Effects of macro vs. micro initialization and ocean initial-condition memory on the evolution of ensemble spread in the CESM2 large ensemble.

Unlabelled: "Single Model initial-condition Large Ensembles" (SMILEs) conducted with Earth system models have transformed our ability to quantify internal climate variability and forced climate change at local and regional scales. An important consideration in their experimental design is the choice of initialization procedure as this influences the duration of initial-condition memory, with implications for interpreting the temporal evolution of both the ensemble-mean and ensemble-spread. Here we leverage the strategic design of the 100-member Community Earth System Model version 2 (CESM2) SMILE to investigate the dependence of ensemble spread on the method of initialization (micro- vs.

GARD-LENS: A downscaled large ensemble dataset for understanding future climate and its uncertainties.

This article introduces the Generalized Analog Regression Downscaling method Large Ensemble (GARD-LENS) dataset, comprised of daily precipitation, mean temperature, and temperature range over the Contiguous U.S., Alaska, and Hawaii at 12-km, 4-km, and 1-km resolutions, respectively.

Pacific decadal oscillation and ENSO forcings of northerly low-level jets in South America.

The hydrological cycle in South America during austral summer, including extreme precipitation and floods, is significantly influenced by northerly low-level jets (LLJs) along the eastern Andes. These synoptic weather events have been associated with three different types of LLJs (Central, Northern, and Andes) and are sensitive to remote large-scale forcings. This study investigates how tropical forcings related to El Niño/Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) regulate the duration and frequency of each LLJ type and their impacts on extreme precipitation.

The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States.

Many current gridded surface meteorological datasets are inadequate for quantifying near-surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather.

Impacts of Thunderstorm-Generated Gravity Waves on the Ionosphere-Thermosphere Using TIEGCM-NG/MAGIC Simulations and Comparisons With GNSS TEC, ICON, and COSMIC-2 Observations.

We use the TIEGCM-NG nudged by MAGIC gravity waves to study the impacts of a severe thunderstorm system, with a hundred tornado touchdowns, on the ionospheric and thermospheric disturbances. The generated waves induce a distinct concentric ring pattern on GNSS TIDs with horizontal scales of 150-400 km and phase speeds of 150-300 m/s, which is well simulated by the model. The waves show substantial vertical evolution in period, initially dominated by 0.

A magnetohydrodynamic mechanism for the formation of solar polar vortices.

Polar vortices are ubiquitous features of planetary atmospheric flows, from the Earth-like rocky planets to Jupiter- and Saturn-like gas giant planets. Very little is known about their existence or dynamics on the Sun. What should be expected near the Sun's pole for the upcoming solar multi-viewpoint and polar missions? Here, we report the magnetohydrodynamic (MHD) nonlinear simulations for the formation and evolution of solar polar vortices using a near-surface MHD shallow-water model.

HyG: A hydraulic geometry dataset derived from historical stream gage measurements across the conterminous US.

Regional- and continental-scale hydrologic models are increasingly important forecasting tools, yet they rely on highly variable channel parameters (e.g. width, depth, hydraulic resistance) that remain unquantified for millions of stream reaches across the country.

The pace of change of summertime temperature extremes.

Summer temperature extremes can have large impacts on humans and the biosphere, and an increase in heat extremes is one of the most visible symptoms of climate change. Multiple mechanisms have been proposed that would predict faster warming of heat extremes than typical summer days, but it is unclear whether this is occurring. Here, we show that, in both observations and historical climate model simulations, the hottest summer days have warmed at the same pace as the median globally, in each hemisphere, and in the tropics from 1959 to 2023.

DeepMIP-Eocene-p1: multi-model dataset and interactive web application for Eocene climate research.

Paleoclimate model simulations provide reference data to help interpret the geological record and offer a unique opportunity to evaluate the performance of current models under diverse boundary conditions. Here, we present a dataset of 35 climate model simulations of the warm early Eocene Climatic Optimum (EECO; ~ 50 million years ago) and corresponding preindustrial reference experiments. To streamline the use of the data, we apply standardised naming conventions and quality checks across eight modelling groups that have carried out coordinated simulations as part of the Deep-Time Model Intercomparison Project (DeepMIP).

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.

Examining urban resilience through a food-water-energy nexus lens to understand the effects of climate change.

Urban centers located on the coast expose some of the most vulnerable populations to the effects of climate change. In addition to the challenges faced by high population densities and interdependent social-ecological systems, there is an increasing demand for resources. Exposing the pinch points that are already sensitive to extreme weather, highlights the urban systems that will be least resilient in the face of climate change.

Sociodemographic Determinants of Extreme Heat and Ozone Risk Among Older Adults in 3 Sun Belt Cities.

Background: Vulnerable populations across the United States are frequently exposed to extreme heat, which is becoming more intense due to a combination of climate change and urban-induced warming. Extreme heat can be particularly detrimental to the health and well-being of older citizens when it is combined with ozone. Although population-based studies have demonstrated associations between ozone, extreme heat, and human health, few studies focused on the role of social and behavioral factors that increase indoor risk and exposure among older adults.

Managing synthetic N-fertilizer emissions in India: Insights from field surveys across 102 districts.

The use of fixed emission factors (EFs), combined with insufficient temporal distribution, leads to substantial uncertainties in current emission inventories for India, the world's second-largest producer and consumer of synthetic N-fertilizers. Our study aimed to improve the NH and NO emission estimates by utilizing crop-specific district-level activity data and refined EFs tailored to Indian conditions. In this study, a comprehensive NH and NO emission inventory (EI) is methodically developed at 0.

Air Quality Monitoring and the Safety of Farmworkers in Wildfire Mandatory Evacuation Zones.

The increasing frequency and severity of wildfires due to climate change pose health risks to migrant farm workers laboring in wildfire-prone regions. This study focuses on Sonoma County, California, investigating the effectiveness of air monitoring and safety protections for farmworkers. The analysis employs AirNow and PurpleAir PM data acquired during the 2020 wildfire season, comparing spatial variability in air pollution.

Are turbulence effects on droplet collision-coalescence a key to understanding observed rain formation in clouds?

Rain formation is a critical factor governing the lifecycle and radiative forcing of clouds and therefore it is a key element of weather and climate. Cloud microphysics-turbulence interactions occur across a wide range of scales and are challenging to represent in atmospheric models with limited resolution. Based on past experiments and idealized numerical simulations, it has been postulated that cloud turbulence accelerates rain formation by enhancing drop collision-coalescence.

Data-driven modeling of equatorial atmospheric waves: The role of moisture and nonlinearity on global-scale instabilities and propagation speeds.

The equatorial region of the Earth's atmosphere serves as both a significant locus for phenomena, including the Madden-Julian Oscillation (MJO), and a source of formidable complexity. This complexity arises from the intricate interplay between nonlinearity and thermodynamic processes, particularly those involving moisture. In this study, we employ a normal mode decomposition of atmospheric reanalysis ERA-5 datasets to investigate the influence of nonlinearity and moisture on amplitude growth, propagation speed, and mode coupling associated with equatorially trapped waves.

Effectiveness of respiratory face masks in reducing acute PM pollution exposure during peak pollution period in Delhi.

The cities of North India, such as Delhi, face a significant public health threat from severe air pollution. Between October 2021 and January 2022, 79 % of Delhi's daily average PM (Particulate matter with an aerodynamic diameter ≤ 2.5 μm) values exceeded 100 μg/m (the permissible level being 60 μg/m as per Indian standards).

Factors influencing underrepresented geoscientists' decisions to accept or decline faculty job offers.

Many geoscience departments are taking steps to recruit and retain faculty from underrepresented groups. Here we interview 19 geoscientists who identify as an underrepresented race or gender who recently declined a tenure-track faculty job offer. A range of key factors influenced their decisions to accept or decline a position including commitment to diversity, equity, and inclusion (DEI) including personal identities, DEI initiatives, and mentorship; (in)civility during job interviews; values revealed in negotiation; and compatibility with personal life including family and geography.

Last Glacial Maximum pattern effects reduce climate sensitivity estimates.

Here, we show that the Last Glacial Maximum (LGM) provides a stronger constraint on equilibrium climate sensitivity (ECS), the global warming from increasing greenhouse gases, after accounting for temperature patterns. Feedbacks governing ECS depend on spatial patterns of surface temperature ("pattern effects"); hence, using the LGM to constrain future warming requires quantifying how temperature patterns produce different feedbacks during LGM cooling versus modern-day warming. Combining data assimilation reconstructions with atmospheric models, we show that the climate is more sensitive to LGM forcing because ice sheets amplify extratropical cooling where feedbacks are destabilizing.

East Asian summer monsoon delivers large abundances of very-short-lived organic chlorine substances to the lower stratosphere.

Deep convection in the Asian summer monsoon is a significant transport process for lifting pollutants from the planetary boundary layer to the tropopause level. This process enables efficient injection into the stratosphere of reactive species such as chlorinated very-short-lived substances (Cl-VSLSs) that deplete ozone. Past studies of convective transport associated with the Asian summer monsoon have focused mostly on the south Asian summer monsoon.

High-resolution repeat topography of drifting ice floes in the Arctic Ocean from terrestrial laser scanning.

Snow and ice topography impact and are impacted by fluxes of mass, energy, and momentum in Arctic sea ice. We measured the topography on approximately a 0.5 km drifting parcel of Arctic sea ice on 42 separate days from 18 October 2019 to 9 May 2020 via Terrestrial Laser Scanning (TLS).