First Observational Evidence That Biological Giant CCN Control Urban Rainfall Character: A Natural Experiment from Islamabad's Paper Mulberry Removal

Ali Bin Shahid 

Modeling studies predict that biological aerosol, specifically pollen acting as giant cloud condensation nuclei (GCCN), can modify precipitation character by initiating collision-coalescence and warm rain in shallow cloud (Steiner et al., 2015; Wozniak et al., 2018; Paukert et al., 2025). No observational study has tested this prediction. We exploit a natural experiment, the removal of ~29,000 paper mulberry (Broussonetia papyrifera) trees from Islamabad, Pakistan, whose pollen (30,000–50,000 grains/m³, 3–4× the modeled effect threshold) dominated the March aerosol budget, to provide the first observational evidence that biological GCCN control the rainfall intensity distribution.

We derive discriminating predictions from four competing mechanisms: (H1) giant CCN loss, (H2) evapotranspiration decline, (H3) urban heat island intensification, and (H4) anthropogenic fine-aerosol increase. These four mechanisms predict different responses in the rainfall intensity distribution, a distinction not previously exploited in the urban precipitation literature. Six tests applied to the 23-year PMD pollen record (2003–2025) and 43 years of CHIRPS daily precipitation (1981–2023) yield unambiguous results: pollen correlates specifically with light rain days (0.2–5 mm; r=+0.507, p=0.014) but not with heavy rain days (>20 mm; p=0.169), total precipitation (p=0.595), or mean rain intensity (p=0.760). The effect is confined to the March pollen season, tracks year-to-year pollen variability including a natural dip (2013–2016) and recovery (2017–2023) uncorrelated with canopy area or urbanization, and is absent from the adjacent control city (Rawalpindi, 15 km, same synoptic forcing). The giant CCN hypothesis (H1) passes all six tests. Evapotranspiration, urban heat, and aerosol shift hypotheses each fail multiple tests.

This constitutes the first observational validation of modeled bioaerosol-precipitation interactions, the first use of intensity partitioning to discriminate aerosol mechanisms in an urban setting, and the first resolution of the bidirectional pollen-rain confound that has obscured the giant-CCN signal in aerobiological data.