Future tropical cyclone activity is a topic of great scientific and societal interest. In the absence of a climate theory of tropical cyclogenesis, general circulation models are the primary tool available for investigating the issue. However, the identification of tropical cyclones in model data at moderate resolution is complex, and numerous schemes have been developed for their detection.The influence of different tracking schemes on detected tropical cyclone activity and responses in the Hurricane Working Group experiments is examined herein. These are idealized atmospheric general circulation model experiments aimed at determining and distinguishing the effects of increased sea surface temperature and other increased CO 2 effects on tropical cyclone activity. Two tracking schemes are applied to these data and the tracks provided by each modeling group are analyzed.The results herein indicate moderate agreement between the different tracking methods, with some models and experiments showing better agreement across schemes than others. When comparing responses between experiments, it is found that much of the disagreement between schemes is due to differences in duration, wind speed, and formation-latitude thresholds. After homogenization in these thresholds, agreement between different tracking methods is improved. However, much disagreement remains, accountable for by more fundamental differences between the tracking schemes. The results indicate that sensitivity testing and selection of objective thresholds are the key factors in obtaining meaningful, reproducible results when tracking tropical cyclones in climate model data at these resolutions, but that more fundamental differences between tracking methods can also have a significant impact on the responses in activity detected.

A season of operational cell and track data from Darwin, Australia, has been analyzed to explore the statistical characteristics of the convective cell heights. The statistics for the monsoon and break regimes are significantly different with the break season cells being higher for a given reflectivity threshold. The monsoon cells produce more rain, but there are fewer intense cells and there is a much larger contribution from stratiform rain. The monsoon cells are also slightly larger, but shorter lived than the breaks. The shorter lifetime may reflect a more rapid transition to a longer-lived stratiform character. The monsoon regime is shown to be associated with large-scale ascent and higher humidity that may lead to more frequent, but weaker cells. Within regimes, the subset of intense cells generally reach near the tropopause or overshoot. However, there is little evidence in the data for a multimodal distribution of cell heights, except perhaps for the intense monsoon cases. Instead, the picture is a continuous distribution of cell heights with the peak of the distribution shifting to higher values as the distributions are conditioned on higher reflectivity.

The sensitivity of global tropical cyclone (TC) activity to changes in a zonally symmetric sea surface temperature (SST) distribution and the associated large-scale atmospheric circulation are investigated. High-resolution (~50-km horizontal grid spacing) atmospheric general circulation model simulations with maximum SST away from the equator are presented. Simulations with both fixed-SST and slab ocean lower boundary conditions are compared. The simulated TCs that form on the poleward flank of the intertropical convergence zone (ITCZ) are tracked and changes in the frequency and intensity of those storms are analyzed between the different experiments. The total accumulated cyclone energy (ACE) increases as the location of the maximum SST shifts farther away from the equator. The location of the ITCZ also shifts in conjunction with changes to the SST profile, and this plays an important role in mediating the frequency and intensity of the TCs that form within this modeling framework.

Political decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. In order to provide these estimates, different approaches to constrain, filter, or weight climate model projections into probabilistic distributions have been proposed. However, an assessment of multiple such methods to, for example, expose cases of agreement or disagreement, is often hindered by a lack of coordination, with methods focusing on a variety of variables, time periods, regions, or model pools. Here, a consistent framework is developed to allow a quantitative comparison of eight different methods; focus is given to summer temperature and precipitation change in three spatial regimes in Europe in 2041-2060 relative to 1995-2014. The analysis draws on projections from several large ensembles, the CMIP5 multi-model ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5. The methods’ key features are summarized, assumptions are discussed and resulting constrained distributions are presented. Method agreement is found to be dependent on the investigated region but is generally higher for median changes than for the uncertainty ranges. This study, therefore, highlights the importance of providing clear context about how different methods affect the assessed uncertainty, particularly the upper and lower percentiles that are of interest to risk-averse stakeholders. The comparison also exposes cases where diverse lines of evidence lead to diverging constraints; additional work is needed to understand how the underlying differences between methods lead to such disagreements and to provide clear guidance to users.