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[1] Reliable monitoring of the leaf area index (LAI) is required to further understand the carbon, water, and energy cycles of forests. In this study, we proposed a new satellite-based method to estimate the overstory LAI (LAI o ) separately from the understory LAI (LAI u ) for larch forests covering eastern Siberia. We modeled forest scenes representative of larch forest structure, with particular consideration of the typical clumped shoot structure of larch. Three-dimensional radiative transfer simulations were then conducted under various forest conditions to establish the relationships between LAI o and seasonal increases in the normalized difference water index after leaf appearance. Model-based sensitivity analyses indicated a maximum error of up to 26% under known noise levels. Averaged at the continental scale, total LAI from our estimates, the CYCLOPES version 3.1, and the Moderate Resolution Imaging Spectroradiometer MOD15 Collection 5 (main algorithm) showed similar ranges in summer. However, spatial pattern of LAI was slightly different, with smoother variability for CYCLOPES LAI. Our LAI and CYLOPES effective LAI reproduced a realistic seasonal variation with exact timing of spring increase in LAI o . The main drawbacks of MOD15 Collection 5 were unrealistically strong temporal variability, and the fact that LAI began to increase earlier than the overstory leaf appearance date. Overall, the results show that our new method is a good alternative to MOD15 Collection 5 and CYCLOPES, as it provides separate estimates of LAI o and LAI u and true LAI instead of effective LAI.Citation: Kobayashi, H., N. Delbart, R. Suzuki, and K. Kushida (2010), A satellite-based method for monitoring seasonality in the overstory leaf area index of Siberian larch forest,

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