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Why Crop Yield Decreases at High Temperatures

EOS - Tue, 07/29/2025 - 12:00
Editors’ Highlights are summaries of recent papers by AGU’s journal editors. Source: AGU Advances

Observational analyses consistently find that yields of major rainfed crops increase with temperature up to a threshold of approximately 32°C, above which they reduce sharply. However, we still have a limited understanding of the explanation for such outcomes and, therefore, future yield projections are uncertain.

Agricultural productivity as a function of cumulative growing-season evapotranspiration. The connection between agricultural productivity and the cumulative water flux out of the ecosystem suggests that a land surface model that explicitly represents transpiration can be useful for exploring yield variations. Credit: Vargas Zeppetello et al. [2025], Figure 2

Vargas Zeppetello et al. [2025] explore an innovative hypothesis, which is both intuitive and revolutionary: that soil water stress limits both agricultural productivity and evaporative cooling, giving rise to increase in near surface temperature and finally decrease of yield at extremely high temperatures. In other words, they assume that water stress, and its influence on evaporative cooling, temperature, and agricultural productivity, drives the yield-temperature relationship.

To test their assumption, the authors use growing-season transpiration from an idealized land surface model as a proxy for yield. This approach reproduces the observed yield-temperature relationship, even though the model includes no mechanisms that limit productivity at high temperatures. In experiments where the influence of temperature on soil moisture is suppressed, yields still decline during hot, dry periods in a manner consistent with the observations. The authors conclude that future yield outcomes depend more critically on changes in rainfall, or irrigation, than suggested by estimates that attribute yield losses primarily to temperature variations.

Citation: Vargas Zeppetello, L. R., Proctor, J., & Huybers, P. (2025). Is water stress the root cause of the observed nonlinear relationship between yield losses and temperature? AGU Advances, 6, e2025AV001704. https://doi.org/10.1029/2025AV001704

—Alberto Montanari, Editor-in-Chief, AGU Advances

Text © 2025. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Effect of spatial resolution of conductivity models for Geomagnetically Induced Currents estimation: case study in a geological complex region

Geophysical Journal International - Tue, 07/29/2025 - 00:00
SummaryIn a region of complex geology, we examine the influence of spatial resolution of conductivity models on Geomagnetically Induced Currents (GICs) estimations. We focus on the southern region of Portugal mainland, for which magnetotelluric (MT) sounding measurements have been obtained with lower noise from human activity. Using two conductivity models inverted from sets of MT soundings with different sampling distance, we look for an interpretation of the differences in GIC estimations at substation grounding resistances. We make use of two different proxies, the Local Effective Field (LEF) and the Regional Electromotive Source (RES), built from the electric induced field at each substation site and the sum of electromotive forces along all transmission lines connected to that substation, respectively. We compare different time signals associated to GICs using a parameter that combines Pearson correlation and linear regression slope, the Correlation Regression Coefficient (CRC). Our main conclusion is that spatially detailed information on lateral heterogeneities of the conductivity associated to complex geology is crucial for a rigorous assessment of GIC hazard, leading to relative differences in GIC standard deviation and in GIC peak values that can amount to more than 100% in certain cases. Additionally, using LEF and RES, we emphasise the non-locality of GIC drivers and bring new input concerning the choice of proxies used to monitor and forecast this kind of hazard.

Crustal rheological characteristics in the Scandinavian Peninsula and its vicinity implied from Lg wave attenuation tomography

Geophysical Journal International - Tue, 07/29/2025 - 00:00
SummaryThe Scandinavian Peninsula and its vicinity comprise highly tectonically diverse blocks, including the Baltic Shield, the continental margin, and the North Sea Basin. The crustal rheology is a critical constraint to understanding the tectonic evolution in this region. Based on 19 416 Lg waveforms from 233 earthquakes and 560 broadband digital stations, using an inversion method combining both single- and two-station ray paths, we constructed a broadband (0.05 and 10.0 Hz) Lg wave attenuation model in the study region, with the resolution approaches to 110 km (∼1°) or higher in areas with dense ray path coverages. The QLg distributions correlate well with regional geological features. The Baltic Shield exhibits the highest QLg, consistent with its thick Precambrian crust and high rheological rigidity developed through Archean Svecofennian orogeny. In contrast, passive margins with crustal thinning, magmatic modification, and thick sedimentary sequences exhibit strong attenuation, reflecting a reduction in rheological strength resulting from interactions with mantle plumes and extensional tectonics. The North Sea Basin exhibits the lowest QLg values and the presence of hydrocarbon-bearing sediments. The extremely high QLg distribution reveals the ancient cratonic core of the Baltic Shield, particularly in areas where the surface rock dating sample cannot be collected due to seawater coverage.

Observations and Seismoacoustic Simulations of Earthquake-Generated Infrasound Waves in Nonepicentral Regions

Geophysical Journal International - Tue, 07/29/2025 - 00:00
SummaryWe analysed infrasound waves associated with the Gyeongju earthquake (ML 5.8) that occurred on September 12, 2016, in the southeastern Korean Peninsula. For infrasound wave detection, the Progressive Multi-channel Correlation method was applied to the infrasound dataset recorded at 7 arrays operating in South Korea at epicentral distances ranging from 178 to 472 km. Based on the back-projection method constrained by array-dependent celerity and azimuth deviation models, the source regions were identified in both the epicentral and nonepicentral regions. Remarkably, the nonepicentral secondary sources of this earthquake were located in regions with shallow water depths: i) the western coastal area in the Yellow Sea and ii) the shallow ocean basin and bank in the East Sea. The location results obtained from the earthquake could be corroborated through its foreshock (ML 5.1), yielding location results consistent with those of the mainshock. The generation of infrasound waves over shallow water depths was fortuitously validated by direct recordings of dominant single-frequency (∼0.3 Hz) infrasound waves at close range via temporary sensors near the ocean basin and bank. We interpreted that low-frequency infrasound signals could be generated from interactions among the ocean floor, shallow seawater, and atmosphere. We performed numerical simulations of seismoacoustic fields to predict ground motions on the seafloor and acoustic transmission efficiency between the water and air interface. The simulations quantified the energy transfer through different media and clarified our observational results. We found that because this solid Earth‒water‒atmosphere coupled air wave has a relatively low frequency (∼0.3 Hz), it can survive propagation over long distances compared with high-frequency infrasound waves generated in inland and mountain regions. In this study, we extend our understanding of water‒atmosphere coupling and the monitoring framework for earthquake-associated nonepicentral infrasound waves, encompassing not only inland ground shaking but also shallow sea regions located far from the epicentre.

Kilotesla magnetic field generation via ultraintense laser interaction with hollow microcapsule

Physical Review E (Plasma physics) - Mon, 07/28/2025 - 10:00

Author(s): S. Chintalwad and David J. Stark

We investigate the generation of kilotesla-level magnetic fields in laser-irradiated hollow conical targets through particle-in-cell simulations. This configuration proves effective in producing magnetic fields tens of kiloteslas in strength that persist on a picosecond timescale. Moreover, the holl…


[Phys. Rev. E 112, 015212] Published Mon Jul 28, 2025

Two-loop turbulent helical magnetohydrodynamics: Large-scale dynamo and energy spectrum

Physical Review E (Plasma physics) - Thu, 07/24/2025 - 10:00

Author(s): Michal Hnatič, Tomáš Lučivjanský, Lukáš Mižišin, Yurii Molotkov, and Andrei Ovsiannikov

We present a two-loop field-theoretic analysis of incompressible helical magnetohydrodynamics (MHD) in fully developed stationary turbulence. A key feature of helical MHD is the appearance of an infrared-unstable “masslike” term in the loop diagrams of the magnetic response function. Physically, thi…


[Phys. Rev. E 112, 015211] Published Thu Jul 24, 2025

Quantification of ion scattering by solar-wind current sheets: Pitch-angle diffusion rates

Physical Review E (Plasma physics) - Wed, 07/23/2025 - 10:00

Author(s): Zijin Zhang, Anton V. Artemyev, and Vassilis Angelopoulos

The transport of energetic particles in the heliosphere is profoundly influenced by interactions with coherent structures in the turbulent magnetic field of the solar wind, particularly current sheets. While prior studies have largely relied on idealized turbulence models, this work quantifies the r…


[Phys. Rev. E 112, 015209] Published Wed Jul 23, 2025

Weak decaying collective-excitation approximation for Yukawa one-component plasmas

Physical Review E (Plasma physics) - Wed, 07/23/2025 - 10:00

Author(s): Ilnaz I. Fairushin and Anatolii V. Mokshin

In this paper, the theoretical model of weak decaying collective excitations characteristic of many-particle systems with long-range interaction potentials is developed using the example of one-component strongly coupled Yukawa plasmas. The proposed model is based on the self-consistent relaxation t…


[Phys. Rev. E 112, 015210] Published Wed Jul 23, 2025

Nonlinear kinetic simulations of Jeans instability in a magnetized dusty plasma

Physical Review E (Plasma physics) - Mon, 07/21/2025 - 10:00

Author(s): Masaru Nakanotani, Luis Lazcano Torres, Gary P. Zank, and Edward Thomas, Jr.

The Jeans instability in a magnetized dusty plasma is considered a fundamental process in space, where magnetic fields are common. We investigate the Jeans instability in a magnetized dusty plasma using 1D and 2D particle-in-cell simulations, in which dust grains are treated as particles and the Poi…


[Phys. Rev. E 112, 015208] Published Mon Jul 21, 2025

Hot spot generation in hybrid $X$ pinches on a portable low-inductive KING generator

Physical Review E (Plasma physics) - Thu, 07/17/2025 - 10:00

Author(s): T. A. Shelkovenko, I. N. Tilikin, A. R. Mingaleev, V. M. Romanova, and S. A. Pikuz

The small-sized, low-voltage, and low-inductive KING generator (190–230 kA, 40 kV, 200–240 ns) was specially designed to work with X-pinches; however, it was unstable in its original design. In the present work, it is experimentally shown that an increase in the inductance of the output node of the …


[Phys. Rev. E 112, 015207] Published Thu Jul 17, 2025

Characterizing PPP ambiguity resolution residuals for precise orbit and clock corrections integrity monitoring

GPS Solutions - Tue, 02/25/2025 - 00:00
Abstract

To meet the high-precision and high-integrity positioning demands of safety–critical applications, monitoring the quality of precise satellite products in global navigation satellite system (GNSS) precise point positioning (PPP) is crucial. This work employs ionosphere-free (IF) PPP with ambiguity resolution (PPP-AR) phase residuals to construct test statistics for monitoring the quality of precise satellite corrections. By utilizing precise satellite orbit and clock products from CODE, WUM, and GRG, the PPP-AR phase residuals were first analyzed with sample moments, Allan variance and power spectral density (PSD). The key findings are as follows: (1) The skewness and kurtosis results indicate that ambiguity-fixed phase residuals deviate from an ideal zero-mean Gaussian distribution and exhibit a super-Gaussian distribution. (2) Allan variance and PSD analysis reveal that flicker noise dominates the phase residuals. (3) The noise amplitudes are similar for all satellites, but certain differences are observed among different GNSS systems and satellite types. (4) The noise level of phase residuals is influenced by the receiver types, antenna types, and precise products from different analysis centers. Leveraging the error characteristics, the two-step Gaussian overbounding (OB) method was employed to estimate the corresponding OB parameters of the phase residuals. The overbounding results demonstrate that, under similar conditions, phase residuals can be bounded by the calculated bound within the acceptable integrity risk after removing the detected outliers. Anomaly monitoring experiments further show that phase residuals can effectively capture anomalies in precise satellite corrections, with the set threshold successfully detecting such anomalies.

Calibration of h'Es from VIPIR2 ionosondes in Japan

Earth,Planets and Space - Tue, 02/25/2025 - 00:00
The measurement of virtual height of the sporadic E layer (h'Es) is very sensitive to the type of ionosonde used and the calibration processes. The ionosondes used by the national institute of communication an...

Solar System Elemental Abundances from the Solar Photosphere and CI-Chondrites

Space Science Reviews - Mon, 02/24/2025 - 00:00
Abstract

Solar photospheric abundances and CI-chondrite compositions are reviewed and updated to obtain representative solar system abundances of the elements and their isotopes. The new photospheric abundances obtained here lead to higher solar metallicity. Full 3D NLTE photospheric analyses are only available for 11 elements. A quality index for analyses is introduced. For several elements, uncertainties remain large. Protosolar mass fractions are H (X = 0.7060), He (Y = 0.2753), and for metals Li to U (Z = 0.0187). The protosolar (C+N)/H agrees within 13% with the ratio for the solar core from the Borexino experiment. Elemental abundances in CI-chondrites were screened by analytical methods, sample sizes, and evaluated using concentration frequency distributions. Aqueously mobile elements (e.g., alkalis, alkaline earths, etc.) often deviate from normal distributions indicating mobilization and/or sequestration into carbonates, phosphates, and sulfates. Revised CI-chondrite abundances of non-volatile elements are similar to earlier estimates. The moderately volatile elements F and Sb are higher than before, as are C, Br and I, whereas the CI-abundances of Hg and N are now significantly lower. The solar system nuclide distribution curves of s-process elements agree within 4% with s-process predictions of Galactic chemical evolution models. P-process nuclide distributions are assessed. No obvious correlation of CI-chondritic to solar elemental abundance ratios with condensation temperatures is observed, nor is there one for ratios of CI-chondrites/solar wind abundances.

Contribution of microtopography off the Ryukyu Islands to coastal sea-level amplification during the 2022 Tonga meteotsunami

Earth,Planets and Space - Mon, 02/24/2025 - 00:00
The January 2022 Tonga volcanic eruption generated atmospheric pressure waves that propagated over the ocean’s surface and triggered a meteotsunami. This meteotsunami caused significant amplitudes exceeding 10...

A new ensemble learning method based on signal source driver for GNSS coordinate time series prediction

GPS Solutions - Sun, 02/23/2025 - 00:00
Abstract

Accurately modeling and prediction the nonlinear motion of GNSS (Global Navigation Satellite System) coordinate time series holds significant theoretical and practical value for the study of geodynamics. A novel integrated network, named Ensemble Learning method based on Signal Source Driver (ELSSD), is proposed, which leverages the strengths of Long Short-Term Memory (LSTM) and Deep Self-Attention Neural Network (DSANN), while integrating GNSS loading data as an additional data source. Additionally, a multi-track synchronous sliding window data processing strategy is designed to address the challenge of multi-source data fusion input. The effectiveness of this algorithm is validated using GNSS coordinate time series from 186 global stations over a period of 10 years. Experimental results initially illustrate that, when accounting for displacement caused by environmental loading effects, there is a marked improvement in the modeling and prediction accuracy compared with GNSS input-only. Furthermore, the application of three ensemble network strategies-Bagging, Boosting, and Stacking-have further been demonstrated to enhance modeling and prediction accuracy. Compared with LSTM and DSANN networks, the proposed ELSSD algorithm achieves an average RMSE (Root Mean Square Error) of 3.6 mm for both modeling and prediction, with modeling accuracy improvements of 4.8% and 6.2%, while prediction accuracy improvements of 5.4% and 5.9%, respectively. With respect to the traditional Least Square method, there is an improvement of 22.1% and 27.9% in modeling and prediction accuracy, respectively. Regarding noise characteristics, there is a significant reduction in colored noise amplitude, with decreases of 36.7% and 36.0% observed in modeling and prediction, respectively. Simultaneously, the velocity uncertainty experiences an average reduction of 27.1% and 27.5%. The average velocity differences are measured at 0.06 mm/year and 0.24 mm/year, respectively. Hence, our findings suggest that the ELSSD algorithm emerges as an effective methodology for handling multi-source data input in GNSS coordinate time series, presenting promising practical applications in the field.

Coseismic slip distribution of the 2024 Noto Peninsula earthquake deduced from dense global navigation satellite system network and interferometric synthetic aperture radar data: effect of assumed dip angle

Earth,Planets and Space - Fri, 02/21/2025 - 00:00
The Mw 7.5 Noto Peninsula earthquake, which occurred on January 1, 2024, was considerably hazardous to the peninsula and surrounding regions owing to a strong motion, large-scale crustal deformation, and subse...

Evidence for pre-Noachian granitic rocks on Mars from quartz in meteorite NWA 7533

Nature Geoscience - Fri, 02/21/2025 - 00:00

Nature Geoscience, Published online: 21 February 2025; doi:10.1038/s41561-025-01653-z

Quartz-rich clasts in Martian meteorite NWA 7533 indicate the presence of granitic rocks on early Mars that formed via hydrothermal activity and impact melting, according to petrologic and in situ geochemical analyses.

Multichannel PredRNN: a storm-time TEC map forecasting model using both temporal and spatial memories

GPS Solutions - Thu, 02/20/2025 - 00:00
Abstract

The predictive learning of total electron content (TEC) spatiotemporal sequences aims to generate future TEC maps by learning from historical data, where both the spatial appearances and temporal variations are crucial for accurate predictions. However, the state-of-the-art TEC map prediction models typically employ sequential stacking of ConvLSTM, ConvGRU, and their variants. These models focus more on modeling temporal variations, and the spatial features extracted from the historical sequence are highly abstracted, resulting in the fine-grained spatial appearances not being adequately memorized or transmitted, leading to fuzzy prediction results during storm time. In this paper, we used PredRNN to propose a storm-time ionospheric TEC spatiotemporal prediction model with multichannel features, named Multichannel PredRNN, which can simultaneously remember the temporal patterns and spatial appearances in input sequence. The temporal memory as well as the spatial memory are updated repeatedly over time, ensuring that both temporal memory and spatiotemporal memory are fully utilized in prediction. According to Dst index, 60 magnetic storm events from 2011 to 2019 were selected as the dataset. We first discussed the impact of feature combinations on predictive performance. The results show that using multichannel feature (TEC + Dst&F10.7), the Multichannel PredRNN and the comparison models ConvGRU and ConvLSTM have the best prediction performance. Then we used the optimal feature combination for prediction. We compared Multichannel PredRNN with IRI-2016, COPG, ConvLSTM and ConvGRU under various conditions, including the entire test magnetic events, periods of quiet and storm, different phases of geomagnetic storms, and the most severe geomagnetic storms. Finally, we compared the performance of different output steps. The experimental results indicate that in all cases, Multichannel PredRNN with dual memory state and zigzag flow is superior to four compared models.

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