Strong Events Research Articles

Opposite spectral properties of Rossby waves during weak and strong stratospheric polar vortex events

Abstract. In this study we provide a systematic characterization of Rossby wave activity during the 25 sudden stratospheric warming (SSW) and 31 strong polar vortex (SPV) events that occurred in the period 1979–2021, identifying the specific tropospheric and stratospheric waves displaying anomalous behaviour during such events. Space–time spectral analysis is applied to ERA5 data for this purpose, so that both the wavenumber and the zonal phase speed of the waves can be assessed. We find that SSW events are associated with a reduction in the phase speed of Rossby waves, first in the stratosphere and then in the troposphere; SPV events are tied to a simultaneous increase of phase speed across vertical levels. Phase speed anomalies become significant around the event and persist for 2–3 weeks afterwards. Changes of Rossby wave properties in the stratosphere during SSW and SPV events are dominated by changes in the background flow, with a systematic reduction or increase, respectively, in eastward propagation of the waves across most wavenumbers. In the troposphere, on the other hand, the effect of the background flow is also complemented by changes in wave properties, with a shift towards higher wavenumbers during SSW events and towards lower wavenumbers for SPV events. The opposite response between SSW and SPV events is also visible in the meridional heat and momentum flux co-spectra, which highlight from a novel perspective the connection between stratospheric Rossby waves and upward propagation of waves.

Frost quakes in wetlands in northern Finland during extreme winter weather conditions and related hazard to urban infrastructure

Abstract. The paper reports the first results of an experiment in northern Finland during winter 2022–2023 that aimed at studying seismic events caused by seasonal freezing in the so-called critical zone (CZ) of the Earth. These events have attracted public attention recently, as multiple reports about them from local inhabitants in Arctic and sub-Arctic areas appeared on social networks. To make an instrumental study of such events, to reveal the relationship between their occurrence and winter weather conditions, and to evaluate the possible hazard, we installed two high-resolution seismic arrays with co-located soil temperature stations at two sites in Finland, one of them being in the city of Oulu in the sub-Arctic area (65.04° N, 25.61° E) and the other one above the polar circle in the municipality of Sodankylä (67.36° N, 26.63° E). The equipment recorded continuous seismic and soil temperature data during November 2022–April 2023. Based on reports from the inhabitants of Talvikangas (Oulu) about the ground shaking and unusual noises on 6 January 2023 and their observations of new fractures on the roads there, we selected the time interval for the identification of frost quakes that originated during that day from continuous seismic records in Talvikangas and in Sodankylä. During the selected time interval, the extremely rapid air temperature drops of about −1.4 °C h−1 in Talvikangas and −0.88 °C h−1 in Sodankylä were observed. We identified and located two types of seismic events – namely, frost quakes with frequencies of about 10–20 Hz, with waveforms like those of tectonic events, and irregularly shaped frost tremors with frequencies of about 120–180 Hz. The sources of frost quakes in Talvikangas are mainly located on irrigated wetland, while in Sodankylä, about 50 % of registered frost quakes were caused by ice fracturing on the Kitinen River. However, several relatively strong events, with their origin in the wetlands, were also recorded. A significant number of sources of frost tremors are confined to wetland areas cut by irrigation channels and to roads cleaned from snow during winter both in Talvikangas and in Sodankylä. We calculated ground accelerations and ground velocities for the strongest events from both groups and compared them to equivalent properties of other seismic signals, like distant local earthquakes in the area, mining production blasts, and cargo train vibration. Our study shows that high-frequency frost tremors corresponding to surface fracture opening in the uppermost frozen surface layer of a thickness of up to 5 cm can directly damage infrastructure objects like roads and basements of buildings. Surface waves, produced by frost quakes and propagating inside the shallow soil layer, have large enough ground accelerations at epicentral distances of hundreds of metres. Therefore, frost quakes should be considered a phenomenon that can potentially damage infrastructures, and they have to be taken into account in seismic hazard assessments. Our research is the first instrumental study of seismic events originating from wetland areas. These events occur as a result of the interaction between the uppermost layer of the solid Earth's CZ and atmosphere processes that deserves further study.

Understanding the drivers of near-surface winds in Adélie Land, East Antarctica

Abstract. Near-surface winds play a crucial role in the climate of Antarctica, but accurately quantifying and understanding their drivers is complex. They result from the contribution of two distinct families of drivers: the large-scale pressure gradient and surface-induced pressure gradients known as katabatic and thermal wind. The extrapolation of vertical potential temperature above the boundary layer down to the surface enables us to separate and quantify the contribution of these different pressure gradients in the momentum budget equations. Using this method applied to outputs of the regional atmospheric model MAR at a 3-hourly resolution, we find that the seasonal and spatial variability in near-surface winds in Adélie Land is dominated by surface processes. On the other hand, high-frequency temporal variability (3-hourly) is mainly controlled by large-scale variability everywhere in Antarctica, except on the coast. In coastal regions, although the katabatic acceleration surpasses all other accelerations in magnitude, none of the katabatic or large-scale accelerations can be identified as the single primary driver of near-surface wind variability. The angle between the large-scale acceleration and the surface slope is a key factor in explaining strong wind speed events: the highest-wind-speed events happen when the katabatic and large-scale forcing are aligned, although each acceleration, when acting alone, can also cause strong wind speed. This study underlines the complexity of the drivers of Antarctic surface winds and the value of the momentum budget decomposition to identify drivers at different spatial and temporal scales.

GmNF-YC4 delays soybean flowering and maturation by directly repressing GmFT2a and GmFT5a expression.

Flowering time and growth period are key agronomic traits which directly affect soybean (Glycine max (L.) Merr.) adaptation to diverse latitudes and farming systems. The FLOWERING LOCUS T (FT) homologs GmFT2a and GmFT5a integrate multiple flowering regulation pathways and significantly advance flowering and maturity in soybean. Pinpointing the genes responsible for regulating GmFT2a and GmFT5a will improve our understanding of the molecular mechanisms governing growth period in soybean. In this study, we identified the Nuclear Factor Y-C (NFY-C) protein GmNF-YC4 as a novel flowering suppressor in soybean under long-day (LD) conditions. GmNF-YC4 delays flowering and maturation by directly repressing the expression of GmFT2a and GmFT5a. In addition, we found that a strong selective sweep event occurred in the chromosomal region harboring the GmNF-YC4 gene during soybean domestication. The GmNF-YC4Hap3 allele was mainly found in wild soybean (Glycine soja Siebold & Zucc.) and has been eliminated from G. max landraces and improved cultivars, which predominantly contain the GmNF-YC4Hap1 allele. Furthermore, the Gmnf-yc4 mutants displayed notably accelerated flowering and maturation under LD conditions. These alleles may prove to be valuable genetic resources for enhancing soybean adaptability to higher latitudes.

Short-term Classification of Strong Solar Energetic Particle Events Using Multivariate Time-series Classifiers

Solar energetic particle (SEP) events are one of the most crucial aspects of space weather that require continuous monitoring and forecasting. Their prediction depends on various factors, including source eruptions. In the present work, we use the Geostationary Solar Energetic Particle data set covering solar cycles 22, 23, and 24. We develop a framework using time-series-based machine-learning (ML) models with the aim of developing robust short-term forecasts by classifying SEP events. For this purpose, we introduce an ensemble learning approach that merges the results from univariate time series of three proton channels (E ≥10, 50, and 100 MeV) and the long-band X-ray flux (1–8 Å) channel from the Geostationary Operational Environmental Satellite missions and analyze their performance. We consider three models, namely, time series forest, supervised time series forest (STSF), and Bag-of-Symbolic Fourier Approximation Symbols. Our study also focuses on understanding and developing confidence in the predictive capabilities of our models. Therefore, we utilize multiple evaluation techniques and metrics. Based on that, we find STSF to perform well in all scenarios. The summary of metrics for the STSF model is as follows: the area under the ROC curve = 0.981, F 1-score = 0.960, true skill statistics = 0.919, Heidke skill score = 0.920, Gilbert skill score = 0.852, and Matthew’s correlation coefficient = 0.920. The Brier score loss of the STSF model is 0.077. This work lays the foundation for building near-real-time short-term SEP event predictions using robust ML methods.

Dynamic shear behaviours of granite under coupled static and high-rate loadings

Understanding dynamic shear behaviours of rock under quasi-static confinement and dynamic loads is not only of great importance in underground engineering structures, but also beneficial to reveal earthquake mechanics regarding pre-stressed rocks fracturing from initial intact to rapid shear sliding. Here we propose a dynamic shear test setup and present full-field observations of stressed rock failure at high shear rate (up to γ˙ = 220 s−1) and sliding at high slip velocity over 10 m/s in the order of coseismic slip, with the integration of a novel triaxial Hopkinson bar (Tri-HB) and high-speed three-dimensional Digital Image Correlation (3D-DIC) techniques. Dynamic shear strength and friction coefficient are determined during the dynamic shear test under confinement, with different shear strain rates and pre-stresses. The dynamic shearing process can be divided into three stages, i.e. shear deformation, fracture degradation and dynamic frictional sliding. The high energy density of shear fracture band is observed, the rate and stress state dependences of rock shear strength and dynamic frictional coefficient are revealed. The dynamic shear strength of granite follows the Mohr-Coulomb criteria under varying pre-stresses and strain rates. The gouge materials with size of 1∼10 μm are generated within the high-rate shearing zone, and this appears to control the frictional resistance. The results could help determination of rock shear strength and post-shear failure, as well as explain the shear rupture and the resistance to slip mechanism of rock faults and strong near-surface earthquake events.

Episodicity in accretion-ejection processes associated with IRAS 15398-3359

The protostar is associated with a bipolar molecular outflow ejected in an nearly northeast-southwest (NE-SW) direction, which has been extensively studied. Previous episodic accretion events have been suggested by this source. Furthermore, the analysis of the morphology and kinematics of the molecular outflow revealed the presence of four bipolar elliptical shock-like structures identified in both lobes. These structures seem to trace different ejections inclined sim 10 from each other on the plane of the sky. This led to the hypothesis that the outflow axis likely precesses and launches material episodically. Since several authors reached the conclusion of the same episodicity scenario by independent observations has become an ideal target to empirically analyze the relationship between accretion and ejection processes. We analyzed ALMA archive observations in Band 6, revealing the presence of low-velocity ($<3.5$ emission from the line to the south and north of the protostar. We studied the morphology and kinematics of the gas; our study seems to support the hypothesis of a precessing episodic outflow. The ALMA observations reveal a north-south (N-S) outflow most likely associated with the protostellar system. This outflow could be older than the well-studied NE-SW outflow. The orientation of the N-S outflow is 50 on the plane of the sky away from that of the NE-SW outflow. We also analyzed the spectral energy distribution of a far away young star and preliminarily discard it as the driver of the SE outflow remnants. The new observations support the hypothesis of strong episodic accretion-ejection events in accompanied by dramatic changes in the orientation of its ejection axis, implying that all the outflows in the region may have been driven by the same protostar.

Triggers of the 2022 Larsen B multi-year landfast sea ice breakout and initial glacier response

Abstract. In late March 2011, landfast sea ice (hereafter, “fast ice”) formed in the northern Larsen B embayment and persisted continuously as multi-year fast ice until January 2022. In the 11 years of fast-ice presence, the northern Larsen B glaciers slowed significantly, thickened in their lower reaches, and developed extensive mélange areas, leading to the formation of ice tongues that extended up to 16 km from the 2011 ice fronts. In situ measurements of ice speed on adjacent ice shelf areas spanning 2011 to 2017 show that the fast ice provided significant resistive stress to ice flow. Fast-ice breakout began in late January 2022 and was closely followed by retreat and breakup of both the fast-ice mélange and the glacier ice tongues. We investigate the probable triggers for the loss of fast ice and document the initial upstream glacier responses. The fast-ice breakup is linked to the arrival of a strong ocean swell event (>1.5 m amplitude; wave period waves >5 s) originating from the northeast. Wave propagation to the ice front was facilitated by a 12-year low in sea ice concentration in the northwestern Weddell Sea, creating a near-ice-free corridor to the open ocean. Remote sensing data in the months following the fast-ice breakout reveals an initial ice flow speed increase (>2-fold), elevation loss (9 to 11 m), and rapid calving of floating and grounded ice for the three main embayment glaciers Crane (11 km), Hektoria (25 km), and Green (18 km).

Enhancing Quantitative Precipitation Estimation of NWP Model With Fundamental Meteorological Variables and Transformer Based Deep Learning Model

AbstractQuantitative precipitation forecasting in numerical weather prediction (NWP) models is contingent upon physicals parameterization schemes. However, uncertainties abound due to limited knowledge of the precipitating processes, leading to degraded forecasting skills. In light of this, our study explores the application of a Swin‐Transformer based deep learning (DL) model as a supplementary tool for enhancing the mapping trajectory between the NWP fundamental variables and the most downstream variable precipitation. Constrained by the observational satellite precipitation product from NOAA CPC Morphing Technique (CMORPH), the DL model serves as the post‐processing tool that can better resolve the precipitation patterns compared to solely based on NWP estimation. Compared to the baseline Weather Research and Forecasting simulation, the DL post‐processing effectively extracts features over meteorological variables, leading to improved precipitation skill scores of 21.7%, 60.5%, and 45.5% for light rain, moderate rain, and heavy rain, respectively, on an hourly basis. We also evaluate two case studies under different driven synoptic conditions and show promising results in estimating heavy precipitation during strong convective precipitation events. Overall, the proposed DL model can provide a vital reference for capturing precipitation‐triggering mechanisms and enhancing precipitation forecasting skills. Additionally, we discuss the sensitivities of the fundamental meteorological variables used in this study, training strategies, and performance limitations.

Ultra-relativistic Electron Acceleration during High-intensity Long-duration Continuous Auroral Electrojet Activity Events

Magnetospheric relativistic electrons are accelerated during substorms and strong convection events that occur during high-intensity long-duration continuous auroral electrojet activity (HILDCAA) events, associated with solar wind high-speed streams (coming from coronal holes). From an analysis of ∼2–20 MeV electrons at L ∼ 2–7 measured by the Van Allen Probe satellite, it is shown that ∼3.4–4.1 days long HILDCAA events are characterized by ∼7.2 MeV electron acceleration in the L ∼ 4.0–6.0 region, which occurs ∼2.9–3.4 days after the onset of HILDCAA. The dominant acceleration process is due to wave–particle interactions between magnetospheric electromagnetic chorus waves and substorm-injected ∼100 keV electrons. The longer the HILDCAA and chorus last, the higher the maximum energy of the accelerated relativistic electrons. The acceleration to higher and higher energies is due to a bootstrap mechanism.

Changes in moisture sources contributed to the onset and development of the 2017-2019 southeast Australian drought

In 2017-2019 southeast Australia experienced one of its most severe droughts since 1900. Rainfall over the region encompassing the Murray-Darling Basin was consistently below average for three consecutive cool seasons, an unprecedented event on record. A strong positive Indian Ocean Dipole event has been previously suggested to have intensified the conditions of the drought in 2019, however the state of the climate drivers cannot fully explain the onset and development of this drought. In this study, we adopt a different approach to investigate processes other than remote climate drivers that may have triggered the drought. Using a Lagrangian model to identify moisture sources to the Murray Darling Basin, we show that local processes were crucial in explaining the onset and development of the drought. We identify the oceanic and terrestrial sources of atmospheric moisture over the Murray Darling Basin and show for the first time a significant decline in rainfall moisture supply from the Tasman Sea in 2017 and 2018. We further show that anomalous atmospheric circulation transported the expected moisture northward toward the Maritime Continent. Our results provide an explanation for the moisture and rainfall deficit that caused the 2017-19 southeast Australian drought. Understanding the processes that led to the 2017-2019 drought is an important step towards improved predictions and planning for future multi-year droughts in Australia.

Modeling of multi-fractional suspended particle pathways in a shallow water basin under influence of strong winds

In this study, we investigate the complex dynamics of multi-fractional suspended particle transport in a shallow water basin subjected to strong wind conditions. Our research focuses on understanding the interplay between wind-induced advection and particle settlement, and its implications for sediment redistribution.Through our analysis, we reveal the distinct behaviors of different sediment fractions. Clay particles, constituting the lowest fraction in sediment cores, remain suspended throughout the simulation due to their low settlement velocity, with relatively stable concentrations. Conversely, the dominant fraction, medium silt, is suspended during intense wind events but quickly settles to the bed due to its higher settling velocity. Wind stress exceeding 0.05 Pa triggers particulate matter erosion, leading to its presence in the water column.Additionally, we explore the 2D distribution of sediment characteristics, including thickness, dry density, and mud fraction, to identify areas prone to erosion and deposition. Our findings demonstrate that coastal areas of the Taganrog Bay experienced significant erosion following strong wind events, exhibiting the thinnest sediment thickness and the highest dry bulk density. Deposition areas, characterized by thicker sediment layers and lower dry density, were often found in proximity to erosion zones, indicating the influence of particle resuspension and settlement processes.Furthermore, we analyze the implications of our findings on the vulnerability of specific regions to erosion and deposition. The central part of the sea contains moderately thicker sediment layers with a moderately high mud fraction, representing a zone of fine sediment accumulation. These fine sediments, including fine silt and clay, remain suspended for longer durations and are redistributed over greater distances by currents.Overall, our study provides valuable understanding into the multi-fractional suspended particle pathways and their interaction with strong winds in shallow water basins. The results contribute to a better understanding of sediment dynamics, which has implications for coastal management, environmental monitoring, and the preservation of benthic ecosystems.

Investigating a Possible Correlation between NOAA-Satellite-Detected Electron Precipitations and South Pacific Tectonic Events

On 4 March 2021, a devastating M8.1 earthquake struck the Kermadec Islands of New Zealand. Given the tremendous energy released during the event, we sought to investigate the event’s potential impact on the ionosphere and the inner Van Allen Belt using data from the high-energy electron detectors on board the NOAA-18 satellite. The survey was also extended to the strongest shallow M6.5+ earthquakes occurring between 150° and 190° in longitude, and between −5° and −35° in latitude over the previous ten years. In nearly all cases, evident electron fluxes entering the loss cone were observed. To explore the possibility of a connection between ionospheric signals and tectonic events in this intensely active region, we analyzed electron losses from the inner Van Allen Belt, taking into account latitude, longitude, day/night times, and proximity to the South Atlantic Anomaly. Compared to previous studies, here only the most significant loss phenomena persistent in the ionosphere were considered. Particular interest was reserved for the intense electron loss events that had a duration spanning from a few to several minutes and occurred several hours before and after strong seismic events. Thereafter, time series of electron counting rates and strong Southern Pacific earthquakes were transformed into binary series, and the series multiplication was investigated. The results suggest four peaks of association, including a first couple between electron perturbations detected for ascending semi-orbits and seismic events and a second one between electron perturbations detected in the southern ionosphere and seismic events. They both anticipated the occurrence of earthquakes, occurring around 4 h before them. Other couples were observed between electron perturbations detected for descending semi-orbits and seismic events and between electron perturbations detected in the northern ionosphere and seismic events. They both occurred around 3 h after the occurrence of earthquakes. The case of perturbations anticipating seismic events has the intriguing properties of sustaining the hypothesis that a physical interaction occurred around 6 h before seismic events as in the West Pacific case. A physical model of electrons detected far several thousands of km from the earthquake epicenters was also presented. However, a simulation of random seismic events suggested that the null hypothesis cannot be fully rejected for these associations, prompting many more analyses and case studies.

Climate and sovereign risk: The Latin American experience with strong ENSO events

Using monthly panel data over the period 2007–2019 for seven Latin American countries, we empirically test the impact of climate shocks, here strong ENSO events (El Niño Southern Oscillations), on sovereign risk. Local Projections are computed to assess the dynamic response of sovereign spreads to ENSO events. Results show that strong El Niño and La Niña shocks lead to a significant increase in sovereign spreads, but with different timing. Strong El Niño shocks are associated with a significant short-term increase in sovereign spreads, while strong La Niña events are associated with a delayed but significant increase in sovereign spreads after a short-term decrease. Thus, our results suggest a potential asymmetry in the effect of these strong ENSO events on sovereign risk. We also highlight high volatility in the dynamics of sovereign spreads, which may reflect an overreaction of investors faced with the high degree of uncertainty generated by the economic and financial consequences associated with strong ENSO events. Complementary time-series estimates suggest that Costa Rica and Peru are especially subject to these effects. Overall, our results provide a warning about the fact that, in the case of Latin American countries, weather shocks associated with strong ENSO events have adverse macroeconomic and financial consequences that can lead to an increase in sovereign risk, hinder their government's ability to act as a ‘climate rescuer’ of last resort, and may be aggravated in the future by climate change.

On the development and analysis of coupled surface–subsurface models of catchments. Part 2. A three-dimensional benchmark model and its properties

The objective of this three-part work is to formulate and rigorously analyse a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled surface and subsurface flows are considered. In this second part, we construct a benchmark catchment scenario and investigate the effects of parameters within their typical ranges. Previous research on coupled surface–subsurface models have focused on numerical simulations of site-specific catchments. Here, our focus is broad, emphasising the study of general solutions to the mathematical models, and their dependencies on dimensionless parameters. This study provides a foundation based on the examination of a geometrically simple three-dimensional benchmark scenario. We develop a non-dimensional coupled surface–subsurface model and extract the key dimensionless parameters. Asymptotic methods demonstrate under what conditions the model can be reduced to a two-dimensional form, where the principal groundwater and overland flows occur in the hillslope direction. Numerical solutions provide guidance on the validity of such reductions, and demonstrate the parametric dependencies corresponding to a strong rainfall event.

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part II: Sensitivity of Surface Wind Speeds to Model Resolution and Physics

Abstract Strong wind events can cause severe economic loss and societal impacts. Peak winds over Wyoming and Colorado occur during the wintertime months, and in Part I of this two-part series, it was shown that the High Resolution Rapid Refresh (HRRR) model displays large negative biases with respect to strong wind events. In Part II of this study, we address two questions: 1) does increasing the horizontal resolution improve the representation of strong wind events over this region, and 2) are the biases in HRRR-forecasted winds related to the selected planetary boundary layer (PBL), surface layer (SL), and/or land surface model (LSM) parameterizations? We conduct Weather Research and Forecasting (WRF) simulations to address these two main questions. Increasing the horizontal resolution leads to a small improvement in the simulation of strong wind speeds over the complex terrain of Wyoming and Colorado. In general, changes in the PBL, SL, and LSM parameterizations show much larger changes in simulated wind speeds compared to increasing the model resolution alone. Specifically, changing from the Mellor-Yamada-Nakanishi-Niino scheme to the Mellor-Yamada-Janjić PBL and SL schemes results in nearly no change in the r2 values, but there is a decrease in the magnitude of the strong wind speed bias (−12.52 m s−1 to −10.16 m s−1). We attribute these differences to differences in the diagnosis of surface wind speeds and mixing in the boundary layer. Further analysis is conducted to determine the value of 1-km forecasts of strong winds compared with wind speed diagnostics commonly used by the National Weather Service.

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part I: Evaluation of Wind Speeds and Gusts

Abstract Strong wind events cause significant societal damage ranging from loss of property and disruption of commerce to loss of life. Over portions of the United States, the strongest winds occur in the cold season and may be driven by interactions with the terrain (downslope winds, gap flow, and mountain wave activity). In Part I of this two-part series, we evaluate the High-Resolution Rapid Refresh (HRRR) model wind speed and gust forecasts for the 2016-2022 winter months over Wyoming and Colorado, an area prone to downslope windstorms and gap flows due to its complex topography. The HRRR model exhibits a positive bias for low wind speeds/gusts and a large negative bias for strong wind speeds/gusts. In general, the model misses many strong wind events, but when it does predict strong winds, there is a high false alarm probability. An analysis of proxies for surface winds is conducted. Specifically, 700-mb and 850-mb geopotential height gradients are found to be good proxies for strong wind speeds and gusts at two wind-prone locations in Wyoming. Given the good agreement between low-level height gradients and surface wind speeds yet a strong negative bias for strong wind speeds and gusts, there is a potential shortcoming in the boundary layer physics in the HRRR model with regard to predicting strong winds over complex terrain, which is the focus of Part II. Lastly, the sites with the largest strong wind speed bias are found to mostly sit on the leeward side of high mountains, suggesting that the HRRR model performs poorly in the prediction of downslope windstorms.

Insights into carbonate environmental conditions in the Chukchi Sea

Abstract. Healthy Arctic marine ecosystems are essential to the food security and sovereignty, culture, and wellbeing of Indigenous Peoples in the Arctic. At the same time, Arctic marine ecosystems are highly susceptible to impacts of climate change and ocean acidification. While increasing ocean and air temperatures and melting sea ice act as direct stressors on the ecosystem, they also indirectly enhance ocean acidification, accelerating the associated changes in the inorganic carbon system. Yet, much is to be learned about the current state and variability of the inorganic carbon system in remote, high-latitude oceans. Here, we present time series (2016–2020) of pH and the partial pressure of carbon dioxide (pCO2) from the northeast Chukchi Sea continental shelf. The Chukchi Ecosystem Observatory includes a suite of subsurface year-round moorings sited amid a biological hotspot that is characterized by high primary productivity and a rich benthic food web that in turn supports coastal Iñupiat, whales, ice seals, walrus (Odobenus rosmarus), and Arctic cod (Boreogadus saida). Our observations suggest that near-bottom waters (33 m depth, 13 m above the seafloor) are a high carbon dioxide and low pH and aragonite saturation state (Ωarag) environment in summer and fall, when organic material from the highly productive summer remineralizes. During this time, Ωarag can be as low as 0.4. In winter, when the site was covered by sea ice, pH was <8 and Ωarag remained undersaturated under the sea ice. There were only two short seasonal periods with relatively higher pH and Ωarag, which we term ocean acidification relaxation events. In spring, high primary production from sea ice algae and phytoplankton blooms led to spikes in pH (pH > 8) and aragonite oversaturation. In late fall, strong wind-driven mixing events that delivered low-CO2 surface water to the shelf also led to events with elevated pH and Ωarag. Given the recent observations of high rates of ocean acidification and a sudden and dramatic shift of the physical, biogeochemical, and ecosystem conditions in the Chukchi Sea, it is possible that the observed extreme conditions at the Chukchi Ecosystem Observatory are deviating from the carbonate conditions to which many species are adapted.

A Composite Tool for Forecasting El Niño: The Case of the 2023–2024 Event

Remotely sensed data play a crucial role in monitoring the El Niño/La Niña Southern Oscillation (ENSO), which is an oceanic-atmospheric phenomenon occurring quasi-periodically with several impacts worldwide, such as specific biological and global climate responses. Since 1980, Earth has witnessed three strong ENSO events (1982–1983, 1997–1998, 2015–2016). In September 2022, La Niña entered its third year and was unlikely to continue through 2024. Instead, since 2022, forecasts have pointed to a transition from La Niña to a Neutral phase in the summer or late 2023. The onset of El Niño occurred around April 2023, and it is anticipated by sophisticated models to be a strong event through the Northern Hemisphere winter (December 2023–February 2024). The aim of this study is to demonstrate the ability of the combination of two new methods to improve the accuracy of the above claim because El Niño apart from climate anomalies, significantly impacts Earth’s ecosystems and human societies, regulating the spread of diseases by insects (e.g., malaria and dengue fever), and influencing nutrients, phytoplankton biomass, and primary productivity. This is done by exploring first the previous major El Niño events in the period January 1876–July 2023. Our calculations show that the ongoing 2023–2024 El Niño will not be the strongest.

The Circumglobal Transport of Massive African Dust and Its Impacts on the Regional Circulation in Remote Atmosphere

Abstract Atmospheric dust from North Africa, the largest and most persistently active dust source over the world, spreads widely in the Northern Hemisphere and plays essential roles in the Earth environment evolution. During 7–24 June 2020, an extremely strong dust event occurred with its westward spreading modulated by the North Atlantic Oscillation (NAO) and its eastward spreading regulated by European blocking, ultimately resulting in the circumglobal transport of African dust. The Mediterranean low pressure linked to the European blocking dipole was the key to facilitating the eastward transport of dust. This record-breaking African dust episode caused a notable diurnal precipitation decrease of 0.98 mm day−1 over northeastern India and a decrease of 1.55 mm day−1 over central North America, which was ascribed to the effect of dust-induced radiative heating on large-scale circulation. It triggered a Rossby wave train and caused anomalous high pressure over northeastern India, which weakened the India summer monsoon and consequently inhibited the occurrence of precipitation. Dust-induced radiative heating also supported the stability in the anomalous warm high over North America, further repressing import of moisture from Atlantic. Ambient moisture and atmospheric instability also presented consistent variation over North America and India characterized as strengthen descending motion and sharply reduced moist convection. This study reports, for the first time, the strong modulation of regional circulation by circumglobally transported African dust, especially in Asia and North America. The new aspects on the unexpected consequences on moisture convection indicate broader roles that the dust may play in the global climate change.