Search for: All records

Abstract. Root-zone water storage capacity (Sr) – the maximum water volume available for vegetation uptake – bolsters ecosystem resilience to droughts and heatwaves, influences land–atmosphere exchange, and controls runoff and groundwater recharge. In land models, Sr serves as a critical parameter to simulate water availability for vegetation and its impact on processes like transpiration and soil moisture dynamics. However, Sr is difficult to measure, especially at large spatial scales, hindering an accurate understanding of many biophysical processes, such as photosynthesis, evapotranspiration, tree mortality, and wildfire risk. Here, we present a global estimate of Sr using measurements of total water storage (TWS) anomalies from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On satellite missions. We find that the median Sr value for global vegetated regions is at least 220±40 mm, which is over 50 % larger than the latest estimate derived from tracking storage change via water fluxes and 380 % larger than that calculated using a typical soil and rooting-depth parameterization. These findings reveal that plant-available water stores exceed the storage capacity of 2 m deep soil in nearly half of Earth's vegetated surface, representing a notably larger extent than previous estimates. Applying our Sr estimates in a global hydrological model improves evapotranspiration simulations compared to other Sr estimates across much of the globe, particularly during droughts, highlighting the robustness of our approach. Our study highlights the importance of continued refinement and validation of Sr estimates and provides a new observational approach for further exploring the impacts of Sr on water resource management and ecosystem sustainability. 

Abstract Satellite‐based evapotranspiration (ET) products such as OpenET and GLEAM are widely used for drought monitoring and ecosystem‐climate studies. However, their ability to accurately capture interannual variability (IAV), a key requirement for such applications, remains under‐evaluated. Here, we assessed IAV in OpenET and GLEAM using an independent water balance approach that combined precipitation, discharge, and GRACE/FO total water storage anomalies across nine river basins in the western United States. Even after accounting for observational uncertainty through a Monte Carlo approach, both products systematically underestimate IAV relative to water balance‐based ET, by more than 60% on average. This result is further supported by long‐term tower measurements from AmeriFlux. We also demonstrated that ET sensitivity to climate and vegetation drivers in OpenET and GLEAM differ substantially from water balance‐based estimates. These findings reveal important limitations in satellite‐based ET products and highlight the need for improved IAV representation to support ecosystem and climate applications. 

In this paper, we investigate a sink-driven three-layer flow in a radial Hele-Shaw cell. The three fluids are of different viscosities, with one fluid occupying an annulus-like domain, forming two interfaces with the other two fluids. Using a boundary integral method and a semi-implicit time stepping scheme, we alleviate the numerical stiffness in updating the interfaces and achieve spectral accuracy in space. The interaction between the two interfaces introduces novel dynamics leading to rich pattern formation phenomena, manifested by two typical events: either one of the two interfaces reaches the sink faster than the other (forming cusp-like morphology), or they come very close to each other (suggesting a possibility of interface merging). In particular, the inner interface can be wrapped by the other to have both scenarios. We find that multiple parameters contribute to the dynamics, including the width of the annular region, the location of the sink, and the mobilities of the fluids. 

Alternative current optimal power flow (ACOPF) problems have been studied for over fifty years, and yet the development of an optimal algorithm to solve them remains a hot and challenging topic for researchers because of their nonlinear and nonconvex nature. A number of methods based on linearization and convexification have been proposed to solve ACOPF problems, which result in near-optimal or local solutions, not optimal solutions. Nowadays, with the prevalence of machine learning, some researchers have begun to utilize this technology to solve ACOPF problems using the historical data generated by the grid operators. The present paper reviews the research on solving ACOPF problems using machine learning and neural networks and proposes future studies. This body of research is at the beginning of this area, and further exploration can be undertaken into the possibilities of solving ACOPF problems using machine learning. 

Abstract Background and AimsA comprehensive standardized evaluation tool was needed to assess community awareness and preparedness when the pandemic hit the United States. This study aimed to develop and validate a new Coronavirus Awareness and Preparedness Scale (CAPS) through psychometric testing. MethodsThis study unfolded in two phases. Phase 1 (conducted in March and April 2020) focused on the development of the scale. Phase 2 (conducted in June and July 2020) measured the reliability and validity of the scale. Psychometric testing, including exploratory factor analysis and reliability testing, was performed with a convenience sample of 1237 faculty, staff, and students at a southern university in the United States. ResultsThe final CAPS model consists of four factors with 26 items: threat (seven items), confidence (11 items), individual precautions (three items), and public precautions (five items). The scale demonstrated satisfactory internal consistency (Cronbach'sα = 0.75). Strong and statistically significant item correlations were observed within the subscales through item analysis. ConclusionThe CAPS is a reliable and valid comprehensive evaluation instrument designed to gauge community awareness and preparedness during the early stages of the COVID‐19 pandemic. Its adaptability makes it suitable for measuring readiness and preparedness concerning any novel airborne disease or future airborne pandemic within a community. 

Abstract Nanomechanical resonators are built into phones, as filters or accelerometers, but they lack a knob to effectively tune the frequency at the nanoscale when it’s easy to tune on an octave the tone of a classical musical instrument like a guitar string. Moreover, the control of deformation in nanomaterials, as two-dimensional (2D) materials, to tailor their electronic properties, i.e., straintronic, opens up avenues for applications in force detection, bolometry or quantum emitters. An accurate control of the deformation within these materials is thus necessary to fully exploit their potential. The precise study of deformations in 2D materials involves measurements of vibration modes and nanomechanics. By using a suspended MoS₂membrane heated by the Joule effect, we induce a strong softening of the mechanical resonance frequency as a function of the electrothermal heating, over one octave. A simple electrical tension is used to modulate the thermal mechanical tuning. Its amplitude is very large, greater than 100% modulation for one volt, compared to other approaches on 2D or 1D materials and, moreover, a very wide frequency range is accessible. Finally, we have related a photo-induced softening of the membrane over very long times with the current measurements and a photothermal effect. 

The synthesis of 1-butyl-2,3-dimethyl-4-vinylimidazolium triflate, its polymerization, and ion exchange to yield a trio of 1-butyl-2,3-dimethyl-4-vinylimidazolium polymers is described. Irrespective of the nature of the anion, substitution at the 2-position of the imidazolium moiety substantially increases the distance between the anion and cation. The methyl substituent at the 2-position also served to expose the importance of H-bonding for the attractive potential between imidazolium moiety and anions in polymers without a methyl group at the 2-position. The thermal characteristics of poly(1-butyl-2,3-dimethyl-4-vinylimidazolium) salts and corresponding poly(1-ethyl-3-methyl-4-vinylimidazolium) salts were evaluated. While the mid-point glass transition temperatures, Tg-mid, for 1-ethyl-3-methyl-4-vinylimidazolium polymers with CF3SO3−, (CF3SO2)2N− and PF6− counterions, were 153 °C, 88 °C and 200 °C, respectively, the Tg-mid values for 1-butyl-2,3-dimethyl-4vinylimidazolium polymers with corresponding counter-ions were tightly clustered at 98 °C, 99 °C and 84 °C, respectively. This dramatically reduced influence of the anion type on the glass transition temperature was attributed to the increased distance between the center of the anions and cations in the 1-butyl-2,3-dimethyl-4-vinylimidazolium polymer set, and minimal H-bonding interactions between the respective anions and the 1-butyl-2,3-dimethyl-4-vinylimidazolium moiety. It is believed that this is the first observation of substantial independence of the glass transition of an ionic polymer on the nature of its counterion. 

The flow in a Hele-Shaw cell with a time-increasing gap poses a unique shrinking interface problem. When the upper plate of the cell is lifted perpendicularly at a prescribed speed, the exterior less viscous fluid penetrates the interior more viscous fluid, which generates complex, time-dependent interfacial patterns through the Saffman–Taylor instability. The pattern formation process sensitively depends on the lifting speed and is still not fully understood. For some lifting speeds, such as linear or exponential speed, the instability is transient and the interface eventually shrinks as a circle. However, linear stability analysis suggests there exist shape invariant shrinking patterns if the gap $b(t)$ is increased more rapidly: $$b(t)=\left (1-({7}/{2})\tau \mathcal {C} t\right )^{-{2}/{7}}$$ , where $$\tau$$ is the surface tension and $$\mathcal {C}$$ is a function of the interface perturbation mode $$k$$ . Here, we use a spectrally accurate boundary integral method together with an efficient time adaptive rescaling scheme, which for the first time makes it possible to explore the nonlinear limiting dynamical behaviour of a vanishing interface. When the gap is increased at a constant rate, our numerical results quantitatively agree with experimental observations (Nase et al. , Phys. Fluids , vol. 23, 2011, 123101). When we use the shape invariant gap $b(t)$ , our nonlinear results reveal the existence of $$k$$ -fold dominant, one-dimensional, web-like networks, where the fractal dimension is reduced to almost unity at late times. We conclude by constructing a morphology diagram for pattern selection that relates the dominant mode $$k$$ of the vanishing interface and the control parameter $$\mathcal {C}$$ .