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Bin Guan

Publications and source records attributed to Bin Guan.

Climate Extremes and Risks: Links Between Climate Science and Decision-Making

The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.

climate extremes↗

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier2 High-Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common dataset consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Atmospheric Rivers↗

Reversible Colorimetric Sensing of Volatile Analytes By Wicking in Close Proximity to A Photonic Film

Isolation of volatile analytes from environmental or biological fluids is a rate-determining step that can delay the response time for continuous sensing. In this paper, we demonstrate a colorimetric sensing system that enables the rapid detection of gas-phase analytes released from a flowing micro-volume fluid sample. The sensor platform is an analyte-responsive metal-insulator-metal (MIM) thin-film structure integrated with a large area quartz micropillar array. This allows precise planar alignment and microscale separation (310 μm) of the optical and fluidic structures. This configuration offers rapid and homogeneous color changes over large areas that permits detection by low-resolution optics or eye, which is well-suited to portable/wearable devices. For our proof-of-principle demonstration, we utilized a poly(methyl methacrylate) (PMMA) spacer and evaluated the sensor's response (color change) to ethanol vapor. We show that the RGB color value is quantitatively linked to the spacer swelling, which is reversible and repeatable. The optofluidic platform reduces the sensor response time from minutes to seconds compared with experiments using a conventional chamber. The sensor's concentration-dependent response was examined, confirming the potential of the reported sensing platform for continuous, compact, and quantitative colorimetric analysis of volatile analytes in low-volume samples, such as biofluids.

Timothy J. Palinski↗