Prioritizing social vulnerability in urban heat mitigation.

We utilized city-scale simulations to quantitatively compare the diverse urban overheating mitigation strategies, specifically tied to social vulnerability and their cooling efficacies during heatwaves. We enhanced the Weather Research and Forecasting model to encompass the urban tree effect and calculate the Universal Thermal Climate Index for assessing thermal comfort. Taking Houston, Texas, and United States as an example, the study reveals that equitably mitigating urban overheat is achievable by considering the city's demographic composition and physical structure.

Global scale assessment of urban precipitation anomalies.

Urbanization has accelerated dramatically across the world over the past decades. Urban influence on surface temperatures is now being considered as a correction term in climatological datasets. Although prior research has investigated urban influences on precipitation for specific cities or selected thunderstorm cases, a comprehensive examination of urban precipitation anomalies on a global scale remains limited.

GLObal Building heights for Urban Studies (UT-GLOBUS) for city- and street- scale urban simulations: Development and first applications.

We introduce University of Texas - GLObal Building heights for Urban Studies (UT-GLOBUS), a dataset providing building heights and urban canopy parameters (UCPs) for more than 1200 city or locales worldwide. UT-GLOBUS combines open-source spaceborne altimetry (ICESat-2 and GEDI) and coarse-resolution urban canopy elevation data with a machine-learning model to estimate building-level information. Validation using LiDAR data from six U.

Analyzing urban influence on extreme winter precipitation through observations and numerical simulation of two South China case studies.

This study investigates the impact of urbanization on extreme winter rainfall in the South China Greater Bay Area (GBA) through the analysis of hourly station observations and simulations using the Weather Research and Forecasting Model with the Single Layer Urban Canopy Model (WRF-SLUCM). Data from 2008 to 2017 reveal that urban areas in the GBA experience lower 99th percentile hourly winter rainfall intensity compared to surrounding rural regions. However, urban locations exhibit higher annual maximum hourly rainfall (Rmax) and very extreme rainfall events (99.

DownScaleBench for developing and applying a deep learning based urban climate downscaling- first results for high-resolution urban precipitation climatology over Austin, Texas.

Cities need climate information to develop resilient infrastructure and for adaptation decisions. The information desired is at the order of magnitudes finer scales relative to what is typically available from climate analysis and future projections. Urban downscaling refers to developing such climate information at the city (order of 1 - 10 km) and neighborhood (order of 0.

Improving the local climate zone classification with building height, imperviousness, and machine learning for urban models.

The Local Climate Zone (LCZ) classification is already widely used in urban heat island and other climate studies. The current classification method does not incorporate crucial urban auxiliary GIS data on building height and imperviousness that could significantly improve urban-type LCZ classification utility as well as accuracy. This study utilized a hybrid GIS- and remote sensing imagery-based framework to systematically compare and evaluate different machine and deep learning methods.

Accelerating flash droughts induced by the joint influence of soil moisture depletion and atmospheric aridity.

The emergence of flash drought has attracted widespread attention due to its rapid onset. However, little is known about the recent evolution of flash droughts in terms of the speed of onset and the causes of such a rapid onset phase of flash droughts. Here, we present a comprehensive assessment of the onset development of flash droughts and the underlying mechanisms on a global scale.

[Effects of astragaloside Ⅳ on inflammatory response and percentage of peripheral blood Th17 cells in mice with ulcerative colitis].

This study aimed to investigate the anti-inflammatory effect of astragaloside Ⅳ in mice with ulcerative colitis(UC) and its effect on the percentage of peripheral blood T helper(Th17) cells. Following the establishment of UC mouse model with 2% sodium dextran sulfate(DSS), mice in the positive control group and low-and high-dose astragaloside Ⅳ groups were treated with corresponding drugs by gavage. Disease activity index(DAI) was calculated, and serum interleukin-17(IL-17), tumor necrosis factor-α(TNF-α), and transforming growth factor-β(TGF-β) levels were assayed by ELISA.

Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979-2100).

Dynamical downscaling is an important approach to obtaining fine-scale weather and climate information. However, dynamical downscaling simulations are often degraded by biases in the large-scale forcing itself. We constructed a bias-corrected global dataset based on 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) dataset.

Divergent effects of climate change on future groundwater availability in key mid-latitude aquifers.

Groundwater provides critical freshwater supply, particularly in dry regions where surface water availability is limited. Climate change impacts on GWS (groundwater storage) could affect the sustainability of freshwater resources. Here, we used a fully-coupled climate model to investigate GWS changes over seven critical aquifers identified as significantly distressed by satellite observations.

Emergent spectral properties of river network topology: an optimal channel network approach.

Characterization of river drainage networks has been a subject of research for many years. However, most previous studies have been limited to quantities which are loosely connected to the topological properties of these networks. In this work, through a graph-theoretic formulation of drainage river networks, we investigate the eigenvalue spectra of their adjacency matrix.

High sensitivity of Indian summer monsoon to Middle East dust absorptive properties.

The absorptive properties of dust aerosols largely determine the magnitude of their radiative impacts on the climate system. Currently, climate models use globally constant values of dust imaginary refractive index (IRI), a parameter describing the dust absorption efficiency of solar radiation, although it is highly variable. Here we show with model experiments that the dust-induced Indian summer monsoon (ISM) rainfall differences (with dust minus without dust) change from -9% to 23% of long-term climatology as the dust IRI is changed from zero to the highest values used in the current literature.

[Correlation between Signs of Living Body in Abdominal and Pelvic Cavities and Syndrome Typing of Chinese Medicine in Colorectal Cancer Patients].

Objective: To explore the correlation between signs of living body in abdominal and pelvic cavities and syndrome typing of Chinese medicine (CM) in colorectal cancer patients.

Methods: Totally 112 colorectal cancer patients undergoing open abdominal surgery or laporoscopic surgery were syndrome typed as five types, i.e.