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The SubNiño4 index based on the subsurface potential temperature around the thermocline beneath the west Pacific warm pool, the Niño 4 region, is examined as a long-range indicator of the surface El Niño–Southern Oscillation (ENSO) and ENSO-driven atmospheric response. The SubNiño4 index captures the evolution of subsurface ocean heat content between the El Niño and La Niña phases of the ENSO cycle, allowing it to serve as a long-range indicator of surface ENSO and hence also many ENSO-driven atmospheric anomalies. The SubNiño4 index has more temporally stable correlations with Niño 3.4 than the widely used western equatorial Pacific warm-water volume indicator. For a lead time of the order of 12 months, Niño 3.4 correlations afforded by the lead observed SubNiño4 index become similar to and can exceed those produced by typical dynamical ENSO predictions. The value and viability of the SubNiño4 index as a simple statistical long-range indicator of ENSO-driven atmospheric response is shown for regional precipitation anomalies throughout the Tropics and fires in Continental and Maritime Southeast Asia.

Large-amplitude meteotsunamis were observed in many areas in Japan, following the arrival of barometric Lamb waves emitted by an underwater volcanic eruption of Hunga Tonga-Hunga Ha‘apai in January 2022. We modeled the power spectra of the tidal level data obtained from 12 tide stations of the Geospatial Information Authority of Japan, based on a method of transfer function which converts the barometric pressure pulse spectra into the meteotsunami spectra. The obtained transfer functions are similar at 12 stations. The pressure pulse spectra are obtained from the ensemble average of ∼1500 Soratena weather sensors of Weathernews Inc. distributed over Japan. The observed meteotsunami spectra can be characterized by the enhanced seiche eigenmodes at each station excited by the mesoscale pressure pulse within the amplitude error of 50%, which contributes for accumulating the necessary knowledge to understand the potential dangers in various different areas over Japan.

Inability of low-resolution ocean models to simulate many important aspects of the large-scale general circulation is a common problem. In the view of physics, the main reason for this failure are the missed dynamical effects of the unresolved small scales of motion on the explicitly resolved large-scale circulation. Complimentary to this mainstream physics-based perspective, we propose to address this failure from the dynamical systems point of view, namely, as the persistent tendency of phase space trajectories representing the low-resolution solution to escape the right region of the corresponding phase space, which is occupied by the reference eddy-resolving solution. Based on this concept, we propose to use methods of constrained optimization to confine the low-resolution solution to remain within the correct phase space region, without attempting to amend the eddy physics by introducing a process-based parameterization. This approach is advocated as a novel framework for data-driven hyper-parameterizations of mesoscale oceanic eddies in non-eddy-resolving models. We tested the idea in the context of classical, baroclinic beta-plane turbulence model and showed that non-eddy-resolving solution can be substantially improved towards the reference eddy-resolving benchmark.

Changes to coastlines and bathymetry alter tidal dynamics and associated sediment transport processes, impacting upon a number of threats facing coastal regions, including flood risk and erosion. Especially vulnerable are coral atolls such as those that make up the Maldives archipelago, which has undergone significant land reclamation in recent years and decades and is also particularly exposed to sea level rise. Here we develop a tidal model of Malé Atoll, Maldives, the first atoll-scale and multi-atoll-scale high-resolution numerical model of the atolls of the Maldives and use it to assess potential changes to sediment grain size distributions in the deeper atoll basin, under sea level rise and coastline alteration scenarios. The results indicate that the impact of coastline modification over the last two decades at the island scale is not limited to the immediate vicinity of the modified island but can also significantly impact the sediment grain size distribution across the wider atoll basin. Additionally, the degree of change in sediment distribution which can be associated with sea level rise that is projected to occur over relatively long time periods is predicted to occur over far shorter time periods with coastline changes, highlighting the need to better understand, predict and mitigate the impact of land reclamation and other coastal modifications before conducting such activities.

Widespread existing geological records from above the modern ice sheet surface and outboard of the current ice margin show that the Antarctic Ice Sheet (AIS) was much more extensive at the Last Glacial Maximum (∼ 20 ka) than at present. However, whether it was ever smaller than present during the last few millennia, and (if so) by how much, is known only for a few locations because direct evidence lies within or beneath the ice sheet, which is challenging to access. Here, we describe how retreat and readvance (henceforth “readvance”) of AIS grounding lines during the Holocene could be detected and quantified using subglacial bedrock, subglacial sediments, marine sediment cores, relative sea-level (RSL) records, geodetic observations, radar data, and ice cores. Of these, only subglacial bedrock and subglacial sediments can provide direct evidence for readvance. Marine archives are of limited utility because readvance commonly covers evidence of earlier retreat. Nevertheless, stratigraphic transitions documenting change in environment may provide support for direct evidence from subglacial records, as can the presence of transgressions in RSL records, and isostatic subsidence. With independent age control, ice structure revealed by radar can be used to infer past changes in ice flow and geometry, and therefore potential readvance. Since ice cores capture changes in surface mass balance, elevation, and atmospheric and oceanic circulation that are known to drive grounding line migration, they also have potential for identifying readvance. A multidisciplinary approach is likely to provide the strongest evidence for or against a smaller-than-present AIS in the Holocene.

The paper deals with an experimental study of tip-clearance cavitation inception and development and its vortical structure coupled with dynamics of the main attached cavity on the suction side of a two-dimensional symmetric hydrofoil equipped with a rotation axis. The gap is formed by the end face of the model and a transparent sidewall of the test channel. The experiments were performed for attack angles of 3° and 9° and 0.4-, 0.8-, 1.75- and 3.75-mm gaps (or 1.8%–17% relative thickness) under various flow conditions on the cavitation number. In order to observe the tip-clearance cavitation occurrence, high-speed imaging was applied. The leakage flow velocity was measured inside the clearance by a modified Particle Tracking Velocimetry technique. It is shown that the mean velocity field of the leaking flow is split into eight distinctive zones where the flow direction and velocity magnitude substantially differ. Positions and extents of these zones are practically independent of the primary flow regime but are affected by the attack angle. Local velocity values of the leakage flow are unexpectedly found to be about 20% higher in the region of a gap cavity than the mean bulk velocity of the incoming flow. Cavitating cores of various vortices manifest themselves in the recorded images, showing that the vortex structure of the leakage flow associated with the tip-clearance cavitation is very complicated and the hydrofoil axis makes it even more complex by inducing new vortices and cavities. For the gaps considered, an increase of its size causes the tip-clearance cavitation to be initiated at higher cavitation numbers, i.e., this is favorable for its occurrence, while the development of the main cavity is hindered. In unsteady flow regimes, dynamics of the primary cavity on the hydrofoil suction side significantly influences the leakage flow direction and the tip-clearance cavitation evolution. Periods of oscillation cycles of the main and gap cavities coincide but the maximum size of the gap cavity is reached with a phase lag relative to the main one. At the small incidence angle, thicker gaps and unsteady flow conditions, extremely transient pressure waves are registered in the clearance, with their velocities ranging from 41 to 81 m/s

The present paper addresses the short-term distribution of zero-crossing wave heights in intermediate and shallow water depths. New physical insights are provided regarding the effects of nonlinearity, directionality, reduced effective water depth and finite spectral bandwidth. These are demonstrated through the analysis of a large database of experimental simulations of short-crested sea-states on flat bed bathymetries. A new wave height model is proposed building upon these physical insights and is calibrated using the experimental data. Independent comparisons between field measurements and the proposed model indicate that it is appropriate to a wide range of incident wave conditions and that it provides considerable improvement over existing models.

Coastal zones are vulnerable to both erosion and flood risk, which can be assessed using coupled hydro- morphodynamic models. However, the use of such models as decision support tools suffers from a high degree of uncertainty, due to both incomplete knowledge and natural variability in the system. In this work, we show for the first time how the multilevel Monte Carlo method (MLMC) can be applied in hydro-morphodynamic coastal ocean modelling, here using the popular model XBeach, to quantify uncertainty by computing statistics of key output variables given uncertain input parameters. MLMC accelerates the Monte Carlo approach through the use of a hierarchy of models with different levels of resolution. Several theoretical and real-world coastal zone case studies are considered here, for which output variables that are key to the assessment of flood and erosion risk, such as wave run-up height and total eroded volume, are estimated. We show that MLMC can significantly reduce computational cost, resulting in speed up factors of 40 or greater compared to a standard Monte Carlo approach, whilst keeping the same level of accuracy. Furthermore, a sophisticated ensemble generating technique is used to estimate the cumulative distribution of output variables from the MLMC output. This allows for the probability of a variable exceeding a certain value to be estimated, such as the probability of a wave run-up height exceeding the height of a seawall. This is a valuable capability that can be used to inform decision-making under uncertainty

A recently developed, height-distributed urban drag parametrization is tested with the London Model, a sub-kilometre resolution version of the Met Office Unified Model over Greater London. The distributed-drag parametrization requires vertical morphology profiles in the form of height-distributed frontal-area functions, which capture the full extent and variability of building heights. London’s morphology profiles are calculated and parametrized by an exponential distribution with the ratio of maximum to mean building height as the parameter. A case study evaluates the differences between the new distributed-drag scheme and the current London Model setup using the MORUSES urban land-surface model. The new drag parametrization shows increased horizontal spatial variability in total surface stress, identifying densely built-up areas, high-rise building clusters, parks, and the river. Effects on the wind speed in the lower levels include a lesser gradient and more heterogeneous wind profiles, extended wakes downwind of the city centre, and vertically growing perturbations that suggest the formation of internal boundary layers. The surface sensible heat fluxes are underpredicted, which is attributed to difficulties coupling the distributed momentum exchange with the surface-based heat exchange., Quarterly Journal of the Royal Meteorological Society, 147 (741), ISSN:0035-9009, ISSN:1477-870X

75 pages, 8 figures, 3 tables, 6 appendixes, supplement https://doi.org/10.5194/esd-12-1295-2021-supplement.-- Code and data availability: The python code that was used for the analysis and to create the plots is available at https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021; Volpi, 2021) and as a Renku project https://renkulab.io/projects/ACE-ASAID/spca-decomposition (last access: 29 March 2021; Volpi and Landwehr, 2021). For the availability of the data used in this study please refer to Tables B1 to B8 in Appendix B, The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question, Rafel Simó, Marina Zamanillo, Pau Cortés-Greus, and Pablo Rodríguez-Ros were supported by the Spanish Ministry of Science through the BIOGAPS project (CTM2016-81008-R), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

The complexity of comprehensive ocean models poses an important question for parameterisations: is there a minimum set of equations that should be parameterised, on the one hand, to reduce the development to a minimum, and, on the other hand, to ensure an accurate representation of large-scale flow patterns? This work seeks to answer the question to assist modern parameterisations be more selective in their targets. For this, we considered a model of the North Atlantic and studied contributions of different model equations to the accuracy of representation of the Gulf Stream at low resolution. Our results suggest that one should focus on parameterising the tracer equations for temperature and salinity, and may leave the other equations in the hydrodynamic part, as well as the atmospheric model unmodified. They also suggest that parameterisations representing only Kinetic Energy Backscatter cannot be fully efficient and the main focus should be shifted towards developing parameterisations of combined Potential/Kinetic Energy Backscatters.

The success of deep learning techniques over the last decades has opened up a new avenue of research for weather forecasting. Here, we take the novel approach of using a neural network to predict full probability density functions at each point in space and time rather than a single output value, thus producing a probabilistic weather forecast. This enables the calculation of both uncertainty and skill metrics for the neural network predictions, and overcomes the common difficulty of inferring uncertainty from these predictions. This approach is data-driven and the neural network is trained on the WeatherBench dataset (processed ERA5 data) to forecast geopotential and temperature 3 and 5 days ahead. Data exploration leads to the identification of the most important input variables, which are also found to agree with physical reasoning, thereby validating our approach. In order to increase computational efficiency further, each neural network is trained on a small subset of these variables. The outputs are then combined through a stacked neural network, the first time such a technique has been applied to weather data. Our approach is found to be more accurate than some numerical weather prediction models and as accurate as more complex alternative neural networks, with the added benefit of providing key probabilistic information necessary for making informed weather forecasts., 21 pages, 14 figures, Github repository: https://github.com/mc4117/ResNet_Weather, Submitted to Quarterly Journal of the Royal Meteorological Society

We present results of Large-eddy simulations (LES) modeling of steady sheet and unsteady cloud cavitation on a two-dimensional hydrofoil which are validated against Particle image velocimetry (PIV) data. The study is performed for the angle of attack of 9° and high Reynolds numbers ReC of the order of 106 providing a strong adverse pressure gradient along the surface. We employ the Schnerr–Sauer and Kunz cavitation models together with the adaptive mesh refinement in critical flow regions where intensive phase transitions occur. Comparison of the LES and visualization results confirms that the flow dynamics is adequately reproduced in the calculations. To correctly match averaged velocity distributions, we propose a new methodology based on conditional averaging of instantaneous velocity fields measured by PIV which only provides information on the liquid phase. This approach leads to an excellent overall agreement between the conditionally averaged fields of the mean velocity and turbulence intensity obtained experimentally and numerically. The benefits of second-order discretization schemes are highlighted as opposed to the lower-order TVD scheme.

The red gurnard (Chelidonichthys kumu) is a coastal benthic fish supporting substantial fisheries in the Indo-West Pacific. Despite this, biological knowledge of the species is limited to New Zealand, placing other fished populations at risk of overexploitation if they are less productive. We determined the age, growth, reproductive biology and commercial catch composition of C. kumu from the trawl fishery in New South Wales (NSW). We also tested the hypothesis that growth rates and body size in NSW would be smaller than New Zealand, given the less productive marine environment in NSW and relative food limitation. Similar to New Zealand, individuals from NSW ranged in length from 13 to 56 cm FL and 1 to 13 years of age, with the largest and oldest fish being predominantly female. Females grew faster and to a greater maximum size than males. Growth was broadly similar between populations in NSW and New Zealand. Spawning period in NSW was protracted (11 months) and peaked in winter, contrasting with a peak in spring/summer in New Zealand. Size-at-maturity was similar between the two regions. The current study provides fundamental biological information to inform stock assessment and management of C. kumu in NSW.

Rapid and accurate prediction of peak storm surges across an extensive coastal region is necessary to inform assessments used to design the systems that protect coastal communities’ life and property. Significant advances in high-fidelity, physics-based numerical models have been made in recent years, but use of these models for probabilistic forecasting and probabilistic hazard assessment is computationally intensive. Several surrogate modeling approaches based on existing databases of high-fidelity synthetic storm surge simulations have been recently suggested to reduce computational burden without substantial loss of accuracy. In these previous studies, however, the surrogate modeling approaches relied on a tropical cyclone condition at one moment (usually at or near landfall), which is not always most correlated with the peak storm surge. In this study, a new one-dimensional convolutional neural network model combined with principal component analysis and a k-means clustering (C1PKNet) is presented that can rapidly predict peak storm surge across an extensive coastal region from time-series of tropical cyclone conditions, namely the storm track. The C1PKNet model was trained and cross-validated for the Chesapeake Bay area of the United States using existing database of 1031 high-fidelity storm surge simulations, including both landfalling and bypassing storms. Moreover, the performance of the C1PKNet model was evaluated based on observations from three historical hurricanes (Hurricane Isabel in 2003, Hurricane Irene in 2011, and Hurricane Sandy in 2012). The results indicate that the C1PKNet model is computationally efficient and can predict peak storm surges from realistic tropical cyclone track time-series. We believe that this new surrogate model can enhance coastal resilience by providing rapid storm surge predictions. Accepted version

This study considers the isopycnal eddy transport of mass and passive tracers in eddy-resolving double-gyre quasigeostrophic oceanic circulation. Here we focus on advective transport, whereas a companion paper focuses on eddy-induced diffusive tracer transport. To work towards parameterising eddy tracer transport we quantify the eddy tracer flux using a transport tensor with eddies defined using a spatial filter, which leads to results distinct from those obtained via a temporal Reynolds eddy decomposition. The advection tensor is the antisymmetric part of the transport tensor, and is so named since the associated tracer transport can be expressed as advection of the large-scale tracer field by a rotational eddy-induced velocity (EIV) u ∗ c with streamfunction A . The EIV u ∗ c is fastest ( ∼ 1 m s−1) where eddy activity is strongest, e.g., in the upper layer, near the eastward jet and western boundary current. Our results suggest that a stochastic closure for the eddy transport would be most suitable since A exhibits a probabilistic distribution when conditioned on, for example, the large-scale relative vorticity. Consistent with closures in ocean circulation models, we quantify eddy mass (isopycnal layer thickness) fluxes as eddy-induced advection by the thickness EIV u ∗ h . The divergent part of u ∗ h – the only part relevant for mass transport in the quasigeostrophic limit – tends to be oriented down the thickness gradient suggesting it quantifies some baroclinic eddy effects similar to those parameterised by the Gent & McWilliams (GM90) EIV. Although u ∗ h has some qualitative similarities to u ∗ c , our results suggest that eddy-induced tracer advection is driven by more than just the thickness-determined EIV and, in turn, more than just the GM90 EIV.

Based on theory and climate model experiments, previous studies suggest most of the uncertainties in projected future changes in meridional energy transport and zonal mean surface temperature can be attributed to cloud feedback. To investigate how radiative and dynamical adjustments modify the influence of cloud-radiative changes on energy transport, this study applies a cloud-locking technique in a fully-coupled climate model, CESM. Under global warming, the impacts of cloud-radiative changes on the meridional energy transport are asymmetric in the two hemispheres. In the Northern Hemisphere, the cloud-radiative changes have little impact on energy transport, because 89% of the cloud-induced heating is balanced locally by increasing outgoing longwave radiation. In the Southern Hemisphere, on the other hand, cloud-induced dynamical changes in the atmosphere and the ocean cause enhanced poleward energy transport, accounting for most of the increase in energy transport under warming. Our experiments highlight that the local longwave radiation adjustment induced by temperature variation can partially offset the impacts of cloud-radiative changes on energy transport, making the estimated impacts smaller than those obtained from directly integrating cloud-radiative changes in previous studies. It is also demonstrated that the cloud-radiative impacts on temperature and energy transport can be significantly modulated by the oceanic circulation, suggesting the necessity of considering atmospheric-oceanic coupling when estimating the impacts of cloud-radiative changes on the climate system.

This study provides an interpretation of isopycnal eddy transport for mass and passive tracers in double-gyre eddy-resolving oceanic circulation. This paper focuses on a transport/diffusion tensor representation of the eddy tracer flux, and a companion paper will focus on advective eddy-induced tracer and mass transports. We use a spatial filter to separate the large and small scales, which leads to results distinct from those obtained via a temporal Reynolds eddy decomposition. To work towards a parameterisation, we relate the eddy tracer flux to the large-scale tracer gradient via the transport tensor K . The symmetric part of K is the diffusion tensor, S , which parameterises diffusive fluxes and whose mixing properties are determined by the signs of its eigenvalues. The eigenvalues of S are robustly of opposite sign (polar) and thus quantify filamentation of the tracer via both up- and down-gradient fluxes. Given the prevalence of polar eigenvalues – which are also obtained for Reynolds eddy fluxes – representing their associated effects should be a target of future eddy tracer transport closures. Given the inherent inhomogeneity and anisotropy of the eddy-induced transport, we argue that a full transport tensor is better suited to this task than scalar coefficients or diagonal tensors. The diffusion axis, which represents the direction of preferential mixing, tends to align with the large-scale velocity vector and contours of large-scale relative vorticity and layer thickness. Strong shears can inhibit this alignment. We show that the large-scale velocity gradient matrix may be suitable for parameterising the transport tensor, in particular at depth. Furthermore, since entries of K and S exhibit probabilistic distributions when conditioned on certain large-scale flow features, we suggest that a stochastic closure for the eddy transport would be most suitable.

A recent paper by Kato and Rose reports a negative correlation between the annual mean entropy production rate of the climate and the absorption of solar radiation in the CERES SYN1deg dataset, using the simplifying assumption that the system is steady in time. It is shown here, however, that when the nonsteady interannual storage of entropy is accounted for, the dataset instead implies a positive correlation; that is, global entropy production rates increase with solar absorption. Furthermore, this increase is consistent with the response demonstrated by an energy balance model and a radiative–convective model. To motivate this updated analysis, a detailed discussion of the conceptual relationship between entropy production, entropy storage, and entropy flows is provided. The storage-corrected estimate for the mean global rate of entropy production in the CERES dataset from all irreversible transfer processes is 81.9 mW m−2 K−1 and from only nonradiative processes is 55.2 mW m−2 K−1 (observations from March 2000 to February 2018).

In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe. However, the link between droughts and climate change is not sufficiently understood. Here we investigate trends in long-term agricultural drought and the influence of increasing temperatures and precipitation deficits. Using a combination of models and observational datasets, we studied trends, spanning the period from 1900 (to approximate pre-industrial conditions) to 2018, for six regions in eastern Africa in four drought-related annually averaged variables: soil moisture, precipitation, temperature, and evaporative demand (E0). In standardized soil moisture data, we found no discernible trends. The strongest influence on soil moisture variability was from precipitation, especially in the drier or water-limited study regions; temperature and E0 did not demonstrate strong relations to soil moisture. However, the error margins on precipitation trend estimates are large and no clear trend is evident, whereas significant positive trends were observed in local temperatures. The trends in E0 are predominantly positive, but we do not find strong relations between E0 and soil moisture trends. Nevertheless, the E0 trend results can still be of interest for irrigation purposes because it is E0 that determines the maximum evaporation rate. We conclude that until now the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and we recommend that any soil moisture analysis be supplemented by an analysis of precipitation deficit., Earth System Dynamics, 12 (1), ISSN:2190-4987, ISSN:2190-4979

Representation of the marine environment is key for reliable coastal hydrodynamic models. This study investigates the implications of common depth-averaged model configuration choices in sufficiently characterising seabed geometry and roughness. In particular, applications requiring a high level of accuracy and/or exhibiting complex flow conditions may call for greater detail in marine environment representation than typically adopted in coastal models. Ramsey Sound, a macrotidal strait in Pembrokeshire, Wales, UK is considered as a case study. The site contains various steeply inclined bathymetric features, including a submerged pinnacle named Horse Rock and a rocky reef called “The Bitches”. The available energy in Ramsey Sound's tidal currents has attracted attention from tidal energy developers. There is interest in accurately modelling the energetic hydrodynamics surrounding its pronounced bathymetry. The coastal flow solver Thetis is applied to simulate the flow conditions in Ramsey Sound. It is shown that notable prominent bathymetric features in the strait influence localised and, most importantly, regional hydrodynamic characteristics. “The Bitches” consistently accelerate flow in the strait while Horse Rock induces a notable wake structure and flow reversals. The model is calibrated against bed- and vessel-mounted Acoustic Doppler Current Profiler (ADCP) observations, by altering seabed roughness parameterisations. A spatially variable and locally scaled Manning coefficient based on diverse seabed classification observations is found to improve model performance in comparison to uniformly applied constants, the latter a more common approach. The local impact of altering the Manning coefficient configuration is found to be greatest during spring flood periods of high velocity currents. Meanwhile, the effect of coarsening the computational mesh around bathymetric features towards values more typically applied in coastal models is investigated. Results indicate severe misrepresentation of seabed geometry and subsequent wake hydrodynamics unless refined to a mesh element size that adequately represents Horse Rock and “The Bitches”.

© 2020 Elsevier B.V. Ocean colour data are commonly used to quantify primary production, study phytoplankton dynamics and calibrate marine models, thus understanding the origin of errors in the retrieved chlorophyll-a (Chl-a) product is critical. One source of uncertainty in retrieved Chl-a products can be related to large photosynthetic cells, characterised by lower mass-specific absorption coefficients due to increased packaging effect. Here, we explore the relationship between phytoplankton size structure and an ocean colour product using optical simulations and in situ observations. Specifically, we use an optical model to explore how phytoplankton cell size and abundance influence phytoplankton absorption and backscattering coefficients and the implication this has for water leaving radiance and the estimated Chl-a derived from satellite ocean colour. The optical model simulations show phytoplankton cell size has a significant impact on the remote-sensing reflectance, with Chl-a packaged in 5 to 10 μm cells resulting in about 54 to 76% the simulated ocean colour Chl-a compared to 1 μm cells, as determined by an algorithm that converts reflectances to Chl-a. To support optical simulations, size-fractionated Chl-a samples were collected from several water masses to investigate the phytoplankton size contribution (i.e., < 2 μm, 2–10 μm and > 10 μm) to the total Chl-a. We focused on the offshore eastern Australian ocean region, largely characterised by oligotrophic waters in which phytoplankton dominate the optical properties of the water column. Of the 22 stations sampled, a total of ten in situ size fractionated Chl-a measurements were matched-up with the corresponding clear-sky satellite Chl-a product. The matched-up points revealed a systematic underestimation of in situ Chl-a. With the low amount of data, it was not possible to statistically relate the satellite underestimation to a specific phytoplankton size class, but the observations showed that the largest satellite Chl-a underestimates were found when phytoplankton larger than 10 μm represented more than 50% of the phytoplankton community. Additional measurements that combine in situ optical measurements with phytoplankton size distribution and carbon/Chl-a ratio would help to clarify the relationship between phytoplankton size structures and remotely sensed Chl-a product.

Subglacial water plays an important role in ice sheet dynamics and stability. Subglacial lakes are often located at the onset of ice streams and have been hypothesised to enhance ice flow downstream by lubricating the ice–bed interface. The most recent subglacial-lake inventory of Antarctica mapped nearly 400 lakes, of which ∼ 14 % are found in West Antarctica. Despite the potential importance of subglacial water for ice dynamics, there is a lack of detailed subglacial-water characterisation in West Antarctica. Using radio-echo sounding data, we analyse the ice–bed interface to detect subglacial lakes. We report 33 previously uncharted subglacial lakes and present a systematic analysis of their physical properties. This represents a ∼ 40 % increase in subglacial lakes in West Antarctica. Additionally, a new digital elevation model of basal topography of the Ellsworth Subglacial Highlands was built and used to create a hydropotential model to simulate the subglacial hydrological network. This allows us to characterise basal hydrology, determine subglacial water catchments and assess their connectivity. We show that the simulated subglacial hydrological catchments of the Rutford Ice Stream, Pine Island Glacier and Thwaites Glacier do not correspond to their ice surface catchments.

In this “Grand Challenges” paper, we review how the carbon isotopic composition of atmospheric CO2 has changed since the Industrial Revolution due to human activities and their influence on the natural carbon cycle, and we provide new estimates of possible future changes for a range of scenarios. Emissions of CO2 from fossil fuel combustion and land use change reduce the ratio of 13C/12C in atmospheric CO2 (δ13CO2). This is because 12C is preferentially assimilated during photosynthesis and δ13C in plant-derived carbon in terrestrial ecosystems and fossil fuels is lower than atmospheric δ13CO2. Emissions of CO2 from fossil fuel combustion also reduce the ratio of 14C/C in atmospheric CO2 (Δ14CO2) because 14C is absent in million-year-old fossil fuels, which have been stored for much longer than the radioactive decay time of 14C. Atmospheric Δ14CO2 rapidly increased in the 1950s to 1960s because of 14C produced during nuclear bomb testing. The resulting trends in δ13C and Δ14C in atmospheric CO2 are influenced not only by these human emissions but also by natural carbon exchanges that mix carbon between the atmosphere and ocean and terrestrial ecosystems. This mixing caused Δ14CO2 to return toward preindustrial levels in the first few decades after the spike from nuclear testing. More recently, as the bomb 14C excess is now mostly well mixed with the decadally overturning carbon reservoirs, fossil fuel emissions have become the main factor driving further decreases in atmospheric Δ14CO2. For δ13CO2, in addition to exchanges between reservoirs, the extent to which 12C is preferentially assimilated during photosynthesis appears to have increased, slowing down the recent δ13CO2 trend slightly. A new compilation of ice core and flask δ13CO2 observations indicates that the decline in δ13CO2 since the preindustrial period is less than some prior estimates, which may have incorporated artifacts owing to offsets from different laboratories' measurements. Atmospheric observations of δ13CO2 have been used to investigate carbon fluxes and the functioning of plants, and they are used for comparison with δ13C in other materials such as tree rings. Atmospheric observations of Δ14CO2 have been used to quantify the rate of air-sea gas exchange and ocean circulation, and the rate of net primary production and the turnover time of carbon in plant material and soils. Atmospheric observations of Δ14CO2 are also used for comparison with Δ14C in other materials in many fields such as archaeology, forensics, and physiology. Another major application is the assessment of regional emissions of CO2 from fossil fuel combustion using Δ14CO2 observations and models. In the future, δ13CO2 and Δ14CO2 will continue to change. The sign and magnitude of the changes are mainly determined by global fossil fuel emissions. We present here simulations of future δ13CO2 and Δ14CO2 for six scenarios based on the shared socioeconomic pathways (SSPs) from the 6th Coupled Model Intercomparison Project (CMIP6). Applications using atmospheric δ13CO2 and Δ14CO2 observations in carbon cycle science and many other fields will be affected by these future changes. We recommend an increased effort toward making coordinated measurements of δ13C and Δ14C across the Earth System and for further development of isotopic modeling and model-data analysis tools. ©2020. American Geophysical Union. All Rights Reserved.

© 2020 Elsevier B.V. Remotely-sensed ocean colour is the main tool for estimating chlorophyll a (Chl-a) concentration and primary productivity on the global scale. In order to investigate the source of errors in remotely-sensed Chl-a concentration we obtained in situ bio-optical properties, in situ reflectances, satellite-derived reflectances and the Chl-a concentration satellite products of the Ocean and Land Colour Instrument (OLCI) Instrument on board Sentinel-3 A in waters off eastern Australia. The mesoscale eddies of these oligotrophic waters provide contrasting phytoplankton communities that allowed us to focus on the effect of phytoplankton size as a source of errors. In these waters, cold-core cyclonic eddies (CE) are dominated by large phytoplankton cells, while small cells dominate warm-core anticyclonic eddies (ACE). The chlorophyll-specific absorption and backscattering from contrasting sites show significant difference due to the differing package effect of phytoplankton size distributions. After normalising the absorption and backscattering spectra to Chl-a associated with just small phytoplankton, the spectra of optical properties become much more similar, showing that small-sized phytoplankton dominate IOPs even when large cells contain the greater fraction of Chl-a concentration of the phytoplankton community. Measured in situ reflectances agreed with reflectances calculated using a simple optical model based on measured IOPs. Furthermore, the in situ measured reflectances agreed well with the OLCI reflectance (mean normalised bias (MNB) of 7% for wavelengths

Large‐scale (500 ≤ r ≤ 2,200 km) outgoing long‐wave radiation (OLR) and water vapour (WV) fields are investigated in satellite observations over the Pacific, linked to ERA‐5 reanalysis data and the ECMWF ensemble forecasts of tropical cyclones (TC) globally. A large‐scale OLR dipole pattern of low and high fluxes are found in both the observations and model. As expected, a low OLR region is positioned within the TC circulation, but there is also a robust high OLR region poleward and west of the TC centre. A dry “black hole” on WV grey‐scale imagery occupies the same region of high OLR. Relative to the central low OLR TC signal, the typical dipole magnitude, distance and orientation of the high OLR regions are 230 W·m−2, 1,150 km, and 145° anticlockwise from east. From the reanalysis we find that the interaction between the vortex and the environmental flows produces upper‐level convergence, low‐level divergence and subsidence throughout the troposphere in the region of high OLR. Analysis of the ECMWF model shows that the position of the high OLR region rotates anticlockwise about the TC centre as the TC moves from westward to eastward. Through use of a sub‐ensemble, we test if capturing the high OLR anomaly has a significant relationship with TC track. We apply a perfect model approach and find that sub‐ensembles that are composed of models whose large‐scale OLR fields closely match the target TC also have a better track. This improvement is mostly attributed to the high OLR component of the dipole.

Wind-generated waves are often treated as stochastic processes. There is particular interest in their spectral density functions, which are often expressed in some parametric form. Such spectral density functions are used as inputs when modelling structural response or other engineering concerns. Therefore, accurate and precise recovery of the parameters of such a form, from observed wave records, is important. Current techniques are known to struggle with recovering certain parameters, especially the peak enhancement factor and spectral tail decay. We introduce an approach from the statistical literature, known as the de-biased Whittle likelihood, and address some practical concerns regarding its implementation in the context of wind-generated waves. We demonstrate, through numerical simulation, that the de-biased Whittle likelihood outperforms current techniques, such as least squares fitting, both in terms of accuracy and precision of the recovered parameters. We also provide a method for estimating the uncertainty of parameter estimates. We perform an example analysis on a data-set recorded off the coast of New Zealand, to illustrate some of the extra practical concerns that arise when estimating the parameters of spectra from observed data.

Destratification of thermally stratified open-channel flow by surface cooling is investigated using direct numerical simulation. The initial states are the equilibrium states resulting from radiative heating. Using these states as initial conditions, a series of direct numerical simulations was run with radiative heating removed and a constant, uniform cooling flux applied at the upper surface. The flow evolves until the initial stable stratification is broken down and replaced by unstable stratification driven by surface cooling. The destratification process is described with reference to the evolution of the internal structure of the turbulent flow field. Based on these observations, we conclude that the dominant time scales in the flow from the perspective of destratification are the time scales associated with shear tτ , convection t∗ and stable density stratification tN . Scaling arguments are then used to derive a scaling relationship for destratification rate as a function of a friction Richardson number Riτ=(tτ/tN)^2 and a convection Richardson number Ri∗=(t∗/tN)^2 . The relationship takes the form DN=C1Riτ^−1+C2Ri∗^−1 , where DN is the destratification rate non-dimensionalised with respect to tN and C1 and C2 are model coefficients. The relationship is compared with simulation results and is shown to accurately predict the destratification rate in the simulations across a range of parameters. This relationship is then integrated to give a formula for the time taken for the flow to destratify.

Large tsunamis can be generated by submarine slides, but these events are rare on human timescales and challenging to observe. Experiments and numerical modelling offer methods to understand the mechanisms by which they generate waves and what the potential hazard might be. However, to fully capture the complex waveform generated by a submarine slide, the slide dynamics must also be accurately modelled. It is computationally difficult to model both a three-dimensional submarine slide whilst simultaneously simulating oceanic-scale tsunamis. Past studies have either coupled localised models of the slide generation to oceanic-scale tsunami simulations or simplified the slide dynamics. Here, we present a new methodology of model coupling that generates the wave in the ocean-scale model via boundary-condition coupling of a two-dimensional dynamic slide simulation. We verify our coupling methodology by comparing model results to a previous simulation of a tsunamigenic slide in the Gulf of Mexico. We then examine the effect of slide deformation on the risk posed by hypothetical submarine slides around the UK. We show the deformable submarine slide simulations produce larger waves than the solid slide simulations due to the details of acceleration and velocity of the slide, although lateral spreading is not modelled. This work offers a new methodology for simulating oceanic-scale tsunamis caused by submarine slides using the output of a two-dimensional, multi-material simulation as input into a three-dimensional ocean model. This facilitates future exploration of the tsunami risk posed by tsunamigenic submarine slides that affect coastlines not normally prone to tsunamis.

Constraining the response time of the climate system to changes in North Atlantic Deep Water (NADW) formation is fundamental to improving climate and Atlantic Meridional Overturning Circulation predictability. Here we report a new synchronization of terrestrial, marine, and ice-core records, which allows the first quantitative determination of the response time of North Atlantic climate to changes in high-latitude NADW formation rate during the last deglaciation. Using a continuous record of deep water ventilation from the Nordic Seas, we identify a ∼400-year lead of changes in high-latitude NADW formation ahead of abrupt climate changes recorded in Greenland ice cores at the onset and end of the Younger Dryas stadial, which likely occurred in response to gradual changes in temperature- and wind-driven freshwater transport. We suggest that variations in Nordic Seas deep-water circulation are precursors to abrupt climate changes and that future model studies should address this phasing., The response time of North Atlantic climate to changes in high-latitude deep-water formation during the last deglaciation is still unclear. Here the authors show that gradual changes in Nordic Seas deep-water circulation systematically lead ahead of abrupt regional climate shifts by ~400 years.

Numerical storm surge models are essential to forecasting coastal flood hazard and informing the design of coastal defences. However, such models rely on a variety of inputs, many of which carry uncertainty. An awareness and understanding of the sensitivity of model outputs with respect to those uncertain inputs is therefore essential when interpreting model results. Here, we use an unstructured-mesh numerical coastal ocean model, Thetis, and its adjoint, to perform a sensitivity analysis for a hindcast of the 5th/6th December 2013 North Sea surge event, with respect to the bottom friction coefficient, bathymetry and wind stress forcing. The results reveal spatial and temporal patterns of sensitivity, providing physical insight into the mechanisms of surge generation and propagation. For example, the sensitivity of the skew surge to the bathymetry reveals the protective effect of a sand bank off the UK east coast. The results can also be used to propagate uncertainties through the numerical model; based on estimates of model input uncertainties, we estimate that modelled skew surges carry uncertainties of around 5 cm and 15 cm due to bathymetry and bottom friction, respectively. While these uncertainties are small compared with the typical spread in an ensemble storm surge forecast due to uncertain meteorological inputs, the adjoint-derived model sensitivities can nevertheless be used to inform future model calibration and data acquisition efforts in order to reduce uncertainty. Our results demonstrate the power of adjoint methods to gain insight into a storm surge model, providing information complementary to traditional ensemble uncertainty quantification methods.

The unstructured mesh, discontinuous Galerkin finite element discretisation based coastal ocean model, Thetis, has been extended to include non-hydrostatic (buoyancy-driven and free surface) dynamics. Two alternative approaches to achieve this are described in this work. The first (a 3D based algorithm) makes use of prismatic element based meshes and uses a split-step pressure projection method for baroclinic and barotropic modes, while the second (a 2D based algorithm) adopts a novel multi-layer approach to convert a 3D problem into a combination of multiple 2D computations with only 2D triangle meshes required. Model development is carried out at high-level with the Firedrake library, using code generation techniques to automatically produce low-level code for the discretised model equations in an efficient and rapid manner. Through comparisons against several barotropic/baroclinic test cases where non hydrostatic effects are important, the implemented approaches are verified and validated, and the proposed algorithms compared. Depending on whether the problems are dominated by dispersive, baroclinic or barotropic features, recommendation are given over the use of full 3D or multi-layer 2D based approaches to achieve optimal computational accuracy and efficiency. It is demonstrated that while in general the 2D approach is well-suited for barotropic problems and dispersive free surface waves, the 3D approach is more advantageous for simulating baroclinic buoyancy-driven flows due in part to the high vertical resolution typically required to represent the active tracer fields. Keywords: Discontinuous Galerkin, Finite element, Unstructured mesh, Baroclinic flow, Non-hydrostatic, Dispersion, Free surface

Ocean dynamics served an important role during past dramatic climate changes via impacts on deep-ocean carbon storage. Such changes are recorded in sedimentary proxies of hydrographic change on continental margins, which lie at the ocean–atmosphere–earth interface. However, interpretations of these records are challenging, given complex interplays among processes delivering particulate material to and from ocean margins. Here we report radiocarbon (14C) signatures measured for organic carbon in differing grain-size sediment fractions and foraminifera in a sediment core retrieved from the southwest Iberian margin, spanning the last ~25,000 yr. Variable differences of 0–5000 yr in radiocarbon age are apparent between organic carbon in differing grain-sizes and foraminifera of the same sediment layer. The magnitude of 14C differences co-varies with key paleoceanographic indices (e.g., proximal bottom-current density gradients), which we interpret as evidence of Atlantic–Mediterranean seawater exchange influencing grain-size specific carbon accumulation and translocation. These findings underscore an important link between regional hydrodynamics and interpretations of down-core sedimentary proxies., Marine sedimentary records and the proxies within play a central role in unlocking our understanding of past climates, yet interpreting the signals they contain can be complex. Here, the authors reveal and discuss the complex effects of hydrodynamics on carbon accumulation in the sediments off the Iberian margin.

Accurate representation of large-scale flow patterns in low-resolution ocean simulations is one of the most challenging problems in ocean modelling. The main difficulty is to correctly reproduce effects of unresolved small scales on the resolved large scales. For this purpose, most of current research is focused on development of parameterizations directly accounting for the small scales. In this work we propose an alternative to the mainstream ideas by showing how to reconstruct a dynamical system from the available reference solution data (our proxy for observations) and, then, how to use this system for modelling not only large-scale but also nominally-resolved flow patterns at low resolutions. This approach is advocated as a part of the novel framework for data-driven hyper-parameterization of mesoscale oceanic eddies in non-eddy-resolving models. The main characteristic of this framework is that it does not require to know the physics behind large–small scale interactions to reproduce both large and small scales in low-resolution ocean simulations. We tested it in the context of a three-layer, statistically equilibrated, steadily forced quasigeostrophic model for the beta-plane configuration and showed that non-eddy-resolving solution can be substantially improved towards the reference eddy-resolving benchmark. The proposed methodology robustly allows to retrieve a system of equations governing reduced dynamics of the observed data, while the additional adaptive nudging counteracts numerical instabilities by keeping solutions in the region of phase space occupied by the reference fields. Remarkably, its solutions simulate not only large-scale but also small-scale flow features, which can be nominally resolved by the low-resolution grid. In addition, the proposed method reproduces realistic vortex trajectories. One of the important and general conclusions that can be drawn from our results is that not only mesoscale eddy parameterization is possible in principle but also it can be highly accurate (up to reproducing individual vortices) for significantly reduced dynamics (down to 30 degrees of freedom). This conclusion provides great optimism for the ongoing parameterization studies, which are still far away from being completed.

A common approach for parameterising eddy transport of passive tracers by mesoscale eddies in the ocean is by invoking a transport tensor. The symmetric part of this tensor, the diffusion tensor, quantifies diffusive eddy tracer transport. Recent studies have diagnosed opposite-signed eigenvalues (diffusivities) of the diffusion tensor from eddy-resolving simulations, while all current parameterisations implement only positive diffusivities. For opposite-signed eigenvalues the associated diffusive eddy tracer flux is not necessarily down-gradient and therefore may not mix the tracer by transferring variance to the small scales. In this study we explore such diffusive eddy fluxes by using an eddy-resolving simulation of passive tracers with a relaxation (source/sink) forcing. After confirming that the diffusion tensors for different tracer pairs have opposite-signed eigenvalues, we show that the corresponding diffusive eddy tracer flux drives a net down-gradient transfer of variance, as would be guaranteed when the diffusion tensor eigenvalues are both positive. Locally up-gradient fluxes are common, with their frequency strongly dependent on the relaxation profile. The effects of weakening/strengthening the relaxation on the frequency of down-gradient fluxes is different for each tracer. However, for all tracers considered the amplitude of the net down-gradient transfer weakens as the relaxation strengthens, a consequence of the homogeneous diffusion dissipating less eddy variance. Our results indicate that for oceanic tracers with sources/sinks the parameterised diffusive eddy tracer fluxes should not be globally down-gradient.

The synoptic situation and mesoscale structure of an explosive extratropical cyclone over the Northwestern Pacific in March 2007 are investigated through weather station observations and data reanalysis. The cyclone is located beneath the poleward side of the exit of a 200 hPa jet, which is a strong divergent region aloft. At mid-level, the cyclone lies on the downstream side of a well-developed trough, where a strong ascending motion frequently occurs. Cross-section analyses with weather station data show that the cyclone has a warm and moist core. A ‘nose’ of the cold front, which is characterized by a low-level protruding structure in the equivalent potential temperature field, forms when the cyclone moves offshore. This ‘nose’ structure is hypothesized to have been caused by the heating effect of the Kuroshio Current. Two low-level jet streams are also identified on the western and eastern sides of the cold front. The western jet conveys cold and dry air at 800–900 hPa. The wind in the northern part is northeasterly, and the wind in the southern part is northwesterly. By contrast, the eastern jet carries warm and moist air into the cyclone system, ascending northward from 900 hPa to 600–700 hPa. The southern part is dominated by the southerly wind, and the wind in the northern part is southwesterly. The eastern and western jets significantly increase the air temperature and moisture contrast in the vicinity of the cold front. This increase could play an important role in improving the rapid cyclogenesis process.

In this paper, an Ensemble Kalman Filter (EnKF) based regional ocean data assimilation system has been developed and applied to the South Australian Sea. This system consists of the data assimilation algorithm provided by the NCAR Data Assimilation Research Testbed (DART) and the Regional Ocean Modelling System (ROMS). We describe the first implementation of the physical balance operator (temperature-salinity, hydrostatic and geostrophic balance) to DART, to reduce the spurious waves which may be introduced during the data assimilation process. The effect of the balance operator is validated in both an idealised shallow water model and the ROMS model real case study. In the shallow water model, the geostrophic balance operator eliminates spurious ageostrophic waves and produces a better sea surface height (SSH) and velocity analysis and forecast. Its impact increases as the sea surface height and wind stress increase. In the real case, satellite-observed sea surface temperature (SST) and SSH are assimilated in the South Australian Sea with 50 ensembles using the Ensemble Adjustment Kalman Filter (EAKF). Assimilating SSH and SST enhances the estimation of SSH and SST in the entire domain, respectively. Assimilation with the balance operator produces a more realistic simulation of surface currents and subsurface temperature profile. The best improvement is obtained when only SSH is assimilated with the balance operator. A case study with a storm suggests that the benefit of the balance operator is of particular importance under high wind stress conditions. Implementing the balance operator could be a general benefit to ocean data assimilation systems.

A mechanism leading to the self-weakening of tropical cyclones is proposed using the Weather and Research and Forecasting model. A comparison between an experiment with variable Coriolis parameter f and one on an f-plane shows that, after the initial intensification, the former is characterized by a smaller intensity. As opposed to the tropical cyclone on the f-plane, the one with variable f weakens significantly after reaching maturity. Analyses of the 3D circulation show that the main reason for the weakening is dry intrusion in the mid-upper troposphere from the west. Once the dry intrusion reaches the inner vortex, strong downdraughts reduce the high equivalent potential temperature in the boundary-layer inflow. The subsequent updraughts in the eyewall, characterized by lower equivalent potential temperature, are considerably reduced and, consequently, the secondary circulation weakens. Back-trajectories are used to determine the origin of the dry intrusion. It is found that the air parcels expelled from the storm deep convection into the outflow layer recirculate anticyclonically back into the vortex, causing a self-weakening of the tropical cyclone. A time span for the recirculation of at least 48 h allows the air parcels to sink substantially before reaching the vortex circulation. Some implications of the intrinsic nature of this process are briefly discussed.

Subglacial roughness can be determined at a variety of length scales from radio-echo sounding (RES) data either via statistical analysis of topography or inferred from basal radar scattering. Past studies have demonstrated that subglacial terrain exhibits self-affine (power law) roughness scaling behaviour, but existing radar scattering models do not take this into account. Here, using RES data from northern Greenland, we introduce a self-affine statistical framework that enables a consistent integration of topographic-scale roughness with the electromagnetic theory of radar scattering. We demonstrate that the degree of radar scattering, quantified using the waveform abruptness (pulse peakiness), is topographically controlled by the Hurst (roughness power law) exponent. Notably, specular bed reflections are associated with a lower Hurst exponent, with diffuse scattering associated with a higher Hurst exponent. Abrupt waveforms (specular reflections) have previously been used as a RES diagnostic for basal water, and to test this assumption we compare our radar scattering map with a recent prediction for the basal thermal state. We demonstrate that the majority of thawed regions (above pressure melting point) exhibit a diffuse scattering signature, which is in contradiction to the prior approach. Self-affine statistics provide a generalised model for subglacial terrain and can improve our understanding of the relationship between basal properties and ice-sheet dynamics.

This paper investigates the average shape of the largest waves arising in finite water depths. Specifically, the largest waves recorded in time histories of the water surface elevation at a single point have been examined. These are compared to commonly applied theories in engineering and oceanographic practice. To achieve this both field observations and a new set of laboratory measurements are considered. The latter concern long random simulations of directionally spread sea states generated using realistic Joint North Sea Wave Project (JONSWAP) frequency spectra. It is shown that approximations related to the linear theory of quasi-determinism (QD) cannot describe some key characteristics of the largest waves. While second-order corrections to the QD predictions provide an improvement, key effects arising in very steep or shallow water sea states are not captured. While studies involving idealized wave groups have demonstrated significant changes arising as a result of higher-order nonlinear wave–wave interactions, these have not been observed in random sea states. The present paper addresses this discrepancy by decomposing random wave measurements into separate populations of breaking and nonbreaking waves. The characteristics of average wave shapes in the two populations are examined and their key differences discussed. These explain the mismatch between findings in earlier random and deterministic wave studies.

We provide a novel methodology for computing the most likely path taken by drifters between arbitrary fixed locations in the ocean. We also provide an estimate of the travel time associated with this path. Lagrangian pathways and travel times are of practical value not just in understanding surface velocities, but also in modelling the transport of ocean-borne species such as planktonic organisms, and floating debris such as plastics. In particular, the estimated travel time can be used to compute an estimated Lagrangian distance, which is often more informative than Euclidean distance in understanding connectivity between locations. Our methodology is purely data-driven, and requires no simulations of drifter trajectories, in contrast to existing approaches. Our method scales globally and can simultaneously handle multiple locations in the ocean. Furthermore, we provide estimates of the error and uncertainty associated with both the most likely path and the associated travel time., Comment: 27 pages, 10 figures in the main text. 13 pages, 8 figures in the supplemental material

International audience; A stochastic representation based on a physical transport principle is proposed to account for mesoscale eddy effects on the evolution of the large-scale flow. This framework arises from a decomposition of the Lagrangian velocity into a smooth in time component and a highly oscillating term. One important characteristic of this random model is that it conserves the energy of any transported scalar. Such an energy-preserving representation is tested for the coarse simulation of a barotropic circulation in a shallow ocean basin, driven by a symmetric double-gyres wind forcing. The empirical spatial correlation of the random small-scale velocity is estimated from data of an eddy-resolving simulation. After reaching a turbulent equilibrium state, a statistical analysis of tracers shows that the proposed random model enables us to reproduce accurately, on a coarse mesh, the local structures of the first four statistical moments (mean, variance, skewness and kurtosis) of the high-resolution eddy-resolved data.

The equilibrium climate sensitivity (ECS, in K) to CO2 doubling is a large source of uncertainty in projections of future anthropogenic climate change. Estimates of ECS made from non-equilibrium states or in response to radiative forcings other than 2 × CO2 are called “effective climate sensitivity” (EffCS, in K). Taking a “perfect-model” approach, using coupled atmosphere–ocean general circulation model (AOGCM) experiments, we evaluate the accuracy with which CO2 EffCS can be estimated from climate change in the “historical” period (since about 1860). We find that (1) for statistical reasons, unforced variability makes the estimate of historical EffCS both uncertain and biased; it is overestimated by about 10% if the energy balance is applied to the entire historical period, 20% for 30-year periods, and larger factors for interannual variability, (2) systematic uncertainty in historical radiative forcing translates into an uncertainty of ±30–45% (standard deviation) in historical EffCS, (3) the response to the changing relative importance of the forcing agents, principally CO2 and volcanic aerosol, causes historical EffCS to vary over multidecadal timescales by a factor of two. In recent decades it reached its maximum in the AOGCM historical experiment (similar to the multimodel-mean CO2 EffCS of 3.6 K from idealised experiments), but its minimum in the real world (1.6 K for an observational estimate for 1985–2011, similar to the multimodel-mean value for volcanic forcing). The real-world variations mean that historical EffCS underestimates CO2 EffCS by 30% when considering the entire historical period. The difference for recent decades implies that either unforced variability or the response to volcanic forcing causes a much stronger regional pattern of sea surface temperature change in the real world than in AOGCMs. We speculate that this could be explained by a deficiency in simulated coupled atmosphere–ocean feedbacks which reinforce the pattern (resembling the Interdecadal Pacific Oscillation in some respects) that causes the low EffCS. We conclude that energy-balance estimates of CO2 EffCS are most accurate from periods unaffected by volcanic forcing. Atmosphere GCMs provided with observed sea surface temperature for the 1920s to the 1950s, which was such a period, give a range of about 2.0–4.5 K, agreeing with idealised CO2 AOGCM experiments; the consistency is a reason for confidence in this range as an estimate of CO2 EffCS. Unless another explosive volcanic eruption oc37 curs, the first 30 years of the present century may give a more accurate energy-balance historical estimate of this quantity.

New large-scale experiments on the influence of storm sequencing on beach profile evolution are presented. The experiments comprised three sequences that commenced from the same initial beach profile. Each sequence consisted of two storms of different energy, with each storm followed by a recovery phase. A specific focus of the experiments was the influence of storm chronology as well as the influence of the recovery wave energy and duration on beach evolution. The breaker bar and the shoreline are studied as indicators for the beach response. Both evolve towards an equilibrium location for each wave condition where the breaker bar reaches its equilibrium much faster than the shoreline. Overall, no enhanced beach erosion due to storm sequencing is observed. Despite a similar cumulative wave power of the three sequences, the final beach configuration of each sequence seems to be determined by the last wave condition instead of previous storms. However, storm sequencing is important when the beach profile has not yet fully recovered before being disrupted by the subsequent storm. In this case, the second storm does not necessarily cause further erosion but can result in onshore sediment transport and hence, form part of the recovery. The bulk onshore sediment transport as well as the shoreline recovery rate vary depending on the wave condition and the profile disequilibrium and show a maximum value for a recovery condition with an intermediate wave energy. The very low energy condition that was performed for a long duration (24 hours) generated a near-stationary beach profile with typical features of a reflective beach.

The present paper investigates the short-term statistical distribution of wave heights. Specifically, some of the most commonly applied wave height distributions are assessed using field measurements. The latter comprise of wave radar observations from 10 different locations in the North Sea and cover water depths between 7.7 m and 45 m. In total, the field database includes more than 200 million waves, making it one of the largest of its kind in this water depth regime. In using these data, the accuracy of existing wave height distributions has been examined and guidance is provided concerning the best performing models and their domain of applicability. Additionally, insights concerning the influence of key met-ocean parameters are also provided. Taken together, the results in this paper present an overview of the statistical behaviour of wave heights in finite water depths, as observed in the field.

An important open question in fluid dynamics concerns the effect of small scales in structuring a fluid flow. In oceanic or atmospheric flows, this is aptly captured in wave–current interactions through the study of the well-known Langmuir secondary circulation. Such wave–current interactions are described by the Craik–Leibovich system, in which the action of a wave-induced velocity, the Stokes drift, produces a so-called “vortex force” that causes streaking in the flow. In this work, we show that these results can be generalized as a generic effect of the spatial inhomogeneity of the statistical properties of the small-scale flow components. As demonstrated, this is well captured through a stochastic representation of the flow.

Past changes in global industrial aerosol emissions have played a significant role in historical shifts in African rainfall, and yet assessment of the impact on African rainfall of near-term (10–40 yr) potential aerosol emission pathways remains largely unexplored. While existing literature links future aerosol declines to a northward shift of Sahel rainfall, existing climate projections rely on RCP scenarios that do not explore the range of air quality drivers. Here we present projections from two emission scenarios that better envelop the range of potential aerosol emissions. More aggressive emission cuts result in northward shifts of the tropical rainbands whose signal can emerge from expected internal variability on short, 10–20-yr time horizons. We also show for the first time that this northward shift also impacts East Africa, with evidence of delays to both onset and withdrawal of the short rains. However, comparisons of rainfall impacts across models suggest that only certain aspects of both the West and East African model responses may be robust, given model uncertainties. This work motivates the need for wider exploration of air quality scenarios in the climate science community to assess the robustness of these projected changes and to provide evidence to underpin climate adaptation in Africa. In particular, revised estimates of emission impacts of legislated measures every 5–10 years would have a value in providing near-term climate adaptation information for African stakeholders.

A promising development of the last decade in the numerical modelling of geophysical fluids has been the compatible finite‐element framework. Indeed, this will form the basis for the next‐generation dynamical core of the Met Office. For this framework to be useful for numerical weather prediction models, it must be able to handle descriptions of unresolved and diabatic processes. These processes offer a challenging test for any numerical discretisation, and have not yet been described within the compatible finite‐element framework. The main contribution of this article is to extend a discretisation using this new framework to include moist thermodynamics. Our results demonstrate that discretisations within the compatible finite‐element framework can be robust enough also to describe moist atmospheric processes. We describe our discretisation strategy, including treatment of moist processes, and present two configurations of the model using different sets of function spaces with different degrees of finite element. The performance of the model is demonstrated through several test cases. Two of these test cases are new cloudy‐atmosphere variants of existing test cases: inertia–gravity waves in a two‐dimensional vertical slice and a three‐dimensional rising thermal.

Land models are often used to simulate terrestrial responses to future environmental changes, but these models are not commonly evaluated with data from experimental manipulations. Results from experimental manipulations can identify and evaluate model assumptions that are consistent with appropriate ecosystem responses to future environmental change. We conducted simulations using three coupled carbon‐nitrogen versions of the Community Land Model (CLM, versions 4, 4.5, and—the newly developed—5), and compared the simulated response to nitrogen (N) and atmospheric carbon dioxide (CO2) enrichment with meta‐analyses of observations from similar experimental manipulations. In control simulations, successive versions of CLM showed a poleward increase in gross primary productivity and an overall bias reduction, compared to FLUXNET‐MTE observations. Simulations with N and CO2 enrichment demonstrate that CLM transitioned from a model that exhibited strong nitrogen limitation of the terrestrial carbon cycle (CLM4) to a model that showed greater responsiveness to elevated concentrations of CO2 in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO2 enrichment than previous versions of the model. These simulations also exposed shortcomings in structural assumptions and parameterizations. Specifically, no version of CLM captures changes in plant physiology, allocation, and nutrient uptake that are likely important aspects of terrestrial ecosystems' responses to environmental change. These highlight priority areas that should be addressed in future model developments. Moving forward, incorporating results from experimental manipulations into model benchmarking tools that are used to evaluate model performance will help increase confidence in terrestrial carbon cycle projections., Key Points Experimental manipulations provide critical insights into ecosystem responses to environmental change that can evaluate land modelsParametric and structural changes to the Community Land Model version 5 improve the simulated response to environmental changeModel assumptions related to nutrient acquisition strategies and trade‐offs between carbon and nitrogen limitation deserve further attention

The problem of augmenting low-resolution ocean circulation models with the information extracted from the data relevant to the unresolved subgrid processes is addressed. A highly nonlinear model of eddy-resolving oceanic circulation – quasigeostrophic wind-driven double gyres – is considered. The model solutions are characterized by a vigorous dynamic coupling between the resolved large-scale and small-scale (eddy) flow features. This solution provides the data for augmenting the low-resolution model with the same configuration. The eddy forcing field, which contains the essential information about coupling between the large and eddy scales, is obtained, modified, coarse-grained and added to augment the low-resolution model. The implemented modification involves novel data-adaptive harmonic decomposition analysis and dynamical constraining based on the low-resolution nonlinear advection operator. The resulting augmentation of the low-resolution model significantly improves the solution, including its time-mean circulation and low-frequency variability. This result also paves the way for a systematic data-driven emulation of unresolved and under-resolved scales of motion.