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Fire is an integral part of Earth’s system that links regional and global biogeochemical cycles, human activities, and ecosystems. Global estimates for biomass burning indicate that Africa is responsible for ~70% of global burned area and ~50% of fire-related carbon emissions. Previous studies have documented an overall decline in burned area in the African continent, but changes in fire patterns, such as the frequency and size of different fire categories, have not been assessed. In this study, long-term fire trends were investigated using the latest burned area data from the MODerate resolution Imaging Spectroradiometer (MODIS) and the Global Fire Emission Database (GFED4s) over Central Africa (10°E–40°E, 15°N–15°S). A 3D (latitude, longitude, time) connected-component labeling algorithm was applied to identify individual fires and their sizes. The results show a decline in burned area by 2.7–3.2 Mha yr⁻¹(~1.3% yr⁻¹) for the period 2003–2017, particularly in northern Central Africa. This decline was attributed to significant decreases in both fire frequency and size, particularly for large fires (>100 ha) which contribute to ~90% of the total burned area. Burned area declined in tropical savannas and grasslands but increased at the edges of the Congolese rainforest. A random forest regression model was applied to quantify the influences of climatic conditions, fuel availability, and agricultural activity on burned area changes. Overall, suppressed fuel, increased dry season length, and decreased rainfall contributed to significant declines in burned area in savannas and grasslands. At the edges of the southern Congolese rainforest, suppressed rainfall and warmer temperature were responsible for the increased burned area.

Using observational rainfall datasets, we identify a positive correlation between precipitation over Central Equatorial Africa (CEA) and the Indian Ocean Dipole (IOD) during September‐December (SOND) for the period 1981–2019. Rainfall amount significantly increases during positive IOD events. The enhancement in precipitation is primarily attributed to increased rainfall frequency and reaches the maximum in October. IOD impacts rainfall via modifying the Walker circulation over the tropical Indian Ocean and moisture in the middle troposphere over CEA. The Madden‐Julian Oscillation (MJO) activity covaries with IOD to modulate the African Easterly Jet, which is critical to convection development over CEA. SOND rainfall has increased for the last two decades, which is concurrent with increases in both the IOD index and the correlation between IOD and rainfall. The IOD‐congruent rainfall changes potentially account for much of rainfall trends in southern and eastern CEA.

Heat waves are increasing in frequency, duration, and intensity and are strongly linked to anthropogenic climate change. However, few studies have examined heat waves in Florida, despite an older population and increasingly urbanized land areas that make it particularly susceptible to heat impacts. Heavy precipitation events are also becoming more frequent and intense; recent climate model simulations showed that heavy precipitation in the three days after a Florida heat wave follow these trends, yet the underlying dynamic and thermodynamic mechanisms have not been investigated. In this study, a heat wave climatology and trend analysis are developed from 1950 to 2016 for seven major airports in Florida. Heat waves are defined based on the 95th percentile of daily maximum, minimum, and mean temperatures. Results show that heat waves exhibit statistically significant increases in frequency and duration at most stations, especially for mean and minimum temperature events. Frequency and duration increases are most prominent at Tallahassee, Tampa, Miami, and Key West. Heat waves in northern Florida are characterized by large-scale continental ridging, while heat waves in central and southern Florida are associated with a combination of a continental ridge and a westward extension of the Bermuda–Azores high. Heavy precipitation events that follow a heat wave are characterized by anomalously large ascent and moisture, as well as strong instability. Light precipitation events in northern Florida are characterized by advection of drier air from the continent, while over central and southern Florida, prolonged subsidence is the most important difference between heavy and light events.

A frequency–wavenumber power ([Formula: see text]) spectrum was constructed using satellite-derived outgoing longwave radiation (OLR) and brightness temperature for the tropical latitudes. Since the two datasets overlap for over 34 years with nonintersecting sources in error and compare relatively well with each other, it is possible to diagnose trends in the tropical wave activity from the two datasets with confidence. The results suggest a weakening trend in [Formula: see text] characterized by high interannual variability for wave activity occurring in the low-frequency part of the spectrum and a steady increase in [Formula: see text] with relatively low interannual variability for wave activity occurring in the high-frequency part of the spectrum. The results show the parts of the spectrum representing the Madden–Julian oscillation and equatorial Rossby wave losing [Formula: see text] and other parts of the spectrum representing Kelvin waves, mixed Rossby–gravity waves, and tropical disturbance–like wave activity gaining [Formula: see text]. Similar results were obtained when trends in variance corresponding to the first principal component were produced using spectrally filtered OLR data representative of atmospheric equatorial waves. Spatial trends in the active phase of wave events and the mean duration of events are also shown for the different wave types. Linear trends in [Formula: see text] for the entire spectrum and regional means in the spectrum corresponding to the abovementioned five wave types with confidence intervals are also presented in the paper. Finally, we demonstrate that El Niño–Southern Oscillation variability does not appear to control the overall spatial patterns and trends observed in the [Formula: see text] spectrum.