No changes in overall AMOC strength in interglacial PMIP4 time slices

The Atlantic Meridional Overturning Circulation (AMOC) is a key mechanism of poleward heat transport and an important part of the global climate system. How it responded to past changes in forcing, such as those experienced during Quaternary interglacials, is an intriguing and open question. Previous modelling studies suggest an enhanced AMOC in the mid-Holocene compared to the preindustrial period. In earlier simulations from the Palaeoclimate Modelling Intercomparison Project (PMIP), this arose from feedbacks between sea ice and AMOC changes, which were dependent on resolution. Here we present an initial analysis of recently available PMIP4 simulations for three experiments representing different interglacial conditions – one 127 000 years ago within the Last Interglacial (127 ka, called lig127k), one in the middle of the Holocene (midHolocene, 6 ka), and a preindustrial control simulation (piControl, 1850 CE). Both lig127k and midHolocene have altered orbital configurations compared to piControl. The ensemble mean of the PMIP4 models shows the strength of the AMOC does not markedly change between the midHolocene and piControl experiments or between the lig127k and piControl experiments. Therefore, it appears orbital forcing itself does not alter the overall AMOC. We further investigate the coherency of the forced response in AMOC across the two interglacials, along with the strength of the signal, using eight PMIP4 models which performed both interglacial experiments. Only two models show a stronger change with the stronger forcing, but those models disagree on the direction of the change. We propose that the strong signals in these two models are caused by a combination of forcing and the internal variability. After investigating the AMOC changes in the interglacials, we further explored the impact of AMOC on the climate system, especially on the changes in the simulated surface temperature and precipitation. After identifying the AMOC's fingerprint on the surface temperature and rainfall, we demonstrate that only a small percentage of the simulated surface climate changes could be attributed to the AMOC. Proxy records of sedimentary ratio during the two interglacial periods both show a similar AMOC strength compared to the preindustrial, which fits nicely with the simulated results. Although the overall AMOC strength shows minimal changes, future work is required to explore whether this occurs through compensating variations in the different components of AMOC (such as Iceland–Scotland overflow water). This line of evidence cautions against interpreting reconstructions of past interglacial climate as being driven by AMOC, outside of abrupt events

Characterizing Spatial Structure in Climate Model Ensembles

This paper presents a methodology that is designed for rapid exploratory analysis of the outputs from ensembles of climate models, especially when these outputs consist of maps. The approach formalizes and extends the technique of “intermodel empirical orthogonal function” analysis, combining multivariate analysis of variance techniques with singular value decompositions (SVDs) of structured components of the ensemble data matrix. The SVDs yield spatial patterns associated with these components, which we call ensemble principal patterns (EPPs). A unique hierarchical partitioning of variation is obtained for balanced ensembles in which all combinations of factors, such as GCM and RCM pairs in a regional ensemble, appear with equal frequency: suggestions are also proposed to handle unbalanced ensembles without imputing missing values or discarding runs. Applications include the selection of ensemble members to propagate uncertainty into subsequent analyses, and the diagnosis of modes of variation associated with specific model variants or parameter perturbations. The approach is illustrated using outputs from the EuroCORDEX regional ensemble over the United Kingdom

Variability of surface climate in simulations of past and future

It is virtually certain that the mean surface temperature of the Earth will continue to increase under realistic emission scenarios, yet comparatively little is known about future changes in climate variability. This study explores changes in climate variability over the large range of climates simulated by the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5/6) and the Paleoclimate Modeling Intercomparison Project Phase 3 (PMIP3), including time slices of the Last Glacial Maximum, the mid-Holocene, and idealized experiments (1 % CO2 and abrupt4×CO2). These states encompass climates within a range of 12 ∘C in global mean temperature change. We examine climate variability from the perspectives of local interannual change, coherent climate modes, and through compositing extremes. The change in the interannual variability of precipitation is strongly dependent upon the local change in the total amount of precipitation. At the global scale, temperature variability is inversely related to mean temperature change on intra-seasonal to multidecadal timescales. This decrease is stronger over the oceans, while there is increased temperature variability over subtropical land areas (40∘ S–40∘ N) in warmer simulations. We systematically investigate changes in the standard deviation of modes of climate variability, including the North Atlantic Oscillation, the El Niño–Southern Oscillation, and the Southern Annular Mode, with global mean temperature change. While several climate modes do show consistent relationships (most notably the Atlantic Zonal Mode), no generalizable pattern emerges. By compositing extreme precipitation years across the ensemble, we demonstrate that the same large-scale modes influencing rainfall variability in Mediterranean climates persist throughout paleoclimate and future simulations. The robust nature of the response of climate variability, between cold and warm climates as well as across multiple timescales, suggests that observations and proxy reconstructions could provide a meaningful constraint on climate variability in future projections

Characterization of the stimulators of protein-directed ribosomal frameshifting in Theiler's murine encephalomyelitis virus.

Many viruses utilize programmed -1 ribosomal frameshifting (-1 PRF) to express additional proteins or to produce frameshift and non-frameshift protein products at a fixed stoichiometric ratio. PRF is also utilized in the expression of a small number of cellular genes. Frameshifting is typically stimulated by signals contained within the mRNA: a 'slippery' sequence and a 3'-adjacent RNA structure. Recently, we showed that -1 PRF in encephalomyocarditis virus (EMCV) is trans-activated by the viral 2A protein, leading to a temporal change in PRF efficiency from 0% to 70% during virus infection. Here we analyzed PRF in the related Theiler's murine encephalomyelitis virus (TMEV). We show that 2A is also required for PRF in TMEV and can stimulate PRF to levels as high as 58% in rabbit reticulocyte cell-free translations and 81% during virus infection. We also show that TMEV 2A trans-activates PRF on the EMCV signal but not vice versa. We present an extensive mutational analysis of the frameshift stimulators (mRNA signals and 2A protein) analysing activity in in vitro translation, electrophoretic mobility shift and in vitro ribosome pausing assays. We also investigate the PRF mRNA signal with RNA structure probing. Our results substantially extend previous characterization of protein-stimulated PRF

Climate-groundwater dynamics inferred from GRACE and the role of hydraulic memory

Groundwater is the largest store of freshwater on Earth after the cryosphere and provides a substantial proportion of the water used for domestic, irrigation and industrial purposes. Knowledge of this essential resource remains incomplete, in part, because of observational challenges of scale and accessibility. Here we examine a 14-year period (2002–2016) of GRACE observations to investigate climate-groundwater dynamics of 14 tropical and sub-tropical aquifers selected from WHYMAP's 37 large aquifer systems of the world. GRACE-derived changes in groundwater storage resolved using GRACE JPL Mascons and the CLM Land Surface Model are related to precipitation time series and regional-scale hydrogeology. We show that aquifers in dryland environments exhibit long-term hydraulic memory through a strong correlation between groundwater storage changes and annual precipitation anomalies integrated over the time series; aquifers in humid environments show short-term memory through strong correlation with monthly precipitation. This classification is consistent with estimates of Groundwater Response Times calculated from the hydrogeological properties of each system, with long (short) hydraulic memory associated with slow (rapid) response times. The results suggest that groundwater systems in dryland environments may be less sensitive to seasonal climate variability but vulnerable to long-term trends from which they will be slow to recover. In contrast, aquifers in humid regions may be more sensitive to seasonal climate disturbances such as ENSO-related drought but may also be relatively quick to recover. Exceptions to this general pattern are traced to human interventions through groundwater abstraction. Hydraulic memory is an important factor in the management of groundwater resources, particularly under climate change

Analysing the PMIP4-CMIP6 collection: a workflow and tool (pmip_p2fvar_analyzer v1)

Experiment outputs are now available from the Coupled Model Intercomparison Project's sixth phase (CMIP6) and the past climate experiments defined in the Palaeoclimate Modelling Intercomparison Project's fourth phase (PMIP4). All of this output is freely available from the Earth System Grid Federation (ESGF). Yet there is overhead in analysing this resource that may prove complicated or prohibitive. Here we document the steps taken by ourselves to produce ensemble analyses covering past and future simulations. We outline the strategy used to curate, adjust the monthly calendar aggregation and process the information downloaded from the ESGF. The results of these steps were used to perform analysis for several of the initial publications arising from PMIP4. We provide post-processed fields for each simulation, such as climatologies and common measures of variability. Example scripts used to visualise and analyse these fields are provided for several important case studies

Assessing the epidemic potential of RNA and DNA viruses

Many new and emerging RNA and DNA viruses are zoonotic or have zoonotic origins in an animal reservoir that is usually mammalian and sometimes avian. Not all zoonotic viruses are transmissible (directly or by an arthropod vector) between human hosts. Virus genome sequence data provide the best evidence of transmission. Of human transmissible virus, 37 species have so far been restricted to self-limiting outbreaks. These viruses are priorities for surveillance because relatively minor changes in their epidemiologies can potentially lead to major changes in the threat they pose to public health. On the basis of comparisons across all recognized human viruses, we consider the characteristics of these priority viruses and assess the likelihood that they will further emerge in human populations. We also assess the likelihood that a virus that can infect humans but is not capable of transmission (directly or by a vector) between human hosts can acquire that capability