National Center for Atmospheric Research

Abstract Cold plasma distribution in the ionosphere‐plasmasphere system governs wave‐particle interactions, plasma energization and loss, and radio wave propagation. A longstanding observational gap at altitudes 800–8,000 km has largely prevented studying the coupled dynamics of the two regions. Here, we show that observations by JAXA's Arase mission can bridge this gap. Electron densities inferred from the upper hybrid resonance frequencies measured by Arase are highly consistent with radio occultation profiles from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission, with a median difference of 5%. Using the combined COSMIC‐Arase data set, we provide a convenient way to reconcile the two regions in empirical models based on the analytical Chapman function inversion for scale height. Our results enable studying fundamental questions about the ionosphere‐plasmasphere coupling, their transition, and life cycle of cold plasma in near‐Earth space.

Abstract 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. Methods We conducted a household survey that aimed to understand how older adults are affected by extreme heat and ozone pollution inside and outside of their homes across Houston, Phoenix, and Los Angeles. We examine contributing factors to the risk of self-reported health effects using a generalized linear mixed-effects regression model of telephone survey data of 909 older adults in 2017. Results We found an increased occurrence of self-reported symptoms for extreme heat with preexisting respiratory health conditions and a lack of air conditioning access; self-reported ozone symptoms were more likely with preexisting respiratory health conditions. The risk of heat-related symptoms was slightly higher in Los Angeles than Houston and Phoenix. We found several demographic, housing, and behavioral characteristics that influenced the risk of heat- and ozone-related symptoms. Conclusions The increased risk among older adults based on specific social and behavioral factors identified in this study can inform public health policy and help cities tailor their heat and ozone response plans to the specific needs of this vulnerable population.

Climate feedbacks are expected to increase over time due to the “pattern effect,” which describes the influence of the pattern of surface warming on global climate feedbacks. Delayed warming in the tropical east Pacific - as seen in abrupt4xCO2 simulations - causes increases in climate feedbacks and warming. Several explanations for the relationship between the pattern of sea-surface temperature (SST) warming and climate feedbacks have been proposed, but previous literature has not reached a consensus. Previous literature has often highlighted the role of “tropospheric stability,” whose changes are highly correlated with changes in low clouds with warming. Relatedly, a “circus tent" model posits that in regions of deep convection, convection communicates local SST anomalies vertically. The pattern of SST response also influences the strength of the “Walker circulation”. We introduce a new ensemble of patch experiments and use it, along with observations and reanalysis of the historical period, to evaluate these three proposed mechanisms, in isolation and their relationship to one another. The ensemble of patch experiments is created using the Community Atmosphere Model, version 6 (CAM6) by applying SST patches consistent with the Green's Function Model Intercomparison Project (GFMIP) protocol. This ensemble uses a satellite simulator package, enabling enhanced cloud diagnostics, which reveals that tropical marine low-cloud feedbacks are sensitive to SST anomalies in deep convective regions (nonlocally). Consistently, we find evidence that the circus tent and lower tropospheric stability mechanisms largely explain the relationship between the pattern of SST warming and climate feedbacks and are closely related to one another.

This study analyzes ozone (O3) dry deposition fluxes and velocities (Vd) from twelve regional-scale simulations that were performed over North America and Europe in Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). AQMEII4 collected grid-aggregated and land use (LU)-specific O3 Vd and effective conductances and fluxes for the four major dry deposition pathways. Consistent with recent findings in the AQMEII4 point model intercomparison study, analysis of the grid-aggregated fields shows that grid models with similar Vd can exhibit significant differences in the absolute and relative contributions of the different depositional pathways. Analysis of LU-specific Vd and effective conductances reveals a general increase in model spread compared to grid-aggregated values. This indicates that an analysis of only grid-aggregated deposition diagnostics can mask process-specific differences that exist between schemes. An analysis of AQMEII4 LU distributions across models revealed substantial differences in the spatial patterns and abundance of certain LU categories over both domains, especially for non-forest partially vegetated categories such as agricultural areas, shrubland, and grassland. We demonstrate that these differences can significantly contribute to or even drive differences in LU-specific dry deposition fluxes which can increase the variability in model predictions of ozone. Two recommendations for future deposition-focused modeling studies emerging from the AQMEII4 analyses presented here are to 1) routinely generate diagnostic outputs to advance a process-based understanding of modeled deposition and support impact analyses, and 2) recognize the importance of documenting and analyzing the representation of LU across models and work towards harmonizing this aspect when using air-quality grid models and model ensembles for deposition analyses.

Abstract We present a case study of a moderate geomagnetic storm, which exhibits an abrupt relativistic enhancement in the heart of the radiation belt accompanied by low‐latitude purple auroral emission. The relativistic enhancement occurs on a timescale of tens of minutes and reaches MeV energies deep within the inner magnetosphere. The enhancement is concurrent with mesoscale purple patches which protrude below the pre‐existing auroral oval. We analyze the event using a novel combination of observational data sets and physics‐based modeling. This includes multispectral auroral imaging, dosimeter data from the Global Positioning System constellation, auroral transport modeling, and global geospace modeling. Our analysis reveals the cause of both the radiation belt enhancement and purple emission to be direct, mesoscale injections of electrons reaching relativistic energies. Finally, we show that these injections are most likely caused by near‐Earth reconnection which produces deeply depleted entropy bubbles capable of trapping and transporting energetic particles into the inner magnetosphere.

Abstract Statistical downscaling is a computationally efficient approach in producing a large ensemble of fine-resolution future climate projections to support local climate adaptation efforts. Here, we propose a deep learning–based framework, named BC_DLD, to downscale the Coupled Model Intercomparison Project phase 6 (CMIP6) Earth system model (ESM) outputs from the coarse native resolution to a locally relevant fine resolution at kilometer scale and apply it to the Northeast United States, a region experiencing rapid increase of heavy precipitation and in great need for locally actionable climate information. Employing a two-phase multivariate approach by utilizing an empirical-quantile delta mapping (E-QDM) approach for bias correction at a coarse resolution and deep convolutional neural networks (CNNs) for downscaling the corrected data to a finer spatial resolution, BC_DLD is designed to preserve the spatial characteristics from observations while retaining the temporal characteristics and climate change signals from ESMs. Here, we demonstrate the implementation of BC_DLD by downscaling the outputs of GFDL-ESM4 historical run and future shared socioeconomic pathway (SSP) 5–8.5 scenario over the Northeast, from ∼100 to ∼25 km [using fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5) as reference] and then further down to ∼6 km (using Livneh data as reference), and compare the downscaled data with an existing product, localized constructed analogs, version 2 (LOCA2). Despite using the same observational training data as LOCA2, BC_DLD produces more intense and rapid future increase of extreme precipitation than LOCA2, alleviating the underestimation of extremes common among statistical downscaling products. The emergent relationship between extreme precipitation intensity and temperature in BC_DLD more closely resembles the observations, further establishing its efficacy in producing useful and usable future climate projections.

Abstract The early career stage for scientific researchers and faculty is fraught with challenges, including establishing professional relationships, securing funding, balancing work and personal life, and navigating job uncertainties. Early career professionals were among those especially impacted by the COVID-19 pandemic, in having limited opportunities for networking and professional development. Recognizing these challenges, the University Corporation for Atmospheric Research (UCAR) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) piloted a 1-day professional development workshop in Boulder, Colorado, on 8 October 2023 as a preworkshop for the biannual UCAR Members Meeting. We hoped to foster networking and peer learning among 122 attendees from the atmospheric sciences, 76 (62%) of whom were university faculty and 46 (38%) of whom were postdocs, researchers, and staff from NSF NCAR and UCAR. Participants, representing 58 universities across the U.S. and Canada, engaged in a program that included networking events, informational sessions, and hands-on workshops. Sessions covered topics such as active learning, mentoring graduate students, understanding tenure, time management, mental health, fostering welcoming environments, and grant proposal writing. Feedback from participants highlighted the value of networking opportunities and peer learning, emphasizing the importance of continued professional development tailored to early career scientists’ needs. The workshop also allowed us to learn more about challenges early career professionals are facing. This workshop serves as a model for future initiatives aimed at supporting early career researchers in Earth system science and related fields.

We investigate the high-latitude Joule heating in a recently developed high-resolution configuration of the WACCM-X whole-atmosphere model coupled to the GAMERA magnetosphere model. Model resolution and geomagnetic forcing effects during the severe ge

Accurate forecasting of PM₂.₅ (particulate matter ≤ 2.5 μm) is essential for effective air quality management, particularly in urban areas like Delhi, which frequently experience severe pollution episodes. This study evaluates the predictive capabilit

Previous studies indicate that climate models misrepresent southeast United States coastal sea level variability but do not propose a definitive mechanistic explanation. Here, by isolating a mode of variability responsible for the majority of observed