Work

Fused Satellite Fire Products Reveal Fire Diurnal Cycles and Improve Fire Emission Estimates over North America and East Asia

Year: 2025

Type: article

Abstract: Estimating biomass burning emissions remains challenging due to both the substantial spatiotemporal variability of fires and the inherent uncertainties associated with the limited overpass frequency of polar-orbiting satellites. Integrating geostationary (5–10 min, 2 km) and polar-orbiting (twice daily, 375 m) satellite observations provides a detailed characterization of active fire diurnal cycles. However, the conventional unimodal Gaussian approximation (Pol/Geo-Uni), commonly used in fire emission models, fails to accurately reproduce the diurnal patterns. This study systematically analyzed the seasonal and diurnal variation in different types of active fires (AFs) and fire radiative power (FRP) across North America (GOES-16, ABI) and East Asia (Himawari-8, AHI). In North America, forest and savanna fires exhibited high FRP and a pronounced bimodal diurnal cycle lasting 4–8 h, whereas the corresponding fire types in East Asia exhibited a shorter, unimodal pattern of 2–4 h. Agricultural fires in East Asia were predominantly small in scale with low FRP, and frequently occurred at night. We used a modified Gaussian function to estimate dry matter burned (DMB), quantitating regional emission impacts for different fire types. The fused product (VIIRS/ABI-Bi) yielded amounts of DMB in North America that was 1.22 and 1.24 times higher than that from VIIRS/ABI-Uni and GFASv1.2, respectively. In East Asia, VIIRS/AHI-Bi DMB exceeded those from VIIRS/AHI-Uni and GFASv1.2 by 1.08 and 0.94 times, with agricultural fire estimates during the fire season being 1.18–1.62 times higher. This increase was notably pronounced in eastern China, where VIIRS/AHI-Bi DMB reached 1.76 to 9.77 times higher than estimates from VIIRS/AHI-Uni, GFED5, GFED4.1s, and GFASv1.2. Overall, integrating high spatiotemporal resolution satellite fire products with regionally diurnal models can substantially improve emission estimates, particularly for frequent, small-scale fire events.

Source: Remote Sensing

DOI: 10.3390/rs18010052