Bridging Scales: An Approach to Evaluate the Temporal Patterns of Global Transpiration Products Using Tree-Scale Sap Flow Data

Transpiration is a key process driving energy, water and thus carbon dynamics. Global transpiration products are fundamental for understanding and predicting vegetation processes. However, validation of these transpiration products is limited, mainly due to lack of suitable data sets. We propose a method to use SAPFLUXNET, the first quality-controlled global tree sap flow (SF) database, for evaluating transpiration products at global scale. Our method is based on evaluating temporal mismatches, rather than absolute values, by standardizing both transpiration and SF products. We evaluate how transpiration responses to hydro-meteorological variation from the Global Land Evaporation Amsterdam Model (GLEAM), a widely used global transpiration product, compare to in situ responses from SAPFLUXNET field data. Our results show GLEAM and SAPFLUXNET temporal trends are in good agreement, but diverge under extreme conditions. Their temporal mismatches differ depending on the magnitude of transpiration and are not random, but linked to energy and water availability. Despite limitations, we show that the new global SAPFLUXNET data set is a valuable tool to evaluate T products and identify problematic assumptions and processes embedded in models. The approach we propose can, therefore, be the foundation for a wider use of SAPFLUXNET, a new, independent, source of information, to understand the mechanisms controlling global transpiration fluxes.Plain Language Summary Transpiration, the water evaporating from leaves, is a key element in the energy, water and carbon cycles of terrestrial ecosystems. Understanding patterns of transpiration at global scales is fundamental for prediction of future climates. Several models are used for estimating global transpiration, however identifying limitations and biases in these models is difficult, because we lack field data to compare them against. In this work, we propose a new method to enable tree-level sap flow (SF) data from SAPFLUXNET, the first global SF database, to be used to evaluate transpiration products and models. We evaluated how well GLEAM, a widely used transpiration product, matches SAPFLUXNET field data. We found GLEAM and SAPFLUXNET data to be in reasonable agreement however, mismatches occur under extreme dry or wet meteorological conditions, conditions which are likely to become more common under future climates. The detection of mismatches between SAPFLUXNET and GLEAM data is valuable for the identification of model processes and assumptions which could be reasonable within current climate, but inadequate for future climate conditions. The method we propose allows the use of SAPFLUXNET to understand the true mechanisms controlling global transpiration providing a new, independent, source of information to evaluate transpiration products and models.

Automated summary

Tree-level sap flow data can be used to evaluate the quality of global transpiration products and identify issues and assumptions in models. By comparing it with global transpiration products, inconsistencies under extreme climatic conditions can be detected, providing the basis for model improvement.