Feed aggregator

Abstract

The electromagnetic interaction between Europa and the plasma sheet in the Jovian magnetosphere generates Alfvén waves, ultimately generating auroral footprints in Jupiter's atmosphere. The position of Europa's auroral footprint is a proxy for travel time of the Alfvén waves. We measured Europa's footprint position using the far-ultraviolet images of Jupiter obtained by the Hubble Space Telescope in two observing campaigns in 2014 and 2022. The measured footprint position indicates a longer Alfvén travel time in the 2022 campaign. We retrieved the plasma sheet parameters at Europa's orbit from the footprint position by tracing the Alfvén waves launched at Europa and found an increase of both mass density and temperature in the plasma sheet in 2022. The Poynting flux generated at Europa is calculated with the retrieved plasma sheet parameters, which suggests the total energy transfer from Europa to its auroral footprint is similar to the case of Io.

Abstract

Quantifying the variable impacts of wildfire smoke on ozone air quality is challenging. Here we use airborne measurements from the 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN) to parameterize emissions of reactive nitrogen (NOy) from wildfires into peroxyacetyl nitrate (PAN; 37%), NO3 − (27%), and NO (36%) in a global chemistry-climate model with 13 km spatial resolution over the contiguous US. The NOy partitioning, compared with emitting all NOy as NO, reduces model ozone bias in near-fire smoke plumes sampled by the aircraft and enhances ozone downwind by 5–10 ppbv when Canadian smoke plumes travel to Washington, Utah, Colorado, and Texas. Using multi-platform observations, we identify the smoke-influenced days with daily maximum 8-hr average (MDA8) ozone of 70–88 ppbv in Kennewick, Salt Lake City, Denver and Dallas. On these days, wildfire smoke enhanced MDA8 ozone by 5–25 ppbv, through ozone produced remotely during plume transport and locally via interactions of smoke plume with urban emissions.

Abstract

In this study, we analyze the spatiotemporal patterns of propagation of pre-monsoon heatwaves and their drivers in India. Using complex networks, we find that heatwaves originate most frequently in northwest India and propagate in the northeast or southeast direction. Heatwaves propagating in the northeast direction have a higher intensity, lower moving distance, smaller areal coverage, and shorter duration than heatwaves moving in the southeast. We find that the larger area and duration of heatwaves propagating southeast are a result of development of larger and more persistent high-pressure systems extending over entire northern and eastern India, which are influenced by El Niño Southern Oscillation. On the other hand, higher radiative fluxes and larger heat entrainment in the boundary layer in the heatwaves propagating northeast contribute to their higher intensities.

Abstract

Ice sheet feedbacks are underrepresented in model assessments of climate sensitivity and their magnitudes are still poorly constrained. We combine a recently published record of Earth's Energy Imbalance (EEI) with existing reconstructions of temperature, atmospheric composition, and sea level to estimate both the magnitude and timescale of the ice sheet-albedo feedback since the Last Glacial Maximum. This facilitates the first opportunity to quantify this feedback over the most recent deglaciation using a proxy data-driven approach. We find the ice sheet-albedo feedback to be amplifying, increasing the total climate feedback parameter by 42% and reaching an equilibrium magnitude of 0.55 Wm−2K−1, with a 66% confidence interval of 0.45–0.63 Wm−2K−1. The timescale to equilibrium is estimated as 3.6 ka (66% confidence: 1.9–5.5 ka). These results provide new evidence for the timescale and magnitude of the amplifying ice sheet-albedo feedback that will drive anthropogenic warming for millennia to come.

Abstract

Tropical cyclones (TCs), especially intense TCs, pose serious threats to life and property particularly in the affected coastal regions. Understanding the factors determining the TC intensification rate (IR) remains a great challenge. This study identifies the dominant factors responsible for the observed significant increase in TC IR over the western North Pacific in recent decades using the energetically based dynamical system model of TC intensification. It is found that the environmental dynamical efficiency mainly contributed by vertical wind shear and upper-level divergence is responsible for the long-term changes in TC IR during the strong TC stage, but it played a secondary role in the long-term changes in IR during the weak TC stage. The latter were primarily contributed by the maximum potential intensity, which is primarily determined by sea surface temperature. Results also strongly suggest that global warming is the primary driver of the long-term changes in TC IR.

Abstract

Determining the mechanisms responsible for intraplate volcanism - such as slab devolatilization melting versus active mantle plumes - remains a challenge. The greater South China Sea (SCS) region has experienced extensive intraplate Cenozoic volcanism across areas including Hainan, Southeast Indochina, northern Borneo, the northern SCS, and the post-spreading SCS basin. The prevalence of volcanism distributed widely across this region prompts fundamental questions about the key geodynamic processes driving such diverse magmatic activities. In this study, we elucidate the mantle transition zone (MTZ) discontinuities in this region using SS precursors, which helps to overcome the sparse seismic coverage due to its predominantly oceanic setting. We collected over 16,000 high-quality seismograms that sample the upper mantle and MTZ beneath this region from global earthquakes and stations. After correcting for the effects of shallow crustal variations and upper mantle heterogeneity on traveltimes of SS phases and their precursors, we unveil lateral variations in the MTZ boundaries (d410 and d660) and intricate features of the mid-MTZ reflectors (S520S). Significant MTZ thinning and normal S520S waveforms beneath Hainan provide compelling evidence for mantle upwelling through the MTZ. Conversely, the evident splitting of S520S beneath the northern SCS, Southeast Indochina, and northern Borneo, all characterized by stagnant subducted slabs, indicates that the volcanism in these regions likely originated from a mechanism distinct from the active upwelling beneath Hainan. Dehydration melting attributed to devolatilizing stagnant slabs in the MTZ is a potential cause for Cenozoic volcanism in these regions.

Abstract

Utilizing multistatic specular meteor radar (MSMR) observations, this study delves into global aspects of wind perturbations in the mesosphere and lower thermosphere (MLT) from the unprecedented 2022 eruption of the Hunga Tonga-Hunga Ha'apai (HTHH) submarine volcano. The combination of MSMR observations from different viewing angles over South America and Europe, and the decomposition of the horizontal wind in components along and transversal to the HTHH eruption's epicenter direction allow an unambiguous detection and identification of MLT perturbations related to the eruption. The performance of this decomposition is evaluated using Whole Atmosphere Community Climate Model with thermosphere/ionosphere extension (WACCM-X) simulations of the event. The approach shows that indeed the HTHH eruption signals are clearly identified, and other signals can be easily discarded. The winds in this decomposition display dominant Eastward soliton-like perturbations observed as far as 25,000 km from HTHH, and propagating at 242 m/s. A weaker perturbation observed only over Europe propagates faster (but slower than 300 m/s) in the Westward direction. These results suggest that we might be observing the so-called Pekeris mode, also consistent with the L 1 pseudomode, reproduced by WACCM-X simulations at MLT altitudes. They also rule out the previous hypothesis connecting the observations in South America to the Tsunami associated with the eruption because these perturbations are observed over Europe as well. Despite the progress, the L 0 pseudomode in the MLT reproduced by WACCM-X remains elusive to observations.

Abstract

Accurate surface longwave downward radiation (SLDR) is crucial for understanding mountain climate dynamics. While existing algorithms notably improve the accuracy of clear-sky SLDR, a terrain correction algorithm that can correct remotely sensed and model-simulated all-sky SLDR on a large scale remains largely unexplored. Here, we propose a parameterization scheme for estimating all-sky SLDR in rugged terrain. We primarily improve the estimation of nearby terrain thermal contribution by considering topographic asymmetry and incorporate the effects of ice cloud thermal scattering under low water vapor conditions. We validate the reliability of our model using the Discrete Anisotropic Radiative Transfer (DART) model, demonstrating a good agreement with a bias value of −12.8 W/m2 and a RMSE value of 28.2 W/m2. Further evaluation against the Essential Thermal Infrared Remote Sensing (ELITE) SLDR product at three TIPEX-III in situ sites, located near the bottom of deep valleys with predominantly flat surfaces, indicates significant improvement in our model, reducing the mean bias by 7.4 W/m2 and the mean RMSE by 4.1 W/m2. Post-terrain correction, the ELITE SLDR difference map exhibits a spatial pattern of “small in the northwest and large in the southeast” in the study area, with the maximum differences reaching 67 W/m2 in the daytime and 54 W/m2 at nighttime. Comparison with existing methods reveals similar improvements due to the consideration of terrain effects. Overall, our SLDR correction model shows enormous potential for correcting remotely sensed and model-simulated SLDR products on a large scale.

Boundary layer height variations under sunny, rainy, and cloudy weather conditions.

Abstract

The coastal boundary layer height (CBLH/Coastal-BLH) is critical in determining the exchange of heat, momentum, and materials between the land and ocean, thereby regulating the local climate and weather change. However, due to the complexity of geographical characteristics and meteorological conditions, accurate estimation of the CBLH remains challenging. Herein, based on continuous high-resolution measurements of CBL performed from November 2019 to April 2020 in coastal Ningbo city in eastern China, an optimal weighted ensemble model (OWEM) integrating multi-meteorological variables of the ERA5 reanalysis data sets is constructed and validated to estimate the CBLH. The mean absolute percentage error of the derived CBLH by OWEM is as low as 3%–5%, significantly lower than that of 36%–65% of the ERA5 CBLH products. Furthermore, three categories of different weather scenarios, that is, sunny, cloudy, and rainy, are separately discussed, and OWEM shows greater performance and higher accuracies in comparison with the traditional Least Absolute Shrinkage and Selection Operator, Random Forest, Adaboost, LightGBM, and ensemble model, among which, OWEM under fair weather days behave best, with a robust R 2 of 0.97 and a minimum mean absolute error (MAE) of 23 m. Further training results based on wind flow classification, that is, land breeze, sea breeze, and parallel wind, also indicate the outperformance of OWEM than other models, with a relatively large error in parallel wind of 50 m. Subsequent analysis of the Shapley Additive Explanations method strongly correlated with model feature importance, both reveal that thermodynamic factors such as temperature (T2m) and wind velocity (10 m U) are the major factors positively related to estimation accuracy during sunny days. Nevertheless, Relative Humidity dominates on rainy and cloudy days, TP on land breeze days, and dynamic variables like 10 m U and 10 m V on entire types of wind flow weather. In conclusion, the accurate estimation of CBLH from OWEM serves as a feasible and innovative approach, providing technical support for marine meteorology and related engineering applications, for example, onshore wind power, coastal ecological protection, etc.

Abstract

The impacts of falling ice radiative effects (FIREs) on land-atmosphere feedback processes were examined, with a focus on the fidelity of land surface properties and their variability as inferred by global climate models (GCMs). We conducted a pair of sensitivity experiments using the National Center for Atmospheric Research (NCAR) Community Earth System Model Version 1 (CESM1) in fully coupled modes with FIREs turned on and off. This allowed us to investigate the seasonal response of land surface properties to changes in radiation fluxes and land surface temperature (LST) associated with FIREs across global land areas. Our findings indicate that during boreal winter, excluding FIREs results in less surface downward longwave and net flux (∼5–15 Wm−2), leading to a colder land surface (∼2–4 K) and air temperatures (∼1–4 K) at mid- and high latitudes. Consequently, the surface frozen soil layer and snow cover persist through spring, delaying snowmelt and thawing until summer. This delay reduces liquid soil moisture, thereby suppressing vegetation productivity in subsequent seasons. Conversely, tropical regions, exhibit contrasting responses, with a warmer land surface (∼0.5 K) and warmer air temperatures (∼0.1–0.5 K) due to increased surface downward shortwave and net flux (∼2–10 Wm−2). This enhancement in radiation fosters increased vegetation productivity throughout the seasonal cycle. These findings illustrate a local response of land surface properties to changes in the surface energy balance and LST, highlighting the significant role that FIREs play in land surface modeling within GCMs.

Cloud phase estimation and macrophysical properties of low-level clouds using in-situ and radar measurements over the Southern Ocean during the SOCRATES campaign
Anik Das, Baike Xi, Xiaojian Zheng, and Xiquan Dong
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-124,2024
Preprint under review for AMT (discussion: open, 0 comments)
Understanding the cloud phase and macrophysical properties of Southern Ocean clouds is crucial to enhancing our understanding of the region. The cloud radar and in-situ probes during the SOCRATES aircraft campaign are used to develop a new method to determine cloud boundaries and dominant phase. Low clouds (<3km) are found to be the most dominant cloud type (~90%), with liquid being the most dominant phase type, followed by ice and mixed with a greater incidence of drizzle around the cloud base.

Cloud masks and cloud type classification using EarthCARE CPR and ATLID
Hajime Okamoto, Kaori Sato, Tomoaki Nishizawa, Yoshitaka Jin, Shota Ogawa, Hiroshi Ishimoto, Yuichiro Hagihara, EIji Oikawa, Maki Kikuchi, Masaki Satoh, and Wooosub Roh
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-103,2024
Preprint under review for AMT (discussion: open, 0 comments)
The article gives the descriptions of the Japan Aerospace Exploration Agency (JAXA) level 2 (L2) cloud mask and cloud particle type algorithms for CPR and ATLID onboard Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) satellite. The 355nm-multiple scattering polarization lidar was used to develop ATLID algorithm. Evaluations show the agreements for CPR-only, ATLID-only and CPR-ATLID synergy algorithms to be about 80%, 85% and 80%, respectively on average for about two EarthCARE orbits.

Abstract

The East African Rift System (EARS) provides an opportunity to constrain the relationship between magmatism and plate thinning. During continental rifting, magmatism is often considered a derivative of strain accommodation—as the continental plate thins, decompression melting of the upper mantle occurs. The Turkana Depression preserves among the most extensive Cenozoic magmatic record in the rift. This magmatic record, which comprises distinct basaltic pulses followed by periods of relative magmatic quiescence, is perplexing given the lack of evidence for temporal heterogeneity in the thermo-chemical state of the upper mantle, the nonexistence of lithospheric delamination related fast-wave speed anomalies in the upper mantle, and the absence of evidence for sudden, accelerated divergence of Nubia and Somalia. We focus on the Pliocene Gombe Stratoid Series and show how lithospheric thinning may result in pulsed magma generation from a plume-influenced mantle. By solving the 1D advection-diffusion equation using rates of plate thinning broadly equivalent to those measured geodetically today we show that despite elevated mantle potential temperature, melt generation may not occur and thereby result in extended intervals of quiescence. By contrast, an increase in the rate of plate thinning can generate magma volumes that are on the order of that estimated for the parental magma of the Gombe Stratoid Series. The coincidence of large-volume stratiform basalt events within the East African Rift shortly before the development of axial zones of tectonic-magmatic activity suggests that the plate thinning needed to form these stratiform basalts may herald the onset of the localization of strain.

Flood relief logistics planning for coastal cities: a case study in Shanghai, China
Pujun Liang, Jie Yin, Dandan Wang, Yi Lu, Yuhan Yang, Dan Gao, and Jianfeng Mai
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-88,2024
Preprint under review for NHESS (discussion: open, 1 comment)
Addressing coastal city flood risks, this article examines relief logistics planning, employing a GIS-network analysis and optimization model to minimize costs and dissatisfaction. The investigation, grounded in Shanghai's emergency infrastructure and flood relief logistics framework, presents feasible distribution strategies. Meanwhile, the case study indicates that the supply levels of Emergency Flood Shelters and Emergency Reserve Warehouses vary in different coastal flood scenarios.

Abstract

In this study, we use multi-instrument observations (all-sky imager (ASI), global navigation satellite system (GPS) receivers, digisonde) to study the interaction of nighttime medium-scale traveling ionospheric disturbances (MSTIDs) on 13 November 2018. The most attractive aspect of this event is that the interaction appeared between two dark bands both propagated southwestward. The airglow observations show that the latter band moved faster and caught up with the former, and these two bands merged into a new one. The propagating characteristics and morphology of the MSTIDs changed during the interaction process. The simulations from the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) suggested that the ionospheric background zonal winds and electron density distributions could play essential roles in the interaction of the MSTIDs. Moreover, the merging process might be associated with the electrostatic reconnection.

Abstract

Wave particle interactions are very important to understand the intricate evolution of the Earth's radiation belt electrons. Kinetic simulations, in terms of solving the Fokker-Planck equation based on the quasilinear theory, are usually used to simulate the radiation belt electron dynamic evolution. However, the global wave and plasma density distributions adopted in the kinetic simulations are very difficult to be directly obtained by satellites. Here we present a new model, by integrating the machine learning technique and kinetic simulations, to analyze the spatiotemporal evolution of radiation belt electrons scattered by lower band chorus (LBC). Compared to the observations, our integrated model produces effectively the global distribution of plasmapause location, plasma density, and LBC intensity, and assesses quantitatively the scattering effect driven by LBC waves at different magnetic local times (MLT), L-shell (the Mcllwain L-parameter), and time. Incorporating the effect of radiation electron drift, we further use the 2-D Fokker-Planck equation to simulate the variations of electron phase space density in different MLT sectors at a fixed L, and find that the integrated model replicates reasonably the multi-MeV electron acceleration at L = 4.5 during the period from the main phase to the early recovery phase of the storm. Our results demonstrate that such an integrated model, on basis of a combination of the machine learning technique and kinetic simulations, provides valuable means for improved understanding of the global dynamic evolution of the Earth's radiation belt electrons.

Long-term changes in the dependence of NmF2 on solar flux at Juliusruh
Maria Gloria Tan Jun Rios, Claudia Borries, Huixin Liu, and Jens Mielich
Ann. Geophys. Discuss., https//doi.org/10.5194/angeo-2024-11,2024
Preprint under review for ANGEO (discussion: open, 3 comments)
The study analyzes hourly NmF2 data from Juliusruh (1957 to 2023) and examines the response of NmF2 to solar flux by using three different solar EUV proxies for six solar cycles, including a separation of the ascending and descending phases. The response is better represented with a quadratic regression and F30 shows the highest correlation for describing NmF2 dependence over time. These results revealed a steady decrease in NmF2, influenced by the intensity of the solar activity index.

Abstract

Previous simulations have suggested that O+ outflow plays a role in driving the sawtooth oscillations. This study investigates the role of O+ by identifying the differences in ionospheric outflow between sawtooth and non-sawtooth storms using 11 years of FAST/Time of flight Energy Angle Mass Spectrograph (TEAMS) ion composition data from 1996 through 2007 during storms driven by coronal mass ejections. We find that the storm's initial phase shows larger O+ outflow during non-sawtooth storms, and the main and recovery phases revealed differences in the location of ionospheric outflow. On the pre-midnight sector, a larger O+ outflow was observed during the main phase of sawtooth storms, while non-sawtooth storms exhibited stronger O+ outflow during the recovery phase. On the dayside, the peak outflow shifts significantly toward dawn during sawtooth storms. This strong dawnside sector outflow during sawtooth storms warrants consideration.

Abstract

This study reports coordinated observation of ionospheric irregularities from VHF Radar, GPS and IRNSS (Indian Regional Navigation Satellite System), from regions near the northern crest of the EIA (Equatorial Ionization Anomaly), which has not been explored earlier. Efforts have been made to study the signal-in-space environment for concurrent detection of ionospheric irregularities over a range of radio frequency, starting from 53 MHz of the Radar, to L-band of GPS at 1,575.42 MHz and S band signal of IRNSS at 2,492.5 MHz. The radar is operational at Ionosphere Field Station, Haringhata (geographic latitude 22.93°N; geographic longitude 88.51°E; magnetic dip angle 36.2°N) of University of Calcutta. The GPS and IRNSS data are recorded at Calcutta (22.58°N, 88.38°E geographic; magnetic dip: 36°N), separated from Haringhata by 50 km. The spatial as well as temporal variations of irregularities affecting different radio frequencies have been presented. Coordinated observations have been made during period of March–April 2023. Results of the study reveal the common zone of impact of the different radio frequency links spanning from 53 to 2,592.5 MHz and was identified within 16°–25°N, 85°–90°E. During coordinated observations made over several days, irregularity structures have been observed with radar, having backscatter SNR (Signal to Noise ratio) intensity within −5 to 15 dB. During this time, while intense L band scintillation was recorded on multiple satellites of GPS, scintillation recorded at S band signal was moderate to intense.

Abstract

Debris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post-event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric (Q*) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross-section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow-type observations.