Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land

Abstract

The land system sequesters approximately 25% of anthropogenic CO 2 emissions (Le Quéré et al., 2018), thus slows the increase of atmospheric CO 2 concentration and global climate change. However, it is highly uncertain how the terrestrial carbon sink strength will change in the future given that warmer global temperatures impact vegetation carbon fixation in diverging ways whereas higher CO 2 concentration leads to higher water use efficiency (Fernández-Martínez et al., 2019;Sperry et al., 2019) and that nutrient limitation modulates vegetation responses to elevated CO 2 (Terrer et al., 2019). Despite the importance of the magnitude of land net CO 2 uptake, overall spatial and temporal patterns of global terrestrial carbon sink strength remain poorly understood given the lack of direct observations at the landscape scale (e.g., in a grid cell) for the entire globe (D. N. Huntzinger

Effect of spatial and temporal “drought legacy” on dust sources in adjacent ecoregions

“…The inclusion of drought legacy effects improves the ability of a land surface model to address plant response to the environment after a drought (Wang et al, 2023). In addition to decisions of land man-…”

Evaluation of Leaf‐To‐Canopy Upscaling Approaches for Simulating Canopy Carbonyl Sulfide Uptake and Gross Primary Productivity

“…Moreover, comprehensive leaf trait data sets (Kattge et al., 2020) provide many of the parameters required to resolve the variation related to canopy position (Niinemets et al., 2015). A new generation of terrestrial biosphere models such as CLM‐ml (Bonan et al., 2018) and CliMA (Wang et al., 2023) is increasingly moving toward the multilayer canopy approach, which has been demonstrated to be more reliable, more robust and more authentic than the BL approach (Bonan et al., 2021).…”

The Importance of Hyperspectral Soil Albedo Information for Improving Earth System Model Projections

“…The CliMA‐Land radiative transfer scheme is based on the vertically heterogeneous mSCOPE (Yang et al., 2017), which makes use of Fluspect (Vilfan et al., 2016) to simulate leaf reflectance, transmittance, and fluorescence at leaf level, and a SAIL based formulation (Verhoef, 1984) to compute spectrally resolved radiative transfer, as well as emitted fluorescence (van der Tol et al., 2016). However, some important changes were incorporated into the new CliMA‐Land radiative transfer scheme including: (a) accounting for carotenoid light absorption as part of absorbed photosynthetically active radiation (Wang & Frankenberg, 2022; Wang et al., 2021, 2023) and (b) accounting for horizontal canopy structure with the inclusion of a clumping index (Braghiere et al., 2021a).…”

“…The CliMA-Land radiative transfer scheme is based on the vertically heterogeneous mSCOPE (Yang et al, 2017), which makes use of Fluspect (Vilfan et al, 2016) to simulate leaf reflectance, transmittance, and fluorescence at leaf level, and a SAIL based formulation (Verhoef, 1984) to compute spectrally resolved radiative transfer, as well as emitted fluorescence (van der Tol et al, 2016). However, some important changes were incorporated into the new CliMA-Land radiative transfer scheme including: (a) accounting for carotenoid light absorption as part of absorbed photosynthetically active radiation Wang et al, 2021Wang et al, , 2023 and (b) accounting for horizontal canopy structure with the inclusion of a clumping index (Braghiere et al, 2021a). We used the gridded Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product at 0.5° spatial resolution and 8-day temporal resolution (Yuan et al, 2011), weekly mean leaf chlorophyll content to represent seasonality of canopy greenness (Croft et al, 2020), and assumed leaf carotenoid content being 1/7 of the chlorophyll content, specific leaf area as the inverse of leaf mass per area (Butler et al, 2017), leaf photosynthetic capacity represented by the maximum carboxylation rate at a reference temperature of 25°C (Vcmax25) from a machine learning based product (Luo et al, 2021), the maximum electron transport rate at a reference temperature of 25°C (Jmax25), and respiration rate at a reference temperature of 25°C (Rd25) scaled from Vcmax25 as Jmax25 = 1.67.Vcmax25 and Rd25 = 0.015.Vcmax25, a canopy height map was used to initialize plant hydraulic architecture within each simulation (Simard et al, 2011), and MODIS clumping index was used to represent canopy horizontal structure (Braghiere et al, 2019;He et al, 2012).…”