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The Standardized Precipitation Index (SPI) is computed over CONUS using daily precipitation estimates from the NOAA Daily U.S. Climate Gridded Dataset (NClimGrid-Daily). From the NClimGrid-SPI (1951-present; 0.05°x0.05°), we derive historical hydro-climatological conditions and drought information from the Drought Severity and Coverage Index (DSCI) which combines drought levels into a single areal value (from 0 to 500). One of our objective is to better understand drought dynamic and particularly how drought episodes evolve from short term rainfall deficit (i.e., less than three months) to persistent drought condition (i.e., beyond nine months). To investigate how those cascading effect work, we use a Machine Learning (ML) approach to identify spatio-temporal patterns of drought episodes over CONUS. Several unsupervised ML clustering algorithms are tested using an ensemble of features including drought duration, rainfall accumulation, drought severity (maximum DSCI, time of maximum DSCI), seasonality (drought beginning and end dates), location (latitude, longitude). Results show that the most severe drought events (i.e., DSCI > 350) are those that have the longest durations and for which drought relief is associated with higher rainfall accumulation regardless of the location considered. Furthermore, there is an apparent consistency across accumulation scales and the number of parameters selected with an optimum number of clusters around four. The Euclidian distance ML models tested seems to be able to define spatiotemporal areas of similar drought patterns. Differences between models are observed in terms of spatial definitions and predominance of a cluster at a given location. The strongest prevalence of a given cluster has allowed to isolate areas of coherence such as the Pacific Northwest, the PNW, the Eastern Seaboard and the Southeast, and the Southwest area along the MX-US border. Domain delineations are weaker for areas such as the Rockies, the Midwest, and the Great Plains. While the SPI algorithm assumes a Gamma (McKee et al., 1993) or a Pearson III (Guttman, 1998) distribution for monthly rainfall accumulation periods, results show that this assumption might not be optimal depending on the domain considered and the accumulation period when applied to daily drought monitoring.

Abstract We present results from Space Test Program Satellite‐6 (STP Sat‐6) in geosynchronous orbit. The electron detector, named SEED (Solid‐state Energetic Electron Detector) is built entirely from commercial‐off‐the‐shelf (COTS) parts. The instrument data show the electron environment over the entire energy range of detection and over angular resolution. We compare the instrument data to the Magnetospheric Particle Sensor—High Energy (MPS‐HI) data onboard GOES‐17 located nearby to STP Sat‐6 which were briefly available for 19 days. We conclude that instruments made from COTS components are an inexpensive and viable way to build particle detectors for geosynchronous orbit.

Abstract. Ocean dissolved oxygen (O2) is an essential climate variable crucial for sustaining the marine life; thus, changes of O2 at various spatiotemporal scales should be quantified and understood. Here, we study the climatology and annual cycle of O2 at regional to global scales using eight available gridded observational products. These datasets are generated by different groups using different primary data selection, quality control, bias correction and interpolation methods including statistical and machine-learning based mapping methods. A common set of metrics was collaboratively developed by the community of Gridded Observational Dataset Intercomparison Project-Dissolved Oxygen (GODIP-DO) to facilitate the inter-comparison, which allows assessing the robustness of the uncertainties through the spread of the products. Global mean O2 profiles are consistent among all products (±3 µmol kg-1), with the well-established decrease from high surface values to a minimum ~1000 meters, and subsequent increase to higher O2 at depth, although local differences could reach ±25 µmol kg-1 (0–1000 m). The hemispheric O2 annual cycle correlates strongly with ocean temperature changes, suggesting the key driver of temperature for the O2 annual cycle. However, there is substantial variation in the global mean 0–100 m O2 annual cycle, the magnitude ranges from -1 to 0.8 μmol kg-1, with a standard deviation of the datasets of ~0.3 μmol kg-1. Average oxygen minimum zones (OMZ) volume among the products is 80.92 × 106 km3 (±1.95 %) for a 60 µmol kg-1 threshold and 152.00 × 106 km3 (±1.72 %) for a 90 µmol kg-1 threshold. Our results serve as a starting point for resolving the uncertainty budget of the ocean O2 changes.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Mediterranean Sea (MedSea) is highly sensitive to climate-driven changes in temperature, oxygen, and pH, among other variables. To better assess these long-term trends, we developed CARIMED (CARbon, tracers, and ancillary data In the MEDiterranean Sea), the first comprehensive, harmonised data synthesis product for the MedSea. CARIMED integrates hydrographic, inorganic carbon, transient tracer, and ancillary measurements from 46 research cruises spanning the period from 1976 to 2018, containing observations for the entire water column across all MedSea sub-basins. A substantial component of the data was retrieved from fragmented or locally archived historical records, thus consolidating previously inaccessible measurements. Following global synthesis approaches, CARIMED applies a quality-controlled, and bias-adjusted framework. A key adaptation was the secondary quality control (2QC) procedure, specifically tailored to the MedSea's unique hydrography, utilising sub-basin divisions and supplementary checks (including statistical consistency assessments) to resolve complex, often contradictory, inter-cruise offsets. This rigorous process minimised systematic biases, yielding a dataset with improved consistency, and highlights the urgent need for adapted standard operating procedures and reference materials to address the MedSea biogeochemical particularities. CARIMED delivers two complementary, freely available products: the aggregated original cruise data product (<a href="https://doi.org/10.20350/digitalCSIC/17785" target="_blank" rel="noopener">https://doi.org/10.20350/digitalCSIC/17785</a>; Garc&iacute;a-Ib&aacute;&ntilde;ez et al., 2025) and the final bias-adjusted data synthesis product (<a href="https://doi.org/10.25921/cp5b-zq67" target="_blank" rel="noopener">https://doi.org/10.25921/cp5b-zq67</a>; &Aacute;lvarez et al., 2025). This essential resource establishes a new benchmark for assessing long-term biogeochemical trends, validating regional ocean models, and supporting climate-change mitigation and adaptation strategies in this rapidly changing semi-enclosed basin.

Abstract IGRF-14 is the fourteenth generation of the International Geomagnetic Reference Field (IGRF), a spherical harmonic model of Earth’s main magnetic field and its secular variation, developed through international collaboration under the auspices of the International Association of Geomagnetism and Aeronomy (IAGA). This paper describes the development, in October 2024, of candidate main field (MF) models at epochs 2020.0 and 2025.0, and a secular variation (SV) model at 2025.0, derived from Swarm satellite data, as well as the validation of the SV model using ground-based observatory measurements. Swarm data collected through May 2025 were subsequently used to update the continuous parent model from which these candidates were derived, which now spans 2014.42 to 2024.92. This model is used to conduct a retrospective assessment of SV performance and to analyze recent secular acceleration (SA) signals. Our results reveal a pronounced SA pulse centered in 2022 and provide evidence for a geomagnetic jerk in 2024, confirmed by recent observatory data from Western Europe and North America. These rapid, nonlinear core field changes have already contributed to the early degradation of the IGRF-14 SV forecast, underscoring the challenges of modeling geomagnetic field evolution and the importance of continuous satellite and ground-based observations. Graphical Abstract

We investigate the occurrence characteristics and amplitude-frequency relationships of Pc5 ultra-low frequency (ULF) waves (1.67–6.7 mHz) using 30 years of GOES magnetic field data (1995–2025) from GOES-8 to GOES-18. An enhanced CLEAN algorithm, employing iterative Hanning peak model fitting and subtraction, identified 27,279 radial, 26,145 azimuthal, and 31,259 parallel wave events in the Mean Field-Aligned coordinate system. Radial and parallel waves exhibit peak amplitudes between 9–15 MLT, driven by solar wind dynamic pressure, while azimuthal and parallel components dominate in the 15–21 MLT sector, consistent with Kelvin-Helmholtz instability. Strong power-law relationships (R^2 ge 0.85) between amplitude and frequency are observed for radial and azimuthal components in dawn and dusk sectors, with weaker correlations for the parallel component (R^2 le 0.24). These relationships vary with solar wind conditions, with radial components showing robust power-law fits under strong and moderate conditions (R^2 ge 0.93). ULF wave occurrence rates peak during solar maxima, correlating strongly with solar wind parameters (R^2 ge 0.73), and exhibit quasi-biennial oscillations (QBOs)–short-term (1.5–4 year) modulations linked to solar dynamo processes. High-pass filtered data show strong correlations with dynamic pressure (R^2 ge 0.85). These findings resolve discrepancies in prior studies, highlighting the interplay of solar cycle, QBOs, and MLT-dependent drivers in Pc5 ULF wave dynamics, with implications for radiation belt dynamics and space weather forecasting.

Abstract. Magnetic flux ropes are helical structures of magnetic field which form in a variety of magnetized plasmas. In near-Earth space, flux ropes are a manifestation of energy transfer at the magnetopause and in the magnetotail current sheet. We present a new method to detect magnetic flux ropes in large-scale simulations using only magnetic field line tracing. The method does not require prior identification of structures of interest such as current sheets or null lines and thus allows one to identify flux ropes of any size and orientation anywhere in the simulation domain. In this work, the new method is implemented in the hybrid-Vlasov model Vlasiator and demonstrated in global simulations of the terrestrial magnetosphere. We study the evolution of flux ropes forming during flux transfer events on the dayside magnetopause under a southward interplanetary magnetic field. It is found that flux ropes with an axial orientation along the dawn–dusk direction and propagating beyond the cusps will rapidly reconnect with the lobe magnetic field and vanish. In contrast, the flux ropes remaining near the equatorial plane and with an axial orientation along the flow direction – that is, tangential to the magnetopause – can maintain their structure and propagate tens of Earth radii down the tail in the absence of a reconnecting shear magnetic field component. These results are a step forward in the global characterization of flux ropes in and around the magnetosphere and may help in guiding the search for elusive far-tail flux ropes in satellite measurements.

Ocean dissolved oxygen (O2) is an essential climate variable that is crucial for the sustainment of ocean life; thus, changes of O2 at various spatiotemporal scales should be quantified and understood. Here, we study the mean state (climatology) and a

Identifying the influence of low-density Indigenous populations in paleofire records has been methodologically challenging. In the Southwest United States, well-replicated fire histories suggest that abundant lightning and suitable climate conditions drove frequent low-severity wildfires in dry pine forests independent of human activities even as ethnography provided hints that highly mobile indigenous populations used fire in myriad land use contexts. Here, we leverage published and unpublished tree-ring fire history records from pine forests in Western Apache (Ndee) traditional territory in central and eastern Arizona (N = 34 sites, N = 649 trees) to demonstrate that historical fire regimes were overwhelmingly influenced by Ndee cultural burning. Our tree-ring synthesis shows significantly more frequent fires in Ndee territory than elsewhere in the region for centuries before the establishment of reservations (1600-1870 CE). Despite the heightened fire activity, fires were largely small and asynchronous, occurred disproportionately in late April and May, when Ndee invested significant subsistence activities in these pine forests, and occurred independent of climate drivers. This suggests that Ndee fire stewardship created a patchwork of nearly annual small, spring fires that inhibited natural fire spread and limited the influence of drought on fire activity. Our work shows that even relatively small, highly mobile populations of forager-gardeners had significant influence on some pre-Euroamerican fire regimes despite abundant natural ignitions. Our study shows clearly that Indigenous fire management impacted fire-size distributions, fire frequencies, and fire seasonality in ways that cannot be explained by seasonal and annual lightning densities.

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