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Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable.

Recently, we developed seasonal prediction schemes with improved skill to predict tropical cyclone (TC) activity up to 3 months in advance for the Solomon Islands (SI) region (5°–15°S, 155°–170°E) using sophisticated Bayesian regression techniques. However, TC prediction at subseasonal timescale (i.e., 1–4 weeks in advance) is not being researched for that region despite growing demands from decision makers at sectoral level. In this paper, we first assess the feasibility of developing subseasonal prediction frameworks for the SI region using a pool of predictors that are known to affect TC activity in the region. We then evaluate multiple predictor combinations to develop the most appropriate models using a statistical approach to forecast weekly TC activity up to 4 weeks in advance. Predictors used include indices of various natural climate variability modes, namely the Madden–Julian Oscillation (MJO), the El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and the Interdecadal Pacific Oscillation (IPO). These modes often have robust physical and statistical relationships with TC occurrences in the SI region and the broader southwest Pacific territory as shown by preceding studies. Additionally, we incorporate TC seasonality as a potential predictor given the persistence of TCs occurring more in certain months than others. Note that a model with seasonality predictor alone (hereafter called the "climatology" model) forms a baseline for comparisons. The hindcast verifications of the forecasts using leave‐one‐out cross‐validation procedure over the study period 1975–2019 indicate considerable improvements in prediction skill of our logistic regression models over climatology, even up to 4 weeks in advance. This study sets the foundation for introducing subseasonal prediction services, which is a national priority for improved decision making in sectors like agriculture and food security, water, health and disaster risk mitigation in the Solomon Islands. [ABSTRACT FROM AUTHOR]

This study examines the climatology, variability, and trends of tropical cyclones (TCs) affecting the Solomon Islands (SI) territory, in the wider southwest Pacific (SWP), using the South Pacific Enhanced Archive for Tropical Cyclones (SPEArTC) database. During the period 1969/1970–2018/2019, 168 TCs were recorded in the SI territory. A cluster analysis is used to objectively partition these tracks into three clusters of similar TC trajectories to obtain better insights into the effects of natural climate variability, particularly due to the El Niño–Southern Oscillation (ENSO) phenomenon, which otherwise is not very apparent for TCs when considered collectively in the SI region. We find that TCs in clusters 1 and 3 show enhanced activity during El Niño phase, whereas TCs in cluster 2 are enhanced during La Niña and neutral phases. In addition to being modulated by ENSO, TCs in clusters 2 and 3 show statistically significant modulation at an intraseasonal timescale due to the Madden–Julian Oscillation (MJO) phenomenon. There are also some indications through sophisticated Bayesian modelling that TCs in clusters 2 and 3 are slightly influenced by the Interdecadal Pacific Oscillation (IPO). These results can have substantial implications for cluster‐specific development of TC prediction schemes for the SI region. [ABSTRACT FROM AUTHOR]

The impact of anthropogenic global warming on tropical cyclone (TC) frequency remains a challenging issue, partly due to a relatively short period of reliable observational TC records and inconsistencies in climate model simulations. Using TC detection from 20 CMIP6 historical simulations, we show that the majority (75%) of these models show a decrease in global-scale TC frequency from 1850 to 2014. We demonstrated that this result is largely explained by weakened mid-tropospheric upward motion in CMIP6 models over the Pacific and Atlantic main development regions. The reduced upward motion is due to a zonal circulation adjustment and shifts in Intertropical Convergence Zone in response to global warming. In the South Indian Ocean, reduced TC frequency is mainly due to the decreased survival rate of TC seeds because of an increased saturation deficit in a warming climate. Our analysis highlights global warming's potential impact on the historical decrease in global TC frequency. [ABSTRACT FROM AUTHOR]

The impact of anthropogenic global warming on tropical cyclone (TC) frequency remains a challenging issue, partly due to a relatively short period of reliable observational TC records and inconsistencies in climate model simulations. Using TC detection from 20 CMIP6 historical simulations, we show that the majority (75%) of these models show a decrease in global-scale TC frequency from 1850 to 2014. We demonstrated that this result is largely explained by weakened mid-tropospheric upward motion in CMIP6 models over the Pacific and Atlantic main development regions. The reduced upward motion is due to a zonal circulation adjustment and shifts in Intertropical Convergence Zone in response to global warming. In the South Indian Ocean, reduced TC frequency is mainly due to the decreased survival rate of TC seeds because of an increased saturation deficit in a warming climate. Our analysis highlights global warming's potential impact on the historical decrease in global TC frequency.