The Atlantic Meridional Overturning Circulation (AMOC) impacts temperatures, ecosystems, and the carbon cycle. However, how AMOC affects the carbon cycle remains poorly understood, in part because the respective contributions of different physical and biological mechanisms that impact carbon storage in the ocean are not typically diagnosed in climate models. Here we explore modeled effects of an AMOC shutdown on Dissolved Inorganic Carbon (DIC) in the ocean by applying a new decomposition that explicitly calculates preformed and regenerated DIC components and separates physical and biological contributions. An extensive evaluation of the method in transient simulations finds that, in most cases, it is accurate and reliable, especially for basin-wide changes, whereas errors can be significant at global and local scales. In contrast, estimates of respired carbon based on Apparent Oxygen Utilization lead to large errors and are generally not reliable. In response to a shutdown of the AMOC, ocean carbon increases and then decreases, leading to opposite changes in atmospheric CO2. DIC changes are dominated by opposing changes in biological carbon storage. Whereas regenerated components increase in the Atlantic and dominate the initial increase in global ocean DIC, preformed components decrease in the other ocean basins and dominate the long-term DIC decrease. Biological disequilibrium is an important contribution to preformed carbon changes. Biological saturation carbon decreases in the Pacific, Indian, and Southern Oceans due to a decrease in surface alkalinity. The spatial patterns of the DIC components and their changes in response to an AMOC collapse are presented.

A document by Mark B. Moldwin. Click on the document to view its contents.

In Illinois, wheat (Triticum aestivum L.) is primarily cultivated in a wheat-soybean [Glycine max (L) Merr.] double-crop system. The University of Illinois wheat breeding program has been ongoing for over 75 years. Currently, it aims to improve the profitability of wheat-soybean double cropping by developing high-yielding, early-maturing wheat varieties with good grain quality. We aimed to estimate the genetic trends for grain yield, test weight, heading time, and plant height in the past 21 years of breeding at the University of Illinois to determine if these trends align with the program’s current breeding goals. We retrieved the phenotypic data from advanced yield trials, where 1,690 genotypes were evaluated from 2001 to 2021 in six locations, resulting in 67,362 observations. The presence of check genotypes allowed us to use the control population method to estimate the genetic trends, in which the check genotypes are utilized to separate genetic and nongenetic trends. Using mixed models, we identified a positive genetic trend for grain yield (33 kg ha-1 yr-1), heading time (-0.07 d yr-1), and test weight (0.91 g L-1 yr-1). Genetic trends were not significantly different from zero for plant height. Nongenetic and total phenotypic trends were not significant for grain yield. Our study revealed that the University of Illinois wheat breeding program has helped maintain the profitability of wheat-soybean double cropping in Illinois. Progress has been made by developing germplasm with higher grain yield and test weight without extending the growth cycle.

Afforestation and bioenergy with carbon capture and storage (BECCS) are two typical land-based carbon dioxide removal strategies to combat climate change. We use life cycle assessment (LCA)-integrated Earth system modeling to compare their carbon sequestration efficiencies and associated environmental impacts. The results show that, for achieving the same 0.1 ℃ global cooling effect by year 2099 under a business-as-usual emission scenario, around 101 to 226 GtC (gigatonnes of carbon) need to be bio-assimilated on land via afforestation cumulatively, while BECCS demands 21.55 to 79.47 GtC to be extracted from vegetation carbon pool to produce bioelectricity. Our study confirms the relatively higher carbon dioxide removal potential of BECCS compared to afforestation and highlights the value of using the LCA-integrated Earth system modeling method to investigate the large-scale climate mitigation practices.

We investigated tsunamis of an Mw 7.1 earthquake in the Hyuganada Sea in 2024, observed by a new dense and wide seafloor observation network, N-net, installed in the western Nankai Trough. A joint inversion of the offshore tsunami and onshore GNSS data revealed a maximum slip of 2.4 m with a significant slip near the centroid from the teleseismic analysis. The joint inversion provided reliable constraints for both up-dip and down-dip extents of the fault, while the inversions using either dataset showed limitations in the fault constraint. Comparisons with past earthquakes indicate the 2024 earthquake ruptured part of the asperity of the 1961 earthquake but not those of the 1996 earthquakes. Our fault modeling jointly using offshore and onshore data suggests the interplate seismic coupling ratio in this region is < 0.4, which was much smaller than those in the anticipated megathrust earthquake source region in the Nankai Trough.

The eastern coastline of Staten Island is vulnerable to both storm surge and sea level rise, as evidenced by extensive inundation during Superstorm Sandy in 2012. On this developed beach, there have been many attempts to lessen erosion, most notably the installation of groins to interrupt littoral drift of beach sand and artificial dunes to protect areas most vulnerable to erosion. The Army Corps of Engineers plan to install a more extensive protective system by 2030, consisting mostly of a buried seawall. This study reports on a series of five beach surveys conducted over the course of a year, to interpret current processes and variations in sediment movement as well as providing a baseline for any changes that may occur after the seawall is constructed. During each survey, 12 transects were measured using ranging poles and a Brunton transit to map the slope of the beach from the low tide mark to the base of the small dunes. Sand samples were collected at intervals along these transects, and sieved for grain size analysis. The profiles are typical of a sandy, wave-dominated beach, with a ridge of coarse sand and gravel at the low tide line and a beach face angle of 5-8°, levelling out beyond the top of the berm. Generally, the beach face is composed of medium to coarse sand, with moderate to poor sorting. These characteristics are typical of a reflective shoreline in an area with a low tidal range. Although the beach is significantly wider on the up-current side of the groins, the beach face angle is similar to the rest of the beach due to wave action. The narrowest parts of the beach are at the locations of greatest erosion, and are found where longshore currents diverge or behind large groins where the beach is starved of sediment. At these locations, artificial dunes form part of the sediment supply when they are eroded, influencing the grain size of the beach sands. Another anthropogenic influence comes from the practice of beach raking, which appears to lower the level of the backshore during summer. It may also have an influence on the grain size distribution in the remaining sand. Overall, the natural reflective nature of the shoreline along with anthropogenic influence in a densely populated area, leave it vulnerable to future storms and sea level rise. Future monitoring and comparison with this baseline will assist with mitigating these hazards.

Groundwater is the primary drinking and industrial water source for Memphis and Shelby County, Tennessee, with exploration dating back to the 1800s. The Eocene Memphis aquifer features medium to coarse sand layers interbedded with silt, clay, and lignite, capped by the confining silty clay osf the Cook Mountain Formation. In some areas, this confinement is breached, influenced by stratigraphic heterogeneity and numerous faults that displace Eocene strata. This study employs high-density Airborne Electromagnetic (AEM) data and geophysical well logs to delineate stratigraphy and geologic structures, clarifying hydrostratigraphic continuity and potential compartmentalization of groundwater flow. AEM data interpretation highlights the low resistivity Cook Mountain Formation to map folds and faults, with well logs constraining a consistent structural model. Using tools like Geoscene-3D and Petrel, we will create a three-dimensional representation of the data and conduct comparative analyses with potentiometric surface maps to assess structural and stratigraphic influences on regional groundwater flow patterns, enhancing predictions for resource availability and sustainability.

The upper mesosphere and lower thermosphere (UMLT) is the least explored atmospheric region, with the variability of water vapor, ozone, and temperature remaining poorly understood. This study demonstrates that the UMLT climate during non-summer months is governed by bottom-up processes. Specifically, tropical upwelling drives the transport of H2O, which negatively modulates the secondary ozone layer, while radiative heating of O3 influences temperatures above 90 km (T90). This “upwelling—H2O—O3—T90” link is non-localized, propagating upward and poleward at each step, creating a highly structured climate. Temperatures near 80 km (T80), dominated by adiabatic cooling, serve as an indicator of upwelling. Notably, high-latitude T90 is positively correlated with low-latitude T80 in both hemispheres, and the interannual variability of H2O, O3, and T90 exhibits interhemispheric symmetry. This study challenges the conventional view that UMLT climate is primarily driven by solar and CO2 forcing, highlighting the critical role of atmospheric dynamics.

In climate studies, it is crucial to distinguish between changes caused by natural variability and those resulting from external forcing. Here we use a suite of numerical experiments based on the ECCO-Darwin ocean biogeochemistry model to separate the impact of the atmospheric carbon dioxide (CO 2) growth rate and climate on the ocean carbon sink-with a goal of disentangling the space-time variability of the dominant drivers. When globally integrated, the variable atmospheric growth rate and climate exhibit similar magnitude impacts on ocean carbon uptake. At local scales, interannual variability in air-sea CO 2 flux is dominated by climate. The implications of our study for real-world ocean observing systems are clear: in order to detect future changes in the ocean sink due to slowing atmospheric CO 2 growth rates, better observing systems and constraints on climate-driven ocean variability are required. Plain Language Summary In climate research, it's important to determine whether changes in the ocean's ability to absorb carbon dioxide (CO 2) are due to natural climate variations or human activities. This study uses a computer model to analyze how different factors affect the ocean's absorption of CO 2. Our results show that changes in the rate of atmospheric CO 2 growth from year to year and natural climate fluctuations have a similar amount of impact on ocean carbon sequestration when considering the entire globe. However, when zooming into smaller, more-localized regions, natural climate variability plays a bigger role in driving shortterm changes. This means that to track changes in how much carbon the ocean is absorbing in the futureespecially if we start to see slower increases in atmospheric CO 2 due to efforts to reduce emissions-improved monitoring systems and a better understanding of climate-related changes in the ocean will be needed.

This study compares acid digestion and temperature ramping methods for obtaining soil organic carbon (SOC) reference data to train Fourier Transform Near Infrared (FT-NIR) models in carbonate-rich Saskatchewan agricultural soils. FT-NIR spectra were measured on soil samples (n = 431) from carbonate-rich Dark Brown Chernozem soil, with quantification of inorganic and organic carbon. Spectra were transformed using continuous wavelet transform and analyzed using cubist regression tree models. Models were built using a 70:30 train-test split validation approach. Spectral feature selection, wavelet scale, model and hyperparameter optimization were conducted using 5-fold cross-validation analysis on the training dataset. All validation metrics were calculated using the testing dataset. The temperature ramping method identified outliers with SIC greater than 1.5%, which were not detected using the acid digestion method. SOC prediction accuracy was higher using temperature ramping data (r2 = 0.66, ccc = 0.78) compared to acid digestion data (r2 = 0.44, ccc = 0.64), while TC prediction accuracy was similar for both methods (r2 = 0.58, ccc = 0.71). Removing samples with high carbonate (SIC > 1.5%) improved SOC and TC prediction accuracy using temperature ramping data (r2 = 0.71, ccc = 0.80 for SOC; r2 = 0.64; ccc = 0.75 for TC), but not when using acid digestion method. This study suggests that high carbonate content may negatively affects SOC model accuracy, especially when relying upon acid digestion methods for reference SOC data.

Snowfall is the primary contributor to Antarctic surface mass balance. Identifying regional-scale mechanisms that drive extreme snowfall provides context for investigating changes in Antarctic surface mass balance in a warmer climate. We compare drivers of extreme snowfall across five Antarctic regions using machine learning and traditional synoptic diagnostics. A convolutional neural network identifies top snow days with an accuracy of 92–94% per region when trained on just atmospheric moisture and low-level meridional wind, highlighting the importance of atmospheric river-like structures to extreme Antarctic snowfall. The network’s skill depends mainly on low-level wind in East Antarctica and atmospheric moisture in West Antarctica, suggesting that dynamic processes are comparatively more important in driving East Antarctic extreme snowfall. We leverage the quasi-geostrophic omega equation to identify mechanisms for ascent and snowfall production, and we find that East Antarctic extreme snowfall days feature stronger synoptic-scale forcing for ascent compared to West Antarctica.

Interpretation of landscape evolution and glacial history in built-up areas relies on small and often temporary exposures of sediment created during construction, aided by the examination of lidar data and published descriptions of past outcrops. This study focuses on two outcrops of fluvioglacial sediments in the southern part of Staten Island, and places them in the context of published work on the surrounding area. It aims to resolve an earlier disagreement on the origin and timing of these sediments, previously interpreted as either Pliocene Pennsauken Formation or Nebraskan glacial outwash. The two sites are approximately 30 m apart, and were exposed at different times. However, detailed logging of the beds and grain size analysis of samples collected provides a clear picture of the relationship between them. Combining the data from the two sites, we see an approximately 3.5 m thick sequence of sands and gravels with abundant cross-bedding, interpreted as fluvioglacial outwash. This sequence directly overlies the Cretaceous Raritan Formation at the first location and is capped by Wisconsinan glacial till at the second location. Potentially, this stratigraphy could be valid for either the Pennsauken Formation or pre-Wisconsinan glacial outwash, so additional evidence is needed. Sedimentary structures and grain size distributions would be similar in both cases, however the pebble compositions seen here suggest reworking of earlier glacial till, and do not match reported compositions from the Pennsauken Formation. These outcrops also appear to be lower in altitude than the projected base of the Pennsauken plain, suggesting that these sediments were deposited in a valley eroded into both the Raritan and Pennsauken Formations. Based on this work, the most likely origin of these sediments is pre-Wisconsinan glacial outwash, however it is possible that any future exposure during construction could provide further evidence to contradict this interpretation. Ultimately, this work should continue as the location of Staten Island between New Jersey and Long Island is essential for correlating Pliocene and Pleistocene deposits from these independently studied locations.

Since 1980, the U.S. has experienced 391 climate disaster events that each caused over $1 billion in losses. Droughts account for 13% of these disasters, with total losses over $360 billion. Accelerated climate change and development in areas vulnerable to climate impacts are escalating these water security risks, requiring urgent shifts in scientific research towards more actionable information for decision-making and climate resilience. A key challenge to developing science-based solutions for these events is creating robust data and tools that provide relevant policy and water management information that are easy to access and interpret, transparent in their development and use, and tailored for stakeholder needs. We present three of our ongoing interdisciplinary research efforts leveraging advancements in land surface modeling (LSM) and Earth observations (EOs) to address water security challenges across North America. First, NASA’s Land Information System team is developing phase three of the North American Land Data Assimilation System (NLDAS-3). NLDAS is a crucial LSM environment supporting water resource management, drought monitoring, and other uses. Building on stakeholder feedback and progress in data assimilation (DA), NLDAS-3 will provide more timely, robust, and accessible information for water resource operations and research. Next, we highlight a collaborative effort between university researchers and water resource managers for long-term planning in the Colorado River Basin. This multi-phase work resulted in future hydrologic scenarios that were incorporated into drought shortage negotiations, a user-centered web tool with interactive analyses of future hydrology scenarios under forest disturbance and climate uncertainties, and ongoing development of a hydrologic monitoring and early warning forecast system. Finally, we detail efforts to disentangle human and climate influences on agricultural drought in the Western U.S. This work integrates LSM, DA, and data-driven analyses to provide metrics for enhanced drought monitoring and resilience, extendable to other regions. Through these examples, we will discuss lessons learned, challenges, and opportunities to inform environmental research seeking similar actionable solutions relevant across sectors and globally.

The distance over which planktonic larvae are dispersed and the variability within that dispersal distance are important for understanding gene flow and persistence of species with planktonic larvae in the coastal ocean. The breadth of spatial and temporal scales that can be important to dispersal in shelf seas makes direct observations of larvae, and thus these statistics difficult - instead, we often use numerical simulations of circulation to estimate the statistics of larval dispersal. However, meroplanktonic life histories are most common in coastal regions where drifter-based estimates of circulation are sparsely distributed, making validation of these numerical simulations quite difficult. We use a novel technique to validate climatological mean and standard deviation of dispersal distance at a global scale by drawing on the tens of thousands of sparsely distributed drifter observations on the shelf. Numerical dispersal estimates were made using Lagrangian particle trajectories calculated with circulation fields from a 1/12{degree sign} global physical model and were validated against drifter data from the Global Drifter Program (GDP). The median dispersal distance of a climatological ensemble of numerical drifters released from a single location were found to match GDP drifter estimates quite well (with a mean deviation of 0.2%), while model estimates of dispersal were shown to underestimate the diffusivity of GDP drifters by 30 to 50%. Our results indicate that while global numerical estimates of dispersal statistics provide a close approximation of median dispersal distance in the coastal ocean, these numerical simulations underestimate the overall variation present in the coastal ocean.

A document by Berkay Aydin. Click on the document to view its contents.

In this study, we investigate the ionospheric disturbances caused by a moderate geomagnetic storm (maximum Kp = 6) occurring between February 26th and March 1st. Ionospheric response for the coupling between the solar wind, magnetosphere, and ionosphere systems can be observed across various regions of the globe and it may vary according to the local/regional background ionospheric conditions. We analyzed space and ground-based instruments (e.g., ionosondes, TEC, GUVI imager, incoherent scatter radar) covering from Antarctica to equatorial latitudes in South America. From a global perspective, we observed two ionospheric storms. The first, with a negative phase observed as a significant decrease (>30%) in the F2-layer critical frequency (foF2), occurred on February 27th at 01:00 UT. This negative phase storm was observed in all the considered regions, with the intensity progressively decreasing from higher to lower latitudes. It is worth mentioning that, for the Antarctic station, we consider the local regime of the Weddell Sea Anomaly. The second ionospheric storm occurred during the recovery phase of the geomagnetic storm on February 28th. In this last case, an enhancement above 30% in foF2 was observed only in the low-latitude station. Subsequently, the geomagnetic storm produced a super fountain effect at the Equatorial Ionization Anomaly (EIA) resulting in the enhancement of foF2.

A document by Edrian Paul Liao. Click on the document to view its contents.

Atmospheric surface pressure provides valuable information on the vertical dynamical structure of the atmosphere. Previous studies have reported that among the waves observed in surface pressure, semi-diurnal tides (SDTs) are significantly affected by the stratospheric quasi-biennial oscillation (QBO). Using historical surface-pressure observations and the Earth-system model MRI-ESM2.0, this study confirms that SDTs and the QBO are synchronized, such that SDT amplitude respectively increases or decreases at a rate of ~1 Pa per 20 ms−1 during westerly or easterly phases of the QBO at 30 hPa. Our numerical simulations and a linear analytical model support the QBO–SDT relationship being dynamically forced by background zonal winds rather than by anomalous ozone radiative heating. We also find that the QBO–SDT relationship was notably disturbed by the volcanic eruptions of Mount Agung in 1963 and Mount Pinatubo in 1991, during which increased shortwave radiative absorption caused by stratospheric aerosol enhanced the SDT amplitude. Short-lived El Nino events also occurred, moistening the upper troposphere to provide extra solar heating when volcanic aerosol was transported to higher latitudes. The influence of volcanic eruptions and El Nino events overlap with the QBO frequency band, jointly working as ‘noise’ in QBO–SDT synchronization.