Month: April 2025

Our new paper, “Observation and simulation of methane plumes during the morning boundary layer transition“, is published in Journal of Geophysical Research: Atmospheres (IF: 3.8).

The paper can be downloaded at https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2024JD042317.

Authors: Xiao-Ming Hu, Wesley Honeycutt, Chenghao Wang, Binbin Weng, Bowen Zhou, & Ming Xue

Abstract: Methane (CH₄) contributes significantly to global warming. However, accurate identification of CH₄ sources for reducing CH₄ emissions is often hampered by inadequate accuracy and spatiotemporal coverage of CH₄ detection, and lack of accurate CH₄ forward modeling used in top-down inversion systems. In this study, a field experiment was conducted in Pampa, Texas using two CH₄ sensors (LI-COR and OGI camera) to detect CH₄ releases. We investigated whether high-resolution simulations using the Weather Research and Forecasting (WRF) model with greenhouse gases (WRF-GHG) could accurately simulate the CH₄ plumes in the presence of evolving atmospheric boundary layer from sunrise to noon. CH₄ plumes showed substantial variation in time. At a release rate of ∼17.5 kg hr⁻¹, the maximum enhancement of CH₄ measured by LI-COR was 2.6 ppm at sunrise (7:36 a.m.), 250 m from the release location. Within half an hour after sunrise, this enhancement decreased to 0.3–0.4 ppm. The enhancement was 0.2 ppm by 10:00 a.m. and further dropped to less than 0.1 ppm after 11:30 a.m. Due to the low temperature at sunrise, the OGI camera failed to detect the CH₄ plume. The WRF-GHG large-eddy simulation (LES) with 32 m grid spacing successfully reproduced these CH₄ enhancements. In situ measurements together with numerical simulations illustrate the impact of the transition from a stable boundary layer in the early morning to a convective boundary layer at noon on the dispersion of CH₄ plumes. Additionally, CH₄ plumes from a cattle farm in Oklahoma are briefly examined using the same modeling approach.

DOI: https://doi.org/10.1029/2024JD042317

Our new paper, “Assessment of convection-permitting hydroclimate modeling in urban areas across the contiguous United States“, is published in Urban Climate (IF: 6.0). This work was led by undergraduate student Liam Thompson. Congratulations, Liam!

The paper can be downloaded at https://www.sciencedirect.com/science/article/pii/S2212095525000914.

Authors: Liam Thompson, Chenghao Wang, Cenlin He, Tzu-Shun Lin, Changhai Liu, and Jimy Dudhia

Abstract: Accurate representation of urban areas in weather and climate models is crucial for simulating interactions between urban surfaces and the atmospheric boundary layer, especially in high-resolution regional models that resolve deep convection. However, many continental-scale simulations use simplified urban parameterizations, raising questions about their ability to reproduce urban hydroclimate. This study evaluates CONUS404—a recent USGS-NCAR 4-km convection-permitting hydroclimate modeling dataset—in urban areas across the contiguous United States (CONUS). We assessed hourly near-surface air temperature, dewpoint, and wind speed simulations at 208 urban and 342 non-urban station locations from 2011 to 2020 using observations. Results show that CONUS404 performs better for air temperature in urban areas, with a slight mean warm bias (0.08 °C) at urban stations and a mean cold bias (−0.52 °C) at non-urban stations. Dewpoint simulations exhibit stronger dry biases at urban stations, suggesting underrepresented evapotranspiration from urban vegetation. Wind speed is generally underestimated, with average biases of −0.74 m s⁻¹ at urban and −0.35 m s⁻¹ at non-urban stations. Seasonal analyses reveal larger model errors for wintertime temperature and dewpoint that strongly depend on urban fraction. These findings highlight the limitations of the bulk urban parameterization in CONUS404, underscoring the need for enhanced urban representations to improve continental-scale hydroclimate simulations.

DOI: https://doi.org/10.1016/j.uclim.2025.102375