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This paper presents a fractional approach to study the mathematical model of tsunami wave propagation along a coastline of an ocean. Fractional Reduced Differential Transform Method (FRDTM) is used to analyze this model. The present model has been studied on the shallow-water assumption. It is represented by a time-fractional coupled system of non-linear partial differential equations. Solutions to the proposed model for different coastal slopes and ocean depths have been obtained. Effects of coast slope and sea depth variations on tsunami wave velocity and wave amplification have been demonstrated at different time levels and different orders α . The obtained results are compared with Elzaki Adomian Decomposition Method (EADM) to validate the proposed method for an order α = 1 .

Generating accurate weather forecasts of planetary boundary layer (PBL) properties is challenging in many geographical regions, oftentimes due to complex topography or horizontal variability in, for example, land characteristics. While recent advances in high-performance computing platforms have led to an increase in the spatial resolution of numerical weather prediction (NWP) models, the horizontal gridcell spacing (Δx) of many regional-scale NWP models currently fall within or are beginning to approach the gray zone (i.e., Δx ≈ 100–1000 m). At these gridcell spacings, three-dimensional (3D) effects are important, as the most energetic turbulent eddies are neither fully parameterized (as in traditional mesoscale simulations) nor fully resolved [as in traditional large-eddy simulations (LES)]. In light of this modeling challenge, we have implemented a 3D PBL parameterization for high-resolution mesoscale simulations using the Weather Research and Forecasting Model. The PBL scheme, which is based on the algebraic model developed by Mellor and Yamada, accounts for the 3D effects of turbulence by calculating explicitly the momentum, heat, and moisture flux divergences in addition to the turbulent kinetic energy. In this study, we present results from idealized simulations in the gray zone that illustrate the benefit of using a fully consistent turbulence closure framework under convective conditions. While the 3D PBL scheme reproduces the evolution of convective features more appropriately than the traditional 1D PBL scheme, we highlight the need to improve the turbulent length scale formulation. Significance Statement The spatial resolution of weather models continues to increase at a rapid rate in accordance with the enhancement of computing power. As a result, smaller-scale atmospheric features become more explicitly resolved. However, most numerical models still ignore the impact of horizontal weather variations on boundary layer flows, which becomes more important at these smaller spatial scales. To address this issue, we have implemented a new modeling approach, using fundamental principles, which accounts for horizontal variability. Our results show that including three-dimensional effects of turbulence is necessary to achieve realistic boundary layer characteristics. This novel technique may be useful for many applications including complex terrain flows, pollutant dispersion, and surface–atmosphere interaction studies.

The Antarctic Slope Current (ASC) plays a central role in redistributing water masses, sea ice, and tracer properties around the Antarctic margins, and in mediating cross-slope exchanges. While the ASC has historically been understood as a wind-driven circulation, recent studies have highlighted important momentum transfers due to mesoscale eddies and tidal flows. Furthermore, momentum input due to wind stress is transferred through sea ice to the ASC during most of the year, yet previous studies have typically considered the circulations of the ocean and sea ice independently. Thus, it remains unclear how the momentum input from the winds is mediated by sea ice, tidal forcing, and transient eddies in the ocean, and how the resulting momentum transfers serve to structure the ASC. In this study the dynamics of the coupled ocean–sea ice–ASC circulation are investigated using high-resolution process-oriented simulations and interpreted with the aid of a reduced-order model. In almost all simulations considered here, sea ice redistributes almost 100% of the wind stress away from the continental slope, resulting in approximately identical sea ice and ocean surface flows in the core of the ASC in a fully spun-up equilibrium state. This ice–ocean coupling results from suppression of vertical momentum transfer by mesoscale eddies over the continental slope, which allows the sea ice to accelerate the ocean surface flow until the speeds coincide. Tidal acceleration of the along-slope flow exaggerates this effect and may even result in ocean-to-ice momentum transfer. The implications of these findings for along- and across-slope transport of water masses and sea ice around Antarctica are discussed.

Due to global warming, the decline in the Arctic sea ice has been accelerating over the last four decades, with a rate that was not anticipated by climate models. To improve these models, there is the need to rely on comprehensive field data. Seismic methods are known for their potential to estimate sea-ice thickness and mechanical properties with very good accuracy. However, with the hostile environment and logistical difficulties imposed by the polar regions, seismic studies have remained rare. Due to the rapid technological and methodological progress of the last decade, there has been a recent reconsideration of such approaches. This paper introduces a methodological approach for passive monitoring of both sea-ice thickness and mechanical properties. To demonstrate this concept, we use data from a seismic experiment where an array of 247 geophones was deployed on sea ice in a fjord at Svalbard, between March 1 and 24, 2019. From the continuous recording of the ambient seismic field, the empirical Green's function of the seismic waves guided in the ice layer was recovered via the so-called 'noise correlation function'. Using specific array processing, the multi-modal dispersion curves of the ice layer were calculated from the noise correlation function, and then inverted for the thickness and elastic properties of the sea ice via Bayesian inference. The evolution of sea-ice properties was monitored for 24 days, and values are consistent with the literature, as well as with measurements made directly in the field.

The mechanisms that amplify orbitally-driven changes in insolation and drive the glacial cycles of the past 2.6 million years, the Pleistocene, are poorly understood. Previous studies indicate that cloud-phase feedbacks oppose ice sheet initiation when orbital configuration supports ice sheet growth. Cloud phase was observationally constrained in a recent study and provides evidence for a weaker negative cloud feedback in response to carbon dioxide doubling. We observationally constrain cloud phase in the Community Earth System Model and explore how changes in orbital configuration impact the climate response. Constraining cloud phase weakens the negative high latitude cloud phase feedback and unmasks positive water vapor and cloud feedbacks (amount and optical depth) that extend cooling to lower latitudes. Snowfall accumulation and ablation metrics also support ice sheet expansion as seen in proxy records. This indicates that well-known cloud and water vapor feedbacks are the mechanisms amplifying orbital climate forcing.

International audience; In-flight ice accretion under parametric uncertainty is investigated. Three test cases are presented which reproduce experiments carried out at the NASA's Glenn Icing Research Tunnel (IRT) facility. A preliminary accuracy assessment, achieved comparing numerical predictions against experimental observations, confirm the robustness and the predictiveness of the computerized icing model. Besides, sensitivity analyses highlight the variance of the targeted outputs with respect to the different uncertain inputs. In rime icing conditions, a predominant role is played by the uncertainty affecting the airfoil angle of attack, the cloud liquid water content and the droplets’ mean volume diameter. In glaze icing condition, the sensitivity analysis shows instead that the output variability is due mainly to the ambient temperature uncertainty. Results expose a major criticality of standard uncertainty quantification techniques. The issue is inherent the approximation of the full icing model behavior in domain regions scarcely affected by ice build up. To mitigate the issue, a non-linear regression method is proposed and applied.

The Amery Ice Shelf (AIS), East Antarctica, has a layered structure, due to the presence of both meteoric and marine ice. In this study, the thermal structure of the AIS and its spatial pattern are evaluated and analysed through borehole observations and numerical simulations with Elmer/Ice, a full-Stokes ice sheet/shelf model. In the area with marine ice, a near-isothermal basal layer up to 120 m thick is observed, which closely conforms to the pressure-dependent freezing temperature of seawater. In the area experiencing basal melting, large temperature gradients, up to −0.36 ∘C m−1, are observed at the base. Three-dimensional (3-D) steady-state temperature simulations with four different basal mass balance (BMB) datasets for the AIS reveal a high sensitivity of ice shelf thermal structure to the distribution of BMB. We also construct a one-dimensional (1-D) transient temperature column model to simulate the process of an ice column moving along a flowline with corresponding boundary conditions, which achieves slightly better agreement with borehole observations than the 3-D simulations. Our simulations reveal internal cold ice advected from higher elevations by the AIS's main inlet glaciers, warming downstream along the ice flow, and we suggest the thermal structures dominated by these cold cores may commonly exist among Antarctic ice shelves. For the marine ice, the porous structure of its lower layer and interactions with ocean below determine the local thermal regime and give rise to the near-isothermal phenomenon. The limitations in our simulations identify the need for ice shelf–ocean coupled models with improved thermodynamics and more comprehensive boundary conditions. Given the temperature dependence of ice rheology, the depth-averaged ice stiffness factor B(T′)‾ derived from the most realistic simulated temperature field is presented to quantify the influence of the temperature distribution on ice shelf dynamics. The full 3-D temperature field provides a useful input to future modelling studies.

In order to study the propagation laws of acoustic wave of coal samples from the Upper Permian Xuanwei Formation in the east of Yunnan Province, China, under saturated water and dry conditions, the basic physical parameters, acoustic parameters and anisotropic parameters were obtained through the experiments. Based on FFT and wavelet analysis theory, the spectral characteristics of coal samples under different conditions were studied. The results show that physical parameters of coal samples in different directions have different values, that is, the anisotropy of coal samples is obvious. When the coal samples are saturated with water, the acoustic velocities and the attenuation coefficient increase, whereas the dominant frequency decreases. The signal amplitude of the frequency domain significantly decreases, that is, the internal structure of coal samples is damaged. The P-wave velocity and S-wave velocity increase with the increase of the confining pressure, whereas the anisotropy parameters decrease with the increase of the confining pressure. Overall, this study provides the basis to understand basic acoustic information and anisotropy characteristics of coal samples.

In view of the classical Lucas-Washburn equation, which can only describe the spontaneous imbibition of single wetted capillary, a tilted composite capillary model with circular cross section, composed of different wettability capillary wall was established. The model can describe the spontaneous oil-water imbibition of water-wet capillary, oil-wet capillary and mixed wetting capillary. Through numerical solution of the model equation, it is found that the component content of the capillary walls, the capillary radius and the oil-water viscosity ratio have great effects on the spontaneous oil-water imbibition. Effects of capillary inclination angle and inertia force on spontaneous oil-water imbibition are related to the capillary scale. Effects of capillary inclination angle and inertia force can be ignored in small radius capillary, while effects of inclination angle and inertia force can not be ignored in large radius capillary.

A notable number of high-impact weather extremes have occurred in recent years, often associated with persistent, strongly meandering atmospheric circulation patterns known as Rossby waves. Because of the high societal and ecosystem impacts, it is of great interest to be able to accurately project how such extreme events will change with climate change, and to predict these events on seasonal-to-subseasonal (S2S) time scales. There are multiple physical links connecting upper-atmosphere circulation patterns to surface weather extremes, and it is asking a lot of our dynamical models to accurately simulate all of these. Subsequently, our confidence in future projections and S2S forecasts of extreme events connected to Rossby waves remains relatively low. We also lack full fundamental theories for the growth and propagation of Rossby waves on the spatial and temporal scales relevant to extreme events, particularly under strongly nonlinear conditions. By focusing on one of the first links in the chain from upper-atmospheric conditions to surface extremes—the Rossby waveguide—it may be possible to circumvent some model biases in later links. To further our understanding of the nature of waveguides, links to persistent surface weather events and their representation in models, we recommend exploring these links in model hierarchies of increasing complexity, developing fundamental theory, exploiting novel large ensemble datasets, harnessing deep learning, and increased community collaboration. This would help increase understanding and confidence in both S2S predictions of extremes and of projections of the impact of climate change on extreme weather events.

This paper examines the interaction of tropical moisture with an atmospheric river. The analysis of this paper is focused mainly on dropsonde data collected during the fifth day of the Convective Processes Experiment (CPEX). An area of interest is chosen over the central Gulf of Mexico, where the remnant moisture of the tropical system Beatriz penetrated from the Eastern Pacific after making landfall in the western coast of Mexi-co. Results in this study show an eastward-tilting pattern of enhanced mid-level vorticity, coupled with high saturation fraction and low instability index in the predominantly stratiform regime present in the region. An inverse relation between saturation fraction and instability index, as indicated by moisture quasi-equilibrium (MQE), is found in a previously-dominant convective regime. Strong vertical shear signals that the vorticity pattern within this stratiform system is being advected poleward into mid-latitudes. Poleward-moving moisture plumes in narrow channels called atmospheric rivers (ARs) are observed during the mission. We provide insights into vorticity and MQE as conceptual tools to characterize the moisture mechanism of atmospheric rivers near the tropics, where the physical processes behind these river-like structures are less well-understood.

The Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO) are fundamental modes of variability in the tropical atmosphere on the intraseasonal time scale. A linear model, using a moist shallow water equation set on an equatorial beta plane, is developed to provide a unified treatment of the two modes and to understand their growth and propagation over the Indian Ocean. Moisture is assumed to increase linearly with longitude and to decrease quadratically with latitude. Solutions are obtained through linear stability analysis, considering the gravest (n = 1) meridional mode with nonzero meridional velocity. Anomalies in zonal moisture advection and surface fluxes are both proportional to those in zonal wind, but of opposite sign. With observation-based estimates for both effects, the zonal advection dominates, and drives the planetary-scale instability. With a sufficiently small meridional moisture gradient, the horizontal structure exhibits oscillations with latitude and a northwest–southeast horizontal tilt in the Northern Hemisphere, qualitatively resembling the observed BSISO. As the meridional moisture gradient increases, the horizontal tilt decreases and the spatial pattern transforms toward the “swallowtail” structure associated with the MJO, with cyclonic gyres in both hemispheres straddling the equatorial precipitation maximum. These results suggest that the magnitude of the meridional moisture gradient shapes the horizontal structures, leading to the transformation from the BSISO-like tilted horizontal structure to the MJO-like neutral wave structure as the meridional moisture gradient changes with the seasons. The existence and behavior of these intraseasonal modes can be understood as a consequence of phase speed matching between the equatorial mode with zero meridional velocity (analogous to the dry Kelvin wave) and a local off-equatorial component that is characterized by considering an otherwise similar system on an f plane.

We investigate the error scaling and computational cost of wall-modeled large-eddy simulation (WMLES) for external aerodynamic applications. The NASA Juncture Flow is used as representative of an aircraft with trailing-edge smooth-body separation. Two gridding strategies are examined: i) constant-size grid, in which the near-wall grid size has a constant value and ii) boundary-layer-conforming grid (BL-conforming grid), in which the grid size varies to accommodate the growth of the boundary-layer thickness. Our results are accompanied by a theoretical analysis of the cost and expected error scaling for the mean pressure coefficient ($C_p$) and mean velocity profiles. The prediction of $C_p$ is within less than $5\%$ error for all the grids studied, even when the boundary layers are marginally resolved. The high accuracy in the prediction of $C_p$ is attributed to the outer-layer nature of the mean pressure in attached flows. The errors in the predicted mean velocity profiles exhibit a large variability depending on the location considered, namely, fuselage, wing-body juncture, or separated trailing-edge. WMLES performs as expected in regions where the flow resembles a zero-pressure-gradient turbulent boundary layer such as the fuselage ($, arXiv admin note: text overlap with arXiv:2101.00331

The improved and updated Coupled Arctic Prediction System (CAPS) is evaluated using a set of Pan-Arctic prediction experiments for the year 2018. CAPS is built on the Weather Research and Forecasting model (WRF), the Regional Ocean Modeling System (ROMS), the Community Ice CodE (CICE), and a data assimilation based on the local error subspace transform Kalman filter. We analyze physical processes linking improved and changed physical parameterizations in WRF, ROMS, and CICE to changes in the simulated Arctic sea ice state. Our results show that the improved convection and boundary layer schemes in WRF result in an improved simulation of downward radiative fluxes and near-surface air temperature, which influences the predicted ice thickness. The changed tracer advection and vertical mixing schemes in ROMS reduce the bias in sea surface temperature and change ocean temperature and salinity structure in the surface layer, leading to improved evolution of the predicted ice extent (particularly correcting the late ice recovery issue in the previous CAPS). The improved sea ice thermodynamics in CICE have noticeable influences on the predicted ice thickness. The updated CAPS can better predict the evolution of Arctic sea ice during the melting season compared with its predecessor, though the prediction still has some biases at the regional scale. We further show that the updated CAPS can remain skillful beyond the melting season, which may have a potential value for stakeholders to make decisions for socioeconomic activities in the Arctic.

The violent fluid motion in a partially filled vessel is called sloshing. Resonance occurs when the natural frequency of the fluid oscillation approaches that of its container. This result may lead to structural failure. In this study, a Smoothed Particle Hydrodynamics (SPH) model is established to investigate the sloshing motion in a shallow water reservoir. Sloshing in a submerged obstacle, cylinder array, rectangular and wall-inclined topography is considered. In terms of results, the cylinder array is more effective than the other models to reduce the impact force due to the sloshing wave in a rectangular tank. The results prove that the proposed SPH model is capable of simulating sloshing in the shallow water tank.

Free-drift estimates of sea ice motion are necessary to produce a seamless observational record combining buoy and satellite-derived sea ice motion vectors. We develop a new parameterization for the free drift of sea ice based on wind forcing, wind turning angle, sea ice state variables (thickness and concentration), and estimates of the ocean currents. Given the fact that the spatial distribution of the wind–ice–ocean transfer coefficient has a similar structure to that of the spatial distribution of sea ice thickness, we take the standard free-drift equation and introduce a wind–ice–ocean transfer coefficient that scales linearly with ice thickness. Results show a mean bias error of −0.5 cm s−1 (low-speed bias) and a root-mean-square error of 5.1 cm s−1, considering daily buoy drift data as truth. This represents a 35 % reduction of the error on drift speed compared to the free-drift estimates used in the Polar Pathfinder dataset (Tschudi et al., 2019b). The thickness-dependent transfer coefficient provides an improved seasonality and long-term trend of the sea ice drift speed, with a minimum (maximum) drift speed in May (October), compared to July (January) for the constant transfer coefficient parameterizations which simply follow the peak in mean surface wind stresses. Over the 1979–2019 period, the trend in sea ice drift in this new model is +0.45 cm s−1 per decade compared with +0.39 cm s−1 per decade from the buoy observations, whereas there is essentially no trend in a free-drift parameterization with a constant transfer coefficient (−0.09 cm s−1 per decade) or the Polar Pathfinder free-drift input data (−0.01 cm s−1 per decade). The optimal wind turning angle obtained from a least-squares fitting is 25∘, resulting in a mean error and a root-mean-square error of +3 and 42∘ on the direction of the drift, respectively. The ocean current estimates obtained from the minimization procedure resolve key large-scale features such as the Beaufort Gyre and Transpolar Drift Stream and are in good agreement with ocean state estimates from the ECCO, GLORYS, and PIOMAS ice–ocean reanalyses, as well as geostrophic currents from dynamical ocean topography, with a root-mean-square difference of 2.4, 2.9, 2.6, and 3.8 cm s−1, respectively. Finally, a repeat of the analysis on two sub-sections of the time series (pre- and post-2000) clearly shows the acceleration of the Beaufort Gyre (particularly along the Alaskan coastline) and an expansion of the gyre in the post-2000s, concurrent with a thinning of the sea ice cover and the observed acceleration of the ice drift speed and ocean currents. This new dataset is publicly available for complementing merged observation-based sea ice drift datasets that include satellite and buoy drift records.

Lightning is frequently initiated within the convective regions of thunderstorms, and so flash rates tend to follow trends in updraft speed and volume. It has been suggested that lightning production is linked to the turbulent flow generated by updrafts as turbulent eddies organize charged hydrometeors into complex charge structures. These complex charge structures consist of local regions of increased charge magnitudes between which flash-initiating electric fields may be generated. How turbulent kinematics influences lightning production, however, remains unclear. In this study, lightning flashes produced in a multicell and two supercell storms simulated using The Collaborative Model for Multiscale Atmospheric Simulation (COMMAS) were examined to identify the kinematic flow structures within which they occurred. By relating the structures of updrafts to thermals, initiated lightning flashes were expected to be located where the rate of strain and rotational flow are equal, or between updraft and eddy flow features. Results showed that the average lightning flash is initiated in kinematic flow structures dominated by vortical flow patterns, similar to those of thermals, and the structures’ kinematics are characterized by horizontal vorticity and vertical shearing. These kinematic features were common across all cases and demonstrated that where flash-initiating electric fields are generated is along the periphery of updrafts where turbulent eddies are produced. Careful consideration of flow structures near initiated flashes is consistent with those of thermals rising through a storm.

Climate model emulators have a crucial role in assessing warming levels of many emission scenarios from probabilistic climate projections, based on new insights into Earth system response to CO2 and other forcing factors. This article describes one such tool, MCE, from model formulation to application examples associated with a recent model intercomparison study. The MCE is based on impulse response functions and parameterized physics of effective radiative forcing and carbon uptake over ocean and land. Perturbed model parameters for probabilistic projections are generated from statistical models and constrained with a Metropolis-Hastings independence sampler. A part of the model parameters associated with CO2-induced warming have a covariance structure, as diagnosed from complex climate models of the Coupled Model Intercomparison Project (CMIP). Although perturbed ensembles can cover the diversity of CMIP models effectively, they need to be constrained toward substantially lower climate sensitivity for the resulting historical warming to agree with the observed trends over recent decades. The model's simplicity and resulting successful calibration imply that a method with less complicated structures and fewer control parameters offers advantages when building reasonable perturbed ensembles in a transparent way. Experimental results for future scenarios show distinct differences between CMIP- and observation-consistent ensembles, suggesting that perturbed ensembles for scenario assessment need to be properly constrained with new insights into forced response over historical periods.

Ionospheric F-region irregularities can acutely affect navigation and communication systems. To develop predictive capabilities on their occurrence, it is key to understand their variabilities in a wide range of time scales. Previous studies at low latitudes in South America have been performed mostly in the eastern region. However, there are still few reports on the spread-F over Argentina owing to a lack of ionosonde data. This work presents the analysis of the spread-F (range spread-F and frequency spread-F) and plasma bubble occurrence characteristics near the southern crest of the Equatorial Ionization Anomaly in Argentina (Tucuman, 26.8°S, 65.2°W; magnetic latitude 15.5°S). We used ionosonde and Global Positioning System (GPS) data from November 2014 to December 2019 for different solar and geomagnetic conditions. The data show that spread-F and plasma bubble occurrence rates peak in local summer and are minimum in equinox and winter, respectively. There is a negative correlation between each type of spread-F and solar activity, whereas the opposite happens for plasma bubbles. Geomagnetic activity suppresses the generation of spread-F in equinox and summer and enhances it in winter. Plasma bubble occurrence is higher during disturbed days than during quiet days, but under medium solar activity, summer months register more plasma bubbles in quiet conditions. Range spread-F observed in winter under low solar activity is not associated with plasma bubbles originated at the magnetic equator. These results contribute to the knowledge necessary to improve the prediction of the spatial and temporal distribution of the night-time ionospheric irregularities.

Recent study indicates that the non-instantaneous interaction of convection and circulation is essential for evolution of large-scale convective systems. It is incorporated into cumulus parameterization (CP) by relating cloud-base mass flux of shallow convection to a composite of subcloud moisture convergence in the past 6 h. Three pairs of 19-yr simulations with original and modified CP schemes are conducted in a tropical channel model to verify their ability to reproduce the Madden–Julian oscillation (MJO). More coherent tropical precipitation and improved eastward propagation signal are observed in the simulations with the modified CP schemes based on the non-instantaneous interaction. It is found that enhanced feedback between shallow convection and low-level moisture convergence results in amplified shallow convective heating, and then generates reinforced moisture convergence, which transports more moisture upward. The improved simulations of eastward propagation of the MJO are largely attributed to higher specific humidity below 600 hPa in the free troposphere to the east of maximum rainfall center, which is related to stronger boundary layer moisture convergence forced by shallow convection. Large-scale horizontal advection causes asymmetric moisture tendencies relative to rainfall center (positive to the east and negative to the west) and also gives rise to eastward propagation. The zonal advection, especially the advection of anomalous specific humidity by mean zonal wind, is found to dominate the difference of horizontal advection between each pair of simulations. The results indicate the vital importance of non-instantaneous feedback between shallow convection and moisture convergence for convection organization and the eastward MJO propagation.

Global differences of temperature and buoyancy flux at the ocean surface are responsible for small-scale convection at high latitudes, global overturning, and the top-to-bottom density difference in the oceans. With planetary rotation the convection also contributes to the large-scale horizontal, geostrophic circulation, and it crucially involves a 3D linkage between the geostrophic circulation and vertical overturning. The governing dynamics of such a surface-forced convective flow are fundamentally different from Rayleigh–Bénard convection, and the role of buoyancy forcing in the oceans is poorly understood. Geostrophic balance adds to the constraints on transport in horizontal convection, as illustrated by experiments, theoretical scaling, and turbulence-resolving simulations for closed (mid-latitude) basins and an annulus or reentrant zonal (circumpolar) channel. In these geometries, buoyancy drives either horizontal mid-latitude gyre recirculations or a strong Antarctic Circumpolar Current, respectively, in addition to overturning. At large Rayleigh numbers the release of available potential energy by convection leads to turbulent mixing with a mixing efficiency approaching unity. Turbulence-resolving models are also revealing the relative roles of wind stress and buoyancy when there is mixed forcing, and in future work they need to include the effects of turbulent mixing due to energy input from tides.

Energetic particle precipitation associated with pulsating aurora (PsA) can reach down to lower mesospheric altitudes and deplete ozone. It is well documented that pulsating aurora is a common phenomenon during substorm recovery phases. This indicates that using magnetic indices to model the chemistry induced by PsA electrons could underestimate the energy deposition in the atmosphere. Integrating satellite measurements of precipitating electrons in models is considered to be an alternative way to account for such an underestimation. One way to do this is to test and validate the existing ion chemistry models using integrated measurements from satellite and ground-based observations. By using satellite measurements, an average or typical spectrum of PsA electrons can be constructed and used as an input in models to study the effects of the energetic electrons in the atmosphere. In this study, we compare electron densities from the EISCAT (European Incoherent Scatter scientific radar system) radars with auroral ion chemistry and the energetics model by using pulsating aurora spectra derived from the Polar Operational Environmental Satellite (POES) as an energy input for the model. We found a good agreement between the model and EISCAT electron densities in the region dominated by patchy pulsating aurora. However, the magnitude of the observed electron densities suggests a significant difference in the flux of precipitating electrons for different pulsating aurora types (structures) observed.

Marine X-band radar has been suggested to be capable of monitoring significant wave heights in both offshore and open sea areas. In contrast to studies on offshore radar, significant wave height estimations from coastal radar images, which exhibit complicated radar backscattering features, have received little attention. This study proposes a method for retrieving the significant wave height from coastal areas that are often influenced by nononshore winds. The square root of the signal-to-noise ratio in radar images has been widely applied to estimate the significant wave height. However, nononshore wind cases show a poor correlation between the square root of the signal-to-noise ratio and the in situ significant wave height. In addition, the spectral shapes from radar images in nononshore wind cases are very different from those in onshore wind cases. To improve the significant wave height estimations from coastal radar images, we implement an artificial neural network algorithm. After training and testing the algorithm, we confirm that the estimated significant wave heights are more reliable for both onshore and nononshore wind cases if the square root of the signal-to-noise ratio, power from nearshore radar subimages, and in situ wind components are included in the input layer of the neural network.

Wind stress, wind waves, and turbulence are essential variables and play a critical role in regulating a series of physical and biogeochemical processes in large shallow lakes. However, the parameterization of these variables and simulation of their interactions in large shallow lakes have not been strictly evaluated owing to a lack of field observations of lake hydrodynamic processes. To address this problem, two process-based field observations were conducted to record the development of summer and winter wind-driven currents in Lake Taihu, a large shallow lake in China. Using these observations and numerical experiments, a Wave and Current Coupled Model (WCCM) is developed by rebuilding the wind drag coefficient expression, introducing wave-induced radiation stress, and adopting a simple turbulence scheme to simulate wind-driven currents in Lake Taihu. The results show that the WCCM can accurately simulate the upwelling process driven by wind-driven currents during the field observations. A comparison with a reference model indicates a 42.9 % increase of the WCCM-simulated current speed, which is mainly attributed to the new wind drag coefficient expression. The WCCM-simulated current direction and field are also improved owing to the introduction of wave-induced radiation stress. The use of the simple turbulent scheme in the WCCM improves the efficiency of the upwelling process simulation. The WCCM thus provides a sound basis for simulating shallow lake ecosystems.

Coherent microwave radar, which is a rapidly emerging tool to sense waves, usually utilizes the orbit velocities extracted from either temporal or spatial radar echoes. The distribution of energy in the wavenumber-frequency spectrum is changed by some nonlinear features, and correspondingly, this kind of method always provides a significantly overestimated wave period. To address this problem, a novel inversion algorithm, which utilizes the spatial and temporal returns collected with a recently developed coherent S-band radar, is proposed for retrieving wave parameters. A 2-D Fourier transform is applied to the spatial-temporal matrix of velocities to estimate the wavenumber-frequency spectrum. Then the wavenumber-frequency spectrum is integrated over the wavenumber domain to obtain the 1-D velocity spectrum. And the wave height spectrum is estimated from the 1-D velocity spectrum by the direct transform relationship between the 1-D velocity spectrum and the wave height spectrum. Later, significant wave heights and mean wave periods can be derived by the zeroth and first moments of the wave height spectra, respectively. The algorithm is validated using simulation and real data. An approximately four-day dataset collected with a shore-based coherent S-band radar deployed at Beishuang island during a typhoon period is reanalyzed and used to retrieve significant wave heights and mean wave periods. Comparisons between the measurements of radar and wave buoy are conducted, and radar-derived and buoy-measured wave parameters are in a reasonable agreement with a coherent coefficient over 0.9. The results indicate that the proposed method is effective for wave measurements using coherent S-band radar.

The proliferation of synthetic aperture radar (SAR) imagery, its accessibility in open platforms like Google Earth Engine, and the development of automated classification and geophysical information extraction algorithms have prompted the need for understanding the role of incidence angle (IA) on radar scattering mechanism, backscatter intensity, and classification accuracy. This letter demonstrates the dependence of image texture parameters on SAR IA, using Arctic landfast sea ice samples extracted from C-band frequency Sentinel-1 SAR scenes collected during the winter period. Gray-level cooccurrence matrix (GLCM) derived texture parameters, and occurrence texture parameters, derived from undeformed first-year sea ice and multi-year sea ice, which are dominated by surface and volume scattering mechanisms, respectively, were analyzed. All GLCM texture parameters were found to be dependent on IA, highlighting the need for consideration of angular dependence in texture parameters, particularly in the development of image classification and inversion algorithms utilizing them. Occurrence texture parameters showed negligible influence by IA; however, feature discrimination capability was also lost. Some GLCM parameters had similar angular dependencies for both sea ice types, suggesting that, in some cases, global image normalization approaches for texture may be applied to account for the IA effect.

The initiation of the Madden–Julian oscillation over the Indian Ocean is examined through the use of a moisture budget that applies a version of the weak temperature gradient (WTG) approximation that does not neglect dry adiabatic vertical motions. Examination of this budget in ERA-Interim reveals that horizontal moisture advection and vertical advection by dry adiabatic lifting govern the moistening of the troposphere for both primary and successive MJO initiation events. For both types of initiation events, horizontal moisture advection peaks prior to the maximum moisture tendency, while dry adiabatic lifting peaks after the maximum moisture tendency. Once convection initiates, moisture is maintained by anomalous radiative and adiabatic lifting. The dry adiabatic lifting during successive MJO initiation is attributed to the return of the circumnavigating circulation from a previous MJO event, while in primary events the planetary-scale circulation appears to originate over South America. Examination of the same budget with data from the DYNAMO northern sounding array shows that adiabatic lifting contributes significantly to MJO maintenance, with a contribution that is comparable to that of surface heat fluxes. However, results from the DYNAMO data disagree with those from ERA-Interim over the importance of adiabatic lifting to the moistening of the troposphere prior to the onset of convection. In spite of these differences, the results from the two datasets show that small departures from WTG balance in the form of dry adiabatic motions cannot be neglected when considering MJO convective onset.

This study formulates three-dimensional (3D) residual flow, treating both stationary and transient waves. The zonal and meridional momentum equations contain four terms: the geostrophic wind tendency, Coriolis force for the residual horizontal flow, product of the geostrophic wind and potential vorticity other than the constant planetary vorticity, and friction. The thermodynamic equation contains three terms: the potential temperature tendency, advection of the basic potential temperature by the residual vertical flow, and diabatic heating. The zonal mean of the 3D residual flow equals the time mean of the residual flow of the transformed Eulerian-mean equations. The new residual flow is the sum of that derived by Plumb for transient waves and the quadratic terms of the time-mean fields, which correspond approximately to the Stokes correction due to stationary waves. The 3D residual flow and momentum equations are symmetric in the zonal and meridional directions, in contrast with those formulated by Kinoshita et al., which treat the time-mean zonal-mean zonal wind as the basic wind. The newly derived formulas are applied to the climatology of the 3D structure of the deep branch of the Brewer–Dobson circulation. In the Northern Hemisphere in December–February, the residual flows are directed inward toward the polar vortex strongly over east Siberia, where the downward flow is maximized, and weakly over the Atlantic; meanwhile, they are directed outward from the vortex over North America and Europe. A longitudinal dependence of the poleward flow is also observed in the Southern Hemisphere in June–August.

A new model is presented for multisite statistical downscaling of temperature and precipitation using convolutional conditional neural processes (convCNPs). ConvCNPs are a recently developed class of models that allow deep learning techniques to be applied to off-the-grid spatio-temporal data. This model has a substantial advantage over existing downscaling methods in that the trained model can be used to generate multisite predictions at an arbitrary set of locations, regardless of the availability of training data. The convCNP model is shown to outperform an ensemble of existing downscaling techniques over Europe for both temperature and precipitation taken from the VALUE intercomparison project. The model also outperforms an approach that uses Gaussian processes to interpolate single-site downscaling models at unseen locations. Importantly, substantial improvement is seen in the representation of extreme precipitation events. These results indicate that the convCNP is a robust downscaling model suitable for generating localised projections for use in climate impact studies, and motivates further research into applications of deep learning techniques in statistical downscaling., 26 pages, 12 figures

Simulation results are used to assist algorithm development for extracting the ocean surface significant wave height (SWH) from microwave scattering of satellite broadcast signals from the ocean surface. The analysis shows that the Doppler frequency spectrum width is a reliable parameter for extracting the SWH. The numerical experiments include both deep and shallow water conditions. The correlation between Doppler frequency spectrum width and SWH is robust and applicable to all wind speeds, inverse wave ages, and water depths tested in this study (5-21 m/s, 0.8-2.0, and 3 m-∞ , respectively).

Oils floating on the sea surface can be observed as ``dark'' patches on radar images since the backscattered signals from the contaminated area are reduced in two dominant ways. First, oil slicks could damp short gravity and capillary waves on the sea surface responsible for backscattering energy. Second, the oil-covered sea surface permittivity decreases significantly if the oil film is sufficiently thick or mixed with seawater, i.e., oil emulsion. In this article, the geometry of the oil-covered sea surface is accounted for by the damping of sea waves, which is described by the model of local balance (MLB) combined with the sea wave spectrum. The radar backscattering is predicted by the advanced integral equation method (AIEM) model. The reflection coefficients are calculated based on a layered-medium model to analyze the impact of oil thickness and emulsions on the radar scattering. Numerical simulations demonstrate that: 1) the sensitivity to oil thickness and water content of the oil spills increases when the radar frequency increases; 2) the backscattering signals exhibit a nonlinear behavior with respect to oil thickness; and 3) high wind speed can generally narrow the difference between the radar backscattering from the clean and oil-covered sea surface, while the incidence angle has little effect. Numerical simulations are then compared with the multifrequency synthetic aperture radar observations acquired during the Gulf of Mexico Deepwater Horizon (DWH) oil spill accident and the 2011 Norwegian Clean Seas Association for Operating Companies (NOFO) oil-on-water exercise. Comparison results show that it is possible to estimate the oil thickness at reasonably good accuracy.

The coupled dynamics of turbulent airflow and a spectrum of waves are known to modify air–sea momentum and scalar fluxes. Waves traveling at oblique angles to the wind are common in the open ocean, and their effects may be especially relevant when constraining fluxes in storm and tropical cyclone conditions. In this study, we employ large-eddy simulation for airflow over steep, strongly forced waves following and opposing oblique wind to elucidate its impacts on the wind speed magnitude and direction, drag coefficient, and wave growth/decay rate. We find that oblique wind maintains a signature of airflow separation while introducing a cross-wave component strongly modified by the waves. The directions of mean wind speed and mean wind shear vary significantly with height and are misaligned from the wind stress direction, particularly toward the surface. As the oblique angle increases, the wave form drag remains positive, but the wave impact on the equivalent surface roughness (drag coefficient) rapidly decreases and becomes negative at large angles. Our findings have significant implications for how the sea-state-dependent drag coefficient is parameterized in forecast models. Our results also suggest that wind speed and wind stress measurements performed on a wave-following platform can be strongly contaminated by the platform motion if the instrument is inside the wave boundary layer of dominant waves. Significance Statement Surface waves increase friction at the sea surface and modify how wind forces upper-ocean currents and turbulence. Therefore, it is important to include effects of different wave conditions in weather and climate forecasts. We aim to inform more accurate forecasts by investigating wind blowing over waves propagating in oblique directions using large-eddy simulation. We find that waves traveling at a 45° angle or larger to the wind grow as expected, but do not increase or even decrease the surface friction felt by the wind—a surprising result that has significant implications for how oblique wind-waves are represented as a source of surface friction in forecast models.

Observations of microwave backscatter from shoaling and breaking surface waves acquired with a shore-based, coherent-on-receive X-band marine radar are presented. The radar was located at the dune cliff of a sandy beach with two breaker bars. Waves were approximately shore-normal (inclination < 10°) during the study period. Consistent with other studies, the backscatter intensity from breaking waves is significantly increased (≈10 dB compared to nonbreaking) with Doppler velocities close to the wave phase velocity in shallow water. The strong backscatter from active breakers can cause a significant amount of signal artifacts due to the leakage of pulse energy into adjacent range cells, in particular behind the breaking crests. In the near range, the backscatter from the undisturbed surface and such pulse smearing artifacts appear as distinct peaks inside the Doppler spectra. Thus, the velocity of both sources of scatterering can be retrieved using a dedicated peak separation algorithm. In the far range (r > 500 m), the artifacts dominate the Doppler signal behind breaking wave crests. Therefore, when investigating the spatio-temporal evolution of breaking wave-induced Doppler velocities with marine radar, the analysis should be restricted to the wave crests and the well-illuminated front faces of the waves. The evolution of Doppler spectra tracked along the crest of an exemplary individual breaking wave is extracted during the steepening, active- and post-breaking stage.

Air–sea momentum and scalar fluxes are strongly influenced by the coupling dynamics between turbulent winds and a spectrum of waves. Because direct field observations are difficult, particularly in high winds, many modeling and laboratory studies have aimed to elucidate the impacts of the sea state and other surface wave features on momentum and energy fluxes between wind and waves as well as on the mean wind profile and drag coefficient. Opposing wind is common under transient winds, for example, under tropical cyclones, but few studies have examined its impacts on air–sea fluxes. In this study, we employ a large-eddy simulation for wind blowing over steep sinusoidal waves of varying phase speeds, both following and opposing wind, to investigate impacts on the mean wind profile, drag coefficient, and wave growth/decay rates. The airflow dynamics and impacts rapidly change as the wave age increases for waves following wind. However, there is a rather smooth transition from the slowest waves following wind to the fastest waves opposing wind, with gradual enhancement of a flow perturbation identified by a strong vorticity layer detached from the crest despite the absence of apparent airflow separation. The vorticity layer appears to increase the effective surface roughness and wave form drag (wave attenuation rate) substantially for faster waves opposing wind. Significance Statement Surface waves increase friction at the sea surface and modify how wind forces upper-ocean currents and turbulence. Therefore, it is important to include effects of different wave conditions in weather and climate forecasts. We aim to inform more accurate forecasts by investigating wind blowing over waves propagating in the opposite direction using large-eddy simulation. We find that when waves oppose wind, they decay as expected, but also increase the surface friction much more drastically than when waves follow wind. This finding has important implications for how waves opposing wind are represented as a source of surface friction in forecast models.

A simplified model for the position of the sun at any location on earth is shown to produce fairly accurate results when compared to values calculated in a spreadsheet from the United States National Oceanic and Atmospheric Administration (NOAA). A straightforward derivation of the model is presented, in which all terms and parameters have clear physical meaning. In the first version of the model, the only parameters are the tilt of the earth's axis and the date and time of the nearest northern hemisphere winter solstice. The differences between the elevation and azimuth calculated using the model and the NOAA results are typically a few degrees or less, and it is seen that the primary cause of these differences is the eccentricity of the earth's orbit. A simple correction is then added to the model, in which the only parameters are the earth's orbital eccentricity and the date and time of the perihelion nearest the solstice already in the model. This removes most of the differences between the model and the NOAA results. The model is shown to work in both the northern and southern hemispheres.

In general, although the climate during the Holocene has been warm, nine well-recognized cold events with an average time interval of more than one thousand years have been highlighted. The forcing mechanism of these cold events with millennial-scale cycles is still widely discussed. In the present study, two different Solar System dynamical processes collectively driven by all eight planets were considered together: the solar inertial motion and the combined planetary tidal force acting on the Sun. In this context, an attempt was made to analyze their effects on solar activity and Holocene North Atlantic cold events at the millennial-scale. These two Solar System dynamical processes were proxied by the distance between the Sun and the Solar System barycenter (DS–S) and the intensity of the combined planetary tidal force (IP–S), respectively. Using the ensemble empirical mode decomposition (EEMD) method, time series data of Solar System dynamics proxies (i.e., DS–S, and IP–S), solar activity proxies (i.e., 14C and 10Be), and a proxy of Holocene North Atlantic cold events (i.e., hematite-stained grains) were decomposed into several intrinsic mode functions (IMFs). After extracting IMF components containing millennial-scale cycles, a correlation analysis was performed. As a result, it was found that the solar inertial motion had ~2,300- and ~1,000-year cycles and the combined planetary tidal force had a ~1,500-year cycle, while the solar activity and Holocene North Atlantic cold events proxies had ~2,300-, ~1,500-, and ~1,000-year cycles, respectively. The correlation analysis revealed that the millennial-scale periodic components of the two Solar System dynamics proxies were largely correlated with that of solar activity and Holocene North Atlantic cold events, suggesting that the solar inertial motion and combined planetary tidal force may work together to impact solar activity, and thus the climate in the North Atlantic. Consequently, solar activity was weaker and the North Atlantic temperature was cooler when the Sun was far from the Solar System barycenter and/or the combined planetary tidal force was weakened. This might indicate the involvement of Solar System dynamics on Holocene North Atlantic cold events at the millennial-scale.

Very high-resolution modelling of the northeastern Baltic Proper shows that preferentially elongated along the flow, submesoscale inhomogeneities of hydrodynamic fields or stripes of the order of 10–20 km in length and 1 km in width, are typical for summer season both in surface mixed layer and for interior layers which are not directly exposed to atmospheric forcing. In surface layer, the presence of stripes is supported by the remote sensing imagery and their vertical extension is comparable with the mixed layer depth (approx. 5–8 m). In the interior layers, the vertical extension of stripes is considerably larger (approx. 10–50 m) and their slopes exceed the isopycnal slope. Four competitive mechanisms of formation of the mesoscale striped texture are considered: stirring of large-scale inhomogeneities by the eddy field, the classic, inviscid adiabatic fluid symmetric instability, the McIntyre instability, and the strain-induced frontogenesis. Based on the instability criteria and the growth rates and geometry of the disturbances, the classic symmetric instability and the strain-induced frontogenesis are probably responsible for the formation of submesoscale striped texture in the surface layer, while in the interior layers, the strain-induced frontogenesis and hypothetically the McIntyre instability can be essential. Stirring of large-scale inhomogeneities by the eddy field could be responsible for formation of striped texture in a passive tracer concentration and in temperature and salinity in the presence of thermohaline gradients on isopycnic surfaces (thermoclinicity), but it does not imply formation of stripes in dynamically active tracers, such as vertical vorticity, horizontal gradients of buoyancy, etc.

Ice sheet subsurface temperature is important for understanding glacier dynamics, yet existing methods to obtain the temperature of the ice sheet column are limited to in situ sources at present. The ultrawideband software-defined microwave radiometer (UWBRAD) has been developed to investigate the remote sensing of ice sheet internal temperatures. UWBRAD measures brightness temperature spectra from 0.5 to 2 GHz using 12 subchannels and employs a sophisticated algorithm for detection and mitigation of radio frequency interference (RFI). The instrument was deployed during a flight over northwestern Greenland in September 2017 and acquired the first wideband low-frequency brightness temperature spectra over the ice sheet and coastal regions. The results reveal strong spatial and spectral variations that correlate well with internal ice sheet temperature information. In this article, the section of the flight path ranging from the Camp Century to NEEM to NGRIP boreholes is used for subsurface temperature estimation. A ``partially coherent'' forward model is applied along with a Robin model for the temperature profile and a two-scale model of ice sheet density variations to describe measured brightness temperatures. Using this model, vertical temperature profiles are retrieved along the flight path using a sequential Bayesian estimator; borehole measurements at the three campsites are used to obtain Bayesian priors. The retrieved temperature profiles show reasonable behaviors and demonstrate the potential of ultrawideband microwave radiometry for remotely sensing internal ice sheet temperatures.

In this paper, a scheme of dual-Doppler radar wind analysis based on a three-dimensional variational method is proposed and performed in two steps. First, the horizontal wind field is simultaneously recovered through minimizing a cost function defined as a radial observation term with the standard conjugate gradient method, avoiding a weighting parameter specification step. Compared with conventional dual-Doppler wind synthesis approaches, this variational method minimizes errors caused by interpolation from radar observation to analysis grid in the iterative solution process, which is one of the main sources of errors. Then, through the accelerated Liebmann method, the vertical velocity is further re-estimated as an extra step by solving the Poisson equation with impermeable conditions imposed at the ground and near the tropopause. The Poisson equation defined by the second derivative of the vertical velocity is derived from the mass continuity equation. Compared with the method proposed by O'Brien, this method is less sensitive to the uncertainty of the boundary conditions and has better stability and reliability. Furthermore, the method proposed in this paper is applied to Doppler radar observation of a squall line process. It is shown that the retrieved vertical wind profile agrees well with the vertical profile obtained with the velocity–azimuth display (VAD) method, and the retrieved radial velocity as well as the analyzed positive and negative velocity centers and horizontal wind shear of the squall line are in accord with radar observations. There is a good correspondence between the divergence field of the derived wind field and the vertical velocity. And, the horizontal and vertical circulations within and around the squall line, as well as strong updrafts, the associated downdrafts, and associated rear inflow of the bow echo, are analyzed well. It is worth mentioning that the variational method in this paper can be applied to simultaneously synthesize the three-dimensional wind field from multiple-Doppler radar observations.

In this study, we introduce a parameterization scheme for slantwise convection (SC) to be considered for models that are too coarse to resolve slantwise convection explicitly (with a horizontal grid spacing coarser than 15 km or less). This SC scheme operates in a locally defined 2D cross section perpendicular to the deep-layer-averaged thermal wind. It applies momentum tendency to adjust the environment toward slantwise neutrality with a prescribed adjustment time scale. Condensational heating and the associated moisture loss are also considered. To evaluate the added value of the SC scheme, we implement it in the Weather Research and Forecasting (WRF) Model to supplement the existing cumulus parameterization schemes for upright convection and test for two different numerical setups: a 2D idealized, unforced release of conditional symmetric instability (CSI) in an initially conditionally stable environment, and a 3D real-data precipitation event containing both CSI and conditional instability along the cold front of a cyclonic storm near the United Kingdom. Both test cases show significant improvements for the coarse-gridded (40-km) simulations when parameterizing slantwise convection. Compared to the 40-km simulations with only the upright convection scheme, the counterparts with the additional SC scheme exhibit a larger extent of CSI neutralization, generate a stronger grid-resolved slantwise circulation, and produce greater amounts of precipitation, all in better agreement with the corresponding fine-gridded reference simulations. Given the importance of slantwise convection in midlatitude weather systems, our results suggest that there exist potential benefits of parameterizing slantwise convection in general circulation models.

Despite the unequal partitioning of land and aerosol sources between the hemispheres, Earth’s albedo is observed to be persistently symmetric about the equator. This symmetry is determined by the compensation of clouds to the clear-sky albedo. Here, the variability of this interhemispheric albedo symmetry is explored by decomposing observed radiative fluxes in the CERES EBAF satellite data record into components reflected by the atmosphere, clouds, and the surface. We find that the degree of interhemispheric albedo symmetry has not changed significantly throughout the observational record. The variability of the interhemispheric difference in reflected solar radiation (asymmetry) is strongly determined by tropical and subtropical cloud cover, particularly those related to nonneutral phases of El Niño–Southern Oscillation (ENSO). As ENSO is the most significant source of interannual variability in reflected radiation on a global scale, this underscores the interhemispheric albedo symmetry as a robust feature of Earth’s current annual mean climate. Comparing this feature in observations with simulations from coupled models reveals that the degree of modeled albedo symmetry is mostly dependent on biases in reflected radiation in the midlatitudes, and that models that overestimate its variability the most have larger biases in reflected radiation in the tropics. The degree of model albedo symmetry is improved when driven with historical sea surface temperatures, indicating that the degree of symmetry in Earth’s albedo is dependent on the representation of cloud responses to coupled ocean–atmosphere processes.

Sea surface temperature (SST) can be measured from space using infrared sensors on Earth-observing satellites. However, the tradeoff between spatial resolution and swath size (and hence revisit time) means that SST products derived from remote sensing measurements commonly only have a moderate resolution (>1 km). In this article, we adapt the design of a super-resolution neural network architecture [specifically very deep super-resolution (VDSR)] to enhance the resolution of both top-of-atmosphere thermal images of sea regions and bottom-of-atmosphere SST images by a factor of 5. When tested on an unseen dataset, the trained neural network yields thermal images that have an RMSE 2-3x smaller than interpolation, with a 6-9 dB improvement in PSNR. A major contribution of the proposed neural network architecture is that it fuses optical and thermal images to propagate the high-resolution information present in the optical image to the restored thermal image. To illustrate the potential benefits of using super-resolution (SR) in the context of oceanography, we present super-resolved SST images of a gyre and an ocean front, revealing details and features otherwise poorly resolved by moderate resolution satellite images.

The photolysis module in Environment and Climate Change Canada's online chemical transport model GEM-MACH (GEM: Global Environmental Multi-scale – MACH: Modelling Air quality and Chemistry) was improved to make use of the online size and composition-resolved representation of atmospheric aerosols and relative humidity in GEM-MACH, to account for aerosol attenuation of radiation in the photolysis calculation. We coupled both the GEM-MACH aerosol module and the MESSy-JVAL (Modular Earth Submodel System) photolysis module, through the use of the online aerosol modeled data and a new Mie lookup table for the model-generated extinction efficiency, absorption and scattering cross sections of each aerosol type. The new algorithm applies a lensing correction factor to the black carbon absorption efficiency (core-shell parameterization) and calculates the scattering and absorption optical depth and asymmetry factor of black carbon, sea salt, dust and other internally mixed components. We carried out a series of simulations with the improved version of MESSy-JVAL and wildfire emission inputs from the Canadian Forest Fire Emissions Prediction System (CFFEPS) for 2 months, compared the model aerosol optical depth (AOD) output to the previous version of MESSy-JVAL, satellite data, ground-based measurements and reanalysis products, and evaluated the effects of AOD calculations and the interactive aerosol feedback on the performance of the GEM-MACH model. The comparison of the improved version of MESSy-JVAL with the previous version showed significant improvements in the model performance with the implementation of the new photolysis module and with adopting the online interactive aerosol concentrations in GEM-MACH. Incorporating these changes to the model resulted in an increase in the correlation coefficient from 0.17 to 0.37 between the GEM-MACH model AOD 1-month hourly output and AERONET (Aerosol Robotic Network) measurements across all the North American sites. Comparisons of the updated model AOD with AERONET measurements for selected Canadian urban and industrial sites, specifically, showed better correlation coefficients for urban AERONET sites and for stations located further south in the domain for both simulation periods (June and January 2018). The predicted monthly averaged AOD using the improved photolysis module followed the spatial patterns of MERRA-2 reanalysis (Modern-Era Retrospective analysis for Research and Applications – version 2), with an overall underprediction of AOD over the common domain for both seasons. Our study also suggests that the domain-wide impacts of direct and indirect effect aerosol feedbacks on the photolysis rates from meteorological changes are considerably greater (3 to 4 times) than the direct aerosol optical effect on the photolysis rate calculations.

Ocean fronts have an important influence on global ocean-atmosphere interactions and marine fishery. Hence, it is of great significance to obtain the positions of the ocean fronts. However, current ocean front detection research confronts two challenges: scarcity of labeled data and limitations of ocean front detection algorithms. To address these two problems, we have collected and labeled an ocean front data set and proposed a new deep learning model for ocean front detection. For concreteness, due to the weak edge property of the ocean fronts, we formulate ocean front detection as a weak edge identification problem and propose the weak edge identification network (WEIN) for ocean front detection. WEIN consists of four convolutional blocks. Each block has a side output layer used to detect front edges at a specific image representation level. The side outputs are then fused to predict (detect) the locations of the ocean fronts. In this work, we adopt two metrics to measure the experimental results, i.e., the F₁-score and intersection over union (IoU). The experimental results with comparison to traditional and deep learning approaches demonstrate the superiority of WEIN for ocean front detection.

A satellite mission onboard a radar sounder for the observation of the earth's polar regions can greatly support the monitoring of the cryosphere and climate change analyses. Several studies are in progress proposing the design and demonstrating the performance of such an earth-orbiting radar sounder (EORS). However, one critical aspect of the cryospheric targets that are often ignored and simplified in these studies is the complex geoelectrical nature of the polar ice. In this article, we present a performance assessment of the polar ice target detectability by focusing on their realistic representation. This is obtained by simulating the orbital radargrams corresponding to different regions of the polar cryosphere by leveraging the data available from airborne campaigns in Antarctica and Greenland. We propose novel performance metrics to analyze the detectability of the internal reflecting horizons (IRHs), the basal interface, and to analyze the nature of the basal interface. This performance assessment strategy can be applied to guide the design of the signal-to-noise ratio (SNR) budget at the surface, which can further support the selection of the main orbital instrument parameters, such as the transmitted power, the two-way antenna gain, and the processing gains.

Recent paleo reconstructions suggest that increased carbon storage in the Southern Ocean during glacial periods contributed to low glacial atmospheric carbon dioxide concentration (pCO2). However, quantifying its contribution in three-dimensional ocean general circulation models (OGCMs) has proven challenging. Here, we show that OGCM simulation with sedimentary process considering enhanced Southern Ocean salinity stratification and iron fertilization from glaciogenic dust during glacial periods improves model-data agreement of glacial deep water with isotopically light carbon, low oxygen, and old radiocarbon ages. The glacial simulation shows a 77-ppm reduction of atmospheric pCO2, which closely matches the paleo record. The Southern Ocean salinity stratification and the iron fertilization from glaciogenic dust amplified the carbonate sedimentary feedback, which caused most of the increased carbon storage in the deep ocean and played an important role in pCO2 reduction. The model-data agreement of Southern Ocean properties is crucial for simulating glacial changes in the ocean carbon cycle., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

It has been proposed that magnetic flux expulsion due to outer core fluid upwellings may affect the geomagnetic secular variation on the core-mantle boundary (Bloxham, 1986). In this process intense horizontal field lines are concentrated below the outer boundary, introducing small radial length scales and consequently strong radial diffusion. We explore such magnetic boundary layers in numerical dynamo simulations with heterogeneous outer boundary heat flux inferred from a tomographic model of lower mantle seismic shear waves velocity anomalies. Our scheme associates magnetic boundary layers to peak horizontal magnetic fields at the top of the shell. In our models mean magnetic boundary layer thickness ranges ≈200-400 km and decreases with increasing magnetic Reynolds number. Extrapolation or interpolation to Earth's core conditions based on total core flow amplitude or its poloidal part gives mean magnetic boundary layer thickness of ≈220 and ≈260-330 km, respectively. We find magnetic boundary layers associated with the azimuthal field at the equatorial region, whereas magnetic boundary layers associated with the meridional field are found at mid latitudes. Negative outer boundary heat flux anomalies yield preferred locations of expulsion of azimuthal field below Africa and the Pacific (at low latitudes of the Northern Hemisphere.), while positive outer boundary heat flux anomalies yield preferred locations of expulsion of meridional field below the Americas and East Asia. Our results suggest that the local diffusion time is on the order of several kyr and the local magnetic Reynolds number is on the order of ≈10, both much smaller than classical estimates., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Multi-fluid models have recently been proposed as an approach to improving the representation of convection in weather and climate models. This is an attractive framework as it is fundamentally dynamical, removing some of the assumptions of mass-flux convection schemes which are invalid at current model resolutions. However, it is still not understood how best to close the multi-fluid equations for atmospheric convection. In this paper we develop a simple two-fluid, single-column model with one rising and one falling fluid. No further modelling of sub-filter variability is included. We then apply this model to Rayleigh-Benard convection, showing that, with minimal closures, the correct scaling of the heat flux (Nu) is predicted over six orders of magnitude of buoyancy forcing (Ra). This suggests that even a very simple two-fluid model can accurately capture the dominant coherent overturning structures of convection.

Ground-based sky imagers have become a valuable tool for cloud monitoring as they allow to observe the local sky in great detail due to their temporally and spatially high-resolution imagery. Set up in pairs, they can be used to estimate both cloud geometry and motion. While considerable effort is currently devoted to their use for cloud shadow forecasting and short-term prediction of solar irradiance for renewable energies, their potential for vertical wind profiling and cloud evolution monitoring has not yet received much attention. We evaluate the accuracy and reliability of such retrievals from two sky imagers in stereo mode by comparing derived 3D cloud motion vector fields with observations from a wind lidar. We find that the wind vectors derived from the detected motion of cumulus clouds and multiple cloud layers can be retrieved with a quality comparable to a wind lidar. Differences in wind speed and direction from both methods remain mostly below 1 to 3 ms−1 in wind speed and 6° to 20° in wind direction, depending on cloud type.

We analyse a tropical cyclone simulated for a realistic ocean-eddy field using the global, nonhydrostatic, fully coupled atmosphere–ocean ICOsahedral Nonhydrostatic (ICON) model. After intensifying rapidly, the tropical cyclone decays following its interaction with a cold wake and subsequently reintensifies as it encounters a subsurface, warm-core eddy. To understand the change in the azimuthal-mean structure and intensity of the tropical cyclone, we invoke a conceptual framework, which recognises the importance of both boundary-layer dynamics and air–sea interactions. Crucially, the framework recognises that the change in the mean radius of updraught at the boundary-layer top is regulated by the expanding outer tangential wind field through boundary-layer dynamics. The decrease in the average equivalent potential temperature of the boundary-layer updraught during the early decay phase is related to an increase in the mean radius of the updraught rather than air–sea interactions. However, later in the decay phase, air–sea interactions contribute to the decrease, which is accompanied by a decrease in the vertical mass flux in the eyewall updraught and, ultimately, a more pronounced spin-down of the tropical cyclone. Air–sea interactions are also important during reintensification, where the tendencies are reversed, that is, the mean radius of the boundary-layer updraught decreases along with an increase in its average equivalent potential temperature and vertical mass flux. The importance of boundary-layer dynamics to the change in the azimuthal-mean structure is underscored by the ability of a steady-state slab boundary-layer model to predict an increasing and, to a lesser extent, decreasing radius of forced ascent for periods of decay and reintensification, respectively. Finally, our simulation highlights the importance of the ocean-eddy field for tropical cyclone intensity forecasts, since the simulated warm-core eddy does not display any sea-surface temperature (SST) signal until it is encountered by the tropical cyclone. © 2021 The Authors. Quarterly Journal of the Royal Meteorological Society published by John Wiley Sons Ltd on behalf of the Royal Meteorological Society.