arrested at a later time with a larger width. This reflects a competition between the frontogenetic rate induced by the secondary circulation associated with vertical momentum mixing by the turbulence and the instability rate for the along-filament shear flow. The frontal turbulence is energized by the shear production of the latter, is nonlocally transported away from the primary production zone at the filament centerline, and cascades to dissipation in a broad region surrounding the filament. The turbulent momentum fluxes arresting the frontogenesis are supported across a wide range of horizontal scales.

Nitrous oxide and methane production and consumption at five full-size denitrifying bioreactors treating subsurface drainage water

Nitrate (NO3−) removal in denitrifying bioreactors is influenced by flow, water chemistry, and design, but it is not known how these widely varying factors impact the production of nitrous oxide (N2O) or methane (CH4) across sites. Woodchip bioreactors link the hydrosphere and atmosphere in this respect, so five full-size bioreactors in Illinois, USA, were monitored for NO3−, N2O, and CH4 to better document where this water treatment technology resides along the pollution swapping to climate smart spectrum. Both surface fluxes and dissolved forms of N2O and CH4 were measured (n = 7–11 sampling campaigns per site) at bioreactors ranging from <1 to nearly 5 years old and treating subsurface drainage areas from between 6.9 and 29 ha. Across all sites, N2O surface and dissolved volumetric production rates averaged 1.0 ± 1.6 mg N2O-N/m3-d and 24 ± 62 mg dN2O-N/m3-d, respectively, and CH4 production rates averaged 6.0 ± 26 mg CH4-C/m3-d and 310 ± 520 mg dCH4-C/m3-d for surface and dissolved, respectively. However, N2O was consistently consumed at one bioreactor, and only three of the five sites produced notable CH4. Surface fluxes of CH4 were significantly reduced by the presence of a soil cover. Bioreactor denitrification was relatively efficient, with only 0.51 ± 3.5 % of removed nitrate emitted as N2O (n = 48). Modeled indirect N2O emissions factors were significantly lower when a bioreactor was present versus absent (EF5: 0.0055 versus 0.0062 kg N2O-N/kg NO3-N; p = 0.0011). While further greenhouse gas research on bioreactors is recommended, this should not be used as an excuse to slow adoption efforts. Bioreactors provide a practical option for voluntary water quality improvement in the heavily tile-drained US Midwest and elsewhere.

Comparison of Forecasting Biases Over New York State Mesonet: A Wet Summer Versus a Dry Summer

AbstractExtreme weather events are occurring with increasing frequent due to the climate change. This increasing frequency may introduce more uncertainty in weather forecasting model performance, particularly when considering the intricate relationship of the land surface and atmosphere coupling system. In this study, we utilize data from the sophisticated New York State Mesonet to evaluate the performance of a forecasting system based on WRF Version 4 model, drawing insights from both dry and wet summers. Additionally, the model's performance is assessed on two land surface types: forest and farmland, to provide a comprehensive evaluation of impact of land surface heterogeneity. The surface meteorology, fluxes, and cloud development are assessed. The coupling between surface and atmosphere is diagnosed using a mixing diagram which serves to represent surface thermodynamic properties. The results reveal a systematic increase in warm season dry and warm biases, especially for forested sites during a drought year. The model exhibits heightened sensitivity to drought conditions, resulting in a substantial underestimation of latent heat fluxes during such period. During days with boundary layer clouds, the mixing diagram shows a notably slower growth of moist static energy in the model compared to observation. It is possible that these biases partly attribute to the underestimation of cloud optical depth due to not enough energy for the cloud development.

Analysis of Radon Near-Surface Measurements, Using Co-Located Ozone Data, Radio-Sounding Vertical Profiles, Sensible Heat Flux and Back-Trajectory Calculation

Simultaneous and co-located observations of near-surface Radon-222, ozone and meteorological parameters in a central Italy observation site operated by the University of L’Aquila (Italy), are used to study the physical drivers of the radon abundance during night-time hours. The knowledge of the potential temperature vertical gradient in the surface layer of nocturnal thermal inversion is made possible using co-located radio-sounding vertical profiles of pressure and temperature, thus making possible to indirectly infer the local surface flux of atmospheric radon (16 ± 6 mBq m−2 s−1). The dynamical removal due to turbulent convective motions is found to be the dominant controlling process, determining large differences in the near-surface radon abundance between stable and unstable conditions of the nocturnal Planetary Boundary Layer (PBL). Usual unstable PBL conditions during daytime hours induce an effective dynamical vertical dilution of surface radon, which rapidly reaches a quasi-steady-state abundance during mid-day and afternoon hours, with very low concentration values (5.1 ± 2.0 Bq m−3). Using back-trajectory reanalyses, estimates of local radon fluxes and vertical mixing efficiencies inside the PBL along the air mass latitudinal-longitudinal path and finally the irreversible radon loss due to radioactive decay, we have explored the fraction of daytime radon attributable to long-range advection in the continental near-mountain measurement site of L’Aquila (44 ± 18%).