Fri, 27 Jan 2012

14:30 - 15:30
DH 3rd floor SR

Variable transformations and preconditioning in variational data assimilation

Dr. Amos S. Lawless
(University of Reading)
Abstract

Data assimilation aims to correct a forecast of a physical system, such as the atmosphere or ocean, using observations of that system, in order to provide a best estimate of the current system state. Since it is not possible to observe the whole state it is important to know how errors in different variables of the forecast are related to each other, so that all fields may be corrected consistently. In the first part of this talk we consider how we may impose constraints between different physical variables in data assimilation. We examine how we can use our knowledge of atmospheric physics to pose the assimilation problem in variables that are assumed to be uncorrelated. Using a shallow-water model we demonstrate that this is best achieved by using potential vorticity rather than vorticity to capture the balanced part of the flow. The second part of the talk will consider a further transformation of variables to represent spatial correlations. We show how the accuracy and efficiency with which we can solve the transformed assimilation problem (as measured by the condition number) is affected by the observation distribution and accuracy and by the assumed correlation lengthscales. Theoretical results will be illustrated using the Met Office variational data assimilation scheme.

Fri, 21 Oct 2011

14:30 - 15:30
DH 3rd floor SR

The Timescales of The Ocean Circulation and Climate

Prof. Carl Wunsch
(MIT)
Abstract

Studies of the ocean circulation and climate have come to be dominated by the results of complex numerical models encompassing hundreds of thousands of lines of computer code and whose physics may be more difficult to penetrate than the real system. Some insight into the large-scale ocean circulation can perhaps be gained by taking a step back and considering the gross time scales governing oceanic changes. These can derived from a wide variety of simple considerations such as energy flux rates, signal velocities, tracer equilibrium times, and others. At any given time, observed changes are likely a summation of shifts taking place over all of these time scales.

Fri, 02 Dec 2011

14:30 - 15:30
DH 3rd floor SR

The role of carbon in past and future climate

Prof. Andrew Fowler
(Department of Mathematics and Statistics)
Abstract

There is much current concern over the future evolution of climate under conditions of increased atmospheric carbon. Much of the focus is on a bottom-up approach in which weather/climate models of severe complexity are solved and extrapolated beyond their presently validated parameter ranges. An alternative view takes a top-down approach, in which the past Earth itself is used as a laboratory; in this view, ice-core records show a strong association of carbon with atmospheric temperature throughout the Pleistocene ice ages. This suggests that carbon variations drove the ice ages. In this talk I build the simplest model which can accommodate this observation, and I show that it is reasonably able to explain the observations. The model can then be extrapolated to offer commentary on the cooling of the planet since the Eocene, and the likely evolution of climate under the current industrial production of atmospheric carbon.

Fri, 18 Nov 2011
14:30
DH 3rd floor SR

Insights into the Mechanisms of Regional Sea Level Variability from Wind Stress and Heat Content

Dr Simon Holgate
(National Oceanography Centre)
Abstract

Rising sea levels are frequently cited as one of the most pressing societal consequences of climate change. In order to understand the present day change in sea level we need to place it in the context of historical changes. The primary source of information on sea level change over the past 100-150 years is tide gauges. However, these tide gauges are a globally sparse set of point measurements located largely at the coast. "Global mean sea level" calculated from these tide gauges is therefore biased and is also more variable than than global mean sea level calculated from the past 19 years of satellite altimtery measurements.

The work presented here explores the use of simple statistical approaches which make use of reanalysis wind stress datasets and heat content reconstructions to model the sea level records. It is shown that these simple models have skill in reproducing variability at decadal time-scales. The results suggest that there are active regions of wind stress and heat content in the ocean which affect regional variability in sea level records that point to the atmospheric and oceanic processes which drive the variability. Acceleration seen in the longest continous sea level record at Brest is shown to be partially attributable to changes in wind stress over the past 140 years.

Fri, 04 Nov 2011

14:30 - 15:30
DH 3rd floor SR

Data-based stochastic subgrid-scale parametrisation: an approach using cluster-weighted modelling

Dr Frank Kwasniok
(University of Exeter)
Abstract

A new approach for data-based stochastic parametrisation of unresolved scales and processes in numerical weather and climate prediction models is introduced. The subgrid-scale model is conditional on the state of the resolved scales, consisting of a collection of local models. A clustering algorithm in the space of the resolved variables is combined with statistical modelling of the impact of the unresolved variables. The clusters and the parameters of the associated subgrid models are estimated simultaneously from data. The method is tested and explored in the framework of the Lorenz '96 model using discrete Markov processes as local statistical models. Performance of the scheme is investigated for long-term simulations as well as ensemble prediction. The present method clearly outperforms simple parametrisation schemes and compares favourably with another recently proposed subgrid scheme also based on conditional Markov chains.

Subscribe to DH 3rd floor SR