Local vortex-structured auroral spiral and a large-scale transpolar arc (TPA) were contemporaneously observed by the Polar ultraviolet imager (UVI), when a substorm almost recovered. The TPA grew along the dawnside auroral oval from the nightside to the dayside (oval-aligned TPA), and a chain of multiple auroral spots and spiral were located azimuthally near the poleward edge of the nightside auroral oval. Contemporaneous appearances of the TPA and the auroral spiral can be seen after the spiral appeared alone. Polar also detected the oval-aligned TPA and another dawnside TPA with the nightside end distorted toward the premidnight sector (J-shaped TPA) before and after the spiral’s formation, respectively. To examine these associated magnetotail structures, we performed global magnetohydrodynamic (MHD) simulations, based on two different types of code, BAT-S-RUS and improved REPPU, and examined how the field-aligned current (FAC) profiles varied in association with changes of the auroral form to TPA and/or auroral spiral. Global MHD simulations with the two different types of code can reproduce the TPAs and the associated FAC structures in the magnetotail. The auroral spiral and its nightside FAC profile, however, were not formed in both simulations, suggesting that its formation process cannot be treated within an MHD framework but is closely related to some kinetic process. When the J-shaped TPA and the auroral spiral contemporaneously appeared, the two MHD simulations could not reproduce the TPA, spiral and their associated magnetotail FAC structures, also advocating that a kinetic effect related to the spiral formation might prevent the TPA occurrence.

A document by Edward Gregory Nerney. Click on the document to view its contents.

A document by Hannah Glover. Click on the document to view its contents.

A document by Wang Mudan. Click on the document to view its contents.

The effect of warming-induced changes in different marine physical, chemical, and biological processes on ocean acidification has been largely overlooked. This study uses an Earth system model to investigate the impacts of warming-induced changes in marine dynamical and thermodynamical processes, CO2 solubility, and biological processes on ocean acidification. Under the representative concentration pathway RCP8.5 and its extension, relative to the simulation without CO2-induced warming effects on the ocean carbon cyle, by year 2500, warming increases global ocean mean [CO32-] by 11.6 μmol kg-1, of which 53% is associated with warming-induced changes in dynamical and thermodynamical processes, 20% is associated with warming-induced changes in CO2 solubility, and 27% is associated with warming-induced changes in ocean biological rates. In the Arc-Atlantic Ocean, mainly due to the greater temperature-induced changes in dynamical and thermodynamical processes, the total warming effect on the ocean carbon cycle acts to increase ocean mean [CO32-] by a considerable 60%, in particular, up to 109% in the depth of ~2500 m, by year 2500. In our simulated results, warming-induced changes in individual biological processes, including phytoplankton growth and mortality rates, and detritus remineralization rate, as well as total biological effects are found to affect ocean acidification by an amount comparable to or greater than that caused by warming-induced changes in dynamical and thermodynamical processes and CO2 solubility. Our study highlights the potentially important role of CO2-induced warming in ocean acidification and the ocean carbon cycle.

Typhoon Saola’s (2023) anti-clockwise loop track was monitored by six spaceborne synthetic aperture radar (SAR) images, offering a unique opportunity to investigate the physical factor known as steering flow, a widely accepted concept for studying tropical cyclone (TC) movement and storm surges. Despite its importance, direct observations of steering flows are limited. To address the complex movements observed during the loop track, we propose a novel method to decompose the SAR-derived high-resolution surface wind field into: 1) symmetric rotational winds, 2) general steering flow across three consecutive SAR cases within ~24 hours, and 3) the remaining steering flow. Our analysis reveals that the newly determined remaining steering flows from north effectively explain the loop track associated with two general steering flows, identified as the western North Pacific summer monsoon (WNPSM) from southeast and Indian summer monsoon (ISM) from southwest.

The Earth surface Mineral dust source InvesTigation (EMIT) is a visible-to- shortwave infrared imaging spectrometer currently aboard the International Space Station. Derivations of fractional cover from spectral unmixing algorithms have provided insights into various ecosystem functions. In the case of EMIT, they will be used by multiple global Earth systems models to constrain the sign of dust-related radiative forcing. This study aims to evaluate the efficacy of different approaches for estimating fractional cover and quantifying the corresponding uncertainty, and serves as a model to encapsulate the true error budget for EMIT. We simulated surface reflectance from a spectral library compiled from various drylands to generate millions of candidate spectra made up of different random fractions of nonphotosynthetic vegetation (NPV), green vegetation (GV), and soil. Simulated spectra were used as-is but we also tested the impact of atmospheric conditions/surface reflectance retrieval by using them to calculate top-of-atmosphere radiance then using the current EMIT surface reflectance retrieval algorithm to estimate apparent surface reflectance. We tested approaches to unmixing these simulated spectra using multiple strategies for dealing with spectrum brightness, within-class spectral variability, and library selection. We also incorporated a Monte Carlo approach to stabilize fractional cover retrievals and quantify uncertainty. The best spectral unmixing approaches produced mean absolute error <0.10 for NPV and soil and <0.06 for GV with uncertainties ≤ ± 0.02 for all classes. We named this innovative approach EndMember Combination Monte Carlo, E(MC) ², unmixing and found that our fractional cover retrievals are insensitive to atmospheric residuals in the surface reflectance data.

In this paper, we investigated the seasonal and geomagnetic dependence of the auroral $E$-region neutral winds and the tidal components between 90–125 km using nearly continuously sampled measurements from the Poker Flat Incoherent Scatter Radar (PFISR) from 2010–2019. The average winds show consistent semidiurnal oscillations between 100–-115 km and diurnal oscillations above 115 km in all seasons with some seasonal and geomagnetic activity dependencies. In general, the semidiurnal oscillation in zonal and meridional directions is strongest in summer and weakest in winter. The diurnal oscillation is strongest in winter and weakest in spring. More details on the seasonal and geomagnetic activity dependencies are revealed in the tidal decomposition results. Tidal decomposition results show eastward mean wind below 115 km in summer, fall, and winter and westward mean wind above 115 km in all seasons. The meridional mean is northward below 115 km and southward above in all seasons. The diurnal amplitudes are small below 110 km and increase with altitude above 110 km in all seasons with larger enhancements in the meridional direction. The semidiurnal amplitudes increase with altitude below 110 km and reach a maximum at around 110 km, then decrease or keep stable (depending on the geomagnetic activity) above 110 km in both directions and all seasons. The diurnal phases shift to earlier times with the increase of geomagnetic activity but show different variations with altitudes in zonal and meridional directions. The semidiurnal phases show a downward progressing trend in both directions and in all seasons.

Bi-spectral retrievals of droplet effective radius and cloud optical depth are widely utilized to estimate aerosol cloud interactions (ACI) in warm clouds in the marine boundary layer. Here, we assess the effect of retrieval errors due to the neglect of 3D radiative transfer during the retrieval process on this analysis of ACI. We use an ensemble of stochastically-modelled cloud fields and 3D radiative transfer simulations to study the retrieval errors at a solar zenith angle of 30. Simulated retrieval biases in droplet number concentration (𝑵𝒅) for all three MODIS channels vary systematically from +35% to -80% as cloud heterogeneity increases. Pixel-level errors can be much larger. Commonly utilized subsampling strategies do not reduce the systematic variation in retrieval error. Negative error correlations between optical depth and droplet effective radius produce spuriously negative slopes between the logarithm of liquid water path and 𝑵𝒅 (-1.0 to -0.3). Pixels at the centre of (8 km)2 patches that are not overcast have a relative bias in 𝑵𝒅 of -50%. The relative frequency of these biased pixels varies linearly with the clear fraction in MODIS data and form the basis for a simple parameterization of 𝑵𝒅 bias that varies with cloud fraction. Using this parameterization, synthetic data experiments indicate that estimates of the first indirect effect in the tropical ocean can be overestimated by up to 30%, and the effect of aerosol on cloud fraction is overestimated by 50%, due to neglecting the correlation between retrieval errors and cloud microphysics.

Clouds are crucial to Earth’s climate system, influencing radiation and contributing to climate projection uncertainties. Here, the simulated cloud fraction by the sixth version of the Canadian Regional Climate Model (CRCM6/GEM5) was evaluated using CALIPSO lidar retrievals and the second version of the Cloud Feedback Intercomparison Project (CFMIP) Observation Simulator Package (COSP2) for the years 2014 and 2015. Horizontal and vertical distributions of clouds in the CRCM6/GEM5 model were evaluated using cloud profiles and four cloud categories (total, high-, mid- and low-level clouds) derived directly from the CRCM6/GEM5 model and treated using the COSP2 satellite simulator. A seasonal analysis was conducted across specific regions in North America. Results showed that the use of COSP2 is essential for comparing CRCM6/GEM5 outputs against satellite data to account for variable definitions and signal attenuation of active instruments (e.g., Cloud-Aerosol Lidar with Orthogonal Polarization: CALIOP). Spatial and vertical cloud distributions and seasonal patterns were generally well represented by the CRCM6/GEM5 for both winter (December-February) and summer (June-August). High- and low-level clouds were particularly well-represented, especially in winter. The CRCM6/GEM5 model demonstrated some difficulty producing enough clouds to accurately represent those at mid-level. Cloud fraction representation was systematically better during winter than summer. The CRCM6/GEM5 generally performed well over the whole North American domain for the four cloud categories and COSP2 was confirmed to help mitigate discrepancies in variable definitions. These results contribute to a better understanding of the CRCM6/GEM5 cloud representations and the use of COSP2 with high-resolution models.

For accurate and timely space weather forecasting, advanced knowledge of the ambient solar wind is required, both for its direct impact on the magnetosphere and for accurately forecasting the propagation of coronal mass ejections to Earth. Data assimilation (DA) combines model output and observations to form an optimum estimation of reality. Initial experiments with assimilation of in situ solar wind observations suggest the potential for significant improvement in the forecast skill of near-Earth solar wind conditions. However, these experiments have assimilated science-quality observations, rather than near-real-time (NRT) data that would be available to an operational forecast scheme. Here, we assimilate both NRT and science observations from the Solar Terrestrial Relations Observatory (STEREO) and near-Earth observations from the Advanced Composition Explorer (ACE) and Deep Space Climate Observatory (DSCOVR) spacecraft. We show that forecasts using NRT data are comparable to those based on science-level data. This suggests that an operational solar wind DA scheme would provide significant forecast improvement, with reduction in the mean absolute error (MAE) of solar wind speed around 45% over forecasts without DA. With a proposed space weather monitor planned for the L5 Lagrange point, we also quantify the solar wind forecast gain expected from L5 observations alongside existing observations from L1. This is achieved using particular configurations of the STEREO and L1 spacecraft. There is a 15.5% improvement for forecast lead times of less than 5 days when observations from L5 are assimilated alongside those from L1, compared to assimilation of L1 observations alone.

Urban environments are increasingly impacted by heavy metals pollution originating from traffic emissions, solid waste burning, and other anthropogenic sources (i.e., foundries, smelters, oil refineries, petrochemical plants, pesticide production, and chemical industries). Suspended particulate matter (SPM) serves as a carrier for heavy metals, posing a potential risk to vegetation and human health. This study aimed to investigate the levels and distribution of heavy metals, including Ag, Cd, Co, Mo, V, As, Cr, Ni, Pb, Cu, Mn, Zn, and Fe, accumulated on the surface and inside the leaves of six plant species (Ficus benghalensis, Ficus religiosa, Polyalthia longifolia, Azadirachta indica, Ficus benjamina, and Bougainvillea glabra) during the pre-and post-monsoon at Okhla Phase-2 and Siri Fort in the Delhi, India. Leaves samples were collected from both sites during the pre- and post- monsoon and analyzed for heavy metals content using Inductively Coupled Plasma Optical Emission spectroscopy (ICP-OES). Results revealed that the pre-monsoon exhibited about 9 % higher levels of heavy metals concentration than post-monsoon, possibly because of washout effects due to rainfall during the monsoon and seasonal variations in atmospheric deposition. Moreover, among all plant species the average of accumulated heavy metals in the both seasons inside the leaves has been observed in the following pattern: F. benjamina (55.51 mg/kg) > B. glabra (43.77 mg/kg) > F.benghalensis (40.55 mg/kg) > A. indica (34.23 mg/kg) > P. longifolia (34.00 mg/kg) > F. religiosa (31.51 mg/kg). The study highlighted F. benjamina and B. glabra as potential bioindicators of heavy metal pollution due to their higher metal’s uptake. The findings of this research contribute to understanding heavy metals pollution in urban areas, emphasizing the importance of monitoring, and mitigating the impact of atmospheric deposition on vegetation. Furthermore, identifying plants with varying metals accumulation capabilities can aid in developing phytoremediation strategies to combat metallic pollutants.Keywords: Heavy metals, Bougainvillea glabra, Atmospheric deposition

To gain a deep understanding of the soil-plant-atmosphere continuum, it is crucial for land surface models to consider plant-related processes. This study focuses on the role of leaf stomatal conductance, which is central to photosynthesis and transpiration. Previous research showed that existing stomatal conductance schemes yield divergent results within a land surface model (LSM), implying a knowledge gap. We further the investigation on the performance of five representative stomatal conductance schemes using a full-fledged LSM, VIC+, and conduct a comparison study over a period of one to two years at two U.S. sites, Blodgett and Duke. Our results reveal substantial differences in modeling outcomes for stomatal conductance, leaf water potential, and leaf CO2 concentration. To gain a better understanding of the divergence among the modeling results, we examine the reasonableness of hourly output variables. Boundaries for unreasonable results are first established using published data for similar conditions, combined with physical reasoning, and judgements thus circumventing limitations of the lack of observational data. Based on them, large portions of the output from these schemes are deemed unreasonable. Treating these schemes as equally plausible or of the same level of credence, we present a new approach in which the stomatal conductance is estimated by simultaneously using multiple plausible expressions derived from two different schemes. This results in the introduction of an additional variable that binds two schemes into a robust one. This new scheme gives a significantly lower percentage of unreasonable variable combinations in its outputs, demonstrating its effectiveness.

The 2022 eruption at Mauna Loa, Hawai‘i, marked the first extrusive activity from the volcano after 38 years of quiescence. The eruption was preceded by several years of seismic unrest in the vicinity of the volcano’s summit. Characterizing the structure and dynamics of seismogenic features within Mauna Loa during this pre-eruptive interval may provide insights into how pre- and co-eruptive processes manifest seismically at the volcano. In particular, the extent to which seismicity may be used to forecast the location and timing of future eruptions is unclear. To address these questions, we construct a catalog of relocated seismicity on Mauna Loa spanning 2011-2023. Our earthquake locations image complex, sub-kilometer-scale seismogenic structures in the caldera and southwest rift zone. We additionally identify a set of streaks of seismicity in the volcano’s northwest flank that are radially oriented about the summit. Using a rate-and-state friction model for earthquake occurrences, we demonstrate that the seismicity rate in this region can be modeled as a function of the stressing history caused by magma accumulation beneath the summit. Finally, we observe a mid-2019 step change in the seismicity rate in the Ka‘oiki region that may have altered the stress state of the northeast rift zone in the three years before the eruption. Our observations provide a framework for interpreting future seismic unrest at Mauna Loa.

The height of stratocumulus clouds (Sc) in the Northeast Atlantic, off the coast of Africa in the Central Macaronesian region, has been examined over the past two decades. We analyzed a dataset of sounding and surface meteorological data from the islands of Madeira and Tenerife to investigate cloud base height (CBH) and cloud top height (CTH) using the lifting condensation level and the height of the trade wind inversion base as proxies. The results of a Mann-Kendall analysis indicate a statistically significant downward trend in the height of the Sc boundaries at both locations. This trend is particularly pronounced towards the northern end of the Central Macaronesian region (Madeira), where the decrease is more than double that the observed at the southern end (Tenerife). The decrease in CTH is consistent with the observed increase in subsidence at the 850 hPa level over the last two decades, which may be related to the observed expansion and intensification of the Azores High (AH). The observed change in the CBH can be attributed to an increase in the moisture content of the air, in line with the observed changes in the regional and local sea surface temperature. However, it cannot be ruled out that changes in the AH, also evidenced by the observed trend in surface pressure at Central Macaronesia, have altered the moisture transport patterns. While the observed changes in the Sc may have significant implications for regional climatic conditions, the most imminent effects are on the height distribution of cloud forests.

A document by Kristian Strommen. Click on the document to view its contents.

Annual North Atlantic tropical cyclone (TC) counts are frequently modeled as a Poisson process with a state-dependent rate. We provide a lower bound on the forecasting error of this class of models. Remarkably we find this bound is already saturated by a simple linear model that explains roughly 50\% of the annual variance using three climate indices: El Ni\ no/Southern Oscillation (ENSO), average sea surface temperature (SST) in the main development region (MDR) of the North Atlantic and the North Atlantic oscillation (NAO) atmospheric circulation index \cite{Kozar2012}. As expected under the bound, increased model complexity does not help: we demonstrate that allowing for quadratic and interaction terms, or using an Elastic Net to forecast TC counts using global SST maps, produces no detectable increase in skill. We provide evidence that observed TC counts are consistent with a Poisson process, limiting possible improvements in TC modeling by relaxing the Poisson assumption.

A document by Xiaochen Zhao. Click on the document to view its contents.