Synoptic-scale monsoon disturbances produce the majority of continental rainfall in the monsoon regions of South Asia and Australia, yet there is little understanding of the conditions that foster development of these low pressure systems. Here a genesis index is used to associate monsoon disturbance genesis in a global domain with monthly mean, climatological environmental variables. This monsoon disturbance genesis index (MDGI) is based on four objectively selected variables: Total column water vapor, low-level absolute vorticity, an approximate measure of convective available potential energy, and midtropospheric relative humidity. A Poisson regression is used to estimate the index coefficients. Unlike existing tropical cyclone genesis indices, the MDGI is defined over both land and ocean, consistent with the fact that monsoon disturbance genesis can occur over land. The index coefficients change little from their global values when estimated separately for the Asian-Australian monsoon region or the Indian monsoon region, suggesting that the conditions favorable for monsoon disturbance genesis, and perhaps the dynamics of genesis itself, are common across multiple monsoon regions. Vertical wind shear is found to be a useful predictor in some regional subdomains; although previous studies suggested that baroclinicity may foster monsoon disturbance genesis, here genesis frequency is shown to be reduced in regions of strong climatological vertical shear. The coefficients of the MDGI suggest that monsoon disturbance genesis is fostered by humid, convectively unstable environments that are rich in vorticity. Similarities with indices used to describe the distribution of tropical cyclone genesis are discussed.

This manuscript discusses the challenges in detecting and attributing recently observed trends in the Atlantic tropical cyclone (TC) and the epistemic uncertainty we face in assessing future risk. We use synthetic storms downscaled from five CMIP5 models by the Columbia HAZard model (CHAZ), and directly simulated storms from high-resolution climate models. We examine three aspects of recent TC activity: the upward trend and multi-decadal oscillation of the annual frequency, the increase in storm wind intensity, and the decrease in forward speed. Some data sets suggest that these trends and oscillation are forced while others suggest that they can be explained by natural variability. Projections under warming climate scenarios also show a wide range of possibilities, especially for the annual frequencies, which increase or decrease depending on the choice of moisture variable used in the CHAZ model and on the choice of climate model. The uncertainties in the annual frequency lead to epistemic uncertainties in TC risk assessment. Here, we investigate the potential for reduction of these epistemic uncertainties through a statistical practice, namely likelihood analysis. We find that historical observations are more consistent with the simulations with increasing frequency than those with decreasing frequency, but we are not able to rule out the latter. We argue that the most rational way to treat epistemic uncertainty is to consider all outcomes contained in the results. In the context of risk assessment, since the results contain possible outcomes in which TC risk is increasing, this view implies that the risk is increasing.