Understanding Terrestrial Water and Carbon Cycles and Their Interactions Using Integrated SMAP Soil Moisture and OCO-2 SIF Observations and Land Surface Models

Recently, more advanced synchronous global-scale satellite observations, the Soil Moisture Active Passive enhanced Level 3 (SMAP L3) soil moisture product and the Orbiting Carbon Observatory 2 (OCO-2) solar-induced chlorophyll fluorescence (SIF) product, provide an opportunity to improve the predictive understanding of both water and carbon cycles in land surface modeling. The Simplified Simple Biosphere Model version 4 (SSiB4) was coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (TRIFFID) and a mechanistic representation of SIF. Incorporating dynamic vegetation processes reduced global SIF root-mean-squared error (RMSE) by 12%. Offline experiments were conducted to understand the water and carbon cycles and their interactions using satellite data as constraints. Results indicate that soil hydraulic properties, the soil hydraulic conductivity at saturation (Ks) and the water retention curve, significantly impact soil moisture and SIF simulation, especially in the semi-arid regions. The wilting point and maximum Rubisco carboxylation rate (Vmax) affect photosynthesis and transpiration, then soil moisture. However, without atmospheric feedback processes, their effects on soil moisture are undermined due to the compensation between soil evaporation and transpiration. With optimized parameters based on SMAP L3 and OCO-2 data, the global RMSE of soil moisture and SIF simulations decreased by 15% and 12%, respectively. These findings highlight the importance of integrating advanced satellite data and dynamic vegetation processes to improve land surface models, enhancing understanding of terrestrial water and carbon cycles. This study used advanced satellite observations and land surface models to learn more about the water and carbon cycles and their interactions. The soil hydraulic conductivity at saturation (Ks) and the parameter for the water retention curve were identified as important. They affect how fast water can move in soil and how much water can be held by soil, which affects the available water in the soil for plants to use and makes them particularly important in water and carbon cycle simulation in dry areas. Two vegetation parameters affecting photosynthesis can help to improve the carbon cycle simulation but cannot change the soil moisture much because of the offline model limitation. The adjustment on the two soil property parameters and the two vegetation parameters improved the global water cycle simulation by 15% and the carbon cycle simulation by 12%. The introduction of dynamic vegetation processes into our model improved the carbon cycle simulation by 12% globally and helped to better understand the water and carbon cycles and their interactions. Key processes and parameters are identified using satellite data for advances in understanding carbon and water cycles and interactions The soil hydraulic properties, wilting point, and maximum Rubisco carboxylation rate are key parameters linking water-carbon cycles The dynamic vegetation process plays an important role in water and carbon cycles