Professor Myles Allen CBE FRS

Abstract:

The development of the demonstration release software which solves the modeling tasks such as climate simulation, was discussed. The package was designed in a modular fashion to simplify upgrades of separate sections without requiring large downloads. One central server will initially manage the ensemble of climate models and the data generated. The server implementation is based on a standard web servers and mySQL database.

Abstract:

We assess the robustness of previous optimal detection and attribution studies considering zonal-mean temperatures. Principal results, which have consistently pointed towards a demonstrable anthropogenic influence on recently observed upper air temperatures, are confirmed. Importantly our detection results are not critically dependent on the inclusion of stratospheric as well as tropospheric temperatures. We find that detection is dependent on input field pre-processing choices, and on the choice of detection algorithm. There are a number of cases where either no signals are detected, or results fail a consistency test.

Abstract:

We assess the robustness of previous optimal detection and attribution studies considering zonal-mean temperatures. Principal results, which have consistently pointed towards a demonstrable anthropogenic influence on recently observed upper air temperatures, are confirmed. Importantly our detection results are not critically dependent on the inclusion of stratospheric as well as tropospheric temperatures. We find that detection is dependent on input field pre-processing choices, and on the choice of detection algorithm. There are a number of cases where either no signals are detected, or results fail a consistency test.

Abstract:

We explore sensitivity analyses of ocean circulation models by comparing the adjoint and direct-perturbation methods. We study the sensitivity of time-averaged inter-gyre vorticity transport to the imposed wind-stress curl in an eddy-permitting reduced-gravity ocean of a double gyre. Two regimes exist: a non-chaotic regime for low wind-stress curl, and a chaotic regime for stronger wind forcing. Direct-perturbation methods are found to converge, with increasing integration time, to a stable 'climate' sensitivity in both the chaotic and non-chaotic regimes. The adjoint method converges in the non-chaotic regime but diverges in the chaotic regime. The divergence of adjoint sensitivity in the chaotic regime is directly related to the chaotic divergence of solution trajectories through phase-space. Thus, standard adjoint sensitivity methods cannot be used to estimate climate sensitivity in chaotic ocean circulation models. An alternative method using an ensemble of adjoint calculations is explored. This is found to give estimates of the climate sensitivity of the time-mean vorticity transport with O(25%) error or less for integration times ranging from one month to one year. The ensemble-adjoint method is particularly useful when one wishes to produce a map of sensitivities (for example, the sensitivity of the advective vorticity transport to wind stress at every point in the domain) as direct sensitivity calculations for each point in the map are avoided. However, an ensemble-adjoint of the variance of the vorticity transport to wind-stress curl fails to estimate the climate sensitivity. We conclude that the most reliable method of determining the climate sensitivity is the direct-perturbation method, but ensemble-adjoint techniques may be of use in some problems.

Abstract:

What can we say about changes in the hydrologic cycle on 50-year timescales when we cannot predict rainfall next week? Eventually, perhaps, a great deal: the overall climate response to increasing atmospheric concentrations of greenhouse gases may prove much simpler and more predictable than the chaos of short-term weather. Quantifying the diversity of possible responses is essential for any objective, probability-based climate forecast, and this task will require a new generation of climate modelling experiments, systematically exploring the range of model behaviour that is consistent with observations. It will be substantially harder to quantify the range of possible changes in the hydrologic cycle than in global-mean temperature, both because the observations are less complete and because the physical constraints are weaker.