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Abstract

The physical processes governing a tropical cyclone's lifecycle are largely understood, but key processes occur at scales below those resolved by global climate models. Increased resolution may help simulate realistic tropical cyclone intensification. We examined fully coupled, global storm-resolving models run at resolutions in the range 28–2.8 km in the atmosphere and 28–5 km in the ocean. Simulated tropical cyclone activity, peak intensity, intensification rate, and horizontal wind structure are all more realistic at a resolution of ∼5 km compared with coarser resolutions. Rapid intensification, which is absent at typical climate model resolutions, is also captured, and exhibits sensitivity to how, and if, deep convection is parameterized. Additionally, the observed decrease in inner-core horizontal size with increasing intensification rate is captured at storm-resolving resolution. These findings highlight the importance of global storm-resolving models for quantifying risk and understanding the role of intense tropical cyclones in the climate system.

Abstract

Decadal variations in near-surface wind speed (NSWS) and their causes are poorly understood. We found that the decadal transition of winter NSWS in northern China (NC) was 10 years earlier than in southern China (SC), which could be linked to the changes in intensities of the eastward wave-activity flux and Siberian High (SH) induced by the Warm Arctic-Cold Eurasia (WACE) dipole pattern. From 1973 to 1990, the WACE pattern from positive to negative phases confined the eastward wave trains to high latitudes with a decreasing SH, inducing an NSWS reduction. From 1991 to 2000, the WACE strengthened from negative to positive phases, causing a decadal transition in NSWS first in NC. After 2000, accompanied by the strengthening of the positive WACE, the eastward wave trains propagated downstream to lower latitudes, the SH and the meridional pressure gradient enhanced. Therefore, the transition of decadal NSWS occurred in SC until 2000.

Abstract

Nighttime oxidation of monoterpenes (MT) via the nitrate radical (NO3) and ozone (O3) contributes to the formation of secondary organic aerosol (SOA). This study uses observations in Atlanta, Georgia from 2011 to 2022 to quantify trends in nighttime production of NO3 (PNO3) and O3 concentrations and compare to model outputs from the EPA's Air QUAlity TimE Series Project (EQUATES). We present urban-suburban gradients in nighttime NO3 and O3 concentrations and quantify their fractional importance (F) for MT oxidation. Both observations and EQUATES show a decline in PNO3, with modeled PNO3 declining faster than observations. Despite decreasing PNO3, we find that NO3 continues to dominate nocturnal boundary layer (NBL) MT oxidation (FNO3 = 60%) in 2017, 2021, and 2022, which is consistent with EQUATES (FNO3 = 80%) from 2013 to 2019. This contrasts an anticipated decline in FNO3 based on prior observations in the nighttime residual layer, where O3 is the dominant oxidant. Using two case studies of heatwaves in summer 2022, we show that extreme heat events can increase NO3 concentrations and FNO3, leading to short MT lifetimes (<1 hr) and high gas-phase organic nitrate production. Regardless of the presence of heatwaves, our findings suggest sustained organic nitrate aerosol formation in the urban SE US under declining NOx emissions, and highlight the need for improved representation of extreme heat events in chemistry-transport models and additional observations along urban to rural gradients.

Abstract

Iron emissions from human activities, such as oil combustion and smelting, affect the Earth's climate and marine ecosystems. These emissions are difficult to quantify accurately due to a lack of observations, particularly in remote ocean regions. In this study, we used long-term, near-source observations in areas with a dominance of anthropogenic iron emissions in various parts of the world to better estimate the total amount of anthropogenic iron emissions. We also used a statistical source apportionment method to identify the anthropogenic components and their sub-sources from bulk aerosol observations in the United States. We find that the estimates of anthropogenic iron emissions are within a factor of 3 in most regions compared to previous inventory estimates. Under- or overestimation varied by region and depended on the number of sites, interannual variability, and the statistical filter choice. Smelting-related iron emissions are overestimated by a factor of 1.5 in East Asia compared to previous estimates. More long-term iron observations and the consideration of the influence of dust and wildfires could help reduce the uncertainty in anthropogenic iron emissions estimates.

HTAP3 Fires: Towards a multi-model, multi-pollutant study of fire impacts
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Stephen R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christophe Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-126,2024
Preprint under review for GMD (discussion: open, 0 comments)
The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model set up are discussed, and the official recommendations for the project are presented.

Development of an under-ice river discharge forecasting system in Delft-Flood Early Warning System (Delft-FEWS) for the Chaudière River based on a coupled hydrological-hydrodynamic modelling approach
Kh Rahat Usman, Rodolfo Alvarado Montero, Tadros Ghobrial, François Anctil, and Arnejan van Loenen
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-116,2024
Preprint under review for GMD (discussion: open, 0 comments)
Rivers in cold climate regions such as Canada undergo freeze up during winters which makes the estimation forecasting of under-ice discharge very challenging and uncertain since there is no reliable method other than direct measurements. The current study explored the potential of deploying a coupled modelling framework for the estimation and forecasting of this parameter. The framework showed promising potential in addressing the challenge of estimating and forecasting the under-ice discharge.

Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event
Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième
Nat. Hazards Earth Syst. Sci., 24, 2857–2874, https://doi.org/10.5194/nhess-24-2857-2024, 2024
Early warning is essential to minimise the impact of flash floods. We explore the use of highly detailed flood models to simulate the 2021 flood event in the lower Ahr valley (Germany). Using very high-resolution models resolving individual streets and buildings, we produce detailed, quantitative, and actionable information for early flood warning systems. Using state-of-the-art computational technology, these models can guarantee very fast forecasts which allow for sufficient time to respond.

Abstract

We propose the lag-1 autocorrelation of daily precipitation as a simple diagnostic of tropical precipitation variability in climate models. This metric generally has a relatively uniform distribution of positive values across the tropics. However, selected land regions are characterized by exceptionally low autocorrelation values. Low values correspond to the dominance of high frequency variance in precipitation, and specifically of high frequency convectively coupled equatorial waves. Consistent with previous work, we show that CMIP6 climate models overestimate the autocorrelation. Global kilometer-scale models capture the observed autocorrelation when deep convection is explicitly simulated. When a deep convection parameterization is used, though, the autocorrelation increases over land and ocean, suggesting that land surface-atmosphere interactions are not responsible for the changes in autocorrelation. Furthermore, the metric also tracks the accuracy of the representation of the relative importance of high frequency and low frequency convectively coupled equatorial waves in the models.

Abstract

The globally averaged diurnal temperature range (DTR) has shrunk since the mid-20th century, and climate models project further shrinking. Observations indicate a slowdown or reversal of this trend in recent decades. Here, we show that DTR has a minimum for average temperatures close to 0°C. Observed DTR shrinks strongly at colder temperature, where warming shifts the average temperature toward the DTR minimum, and expands at warmer temperature, where warming shifts the average temperature away from the DTR minimum. Most, but not all climate models reproduce the minimum DTR close to average temperatures of 0°C and a stronger DTR shrinking at colder temperature. In models that reproduce the DTR minimum, DTR shrinking slows down significantly in recent decades. Models project that the global-mean DTR will shrink over the 21st century, and models with a DTR minimum close to 0°C project slower shrinking than other models.

Abstract

Wet and cold biases on the Tibetan Plateau (TP) commonly exist in global and regional climate simulations. Previous studies have explored the possible causes of wet and cold biases and contributed to reducing these biases. However, the connection between wet and cold biases remains insufficiently addressed. Our research indicates that the TP wet bias converts into positive snow amount bias not continually but efficiently and concentratedly, under the control of snow phenology in different regions. Furthermore, the complex relationship between snow amount, snow coverage and surface albedo restricts the transformation of snow amount to surface albedo bias, and thus to cold bias. Our research highlights the spatio-temporally divergent transformation of wet to cold bias on the TP during snow season, providing a novel perspective to understand the intrinsic connection between wet and cold biases and improve climate simulations on the TP.

Abstract

Microbial acetate metabolism is an important part of marine carbon cycling. We present a comprehensive study to constrain microbial acetate metabolism and its regulation in surface seawater of the northwest Pacific Ocean. We found that acetate oxidation (rate constant k: 0.016–0.506 day−1) accounted for 77.6%–99.4% of the total microbial acetate uptake, suggesting that acetate was predominantly used as a microbial energy source. Acetate also served as a significant biomass carbon source, as reflected by the elevated contribution of acetate assimilation to bacterial carbon production. Acetate turnover was largely influenced by water mass mixing and nutrient conditions. Atmospheric deposition was a source of acetate in surface water and this process can also impact the microbial acetate uptake. Microbial utilization of acetate could account for up to 25.9% of the bacterial carbon demand, suggesting the significant role of acetate metabolism in microbial carbon cycling in the open ocean.

No abstract is available for this article.

Abstract

In this paper, we demonstrate the applicability of the data-driven solar energetic particle (SEP) model, SOlar-wind with FIeld-lines and Energetic-particles (SOFIE), to simulate the acceleration and transport processes of SEPs and make forecast of the energetic proton flux at energies ≥10 MeV that will be observed near 1 AU. The SOFIE model is built upon the Space Weather Modeling Framework developed at the University of Michigan. In SOFIE, the background solar wind plasma in the solar corona and interplanetary space is calculated by the Stream-Aligned Aflvén Wave Solar-atmosphere Model(-Realtime) driven by the near-real-time hourly updated Global Oscillation Network Group solar magnetograms. In the background solar wind, coronal mass ejections (CMEs) are launched by placing an force-imbalanced magnetic flux rope on top of the parent active region, using the Eruptive Event Generator using Gibson-Low model. The acceleration and transport processes are modeled by the Multiple-Field-Line Advection Model for Particle Acceleration. In this work, nine SEP events (Solar Heliospheric and INterplanetary Environment challenge/campaign events) are modeled. The three modules in SOFIE are validated and evaluated by comparing with observations, including the steady-state background solar wind properties, the white-light image of the CMEs, and the flux of solar energetic protons, at energies of ≥10 MeV.

Abstract

In this study, the thermospheric mass density (TMD) features observed by the CHAllenging Minisatellite Payload between 2002 and 2010 were extracted using deep learning (DL) technology; the TMD features were then mapped and modeled with the Interplanetary environment information (IEI), solar radiation, and geomagnetic indices. The DL model was used to simulate the TMD features during Day of Year (DOY) 222–241 in 2014, a period that experienced complex solar-terrestrial environmental variations. We explore the TMD features under different solar-terrestrial environmental conditions and discuss the effects of various inputs by comparing the DL simulation results with satellite observations from Gravity Recovery and Climate Experiment-A and Swarm-A, as well as the simulation results from Jacchia-Bowman 2008, Naval Research Laboratory Mass Spectrometer Incoherent Scatter radar model 2.1, and Drag Temperature Model 2013. These results show that the DL model can better capture the TMD features after adding IEI. Part of these TMD features, including the high-latitude TMD enhancement during the space hurricane event (DOY 232, 2014) and global TMD variations under complex solar-terrestrial environmental disturbances (DOY 222–225, 2014), cannot be well described by the geomagnetic indices. The DL model indicates that the east-west component of the interplanetary magnetic field (IMF By) has a great impact on TMD variations, and its modulation is different from the typical energy injection process during storms. Our results emphasize the crucial influence of IEI on TMD under both geomagnetic disturbances and quiet conditions.

Abstract

The Earth's ionosphere undergoes regular intra-annual variations (IAVs) characterized by two peaks and troughs around the equinoxes and solstices. This phenomenon is crucial for analyzing the ionospheric response to geomagnetic storms. This study presents a comprehensive analysis of the IAVs contributed by diurnal and semidiurnal migrating tides (DW1 and SW2) using Global Ionospheric Maps (GIMs) data from 2017 to 2021. Through data stacking techniques, the seasonal variability and splitting phenomenon of DW1 and SW2 across different latitudes are examined. The findings indicate that the splitting of these tides can be attributed to their quasi-periodic variations, predominantly composed of annual oscillation (AO) and semiannual oscillation (SAO). The combination of DW1, SW2, and their side-band harmonics results in beats with annual and semiannual periodicities, enabling the restoration of the seasonal variations in DW1 and SW2. The ionospheric day-to-day variations were reconstructed by superimposing DW1 and SW2, and their IAVs were evaluated using the envelope method. Comparison with IAVs driven by Earth's orbital geometry reveals that tide-driven IAVs are more significant, and both exhibit solar activity dependence. The results advance the understanding of ionospheric variability, emphasizing the critical role of tidal contributions.

Abstract

This paper investigates time-lag effects of ionospheric response to two severe geomagnetic storms (Kp = 8) on the degradation of kinematic precise point positioning (PPP) solutions, utilizing over 5500 Global Navigation Satellite Systems (GNSS) stations distributed worldwide. Focusing on these two severe geomagnetic storms that occurred during solar cycle 24, the study employs an open-source positioning software package, namely RTKLIB, to derive the PPP solutions. The findings reveal significant variations in time lags across different magnetic latitudes. These variations are driven by ionospheric responses to a southward interplanetary magnetic field and subsequent decreases in the SMY-H index during the 2015 St. Patrick's Day Storm and the 2017 September 7–8 Storm. Specifically, at high latitudes, PPP degradation primarily manifests during the main phase of the storm, resulting in delays spanning from several minutes to 1–2 hr after the sudden onset of the storm. In contrast, mid- and low latitudes exhibit a wider range of delays extending up to tens of hours. Notably, rapid positioning degradation is observed predominantly at the magnetic local time noon and midnight sectors. The study discusses these time lag effects concerning the intensity of various ionospheric disturbances triggered by the interactions among the solar wind, magnetosphere, and ionosphere during geomagnetic storms. The insights obtained from this research have the potential to be integrated into physics-based and machine-learning models to enhance forecasting capabilities of space weather impacts.

No abstract is available for this article.

Abstract

In this study, we investigate the impacts of the 17 March 2013 strong geomagnetic storm on the wholly coupled Solar Wind-Magnetosphere-Ionosphere-Thermosphere system-of-systems. Obtained from multipoint observations, our new results show (1) the solar-wind Alfven waves propagating antisunward in the sheath region and (2) oscillating solar wind interplanetary magnetic field (IMF) and electric (E) field (IEF EY) that powered (3) rigorous dayside and nightside flux transfer events (FTEs) when (4) the nightside-reconnection-related short circuiting led to fast-time Subauroral Ion Drifts (SAID) and Subauroral Polarization Streams (SAPS) E field development across the inner-magnetosphere plasmapause where the solar-wind Alfven waves (4) transitioned into kinetic Alfven waves (5) fueling the hot zone. Also, the antisunward solar-wind Alfven waves (6) drove enhanced large-scale region-1 field-aligned currents creating (7) undershielding conditions (8) allowing the dawn-to-dusk convection E field's earthward penetration, and (9) generated increased solar-wind kinetic energy, which became deposited (10) to the ionosphere increasing the ionospheric electron temperature (by the downward flowing suprathermal electron fluxes) and (11) to the thermosphere oscillating the neutral winds and increasing the neutral temperature, and finally leading to (12) the development of bright stable auroral red (SAR) arcs in (13) the enhanced SAID/SAPS flow channels (FCs) developed during FTEs, (14) demonstrated with FC-2 and FC-3 events, in the enhanced polar convection that (15) the Rice Convection Model could reproduce. Finally, we conclude the antisunward-propagating large-amplitude solar-wind Alfven waves' ultimate significant role in creating the favorable conditions for the various phenomena documented with the new observational results (1–14).

No abstract is available for this article.

Abstract

The low frictional strength of smectite minerals, such as montmorillonite, is thought to play a critical role in controlling the rheology and the stability of clay-rich faults. In this study, we perform molecular dynamics simulations on a model clay system. Clay platelets are simplified as oblate ellipsoids interacting via the Gay-Berne potential. We study the rheology and structural development during shear in this model system, which is sheared at constant strain rates for 10 strains after compression and equilibrium. We find that the system exhibits velocity-strengthening behavior over a range of normal stresses from 1.68 to 56.18 MPa and a range of strain rates from 6.93 × 105 to 6.93 × 108/s. The relationship between shear stress and strain rate follows the Herschel-Bulkley model. Shear localization is observed at lower strain rates despite the velocity-strengthening friction, while homogeneous shear is realized at higher strain rates. The structure change due to shear is analyzed from various aspects: the porosity, particle orientation, velocity profile, and the parallel radial distribution function. We find that particle rearrangement and compaction dominate at the early stage of shear when the shear stress increases. The shear band starts to form in the later stage as the shear stress decreases and relaxes to a steady-state value. The structural development at low strain rates is similar to previous experimental observations. The stacking structure is reduced during shear and restores logarithmically with time in the rest period.