The ILRS completed the reanalysis of the entire period of useful data from geodetic spherical targets spanning 1983 to end of 2020. The combined products were submitted to ITRS for the development of the ITRF2020. The main period that is supported by all four target satellites (LAGEOS, LAGEOS-2 and the two Etalons) was already used in a preliminary release of an ITRF2020 model in May 2021. For the period 1983-1993 with only LAGEOS data the reduction was in of 15-day arcs with 3-day averaged EOP. Due to the lack of a priori estimated mean biases for the 1983-1993 period, we adjusted a 15-day average bias at all stations to accommodate systematic and target signature errors. Otherwise the reanalysis used the same improved modeling of the 1993-2020 data. The adoption of predetermined mean biases ensured the results are minimally affected by systematic errors in the data. The 2021 ILRS contribution to ITRF2020 minimized the scale difference between SLR and VLBI below 2 mm (ITRF2014 ~9 mm). The reanalysis incorporates an improved “target signature” model (CoG) for better separation of true systematic errors from errors in describing the target’s signature. The ILRS Analysis Standing Committee—ASC devoted its efforts on developing the new analysis approach over the past 5 years. The robust estimation of persistent systematic errors at the millimeter level, while still considering information provided by the stations, permitted the adoption of a consistent series of long-term mean corrections for each station for the period 1993-2020, that are now pre-applied. The use of this approach for this reanalysis led to improved results, reflected in the new time series of the TRF origin and especially in its scale. Seven official ILRS Analysis Centers contributed to the weekly time series and six ACs contributed to the 15-day series for 1983-1993, all computed according to the ILRS ASC guidelines. The series were combined by the ILRS Combination Center to obtain the official ILRS product contribution to ITRF2020 spanning a 38-year period. The presentation will provide an overview of the analysis procedures and models, and it will demonstrate the level of improvement with respect to the previous ILRS product series; the stability and consistency of the solution are discussed for the individual AC contributions and the combined SLR time series.

The timing and location of microcracking events, their propagation and coalescence to form macrocracks, and their development by tension, shearing or mixed modes are little known but essential to understanding the fracture of intact rock by freezing and thawing. The aims of the present study are to investigate the mechanisms and transition of micro- and macrocracking during repeated freeze–thaw, and to develop a statistical model of crack propagation that assesses the distance and angular relationship of neighbouring cracking events arranged in their temporal order of occurrence. Eight acoustic emission (AE) sensors mounted on a 300 mm cubic block of chalk captured the three-dimensional locations of microcracking events in their temporal order of occurrence during 16 seasonal freeze‒thaw cycles simulating an active layer above permafrost. AE events occurred mostly during thawing periods (45%) and freeze-to-thaw transitions (37%) rather than during freezing periods (9%) and thaw-to-freeze transitions (8%), suggesting that most AE (microcrack) events were driven by the process of ice segregation rather than volumetric expansion. The outcomes of a novel statistical model of crack propagation based on two boundary conditions—inside–out and outside–in modes of cracking—were assessed based on Bayes’ theorem by testing the hypothesis that the inside–out mode of cracking was favoured by tensional activity, whereas the outside–in mode supported by shearing events. In both situations, the hypothesis accounted for 54–73% confidence level. The microcrack propagation model can distinguish reasonably between cracks formed by volumetric expansion and ice segregation.

Improving the estimation of CO2 exchange between the atmosphere and terrestrial ecosystems is critical to reducing the large uncertainty in the global carbon budget. Large amounts of the atmospheric CO2 assimilated by plants return to the atmosphere by ecosystem respiration (Reco), including plant autotrophic respiration (Ra) and soil microbial heterotrophic respiration (Rh). However, Ra and Rh are challenging to be estimated at large regional scales because of the limited understanding of the complex interactions among physical, chemical, and biological processes and the resulting high spatio-temporal dynamics. Traditional approaches for estimating Reco including process-based (PB) models are limited by human knowledge resulting in limited accuracy and efficiency. Accumulation of the in situ observation of net ecosystem exchange (NEE), weather, and soil, and satellite data of GPP, LAI and soil moisture make it possible for applying data driven machine learning (ML) approaches. But the ML model approach has disadvantages of omission of domain knowledge and lack of interpretability. Here we propose a novel knowledge guided machine learning (KGML) method for predicting daily Ra and Rh in the US crop fields. With Gated Recurrent Unit (GRU) as the basis, we develop the KGML models constructing the hierarchical structure of ML with a mass balance constraint. The KGML models were pre-trained using synthetic data generated by an advanced agroecosystem model, ecosys, and re-trained with real-world FLUXNET observation data. We extrapolate the best KGML model to crop fields over the US with the help of satellite data, reanalysis climate forcings, and soil database to reveal the spatio-temporal variations and key controlling factors. We believe this study advances the interpretable machine learning concept for carbon cycle estimation and will shed light on many other process-based biogeochemistry research.

In this study we investigate the occurrence of primary biological aerosol particles (PBAP) over all sectors of the Southern Ocean (SO) based on a 90-day dataset collected during the Antarctic Circumnavigation Expedition (ACE) in austral summer 2016-2017. Super-micrometer PBAP (1 to 16 µm diameter) were measured by a wide band integrated bioaerosol sensor (WIBS-4). Low (3σ) and high (9σ) fluorescence thresholds are used to obtain statistics on fluorescent and hyper-fluorescent PBAP, respectively. Our focus is on data obtained over the pristine ocean, i.e. more than 200 km away from land. The results indicate that (hyper-)fluorescent PBAP are correlated to atmospheric variables associated with sea spray aerosol (SSA) particles (wind speed, total super-micrometer aerosol number concentration, chloride and sodium concentrations). This suggests that a main source of PBAP over the SO is SSA. The median fraction of fluorescent and hyper-fluorescent PBAP to super-micrometer SSA is 1.6% and 0.13%, respectively. We demonstrate that the fraction of (hyper-)fluorescent PBAP to total super-micrometer particles positively correlates with concentrations of bacteria and several taxa of phytoplankton measured in seawater, indicating that marine biota concentrations modulate the PBAP source flux. We investigate the fluorescent properties of (hyper-)fluorescent PBAP for several events that occurred near land masses. We find that the fluorescence signal characteristics of particles near land is much more variable than over the pristine ocean. We conclude that the source and concentration of fluorescent PBAP over the open ocean is similar across all sectors of the SO.

On steep alluvial fans, debris floods happen rarely but are often catastrophic. Debris floods and their associated hazards are well documented, but the time between flood events has generally been considered a period of ‘dormancy’, and thus ignored. Here, we present results from a series of four alluvial fan experiments in which we examine the inter-flood period processes and their influence at both event and fan evolution timescales. We built each fan from the same number of debris floods, and the same volume of sediment, but varied the duration of the inter-flood period. This duration had a fundamental influence on fan morphology: in particular fan slope and fan area varied between the experiments. In addition, longer inter-flood periods led to increased flow channelization and channel incision near the fan apex. Our findings challenge the notion that inter-flood periods on steep alluvial fans may be considered dormant. Moreover, the results suggest that longer inter-flood periods may act to contain subsequent debris flood events, shift the locus of debris flood hazard, and reduce their severity.

The evolution of mantle composition can be viewed as process of destruction whereby the initial chemical state is overprinted and reworked with time. Analyses of ocean island basalts reveals that some portion of the mantle has survived this process, retaining a chemically ‘primitive’ signature. A question that remains is how this primitive signature has survived four and half billion years of vigorous convection. We hypothesize that some of Earth’s primitive mantle is buried within a slab graveyard at the core-mantle boundary. We explore this possibility using high‐resolution finite element models of mantle convection, in which oceanic lithosphere is produced at zones of plate spreading and subducted at zones of plate convergence. Upon subduction, dense oceanic crust sinks to the base of the mantle and gradually accumulates to form broad and robust thermochemical piles. Sinking oceanic crust entrains the surrounding mantle whose composition is predominantly primitive early in the model’s evolution. As a result, thermochemical piles are initially supplied with relatively high concentrations of primitive material –summing up to ~30% their total mass. The dense oceanic crust that dominates the piles resists efficient mixing and preserves the primitive material that it is intermingled with. The significance of this process is shown to be proportional the rate of mantle processing through time and the excess density of oceanic crust at mantle pressures and temperatures. Unlike existing theories for the survival of Earth’s primitive mantle, this one does not require the early Earth to have anomalously high density or large scale viscosity contrasts.

Significant sediment flux and deposition in a sedimentary system are influenced by climate changes, tectonics, lithology, and the sedimentary system’s internal dynamics. Identifying the timing of depositional periods from stratigraphic records is a first step to critically evaluating the controls of sediment flux and deposition. Here, we show that ages of single-grain K-feldspar luminescence subpopulations may provide information on the timing of previous major depositional periods. We analyzed 754 K-feldspar single-grains from 17 samples from the surface to ~9 m-depth in a trench located downstream of the Mission Creek catchment. Single-grain luminescence subpopulation ages significantly overlap at least eight times since ~12.0 ka indicating a common depositional history. These depositional periods correspond reasonably well with the wetter climate periods based on hydroclimatic proxies from nearby locations. Our findings imply a first-order climatic control on sediment depositional history in southern California on a millennial timescale.

Shock recovery experiments using ALH-78084 H3 and Y-793375 L3 chondrites are conducted in the shock pressure range of 11–43 GPa to reproduce shock-induced melting and chondrule flattening. Shock experiments prove that shock-induced melting occurs beyond 11 GPa at least. The melting occurs at the boundaries between chondrules and matrices. The melts include fine-grained silicate minerals, glasses, and amoeba or spherical metallic Fe-Ni or metallic Fe-Ni­–iron-sulfide with a eutectic texture, which coincides with shock-induced melts in shocked natural chondrites. Shock experiments also prove that shock-induced flattening of chondrules occurs and the flattening degree increases with increasing shock pressure. Taking account of not only the shock experiments of ordinary chondrites but also carbonaceous chondrites, the flattening degree does not depend significantly on the densities, porosities, and chondrule/matrix ratios of chondrites. Considering the shock experiments of the Allende CV3 and Murchison CM2 carbonaceous chondrites along with present shock experiments using H/L3 ordinary chondrites, the aspect ratios of chondrules in unequilibrated chondrites (Rcho) can be expressed as follows: Rcho = 0.011 (±1) × Pressure (GPa) + 1.18 (±3). The long axes of chondrules in shocked ALH-78084 H3 and Y-793375 L3 chondrites have preferred orientations and the degree increases with increasing shock pressure. Natural L/LL3 ordinary chondrites with shock-induced melts have higher aspect ratios and preferred orientations than those without shock-induced melts although it is difficult to determine quantitatively shock pressure using the empirical formula between the aspect ratios of chondrules and shock pressure.

Accurately simulating the interactions between the components of a coupled Earth modelling system (atmosphere, sea-ice, and wave) on a kilometer-scale resolution is a new challenge in operational numerical weather prediction. It is difficult due to the complexity of interactive mechanisms, the limited accuracy of model components and scarcity of observations available for assessing relevant coupled processes. This study presents a newly developed convective-scale atmosphere-wave coupled forecasting system for the European Arctic. The HARMONIE-AROME configuration of the ALADIN-HIRLAM numerical weather prediction system is coupled to the spectral wave model WAVEWATCH III using the OASIS3 model coupling toolkit. We analyze the impact of representing the kilometer-scale atmosphere-wave interactions through coupled and uncoupled forecasts on a model domain with 2.5 km spatial resolution. In order to assess the coupled model’s accuracy and uncertainties we compare 48-hour model forecasts against satellite observational products such as Advanced Scatterometer 10 m wind speed, and altimeter based significant wave height. The fully coupled atmosphere-wave model results closely match both satellite-based wind speed and significant wave height observations as well as surface pressure and wind speed measurements from selected coastal station observation sites. Furthermore, the coupled model contains smaller standard deviation of errors in both 10m wind speed and significant wave height parameters when compared to the uncoupled model forecasts. Atmosphere and wave coupling reduces the short term forecast error variability of 10m wind speed and significant wave height with the greatest benefit occurring for high wind and wave conditions.

Realistic representation of detailed rainfall characteristics on local scale by current state-of-the-art climate models remains a key challenge, especially on sub-daily timescales. In this research, the convection-permitting Weather Research and Forecasting (WRF) model configured with 1.5 km grid spacing is used to simulate precipitation on sub-daily timescales over the Yangtze River Delta Region of China for continuous 10 years (2005–2014). The simulations are compared to rain gauge observations, reanalysis data, and the simulations of a lower resolution WRF with 9 km grid spacing that has a parameterization of convection. The results show that precipitation over the region can be well captured by using the convection-permitting model (CPM). Furthermore, the intensity, duration and coverage of these precipitation events can be more accurately described by the CPM. On the convection timescales of 1–4 hours, especially for heavy rainfall events, the CPM is more accurate than the convection-parameterized model in capturing the short-duration events, which may be related to its better account of physical processes related with the convection on the convection-permitting scale. In addition, the extreme events which are more localized and with short-duration can be represented better by the CPM while the convection-parameterized model tends to produce widespread precipitation events covering more grid cells than observed. Biases of the simulation by the 9-km mesh convection-parameterized mode appear to be related to the deficiencies in the representation of convections.

An energy spectrum of electrons from 180 keV to 550 keV precipitating into the dayside polar ionosphere is observed for the first time by the HEP instrument onboard the RockSat-XN sounding rocket under geomagnetically quiet condition (AE ≤100 nT) at Andøya, Norway. The observed energy spectrum of precipitating electrons follows a power law of -4.86 and the electron flux does not vary much over the observation period (~274.4 seconds). A few minutes before the RockSat-XN observation, POES18 / MEPED observed precipitating electrons, which suggest chorus wave activities at the location close to the rocket trajectory. A ground-based VLF receiver observation at Lovozero, Russia also supports the presence of chorus waves during the rocket observation. A test-particle simulation for wave-particle interactions based on the Arase satellite data shows a similar energy spectrum of precipitating electrons, consistent with the RockSat-XN observation. These results suggest that the precipitation observed by RockSat-XN is likely to be caused by the wave-particle interactions between chorus waves and sub-relativistic electrons.

Over 95% of volcanism on Earth occurs at mid-ocean ridges (MORs) where tectonic plates diverge. How melt is produced depends on the mineral composition and water content. However, it has proven challenging to understand how melting changes when one or more minerals have completely melted. This project examines differences on MOR melting that come with different assumptions in solidus changes with exhaustion of one of the component minerals, clinopyroxene (cpx). To do this, we constructed 2D numerical models of temperature, mantle flow, and melt production at MORs. We ran several models with different amounts of temperature shift in the solidus with loss of cpx. Using zero shift as a baseline, melting starts around 80km depth and peaks at 35km, exhausting cpx, lowering melt output. A second smaller melting region develops more shallowly where there is no cpx. Additional trials in changing the shift in solidus with loss of cpx were done with varying amounts of mantle hydration. For all trials, total melt decreases with larger shifts in solidus. The shallower melting disappears as greater shifts are made. Increasing hydration allows melting to start at deeper depths, but has little effect on the total amount of melt production.

The climatology of atomic oxygen (O) in the MLT (mesosphere and lower thermosphere) is balanced by O production via photodissociation in the lower thermosphere and recombination in the upper mesosphere. The motivation here is to establish the intra-annual variation in the eddy diffusion coefficients and eddy velocity in the MLT based on the constituent climatology of the region. The analysis method, originally developed in the 60’s (Colegrove et al. 1965), was refined for a study of MLT global inter-annual variations in global mean values (Swenson et al. 2018, 2019, respectively) ,(S19). In the this study, the intra-annual cycle was divided into twenty-six (two-week) periods for each of three zones, the northern hemisphere (NH, 15 to 55 degrees ), southern hemisphere (SH, -15 to -55 degrees ), and the equatorial region (EQ, 15 to -15 degrees ). Sixteen years of SABER O density measurements (2002-2018) and MSIS 2.0 model N , O and T profiles (80-96 km) were determined for each of the periods and zones for determination of O eddy diffusion velocities and fluxes. Atomic oxygen diffusive fluxes ([O]*v, 80-96 km) are balanced by the continuity of chemical loss, but the intra-annual variation of k$_{zz}$ (determined from v ) and [O] are determined separately. The major findings include: 1) A dominant AO below 87 km in the NH and SH zones, with the largest variation in amplitude between winter and summer at 83 km. 2) A dominant SAO at all altitudes (80-96 km) in the EQ zone. 3) Intra-annual variability in the global average [O] and k$_{zz}$ contribute to variability of O eddy transport in the MLT.

The application of neural networks (NN) in groundwater (GW) level prediction has been shown promising by previous works. Yet, previous works have relied on a variety of inputs, such as air temperature, pumping rates, precipitation, service population, and others. This work presents a long short-term memory neural network (LSTM-NN) for GW level forecasting using only previously observed GW level data as the input without resorting to any other type of data and information about a groundwater basin. This work applies the LSTM-NN for short-term and long-term GW level forecasting in the Edwards aquifer in Texas. The Adam optimizer is employed for training the LSTM-NN. The performance of the LSTM-NN was compared with that of a simple NN under 36 different scenarios with prediction horizons ranging from one day to three months, and covering several conditions of data availability. This paper’s results demonstrate the superiority of the LSTM-NN over the simple-NN in all scenarios and the success of the LSTM-NN in accurate GW level prediction. The LSTM-NN predicts one lag, up to four lags, and up to 26 lags ahead GW level with an accuracy (R2) of at least 99.89%, 99.00%, and 90.00%, respectively, over a testing period longer than 17 years of the most recent records. The quality of this work’s results demonstrates the capacity of machine learning (ML) in groundwater prediction, and affirms the importance of gathering high-quality, long-term, GW level data for predicting key groundwater characteristics useful in sustainable groundwater management.

The eruption frequency of geysers can be studied easily on the surface. However, details of the internal structure including possible water and gas filled chambers feeding eruptions and the driving mechanisms remain elusive. We recorded eruptions at Strokkur in June 2018 with a multidisciplinary network of seismometers, tiltmeter, video cameras and water pressure sensors to study the eruptive cycle, internal geyser structure and driving mechanisms in detail. An eruptive cycle at Strokkur always consists of 4 phases: the eruption (Phase 1), post-eruptive conduit refilling (Phase 2), gas filling of the bubble trap (Phase 3) and regular bubble migration and implosion at depth in the conduit (Phase 4). For a typical single eruption Phase 1 and 2 persist for 13.1 s. Phase 3 contains a 26.1 s long eruption coda of on average 19 seismic peaks spaced 1.5 s apart generated at 25 to 30 m depth, 13 to 23 m west of the conduit when the bubble trap refills with gas. Phase 4 starts on average 0.9 minutes after the beginning of the eruption and persists for 2.3 min. In this phase on average 8 large bubbles leave the bubble trap and implode at a spacing of 24.5 s at about 7 m depth in the conduit. The duration of the eruption and recharging phase linearly increases with the number of water fountains in close succession (Phase 1), likely due to a larger water, gas and heat loss from the bubble trap and conduit.

Magnetic particles associated with iron (Fe) oxides are widespread on the surface of Earth and Mars and serve as reasonable climatic indicators. Ferrimagnetic maghemite (Mgh) and antiferromagnetic hematite (Hm), which dominate magnetism and redness, often coexist or compete with each other in soils and sediments. The formation efficiency of Mgh relative to Hm could be modulated by geochemical background in addition to climate, especially by phosphate (P), which has a high affinity on the surface of precursor iron oxides in natural systems. We investigated two Ferralsol sequences around a P mining field with comparable climate but contrasting P/Fe ratios. High P/Fe retards iron oxide crystallization as well as grain growth and transformation into Hm, which thereby promotes more effective accumulation of ferrimagnetic Mgh as intermediate products. The ligand-protected effect well interprets asynchronous changes in magnetism and redness in soils and sediments across large spatial and temporal scales.

Geoscientists often spend significant research time identifying, downloading, and refining geospatial data before they can use it for analysis. Exploring interdisciplinary data is even more challenging because it may be difficult to evaluate data quality outside of one’s expertise. QGreenland, a newly funded EarthCube project, is designed to remove these barriers for interdisciplinary Greenland-focused research and analysis via an open data, open platform Greenland GIS tool. QGreenland will combine interdisciplinary data (e.g., glaciology, human health, geopolitics, hydrology, biology, etc.) curated by an international Editorial Board into a unified, all-in-one GIS environment for offline and online use. The package is designed for the open source GIS platform QGIS. QGreenland will include multiple levels of data use: 1) a fully downloadable base package ready for offline use, 2) additional disciplinary and/or high-resolution data extension packages for select download, and 3) online-access-only data to facilitate especially large datasets or updating time series. Software development has begun and we look forward to discussing techniques to create the best open access, reproducible methods for package creation and future sustainability. We also now have a beta version available for experimentation and feedback from interested users and the Editorial Board. The version 1 public release is slated for fall 2020, with two subsequent annual updates. As an interdisciplinary data package, QGreenland is designed to aid collaboration and discovery across fields. Along with discussing QGreenland development, we will also provide an example use case to demonstrate the potential utility of QGreenland for researchers, educators, planners, and communities.

Aircraft observations collected during the Southern Ocean Cloud Radiation Aerosol Transport Experimental Study (SOCRATES) in January-February of 2018 are used to evaluate cloud properties from three satellite-imager datasets: (i) the Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 (collection 6.1) cloud product, (ii) the CERES-MODIS Edition 4 cloud product, and (iii) the NASA SatCORPS Himawari-8 cloud product. Overall the satellite retrievals compare well with the in situ observations, with little bias and modest to good correlation coefficients when considering all aircraft profiles for which there are coincident MODIS observations. The Himawari-8 product does, however, show a statistically significant mean bias of about 1.2 μm for effective radius (re) and 2.6 for optical depth (τ) when applied to a larger set of profiles with coincident Himawari-8 observations. The low overall mean-bias in the re retrievals is due in part to compensating errors between cases that are non- or lightly-precipitating, with cases that have heavier precipitation. re is slightly biased high (by about 0.5 to 1.0 μm) for non- and lightly-precipitating cases and biased low by about 3 to 4 μm for heavily-precipitating cases when precipitation exits near cloud top. The bias in non- and lightly-precipitating conditions is due to (at least in part) having assumed a drop size distribution in the retrieval that is too broad. These biases in the re ultimately propagate into the retrieved liquid water path and number concentration.