Anthropogenic aerosols are dominant drivers of historical monsoon rainfall change. However, large uncertainties in the radiative forcing associated with anthropogenic aerosol emissions, and the dynamical response to this forcing, lead to uncertainty in the simulated monsoon response. We use historical simulations in which aerosol emissions are scaled by factors from 0.2 to 1.5 to explore the monsoon sensitivity to aerosol forcing uncertainty (−0.3 W m to −1.6 W m). Hemispheric asymmetry in emissions generates a strong relationship between scaling factor and both hemispheric temperature contrast and meridional location of tropical rainfall. Increasing the scaling from 0.2 to 1.5 reduces the global monsoon area by 3% and the global monsoon intensity by 2% over 1950–2014, and changes the dominant influence on the 1950–1980 monsoon rainfall trend from greenhouse gas to aerosol. Regionally, aerosol scaling has a pronounced effect on Northern Hemisphere monsoon rainfall.

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates key assumptions for many of the statistical methods ordinarily used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate, relative, and non-negative parts of a whole and are then characterized as so-called compositional data. This paper introduces the field of compositional data analysis to the biomass burning emissions community and provides examples of statistical treatment of emissions data. Measures and tests of proportionality, unlike ordinary correlation, allow one to coherently investigate associations between parts of the smoke composition. An alternative method based on compositional linear trends was applied to estimate trace gas composition over a range of combustion efficiency which reduced prediction error by 4 percent while avoiding use of modified combustion efficiency as if it were an independent variable. Use of log-ratio balances to create meaningful contrasts between compositional parts definitively stressed differences in smoke emissions from fuel types originating in the southeastern and southwestern U.S. Application of compositional statistical methods as an appropriate approach to account for the relative nature of data about the composition of smoke emissions and the atmosphere is recommended.

We show that in the tropics, tropical atmospheric dynamics force the subcloud moist static energy (MSE) over land and ocean to be very similar in, and only in, regions of deep convection. Using observed rainfall as a proxy for convection and reanalysis data to calculate MSE, we show that subcloud MSE in the non-convective regions may differ substantially between land and ocean but is uniform across latitudes in convective regions even on a daily timescale. This result holds also in CMIP5 model simulations of past cold and future warm climates. Furthermore, the distribution of rainfall amount in subcloud MSE is very similar over land and ocean with the peak at 343 J/g and a half width at half maximum of 3 J/g. As a result, the annual-maximum subcloud MSE at each location over land and ocean is subject to a common upper bound set by the convective regions.

Microplastic (MP) contamination of freshwaters and soils has become one of the major challenges within the Anthropocene. MP is transported in large quantities through river systems from land to sea. However, the question is whether there is transport only or also deposition within the system? Floodplains and their soils as part of the river system are known for their sink function for sediments, nutrients, and pollutants. The present case study analyzes the spatial distribution of large (L-MP, 2,000–1,000 μm) and medium (M-MP, 1,000–500 μm) MP particles in floodplain soils of the Lahn River (Germany). Based on a geospatial sampling concept, the MP contents in floodplain soils are investigated down to a depth of 2 meters through a holistic method approach. The analysis of the plastic particles is carried out by density separation, visual fluorescence identification, and additional ATR-FTIR analysis. In addition, grain size analyses and 210Pb/137Cs dating was performed to reconstruct the MP deposition conditions in floodplains. The results prove a spatial frequent accumulation of MP in upper floodplain soils (0–50 cm) deposited by flood dynamics since the 1960s. MP detection over the entire soil column to a depth of 2 meters and below recent (>1960) sediment accumulation indicates MP relocation and in-situ vertical transfer of mobile MP particles through natural processes (e.g., preferential flow, bioturbation). Furthermore, the role of MP as a potential marker of the Anthropocene is assessed based on the findings. This study advances our understanding of the deposition and relocation of MP at the aquatic-terrestrial interface.

Static distortion of magnetotelluric data is a common effect that can impede the reliable imaging of subsurface structures. Recently we presented an inversion approach that includes a mathematical description of the effect of static distortion as inversion parameters and demonstrated its efficiency with real data. We now systematically investigate the stability of this inversion approach with respect to different inversion strategies, starting models and model parametrizations. We utilize a dataset of 310 magnetotelluric sites that has been acquired for geothermal exploration. In addition, to impedance tensor estimates over a broad frequency range, the dataset also comprises transient electromagnetic measurements to determine near surface conductivity and estimates of distortion at each site. We therefore can compare our inversion approach to these distortion estimates and the resulting inversion models. Our experiments show that inversion with distortion correction produces stable results for various different inversion strategies and for different starting models. Compared to inversion without distortion correction, we can reproduce the observed data better and reduce subsurface artefacts. In contrast, shifting the impedance curves at high frequencies to match the transient electromagnetic measurements reduces the misfit of the starting model, but does not have a strong impact on the final results. Thus our results suggest that including a description of distortion in the inversion is more efficient and should become a standard approach for magnetotelluric inversion.

The observational impacts of satellite data assimilation on extended-range forecasts of sudden stratospheric warmings (SSWs) are investigated by conducting ensemble reforecast experiments. We use two Japanese novel reanalysis products: the Japanese 55-year reanalysis (JRA-55) and its subset that assimilates conventional observations only (JRA-55C). A comparative examination on the reproducibility for SSWs between the two ensemble forecasts reveals that the impact of satellite observations is significant for forecasts starting 5 days before the SSW onset, with 20% less accuracy in the JRA-55C forecasts. Moreover, some of forecasts of vortex-splitting SSWs show a sudden appearance of deep difference, which lasts over a few months in the lower stratosphere and significantly affects the surface climate. These results highlight an important role of mesospheric and upper stratospheric circulations on the onset and development of SSWs.

Satellite data show substantial drops in nitrogen dioxide (NO2) during COVID-19 physical distancing. To attribute NO2 changes to NOx emissions changes over short timescales, one must account for meteorological effects. We find that meteorological patterns were especially favorable for low NO2 in much of the U.S. in spring 2020, complicating comparisons with spring 2019. Meteorological variations between years can cause column NO2 differences of ~15% over monthly timescales. After accounting for sun angle and meteorological considerations, we calculate that NO2 drops ranged between 9.2 – 43.4% among twenty cities in North America, with a median of 21.6%. Of the studied cities, largest NO2 drops (>30%) were in San Jose, Los Angeles, and Toronto, and smallest drops (<12%) were in Miami, Minneapolis, and Dallas. These normalized NO2 changes can be used to highlight locations with greater activity changes and better understand the sources contributing to adverse air quality in each city.

We propose two new methods to calibrate the parameters of the epidemic-type aftershock sequence (ETAS) model based on expectation maximization (EM) while accounting for temporal variation of catalog completeness. The first method allows for model calibration on earthquake catalogs with long history, featuring temporal variation of the magnitude of completeness, mc. This extended calibration technique is beneficial for long-term probabilistic seismic hazard assessment (PSHA), which is often based on a mixture of instrumental and historical catalogs. The second method jointly estimates ETAS parameters and high-frequency detection incompleteness to address the potential biases in parameter calibration due to short-term aftershock incompleteness. For this, we generalize the concept of completeness magnitude and consider a rate- and magnitude-dependent detection probability – embracing incompleteness instead of avoiding it. Using synthetic tests, we show that both methods can accurately invert the parameters of simulated catalogs. We then use them to estimate ETAS parameters for California using the earthquake catalog since 1932. To explore how the newly gained information from the second method affects earthquakes’ predictability, we conduct pseudo-prospective forecasting experiments for California. Our proposed model significantly outperforms the base ETAS model, and we find that the ability to include small earthquakes for simulation of future scenarios is the main driver of the improvement. Our results point towards a preference of earthquakes to trigger similarly sized aftershocks, which has potentially major implications for our understanding of earthquake interaction mechanisms and for the future of seismicity forecasting.

Passive satellite observations play an important role in monitoring global aerosol properties and helping quantify aerosol radiative forcing in the climate system. The quality of aerosol retrievals from the satellite platform relies on well-calibrated radiance measurements from multiple spectral bands, and the availability of appropriate particle optical models. Inaccurate scattering phase function assumptions can introduce large retrieval errors. High-spatial resolution, dual-view observations from the Advanced Baseline Imagers (ABI) on board the two most recent Geostationary Operational Environmental Satellites (GOES), East and West, provide a unique opportunity to better constrain the aerosol phase function. Using dual GOES reflectance measurements for a dust event in the Gulf of Mexico in 2019, we demonstrate how a first-guess phase function can be reconstructed by considering the variations in observed scattering angle throughout the day. Using the reconstructed phase function, aerosol optical depth retrievals from the two satellites are self-consistent and agree well with surface-based optical depth estimates. We evaluate our methodology and reconstructed phase function against independent retrievals made from low-Earth-orbit multi-angle observations for a different dust event in 2020. Our new aerosol optical depth retrievals have a root-mean-square-difference of 0.028 – 0.087. Furthermore, the retrievals between the two geostationary satellites for this case agree within about 0.06±0.073, as compared to larger discrepancies between the operational GOES products, which do not employ the dual-view technique.

Hydrogen (H) and sulfur (S) are light element candidates to enter the core of planetary bodies. Although Fe-S and Fe-H systems have been studied individually, the Fe-S-H ternary system has only been investigated up to 16 GPa and 1723 K. We have investigated the Fe-S-H system at pressures and temperatures (P-T) relevant to the cores of Mars-sized planets (up to 45 GPa and well above the melting temperature of FeS) in the laser-heated diamond anvil cell combined with in situ synchrotron X-ray diffraction. We found that at high P-T, Fe3S is unstable if H exists in the system. Instead, separate Fe–H and Fe–S phases appear at 23–35 GPa. At pressures above 35 GPa, we found a new phase appearing while Fe–S phases disappear and Fe–H phases remain. Our analysis indicates that the new phase likely contains both S and H in the crystal structure (tentatively FeSH). The observed pressure dependent changes in the phase relation may be important for understanding the structure and dynamics of the Martian core and the cores of Mars-sized exoplanets.

In this study, a neural network (NN) emulator for radiation parameterization was developed for the use of an operational weather forecasting model in the Korea Meteorological Administration. The development of the NN emulator was based on large-scale training sets and 96 categories (longwave–shortwave, months, land–ocean, and clear–cloud). As the radiation parameterization was replaced by the NN emulator, a 60-fold speedup for the radiation process was achieved, with a decrease of 87.26% in the total computation time. The accuracy of the NN emulator was strictly evaluated through comparison with the results obtained from the infrequent use of the original radiation scheme with the same computational cost. The mean errors of the NN radiation emulator were significantly reduced by 21–34% compared with the infrequent method. The combination of using the NN radiation emulator and applying it infrequently provided an additional speedup of up to 36-fold, corresponding to 2180 times speedup compared with the control run, without a significant reduction in accuracy. The optimized structure for the radiation emulator designed in this study also showed universal robustness even in the use of limited training sets with incomplete coverage. In conclusion, the NN radiation emulator in this study provides benefits regarding both accuracy and computational cost, making it useful for improving weather forecasting modeling.

This study investigates how wind shear and momentum fluxes in the surface- and boundary layer vary across wind and cloud regimes. We use a nine-year-long data set from the Cabauw tower of the Ruisdael Observatory (NL) complemented by (8.2 x 8.2 km^2) daily LES hindcasts. An automated algorithm classifies observed and simulated days into different cloud regimes: 1) clear-sky days, 2) days with convective clouds (cumulus) rooted in the surface layer, with three ranges of cloud cover, and 3) days with clouds not rooted near the surface. Categorized days in observations and LES do not fully match, with a tendency of the LES to develop convective clouds on clear-sky days and less frequently produce non-rooted clouds, whose scales are far larger than the LES domain. Even so, the climatology and diurnal cycle of winds are for each regime very similar in LES and observations, strengthening our confidence in LES’ skill to reproduce certain clouds for an atmospheric state. Wind shear is smallest in clear-sky and cumulus regimes with limited cloud cover (CLCC), which also have the weakest 200 m wind speed and largest surface buoyancy flux. They have notably larger cross-wind fluxes, although along-wind momentum flux profiles are similar across all regimes. Cloudy days have larger momentum fluxes distributed over deeper layers, sustaining up to 20% of the surface flux value at cloud base. Compared to clear-sky, the CLCC regimes have stronger updrafts and deeper mixed-layers. At similar atmospheric stability, surface friction is larger and underestimated by Monin-Obukhov Similarity Theory.

We discuss improving forecasts of winds in the lower stratosphere using machine learning to post-process the output of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System. We post-process global three-dimensional predictions, and demonstrate distilling the analog ensemble (AnEn) method into a deep neural network which reduces post-processing latency to near zero maintaining increased forecast skill. This approach reduces the error with respect to ECMWF high-resolution deterministic prediction between 2-15% for wind speed and 15-25% for direction, and is on par with ECMWF ensemble (ENS) forecast skill to hour 60. Verifying with Loon data from stratospheric balloons, AnEn has 20% lower error than ENS for wind speed and 15% for wind direction, despite significantly lower real-time computational cost to ENS. Similar performance patterns are reported for probabilistic predictions, with larger improvements of AnEn with respect to ENS. We also demonstrate that AnEn generates a calibrated probabilistic forecast.

Distributed Acoustic Sensing (DAS) was originally intended to measure oscillatory strain at frequencies of 1 Hertz or more on a fiber optic cable. Recently, measurements at much lower frequencies have opened the possibility of using DAS as a dynamic strain sensor in boreholes. A fiber optic cable mechanically coupled to a geologic formation will strain in response to hydraulic stresses in pores and fractures. A DAS interrogator can measure dynamic strain in the borehole which can be related to fluid pressure through the mechanical compliance properties of the formation. Because DAS makes distributed measurements, it is capable of both locating hydraulically active features and quantifying the fluid pressure in the formation. We present field experiments in which a fiber optic cable was mechanically coupled to two crystalline rock boreholes. The formation was stressed hydraulically at another well using alternating injection and pumping. The DAS instrument measured oscillating strain at the location of a fracture zone known to be hydraulically active. Rock displacements of less than one nanometer were measured. Laboratory experiments confirm that displacement is measured correctly. These results suggest that fiber optic cable embedded in geologic formations may be used to map hydraulic connections in three dimensional fracture networks. A great advantage of this approach is that strain, an indirect measure of hydraulic stress, can be measured without beforehand knowledge of flowing fractures that intersect boreholes. The technology has obvious applications in water resources, geothermal energy, CO sequestration, and remediation of groundwater in fractured bedrock.

Bedload movement is fundamentally probabilistic. Our quantitative understanding of gravel transport is particularly limited when flow conditions just exceed thresholds of motion, in part because of difficulties in measuring transport statistics during floods. We used accelerometer-embedded tracer clasts to precisely measure the timing of grain motions and rests during snowmelt floods in Halfmoon Creek, a gravel-bed mountain stream in Colorado, USA. These new data let us explore how probabilities of tracer movement vary with snowmelt discharge. Bedload hysteresis occurred over both daily and seasonal timescales, and included clockwise, counter-clockwise, and figure-eight patterns. We quantitatively explain these observations in terms of how thresholds of motion progressively evolved over 22 days during a seasonal snowmelt flood. Our results suggest that thresholds of motion are functions of both (a) cumulative shear stress and (b) temporal changes in shear stress during floods.

The first demonstration of rocket exhaust driven amplification (REDA) of whistler mode waves occurred on 26 May 2020 by transferring energy from pickup ions in a rocket exhaust plume to EM waves. The source of coherent VLF waves was the Navy NML Transmitter at 25.2 kHz located in LaMoure, North Dakota. The topside ionosphere at 480 km altitude became an amplifying medium with a 60 second firing of the Cygnus BT-4 engine. The rocket engine injected exhaust as a neutral cloud moving perpendicular to field lines that connected the NML transmitter to the VLF Radio Receiver Instrument (RRI) on e-POP/SWARM-E. Charge exchange between the ambient O+ ions and the hypersonic water molecules in the exhaust produced H2O+ ions in a ring-beam velocity distribution. The 25.2 kHz VLF signal from NML was amplified by 30 dB for a period 77 seconds as observed by the RRI. Simultaneously, preexisting coherent ELF waves at 300 Hz were amplified by 50 dB during and after the Cygnus burn. Extremely strong coherent emissions and quasi-periodic bursts in the 300 to 310 Hz frequency range lasted for 200 seconds after the release. The excitation of an ELF whistler cavity may have lasted even longer, but the orbit of the SWARM-E/e-POP moved the RRI sensor away from the wave emission region. The amplified 300 Hz ELF waves may have gained even more energy by cyclotron resonance with radiation belt electrons as they were ducted between geomagnetic-conjugate hemispheres.

Tropical Instability Vortices (TIVs) have a major influence on the physics and biogeochemistry of the equatorial Pacific. Using an eddy-resolving configuration of the Community Earth System Model (CESM-HR) and Lagrangian particle tracking, we examine TIV impacts on the three-dimensional structure and variability of dissolved oxygen (O2) in the upper equatorial Pacific water column. In CESM-HR, the simulated generation and westward propagation of TIVs from boreal summer through winter lead to the seasonal oxygenation of the upper northern equatorial Pacific, exhibited as a deepening of hypoxic depth west of 120ºW. TIV effects on the equatorial Pacific oxygen balance are dominated by eddy-advection and mixing, while indirect TIV effects on O2 consumption play minor roles. These advective effects reflect the transient displacements of isopycnals by eddy pumping as well as vortex transport of oxygen by eddy trapping, stirring, and subduction. TIVs influence on the upper equatorial Pacific O2 distribution and variability has important implications for understanding and modeling marine ecosystem dynamics and habitats, and should be taken into consideration in designing observation networks in this region.

The Atmosphere-Space Interactions Monitor measures Terrestrial Gamma-Ray Flashes (TGFs) simultaneously with optical emissions from associated lightning activity. We analyzed optical measurements at 180-230 nm, 337 nm and 777.4 nm related to 69 TGFs observed between June 2018 and October 2019. All TGFs are associated with optical emissions with 90% at the onset of a large optical pulse, suggesting that they are connected with the initiation of current surges. A simple model of photon delay induced by cloud scattering suggests that the sources of the optical pulses are from 0.7 ms before to 4.4 ms after the TGFs, with a median of -10±80 μs, and 1-5 km below the cloud top. The pulses have rise times comparable to lightning without identified TGFs, while the FWHM is twice as long. Pulse amplitudes at 337 nm are ∼3 times larger than at 777.4 nm. The results support the leader-streamer mechanism for TGF generation.