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At least 55 records · Page 3

Multi-decade high-resolution regional hindcasts for wave energy resource characterization in U.S. coastal waters

Long-term, high-resolution, regional wave hindcast datasets were generated using unstructured-grid Simulating WAves Nearshore (SWAN) models for the U.S. coastal waters to support nearshore wave energy development in the U.S. including those bordering U.S. territorial islands. The model domains resolved the entire U.S. exclusive economic zones, with a spatial resolution of approximately 200 m nearshore. The regional SWAN models were driven by the global WAVEWATCH III® model outputs and run for a 42-year period from 1979 to 2020. Extensive model validations were performed using buoy observations and altimeter data. Regional resource characterization was performed based on hindcast data points at 2 km from shore and along the 100 m isobath. Aggregations of wave resource parameters were produced, and spatial and seasonal variations were analyzed for all the regions. Wave resource metrics recommended by international standards, including a 3-hour time series of six resource parameters, hourly frequency- and directionally resolved wave spectra at selected “virtual buoy” locations, and average-annual values of omni-directional wave power, significant wave height, and energy period are publicly disseminated through an Amazon Web Service and a Marine Energy Atlas web application tool to facilitate wave energy research and a wide range of coastal ocean applications.

16 TIDAL AND WAVE POWER↗

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. In this work we used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH 4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH 4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH 4 emissions.

59 BASIC BIOLOGICAL SCIENCES↗

Vertical profiles of trace gas and aerosol properties over the eastern North Atlantic: variations with season and synoptic condition

Abstract. Because of their extensive coverage, marine low clouds greatly impact the global climate. Presently, the response of marine low clouds to the changes in atmospheric aerosols remains a major source of uncertainty in climate simulations. One key contribution to this large uncertainty derives from the poor understanding of the properties and processes of marine aerosols under natural conditions and the perturbation by anthropogenic emissions. The eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer (MBL) clouds, where cloud albedo and precipitation are highly susceptible to perturbations in aerosol properties. Here we examine the key processes that drive the cloud condensation nuclei (CCN) population in the MBL using comprehensive characterizations of aerosol and trace gas vertical profiles during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. During ACE-ENA, a total of 39 research flights were conducted in the Azores: 20 during summer 2017 and 19 during winter 2018. During summer, long-range-transported aerosol layers were periodically observed in the lower free troposphere (FT), leading to elevated FT CCN concentrations (NCCN). Both biomass burning and pollution from North America contribute to submicron aerosol mass in these layers, with pollution likely the dominant contributor. In contrast, long-range transported continental emissions have a much weaker influence on the aerosol properties in the ENA during the winter season. While the entrainment of FT air is a major source of particle number in the MBL for both seasons, on average it does not serve as a direct source of CCN in the MBL because the average FT NCCN is the same or even lower than that in the MBL. The particle number flux due to FT entrainment is dominated by pre-CCN (particles that are too small to form cloud droplets under typical conditions, i.e., particles with sizes below the Hoppel minimum) due to the elevated Npre-CCN in the lower FT. Once these pre-CCN are entrained into the MBL, they can grow and reach CCN size range through condensational growth, representing an indirect and major source of MBL CCN in the ENA. The impact of synoptic conditions on the aerosol properties is examined. Under pre-front and post-front conditions, shallow convective activity often leads to a deep and decoupled boundary layer. Coalescence scavenging and evaporation of drizzle below clouds lead to reduced NCCN and larger accumulation-mode particle sizes in the upper cloud-containing decoupled layer, indicating that surface measurements overestimate the NCCN relevant to the formation of MBL clouds under decoupled conditions.

54 ENVIRONMENTAL SCIENCES↗

Incorporating Diurnal and Meter-Scale Variations of Ambient CO 2 Concentrations in Development of Direct Air Capture Technologies

To be implemented on climate-relevant scales, direct air capture of CO 2 (DAC) will require large capital-intensive facilities and careful attention to cost minimization. In making decisions among potential sites for DAC facilities, all of the factors that will impact process cost and efficiency should be considered. In this paper we focus on a factor that has previously received little attention in the DAC community, namely variations in atmospheric conditions on hourly time scales and length scales of meters. We present data curated from extensive previous studies of biosphere-atmosphere fluxes with observations of CO 2 concentration, temperature, and relative humidity (RH) with hourly resolution from many sites in North America. These include locations where typical diurnal variations in CO 2 concentration during summer months exceeds 150 ppm. These variations are larger than the seasonal variations that exist between averaged CO 2 concentrations in winter and summer, and they are highly correlated with diurnal variations in temperature and RH. Diurnal variations are dependent on the height above ground at which CO 2 concentrations are measured, with smaller variations existing at heights of 10 m or more than at ground level. We illustrate the potential implications of these short-term variations for the operation and optimization of a DAC process with process-level calculations for a specific adsorption-based process using amine-rich adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Influence of Temperature Inversion on the Vertical Distribution of Aerosols

Temperature inversion plays an important role in the accumulation and diffusion of aerosols. In this study, the relationship between temperature inversion and the vertical distribution of aerosols is investigated based on Raman lidar observations taken from January 2010 to September 2015 at the Atmospheric Radiation Measurement site in the Southern Great Plains, USA. First, the diurnal and seasonal variations of the surface-based inversion (SBI) and elevated temperature inversion (EI) are investigated. The results indicate that the occurrence frequency of SBI and EI have different seasonal trends. SBI has the highest frequency in summer, while EI has the highest frequency in winter. The diurnal variation of SBI is obvious, with a higher frequency in nighttime and a lower frequency in daytime. The inversion intensity (ΔT) and inversion depth (ΔZ) of SBI and EI have consistent diurnal and seasonal trends. The effects of SBI and EI on the vertical distribution of aerosols are then analyzed. The mean aerosol optical depth (AOD) below the SBI height shows a clear seasonal variation, which is consistent with the seasonal trends of ΔT and ΔZ. This phenomenon also occurs on the AOD below EI top height. The sensitivity analysis shows that the mean AOD below SBI height or EI top height increases with an increase of the ΔT and ΔZ of SBI (EI). It indicates that ΔT and ΔZ are the key factors affecting the vertical distribution of aerosols. In addition, the variation of AOD below and above EI top height is opposite to that of AOD below and above EI bottom height under different ΔT and ΔZ conditions. The correlation coefficients between ΔT (ΔZ) of EI with AOD in EI were 0.62 (0.65). These results indicate that the space between EI bottom height and EI top height can store aerosols. The larger the ΔZ of EI, the more aerosols are stored. These findings contribute to our understanding of the effect of temperature inversion on the vertical distribution of aerosols.

54 ENVIRONMENTAL SCIENCES↗

Carbon content of soil fractions varies with season, rainfall, and soil fertility across a lowland tropical moist forest gradient

Tropical forests contain some of the largest soil carbon (C) stocks on Earth, making them broadly relevant to terrestrial-climate feedbacks, yet our understanding of how their soil organic C (SOC) fractions vary over space and time is limited. We studied effects of season, fertility, and mean annual precipitation (MAP) on the C contents of soil fractions across 14 lowland forests in Panama. We measured free-debris, occluded-debris, and mineral-associated SOC fractions, as well as soluble C associated with each fraction. We hypothesized that mineral-associated SOC would be greatest in infertile, strongly weathered soils with large reactive mineral contents. We also hypothesized that the debris SOC fractions would accumulate during the dry season, reflecting seasonal increases in litterfall. To address this, we compared soil fractions in wet and dry seasons from fertile and infertile soils across a range of 1809 – 2864 mm MAP. The C content (mg C / g soil) of all soil fractions varied with fertility and MAP: specifically, free-debris SOC was greatest in wet, high-fertility soils, and occluded-debris SOC was greater in high-fertility than low-fertility soils. The mineral-associated SOC fraction, which contained the majority of bulk soil C, showed increasing C content with greater MAP in infertile sites, presumably driving similar spatial patterns in the bulk soil. Only the free-debris SOC fraction showed strong seasonal variation, increasing in mass during the dry season. Nitrogen behaved similarly to C. In summary, soil C contents increased with MAP in infertile sites but not fertile sites, driven by the mineral-associated SOC fraction. The dry season had greater free-debris SOC, but this seasonal trend was not apparent in bulk soil C, likely because of the small size of the free-debris SOC fraction. Furthermore, changes in the quantity and seasonality of precipitation, which are projected for tropical forests, might shift spatial and temporal patterns of soil C storage, which would in turn influence forest-climate feedbacks for this C-rich biome.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements

Abstract. Cloud droplet number concentration (Nd) is crucial for understanding aerosol–cloud interactions (ACI) and associated radiative effects. We present evaluations of four ground-based Nd retrievals based on comprehensive datasets from the Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The Nd retrieval methods use ARM ENA observatory ground-based remote sensing observations from a micropulse lidar, Raman lidar, cloud radar, and the ARM NDROP (Droplet Number Concentration) value-added product (VAP), all of which also retrieve cloud effective radius (re). The retrievals are compared against aircraft measurements from the fast cloud droplet probe (FCDP) and the cloud and aerosol spectrometer (CAS) obtained from low-level marine boundary layer clouds on 12 flight days during summer and winter seasons. Additionally, the in situ measurements are used to validate the assumptions and characterizations used in the retrieval algorithms. Statistical comparisons of the probability distribution function (PDF) of the Nd and cloud re retrievals with aircraft measurements demonstrate that these retrievals align well with in situ measurements for overcast clouds, but they may substantially differ for broken clouds or clouds with low liquid water path (LWP). The retrievals are applied to 4 years of ground-based remote sensing measurements of overcast marine boundary layer clouds at the ARM ENA observatory to find that Nd (re) values exhibit seasonal variations, with higher (lower) values during the summer season and lower (higher) values during the winter season. The ensemble of various retrievals using different measurements and retrieval algorithms such as those in this paper can help to quantify Nd retrieval uncertainties and identify reliable Nd retrieval scenarios. Of the retrieval methods, we recommend using the micropulse lidar-based method. This method has good agreement with in situ measurements, less sensitivity to issues arising from precipitation and low cloud LWP and/or optical depth, and broad applicability by functioning for both daytime and nighttime conditions.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of Four Ground-based Retrievals of Cloud Droplet Number Concentration in Marine Stratocumulus with Aircraft In Situ Measurements

Cloud droplet number concentration (N d ) is crucial for understanding aerosol-cloud interactions (ACI) and associated radiative effects. We present evaluations of four ground-based N d retrievals based on comprehensive datasets from the Atmospheric Radiation Measurements (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The N d retrieval methods use ARM ENA observatory ground-based remote sensing observations from a Micropulse lidar, Raman lidar, cloud radar, and the ARM NDROP Value-added Product (VAP), all of which also retrieve cloud effective radius (r e ). The retrievals are compared against aircraft measurements from the Fast-Cloud Droplet Probe (FCDP) and the Cloud and Aerosol Spectrometer (CAS) obtained from low-level marine boundary layer clouds on 12 flight days during summer and winter seasons. Additionally, the in situ measurements are used to validate the assumptions and characterizations used in the retrieval algorithms. Statistical comparisons of the probability distribution function (PDF) of the N d and cloud r e retrievals with aircraft measurements demonstrate that these retrievals align well with in situ measurements for overcast clouds, but they may substantially differ for broken clouds or clouds with low liquid water path (LWP). The retrievals are applied to four years of ground-based remote sensing measurements of overcast marine boundary layer clouds at the ARM ENA observatory to find that N d (r e ) values exhibit seasonal variations, with higher (lower) values during the summer season and lower (higher) values during the winter season. The ensemble of various retrievals using different measurements and retrieval algorithms such as those in this paper can help to quantify N d retrieval uncertainties and identify reliable N d retrieval scenarios. Of the retrieval methods, we recommend using the using the Micropulse lidar-based method given its good agreement with in situ measurements, it has less sensitivity to issues arising from precipitation and low cloud LWP/optical depth, and it has broad applicability by functioning for both day and nighttime conditions.

54 ENVIRONMENTAL SCIENCES↗

Seasonal non-structural carbohydrate dynamics differ between twig bark and xylem tissues

Despite extensive research non-structural carbohydrate (NSC), the distribution of total NSC (TNC) and its primary components (sugar and starch) to the bark and xylem of twigs remains poorly understood. We determined seasonal NSC dynamics in twig bark and xylem in seven temperate tree species exhibiting different xylem anatomies and leaf habits. Seasonal trends in sugar were similar across species with concentrations peaking at least 15 days earlier in the spring for xylem than bark. Furthermore, evergreens exhibited maximum bark starch concentrations in early spring, followed by declines throughout the growing season, whereas deciduous species exhibited early spring declines in bark starch, followed by late growing season increases. Evergreens exhibited limited seasonal variation in xylem starch concentrations, whereas deciduous species exhibited variation in xylem starch concentrations that was similar to variation in bark starch. With a few exceptions, concentrations and seasonal amplitudes for sugar, starch, and TNC were generally higher in bark than xylem. Sugar concentrations were generally higher than starch, especially in the bark, which resulted in variability of TNC concentrations in bark or xylem. NSC concentrations varied significantly between xylem and the entire twig when bark was not explicitly considered. Averaged across species, sugar, starch, and TNC content in bark accounted for 66%, 54%, and 61% of total twig content, respectively, even though bark only accounted for 53% of the total twig mass. We recommend quantifying bark sugar and starch separately from xylem when determining twig NSC concentration and content.

59 BASIC BIOLOGICAL SCIENCES↗

Seasonal Cost-Benefit Analysis of Automated Distribution Feeder Upgrades with Advanced Mitigation Technologies

The increasing deployment of distributed solar photovoltaics (DPV) to meet clean energy goals can trigger adverse grid operation issues, such as voltage excursions and the violation of thermal loading constraints of the power delivery elements (e.g., lines and transformers) on the evolving electricity infrastructure. Such integration issues would require distribution upgrades with associated costs to mitigate them and to maintain reliable and resilient grid operating conditions. Traditional distribution network upgrade approaches use a specific single snapshot analysis that is overly conservative. This study considers a multi-time point analysis to capture both moderate (probable bounds) and extreme grid operating conditions using time points such as minimum load with minimum photovoltaics (PV), maximum load with maximum PV, maximum load with minimum PV, and minimum load with maximum PV. Further, this study investigates seasonal variation impacts and associated distribution upgrade costs for a spring season case (March, representing a low load and high PV scenario) and a summer case (July, representing a high load and high PV scenario). Such seasonal analysis will allow system operators to characterize upgrade requirements and associated costs across various periods. Because the spatial distribution of DPV can impact upgrade and associated costs, this study investigates three common DPV deployment scenarios - randomly deployed, close to the substation, and far from the substation - at different penetration levels. Apart from spatial distribution impacts, this project evaluates the techno-economic impacts of the nodal photovoltaic penetration factor (NPPF) for generating the various DPV deployment scenarios at increasing penetration levels. This project investigates the impact of varying nodal PV-to-load ratios using conservative and extreme NPPF values of 3 and 10, respectively. This study investigates the deployment of traditional infrastructure upgrade strategies, such as installing new voltage regulating equipment, transformers and lines replacements, and the activation of advanced inverter functionality (e.g., autonomous volt/VAR) in expanding PV hosting capacity. Existing DPV systems are assumed to operate with the legacy unity power factor, and we considered the possibility of retrofitting such systems with the activation of volt/VAR control as integration standards and regulations continue to evolve to allow such functions. The cost-benefit analysis metrics used in study include distribution upgrade costs, average cost per watt of the upgrade cost, average marginal cost per watt of the upgrade cost, and power losses.

14 SOLAR ENERGY↗

Bull Trout and Westslope Cutthroat Trout movement in a dam tailrace

Populations of Bull Trout Salvelinus confluentus and Westslope Cutthroat Trout Oncorhynchus clarkii lewisi in the Pend Oreille Basin have declined, partly due to fragmentation caused by hydropower dams. This study aimed to analyze the movements and behavior of these species downstream of Albeni Falls Dam over two years to inform fishway design. Radiotracking investigations were conducted to monitor 10 adult Bull Trout and 17 adult Westslope Cutthroat Trout from September 2008 to July 2010. Macro and micro detection zones were delineated to study fine- and large-scale movements in the tailrace. Macro zones included the spillway and powerhouse tailrace areas. Micro zones were nested within macro zones to identify regions close to the dam where fishway structures could be built. Both Bull Trout and Westslope Cutthroat Trout exhibited high mobility in the dam tailrace, transitioning between macro detection zones. Seasonal variations influenced their distribution patterns. During the spring freshet migration season, both species were primarily detected at the left powerhouse micro zone. In sedentary periods (fall/winter and summer), fish actively swam throughout the tailrace, displaying search behavior. These behavior observations suggest that potential fishway entrances located near dam concrete would be effective: the area near the left powerhouse was identified as the optimal construction location. This study highlights the feasibility of designing fish passage structures to mitigate population fragmentation and support species recovery.

13 HYDRO ENERGY↗

Climatology of Linear Mesoscale Convective System Morphology in the United States based on Random Forests Method

This study uses machine learning methods, specifically the random forest (RF), on a radar-based mesoscale convective system (MCS) tracking dataset to classify the five types of linear MCS morphology in the contiguous United States during the period 2004-2016. The algorithm is trained using radar- and satellite-derived spatial and morphological parameters, and reanalysis environmental information from 5-26yr manually identified nonlinear and five linear MCS modes. The algorithm is then used to automate the classification of linear MCSs over 8 years with high accuracy, providing a systematic, long-term climatology of linear MCSs. Results reveal that nearly 40% of MCSs are classified as linear MCSs, in which half of the linear events belong to the type of system having a leading convective line. The occurrence of linear MCSs shows large annual and seasonal variations. On average, 113 linear MCSs occur annually during the warm season (through March to October), with most of these events clustered from May through August in the central eastern Great Plains. MCS characteristics, including duration, propagation speed, orientation, and system cloud size, have large variability among the different linear modes. The systems having a trailing convective line and the systems having a back-building area of convection typically move more slowly and have higher precipitation rate, and thus have higher potential in producing extreme rainfall and flash flooding. Analysis of the environmental conditions associated with linear MCSs show that the storm-relative flow is of most importance in determining the organization mode of linear MCSs.

Cui, Wenjun↗

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗

Global Simulations of Phase State and Equilibration Time Scales of Secondary Organic Aerosols with GEOS-Chem

The phase state of secondary organic aerosols (SOA) can range from liquid through amorphous semisolid to glassy solid, which is important to consider as it influences various multiphase processes including SOA formation and partitioning, multiphase chemistry, and cloud activation. In this study, we simulate the glass transition temperature and viscosity of SOA over the globe using the global chemical transport model, GEOS-Chem. The simulated spatial distributions show that SOA at the surface exist as liquid over equatorial regions and oceans, semisolid in the midlatitude continental regions, and glassy solid over lands with low relative humidity. The predicted SOA viscosities are mostly consistent with the available measurements. In the free troposphere, SOA particles are mostly predicted to be semisolid at 850 hPa and glassy solid at 500 hPa, except over tropical regions including Amazonia, where SOA are predicted to be low viscous. Phase state also exhibits seasonal variation with a higher frequency of semisolid and solid particles in winter compared to warmer seasons. We calculate equilibration time scales of SOA partitioning (τ eq ) and effective mass accommodation coefficient (α eff ), indicating that τ eq is shorter than the chemical time step of GEOS-Chem of 20 min and αeff is close to unity for most locations at the surface level, supporting the application of equilibrium SOA partitioning. However, τ eq is prolonged and α eff is lowered over drylands and most regions in the upper troposphere, suggesting that kinetically limited growth would need to be considered for these regions in future large-scale model studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cloud and Precipitation Experiment at Kennaook (Cape-K) Science Plan

The Cloud and Precipitation Experiment at Kennaook (CAPE-K) will augment ongoing measurements at the Kennaook/Cape Grim Baseline Air Pollution Station (KCG) with components of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s second Mobile Facility (AMF2) in a deployment that is scheduled to extend from April 2024 through September 2025. Located at Kennaook/Cape Grim on the northwestern tip of Tasmania (40.68° S, 144.69° E), KCG has produced the longest and most consequential record of Southern Hemisphere aerosol and gas-phase chemistry; however, extensive cloud and precipitation measurements have not been collected at this site. CAPE-K is motivated by the fact that model uncertainty in the surface radiation budget due to clouds and precipitation remain significant in this region, where strong latitudinal gradients in cloud feedbacks are found and there are strong and well-documented seasonal variations in marine aerosol properties. Satellite data suggest that cloud properties co-vary with the seasonal cycle in aerosol in the Southern Ocean (SO), yet detailed vertically resolved measurements of cloud and precipitation in the marine boundary layer are sparse. CAPE-K will provide the first such seasonal cycle of measurements in this important latitude band. CAPE-K will provide detailed cloud and precipitation observations over two winter seasons and align with complementary high-value-add activities planned by Australian colleagues, including a voyage of the Research Vessel Investigator (RVI) in May 2025 that will conduct measurements just offshore of KCG.

54 ENVIRONMENTAL SCIENCES↗

Paleo-Megadroughts and Abrupt Climate Changes in the Speleothem Records. Final report

This project is motivated by the speleothem isotope records in Asia, which show regional responses in the hydrologic cycle to different climate forcings. Speleothem isotopic records are typically interpreted in terms of local precipitation variations or monsoon intensity. Our study demonstrates that non-local processes also play an important role. We started this project to understand the regional difference in speleothem isotopic composition between the Last Glacial Maximum (LGM) and the present-day. The record in Southwest China showed greater depletion during the LGM compared to those in East China. Our modeling and analysis showed that speleothems record, in addition, large scale changes in atmospheric circulation and moisture transport and their subsequent impact on precipitation. We developed an algorithm to partition total precipitation according to their formation dynamics, namely into frontal and non-frontal precipitation, and showed that the two have different trends and hence different causal mechanism. We then focused our subsequent attention on circulation impacts on precipitation changes. We applied a machine learning algorithm to detect rainbands in the ERA-Interim reanalysis product, and showed that the seasonal migrations of the rainbands are tied to the seasonal migrations of the jet stream, in particular the northerlies of the jet meanders. These northerlies, in turn, are partly topographic Rossby waves excited as the upstream westerlies impinge on the Tibetan Plateau. The seasonal variations of these upstream westerlies thus contribute to the seasonal movements of the rainbands and regional precipitation changes. Our analysis of the modern precipitation isotope record further confirms the importance of jet stream changes in the isotopic variations and shows that isotope-enriched years have reduced summer seasonality, with less pronounced northward migration of the jet.

54 ENVIRONMENTAL SCIENCES↗

A derecho climatology (2004–2021) in the United States based on machine learning identification of bow echoes

Due to their persistent widespread severe winds, derechos pose significant threats to human safety and property, with impacts comparable to many tornadoes and hurricanes. Yet, automated detection of derechos remains challenging due to the absence of spatiotemporally continuous observations and the complex criteria employed to define the phenomenon. This study presents an objective derecho detection approach capable of automatically identifying derechos through both observations and model results. The approach is grounded in a physically based definition of derechos and integrates three algorithms: (1) the Python Flexible Object Tracker (PyFLEXTRKR) algorithm to track mesoscale convective systems (MCSs), (2) a semantic segmentation convolutional neural network to identify bow echoes, and (3) a comprehensive classification algorithm to detect derechos within MCS life cycles and distinguish derecho-producing from non-derecho-producing MCSs. Using this approach, we developed a novel high-resolution (4 km and hourly) observational dataset of derechos and accompanying derecho-producing MCSs over the United States east of the Rocky Mountains from 2004 to 2021. The dataset consists of two subsets based on different gust speed data sources and is analyzed to document the climatology of derechos in the United States. On average, 12–15 derechos are identified per year, aligning with previous estimations (∼6–21 events annually). The spatial distribution and seasonal variation patterns are consistent with prior studies, showing peak occurrences in the Great Plains and the Midwest during the warm season. Additionally, during the study period, derechos account for approximately 3.1 % of measured damaging gusts (≥25.93 m s−1) over the eastern United States. The dataset is publicly available at https://doi.org/10.5281/zenodo.14835362 (Li et al., 2025).

54 ENVIRONMENTAL SCIENCES↗

A correlation between seasonally changing photoperiod, whole body lipid, and condition factor in juvenile spring Chinook salmon (Oncorhynchus tshawytscha)

The regulation of lipid stores is a central process for the physiology and ecology of fishes. Seasonal variation in lipid stores has been directly linked to survival of fishes across periods of food deprivation. We assessed whether a seasonally changing photoperiod was correlated to seasonal changes in energetic status to help better understand these important processes. Groups of first feeding Chinook salmon fry were introduced to a seasonal photoperiod cycle, but the point of entrance into the seasonal cycle varied from near the winter solstice (December), to either side of the spring equinox (February & May). Temperature and feeding rate were similar for all treatments. Subsequently, condition factor and whole body lipid content were assessed through a seasonal progression. Throughout most of the experiment, length and weight did not differ between the different photoperiod treatments, however whole body lipid and Fulton’s condition factor did. Furthermore, changes in both whole body lipid and Fulton’s condition factor in all treatment groups followed a similar seasonal pattern that was inversely related to day length (highest K and lipid levels found during days with the least light). These results suggest that regardless of age or size, there is a correlation between seasonal changes in photoperiod and changes in body composition in juvenile Chinook salmonids.

Spangenberg, Dina K. (ORCID:000000018861395X)↗