Environmental controls on the light use efficiency of terrestrial gross primary production

Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf-level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy-level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed-effects model. The same model design was fitted to site-based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies

TOPOGRAPHIC WAVES IN OPEN DOMAINS .2. BAY MODES AND RESONANCES

The topographic wave equation is solved in a domain consisting of a channel with a terminating bay zone. For exponential depth profiles the problem reduces to an algebraic eigenvalue problem. In a flat channel adjacent to a shelf–like bay zone the solutions form a countably infinite set of orthogonal bay modes: the spectrum of eigenfrequencies is purely discrete. A channel with transverse topography allows wave propagation towards and away from the bay: the spectrum has a continuous part below the cutoff frequency of free channel waves. Above this cutoff frequency a finite number (possibly zero) of bay-trapped solutions occur. Bounds for this number are given. At particular frequencies below the cutoff the system is in resonance with the incident wave. These resonances are shown to be associated with bay modes

THE TRAPPING AND SCATTERING OF TOPOGRAPHIC WAVES BY ESTUARIES AND HEADLANDS

This paper extends recent theoretical work on sub-inertial trapped modes in bays to consider trapping of energy in the neighbourhood of estuary mouths on coastal shelves. The qualitative form of the theoretical predictions accords well with recent observations on the Scotian Shelf that show energy trapped near the Laurentian Channel at a frequency higher than that of the propagating waves on the shelf.The trapping and scattering of shelf waves is modelled for a shelf-estuary or shelf-headland system by considering barotropic waves in a straight, infinite channel with an attached rectangular estuary or interrupted by a rectangular headland. Taking the depth to increase exponentially with distance from the coast and expanding in cross-shelf modes reduces the problem to a system of real linear algebraic equations.Trapped modes with frequencies above the cutoff frequency of propagating waves are found near the mouth of the estuary. Waves propagating towards the estuary are strongly scattered and, for particular frequencies, incident energy can be either perfectly transmitted or totally reflected. An incident wave can be in resonance with the estuary causing energy to penetrate the estuary. Bounds on the frequencies of trapped and resonant solutions are given and allow an easy modal interpretation.If the frequency of an incident wave is sufficiently high, waves cannot propagate past a headland. Energy at these frequencies can however tunnel through the region and appear as an attenuated wave on the far side. For particular frequencies all energy passes the headland and none is reflected. For headlands long compared with the incident wave, transmission coefficients for single-mode scattering follow from spatially one-dimensional wave mechanics

Destabilization of the thermohaline circulation by transient perturbations to the hydrological cycle

We reconsider the problem of the stability of the thermohaline circulation as described by a two-dimensional Boussinesq model with mixed boundary conditions. We determine how the stability properties of the system depend on the intensity of the hydrological cycle. We define a two-dimensional parameters' space descriptive of the hydrology of the system and determine, by considering suitable quasi-static perturbations, a bounded region where multiple equilibria of the system are realized. We then focus on how the response of the system to finite-amplitude surface freshwater forcings depends on their rate of increase. We show that it is possible to define a robust separation between slow and fast regimes of forcing. Such separation is obtained by singling out an estimate of the critical growth rate for the anomalous forcing, which can be related to the characteristic advective time scale of the system.Comment: 37 pages, 8 figures, submitted to Clim. Dy

Supporting cross-domain system-level environmental and earth science

Answering the key challenges for society due to environmental issues like climate change, pollution and loss of biodiversity, and making the right decisions to tackle these in a cost-efficient and sustainable way requires scientific understanding of the Earth System. This scientific knowledge can then be used to inform the general public and policymakers. Scientific understanding starts with having available the right data, often in the form of observations. Research Infrastructures (RIs) exist to perform these observations in the required quality and to make the data available to first of all the researchers. In the current Big Data era, the increasing challenge is to provide the data in an interoperable and machine-readable and understandable form. The European RIs on environment formed a project cluster called ENVRI that tackles these issues. In this chapter, we introduce the societal relevance of the environmental data produced by the RIs and discuss the issues at hand in providing the relevant data according to the so-called FAIR principles

The influence of ocean variations on the climate of Ireland

The influence of the ocean circulation on the climate of Ireland is more subtle than it first appears. Temperatures in Ireland are warmer than similar Pacific maritime climates. It is heat - carried primarily in the Atlantic overturning circulation - released over the Atlantic that provides this additional warmth. We investigate variations in Irish climate using long-term station-based time series. The Atlantic multidecadal oscillation (AMO) explains over 90% of the pronounced decadal temperature and summer precipitation variation. Understanding the impact of these ocean variations when interpreting long climate records, particularly in the context of a changing climate, is crucial

Characterising half a degree difference: a review of methods for identifying regional climate responses to global warming targets

The Paris Agreement long term global temperature goal refers to two global warming levels: well below 2°C and 1.5°C above preindustrial. Regional climate signals at specific global warming levels, and especially the differences between 1.5°C and 2°C, are not well constrained, however. In particular, methodological challenges related to the assessment of such differences have received limited attention. This paper reviews alternative approaches for identifying regional climate signals associated with global temperature limits, and evaluates the extent to which they constitute a sound basis for impacts analysis. Four methods are outlined, including comparing data from different greenhouse gas scenarios, sub-selecting climate models based on global temperature response, pattern scaling, and extracting anomalies at the time of each global temperature increment. These methods have rarely been applied to compare 2°C with 1.5°C, but some demonstrate potential avenues for useful research. Nevertheless, there are methodological challenges associated with the use of existing climate model experiments, which are generally designed to model responses to different levels of greenhouse gas forcing, rather than to model climate responses to a specific level of forcing that targets a given level of global temperature change. Novel approaches may be required to address policy questions, in particular: to differentiate between half degree warming increments while accounting for different sources of uncertainty; to examine mechanisms of regional climate change including the potential for nonlinear responses; and to explore the relevance of time-lagged processes in the climate system and declining emissions, and the resulting sensitivity to alternative mitigation pathways

Millennial changes in North American wildfire and soil activity over the last glacial cycle

Climate changes in the North Atlantic region during the last glacial cycle were dominated by the slow waxing and waning of the North American ice sheet as well as by intermittent, millennial-scale Dansgaard-Oeschger climate oscillations. However, prior to the last deglaciation, the responses of North American vegetation and biomass burning to these climate variations are uncertain. Ammonium in Greenland ice cores, a product from North American soil emissions and biomass burning events, can help to fill this gap. Here we use continuous, high-resolution measurements of ammonium concentrations between 110,000 to 10,000 years ago from the Greenland NGRIP and GRIP ice cores to reconstruct North American wildfire activity and soil ammonium emissions. We find that on orbital timescales soil emissions increased under warmer climate conditions when vegetation expanded northwards into previously ice-covered areas. For millennial-scale interstadial warm periods during Marine Isotope Stage 3, the fire recurrence rate increased in parallel to the rapid warmings, whereas soil emissions rose more slowly, reflecting slow ice shrinkage and delayed ecosystem changes. We conclude that sudden warming events had little impact on soil ammonium emissions and ammonium transport to Greenland, but did result in a substantial increase in the frequency of North American wildfires

High-resolution mineral dust and sea ice proxy records from the Talos Dome ice core

In this study we report on new non-sea salt calcium (nssCa2+, mineral dust proxy) and sea salt sodium (ssNa+, sea ice proxy) records along the East Antarctic Talos Dome deep ice core in centennial resolution reaching back 150 thousand years (ka) before present. During glacial conditions nssCa2+ fluxes in Talos Dome are strongly related to temperature as has been observed before in other deep Antarctic ice core records, and has been associated with synchronous changes in the main source region (southern South America) during climate variations in the last glacial. However, during warmer climate conditions Talos Dome mineral dust input is clearly elevated compared to other records mainly due to the contribution of additional local dust sources in the Ross Sea area. Based on a simple transport model, we compare nssCa2+ fluxes of different East Antarctic ice cores. From this multi-site comparison we conclude that changes in transport efficiency or atmospheric lifetime of dust particles do have a minor effect compared to source strength changes on the large-scale concentration changes observed in Antarctic ice cores during climate variations of the past 150 ka. Our transport model applied on ice core data is further validated by climate model data. The availability of multiple East Antarctic nssCa2+ records also allows for a revision of a former estimate on the atmospheric CO2 sensitivity to reduced dust induced iron fertilisation in the Southern Ocean during the transition from the Last Glacial Maximum to the Holocene (T1). While a former estimate based on the EPICA Dome C (EDC) record only suggested 20 ppm, we find that reduced dust induced iron fertilisation in the Southern Ocean may be responsible for up to 40 ppm of the total atmospheric CO2 increase during T1. During the last interglacial, ssNa+ levels of EDC and EPICA Dronning Maud Land (EDML) are only half of the Holocene levels, in line with higher temperatures during that period, indicating much reduced sea ice extent in the Atlantic as well as the Indian Ocean sector of the Southern Ocean. In contrast, Holocene ssNa+ flux in Talos Dome is about the same as during the last interglacial, indicating that there was similar ice cover present in the Ross Sea area during MIS 5.5 as during the Holocene

Stochastic climate theory and modeling

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models