China has been experiencing severe ozone (O3) pollution, and the high concentration of O3 exposure can damage crop production, which will threaten the national food security. To better estimate the impact of O3 on crop production loss (CPL), we collect O3 data from CNEMC (China National Environmental Monitoring Centre) and CMIP6 (Coupled Model Intercomparison Project Phase 6) models to quantify O3-induced production losses in the four main crops (i.e., wheat, rice, maize, and soybean) during the historical (2013-2018) and future (2019-2099) periods. Results confirm that the impacts of O3 damage on CPLs become more and more serious during 2013-2018 in China, with the six-year mean losses of 12.2 Mt (8.5%) for wheat, 8.4 Mt (3.8%) of rice, 4.3 Mt (1.6%) of maize, and 0.7 Mt (4.8%) of soybean. The worsened O3 pollution under SSP3-7.0 scenario during the late-century will cause 283.6% (170.3%, 479.4%, 168.0%) increase in wheat (rice, maize, soybean) production losses relative to that in 2018, while the improved O3 air quality under SSP1-2.6 scenario can decrease 73.8% (69.3%, 80.8%, 75.5%) wheat (rice, maize, soybean) yield losses during the late-century relative to 2018. China has the largest population and food consumption worldwide, and the persistent O3 deterioration does have exacerbated the loss of agricultural productions. Therefore, stricter control measures are urgently needed to improve O3 air quality for ensuring national and even per capita food security in future.

Salt marshes offer important ecosystem services to coastal populations and are key organismal habitats, but are under threat as a result of drowning related to sea level rise. The extent to which any given marsh is resilient to sea level rise depends on its ability to produce vertical accretion. This is primarily driven by belowground biomass (BGB) production, which explains why BGB may serve as an early warning sign of vulnerability to marsh drowning. Declines in plant productivity may occur in BGB before aboveground biomass (AGB), indicating that BGB may serve as an early warning sign of vulnerability to marsh drowning. However, landscape assessments of BGB are rare, as BGB is difficult to measure and has high spatiotemporal variability. The Belowground Ecosystem Resiliency Model (BERM) is a geospatial informatics tool to estimate whole-plant biomass (AGB and BGB) with satellite, climate, tide, and elevation data at a 30 m spatial scale and monthly time step. BERM was built using machine learning algorithms and extensive ground-truth calibration datasets in U.S. Georgia Spartina alterniflora marshes. Here, we aimed to characterize landscape salt marsh resilience with BERM. To do this, we generated S. alterniflora AGB and BGB predictions across the Georgia coast, covering an area of 691 km2, from 2014-2023 and identified biomass trends. We found broad declines in BGB alongside gains in AGB. A total of 74% of the marsh experienced a decrease in BGB, with an average annual trend of -0.91%. Simultaneously, 88% of the marsh increased in AGB at an average rate of 0.66% per year. We classified much of the marsh (27% of area) as vulnerable to drowning (defined as a decline in BGB that exceeded model error). We also investigated biomass trends against flooding frequency, where flooding was derived via a remote sensing-based model. BGB losses were greater with increasing flooding frequencies, suggesting that accelerated SLR will further reduce productivity. Based on BERM predictions, early stage marsh drowning is likely widespread, and management actions to conserve ecosystem services are an urgent need.

Forces that govern the motion of planetary flows originate from interactions occurring at scales that are orders of magnitude smaller than the flow itself. These mesoscale and sub–mesoscale eddies contribute to large-scale flow mixing, particle entrainment, and tracer transport. Therefore, oceanic simulations must accurately characterize their contributions to capture the flow dynamics. In this work, a stochastic representation of the primitive equations, derived within the framework of modeling under location uncertainty (LU), is proposed. This framework decomposes the velocity into a smooth–in–time large–scale component and a random field, accounting for unresolved mesoscale and sub–mesoscale motions. The LU framework is unique in its derivation, as it is obtained from physical conservation principles through a stochastic version of the Reynolds transport theorem. Two data-driven approaches are developed to model the random noise using proper orthogonal decomposition and dynamic mode decomposition methods. For higher resolution, model based noise as well as mixture of model based and data driven noise with observational constraints are proposed and compared. Numerical simulations demonstrate that the LU framework improves flow prediction for gyre circulation compared to its deterministic counterpart. Enhanced flow mixing, jet characteristics, and tracer transport are observed. Additionally, terms in the LU framework are analyzed for their contribution to structuring the flow.

A document by Michal Ostrowski. Click on the document to view its contents.

The oxygen content of the ocean’s deep waters is declining, threatening valuable marine ecosystems and the ocean’s crucial role in carbon storage. Widely observed banding in marine sediments is believed to be connected to oxygen-sensitive diagenetic processes in shallow sediments. This study combines a spatial survey of distinctive banding in shallow sediments (< 1 meter below seafloor) with novel 1 million-year long records of banding occurrence at International Ocean Discovery Program (IODP) Sites U1474 and U1313 to assess the link between sedimentary diagenetic bands and bottom water oxygen across the middle to late Pleistocene. The spatial survey of banding in shallow sediments indicates that bands at active redox fronts are most clearly connected to high bottom water oxygen concentrations, while the stratigraphic survey shows numerous instances of the synchronous development of banding in both hemispheres during the Pleistocene’s glacial marine isotope stages (MIS) in tandem with low bottom water oxygen events. A review of available evidence suggests that the diagenetic bands form due to rising bottom water oxygen concentrations, which trap reduced iron sourced from organic matter-enriched deposits from a preceding oxygen minimum. Long-eccentricity paced variability in the abundance of bands in both northern and southern hemispheres suggests orbital control on bottom water oxygen and carbon cycle dynamics.

Climate change is already impacting ecosystem composition and species distributions. Here we study two different, but equally valuable New Zealand fisheries (Tasman Bay and Golden Bay, and Chatham Rise), and the potential impacts of climate change on ecosystem structure. We use mizer, a size-based multispecies modelling package, to simulate interacting fish species in each ecosystem. Utilising therMizer, an extension of mizer which incorporates temperature effects on species' metabolic rate and aerobic scope, we implement historical climate data from the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP). This enables us to recreate the historical time period of 1961–2010, deriving reasonable steady state biomasses closely matching past observations. We then carry out a controlled warming simulation experiment, allowing for temperature to remain steady or to increase for both ecosystems, both with and without fishing pressure. The shallower ecosystem of Tasman and Golden Bay has more thermally-tolerant species and experiences an overall increase in community biomass under warming, whilst the deeper ecosystem of Chatham Rise suffers an overall decline. In addition, fishing has a stronger negative impact on the Chatham Rise community. Smaller bodied animals also tend to be more resilient, both to warming and fishing impacts. Despite differences in community responses, the majority of important fisheries suffer reduced yields under warming in both ecosystems. Issues raised during the incorporation of temperature effects include species’ thermal tolerances and model calibration to data. This study facilitates ecosystem intercomparisons under climate change and offers insight into drivers of ecosystem responses.

Retrieval of ocean surface current using single-antenna synthetic aperture radar (SAR) relies on the removal of the wind and wave signal (wind-wave bias) from the observed SAR Doppler shift. This is often performed using deterministic atmospheric and wave models input into a geophysical model function, though atmospheric models are chaotic, and their predictability is flow-dependent. 251 Sentinel-1 SAR scenes, obtained in 2023 over Skagerrak and Kattegat, are analyzed to assess the uncertainty in the radial velocity estimation caused by uncertainties in the wind speed and direction provided by MEPS, an operational regional atmospheric ensemble system. Using ensemble surface wind direction and speed from MEPS, we investigate the conditions under which the radial velocity retrieval uncertainties exceed community-guided thresholds. The maximum wind speed and direction values that meet the specified thresholds are also estimated using two approaches. Our findings show that retrievals have a higher degree of uncertainty when the wind speed uncertainty exceeds 20% of the mean field, with larger uncertainties associated with low-wind speed conditions. A strong dependency between satellite antenna-look and maximum uncertainty values is reported. Employing ensemble models on radial velocity uncertainty quantification has promising potential and may be extended to operational global products.

We combine lidar temperature observations onboard a research aircraft with numerical simulations in the framework of the SOUTHTRAC (Southern Hemisphere Transport, Dynamics, and Chemistry) Campaign. Deep propagation of gravity waves (GW) from the troposphere to the lower mesosphere is studied above the Southern Andes during two flights in September 2019. We use the Weather Research and Forecasting (WRF) model with a configuration for the simulations that has been validated in a previous study of this campaign. Strong orographic GW were detected during both flights, that were conceived for different latitudes. The observational and numerical data reveal the presence of significant GW attenuation, breaking and secondary wave generation above the stratopause due to the development of convective and dynamic instability as well as conditions for wave evanescence. The GW generated by topography were not able to alter the stable structure of the stratosphere, but the scenario was quite different in the lower mesosphere. The disturbed zones in that layer were produced by the combined effect on lapse rate of the background temperature variation and the perturbations associated with GW, which together may induce large vertical gradients. As a consequence, areas of reduced stability (with low or even negative buoyancy parameter) emerge above the stratopause. The existence of these GW self-induced attenuation layers in the mesosphere where temperature perturbations produce large negative gradients may lead to an amplitude growth control mechanism for the upward propagating waves.

A document by Samuel Fagbemi. Click on the document to view its contents.

Electromagnetic whistler-mode waves play a crucial role in the acceleration and precipitation of radiation belt electrons. Statistical surveys of wave characteristics suggest that these waves should preferentially scatter and precipitate relativistic electrons on the day side. However, the night-side region is expected to be primarily associated with electron acceleration. The recent low-altitude observations reveal relativistic electron precipitation in the night-side region. In this paper, we present statistical surveys of night-side relativistic electron losses due to intense precipitation bursts. We demonstrate that such bursts are associated with storm time substorm injections and are likely related to relativistic electron scattering by ducted whistler-mode waves. We also speculate on the role of injections in creating conditions favorable for relativistic electron precipitation.

Open Collaboration Hydrology (OCH) is an online community and platform devoted to promoting the use and development of open and collaborative water science and management tools. As part of the Voices for Science AGU program, this presentation shares OCH's story, approach, and communication channels. Moreover, this presentation will share the profound impact of open and collaborative approaches on expanding the boundaries of water systems knowledge and its management. Open Collaboration Hydrology embraces participatory/collaborative modelling principles, open science, and the Free Open Source Software standards (FOSS) to facilitate the convergence of diverse perspectives, understandings, and beliefs about water systems. This presentation also aims to inspire attendees by showcasing the transformative potential of Open Collaboration in hydrology and inviting them to engage in making water science resources equitable, accessible, and inclusive for everyone.