The Compensatory CO₂ Fertilization and Stomatal Closure Effects on Runoff Projection From 2016–2099 in the Western United States

Abstract

Water availability in the dry western United States (US) under climate change and increasing water use demand has become a serious concern. Previous studies have projected future runoff changes across the western US but ignored the impacts of ecosystem response to elevated CO2 concentration. Here, we aim to understand the impacts of elevated CO2 on future runoff changes through ecosystem responses to both rising CO2 and associated warming using the Noah‐MP model with representations of vegetation dynamics and plant hydraulics. We first validated Noah‐MP against observed runoff, leaf area index (LAI), and terrestrial water storage anomaly from 1980 to 2015. We then projected future runoff with Noah‐MP under downscaled climates from three climate models under Representative Concentration Pathway 8.5. The projected runoff declines variably from the Pacific Northwest by −11% to the Lower Colorado River basin by −92% from 2016 to 2099. To discern the exact causes, we conducted an attribution analysis of the modeled evapotranspiration from two additional sensitivity experiments: one with constant CO2 and another one with static monthly LAI climatology. Results show that surface “greening” (due to the CO2 fertilization effect) and the stomatal closure effect are the second largest contributors to future runoff change, following the warming effect. These two counteracting CO2 effects are roughly compensatory, leaving the warming effect to remain the dominant contributor to the projected runoff declines at large river basin scales. This study suggests that both surface “greening” and stomatal closure effects are important factors and should be considered together in water resource projections.

Projecting the Changes in Multifaceted Characteristics of Heatwave Events Across China

“…Despite the good performance of the QM approach in correcting the systematic biases in the CMIP6 simulations, there are still uncertainties exist in the different GCMs (Huo et al., 2019; Q. Zhang et al., 2022; X. Zhang et al., 2022). For example, under the SSP2‐4.5 scenario, the standard deviations of all climate models in heatwave intensity are 5.58, 3.95, 1.53, 6.27, 2.18, 6.13, and 4.25 of each sub‐region, respectively (East I, East II, East III, Middle I, Middle II, West I, and West II), indicating that the differences among climate models are larger in the northern regions, which can be also found in the long‐term period (Figure S7 in Supporting Information S1).…”

“…In the available literature on extreme heat events involved heatwave characteristics, various ways using absolute threshold or fixed extreme percentile lead to numerous definitions of heatwave events (e.g., Ratnam et al., 2016; Sharma & Mujumdar, 2017; White et al., 2013), which further affects the systematic assessment of heatwave impacts. Moreover, with the intensified warming in climate projected by model simulations (Brown, 2020; Vogel et al., 2020; Q. Zhang et al., 2022; X. Zhang et al., 2022), identifying the future heatwave with empirical threshold and historical criterion cannot consider the warming trend and local heat acclimatization, and further limits our scientific understanding of heatwave evolution in the future. Thus, in‐depth studies on quantifying the future variation of heatwave characteristics by incorporating short‐term heat stress are imperative, motivating our present research.…”

“…Moreover, with the intensified warming in climate projected by model simulations (Brown, 2020;Vogel et al, 2020;Q. Zhang et al, 2022;X. Zhang et al, 2022), identifying the future heatwave with empirical threshold and historical criterion cannot consider the warming trend and local heat acclimatization, and further limits our scientific understanding of heatwave evolution in the future.…”

Modernizing the open-source community Noah-MP land surface model (version 5.0) with enhanced modularity, interoperability, and applicability

“…Noah-MP can be applied to various spatial scales spanning from point scale locally to ~100-km resolution globally, and temporal scales spanning from sub-daily to decadal time scales. Since its original development, Noah-MP has been used in many important applications, including numerical weather prediction (Suzuki and Zupanski, 2018;Ju et al, 2022), high-resolution climate modeling (Gao et al, 2017;Liu et al, 2017;Rasmussen et al, 2023), land data assimilation (Xu et al, 2021;Nie et al, 2022), drought (Arsenault et al, 2020;Niu et al, 2020;Wu et al, 2021;Abolafia-Rosenzweig et al, 2023a), wildfire (Kumar et al, 2021;Abolafia-Rosenzweig et al, 2022a, 2023b, snowpack evolution (Wrzesien et al, 2015;He et al, 2019;Jiang et al, 2020), hydrology and water resources (Cai et al, 2014;Liang et al, 2019;X. Zhang et al, 2022a;Hazra et al, 2023), crop and agricultural management (Liu et al, 2016;Ingwersen et al, 2018;Warrach-Sagi et al, 2022;Valayamkunnath et al, 2022;Zhang et al, 2020Zhang et al, , 2023, urbanization and heat island (Xu et al, 2018;Salamanca et al, 2018;Patel et al, 2022), biogeochemical cycle (Cai et al, 2016;Brunsell et al, 2021), wind erosion (Jiang et al, 2021), wetland (Z.…”

Aridification of Colorado River Basin's Snowpack Regions Has Driven Water Losses Despite Ameliorating Effects of Vegetation

“…As a result, such studies may have under‐ or over‐estimated the sensitivity of runoff (% °C −1 ) (X.‐Y. Zhang et al., 2022). This is because as CO 2 increases there is a trade‐off between decreasing transpiration due to stomatal closure (Piao et al., 2020; Zhu et al., 2017) and increasing transpiration due to greening or increases in leaf area index (LAI) (Fensholt et al., 2012; Zeng et al., 2018; Zhu et al., 2017).…”