Global instability in the Ghil--Sellers model

The Ghil--Sellers model, a diffusive one-dimensional energy balance model of Earth's climate, features---for a considerable range of the parameter descriptive of the intensity of the incoming radiation---two stable climate states, where the bistability results from the celebrated ice-albedo feedback. The warm state is qualitatively similar to the present climate, while the cold state corresponds to snowball conditions. Additionally, in the region of bistability, one can find unstable climate states. We find such unstable states by applying for the first time in a geophysical context the so-called edge tracking method, which has been used for studying multiple coexisting states in shear flows. This method has a great potential for studying the global instabilities in multistable systems, and for providing crucial information on the possibility of transitions when forcing is present. We examine robustness, efficiency, and accuracy properties of the edge tracking algorithm. We find that the procedure is the most efficient when taking a single bisection per cycle. Due to the strong diffusivity of the system, the transient dynamics, is approximately confined to the heteroclininc trajectory, connecting the fixed unstable and stable states, after relatively short transient times. Such a constraint dictates a functional relationship between observables. We characterize such a relationship between the global average temperature and a descriptor of nonequilibrium thermodynamics, the large scale temperature gradient between low and high latitudes. We find that a maximum of the temperature gradient is realized at the same value of the average temperature, about 270 K, largely independent of the strength of incoming solar radiation. Due to this maximum, a transient increase and nonmonotonic evolution of the temperature gradient is possible and not untypical. We also examine the structural properties of the system defined by bifurcation diagrams describing the equilibria depending on a system parameter of interest, here the solar strength. We construct new bifurcation diagrams in terms of quantities relevant for describing thermodynamic properties such as the temperature gradient and the material entropy production due to heat transport. We compare our results for the energy balance model to results for the intermediate complexity general circulation model the Planet Simulator and find an interesting qualitative agreement

The increasing importance of atmospheric demand for ecosystem water and carbon fluxes

Soil moisture supply and atmospheric demand for water independently limit—and profoundly affect—vegetation productivity and water use during periods of hydrologic stress1, 2, 3, 4. Disentangling the impact of these two drivers on ecosystem carbon and water cycling is difficult because they are often correlated, and experimental tools for manipulating atmospheric demand in the field are lacking. Consequently, the role of atmospheric demand is often not adequately factored into experiments or represented in models5, 6, 7. Here we show that atmospheric demand limits surface conductance and evapotranspiration to a greater extent than soil moisture in many biomes, including mesic forests that are of particular importance to the terrestrial carbon sink8, 9. Further, using projections from ten general circulation models, we show that climate change will increase the importance of atmospheric constraints to carbon and water fluxes in all ecosystems. Consequently, atmospheric demand will become increasingly important for vegetation function, accounting for >70% of growing season limitation to surface conductance in mesic temperate forests. Our results suggest that failure to consider the limiting role of atmospheric demand in experimental designs, simulation models and land management strategies will lead to incorrect projections of ecosystem responses to future climate conditions

Potential effects of warmer worms and vectors on onchocerciasis transmission in West Africa

Development times of eggs, larvae and pupae of vectors of onchocerciasis (Simulium spp.) and of Onchocerca volvulus larvae within the adult females of the vectors decrease with increasing temperature. At and above 25C,the parasite could reach its infective stage in less than 7 days when vectors could transmit after only two gonotrophic cycles. After incorporating exponential functions for vector development into a novel blackfly population model, it was predicted that fly numbers in Liberia and Ghana would peak at air temperatures of 29C and 34C, about 3C and 7C above current monthly averages, respectively; parous rates of forest flies (Liberia) would peak at 298C and of savannah flies (Ghana) at 308C. Small temperature increases (less than 28C) might lead to changes in geographical distributions of different vector taxa. When the new model was linked to an existing framework for the population dynamics of onchocerciasis in humans and vectors, transmission rates and worm loads were projected to increase with temperature to at least 338C. By contrast, analyses of field data on forest flies in Liberia and savannah flies in Ghana, in relation to regional climate change predictions, suggested, on the basis of simple regressions, that 13–41% decreases in fly numbers would be expected between the present and before 2040. Further research is needed to reconcile these conflicting conclusions

Mechanics and thermodynamics of a new minimal model of the atmosphere

The understanding of the fundamental properties of the climate system has long benefitted from the use of simple numerical models able to parsimoniously represent the essential ingredients of its processes. Here, we introduce a new model for the atmosphere that is constructed by supplementing the now-classic Lorenz ’96 one-dimensional lattice model with temperature-like variables. The model features an energy cycle that allows for energy to be converted between the kinetic form and the potential form and for introducing a notion of efficiency. The model’s evolution is controlled by two contributions—a quasi-symplectic and a gradient one, which resemble (yet not conforming to) a metriplectic structure. After investigating the linear stability of the symmetric fixed point, we perform a systematic parametric investigation that allows us to define regions in the parameters space where at steady-state stationary, quasi-periodic, and chaotic motions are realised, and study how the terms responsible for defining the energy budget of the system depend on the external forcing injecting energy in the kinetic and in the potential energy reservoirs. Finally, we find preliminary evidence that the model features extensive chaos. We also introduce a more complex version of the model that is able to accommodate for multiscale dynamics and that features an energy cycle that more closely mimics the one of the Earth’s atmosphere

Mediterranean-climate streams and rivers: geographically separated but ecologically comparable freshwater systems

Streams and rivers in mediterranean-climate regions (med-rivers in med-regions) are ecologically unique, with flow regimes reflecting precipitation patterns. Although timing of drying and flooding is predictable, seasonal and annual intensity of these events is not. Sequential flooding and drying, coupled with anthropogenic influences make these med-rivers among the most stressed riverine habitat worldwide. Med-rivers are hotspots for biodiversity in all med-regions. Species in med-rivers require different, often opposing adaptive mechanisms to survive drought and flood conditions or recover from them. Thus, metacommunities undergo seasonal differences, reflecting cycles of river fragmentation and connectivity, which also affect ecosystem functioning. River conservation and management is challenging, and trade-offs between environmental and human uses are complex, especially under future climate change scenarios. This overview of a Special Issue on med-rivers synthesizes information presented in 21 articles covering the five med-regions worldwide: Mediterranean Basin, coastal California, central Chile, Cape region of South Africa, and southwest and southern Australia. Research programs to increase basic knowledge in less-developed med-regions should be prioritized to achieve increased abilities to better manage med-rivers

Analysis of a bistable climate toy model with physics-based machine learning methods

We propose a comprehensive framework able to address both the predictability of the first and of the second kind for high-dimensional chaotic models. For this purpose, we analyse the properties of a newly introduced multistable climate toy model constructed by coupling the Lorenz ’96 model with a zero-dimensional energy balance model. First, the attractors of the system are identified with Monte Carlo Basin Bifurcation Analysis. Additionally, we are able to detect the Melancholia state separating the two attractors. Then, Neural Ordinary Differential Equations are applied to predict the future state of the system in both of the identified attractors