Improving seasonal forecasting through tropical ocean bias corrections

Initialisation shock is often discussed in the context of coupled atmosphere-ocean forecasting, but its detection has remained elusive. In this paper, the presence of initialisation shock in seasonal forecasts is clearly identified in the variability of the tropical thermocline. The specific source of shock studied here is the use of a bias correction procedure to account for errors in equatorial wind stress forcing during ocean initialisation. It is shown that the abrupt removal of the bias correction at the beginning of the forecast leads to rapid adjustments in the upper ocean, creating a shock that remains in the system for at least three months. By contrast, gradual removal of the correction term, over 20 days, greatly reduces the initialisation shock. Evidence is presented of substantial increases in sea surface temperature (SST) seasonal forecast skill, at around 3–7 months’ lead time, when the gradual removal approach is used. Gains in skill of up to 0.05, as measured by the anomaly correlation coefficient for SST in the Nino4 region, are found, using a modest hindcast set covering four seasonal start dates. The results show that improvements in coupled initialisation aimed at reducing shocks may considerably benefit seasonal forecasting

An assessment of the impact of local processes on dust lifting in martian climate models

Simulation of the lifting of dust from the planetary surface is of substantially greater importance on Mars than on Earth, due to the fundamental role that atmospheric dust plays in the former’s climate, yet the dust emission parameterisations used to date in martian global climate models (MGCMs) lag, understandably, behind their terrestrial counterparts in terms of sophistication. Recent developments in estimating surface roughness length over all martian terrains and in modelling atmospheric circulations at regional to local scales (less than O(100 km)) presents an opportunity to formulate an improved wind stress lifting parameterisation. We have upgraded the conventional scheme by including the spatially varying roughness length in the lifting parameterisation in a fully consistent manner (thereby correcting a possible underestimation of the true threshold level for wind stress lifting), and used a modification to account for deviations from neutral stability in the surface layer. Following these improvements, it is found that wind speeds at typical MGCM resolution never reach the lifting threshold at most gridpoints: winds fall particularly short in the southern midlatitudes, where mean roughness is large. Sub-grid scale variability, manifested in both the near-surface wind field and the surface roughness, is then considered, and is found to be a crucial means of bridging the gap between model winds and thresholds. Both forms of small-scale variability contribute to the formation of dust emission ‘hotspots’: areas within the model gridbox with particularly favourable conditions for lifting, namely a smooth surface combined with strong near-surface gusts. Such small-scale emission could in fact be particularly influential on Mars, due both to the intense positive radiative feedbacks that can drive storm growth and a strong hysteresis effect on saltation. By modelling this variability, dust lifting is predicted at the locations at which dust storms are frequently observed, including the flushing storm sources of Chryse and Utopia, and southern midlatitude areas from which larger storms tend to initiate, such as Hellas and Solis Planum. The seasonal cycle of emission, which includes a double-peaked structure in northern autumn and winter, also appears realistic. Significant increases to lifting rates are produced for any sensible choices of parameters controlling the sub-grid distributions used, but results are sensitive to the smallest scale of variability considered, which high-resolution modelling suggests should be O(1 km) or less. Use of such models in future will permit the use of a diagnosed (rather than prescribed) variable gustiness intensity, which should further enhance dust lifting in the southern hemisphere in particular

Spatiotemporal summation of perimetric stimuli in healthy observers

Spatial summation of perimetric stimuli has been used to derive conclusions about the spatial extent of retinal-cortical convergence, mostly from the size of the critical area of summation (Ricco's area, RA) and critical number of retinal ganglion cells (RGCs). However, spatial summation is known to change dynamically with stimulus duration. Conversely, temporal summation and critical duration also vary with stimulus size. Such an important and often neglected spatiotemporal interaction has important implications for modeling perimetric sensitivity in healthy observers and for formulating hypotheses for changes measured in disease. In this work, we performed experiments on visually heathy observers confirming the interaction of stimulus size and duration in determining summation responses in photopic conditions. We then propose a simplified computational model that captures these aspects of perimetric sensitivity by modelling the total retinal input, the combined effect of stimulus size, duration, and retinal cones-to-RGC ratio. We additionally show that, in the macula, the enlargement of RA with eccentricity might not correspond to a constant critical number of RGCs, as often reported, but to a constant critical total retinal input. We finally compare our results with previous literature and show possible implications for modeling disease, especially glaucoma

Dynamic modeling of nitrogen losses in river networks unravels the coupled effects of hydrological and biogeochemical processes

The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly equally to seasonal and stream-size related variations in the percentage of the stream nitrate flux removed in each watershed

IMPRESSION – prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy

The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar Information Of Nuclei) machine learning system provides an efficient and accurate route to the prediction of NMR parameters from 3-dimensional chemical structures. Here we demonstrate that machine learning predictions, trained on quantum chemical computed values for NMR parameters, are essentially as accurate but computationally much more efficient (tens of milliseconds per molecule) than quantum chemical calculations (hours/days per molecule). Training the machine learning systems on quantum chemical, rather than experimental, data circumvents the need for existence of large, structurally diverse, error-free experimental databases and makes IMPRESSION applicable to solving 3-dimensional problems such as molecular conformation and isomeris

An inverse problem for Voronoi diagrams : a simplified model of non-destructive testing with ultrasonic array

In this paper, we study the inverse problem of recovering the spatially varying material properties of a solid polycrystalline object from ultrasonic travel time measurements taken between pairs of points lying on the domain boundary. We consider a medium of constant density in which the orientation of the material's lattice structure varies in a piecewise constant manner, generating locally anisotropic regions in which the wave speed varies according to the incident wave direction and the material's known slowness curve. This particular problem is inspired by current challenges faced by the ultrasonic non-destructive testing of polycrystalline solids. We model the geometry of the material using Voronoi tessellations and study two simplified inverse problems where we ignore wave refraction. In the first problem, the Voronoi geometry itself and the orientations associated to each region are unknowns. We solve this nonsmooth, nonconvex optimisation problem using a multistart non-linear least squares method. Good reconstructions are achieved, but the method is shown to be sensitive to the addition of noise. The second problem considers the reconstruction of the orientations on a fixed square mesh. This is a smooth optimisation problem but with a much larger number of degrees of freedom. We prove that the orientations can be determined uniquely given enough boundary measurements and provide a numerical method that is more stable with respect to the addition of noise

Optical interferometry-based array of seafloor environmental sensors using a trans-oceanic submarine cable

Optical fiber–based sensing technology can drastically improve Earth observations by enabling the use of existing submarine communication cables as seafloor sensors. Previous interferometric and polarization-based techniques demonstrated environmental sensing over cable lengths up to 10,500 kilometers. However, measurements were limited to the integrated changes over the entire length of the cable. We demonstrate the detection of earthquakes and ocean signals on individual spans between repeaters of a 5860-kilometer-long transatlantic cable rather than the whole cable. By applying this technique to the existing undersea communication cables, which have a repeater-to-repeater span length of 45 to 90 kilometers, the largely unmonitored ocean floor could be instrumented with thousands of permanent real-time environmental sensors without changes to the underwater infrastructure

Simulating the interannual variability of major dust storms on Mars using variable lifting thresholds

The redistribution of a finite amount of martian surface dust during global dust storms and in the intervening periods has been modelled in a dust lifting version of the UK Mars General Circulation Model. When using a constant, uniform threshold in the model’s wind stress lifting parameterisation and assuming an unlimited supply of surface dust, multiannual simulations displayed some variability in dust lifting activity from year to year, arising from internal variability manifested in surface wind stress, but dust storms were limited in size and formed within a relatively short seasonal window. Lifting thresholds were then allowed to vary at each model gridpoint, dependent on the rates of emission or deposition of dust. This enhanced interannual variability in dust storm magnitude and timing, such that model storms covered most of the observed ranges in size and initiation date within a single multiannual simulation. Peak storm magnitude in a given year was primarily determined by the availability of surface dust at a number of key sites in the southern hemisphere. The observed global dust storm (GDS) frequency of roughly one in every 3 years was approximately reproduced, but the model failed to generate these GDSs spontaneously in the southern hemisphere, where they have typically been observed to initiate. After several years of simulation, the surface threshold field—a proxy for net change in surface dust density—showed good qualitative agreement with the observed pattern of martian surface dust cover. The model produced a net northward cross-equatorial dust mass flux, which necessitated the addition of an artificial threshold decrease rate in order to allow the continued generation of dust storms over the course of a multiannual simulation. At standard model resolution, for the southward mass flux due to cross-equatorial flushing storms to offset the northward flux due to GDSs on a timescale of ∼3 years would require an increase in the former by a factor of 3–4. Results at higher model resolution and uncertainties in dust vertical profiles mean that quasi-periodic redistribution of dust on such a timescale nevertheless appears to be a plausible explanation for the observed GDS frequency

The solsticial pause on Mars: 2 modelling and investigation of causes

The martian solsticial pause, presented in a companion paper (Lewis et al. [this issue]. Icarus), was investigated further through a series of model runs using the UK version of the LMD/UK Mars Global Climate Model. It was found that the pause could not be adequately reproduced if radiatively active water ice clouds were omitted from the model. When clouds were used, along with a realistic time-dependent dust opacity distribution, a substantial minimum in near-surface transient eddy activity formed around solstice in both hemispheres. The net effect of the clouds in the model is, by altering the thermal structure of the atmosphere, to decrease the vertical shear of the westerly jet near the surface around solstice, and thus reduce baroclinic growth rates. A similar effect was seen under conditions of large dust loading, implying that northern midlatitude eddy activity will tend to become suppressed after a period of intense flushing storm formation around the northern cap edge. Suppression of baroclinic eddy generation by the barotropic component of the flow and via diabatic eddy dissipation were also investigated as possible mechanisms leading to the formation of the solsticial pause but were found not to make major contributions. Zonal variations in topography were found to be important, as their presence results in weakened transient eddies around winter solstice in both hemispheres, through modification of the near-surface flow. The zonal topographic asymmetry appears to be the primary reason for the weakness of eddy activity in the southern hemisphere relative to the northern hemisphere, and the ultimate cause of the solsticial pause in both hemispheres. The meridional topographic gradient was found to exert a much weaker influence on near-surface transient eddies