996 resultados para Moorland hydrology
Resumo:
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.
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We explore the potential predictability of rapid changes in the Atlantic meridional overturning circulation (MOC) using a coupled global climate model (HadCM3). Rapid changes in the temperature and salinity of surface water in the Nordic Seas, and the flow of dense water through Denmark Strait, are found to be precursors to rapid changes in the model's MOC, with a lead time of around 10 years. The mechanism proposed to explain this potential predictability relies on the development of density anomalies in the Nordic Seas which propagate through Denmark Strait and along the deep western boundary current, affecting the overturning. These rapid changes in the MOC have significant, and widespread, climate impacts which are potentially predictable a few years ahead. Whilst the flow through Denmark Strait is too strong in HadCM3, the presence of such potential predictability motivates the monitoring of water properties in the Nordic Seas and Denmark Strait.
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FAMOUS is an ocean-atmosphere general circulation model of low resolution, capable of simulating approximately 120 years of model climate per wallclock day using current high performance computing facilities. It uses most of the same code as HadCM3, a widely used climate model of higher resolution and computational cost, and has been tuned to reproduce the same climate reasonably well. FAMOUS is useful for climate simulations where the computational cost makes the application of HadCM3 unfeasible, either because of the length of simulation or the size of the ensemble desired. We document a number of scientific and technical improvements to the original version of FAMOUS. These improvements include changes to the parameterisations of ozone and sea-ice which alleviate a significant cold bias from high northern latitudes and the upper troposphere, and the elimination of volume-averaged drifts in ocean tracers. A simple model of the marine carbon cycle has also been included. A particular goal of FAMOUS is to conduct millennial-scale paleoclimate simulations of Quaternary ice ages; to this end, a number of useful changes to the model infrastructure have been made.
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Idealized, convection-resolving simulations of moist orographic flows are conducted to investigate the influence of temperature and moist stability on the drying ratio (DR), defined as the fraction of the impinging water mass removed as orographic precipitation. In flow past a long ridge, where most of the air rises over the barrier rather than detouring around it, DR decreases as the surface temperature (Ts) increases, even as the orographic cap cloud becomes statically unstable at higher Ts and develops embedded convection. This behaviour is explained by a few physical principles: (1) the Clausius–Clapeyron equation dictates that the normalized condensation rate decreases as the flow gets warmer, (2) the replacement of ice-phase precipitation growth with warm-rain processes decreases the efficiency by which condensate is converted to precipitation, thereby lowering precipitation efficiency, and (3) embedded convection acts more to vertically redistribute moisture than to enhance precipitation. Over an isolated mountain, the effects of (1) and (2) are counteracted by moisture deflection around the barrier, which is stronger in the colder, more stable flows.
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Stratospheric Sounding Units (SSU) on the NOAA operational satellites have been the main source of near global temperature trend data above the lower stratosphere. They have been used extensively for comparison with model-derived trends. The SSU senses in the 15 micron band of CO2 and hence the weighting function is sensitive to changes in CO2 concentrations. The impact of this change in weighting function has been ignored in all recent trend analyses. We show that the apparent trends in global mean brightness temperature due to the change in weighting function vary from about -0.4 K/decade to 0.4 K/decade depending on the altitude sensed by the different SSU channels. For some channels, this apparent trend is of a similar size to the trend deduced from SSU data but ignoring the change in weighting function. In the mid-stratosphere, the revised trends are now significantly more negative and in better agreement with model-calculated trends.
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The tropospheric response to midlatitude SST anomalies has been investigated through a series of aquaplanet simulations using a high-resolution version of the Hadley Centre atmosphere model (HadAM3) under perpetual equinox conditions. Model integrations show that increases in the midlatitude SST gradient generally lead to stronger storm tracks that are shifted slightly poleward, consistent with changes in the lower-tropospheric baroclinicity. The large-scale atmospheric response is, however, highly sensitive to the position of the SST gradient anomaly relative to that of the subtropical jet in the unperturbed atmosphere. In particular, when SST gradients are increased very close to the subtropical jet, then the Hadley cell and subtropical jet is strengthened while the storm track and eddy-driven jet are shifted equatorward. Conversely, if the subtropical SST gradients are reduced and the midlatitude gradients increased, then the storm track shows a strong poleward shift and a well-separated eddy-driven jet is produced. The sign of the SST anomaly is shown to play a secondary role in determining the overall tropospheric response. These findings are used to provide a new and consistent interpretation of some previous GCM studies concerning the atmospheric response to midlatitude SST anomalies.
North Atlantic weather regimes response to Indian-western Pacific Ocean warming: A multi-model study