Slope streaks on Mars: Correlations with surface properties and the potential role of water

The Mars Orbiter Camera on board the Mars Global Surveyor spacecraft has returned images of numerous dark streaks that are the result of down-slope mass movement occurring under present-day martian climatic conditions. We systematically analyze over 23,000 high-resolution images and demonstrate that slope streaks form exclusively in regions of low thermal inertia (confirming earlier results), steep slopes, and, remarkably, only where peak temperatures exceed 275 K. The northernmost streaks, which form in the coldest environment, form preferentially on warmer south-facing slopes. Repeat images of sites with slope streaks show changes only if the time interval between the two images includes the warm season. Surprisingly (in light of the theoretically short residence time of H_2O close to the surface), the data support the possibility that small amounts of water are transiently present in low-latitude near-surface regions of Mars and undergo phase transitions at times of high insolation, triggering the observed mass movements

Global reconstruction of historical ocean heat storage and transport

Most of the excess energy stored in the climate system due to anthropogenic greenhouse gas emissions has been taken up by the oceans, leading to thermal expansion and sea level rise. The oceans thus have an important role in the Earth’s energy imbalance. Observational constraints on future anthropogenic warming critically depend on accurate estimates of past ocean heat content (OHC) change. We present a novel reconstruction of OHC since 1871, with global coverage of the full ocean depth. Our estimates combine timeseries of observed sea surface temperatures, with much longer historical coverage than those in the ocean interior, together with a representation (a Green’s function) of time-independent ocean transport processes. For 1955-2017, our estimates are comparable to direct estimates made by infilling the available 3D time-dependent ocean temperature observations. We find that the global ocean absorbed heat during this period at a rate of 0.30 ± 0.06 W/m2 in the upper 2000 m and 0.028 ± 0.026 W/m2 below 2000 m, with large decadal fluctuations. The total OHC change since 1871 is estimated at 436 ±91 × 1021 J, with an increase during 1921-1946 (145 ± 62× 1021 J) that is as large as during 1990-2015. By comparing with direct estimates, we also infer that, during 1955-2017, up to half of the Atlantic Ocean warming and thermosteric sea level rise at low-to-mid latitudes emerged due to heat convergence from changes in ocean transport

A derivative-free optimisation method for global ocean biogeochemical models

The skill of global ocean biogeochemical models, and the earth system models in which they are embedded, can be improved by systematic calibration of the parameter values against observations. However, such tuning is seldom undertaken as these models are computationally very expensive. Here we investigate the performance of DFO-LS, a local, derivative-free optimisation algorithm which has been designed for computationally expensive models with irregular model–data misfit landscapes typical of biogeochemical models. We use DFO-LS to calibrate six parameters of a relatively complex global ocean biogeochemical model (MOPS) against synthetic dissolved oxygen, phosphate and nitrate “observations” from a reference run of the same model with a known parameter configuration. The performance of DFO-LS is compared with that of CMA-ES, another derivative-free algorithm that was applied in a previous study to the same model in one of the first successful attempts at calibrating a global model of this complexity. We find that DFO-LS successfully recovers five of the six parameters in approximately 40 evaluations of the misfit function (each one requiring a 3000-year run of MOPS to equilibrium), while CMA-ES needs over 1200 evaluations. Moreover, DFO-LS reached a “baseline” misfit, defined by observational noise, in just 11–14 evaluations, whereas CMA-ES required approximately 340 evaluations. We also find that the performance of DFO-LS is not significantly affected by observational sparsity, however fewer parameters were successfully optimised in the presence of observational uncertainty. The results presented here suggest that DFO-LS is sufficiently inexpensive and robust to apply to the calibration of complex, global ocean biogeochemical models

Sensitivity analysis of simple global marine biogeochemical models

This study presents results from 46 sensitivity experiments carried out with three structurally simple (2, 3, and 6 biogeochemical state variables, respectively) models of production, export and remineralization of organic phosphorus, coupled to a global ocean circulation model and integrated for 3000 years each. The models' skill is assessed via different misfit functions with respect to the observed global distributions of phosphate and oxygen. Across the different models, the global root-mean square misfit with respect to observed phosphate and oxygen distributions is found to be particularly sensitive to changes in the remineralization length scale, and also to changes in simulated primary production. For this metric, changes in the production and decay of dissolved organic phosphorus as well as in zooplankton parameters are of lesser importance. For a misfit function accounting for the misfit of upper-ocean tracers, however, production parameters and organic phosphorus dynamics play a larger role. Regional misfit patterns are investigated as indicators of potential model deficiencies, such as missing iron limitation, or deficiencies in the sinking and remineralization length scales. In particular, the gradient between phosphate concentrations in the northern North Pacific and the northern North Atlantic is controlled predominantly by the biogeochemical model parameters related to particle flux. For the combined 46 sensitivity experiments performed here, the global misfit to observed oxygen and phosphate distributions shows no clear relation to either simulated global primary or export production for either misfit metric employed. However, a relatively tight relationship that is very similar for the different model of different structural complexity is found between the model-data misfit in oxygen and phosphate distributions to simulated meso- and bathypelagic particle flux. Best agreement with the observed tracer distributions is obtained for simulated particle fluxes that agree most closely with sediment trap data for a nominal depth of about 1000 m, or deeper

The influence of warming patterns on passive ocean heat uptake

The climate's response to forcing depends on how efficiently heat is absorbed by the ocean. Much, if not most, of this ocean heat uptake results from the passive transport of warm surface waters into the ocean's interior. Here we examine how geographic patterns of surface warming influence the efficiency of this passive heat uptake process. We show that the average pattern of surface warming in CMIP5 damps passive ocean heat uptake efficiency by nearly 25%, as compared to homogeneous surface warming. This “pattern effect” occurs because strong ventilation and weak surface warming are robustly colocated, particularly in the Southern Ocean. However, variations in warming patterns across CMIP5 do not drive significant ensemble spread in passive ocean heat uptake efficiency. This spread is likely linked to intermodel differences in ocean circulation, which our idealized results suggest may be dominated by differences in Southern Ocean and subtropical ventilation processes

Influence of GEOTRACES data distribution and misfit function choice on objective parameter retrieval in a marine zinc cycle model

Biogeochemical model behaviour for micronutrients is typically hard to constrain because of the sparsity of observational data, the difficulty of determining parameters in situ, and uncertainties in observations and models. Here, we assess the influence of data distribution, model uncertainty, and the misfit function on objective parameter optimisation in a model of the oceanic cycle of zinc (Zn), an essential micronutrient for marine phytoplankton with a long whole-ocean residence time. We aim to investigate whether observational constraints are sufficient for reconstruction of biogeochemical model behaviour, given that the Zn data coverage provided by the GEOTRACES Intermediate Data Product 2017 is sparse. Furthermore, we aim to assess how optimisation results are affected by the choice of the misfit function and by confounding factors such as analytical uncertainty in the data or biases in the model related to either seasonal variability or the larger-scale circulation. The model framework applied herein combines a marine Zn cycling model with a state-of-the-art estimation of distribution algorithm (Covariance Matrix Adaption Evolution Strategy, CMA-ES) to optimise the model towards synthetic data in an ensemble of 26 optimisations. Provided with a target field that can be perfectly reproduced by the model, optimisation retrieves parameter values perfectly regardless of data coverage. As differences between the model and the system underlying the target field increase, the choice of the misfit function can greatly impact optimisation results, while limitation of data coverage is in most cases of subordinate significance. In cases where optimisation to full or limited data coverage produces relatively distinct model behaviours, we find that applying a misfit metric that compensates for differences in data coverage between ocean basins considerably improves agreement between optimisation results obtained with the two data situations

Evaluation of the Transport Matrix Method for simulation of ocean biogeochemical tracers

Conventional integration of Earth system and ocean models can accrue considerable computational expenses, particularly for marine biogeochemical applications. "Offline" numerical schemes in which only the biogeochemical tracers are time stepped and transported using a pre-computed circulation field can substantially reduce the burden and are thus an attractive alternative. One such scheme is the "transport matrix method" (TMM), which represents tracer transport as a sequence of sparse matrix–vector products that can be performed efficiently on distributed-memory computers. While the TMM has been used for a variety of geochemical and biogeochemical studies, to date the resulting solutions have not been comprehensively assessed against their "online" counterparts. Here, we present a detailed comparison of the two. It is based on simulations of the state-of-the-art biogeochemical sub-model embedded within the widely used coarse-resolution University of Victoria Earth System Climate Model (UVic ESCM). The default, non-linear advection scheme was first replaced with a linear, third-order upwind-biased advection scheme to satisfy the linearity requirement of the TMM. Transport matrices were extracted from an equilibrium run of the physical model and subsequently used to integrate the biogeochemical model offline to equilibrium. The identical biogeochemical model was also run online. Our simulations show that offline integration introduces some bias to biogeochemical quantities through the omission of the polar filtering used in UVic ESCM and in the offline application of time-dependent forcing fields, with high latitudes showing the largest differences with respect to the online model. Differences in other regions and in the seasonality of nutrients and phytoplankton distributions are found to be relatively minor, giving confidence that the TMM is a reliable tool for offline integration of complex biogeochemical models. Moreover, while UVic ESCM is a serial code, the TMM can be run on a parallel machine with no change to the underlying biogeochemical code, thus providing orders of magnitude speed-up over the online model

Temporal and spatial perspectives on the fate of anthropogenic carbon : a carbon cycle slide deck for broad audiences

This slide deck was developed to inform broader scientific, as well as general audiences about the role of the ocean in the global carbon cycle, including key sinks and sources of anthropogenic carbon and how they have evolved through time and space

An estimate of the eddy-induced circulation in the Labrador Sea

Regions of oceanic deep convection such as the Labrador Sea are prone to baroclinic instability. The resulting geostrophic eddies play a crucial role in the post-convection adjustment process which involves both rearrangement of mass so as to release available potential energy and exchange of heat and salt with the boundaries. In this study it is proposed that the slumping of isopycnals associated with baroclinic instability drives an eddy-induced 'overturning circulation' consisting of a surface intensified flow transporting low salinity water from the boundary currents into the interior; sinking motion in the interior; and an 'outflow' at depth transporting newly ventilated Labrador Sea Water towards the boundaries. Typical eddy-induced velocities estimated from hydrographic data are roughly 0.5 cm/s for the surface inflow, 1 m/day for the vertical motion, and 0.1 cm/s for the deeper outflow, in close agreement with those calculated in a numerical model

Controls over Ocean Mesopelagic Interior Carbon Storage (COMICS): Fieldwork, Synthesis, and Modeling Efforts

The ocean's biological carbon pump plays a central role in regulating atmospheric CO2 levels. In particular, the depth at which sinking organic carbon is broken down and respired in the mesopelagic zone is critical, with deeper remineralization resulting in greater carbon storage. Until recently, however, a balanced budget of the supply and consumption of organic carbon in the mesopelagic had not been constructed in any region of the ocean, and the processes controlling organic carbon turnover are still poorly understood. Large-scale data syntheses suggest that a wide range of factors can influence remineralization depth including upper-ocean ecological interactions, and interior dissolved oxygen concentration and temperature. However, these analyses do not provide a mechanistic understanding of remineralization, which increases the challenge of appropriately modeling the mesopelagic carbon dynamics. In light of this, the UK Natural Environment Research Council has funded a programme with this mechanistic understanding as its aim, drawing targeted fieldwork right through to implementation of a new parameterization for mesopelagic remineralization within an IPCC class global biogeochemical model. The Controls over Ocean Mesopelagic Interior Carbon Storage (COMICS) programme will deliver new insights into the processes of carbon cycling in the mesopelagic zone and how these influence ocean carbon storage. Here we outline the programme's rationale, its goals, planned fieldwork, and modeling activities, with the aim of stimulating international collaboration