A grid dataset of leaf age-dependent LAI seasonality product (Lad-LAI) over tropical and subtropical evergreen broadleaved forests

Abstract. Quantification of large-scale leaf age-dependent leaf area index has been lacking in tropical and subtropical evergreen broadleaved forests (TEFs) despite the recognized importance of leaf age in influencing leaf photosynthetic capacity in this region. Here, we simplified the canopy leaves of TEFs into three age cohorts, i.e., young, mature and old one, with different photosynthesis capacity (V_c,max) and produced a first grid dataset of leaf age-dependent LAI product (referred to as Lad-LAI) over the continental scale from satellite observations of TROPOMI (the TROPOspheric Monitoring Instrument) sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis. The seasonality of three LAI cohorts from the new Lad-LAI products agree well at the three sites (one in subtropical Asia and two in Amazon) with very fine collections of monthly LAI of young, mature and old leaves. Continental-scale comparisons with independent Moderate-resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) products and 53 samples of in situ measurements of seasonal litterfall data also demonstrate the robustness of the LAI seasonality of the three leaf age cohorts. The spatial patterns clustered from the three LAI cohorts coincides with those clustered from climatic variables. And the young and mature LAI cohorts perform well in capturing a dry-season green-up of canopy leaves across the wet Amazonia areas where mean annual precipitation exceeds 2,000 mm yr⁻¹, consistent with previous satellite data analysis. The new Lad-LAI products are primed to diagnose the adaption of tropical and subtropical forest to climate change; and will also help improve the development of phenology modules in Earth System Models. The proposed satellite-based approaches can provide reference for mapping finer temporal and spatial resolution LAI products with different leaf age cohorts. The Lad-LAI products are available at https://doi.org/10.6084/m9.figshare.21700955.v2 (Yang et al., 2022).