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At least 253 records · Page 14

Middle to Late Holocene Sea Surface Temperature and Productivity Changes in the Northeast Pacific

Variations of the sea surface temperature (SST) and primary productivity in the northeast Pacific have far‐reaching implications. In addition to influencing the regional and global temperature and hydroclimate, these conditions also control marine ecosystems and their services, which subsequently impact regional economies. Yet, our understanding of the variability and controls of northeast Pacific SST and productivity on timescales exceeding observational records remains limited. Here, we use marine sediment records from seven locations, spanning 25.2°N–59.6°N, in the northeast Pacific to characterize the millennial‐scale variability of SST and productivity from 9,000 to 1,000 years BP. We explore the dynamics of their spatiotemporal evolution and compare these data with transient climate model outputs to identify potential drivers. Through a heat budget analysis and optimal fingerprinting analysis, we characterize the spatial pattern of forcings. We find that SST varied spatially in the northeast Pacific, with higher latitudes exhibiting greater magnitude changes than lower latitudes, which differs from previous work suggesting regional synchronicity and coherence during the Holocene. Our analysis did not find evidence for coherent variability of primary producer community nor carbon export, highlighting the difficulty of identifying the complex interactions between environmental conditions, producers, and carbon export. Model‐proxy disagreement demonstrates the need for higher resolution model frameworks, but shows nonetheless that observed variability in the proxy records can be explained by a combination of greenhouse gas and orbital forcing. Here we suggest that the complex SST variations and marine ecosystem responses to forced changes are important factors that can drive disagreements in model projections.

54 ENVIRONMENTAL SCIENCES↗

Compounding effects of climate change and WUI expansion quadruple the likelihood of extreme-impact wildfires in California

Previous research has examined individual factors contributing to wildfire risk, but the compounding effects of these factors remain underexplored. Here, we introduce the “Integrated Human-centric Wildfire Risk Index (IHWRI)” to quantify the compounding effects of fire-weather intensification and anthropogenic factors—including ignitions and human settlement into wildland—on wildfire risk. While climatic trends increased the frequency of high-risk fire-weather by 2.5-fold, the combination of this trend with wildland-urban interface expansion led to a 4.1-fold increase in the frequency of conditions conducive to extreme-impact wildfires from 1990 to 2022 across California. More than three-quarters of extreme-impact wildfires—defined as the top 20 largest, most destructive, or deadliest events on record—originated within 1 km from the wildland-urban interface. The deadliest and most destructive wildfires—90% of which were human-caused—primarily occurred in the fall, while the largest wildfires—56% of which were human-caused—mostly took place in the summer. By integrating human activity and climate change impacts, we provide a holistic understanding of human-centric wildfire risk, crucial for policy development.

54 ENVIRONMENTAL SCIENCES↗

The Historical Development of Large‐Scale Paleoclimate Field Reconstructions Over the Common Era

Abstract Climate field reconstructions (CFRs) combine modern observational data with paleoclimatic proxies to estimate climate variables over spatiotemporal grids during time periods when widespread observations of climatic conditions do not exist. The Common Era (CE) has been a period over which many seasonally‐ and annually‐resolved CFRs have been produced on regional to global scales. CFRs over the CE were first produced in the 1970s using dendroclimatic records and linear regression‐based approaches. Since that time, many new CFRs have been produced using a wide range of proxy data sets and reconstruction techniques. We assess the early history of research on CFRs for the CE, which provides context for our review of advances in CFR research over the last two decades. We review efforts to derive gridded hydroclimatic CFRs over continental regions using networks of tree‐ring proxies. We subsequently explore work to produce hemispheric‐ and global‐scale CFRs of surface temperature using multi‐proxy data sets, before specifically reviewing recently‐developed data assimilation techniques and how they have been used to produce simultaneous reconstructions of multiple climatic fields globally. We then review efforts to develop standardized and digitized databases of proxy networks for use in CFR research, before concluding with some thoughts on important next steps for CFR development.

Smerdon, Jason E.↗

Storylines for unprecedented heatwaves based on ensemble boosting

Recent temperature extremes have shattered previously observed records, reaching intensities that were inconceivable before the events. Could the possibility of an event with such unprecedented intensity as the 2021 Pacific Northwest heatwave have been foreseen, based on climate model information available before the event? Could the scientific community have quantified its potential intensity based on the current generation of climate models? Here, we demonstrate how an ensemble boosting approach can be used to generate physically plausible storylines of a heatwave hotter than observed in the Pacific Northwest. We also show that heatwaves of much greater intensities than ever observed are possible in other locations like the Greater Chicago and Paris regions. In order to establish confidence in storylines of ‘black swan’-type events, different lines of evidence need to be combined along with process understanding to make this information robust and actionable for stakeholders.

54 ENVIRONMENTAL SCIENCES↗

Commentary: Our “heatshed” moment is now

We are living through a “heatshed” moment, a critical turning point in which heat must be rapidly addressed to protect health and livelihoods worldwide. The year 2024 was the hottest on record since global records began in 1850, and the past 10 years were the hottest decade in recorded history. Although extreme heat is the top weather-related killer in the United States, affecting livelihoods and economies, cities and nations dedicate more attention and resources to other climate hazards, such as hurricanes, floods, droughts, and wildfires. In this commentary, we argue that heat resilience must be rapidly advanced through heat mitigation, heat management, and heat governance efforts to ensure thriving communities in the face of an overheating world.

Extreme heat↗

An Accurate and Automated Convective Vortex Detection Method for Long-Duration Infrasound Microbarometer Data

Heating of the surficial layer of the atmosphere often generates convective vortices, known as “dust devils” when they entrain visible debris. Convective vortices are common on both Earth and Mars, where they affect the climate via dust loading, contribute to wind erosion, impact the efficiency of photovoltaic systems, and potentially result in injury and property damage. However, long-duration terrestrial convective vortex activity records are rare. We have developed a high-precision and high-recall method to extract convective vortex signatures from infrasound microbarometer data streams. The techniques utilizes a wavelet-based detector to capture potential events and then a template matching system to extract the duration of the vortex. Since permanent and temporary infrasound sensors networks are present throughout the globe (many with open data), our method unlocks a vast new convective vortex dataset without requiring the deployment of specialized instrumentation.

54 ENVIRONMENTAL SCIENCES↗

Recent streamflow trends across permafrost basins of North America: Datasets

Climate change impacts, including changing temperatures, precipitation, and vegetation, are widely anticipated to cause major shifts to the permafrost with resulting impacts to hydro-ecosystems across the high latitudes of the globe. However, it is challenging to examine streamflow shifts in these regions owing to a paucity of data, discontinuity of records, and other issues related to data consistency and accuracy. We looked at recent changes in streamflow over 1976-2021 in watersheds affected by varying degrees of permafrost coverage to characterize trends and drivers for a range of watersheds across North America. Data sets are described in detail in the paper associated with this data set, Bennett et al. 2023, Front. Water - Water and Critical Zone, DOI: 10.3389/frwa.2023.1099660.These data contain CSV files of the streamflow, climate, and land surface characteristics for several sites located across the high latitude regions of North America. Both observed and reanalysis data products are provided. These files can be opened using Excel or a text editor, or they can be read, and analyzed in software tools such as Python or R. A brief description of the files is below, and more details can be found in the Methods section.rabpro_stats_north_select_74_55m.csv - This file describes the observed gages used in the analysis.GF31_23_metadat.csv - This file describes the 23 permafrost systems. Columns are as described in rabpro_stats_north_select_74_55m.csv above, with rabpro_id, the id used for the timeseries file mapping in GF31_23_time_series.csv.GF31_23_time_series.csv - This file contains the time series data for the stations described in GF31_23_metadat.csv.GF31_random_reaches_1583.csv - This file describes the 1583 randomly selected permafrost-dominant sites for machine learning analysis.era5_GF31_monthly_vars_random_reaches_1583.csv - This file contains the monthly ERA5 land data for the 1583 randomly selected permafrost-dominant sites.observed.zip: USGS and Hydat station data for the 74 gages analyzed in this study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1975-2022.streamflow_daily_GF31_infilled_1979_2022.csv - infilled daily streamflow data (infilled using GloFAS v 3.1) for 55 gages. Units are m3/sec. 1979-2022.glofas_23.zip - Glofas v3.1 file for the 23 permafrost-dominant gages in the study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1979-2021.glofas_1583.zip - Glofas v3.1 file for the 1583 randomly selected permafrost-dominant gages in the study. Monthly, seasonal, and annual streamflow observations for minimum streamflow, mean streamflow, and maximum streamflow. Units are m3/sec. 1979-2021.

54 ENVIRONMENTAL SCIENCES↗

Synergistic effects of climate warming and atmospheric nutrient deposition on the alpine lake ecosystem in the south-eastern Tibetan Plateau during the Anthropocene

Alpine lakes on the Tibetan Plateau are highly sensitive to global change and have been recognized as the sentinel of climate warming. However, anthropogenic impacts in populated area are migrating to these remote areas via transporting particulate nutrients by atmospheric deposition. Whether warming and nutrient deposition would impose additive or synergistic effects on the lake ecosystem remains largely unknown. Here, we present multi-proxy (sediment pigment and geochemistry) records during the past two centuries at the Cuoqia Lake in the southeast Tibetan Plateau. We found that the lake exhibited rapid ecological changes since 1980 AD characterized by an increase in primary productivity due to algal proliferation, with more rapid growth of green algae and diatoms. These findings are in concert with many other lakes (e.g., Moon Lake and Shade Co) in the same area, suggesting a consistent pattern of ecosystem evolution at the region scale. Statistical analyses suggested that nutrient deposition and climate warming were strongly associated with the variations in primary productivity and algae composition, exerting both individual and interactive effects. In addition, scenario analyses with a well-established process-based ecosystem model further revealed that the two factors not only individually, but also synergistically promoted the algal proliferation and community succession. Such synergy is evident in that the effect of lake warming would be more pronounced under higher nutrient deposition scenario, which is potentially due to higher temperature-driven mineralization in warmer conditions, and higher efficiency of nutrient utilization under enhanced light availability attributing to declining ice thickness and duration in cold seasons. Overall, our study proposes the existence and quantifies the synergistic impacts of climate warming and anthropogenic activities in driving the ecological changes in remote alpine lakes on the Tibetan Plateau. The lake ecological consequences driven by individual factor would be worsen by such synergy, so that we cannot predict the lake ecosystem trajectory in the future based on each factor separately, and more efforts than previously expected would be needed for the lake restoration and management.

Zhang, Can↗

New Particle Formation Event Dataset at the Southern Great Plains (SGP) Observatory from 2018 to 2023

This data set contains observations of new particle formation (NPF) events collected at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory from 2018 to 2023. Measurements include particle number size distributions, radiance measurements, and associated meteorological variables from onsite instrumentation relevant for identifying and characterizing NPF events. Events were identified using standardized criteria and documented to support investigations of aerosol nucleation, growth dynamics, and their interactions with local atmospheric conditions. The data set provides a multi-year record that enables evaluation of seasonal and interannual variability in NPF occurrence and intensity at a mid-continental site. These data are intended to support studies of aerosol-cloud-climate interactions and model evaluation within both ARM and the broader atmospheric science community. More information can be found within the README_NPF_SGP_2018_2023.docx file.

event↗

Tracking westerly wind directions over Europe since the middle Holocene

The variability of the northern westerlies has been considered as one of the key elements for modern and past climate evolution. Their multiscale behavior and underlying control mechanisms, however, are incompletely understood, owing to the complex dynamics of Atlantic sea-level pressures. Here, we present a multi-annually resolved record of the westerly drift over the past 6,500 years from northern Italy. In combination with more than 20 other westerly-sensitive records, our results depict the non-stationary westerly-affected regions over mainland Europe on multi-decadal to multi-centennial time scales, showing that the direction of the westerlies has changed with respect to the migrations of the North Atlantic centers of action since the middle Holocene. Our findings suggest the crucial role of the migrations of the North Atlantic dipole in modulating the westerly-affected domain over Europe, possibly modulated by Atlantic Ocean variability.

54 ENVIRONMENTAL SCIENCES↗

Alteration history of aluminum-rich rocks at Jezero crater, Mars

Aluminum-rich clay minerals are detected across the ancient surface of Mars and record intervals of intense alteration by liquid water. On Earth, these clay minerals can form from hydrothermal alteration or rainfall-driven chemical weathering over thousands to millions of years, but how they formed on Mars remains a mystery. The Perseverance rover discovered light-toned, cobble-sized, aluminum-rich (30-45 wt% Al 2 O 3 ) “float” rocks (rock fragments), with some exhibiting spectral signatures of kaolinite, an aluminum-rich clay mineral. These rocks now enable an investigation into the ancient kaolinite-bearing terrains of Mars. To interpret their formation, we use data from the SuperCam and Mastcam-Z instruments onboard the rover to compare the chemistry and reflectance spectra of the float rocks with deeply weathered paleosols and hydrothermal kaolin deposits from Earth’s geological record. Aluminum and titanium enrichments coupled with depletion of iron and magnesium are unlike hydrothermal deposits and instead comparable to bleached horizons of paleosols that formed under high rainfall during past greenhouse climates on Earth. These rocks therefore likely represent some of the wettest intervals of Mars’ history.

58 GEOSCIENCES↗

The Southern Annular Mode and Southern Ocean Surface Westerly Winds in E3SM

Climate variability and change in the Southern Hemisphere (SH) are influenced by the Southern Annular Mode (SAM) and are closely related to changes in the kinematic properties of the SH surface zonal winds. The SAM and SH surface zonal winds have strong effects on the atmospheric and oceanic circulation system. In this study we investigate the variability and trend in the SAM and position and strength of the surface zonal wind stress (TAUX), using two ensembles of simulations covering the historical record from the Energy Exascale Earth System Model (E3SM-HIST and Atmospheric Model Intercomparison Project) for 1979-2014. In addition, performance of two CO 2 forcing simulations from the E3SM (E3SM-1pctCO2 and 4xCO2) is assessed to examine the sensitivity of the variability and changes in the SAM and SH surface TAUX to climate forcing. In general, all E3SM simulations tend to capture the dominant feature of the SAM pattern reasonably well. The annual SAM index in the E3SM-HIST simulation shows a significant increasing trend. These features are similar to the trends in the strength (along with poleward shift in the position) of the annual surface TAUX. For the climatological surface TAUX position and strength, the two CO 2 forcing simulations show slightly poleward movement and stronger intensity, while the E3SM-HIST is equatorward and weaker than observations. In the relationship between the SAM and surface TAUX, we show that the SAM index exhibits a positive (negative) relationship with the strength (position) of the surface TAUX in the variability for all seasons and annual mean.

54 ENVIRONMENTAL SCIENCES↗

Precipitation in Northeast Mexico Primarily Controlled by the Relative Warming of Atlantic SSTs

Abstract Reconstructing hydroclimate over the Common Era is essential for understanding the dominant mechanisms of precipitation change and improving climate model projections, which currently suggest Northeast Mexico will become drier in the future. Tree‐ring reconstructions have suggested regional rainfall is primarily controlled by Pacific sea‐surface temperatures (SSTs). However, tree ring records tend to reflect winter‐spring rainfall, and thus may not accurately record total annual precipitation. Using the first multiproxy speleothem record spanning the last millennium, combined with results from an atmospheric general circulation model, we demonstrate mean annual rainfall in Northeast Mexico is highly sensitive to Atlantic SST variability. Our findings suggest future precipitation in Northeast Mexico is more dependent upon the warming of Tropical Atlantic SSTs relative to the Tropical Pacific.

Wright, Kevin T.↗

Observing, Measuring, and Assessing the Consequences of Snow Drought

Warmer and shorter winters from climate change will reduce snowpacks in most seasonally snow-covered regions of the world, with consequences for freshwater availability in spring and summer when people and ecosystems demand water most. Recent record-low snowpacks, such as those in the winters of 2013/14 and 2014/15 in the western United States, have led to a surge in research on “snow droughts,” which are pointed to as harbingers of global warming that pose significant societal hazards. Yet, despite the importance of understanding snow droughts to best prepare for their attendant impacts, the concept remains amorphous, with no agreed-upon definition of what they are, how best to measure them, and how such snow droughts connect to warm-season impacts. These knowledge gaps limit our understanding of the risks posed by snow droughts in the present and future, and thus our preparedness for their differential impacts on freshwater resources. To address these issues, we compile a hemispheric ensemble of in situ, satellite, and reanalysis snowpack datasets. We use this ensemble to evaluate the scientific challenges and uncertainties arising from differences in defining and measuring snow droughts, and to identify opportunities to leverage this information to better understand the significance of snow droughts. We show that a clearer quantification of what constitutes a snow drought, including its uncertainties, improves our ability to anticipate costly and disruptive warm-season droughts, which is vital for informing risk management and adaptation to changing snow regimes.

54 ENVIRONMENTAL SCIENCES↗

Hydrogen Generation and Industrial Heat Opportunities for Nuclear Plants in the Gulf Coast

The United States (U.S.) nuclear-generation fleet stands as a critical national strategic asset, playing a pivotal role in achieving climate goals. Operating on light-water reactor (LWR) technologies, this fleet provides the largest share of U.S. carbon-free electrical generation, ensuring 24/7 clean-energy stability. With a proven track record of reliability while operating at high-capacity factors, consistently above 90%, the existing nuclear fleet serves as a cornerstone for sustainable energy. The Department of Energy’s (DOE’s) Light Water Reactor Sustainability (LWRS), Flexible Plant Operations and Generation pathway addresses U.S. nuclear power plant (NPP) grid integration challenges in the face of evolving energy landscapes. Research at Idaho National Laboratory (INL) highlights the potential synergy between high-temperature steam-electrolysis (HTSE) technology and nuclear steam and electricity during periods of high renewable grid penetration. Large-scale nuclear-integrated hydrogen production through HTSE presents significant potential for decarbonizing such energy-intensive sectors as oil refining, petrochemicals, ammonia, and fertilizers. The strategic advantage lies in the nuclear sector’s capability to deliver clean electrical and/or steam output during periods of low demand. Nuclear-produced hydrogen—with its ability to provide high-purity clean H 2 well below the national standard of 1 kg of CO 2 per kg of H 2 —represents a breakthrough methodology. This emphasizes the crucial role NPPs can fill in addressing the increasing need for clean hydrogen, establishing them as essential contributors to decarbonization. This report specifically delves into hydrogen-generation opportunities from the U.S. Gulf Coast region. This study aims to assess NPP capabilities for hydrogen production and to identify practical nearby industrial and pipeline-operator off-takers for nuclear-integrated hydrogen production as well as to present some specific case-study analysis showing the conditions under which nuclear hydrogen production and sale can be profitable. Also considered in this report is preliminary analysis of nuclear-heat opportunities accessible near Waterford NPP via transportation of hypothetical steam pipelines and heat-exchange equipment.

08 HYDROGEN↗

Hot droughts in the Amazon provide a window to a future hypertropical climate

Tropical forests represent the warmest and wettest of Earth’s biomes, but with continued anthropogenic warming, they will be pushed to climate states with no current analogue. Droughts in the tropics are already becoming more intense as they occur at successively higher temperatures. Here, in this study, we synthesize multiple datasets to assess the effects of hot droughts on a central Amazon forest. First, a more than 30-year record of annually resolved forest demographic data from a selective logging experiment showed higher tree mortality during intense droughts, particularly among fast-growing pioneer species with low wood density. Second, analysis of ecophysiological field measurements from the 2015 and 2023 El Niño droughts identified a soil moisture threshold beyond which transpiration rates rapidly declined. As rainless days beyond this threshold continued, drought conditions intensified, increasing the potential for tree mortality from hydraulic failure and carbon starvation. Third, analyses from the Coupled Model Intercomparison Project Phase 6 demonstrated that under high-emission scenarios, a large area of tropical forest will shift to a hotter ‘hypertropical’ climate by 2100. Last, under a hypertropical climate, temperature and moisture conditions during typical dry season months will more frequently exceed identified drought mortality thresholds, elevating the risk of forest dieback. Present-day hot droughts are harbingers of this emerging climate, offering a window for studying tropical forests under expected extreme future conditions.

drought↗

Attribution of the role of climate change in the forest fires in Sweden 2018

In this study, we analyse the role of climate change in the forestfires that raged through large parts of Sweden in the summer of 2018 from ameteorological perspective. This is done by studying the Canadian FireWeather Index (FWI) based on sub-daily data, both in reanalysis data sets(ERA-Interim, ERA5, the Japanese 55 year Reanalysis, JRA-55, and Modern-Era Retrospective analysis for Research and Applications version 2, MERRA-2) and three large-ensemble climatemodels (EC-Earth, weather@home, W@H, and Community Earth System Model, CESM) simulations. The FWI, based on reanalysis, correlates well with the observed burnt area in summer (r=0.6 to 0.8). We find that the maximum FWI in July 2018 had return times of ~24 years (90 % CI, confidence interval, > 10 years) for southern and northern Sweden. Furthermore, we find a negative trend of the FWI for southern Sweden over the 1979 to 2017 time period in the reanalyses, yielding a non-significant reduced probability of such an event. However, the short observational record, large uncertainty between the reanalysis products and large natural variability of the FWI give a large confidence interval around this number that easily includes no change, so we cannot draw robust conclusions from reanalysis data. The three large-ensembles with climate models point to a roughly 1.1 (0.9 to 1.4) times increased probability (non-significant) for such events in the current climate relative to preindustrial climate. For a future climate (2 °C warming), we find a roughly 2 (1.5 to 3) times increased probability for such events relative to the preindustrial climate. The increased fire weather risk is mainly attributed to the increase intemperature. The other main factor, i.e. precipitation during summer months, isprojected to increase for northern Sweden and decrease for southern Sweden. We, however, do not find a clear change in prolonged dry periods in summer months that could explain the increased fire weather risk in the climate models. In summary, we find a (non-significant) reduced probability of such eventsbased on reanalyses, a small (non-significant) increased probability due to global warming up to now and a more robust (significant) increase in the risk for such events in the future based on the climate models.

54 ENVIRONMENTAL SCIENCES↗

In Situ Machine Learning for Intelligent Data Capture on Exascale Platforms. Final Report

In many dynamic systems, interesting events occur locally in time and space. Examples of such systems include ignition events in combustion simulations, material fractures in mechanics simulations, and extreme weather events in climate simulations. Due to memory constraints and data I/O costs, current simulation workflows save data at regularly spaced time-steps, at a fixed rate determined before the start of the simulation. Often this mode of operation results in missed events of interest, necessitating a simulation restart from before an event occurred with more frequent data saves. This data saving workflow is grossly inefficient and is already a bottleneck in the computing process. We propose to develop machine learning algorithms that can detect when interesting dynamical events are occurring, triggering data saves. These machine learning algorithms will perform in situ anomaly detection to flag regions with different dynamical properties than those previously recorded. The adaptive data saves would be local in time and space to match the event of interest, thereby enabling a much more efficient workflow that will reduce data I/O costs and data storage memory requirements. The algorithms will be tested on two applications: auto-ignition simulations and climate simulations. A critical component of this project will be developing machine learning algorithms that can be deployed efficiently in situ on HPC platforms with out-of-the-box functionality. The development of in situ machine learning methods to detect anomalous events would enable a more efficient and effective workflow, in which all the relevant data are saved in a single simulation run, without re-starts or scientist intervention.

42 ENGINEERING↗