Enhancement of ENSO variability by a weakened Atlantic thermohaline circulation in a coupled GCM

A coupled ocean–atmosphere general circulation model is used to investigate the modulation of El Niño–Southern Oscillation (ENSO) variability due to a weakened Atlantic thermohaline circulation (THC). The THC weakening is induced by freshwater perturbations in the North Atlantic, and leads to a well-known sea surface temperature dipole and a southward shift of the intertropical convergence zone (ITCZ) in the tropical Atlantic. Through atmospheric teleconnections and local coupled air–sea feedbacks, a meridionally asymmetric mean state change is generated in the eastern equatorial Pacific, corresponding to a weakened annual cycle, and westerly anomalies develop over the central Pacific. The westerly anomalies are associated with anomalous warming of SST, causing an eastward extension of the west Pacific warm pool particularly in August–February, and enhanced precipitation. These and other changes in the mean state lead in turn to an eastward shift of the zonal wind anomalies associated with El Niño events, and a significant increase in ENSO variability. In response to a 1-Sv (1 Sv ≡ 106 m3 s−1) freshwater input in the North Atlantic, the THC slows down rapidly and it weakens by 86% over years 50–100. The Niño-3 index standard deviation increases by 36% during the first 100-yr simulation relative to the control simulation. Further analysis indicates that the weakened THC not only leads to a stronger ENSO variability, but also leads to a stronger asymmetry between El Niño and La Niña events. This study suggests a role for an atmospheric bridge that rapidly conveys the influence of the Atlantic Ocean to the tropical Pacific and indicates that fluctuations of the THC can mediate not only mean climate globally but also modulate interannual variability. The results may contribute to understanding both the multidecadal variability of ENSO activity during the twentieth century and longer time-scale variability of ENSO, as suggested by some paleoclimate records.

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

Decadal predictability of the Atlantic Ocean in a coupled GCM: forecast skill and optimal perturbations using Linear Inverse Modelling

The decadal predictability of three-dimensional Atlantic Ocean anomalies is examined in a coupled global climate model (HadCM3) using a Linear Inverse Modelling (LIM) approach. It is found that the evolution of temperature and salinity in the Atlantic, and the strength of the meridional overturning circulation (MOC), can be effectively described by a linear dynamical system forced by white noise. The forecasts produced using this linear model are more skillful than other reference forecasts for several decades. Furthermore, significant non-normal amplification is found under several different norms. The regions from which this growth occurs are found to be fairly shallow and located in the far North Atlantic. Initially, anomalies in the Nordic Seas impact the MOC, and the anomalies then grow to fill the entire Atlantic basin, especially at depth, over one to three decades. It is found that the structure of the optimal initial condition for amplification is sensitive to the norm employed, but the initial growth seems to be dominated by MOC-related basin scale changes, irrespective of the choice of norm. The consistent identification of the far North Atlantic as the most sensitive region for small perturbations suggests that additional observations in this region would be optimal for constraining decadal climate predictions.

G-protein-coupled-receptor-mediated presynaptic inhibition in the cerebellum

Throughout the central nervous system a dominant form of inhibition of neurotransmitter release from presynaptic terminals is mediated by G-protein-coupled receptors (GPCRs). Neurotransmitter release is typically induced by action potentials (APs), but can also occur spontaneously. Presynaptic inhibition by GPCRs has been associated with modulation of voltage-dependent ion channels. However, electrophysiological recordings of spontaneous, AP-independent (so-called ‘miniature’) postsynaptic events reveal an additional, important form of GPCR-mediated presynaptic inhibition, distinct from effects on ionic conductances and consistent with a direct action on the vesicle release machinery. Recent studies suggest that such miniature events might be of physiological relevance not only in signalling but also in development. In the cerebellum, neurotransmitter release onto Purkinje cells occurs by AP-dependent and AP-independent pathways. Here, I focus on inhibitory synapses between interneurons and Purkinje cells, which are subject to strong, identifiable regulation by endogenous GPCR agonists, to consider mechanisms of GPCR-mediated presynaptic inhibition.