Improving the detection and tracking of tropical cyclones in atmospheric general circulation models

Dynamical seasonal forecasts of tropical storm frequency require robust and efficient algorithms for detection and tracking of tropical storms in atmospheric general circulation models (AGCMs). Tropical storms are generally detected when dynamic and thermodynamic variables meet specified criteria. Here, it is shown that objectively defined model- and basin-dependent detection criteria improve simulations of tropical storm climatology and interannual variability in low-resolution AGCMs. An improved tracking method provides more realistic tracking and accurate counting of storms

Controlling Spatiotemporal Chaos in a Realistic El Niño Prediction Model

A method for controlling low-order chaotic behavior of continuous spatiotemporal systems is developed and demonstrated in a complex, realistic 3D partial differential equation model that is used successfully for predicting El Niño events in the equatorial Pacific. An unstable periodic orbit that involves a full-domain oscillation is stabilized using a feedback control applied to a single degree of freedom at a carefully chosen single “choke point” in space. A general criterion is presented for determining the optimal points in reconstructed delay-coordinate phase space at which to apply the feedback control.Earth and Planetary Science

Properties of Tropical Cyclones in Atmospheric General Circulation Models

The properties of tropical cyclones in three atmospheric general circulation models (AGCMs) with low-resolution are discussed. The models are analysed for a period of 40 years. Characteristics of the tropical cyclones in the models are analysed and compared with those of observations, such as genesis position, number of cyclones, accumulated cyclone activity, number of storm days, tracks, and others. The three AGCMs have different levels of skill in simulating the different aspects of tropical cyclone activity in different regions. Some of the weak and strong features in simulating tropical cyclone activity variables are common for the three models, others are unique for each model and basin. The relation between model tropical cyclones and ENSO is analyzed in a paper currently in preparation

A statistical assessment of tropical cyclone activity in atmospheric general circulation models

The properties of tropical cyclones in three low-resolution atmospheric general circulation models (AGCMs) in seven ocean basins are discussed. The models are forced by prescribed, observed sea surface temperatures over a period of 40 yr, and their simulations of tropical cyclone activity are compared with observations. The model cyclone characteristics considered include genesis position, number of cyclones per year, seasonality, accumulated cyclone energy, track locations, and number of storm days. Correlations between model and observed interannual variations of these characteristics are evaluated. The models are found able to reproduce the basic features of observed tropical cyclone behavior such as seasonality, general location and interannual variability, but with identifiable biases. A bias correction is applied to the tropical cyclone variables of the three models. The three AGCMs have different levels of realism in simulating different aspects of tropical cyclone activity in different ocean basins. Some strengths and weaknesses in simulating certain tropical cyclone activity variables are common to the three models, while others are unique to each model and/or basin. Although the overall skill of the models in reproducing observed interannual variability of tropical cyclone variables has not surpassed or often even equalled that of statistical models, there exists potential for higher future skills using improved versions of dynamical approaches

A Theory for El Niño and the Southern Oscillation

A coupled atmosphere-ocean model is presented for El Niño and the Southern Oscillation that reproduces its major features, including its recurrence at irregular intervals. The interannual El Niño-Southern Oscillation cycle is maintained by deterministic interactions in the tropical Pacific region. Ocean dynamics alter sea-surface temperature, changing the atmospheric heating; the resulting changes in surface wind alter the ocean dynamics. Annually varying mean conditions largely determine the spatial pattern and temporal evolution of El Niño events

Toward an ethical framework for climate services: A White Paper of the Climate Services Partnership Working Group on Climate Services Ethics

This paper is intended to spur thinking and dialogue among the wide and relatively diverse community of actors engaged in practical activities surrounding the production, translation, transfer and use of climate information for societal decision making. This white paper is intended to start a conversation on ethics in the climate services community. To that end, the CSP Working Group on Climate Services Ethics is accepting comments on this white paper online at www.climate-services.org/ethics

Improved Combination of Multiple Atmospheric GCM Ensembles for Seasonal Prediction

An improved Bayesian optimal weighting scheme is developed and used to combine six atmospheric general circulation model (GCM) seasonal hindcast ensembles. The approach is based on the prior belief that the forecast probabilities of tercile-category precipitation and near-surface temperature are equal to the climatological ones. The six GCMs are integrated over the 1950–97 period with observed monthly SST prescribed at the lower boundary, with 9–24 ensemble members. The weights of the individual models are determined by maximizing the log likelihood of the combination by season over the integration period. A key ingredient of the scheme is the climatological equal-odds forecast, which is included as one of the "models" in the multimodel combination. Simulation skill is quantified in terms of the cross-validated ranked probability skill score (RPSS) for the three-category probabilistic hindcasts. The individual GCM ensembles, simple poolings of three and six models, and the optimally combined multimodel ensemble are compared. The Bayesian optimal weighting scheme outperforms the pooled ensemble, which in turn outperforms the individual models. In the extratropics, its main benefit is to bring much of the large area of negative-precipitation RPSS values up to near-zero values. The skill of the optimal combination is almost always increased (in the large spatial averages considered) when the number of models in the combination is increased from three to six, regardless of which models are included in the three-model combination. Improvements are made to the original Bayesian scheme of Rajagopalan et al. by reducing the dimensionality of the numerical optimization, averaging across data subsamples, and including spatial smoothing of the likelihood function. These modifications are shown to yield increases in cross-validated RPSS skills. The revised scheme appears to be better suited to combining larger sets of models, and, in the future, it should be possible to include statistical models into the weighted ensemble without fundamental difficulty