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Abstract

A M6.8 earthquake struck the High Atlas Mountains in Morocco on 8 September 2023, ending a 63-year seismic silence. We herein attempt to clarify the seismogenic fault and explore the underlying mechanism for this seismic event based on multiple data sets. Utilizing probabilistic Bayesian inversion on interferometric radar data, we determine a seismogenic fault plane centered at a depth of 26 km, striking 251° and dipping 72°, closely aligned with the Tizi n’Test fault system. Given a hypocenter at the Moho depth, the joint inversion of radar and teleseismic data reveals that the rupture concentrates between depths of 12 and 36 km, offsetting the Mohorovičić discontinuity (Moho) at ∼32 km. Considering a strong link between magma activity and failure in lower crust, we propose that the triggering of the earthquake possibly was mantle upwelling that also supports the high topography.

Abstract

The Arabian Sea (AS) hosts the world's thickest and most intense oxygen minimum zone (OMZ), and previous studies have documented a dramatic decline of dissolved oxygen (DO) in the northeastern AS in recent decades. In this study, using the recently released data from Biogeochemical-Argo floats, we found a surprising trend of recovery in deoxygenation within the core region of the OMZ in the AS (ASOMZ) since 2013. The average DO concentration increased by approximately threefold, from ∼0.63 μM in 2013 to ∼1.68 μM in 2022, and the thickness of the ASOMZ decreased by 13%. We find that the weakening of Oman upwelling resulting from the weakening of the summer monsoon is the main driver of oxygenation in the ASOMZ. In addition, the reduction of primary production linked to warming-driven stratification reinforces deoxygenation recovery at depth.

Abstract

Atmospheric rivers (ARs) play a crucial role in the poleward transport of water vapor, and the AR-associated precipitation is a critical component of global water supplies, making it critical that we understand how ARs may change in the future. To approach this issue, integrations of the NASA Goddard Institute for Space Studies global climate model ModelE version 2.1 (GISSE2.1) are employed. Multiple configurations of the model simulating different climates are analyzed: (a) the last-glacial maximum; (b) present day; (c) the end of the 21st century. The thermodynamic and dynamic components of changes to AR frequency are analyzed using a decomposition method. This method utilizes differences in distinct AR seasonal climatology frequencies derived from various vertically integrated water vapor transport (IVT) thresholds to resolve AR frequency into its components. Global mean state changes in poleward AR frequency for different climates are dominated by precipitable water vapor (PWV) changes. A set of idealized cold and warm climates in which present day sea surface temperatures are uniformly changed are considered for a targeted analysis of the south Pacific Ocean basin. For this analysis, frequency and distribution of AR events in the model runs are analyzed by comparing them to changes in the jet stream as well as the Eulerian storm tracks and low-level baroclinicity. Latitudinal shifts in the ARs in the south Pacific Ocean basin using our integrations are not as tightly coupled to these two storm-related climatological metrics in the midlatitudes but fare better on the poleward side of the storm tracks.

Abstract

The detection of preslip, occurring hours to days before a large earthquake, using geodetic measurements has been a major focus in earthquake prediction research. A recent study claims to have detected a preseismic signal interpreted as accelerating slip near the hypocenter of the 2011 great Tohoku-oki earthquake, starting approximately 2 hr before the mainshock. This claim is based on a stacking procedure using GNSS (Global Navigation Satellite System) data. However, a follow-up study demonstrated that the signal disappeared when specific GNSS noise was corrected. Here we utilize tiltmeter records, independent on GNSS, to check whether the claimed preseismic signal is detected using a similar stacking procedure. Our results show no acceleration-like deformation from 2 hr before the mainshock. This indicates that no precursory slip exceeded the noise level of the tilt data, and if any preslip occurred, it was less than 5.0 × 1018 Nm in seismic moment.

Abstract

Marine carbonaceous aerosols, originating from marine and continental sources, are significant global aerosol components. The understanding of marine carbonaceous aerosols is currently limited, especially in the Southern Hemisphere. Furthermore, there is an ongoing debate regarding the contributions of marine fresh and ancient carbon to marine aerosols. To address these gaps, we conducted an extensive investigation utilizing a long-term data set of aerosol samples collected during six Antarctic cruises (28°N–78°S) from 2013 to 2020. Our analysis revealed an average organic carbon (OC) concentration of 1.29 ± 1.15 μg/m3 and an element carbon (EC) concentration of 0.13 ± 0.18 μg/m3 in the samples. These concentrations varied within a range spanning from background marine samples to those impacted by substantial continental transport. Fossil fuel combustion remained the primary source of continental influence in the marine environment, as evidenced by the OC/EC ratio. The δ13CTC value for all samples range from −22.3‰ to −28.4‰, with a mean value of −26.3 ‰. Using a three-endmember isotopic source model, we find that continental carbonaceous aerosols make substantial contributions in the Eastern Indian Ocean (81 ± 4%), while their prevalence is lower in the Southern Ocean (SO) (44 ± 20%). In contrast to mid-latitudes, primary marine aerosol of the SO exhibits a significantly higher contribution from the fresh carbon pool (52 ± 19%). Furthermore, our study suggests that SO sea ice may play a potential role in driving emissions from the fresh carbon pool. These findings contribute to a comprehensive understanding of the effects of carbonaceous aerosols on climate change and the ocean-atmosphere carbon cycle.

Abstract

Dimethyl sulfide (DMS) is the largest source of natural sulfur in the atmosphere and undergoes oxidation reactions resulting in gas-to-particle conversion to form sulfate aerosol. Climate models typically use independent chemical schemes to simulate these processes, however, the sensitivity of sulfate aerosol to the schemes used by CMIP6 models has not been evaluated. Current climate models offer oversimplified DMS oxidation pathways, adding to the ambiguity surrounding the global sulfur burden. Here, we implemented seven DMS and sulfate chemistry schemes, six of which are from CMIP6 models, in an atmosphere-only Earth system model. A large spread in aerosol optical depth (AOD) is simulated (0.077), almost twice the magnitude of the pre-industrial to present-day increase in AOD. Differences are largely driven by the inclusion of the nighttime DMS oxidation reaction with NO3, and in the number of aqueous phase sulfate reactions. Our analysis identifies the importance of DMS-sulfate chemistry for simulating aerosols. We suggest that optimizing DMS/sulfur chemistry schemes is crucial for the accurate simulation of sulfate aerosols.

Abstract

In this paper, we examine differences in cloud adjustments (often called rapid adjustments) that occur as a direct result of abruptly increasing the solar constant by 4% or abruptly quadrupling of atmospheric CO2. In doing so, we devise a novel method for calculating the cloud adjustments for the abrupt solar forcing simulations that uses differences between coupled model simulations with abrupt solar and CO2 forcing, in combination with uncoupled, atmosphere-only, abrupt CO2 forced experiments that have prescribed sea-surface temperature. Our main findings are that (a) there are substantial differences in the responses of stratocumulus and cumulus clouds to solar and CO2 forcing, which follow the differences in the direct radiative effect that solar and CO2 forcing have at cloud top, and (b) there are differences in the adjustment of the average optical depth of high clouds to solar and CO2 forcing that we speculate are driven by the differences in the vertical profile of radiative heating and differences in the pattern of sea-surface temperature change (for a fixed global mean temperature). These cloud adjustments contribute significantly to the total net cloud radiative effect, even after 150 years of simulation.

Abstract

The atmospheric large-scale environment determines the occurrence of local extreme precipitation, and it is unclear how climate change affects this relationship. Here we investigate the present-day relationship between large-scale circulation types (CTs) and daily precipitation extremes over Scandinavia and its future change. A 50-member EC-Earth3 large ensemble is used to assess future changes against internal variability. We show that CTs are related to extreme precipitation over the entire domain. The intensity of extreme daily precipitation increases in all seasons in the future climate, generally following the strength of warming in the six different future scenarios considered. However, no significant future change is found in the relationship between extreme precipitation and the CTs in any season or scenario. The results have important implications for applications that rely on the stability of this relationship, such as statistical and event-based dynamical downscaling of future weather and climate predictions and long-term climate projections.

Abstract

We study the statistical features of magnetosphere-ionosphere (M-I) coupling using a two-way M-I model, the GT configuration of the Multiscale Atmosphere Geospace Environment (MAGE) model. The M-I coupling characteristics, such as field-aligned current, polar cap potential, ionospheric Joule heating, and downward Alfvénic Poynting flux, are binned according to the interplanetary magnetic field clock angles over an entire Carrington Rotation event between 20 March and 16 April 2008. The MAGE model simulates similar distributions of field-aligned currents compared to empirical Weimer/AMPS models and Iridium observations and reproduces the Region 0 current system. The simulated convection potential agrees well with the Weimer empirical model and displays consistent two-cell patterns with SuperDARN observations, which benefit from more extensive data sets. The Joule heating structure in MAGE is generally consistent with both empirical Cosgrove and Weimer models. Moreover, our model reproduces Joule heating enhancements in the cusp region, as presented in the Cosgrove model and observations. The distribution of the simulated Alfvénic Poynting flux is consistent with that observed by the FAST satellite in the dispersive Alfvén wave regime. These M-I coupling characteristics are also binned by the Kp indices, indicating that the Kp dependence of these patterns in the M-I model is more effective than the empirical models within the Carrington Rotation. Furthermore, the MAGE simulation exhibits an improved M-I current-voltage relation that closely resembles the Weimer model, suggesting that the updated global model is significantly improved in terms of M-I coupling.

Abstract

Solar wind is an intermediary in energy transfer from the Sun into the Earth's magnetosphere, and is considered as a decisive driver of energetic electron dynamics at the geosynchronous orbit (GEO). Based on machine learning technology, several models driven by solar wind parameters have been established to predict GEO electron fluxes. However, the relative contributions of different solar wind parameters on GEO electron fluxes are still unclear. Recently, a feature attribution method, Deep SHapley Additive exPlanations (Deep SHAP) is proposed to open black boxes of machine learning models. In this study, we use the Deep SHAP method to quantify contributions of different solar wind parameters with an artificial neural network (ANN) model. Backpropagating the prediction results of this ANN model from 2011 to 2020, SHAP values for four solar wind parameters (interplanetary magnetic field (IMF) B Z, solar wind speed, solar wind dynamic pressure, and proton density) are calculated and comprehensively analyzed. The results suggest that solar wind speed with a lag of 1 day is the most important driver. We further investigate relative roles of different parameters in three specific electron fluxes variation events (corresponding to electron fluxes reaching a local maximum, a local minimum, and unchanged, respectively). The results suggest that high solar wind speed and southward IMF B Z (high dynamic pressures) facilitate increases (decreases) of electron fluxes. These findings help reveal the underlying physical mechanisms of GEO electron dynamics and help develop more accurate prediction models for GEO electron fluxes.

Science, Volume 384, Issue 6701, June 2024.

Science, Volume 384, Issue 6701, June 2024.

Science, Volume 384, Issue 6701, June 2024.

Science, Volume 384, Issue 6701, June 2024.

Compound droughts under climate change in Switzerland
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, 2024
The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.

Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024, 2024
This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and its dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We propose methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the refractivity bias under different atmospheric conditions and thus improve the applications of the GNSS RO data in the deep troposphere.

A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, 2024
This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.

Stability requirements of satellites to detect long-term stratospheric ozone trends based upon Monte Carlo simulations
Mark Weber
Atmos. Meas. Tech., 17, 3597–3604, https://doi.org/10.5194/amt-17-3597-2024, 2024
We investigate how stable the performance of a satellite instrument has to be to be useful for assessing long-term trends in stratospheric ozone. The stability of an instrument is specified in percent per decade and is also called instrument drift. Instrument drifts add to uncertainties of long-term trends. From simulated time series of ozone based on the Monte Carlo approach, we determine stability requirements that are needed to achieve the desired long-term trend uncertainty.

Design and evaluation of BOOGIE: a collector for the analysis of cloud composition and processes: Biological, Organics, Oxidants, soluble Gases, inorganic Ions and metal Elements
Mickael Vaitilingom, Christophe Bernard, Mickael Ribeiro, Christophe Berthod, Angelica Bianco, and Laurent Deguillaume
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-95,2024
Preprint under review for AMT (discussion: open, 0 comments)
The new collector BOOGIE has been designed and evaluated to sample cloud droplets. Computational fluid dynamic simulations are performed to evaluate the sampling efficiency for different droplets size. In situ measurements show very good water collection rates and sampling efficiency. BOOGIE is compared to other cloud collectors and the efficiency is comparable, as well as the chemical and biological compositions.

Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, 2024
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.