Previous estimates of tropical forest carbon loss in the twenty-first century using satellite data typically focus on its magnitude, whereas regional loss trajectories and associated drivers are rarely reported. Here we used different high-resolution satellite datasets to show a doubling of gross tropical forest carbon loss worldwide from 0.97 ± 0.16 PgC yr⁻¹ in 2001–2005 to 1.99 ± 0.13 PgC yr⁻¹ in 2015–2019. This increase in carbon loss from forest conversion is higher than in bookkeeping models forced by land-use statistical data, which show no trend or a slight decline in land-use emissions in the early twenty-first century. Most (82%) of the forest carbon loss is at some stages associated with large-scale commodity or small-scale agriculture activities, particularly in Africa and Southeast Asia. We find that ~70% of former forest lands converted to agriculture in 2001–2019 remained so in 2020, confirming a dominant role of agriculture in long-term pan-tropical carbon reductions on formerly forested landscapes. The acceleration and high rate of forest carbon loss in the twenty-first century suggest that existing strategies to reduce forest loss are not successful; and this failure underscores the importance of monitoring deforestation trends following the new pledges made in Glasgow.

Tropical deforestation was found to cause large reductions in precipitation using a range of observation-based datasets¹. However, the limitations of satellite-based space-for-time statistical analysis have hindered understanding of the roles of reshaped mesoscale atmospheric circulation and regional precipitation recycling at different scales. These effects are considered nonlocal effects, which are distinct from the local effects governed by deforestation-induced reductions in evapotranspiration (ET). Here we show reversed precipitation responses to Amazon deforestation across wet and dry seasons. During the wet season, deforested grids experienced a noteworthy increase in precipitation (0.96 mm month⁻¹ per percentage point forest loss), primarily attributed to enhanced mesoscale atmospheric circulation (that is, nonlocal effect). These nonlocal increases weaken with distance from deforested grids, leading to significant precipitation reductions in buffers beyond 60 km. Conversely, during the dry season, precipitation decreases in deforested grids and throughout all analysis buffers, with local effects from reduced ET dominating. Our findings highlight the intricate balance between local effects and nonlocal effects in driving deforestation–precipitation responses across different seasons and scales and emphasize the urgent need to address the rapid and extensive loss of forest in the Amazon region.

The year 2023 witnessed an extraordinary surge in marine heatwaves (MHWs) across Earth’s oceans, setting new records in duration, extent, and intensity, with MHW activity totaling 53.6 billion °C days square kilometer—more than three standard deviations above the historical norm since 1982. Notable events include the North Atlantic MHW (276-year return period) and the Southwest Pacific (141 years). Using ECCO2 (Estimating the Circulation and Climate of the Ocean-Phase II) high-resolution daily data, we conducted a mixed-layer heat budget analysis and identified region-specific drivers: enhanced shortwave flux and a shallower mixed layer in the North Atlantic and North Pacific, reduced cloud cover and increased advection in the Southwest Pacific, and oceanic advections in the Tropical Eastern Pacific. The 2023 MHWs highlight the intensifying impacts of a warm climate and the challenges in understanding extreme events.

The impact of rapid urbanization on the spatiotemporal pattern of short-term extreme precipitation in China remains unclear at the subnational scale. In this study, we present a general framework that measures urbanization-induced variation in hourly extreme wet season precipitation (April–October) from 1985 to 2012, with reference to a dynamic urban–rural station classification based on annual changes in urban extent. We found that urbanization in south China (<29° N) brings more extreme precipitation to urban areas than to suburbs, and reduces extreme precipitation continually over urban areas in parts of the north and northeast. Over 60% of provincial capital cities show significant changes in extreme precipitation due to urbanization, including smaller size cities separated from large urban clusters. Urbanization enhances extreme precipitation mainly in the local main part of the rainy season, which refers to May in the south (e.g. urban–rural differences of 0.70 mm h⁻¹ in Guangzhou) and July–September in the central and north (1.16 mm h⁻¹ in August of Beijing). Urbanization also increases hourly extreme precipitation at peak times in diurnal cycles. The results indicate that urbanization has caused overall more and more heterogeneous spatial patterns over China and concentrated distributions during the rainy season and peak time. These patterns warrant attention when assessing the risk of increased waterlogging and flash flooding in urban areas.