An observationally-constrained time series of historical aerosol effective radiative forcing (ERF) from 1750 to 2019 is developed in this paper. We find that the time history of aerosol ERFs diagnosed in CMIP6 models exhibits considerable variation and explore how the time history of aerosol forcing influences the probability distributions of present-day aerosol forcing and emergent metrics such as climate sensitivity. Using a simple energy balance model, trained on CMIP6 climate models and constrained by observed near-surface warming and ocean heat uptake, we derive estimates for the historical aerosol forcing. We find 2005-2014 mean aerosol ERF to be -1.1 (-1.8 to -0.5) W m-2 relative to 1750. Assuming recently published historical emissions from fossil fuel and industrial sectors and biomass burning emissions from SSP2-4.5, aerosol ERF in 2019 is -0.9 (-1.5 to -0.4) W m-2. There is a modest recovery in aerosol forcing (+0.025 W m-2 decade-1) between 1980 and 2014. This analysis also gives a 5-95% range of equilibrium climate sensitivity (ECS) of 1.8-5.1C (best estimate 3.1C) with a transient climate response (TCR) of 1.2-2.6C (best estimate 1.8C).

Seismic noise has been widely used to image Earth's structure in the past decades as a powerful supplement to earthquake signals. Although the seismic noise field contains both surface-wave and body-wave components, most previous studies have focused on surface waves due to their large amplitudes. Here, we use array analyses to identify body-wave noise traveling as PKP waves. We find that by cross-correlating the array-stacked horizontal- and vertical-component data in the time windows containing the PKP noise signals, we extract a phase likely representing PKS-PKP, the differential phase between PKS and PKP. This phase can potentially be used for shear-wave-splitting analysis. Our results also suggest that the sources of body-wave noise are extremely heterogeneous in both space and time, which should be accounted for in future studies

How and when plate tectonics initiated remain uncertain. In part, this is because many signals that have been interpreted as diagnostic of plate tectonics can be alternatively explained via hot stagnant-lid tectonics. One such signal involves early Archean phaneritic ultramafic rocks. In the Eoarchean Isua supracrustal belt of southwestern Greenland, some ultramafic rocks have been interpreted as tectonically-exhumed mantle during Eoarchean subduction. To explore whether all Archean phaneritic ultramafic rocks originated as cumulate and/or komatiite – i.e., without requiring plate tectonics – we examined the petrology and geochemistry of such rocks in the Isua supracrustal belt and the Paleoarchean East Pilbara Terrane of northwestern Australia, with Pilbara ultramafic rocks interpreted as representative of rocks from non-plate tectonic settings. We found that Pilbara ultramafic samples have relict cumulate textures, relative enrichment of whole-rock Os, Ir, and Ru versus Pt and Pd, and spinel with variable TiO2, relatively consistent Cr#, and variable and low Mg#. Similar geochemical characteristics also occur in variably altered Isua ultramafic rocks. We show that Isua and Pilbara ultramafic rocks should have interacted with low Pt and Pd melts generated by sequestration of Pd and Pt into sulphide and/or alloy during magma generation or crystallization. Such melts cannot have interacted with a mantle wedge. Furthermore, altered mantle rocks and altered cumulates could have similar rock textures and whole-rock geochemistry such that they may not distinguish mantle from cumulate. Our findings suggest that depleted mantle interpretations are not consistent with geochemistry and/or rock textures obtained from Isua and Pilbara ultramafic rocks. Instead, cumulate textures of Pilbara samples, whole-rock Pt and Pd concentrations, and spinel geochemistry of Isua and Pilbara ultramafic rocks support cumulate origins and metasomatism involving co-genetic melts that formed in hot stagnant-lid settings. Collectively, these findings permit ≤ 3.2 Ga initiation of plate tectonics on Earth.

Warm and dry fohn winds on the Antarctic Peninsula (AP) cause surface melt that can destabilize vulnerable ice shelves. Topographic funneling of these downslope winds through mountain passes and canyons can produce localized wind-induced melt that is difficult to quantify without direct measurements. Our Fohn Detection Algorithm (FonDA) identifies the surface fohn signature that causes melt using data from twelve Automatic Weather Stations on the AP, used to train a machine learning model to detect fohn in 5km Regional Atmospheric Climate Model 2 (RACMO2.3p2) simulations and in the ERA5 reanalysis model. We estimate the fraction of AP surface melt attributed to fohn and possibly katabatic winds and identify the drivers of melt, temporal variability, and long-term trends and evolution from 1979-2018. We find fohn wind-induced melt accounts for 3.1% of the total melt on the AP but can be as high at 18% close to the mountains where the winds are funneled through mountain canyons. Fohn-induced surface melt does not significantly increase from 1979-2018, despite a warmer atmosphere and more positive Southern Annular Mode. However, a significant increase (+0.1Gt y-1) and subsequent decrease/stabilization occurred in 1979-1998 and 1999-2018, consistent with the AP warming and cooling trends during the same time periods. Fohn occurrence more than fohn strength drives the annual variability in fohn-induced melt. Long-term fohn-induced melt trends and evolution are attributable to seasonal changes in fohn occurrence, with increased occurrence in summer, and decreased occurrence in fall, winter, and early spring over the past 20 years.

We present a near surface air temperature (NSAT) fused data product over the contiguous United States using Level 2 data from the Atmospheric Infrared Sounder (AIRS), on the Aqua satellite, and the Cross-track Infrared Microwave Sounding Suite (CrIMSS), on the Suomi National Polar-orbiting Partnership (SNPP) satellite. We create the fused product using Spatial Statistical Data Fusion (SSDF), a procedure for fusing multiple datasets by modeling spatial dependence in the data, along with ground station data from NOAA’s Integrated Surface Database (ISD) which is used to estimate bias and variance in the input satellite datasets. Our fused NSAT product is produced twice daily and on a 0.25-degree latitude-longitude grid. We provide detailed validation using withheld ISD data and comparison with ERA5-Land reanalysis. The fused gridded product has no missing data; has improved accuracy and precision relative to the input satellite datasets, and comparable accuracy and precision to ERA5-Land; and includes improved uncertainty estimates. Over the domain of our study, the fused product decreases daytime bias magnitude by 1.7 K and 0.5 K, nighttime bias magnitude by 1.5 K and 0.2 K, and overall RMSE by 35% and 15% relative to the AIRS and CrIMSS input datasets, respectively. Our method is computationally fast and generalizable, capable of data fusion from multiple datasets estimating the same quantity. Finally, because our product reduces bias, it produces long-term datasets across multi-instrument remote sensing records with improved bias stationarity, even as individual missions and their data records begin and end.

From 29 June to 1 July, 2015, a phreatic eruption occurred in Owakudani, the largest fumarole area in Hakone volcano, Japan. In this study, an interferometric synthetic aperture radar (InSAR) time series analysis of the Advanced Land Observing Satellite-2 (ALOS-2)/Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) data was performed to measure deformation after the eruption. The results show that the central cones of the volcano have subsided since the eruption and its deflation source is located beneath the previously estimated bell-shaped conductor, which is considered as a sealing layer confining a pressurized hydrothermal reservoir. Therefore, the InSAR results demonstrate the deflation of the hydrothermal system beneath the volcano. One possible cause of this deflation is compaction due to a decrease in pore pressure caused by rupture and fluid migration during and after the eruption.

Spectroscopic measurements at top-of-atmosphere are uniquely capable of attributing changes in Earth’s outgoing infrared radiation field to specific greenhouse gasses. The Atmospheric Infrared Sounder (AIRS) placed in orbit in 2002 has spectroscopically resolved a portion of Earth’s outgoing longwave radiation for 17 years. Concurrently, atmospheric CO₂ rose from 373 to 410 ppm, or 28% of the total increase over pre-industrial levels. The IPCC Fifth Assessment Report predicted 0.508±0.102 Wm⁻² additional radiative forcing from this CO₂ increase. Here it is shown that global measurements under nighttime, cloud-clear conditions reveal 0.358±0.067 Wm⁻² of CO₂-induced radiative forcing, or 70% of IPCC model predictions.

Basal magma oceans develop in Earth and Venus after accretion as their mantles solidify from the middle outwards. Fractional crystallization of the basal mantle is buffered by the core and radiogenic and latent heat in the magma ocean. Previous studies showed that Earth’s basal magma ocean would have solidified after two or three billion years. Venus has a relatively hot interior that cools slowly in the absence of plate tectonics, which reduces heat flow through the solid mantle. Consequentially, the basal magma ocean could remain as thick as ~200-400 km today. Vigorous convection of liquid silicates could power a global magnetic field until recently while a core-hosted dynamo is suppressed. The basal magma ocean may be a hidden reservoir of potassium and other incompatible elements. A high tidal Love number could reveal a basal magma ocean and would definitively establish that the core is at least partially liquid.

Plasma beta is an important parameter characterizing dynamics of various systems such as the solar wind, planetary magnetospheres, and accretion disks. Dependence of some plasma properties such as spectral break, relative proton-electron heating, and intermittency has been studied using observations as well as simulations [1,2,3]. In this study, we use particle-in-cell (PIC) simulations of turbulence to study various, yet unexplored, aspects of this beta variation. We analyze kinetic range electric fields, the variation of scale-to-scale energy transfer, and higher order statistics with respect to plasma beta. Systematic trends in the behavior of various quantities are discussed, and their implications for kinetic plasma dissipation are examined. Finally, we extend this approach to laminar reconnection, which shows turbulence like properties of magnetic spectrum and energy cascade [4,5]. References: Chen, et. al., Geophy. Res. Lett. 41.22 (2014); (https://doi.org/10.1002/2014GL062009) Franci, et. al., ApJ 833 91 (2016); (https://doi.org/10.3847/1538-4357/833/1/91) Parashar, et. al., ApJ Lett. 864 L21 (2018);(https://doi.org/10.3847/2041-8213/aadb8b ) Adhikari, et. al., Phys. of Plasmas 27,042305 (2020); (https://doi.org/10.1063/1.5128376) Adhikari, et. al.(2021); (arXiv:2104.12013)

Trade wind convection organises into a rich spectrum of spatial patterns, often in conjunction with precipitation development. Which role spatial organisation plays for precipitation and vice versa is not well understood. We analyse scenes of trade wind convection scanned by the C-band radar Poldirad during the EUREC4A field campaign to investigate how trade wind precipitation fields are spatially organised, quantified by the cells’ number, mean size and spatial arrangement, and how this matters for precipitation characteristics. We find that the mean rain rate, i.e. the amount of precipitation in a scene, and the intensity of precipitation (mean conditional rain rate) relate differently to the spatial pattern of precipitation. While the amount of precipitation increases with mean cell size or number, as it scales well with the precipitation fraction, the intensity increases predominantly with mean cell size. In dry scenes, the increase of precipitation intensity with mean cell size is stronger than in moist scenes. Dry scenes usually contain fewer cells with a higher degree of clustering than moist scenes. High precipitation intensities hence typically occur in dry scenes with rather large, few and strongly clustered cells, while high precipitation amounts typically occur in moist scenes with rather large, numerous and weakly clustered cells. As cell size influences both the intensity and amount of precipitation, its importance is highlighted. Our analyses suggest that the cells’ spatial arrangement, correlating mainly weakly with precipitation characteristics, is of second order importance for precipitation across all regimes, but could be important for high precipitation intensities and to maintain precipitation amounts in dry environments.

Rockfalls generate seismic signals that can be used to detect and monitor rockfall activity. Event locations can be estimated on the basis of arrival times, amplitudes or polarization of these seismic signals. However, surface topography variations can significantly influence seismic wave propagation and hence compromise results. Here we specifically use the signature of topography on the seismic signal to better constrain the source location. Seismic impulse responses are predicted using Spectral Element based simulation of 3D wave propagation in realistic geological media. Subsequently, rockfalls are located by minimizing the misfit between simulated and observed inter-station energy ratios. The method is tested on rockfalls at Dolomieu crater, Piton de la Fournaise volcano, Reunion Island. Both single boulder impacts and distributed granular flows are successfully located. The complete rockfall trajectories are determined by analyzing the signals in sliding time windows. Results from the highest frequency band (here 13-17\,Hz) yield the best spatial resolution, making it possible to distinguish detachment positions less than 100\,m apart. By taking into account surface topography, both vertical and horizontal signal components can be used. Limitations and the noise robustness of the location method are assessed using synthetic signals. Precise representation of the topography controls the location resolution, which is not significantly affected by the assumed impact direction. Tests on the network geometry reveal best resolution when the seismometers triangulate the source. We conclude that this method can improve the monitoring of rockfall activity in real time once a simulated database for the region of interest is created.

The roof and spire of Notre-Dame cathedral in Paris that caught _re and collapsed on April 15, 2019, were covered with 460 tons of lead (Pb). Government reports documented Pb deposition immediately downwind of the cathedral and a 20-fold increase in airborne Pb concentrations at a distance of 50 km in the aftermath. For this study, we collected 100 samples of surface soil from tree pits, parks, and other sites in all directions within 1 km of the cathedral. Concentrations of Pb measured by X-ray uorescence range from 30 to 9000 mg/kg across the area, with a higher proportion of elevated concentrations to the northwest of the cathedral, in the direction of the wind prevailing during the fire. By integrating these observations with a Gaussian process regression model, we estimate that the average concentration of Pb in surface soil downwind of the cathedral is 430 (95% interval, 300-590) mg/kg, nearly double the average Pb concentration in the other directions of 240 (95% interval, 170-320) mg/kg. The di_erence corresponds to an integrated excess Pb inventory within a 1 km radius of 1.0 (95% interval, 0.5-1.5) tons, about 0.2% of all the Pb covering the roof and spire. This is over 6 times the estimated amount of Pb deposited downwind 1-50 km from the cathedral. To what extent the concentrated fallout within 1 km documented here temporarily exposed the downwind population to Pb is di_cult to con_rm independently because too few soil, dust, and blood samples were collected immediately after the fire.

The eastern margin of Madagascar has a prominent relief change from the flat coastal plain to the low-relief high plateau, characterizing a typical great escarpment topography at a passive margin. A quantification of the spatial distribution of erosion rates is necessary to understand the rate of landscape evolution. We present catchment-averaged erosion rates from detrital cosmogenic 10Be concentrations, systematically covering distinct morphological zones of the escarpment. Erosion rates are differentiated across the escarpment, where the high plateau and the coastal plain are slowly eroding with an average rate of 9.7 m/Ma, and the escarpment basins are eroding faster with an average rate of 16.6 m/Ma. The Alaotra-Ankay Graben related basins have the highest erosion rate with an average rate of 27 m/Ma. The spatial pattern of erosion rates indicates a retreating escarpment landscape. Retreat rates calculated from the 10Be concentrations are from 182 m/Ma to 1886 m/Ma. The rates of escarpment retreat on Madagascar are consistent with a model of a steady retreat from the coastline since the time of rifting, similar to the Western Ghats escarpment on its conjugate margin of the India Peninsula.

Quantitative scanning electron microscopy (SEM) quartz microtextural analysis can reveal the transport histories of modern and ancient sediments. However, because workers identify and count microtextures differently, it is difficult to directly compare quantitative microtextural data analyzed by different workers. As a result, the defining microtextures of certain transport modes and their probabilities of occurrence are not well constrained. We used principal component analysis (PCA) to directly compare modern and ancient aeolian, fluvial, and glacial samples from the literature with 9 new samples from active aeolian and glacial environments. Our results demonstrate that PCA can group microtextural samples by transport mode and differentiate between aeolian and fluvial/glacial transport modes across studies. The PCA ordination indicates that aeolian samples are distinct from fluvial and glacial samples, which are in turn difficult to disambiguate from each other. Ancient and modern sediments are also shown to have quantitatively similar microtextural relationships. Therefore, PCA may be a useful tool to constrain the ambiguous transport histories of some ancient sediment grains. As a case study, we analyzed two samples with ambiguous transport histories from the Cryogenian Bråvika Member (Svalbard). Integrating PCA with field observations, we find evidence that the Bråvika Member facies investigated here includes aeolian deposition and may be analogous to syn-glacial Marinoan aeolian units including the Bakoye Formation in Mali and the Whyalla Sandstone in South Australia.

The Arctic climate changes at a faster rate than the rest of the globe. Boundary-layer clouds may play an important role to this change. At temperatures below 0°C, mixed-phase clouds exist and their phase and longevity is influenced by the abundance of ice crystals, which in turn is a function of aerosols serving as ice nucleating particles (INPs). Previous in-situ studies suggested a local source of INPs due to biological activity over open ocean. Here we investigate ice crystal concentrations in clouds below 2km at a large scale, by exploiting a newly-developed dataset - DARDAR-Nice - retrieved from active satellite remote sensing. The dataset spans from 2006-2016. Contrary to previous expectation, we find that at a given latitude and temperature, there are more ice crystals over sea ice than over open ocean. This enhancement is particularly found in clouds south of 70°N, but also at temperatures between 0 and -10°C.

Santolík, O., Kolmašová, I., Pickett, J. S., & Gurnett, D. A. (2021). Multi-point Observation of Hiss Emerging from Lightning Whistlers. Journal of Geophysical Research: Space Physics, 126, e2021JA029524. https://doi.org/10.1029/2021JA029524

The expected rise in major tropical cyclones due to climate change will increase their associated hazards, including ocean waves which are the main design parameter for maritime structures. To assess how climate change will affect tropical cyclone waves in the Gulf of Mexico we use physics-based synthetic tropical cyclones derived for present and future climates, overcoming the limitations imposed by insufficiently long records and inadequate resolution in General Circulation Models. Using events derived from six Coupled Model Intercomparison Project Phase 5 models, we estimate the probability of extreme waves for the present climate, and global warming under the Representative Concentration Pathway 8.5 scenario. The results show the importance of non-stationary wave climates for planning and design of maritime structures to reduce structure failure probability as we transit into a future climate with an increased probability of extreme waves.

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