Explaining the contrast responses of evergreen needle-leaved forest and grassland carbon fluxes during the growing season droughts over the North Temperate Zone

As climate change exacerbates, droughts have become more intense, causing significant, widespread, and enduring adverse effects on carbon dynamics within terrestrial ecosystems. Therefore, it is crucial to quantitatively assess how drought influences carbon fluxes in these ecosystems. This understanding is essential for improving predictions of ecosystem responses to water stress and providing critical information to mitigate the effects of drought. In this study, we collected daily observations from 2004 to 2020 at two eddy covariance sites: one in an evergreen needle-leaved forest (abbreviated as ENFTha) and the other in grassland (abbreviated as GRAGri), both located in the North Temperate Zone. We first quantified the impacts of growing season (GS) droughts (GSD) on gross primary productivity (GPP) and ecosystem respiration (RECO). Our results indicated contrasting impacts of GSD on the two ecosystems: GPP and RECO increased in ENFTha, while they decreased in GRAGri. To explain these contrasting effects, we developed XGBoost models for GPP and RECO in ENFTha and GRAGri during the GS using eight environmental variables. We then applied the TreeExplainer-based SHapley Additive exPlanations framework to assess the significance of these variables in regulating GS carbon fluxes and to analyze their contributions to changes in GSD GPP and RECO. During the GS, four environmental variables—downwelling shortwave radiation (SW), vapor pressure deficit (VPD), longwave radiation (LW), and soil water content (near-surface air temperature (TA), SWC, SW, and LW)—significantly influenced GPP (RECO) in ENFTha and GRAGri, although their importance varied between the two ecosystems. These variables and their interactions also had nonlinear effects on GS GPP and RECO, with distinct threshold effects observed. In ENFTha, the enhanced SW demonstrated greater interaction effects with VPD, leading to increased GPP during GSD. In contrast, the rise in RECO could be attributed to the direct effects of TA. On the other hand, the declined SWC determined the decreases in carbon fluxes in GRAGri

Future drought overestimations due to no constraints of CO2 physiological effect and land-atmosphere coupling on potential evapotranspiration

Various offline drought indices have been widely used to project dryness/wetness and drought changes. However, the results derived from these indices often differ from or even contradict observations and direct projections made by coupled climate models. Therefore, it is crucial to investigate this scientific debate thoroughly and identify the potential causes. This study adopts a water demand-side perspective, focusing on potential evapotranspiration (PET), to address such controversy. Employing the Standardized Precipitation-Evapotranspiration Index (SPEI), three PET models including the Food and Agriculture Organization of the United Nations’ report 56 (FAO-56) Penman–Monteith (PM) model, a corrected FAO-56 PM model incorporating CO _2 physiological effect (PM _CO2 ), and a land-atmosphere coupled PET model (PET-LAC) are further compared. Despite projected increases in PET across most land areas, the PM shows the most pronounced increases among these PET models. Compared to PM _CO2 and PET-LAC, the PM model predicts the most significant drying, with the 3-month SPEI decreasing by 0.50 ± 0.23 yr ^−1 . Additionally, it projects the most substantial drought intensification, with increases in areas, intensity, and duration of 28 ± 6.9%, 0.70 ± 0.20 yr ^−1 , and 2.90 ± 0.83 month yr ^−1 , respectively. Meanwhile, these projections correspond to the most extensive area percentages, with 78.5 ± 10% for drying, 94.8 ± 7.2% for drought intensity, and 93.6 ± 7.9% for drought duration. These findings imply that the commonly used PM model overestimates future drought conditions. Differences and contradictions between the drought projections from PM-based offline indices and direct climate model outputs can be partly attributed to the omission of CO _2 physiological effect and land-atmosphere coupling constraints in the PM model. This study highlights the importance of improving PET models by incorporating these constraints, thereby providing valuable insights for enhancing the accuracy of future drought assessments

Quantifying Impacts of Vegetation Greenness Change on Drought Over Global Vegetation Zones

Abstract Changes in vegetation greenness have altered the regional terrestrial water cycle, yet their influence on drought remains unclear. To quantify the impact of vegetation greenness change on drought across global vegetation zones, this study conducted two simulations with and without linear trends in the Leaf Area Index (LAI), based on the Standardized Precipitation‐Evapotranspiration Index (SPEI) combined with the calibrated Shuttleworth‐Wallace potential evapotranspiration (PET) equation. Results revealed vegetation greening affected 71% of areas, and over 55% of areas experienced increases in PET, decreases in SPEI (indicating drying), and intensified drought conditions. The linear trends in LAI increased potential transpiration but decreased potential soil evaporation in most regions. The changes in drought are determined by the combined effects of these changes in potential transpiration and soil evaporation. This study highlights the critical role of vegetation greenness change in influencing drought

A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth-Wallace model

Abstract. As the theoretical upper bound of evapotranspiration (ET) or water use by ecosystems, potential ET (PET) has always been widely used as a variable linking a variety of disciplines, such as climatology, ecology, hydrology, and agronomy. However, substantial uncertainties exist in the current PET methods (e.g., empiric models and single-layer models) and datasets, because of unrealistic configurations of land surface and unreasonable parameterizations. Therefore, this study comprehensively considered interspecific differences in various vegetation-related parameters (e.g., plant stomatal resistance and CO2 effects on stomatal resistance) to calibrate and parametrize the Shuttleworth-Wallace (SW) model for forests, shrubland, grassland and cropland. We derived the parameters using identified daily ET observations with no water stress (i.e., PET) at 96 eddy covariance (EC) sites across the globe. Model validations suggest that the calibrated model could be transferable from known observations to any location. Based on four popular meteorological datasets, relatively realistic canopy height and time-varying land use/land cover and Leaf Area Index, we generated a global 5 km ensemble mean monthly PET dataset that includes two components of potential transpiration (PT) and soil evaporation (PE) for the 1982–2015 time period. Using this new dataset, the climatological characteristics of PET partitioning and the spatio-temporal changes in PET, PE and PT were investigated. The global mean annual PET was 1200 mm with PT/PET of 40 % and PE/PET of 60 %, and moreover controlled by PT and PE over 43 % and 57 % of the globe, respectively. Globally, the annual PET and PT significantly (p&lt;0.05) increases by 1.25 mm/yr and 1.22 mm/yr over the last 34 years, followed by a slight increase in the annual PE. Overall, the annual PET changes over 53 % of the globe could be attributed to PT, and the rest to PE. The new PET dataset may be used by academic communities and various agencies to conduct climatological analyses, hydrological modelling, drought studies, agricultural water management, and biodiversity conservation. The dataset is available at https://doi.org/10.11888/Terre.tpdc.300193 (Sun et al., 2023). </jats:p

A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model

&lt;jats:p&gt;Abstract. As the theoretical upper bound of evapotranspiration (ET) or water use by ecosystems, potential ET (PET) has always been widely used as a variable linking a variety of disciplines, such as climatology, ecology, hydrology, and agronomy. However, substantial uncertainties exist in the current PET methods (e.g., empiric models and single-layer models) and datasets because of unrealistic configurations of land surface and unreasonable parameterizations. Therefore, this study comprehensively considered interspecific differences in various vegetation-related parameters (e.g., plant stomatal resistance and CO2 effects on stomatal resistance) to calibrate and parametrize the Shuttleworth–Wallace (SW) model for forests, shrubland, grassland, and cropland. We derived the parameters using identified daily ET observations with no water stress (i.e., PET) at 96 eddy covariance (EC) sites across the globe. Model validations suggest that the calibrated model could be transferable from known observations to any location. Based on four popular meteorological datasets, relatively realistic canopy height, time-varying land use or land cover, and the leaf area index, we generated a global 5 km ensemble mean monthly PET dataset that includes two components of potential transpiration (PT) and soil evaporation (PE) for the 1982–2015 time period. Using this new dataset, the climatological characteristics of PET partitioning and the spatiotemporal changes in PET, PE, and PT were investigated. The global mean annual PET was 1198.96 mm with PT/PET of 41 % and PE/PET of 59 %, controlled moreover by PT and PE of over 41 % and 59 % of the globe, respectively. Globally, the annual PET and PT significantly (p&amp;lt;0.05) increase by 1.26 and 1.27 mm yr−1 over the last 34 years, followed by a slight decrease in the annual PE. Overall, the annual PET changes over 53 % of the globe could be attributed to PT, and the rest to PE. The new PET dataset may be used by academic communities and various agencies to conduct climatological analyses, hydrological modeling, drought studies, agricultural water management, and biodiversity conservation. The dataset is available at https://doi.org/10.11888/Terre.tpdc.300193 (Sun et al., 2023). &lt;/jats:p&gt