Using the International Best Track Archive for Climate Stewardship (IBTrACS), the climatology of tropical cyclones is compared between two global best track datasets: 1) the World Meteorological Organization (WMO) subset of IBTrACS (IBTrACS-WMO) and 2) a combination of data from the National Hurricane Center and the Joint Typhoon Warning Center (NHC+JTWC). Comparing the climatologies between IBTrACS-WMO and NHC+JTWC highlights some of the heterogeneities inherent in these datasets for the period of global satellite coverage 1981–2010. The results demonstrate the sensitivity of these climatologies to the choice of best track dataset. Previous studies have examined best track heterogeneities in individual regions, usually the North Atlantic and west Pacific. This study puts those regional issues into their global context. The differences between NHC+JTWC and IBTrACS-WMO are greatest in the west Pacific, where the strongest storms are substantially weaker in IBTrACS-WMO. These disparities strongly affect the global measures of tropical cyclone activity because 30% of the world’s tropical cyclones form in the west Pacific. Because JTWC employs similar procedures throughout most of the globe, the comparisons in this study highlight differences between WMO agencies. For example, NHC+JTWC has more 96-kt (~49 m s−1) storms than IBTrACS-WMO in the west Pacific but fewer in the Australian region. This discrepancy probably points to differing operational procedures between the WMO agencies in the two regions. Without better documentation of historical analysis procedures, the only way to remedy these heterogeneities will be through systematic reanalysis.

This study investigates global tropical cyclone (TC) activity trends from 1990 to 2021, a period marked by largely consistent observational platforms. Several global TC metrics have decreased during this period, with significant decreases in hurricane numbers and Accumulated Cyclone Energy (ACE). Most of this decrease has been driven by significant downward trends in the western North Pacific. Globally, short‐lived named storms, 24‐hr intensification events of ≥50 kt day⁻¹, and TC‐related damage have increased significantly. The increase in short‐lived named storms is likely due to technological improvements, while rapidly intensifying TC increases may be fueled by higher potential intensity. Damage increases are largely due to increased coastal assets. The significant decrease in hurricane numbers and global ACE are likely due to the trend toward a more La Niña‐like base state from 1990 to 2021, favoring North Atlantic TC activity and suppressing North and South Pacific TC activity.

The primary objective of this study is to investigate the recent variability of the eastern African climate. The region of interest is also known as the Greater Horn of Africa (GHA), and comprises the countries of Burundi, Djibouti, Eritrea, Ethiopia, Kenya, Rwanda, Somalia, Sudan, Uganda, and Tanzania.The analysis was based primarily on the construction of empirical orthogonal functions (EOFs) of gauge rainfall data and on CPC Merged Analysis of Precipitation (CMAP) data, derived from a combination of rain‐gauge observations and satellite estimates. The investigation is based on the period 1961–2001 for the ‘short rains’ season of eastern Africa of October through to December. The EOF analysis was supplemented by projection of National Centers for Environmental Prediction wind data onto the rainfall eigenmodes to understand the rainfall–circulation relationships. Furthermore, correlation and composite analyses have been performed with the Climatic Research Unit globally averaged surface‐temperature time series to explore the potential relationship between the climate of eastern Africa and global warming.The most dominant mode of variability (EOF1) based on CMAP data over eastern Africa corresponds to El Niño–southern oscillation (ENSO) climate variability. It is associated with above‐normal rainfall amounts during the short rains throughout the entire region, except for Sudan. The corresponding anomalous low‐level circulation is dominated by easterly inflow from the Indian Ocean, and to a lesser extent the Congo tropical rain forest, into the positive rainfall anomaly region that extends across most of eastern Africa. The easterly inflow into eastern Africa is part of diffluent outflow from the maritime continent during the warm ENSO events. The second eastern African EOF (trend mode) is associated with decadal variability. In distinct contrast from the ENSO mode pattern, the trend mode is characterized by positive rainfall anomalies over the northern sector of eastern Africa and opposite conditions over the southern sector. This rainfall trend mode eluded detection in previous studies that did not include recent decades of data, because the signal was still relatively weak. The wind projection onto this mode indicates that the primary flow that feeds the positive anomaly region over the northern part of eastern Africa emanates primarily from the rainfall‐deficient southern region of eastern Africa and Sudan. Although we do not assign attribution of the trend mode to global warming (in part because of the relatively short period of analysis), the evidence, based on our results and previous studies, strongly suggests a potential connection. Copyright © 2004 Royal Meteorological Society.

An international field campaign, Dynamics of the Madden Julian Oscillation (DYNAMO), took place in the Indian Ocean during October 2011–March 2012 to collect observations for the Madden–Julian oscillation (MJO), especially its convective initiation processes. The large-scale atmospheric and oceanic conditions during the campaign are documented here. The ENSO and the Indian Ocean dipole (IOD) states, the monthly mean monsoon circulation and its associated precipitation, humidity, vertical and meridional/zonal overturning cells, and ocean surface currents are discussed. The evolution of MJO events is described using various fields and indices that have been used to subdivide the campaign into three periods. These periods were 1) 17 September–8 December 2011 (period 1), which featured two robust MJO events that circumnavigated the global tropics with a period of less than 45 days; 2) 9 December 2011–31 January 2012, which contained less coherent activity (period 2); and 3) 1 February–12 April 2012, a period that featured the strongest and most slowly propagating MJO event of the campaign (period 3). Activities of convectively coupled atmospheric Kelvin and equatorial Rossby (ER) waves and their interaction with the MJO are discussed. The overview of the atmospheric and oceanic variability during the field campaign raises several scientific issues pertaining to our understanding of the MJO, or lack thereof. Among others, roles of Kelvin and ER waves in MJO convective initiation, convection-circulation decoupling on the MJO scale, applications of MJO filtering methods and indices, and ocean–atmosphere coupling need further research attention.

A new Madden–Julian oscillation (MJO) index is developed from a combined empirical orthogonal function (EOF) analysis of meridionally averaged 200-hPa velocity potential (VP200), 200-hPa zonal wind (U200), and 850-hPa zonal wind (U850). Like the Wheeler–Hendon Real-time Multivariate MJO (RMM) index, which was developed in the same way except using outgoing longwave radiation (OLR) data instead of VP200, daily data are projected onto the leading pair of EOFs to produce the two-component index. This new index is called the velocity potential MJO (VPM) indices and its properties are quantitatively compared to RMM. Compared to the RMM index, the VPM index detects larger-amplitude MJO-associated signals during boreal summer. This includes a slightly stronger and more coherent modulation of Atlantic tropical cyclones. This result is attributed to the fact that velocity potential preferentially emphasizes the planetary-scale aspects of the divergent circulation, thereby spreading the convectively driven component of the MJO’s signal across the entire globe. VP200 thus deemphasizes the convective signal of the MJO over the Indian Ocean warm pool, where the OLR variability associated with the MJO is concentrated, and enhances the signal over the relatively drier longitudes of the equatorial Pacific and Atlantic. This work provides a useful framework for systematic analysis of the strengths and weaknesses of different MJO indices.

This study investigates the number of tropical cyclone formations that can be attributed to the enhanced convection from equatorial waves within each basin. Tropical depression (TD)-type disturbances (i.e., easterly waves) were the primary tropical cyclone precursors over the Northern Hemisphere basins, particularly the eastern North Pacific and the Atlantic. In the Southern Hemisphere, however, the number of storms attributed to TD-type disturbances and equatorial Rossby waves were roughly equivalent. Equatorward of 20°N, tropical cyclones formed without any equatorial wave precursor most often over the eastern North Pacific and least often over the western North Pacific. The Madden–Julian oscillation (MJO) was an important tropical cyclone precursor over the north Indian, south Indian, and western North Pacific basins. The MJO also affected tropical cyclogenesis by modulating the amplitudes of higher-frequency waves. Each wave type reached the attribution threshold 1.5 times more often, and tropical cyclogenesis was 3 times more likely, within positive MJO-filtered rainfall anomalies than within negative anomalies. The greatest MJO modulation was observed for storms attributed to Kelvin waves over the north Indian Ocean. The large rainfall rates associated with tropical cyclones can alter equatorial wave–filtered anomalies. This study quantifies the contamination over each basin. Tropical cyclones contributed more than 20% of the filtered variance for each wave type over large potions of every basin except the South Pacific. The largest contamination, exceeding 60%, occurred for the TD band near the Philippines. To mitigate the contamination, the tropical cyclone–related anomalies were removed before filtering in this study.