1,721,015 research outputs found
SOFT Development of feature tracking methods
Full text linkThe 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
SOFT feature-tracking software handbook
Full text linkThis 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
Full text linkThis 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
The effect of the nugget on Gaussian process emulators of computer models
No full textThe effect of a Gaussian process parameter known as the nugget, on the development of computer model emulators is investigated. The presence of the nugget results in an emulator that does not interpolate the data and attaches a non-zero uncertainty bound around them. The limits of this approximation are investigated theoretically, and it is shown that they can be as large as those of a least squares model with the same regression functions as the emulator, regardless of the nugget’s value. The likelihood of the correlation function parameters is also studied and two mode types are identified. Type I modes are characterised by an approximation error that is a function of the nugget and can therefore become arbitrarily small, effectively yielding an interpolating emulator. Type II modes result in emulators with a constant approximation error. Apart from a theoretical investigation of the limits of the approximation error, a practical method for automatically imposing restrictions on its extent is introduced. This is achieved by means of a penalty term that is added to the likelihood function, and controls the amount of unexplainable variability in the computer model. The main findings are illustrated on data from an Energy Balance climate model
A space-time model for joint modeling of ocean temperature and salinity levels as measured by Argo Floats
Full text linkThe world's climate is to a large extent driven by the transport of heat and fresh water in the oceans. Regular monitoring, studying, understanding and forecasting of temperature and salinity at different depths of the oceans are a great scientific challenge. Temperature at the ocean surface can be measured from space. However salinity cannot yet be measured by satellites, and space-based measurements can only ever give us values at the surface. Until recently temperature and salinity measurements within the oceans have had to come from expensive research ships. The Argo float program has been funded by various nations to collect actual measurements and rectify this problem.A Bayesian hierarchical model is proposed in this paper describing the spatio-temporal behaviour of the joint distribution of temperature and salinity levels. The model is obtained as a kernel-convolution effect of a single latent spatio-temporal process. Additional terms in the mean describe non-stationarity arising in time and space. Predictive Bayesian model selection criteria have been used to validate the models using data for the year 2003. Illustrative annual prediction maps along with their uncertainty maps are also obtained. The Markov chain Monte Carlo methods are used throughout in the implementation<br/
Extreme wave heights in the North Atlantic from altimeter data
No full textExtreme waves are an important ocean feature. We estimate return values of significant wave height from measurements by satellite altimeters over the North Atlantic. The data were divided into 2° latitude by 2° longitude grid squares and the median along the satellite track was taken in each. Return values were estimated by fitting a Generalised Pareto Distribution to all values above a threshold, which was allowed to vary spatially. This method is objective, more statistically robust and thus theoretically preferable to fitting a distribution to all the data. The novel method gave return values that were up to 37% smaller than those estimated by fitting a Fisher-Tippet 1 distribution to all the data
On the Use of Emulators with Extreme and Highly Nonlinear Geophysical Simulators
Full text linkGaussian process emulators are a powerful tool for understanding complex geophysical simulators, including oceanic and atmospheric general circulation models. Concern has been raised about their ability to emulate complex nonlinear systems. For the first time, using the simple Stommel model, the way in which emulators can reasonably represent the full sampling space of an extreme nonlinear, bimodal system is illustrated. This simple example also shows how an emulator can help to elucidate interactions between parameters. The ideas are further illustrated with a second, more realistic, intermediate complex climate simulator. The paper describes what is meant by an emulator, the methodology of emulators, how emulators can be assessed, and why they are useful. It is shown how simple emulators can be useful to explore the parameter space (initial conditions, process parameters, and boundary conditions) of complex computer simulators, such as ocean and climate general circulation models, even when simulator outcomes contain steps in the response
Rossby waves: synergy in action
No full textRossby waves are an important phenomenon, linking processes in the west of ocean basins with forcing that occurred earlier in the east. We show evidence for such features in satellite-derived datasets of sea-surface height, temperature and ocean colour, using a section of the south Indian Ocean as an example. We discuss the possible mechanisms for an effect on chlorophyll, and we investigate this by comparing the ocean colour signal with the other datasets. In this region, the primary mechanism for a Rossby-wave signal in ocean colour appears to be meridional advection of water across a strong chlorophyll gradient. However, this cannot fully explain the observations in the westernmost basin
A global study of diurnal warming using satellite-derived sea surface temperature
No full textTen years of global infrared satellite data from National Oceanic and Atmospheric Administration's advanced very high resolution radiometer are analyzed to investigate global variations of diurnal warming. Daily nighttime sea surface temperatures (SSTs) are subtracted from adjacent daytime SSTs to give an estimate of diurnal warming (?Tday-night). The results reveal large regions in the tropics and midlatitudes that are frequently susceptible to diurnal warming each year. A strong seasonal pattern exists, dictated by the wind and solar insolation variability. A simple ?T regression model confirms that the observed warming is consistent with the right meteorological conditions of low winds and high insolation. The analysis also reveals how the spatial distribution and magnitude of ?T varies with the drift of the satellite orbit as it shifts from a local overpass time of 1400 to 1600. The results highlight the importance of the diurnal cycle for SST measurements and suggest the need for the diurnal cycle to be included in numerical models
A New Statistical Modelling Approach to Ocean Front Detection from SST Satellite Images
Full text linkOcean fronts are narrow zones of intense dynamic activity that play an important role in global ocean-atmosphere interactions. Owing to their highly variable nature, both in space and time, they are notoriously difficult features to adequately sample using traditional in-situ techniques. In this paper we propose a new statistical modelling approach to detecting and monitoring ocean fronts from AVHRR SST satellite images that builds on the 'front following' algorithm of Shaw and Vennell (2000). Weighted local likelihood is used to provide a smooth, non-parametric description of spatial variations in the position, mean temperature, width and temperature change of an individual front within an image. Weightings are provided by a Gaussian kernel function whose width is automatically determined by likelihood cross-validation. The statistical model fitting approach allows estimation of the uncertainty of each parameter to be quantified, a capability not possessed by other techniques. The algorithm is shown to be robust to noise and missing data in an image, problems that hamper many of the existing front detection schemes. The approach is general and could be used with other remotely sensed data sets, model output or data assimilation products
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