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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Interannual variability and trends of summertime PM2.5-based air quality in the Intermountain West

Abstract Summertime air quality is a growing public health concern in the populated region of Northern Utah. Whereas winter air pollution is highly linked with local atmospheric temperature inversions associated with upper atmospheric high-pressure and radiational cooling in valleys, the relationship between climate factors and the frequency of poor air quality during summer is still unknown. Analyzing the last 20 years of data, we demonstrated that summertime unhealthy days (as defined by PM2.5 air quality index level) in Northern Utah highly correlate with the number of dry-hot days, wildfire size, and an upper atmospheric ridge over the Northwestern United States. The persistent atmospheric ridge enhances lightning-caused fire burned areas in northwestern states and then transports the wildfire smoke toward Northern Utah. Similarly, climate model simulations confirm observational findings, such as an increasing trend of the upper atmospheric ridge and summertime dry days in the northwestern states. Such metrics developed in this study could be used to establish longer-term monitoring and seasonal forecasting for air quality and its compounding factors, which is currently limited to forecasting products for only several days.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Intercomparison of Deep Learning Model Architectures for Atmospheric River Prediction

With a rapid surge in the application of machine learning (ML) for a diverse range of tasks in climate science, the present study addresses a challenge for climate scientists when selecting the optimal ML or deep learning (DL) architecture for a given application. In particular, a DL intercomparison study was performed with a focus on forecasting the position of atmospheric rivers (ARs) on short-range time scales (up to 5-day lead times). AR predictions from multiple DL architectures, including various types of convolutional autoencoders and a vision transformer (ViT), were compared against ECMWF ERA5 reanalysis and hindcasts from a global climate model. DL models with similar trainable parameters were trained on ERA5 reanalysis data and AR positions derived from a thresholding algorithm to ensure a fair comparison among the DL models. Each model’s performance and accuracy in forecasting AR location and key input fields within a 5-day window were assessed using metrics of root-mean-square error, anomaly correlation, and mean intersection over union. The ViT architecture outperformed other autoencoder models in most of the metrics. Incorporating additional meteorological fields only yielded slight improvements in forecasting certain fields at longer lead times. The results also suggest that a smaller number of input time steps or smaller number of autoregressive steps can achieve better prediction skills, while also improving the overall computational efficiency. This research offers valuable insights into the strengths and weaknesses of different DL techniques for AR forecasting, hopefully guiding the development of improved models for forecasting this phenomenon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The QBO–MJO Connection: A Possible Role for the SST and ENSO

We examine the hypothesis that the observed connection between the stratospheric quasi-biennial oscillation (QBO) and the strength of the Madden–Julian oscillation (MJO) is modulated by the sea surface temperature (SST)—for example, by El Niño–Southern Oscillation (ENSO). A composite analysis shows that, globally, La Niña SSTs are remarkably similar to those that occur during the easterly phase of the QBO. A maximum covariance analysis suggests that MJO power and SST are strongly linked on both the ENSO time scale and the QBO time scale. We analyze simulations with a modified configuration of version 2 of the Community Earth System Model, with a high top and fine vertical resolution. The model is able to simulate ENSO, the QBO, and the MJO. The ocean-coupled version of the model simulates the QBO, ENSO, and MJO, but does not simulate the observed QBO–MJO connection. When driven with prescribed observed SST anomalies based on composites for QBO east and QBO west (QBOE and QBOW), however, the same atmospheric model produces a modest enhancement of MJO power during QBOE relative to QBOW, as observed. We explore the possibility that the SST anomalies are forced by the QBO itself. Indeed, composite Hovmöller diagrams based on observations show the propagation of QBO zonal wind anomalies all the way from the upper stratosphere to the surface. Also, subsurface ocean temperature composites reveal a similarity between the western Pacific and Indian Ocean subsurface signal between La Niña and QBOE.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessing Tropical Cyclones’ Contribution to Precipitation over the Eastern United States and Sensitivity to the Variable-Resolution Domain Extent

Tropical cyclones (TCs) can subject an area to heavy precipitation for many hours, or even days, worsening the risk of flooding, which creates dangerous conditions for residents of the U.S. East and Gulf Coasts. To study the representation of TC-related precipitation over the eastern United States in current-generation global climate models, a novel analysis methodology is developed to track TCs and extract their associated precipitation using an estimate of their dynamical outer size. This methodology is applied to three variable-resolution (VR) configurations of the Community Atmosphere Model, version 5 (CAM5), with high-resolution domains over the North Atlantic and one low-resolution conventional configuration, as well as to a combination of reanalysis and observational precipitation data. Metrics and diagnostics such as TC counts, intensities, outer storm sizes, and annual mean total and extreme precipitation are compared between the CAM5 simulations and reanalysis/observations. The high-resolution VR configurations outperform the global low-resolution configuration for all variables in the North Atlantic. Realistic TC intensities are produced by the VR configurations. The total North Atlantic TC counts are lower than observations but better than reanalysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Downward Convective Moisture Transport Dominated by a Few Overshooting Clouds in Marine and Continental Shallow Convection

Abstract In a previous study (Xiao et al., 2023, https://doi.org/10.1029/2022ms003526 ), we found that ignoring the moist convective downdrafts associated with overshooting clouds in parameterizations can lead to significant biases in the simulated depth and liquid water content of a shallow cloud layer. In this study, we seek to better quantify the properties of the clouds responsible for these moist downdrafts to help improve shallow convection parameterizations. We apply a 3‐D cloud‐tracking algorithm to large‐eddy simulations (LESs) of marine and continental shallow convection. We find that top 1% and 2% of the tracked cloud population ranked by lifetime‐mean cloud‐base mass flux can explain 90%–95% of the total downward moisture transport in the upper cloud layer whereas top 10%–20% is required to explain 90%–95% of the total upward moisture transport near mean cloud base. The vertical structure of the clouds in the top 1% and 2% (the overshooting “deep mode”) is also distinctively different from that of the rest of the cloud population (the “shallow mode”). Shallow convection parameterizations need to capture accurately the properties and convective transports of the clouds in both the deep and shallow modes. To do that, our results suggest that mass‐flux parameterizations need to (a) accurately predict the size and number of the deep‐mode clouds and (b) explicitly represent overshooting cloud updrafts and associated moist downdrafts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Amazon Water Cycle: Perspectives from Water Budget Closure and Ocean Salinity

Global and regional water cycle includes precipitation, water vapor divergence, and change of column water vapor in the atmosphere, and land surface evapotranspiration, terrestrial water storage change, and river discharge, which is linked to ocean salinity near the river mouth. The water cycle is a crucial component of the Earth system, and numerous studies have addressed its individual components (e.g., precipitation). Here we assess, for the first time, if remote sensing and reanalysis datasets can accurately and self-consistently portray the Amazon water cycle. This is further assisted with satellite ocean salinity measurements near the mouth of the Amazon River. The widely used practice of taking the mean of an ensemble of datasets to represent water cycle components (e.g., precipitation) can produce large biases in water cycle closure. Additionally, closure is achieved with only a small subset of data combinations (e.g., ERA5 precipitation and evapotranspiration plus GRACE satellite terrestrial water storage), which rules out the lower precipitation and higher evapotranspiration estimates, providing valuable constraints on assessments of precipitation, evapotranspiration, and their ratio. The common approach of using the Óbidos stream gauge (located hundreds of kilometers from the river mouth) multiplied by a constant (1.25) to represent the entire Amazon discharge is found to misrepresent the seasonal cycle, and this can affect the apparent influence of Amazon discharge on tropical Atlantic salinity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

SAIL Supermicron Bioaerosol (SSB) Field Campaign Report

The Surface Atmosphere Integrated Field Laboratory (SAIL) Supermicron Bioaerosol (SSB) study was designed to complement the larger Atmospheric Radiation Measurement (ARM) SAIL science goals to understand aerosol processes and aerosol-cloud interactions in the Colorado River’s East River Watershed Basin. Supermicron aerosol, particles larger than one micron in diameter, and bioaerosols, primary particles containing biological material, are important for understanding atmospheric processes and sources within high mountainous terrain. For example, they can interact with clouds and the water cycle such as by serving as nuclei for cloud droplets and ice crystals that can eventually result in precipitation events. These particles can also be recycled back to the surface via wet and dry deposition, where they can alter plant and microbial growth and/or be reemitted again, forming a positive feedback loop within the Earth system known as bioprecipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Vertical Aerosol Profiling during SAIL (VAPS) Field Campaign Report

To more fully address the science goals of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s Surface Atmosphere Integrated Field Laboratory (SAIL) campaign, particularly the key science question of “How strongly do aerosols affect the surface energy and water balance by altering clouds, precipitation, and surface albedo, and how do these impacts vary seasonally?”, our campaign added instrumentation to planned tethered balloon system (TBS) flights in May and July of 2022. A key aspect of aerosol-cloud interactions is understanding cloud condensation nuclei (CCN) and ice nucleating particle (INP) populations, and how they vary seasonally and spatially. Because the interactions between aerosols and clouds is the target of this work, vertical distributions are particularly important to evaluate. Measurements of aerosol at ground level, below-cloud, and in-cloud will allow a better understanding of the airmasses that are feeding cloud-active particles into low- and mid-level clouds. Measurements of INP and aerosol populations often differ between the ground and aloft, with relationships that likely depend on regional and seasonal. Because of this, collocated measurements of aerosol, CCN, and INP, across different seasons, are crucial to reducing uncertainties in relationships between ground-level and cloud-base aerosol populations. Our campaign added online measurements of CCN using a compact CCN counter and offline filter collections for measurement of INP populations to the SAIL campaign TBS flights in May and July of 2022. The CCN instrument, the CloudPuck, flew and successfully collected data for a total of eight flights across both campaign periods. The IcePuck flew for most flights during the same period. Both instruments have continued to be used for other campaign requests in the SAIL domain. Analysis of this data was proposed through a concurrent DOE Atmospheric System Research (ASR) project submission, which was not funded in 2022. A similar proposal, which would involve analysis of the samples and data collected from this campaign, has been resubmitted in 2023 but a funding decision has not yet been made. If the proposal is again declined, we will seek other resources to ensure that this data can be analyzed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Uncertainties in Simulating Flooding During Hurricane Harvey Using 2D Shallow Water Equations

Abstract Flooding is one of the most impactful weather‐related natural hazards. Numerical models that solve the two dimensional (2D) shallow water equations (SWE) represent the first‐principles approach to simulate all types of spatial flooding, such as pluvial, fluvial, and coastal flooding, and their compound dynamics. High spatial resolution (e.g., () m) is needed in 2D SWE simulations to capture flood dynamics accurately, resulting in formidable computational challenges. Thus, relatively coarser spatial resolutions are used for large‐scale simulations of flooding, which introduce uncertainties in the results. It is unclear how the uncertainty associated with the model resolution compares to the uncertainties in precipitation data sets and assumptions regarding boundary conditions when channelized flows interact with other water bodies. In this study, we compare these three sources of uncertainties in 2D SWE simulations for the 2017 Houston flooding event. Our results show that precipitation uncertainty and mesh resolution have more significant impacts on the simulated streamflow and inundation dynamics than the choice of the downstream boundary condition at the watershed outlet. We point out the viability to confine the uncertainty of coarsening mesh resolution by using the variable resolution mesh (VRM) which refines critical topographic features with far fewer grid cells. Specifically, in simulations with VRM, the simulated inundation depths over the refined region are comparable to that use the finest uniform mesh. This study contributes to understanding the challenges and pathways for applying 2D SWE models to improve the realism of flood simulations over large scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multiscale Airborne Infectious Disease Transmission

Airborne disease transmission is central to many scientific disciplines, including agriculture, veterinary biosafety, medicine, and public health. Legal and regulatory standards are in place to prevent agricultural, nosocomial, and community airborne disease transmission. However, the overall importance of the airborne pathway is underappreciated; e.g., the U.S. National Library of Medicine’s Medical Subjects Headings (MESH) thesaurus lacks an airborne disease transmission indexing term. This has practical consequences, as airborne precautions to control epidemic disease spread may not be taken when airborne transmission is important but unrecognized. Publishing clearer practical methodological guidelines for surveillance studies and disease outbreak evaluations could help address this situation. To inform future work, this paper highlights selected, well-established airborne transmission events, largely cases replicated in multiple, independently conducted scientific studies. Methodologies include field experiments, modeling, epidemiology studies, disease outbreak investigations, and mitigation studies. Collectively, this literature demonstrates that airborne viruses, bacteria, and fungal pathogens have the ability to cause disease in plants, animals, and humans over multiple distances, from near range (<5 m) to continental (>500 km) in scale. The plausibility and implications of undetected airborne disease transmission are discussed, including the notable underreporting of disease burdens for several airborne-transmitted diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Changes in Convective Available Potential Energy and Convective Inhibition under Global Warming

Atmospheric convective available potential energy (CAPE) is expected to increase under greenhouse gas–induced global warming, but a recent regional study also suggests enhanced convective inhibition (CIN) over land although its cause is not well understood. In this study, a global climate model is first evaluated by comparing its CAPE and CIN with reanalysis data, and then their future changes and the underlying causes are examined. The climate model reasonably captures the present-day CAPE and CIN patterns seen in the reanalysis, and projects increased CAPE almost everywhere and stronger CIN over most land under global warming. Over land, the cases or times with medium to strong CAPE or CIN would increase while cases with weak CAPE or CIN would decrease, leading to an overall strengthening in their mean values. These projected changes are confirmed by convection-permitting 4-km model simulations over the United States. The CAPE increase results mainly from increased low-level specific humidity, which leads to more latent heating and buoyancy for a lifted parcel above the level of free convection (LFC) and also a higher level of neutral buoyancy. The enhanced CIN over most land results mainly from reduced low-level relative humidity (RH), which leads to a higher lifting condensation level and a higher LFC and thus more negative buoyancy. Over tropical oceans, the near-surface RH increases slightly, leading to slight weakening of CIN. Over the subtropical eastern Pacific and Atlantic Ocean, the impact of reduced low-level atmospheric lapse rates overshadows the effect of increased specific humidity, leading to decreased CAPE.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of the mid-latitude zonal circulation on dynamic mechanism of anomalous precipitation over China in summer 2021

China was hit by extreme precipitation in July and August of 2021 along with significant monthly variation. The positive precipitation anomalies observed in July were mainly located in eastern China, but these anomalies shifted to the middle and lower reaches of the Yangtze River (MLYR) in August. In this study, we investigated the July and August precipitation anomaly dynamics based on the three-pattern decomposition of global atmospheric circulation (3P-DGAC) method. The results showed that the mid-latitude zonal circulation played a dominant role in July 2021, causing anomalous positive relative vorticity advection over the center of the positive precipitation anomalies, thus providing strong convective activity for the anomalous precipitation. Nevertheless, the August anomalies could be better explained from a climate perspective. The anomalous relative vorticity distribution patterns recorded in August were often accompanied by extreme precipitation in the MLYR, and the negative relative vorticity anomalies identified in Northeast Asia also played a crucial role. In conclusion, the mechanisms of precipitation anomalies in July and August 2021 were almost completely disparate. In this study, we emphasized the role of the mid-latitude zonal circulation in extreme precipitation events, and suggested that the impact of mid-latitude zonal circulation will be further accentuated under global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TRACER SPARC AERI Data

These files contain 24 hour periods of retrieved thermodynamic profiles derived from observations collected by the University of Wisconsin–Madison Space Science and Engineering Center Portable Atmospheric Research Center (SPARC) Atmospheric Emitted Radiance Interferometer (AERI). The TROPoe algorithm is a python equivalent to the AERIoe algorithm (see Turner and Loehnert, 2014; Turner and Blumberg 2019). These data were collected during the TRACER project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Role of Wind Speed in Prolonging Large Fire Durations in the Western US

Abstract The duration of large wildfires in the western US has increased significantly from 1992 to 2020 in the two fire seasons, by 0.76 days yr −1 in summer and 0.55 days yr −1 in fall. The factors driving the trend and variability were analyzed using multiple linear regression models. Our analysis identified the maximum daily wind speed during large fires, which has also increased during the study period, as the primary predictor for the large fire duration. Despite the observed rise in maximum wind speed specifically during large fires, there are no corresponding trends in the average daily mean wind speed throughout the fire seasons. The mechanisms underlying the increase in maximum wind speed during large fires remain unclear and warrant further investigation, as they may pose growing challenges for fire control.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Vertically Resolved Canopy Improves Chemical Transport Model Predictions of Ozone Deposition to North Temperate Forests

Abstract Dry deposition is the second largest tropospheric ozone (O 3 ) sink and occurs through stomatal and nonstomatal pathways. Current O 3 uptake predictions are limited by the simplistic big‐leaf schemes commonly used in chemical transport models (CTMs) to parameterize deposition. Such schemes fail to reproduce observed O 3 fluxes over terrestrial ecosystems, highlighting the need for more realistic treatment of surface‐atmosphere exchange in CTMs. We address this need by linking a resolved canopy model (1D Multi‐Layer Canopy CHemistry and Exchange Model, MLC‐CHEM) to the GEOS‐Chem CTM and use this new framework to simulate O 3 fluxes over three north temperate forests. We compare results with in situ measurements from four field studies and with standalone, observationally constrained MLC‐CHEM runs to test current knowledge of O 3 deposition and its drivers. We show that GEOS‐Chem overpredicts observed O 3 fluxes across all four studies by up to 2×, whereas the resolved‐canopy models capture observed diel profiles of O 3 deposition and in‐canopy concentrations to within 10%. Relative humidity and solar irradiance are strong O 3 flux drivers over these forests, and uncertainties in those fields provide the largest remaining source of model deposition biases. Flux partitioning analysis shows that: (a) nonstomatal loss accounts for 60% of O 3 deposition on average; (b) in‐canopy chemistry makes only a small contribution to total O 3 fluxes; and (c) the CTM big‐leaf treatment overestimates O 3 ‐driven stomatal loss and plant phytotoxicity in these temperate forests by up to 7×. Results motivate the application of fully online vertically explicit canopy schemes in CTMs for improved O 3 predictions.

Vermeuel, Michael P. [Department of Soil, Water, a↗
DOE OSTI2021

Which Combinations of Environmental Conditions and Microphysical Parameter Values Produce a Given Orographic Precipitation Distribution?

This study applies an idealized modeling framework, alongside a Bayesian Markov chain Monte Carlo (MCMC) algorithm, to explore which combinations of upstream environmental conditions and cloud microphysical parameter values can produce a particular precipitation distribution over an idealized two-dimensional, bell-shaped mountain. Simulations focus on orographic precipitation produced when an atmospheric river interacts with topography. MCMC-based analysis reveals that different combinations of parameter values produce a similar precipitation distribution, with the most influential parameters being relative humidity (RH), horizontal wind speed (U), surface potential temperature (θ sfc ), and the snow fall speed coefficient (A s ). RH, U, and A s exhibit interdependence: changes in one or more of these factors can be mitigated by compensating changes in the other(s) to produce similar orographic precipitation rates. The results also indicate that the parameter sensitivities and relationships can vary for spatial subregions and given different environmental conditions. In particular, high θ sfc values are more likely to produce the target precipitation rate and spatial distribution, and thus the ensemble of simulations shows a preference for liquid precipitation at the surface. The results presented here highlight the complexity of orographic precipitation controls, and have implications for flood and water management, observational efforts, and climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Distinctive Pattern of Global Warming in Ocean Heat Content

Abstract Huge heat anomalies in the atmosphere and ocean in recent years are not yet explained. Strong characteristic patterns in temperatures for upper layers of the ocean occurred from 2000 to 2023 in the presence of global warming from increasing atmospheric greenhouse gases. Here, we show that the deep tropics are warming, although sharply modulated by El Niño–Southern Oscillation events, with strong heating in the extratropics near 40°N and 40°–45°S but little heating near 20°N and 25°–30°S. The heating is most clearly manifested in zonal-mean ocean heat content and is evident in sea surface temperatures. The strongest heating is in the Southern Hemisphere, where aerosol effects are small. Estimates are made of the contributions to heating of top-of-atmosphere (TOA) radiation, atmospheric energy transports, surface fluxes of energy, and redistribution of energy by surface winds and ocean currents. The patterns of change are not directly related to TOA radiation but are evident in net surface energy fluxes and inferred ocean heat transports, underscoring their coupled origin. Changes in the atmospheric circulation through a poleward shift in ocean jet streams and storm tracks are reflected in surface wind-driven ocean Ekman transports. As well as human-induced climate change, internal natural variability is likely in play. Hence, the atmosphere and ocean currents are systematically redistributing heat from global warming, profoundly affecting local climates. Significance Statement As the climate changes, it has been difficult to discern meaningful patterns. Distinctive patterns of change have occurred in the ocean when examined as zonal averages around latitude bands. Most excess heat from global warming resides in the ocean and, since 2005, has become focused into bands near 40°N and 40°S, with little net warming in the subtropics. The strongest warming is in the Southern Hemisphere, although sea surface temperatures have increased more in the Northern Hemisphere. Changes in the atmospheric circulation through a poleward shift in the jet stream and storm tracks are primarily responsible along with corresponding changes in ocean currents. These changes are linked through surface exchanges of energy via heat, moisture, and wind stress.

Trenberth, Kevin E. [National Center for Atmospher↗
DOE OSTI2025

Amplified Mesoscale and Submesoscale Variability and Increased Concentration of Precipitation under Global Warming over Western North America

Abstract Cold-season precipitation statistics in simulations from the storm-resolving WRF Model at 6-km and 1-h resolution over western North America are analyzed. Pseudo–global warming future simulations for the 2041–80 period, constrained by GCMs under the RCP8.5 scenario, are compared to the 1981–2020 historical simulation. The analysis focuses on the dynamical properties of precipitation time series at subdaily scales and on the morphology of storms. The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through nonparametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal and spatial Fourier power spectra of precipitation time series and precipitation fields are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns. The results show statistically significant increases in the mean wet-hour precipitation intensity and in the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity. The statistics of change in the frequency of wet hours are more contrasted across the simulation domain. The changes are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more with finer spatial and temporal scales and the HPW and HPP decreasing. These projected changes are expected to have consequences, not only in terms of hydrologic impacts but also in terms of the predictability of precipitation patterns. Significance Statement The precipitation characteristics of winter storms over the western United States and southwestern Canada are analyzed in future climate simulations for the 2041–80 period. As compared to present-day climate, the most intense parts of the storms are projected to produce a higher rainfall volume, with increased concentration over smaller areas and shorter time intervals. The propensity of rainfall intensity to vary rapidly over time will be enhanced in the future according to the simulations. These model predictions imply an increased risk of rapid flooding in small basins. They also suggest that predicting several hours ahead the time and location at which a storm will produce maximum rainfall may become more challenging in the future.

Climate change↗