Urbanization has accelerated dramatically across the world over the past decades. Urban influence on surface temperatures is now being considered as a correction term in climatological datasets. Although prior research has investigated urban influences on precipitation for specific cities or selected thunderstorm cases, a comprehensive examination of urban precipitation anomalies on a global scale remains limited. This research is a global analysis of urban precipitation anomalies for over one thousand cities worldwide. We find that more than 60% of the global cities and their downwind regions are receiving more precipitation than the surrounding rural areas. Moreover, the magnitude of these urban wet islands has nearly doubled in the past 20 y. Urban precipitation anomalies exhibit variations across different continents and climates, with cities in Africa, for example, exhibiting the largest urban annual and extreme precipitation anomalies. Cities are more prone to substantial urban precipitation anomalies under warm and humid climates compared to cold and dry climates. Cities with larger populations, pronounced urban heat island effects, and higher aerosol loads also show noticeable precipitation enhancements. This research maps global urban rainfall hotspots, establishing a foundation for the consideration of urban rainfall corrections in climatology datasets. This advancement holds promise for projecting extreme precipitation and fostering the development of more resilient cities in the future.

The Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement mission (IMERG) has been widely evaluated. However, most of these studies focus on the ultimate merged satellite-gauge precipitation estimate and neglect the valuable intermediate estimates which directly guide the improvement of the IMERG product. This research aims to identify the error sources of the latest IMERG version 6 by evaluating the intermediate and ultimate precipitation estimates, and further examine the influences of regional topography and surface type on these errors. Results show that among six passive microwave (PMW) sensors, the Microwave Humidity Sounder (MHS) has outstanding comprehensive behavior, and Special Sensor Microwave Imager/Sounder (SSMIS) operates advanced at precipitation detection, while the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometry (SAPHIR) has the worst performance. More precipitation events are detected with larger quantitative uncertainty in low-lying places than in highlands, in urban and water body areas than in other places, and more in coastal areas than in inland regions. Infrared (IR) estimate has worse performance than PMW, and the precipitation detectability of IR is more sensitive to the factors of elevation and the distance to the coast, as larger critical successful index (CSI) over lowlands and coastal areas. PMW morphing and the mixing of PMW and IR algorithms partly reverse the conservative feature of the precipitation detection of PMW and IR estimates, resulting in higher probability of detection (POD) and false alert ratio (FAR). Finally, monthly gauge calibration improves most of the statistical indicators and reduces the influence of elevation and surface type factor on these errors.

Urbanization influences regional climates and extreme weather. While previous research has documented urban-induced precipitation for specific cities or storm cases, diurnal urban precipitation anomalies across different landscapes remain poorly understood. Analyzing diurnal and seasonal variations of urban precipitation anomalies across 175 US cities, we found strong urban effects on precipitation especially during summer afternoons. Large, inland cities can receive 10% more summer afternoon rainfall, and the pattern varies with urban heat islands and wind conditions. Coastal cities, under the influence of sea-land breeze, experience three times amplified daily urban precipitation enhancements than inland cities. Urban impacts are also noted for mountain cities, affecting their topography-dominated precipitation patterns. With increasing thresholds of extreme precipitation, most US cities experience more intense rainfall compared to their rural backgrounds. This study enhances our understanding of hitherto poorly documented diurnal aspects of urban rainfall through geographically distributed, landscape-specific rainfall anomalies.

Urbanization modifies precipitation ^1,2 , yet previous studies have reported inconsistent results, with some cities experiencing rainfall enhancement and others showing suppression ³ . To reconcile these discrepancies, we examine how urban impacts vary across storm types using an event-based analysis. With three-dimensional radar reflectivity data (1995–2017), we identify more than 40,000 warm-season storms across four Texas cities (Dallas, Austin, San Antonio and Houston). Here we show that classifying storms into five types reveals distinct urban influences linked to storm scales and dynamics. Local-scale single-cell and isolated storms, driven by atmospheric instability, increase in frequency (7–31%), particularly at night. Synoptic-scale frontal storms show unchanged occurrence but contrasting intensity responses: cold fronts weaken over cities by 16–28%, probably because of thermal and roughness effects, whereas warm fronts exhibit enhanced reflectivity. Tropical systems show no consistent change in frequency or intensity but exhibit a shift of high-reflectivity grid cells towards lower altitudes over urban areas. Given the diverse climate and geography of Texas, this work provides a transferable framework for understanding urban–storm interactions in other regions. These findings move beyond the traditional ‘urban wet or dry islands’ model, advancing our understanding of how urbanization modulates extreme precipitation and informing climate modelling ^4,5 and resilience planning for rapidly growing cities ^6,7 .