The probability of rapid climate change

If you look at a map of the air temperature of the surface of the Earth, you will see that North West Europe, including the UK, is warmer than Alaska, which is at the same latitude but on the Pacific rather than Atlantic Ocean. At school you were probably told that this was because of the Gulf Stream. However, there is a very similar current in the Pacific—the Kuroshio—which takes warm water north past Japan and then out into the Atlantic. Peter Challenor asks: What is the unique feature of the Atlantic that keeps us warm and could it change in the next few years?<br/

SOFT feature-tracking software handbook

This handbook (SOFT_WP31_handbook.pdf) describes the suite of MATLAB programs developed within Work Package 3, task 3.1 of the SOFT Project, for the tracking of large-scale, westward propagating features (planetary waves or westward-travelling eddies) in altimeter data and the removal of the identified features from the datasets. The suite has been applied to TOPEX/POSEIDON data over the Azores region (one of the SOFT study regions) but its modularity makes it adaptable in a straightforward way to other datasets and other regions. The companion to this handbook is the progress report on task 3.1 released in January 2003 (SOFT_WP31_report.pdf), which presents the rationale to the study and gives ample details on the scheme adopted for the fitting of elementary waves (according to a Gaussian wave shape model) to altimeter data. A synopsis of the fitting scheme is briefly recalled in the following sections of this document, for the benefit of the reader. All the code listings are in the appendix. The forecasting of the westward-propagating fields (which is the object of task 3.2 in Work Package 3 id described in version 1 of another report, SOFT_WP32_rep1.pdf

SOFT Wave forecasting report - v.1.0

This report (SOFT_WP32_rep1.pdf) describes the first version of the wave forecasting code developed within Work Package 3, task 3.2 (implementation of a hybrid SOFT tracking system) of the SOFT Project. The forecasting of westward propagating signals (planetary waves or westward-travelling eddies), using the fields of tracked wave from Work Package 3, task 3.1, is one of the two components of the hybrid system which is the overall deliverable of task 3.2. The results presented here are provisional and are likely to be replaced as research proceeds. Related to this report are two other documents:- the progress report on task 3.1 released in January 2003(SOFT_WP31_report.pdf), which presents the rationale to the study and gives ample details on the scheme adopted for the fitting of elementary waves (according to a Gaussian wave shape model) to altimeter data (see also the paper by Cipollini, 2003);- the handbook SOFT_WP31_handbook.pdf describing the suite of MATLAB programs developed within Work Package 3, task 3.1 of the SOFTProject, for the tracking of large-scale, westward propagating features (planetary waves or westward-travelling eddies) in altimeter data and the removal of the identified features from the datasets. The suite has been applied to TOPEX/POSEIDON data over the Azores region (one of the SOFTstudy regions) and the output results have been used for the forecast

SOFT Development of feature tracking methods

The present report describes the work carried out within task 3.1 of Work Package 3 of the SOFT Project. The above task is ‘Development of feature tracking methods’ and consists of the development of a software to track large-scale, westward propagating features (planetary waves or westward-travelling eddies) in the altimetric datasets, and in the removal of the identified features from the datasets. The residual field (that is the original dataset minus the tracked features) is then made available to the other work packages in the Project

Emulating dynamic non-linear simulators using Gaussian processes

The dynamic emulation of non-linear deterministic computer codes where the output is a time series, possibly multivariate, is examined. Such computer models simulate the evolution of some real-world phenomenon over time, for example models of the climate or the functioning of the human brain. The models we are interested in are highly non-linear and exhibit tipping points, bifurcations and chaotic behaviour. However, each simulation run could be too time-consuming to perform analyses that require many runs, including quantifying the variation in model output with respect to changes in the inputs. Therefore, Gaussian process emulators are used to approximate the output of the code. To do this, the flow map of the system under study is emulated over a short time period. Then, it is used in an iterative way to predict the whole time series. A number of ways are proposed to take into account the uncertainty of inputs to the emulators, after fixed initial conditions, and the correlation between them through the time series. The methodology is illustrated with two examples: the highly non-linear dynamical systems described by the Lorenz and Van der Pol equations. In both cases, the predictive performance is relatively high and the measure of uncertainty provided by the method reflects the extent of predictability in each system

Predicting the Output From a Stochastic Computer Model When a Deterministic Approximation is Available

The analysis of computer models can be aided by the construction of surrogate models, or emulators, that statistically model the numerical computer model. Increasingly, computer models are becoming stochastic, yielding different outputs each time they are run, even if the same input values are used. Stochastic computer models are more difficult to analyse and more difficult to emulate - often requiring substantially more computer model runs to fit. We present a method of using deterministic approximations of the computer model to better construct an emulator. The method is applied to numerous toy examples, as well as an idealistic epidemiology model, and a model from the building performance field

Working with the unworkable – a trainee’s case of maternal mourning and ulcerative colitis

In this paper I describe a time-limited piece of work that I undertook as a trainee with a mother whose child had died. The client had developed serious ulcerative colitis and was referred to counselling because she was refusing an operation to treat it. I have conceptualised her illness as the embodiment of her experience of disintegration in grief. As a trainee, I found working in the transference difficult in this case, as though I was betraying the client in some way. The client’s failure to make herself better both from her disease and from mourning her daughter made her continue to feel like a victim. Understanding this as transference and drawing on relational psychoanalytic theory was key to being able to work with her and to begin to make links

Parameterizing the microbial loop: an experiment in reducing model complexity

The structure of the plankton food web in the upper mixed layer has important implications for the export of biogenic material from the euphotic zone. While the action of the microbial loop causes material to be recycled near the surface, activity of the larger zooplankton leads to a significant downward flux of material. The balance between these pathways must be properly represented in climate models to predict carbon export. However, the number of biogeochemical compartments available to represent the food web is limited by the need to couple biogeochemical models with general circulation models. A structurally simple model is therefore sought, with a number of free parameters, which can be constrained by available observations to produce reliable estimates of export.A step towards addressing this aim is described: an attempt is made to emulate the behavior of an 11 compartment model with an explicit microbial loop, using a 4 compartment model. The latter, incorporating a basic microbial loop parameterization, is derived directly from the 'true' model. The results are compared with equivalent results for a 4 compartment model with no representation of the microbial loop. These non-identical twin experiments suggest that export estimates from 4 compartment models are prone to serious biases in regions where the action of the microbial loop is significant. The basic parameterization shows some promise in addressing the problem but a more sophisticated parameterization would be needed to produce reliable estimates. Some recommendations are made for future research