A large strike-slip earthquake occurred in the Caribbean Sea on 28 January 2020. We inverted teleseismic P-waveforms from the earthquake to construct a finite-fault model by a new method of inversion that simultaneously resolves the spatiotemporal evolution of fault geometry and slip. The model showed almost unilateral rupture propagation westward from the epicenter along a 300 km section of the Oriente transform fault with two episodes of rupture at speeds exceeding the local shear-wave velocity. Our modeling indicated that the 2020 Caribbean earthquake rupture encountered a bend in the fault system associated with a bathymetric feature near the source region. The geometric complexity of the fault system triggered multiple rupture episodes and a complex rupture evolution. Our analysis of the earthquake revealed complexity of rupture process and fault geometry previously unrecognized for an oceanic transform fault that was thought to be part of a simple linear transform fault system.

China is home to 12% of the world’s grasslands; second largest in the world. The productivity of Chinese grasslands rapidly declined from 10% degraded in 1970 to 90% degraded by the 2000s. Inner Mongolia, China, is composed of 67%, mainly temperate, grasslands. From 1947-2009 human and livestock populations in Inner Mongolia increased from 5.6-24.7 million and 8.4-96.0 million, respectively. These changes were not only due to rising population increasing food demand, but also policy and lifestyle changes. Though climate change and overgrazing are dominant drivers of degradation, research shows that policies increasing privatization of land rights have significant impacts, namely the Household Production Responsibility System (HPRS) of 1949. In China, grassland degradation is linked to environmental problems of sandstorms, losses of biodiversity and carbon sinks, and droughts. Grassland degradation led to widespread public health concerns including dust storms originating from the arid rangelands of Inner Mongolia that swept pollution across major population centers in China and other Asian countries. Inner Mongolia climate change is evident: from 1951-2009 mean temperature increased at 0.28°C per decade, doubling the global linear warming trend of 0.138°C. This temperature increase was accompanied by a 9.9 mm decrease in precipitation per decade, resulting in decreased gross primary productivity measured by Normalized Difference Vegetation Index (NDVI). This study aims to quantify the Balagaer River Watershed degradation in Inner Mongolia, China from 2000-2019 and explore correlations between climate change, NDVI values, and degradation status. Researchers used GIS analysis of MODIS NDVI data and regressions of NDVI on precipitation and potential evapotranspiration (PET). Differences in NDVI were calculated between years and classified degradation into three categories: slightly, moderately, and heavily degraded. These calculations quantified the percentage of the watershed occupied by each category. Correlations between NDVI and precipitation and NDVI and PET were conducted using Excel at three temporal scales: annual, pre-growing season (October to April), and growing season (May to September). It is expected that decreased precipitation contributed to decreased NDVI.

A drought is a slowly developing natural phenomenon that can occur in all climatic zones and can be defined as a temporary but significant decrease in water availability. Over the past three decades, the cost of droughts in Europe has amounted to over 100 billion euros and it is expected to considerably increase as future droughts are projected to be more severe and long-lasting. Although drought monitoring and management are largely studied in the literature, they often fail at yielding precise information on critical events occurrence and associated impacts such as reduction of electricity production or crop failures. This is due to the difficulty of capturing the complexity of drought dynamics, which evolve over diverse temporal (and spatial) scales, including short-term meteorological droughts, medium-term agricultural droughts, and long-term hydrological droughts, as well as the non-physical aspects related to droughts (water management, irrigation, etc.). In this work, we contribute a Machine Learning based framework named FRIDA (FRamework for Index-based Drought Analysis) for the identification of impact-based, site-specific drought indexes. FRIDA is a fully automated data-driven approach that relies on advanced feature extraction algorithms to identify relevant drought drivers from a pool of candidate hydro-meteorological variables. Selected predictors are combined into an index representing a surrogate of the drought conditions in the considered area, including either observed or simulated water deficits or remotely sensed information about the state of the crops. FRIDA is portable across different contexts for supporting the formulation of basin-specific indexes to better inform drought management strategies. Several real-world examples will be used to provide a synthesis of recent applications of FRIDA in case studies featuring diverse hydroclimatic conditions and variable levels of data availability.

Our knowledge of glacial history of the western (Norwegian) part of the Barents Sea has greatly improved during the last decades, notably due to the high-resolution multibeam swath bathymetry data. In contrast, published seafloor data from the eastern part of the Barents Sea and the Kara Sea are much more sparse. This study presents new geophysical/geological evidence for reconstructing glacial dynamics of the eastern part of the Barents-Kara Ice Sheet during the Last Glacial Maximum and subsequent deglaciation. Archival data used in this study include more than 300,000 km of sparker and high-resolution Parasound profiles verified by boreholes drilled with continuous core recovery to 50-100 m below sea bed. This dataset was used to construct continuous geological cross-sections and a series of maps, including detailed bathymetry (in 10-m isobaths) and sediment thickness maps of major seismo-stratigraphic units. Based on the bathymetric and sediment thickness data we map megascale glacial lineations, drumlin-like ridges up to 50 m high and subglacial channels up to 100 m deep, as well as accumulations of glacial deposits (basal, lateral and end moraines) and ice-proximal acoustically transparent bodies (ATBs). Spatial and stratigraphic analysis of these bedforms enables us to put forward a new hypothesis that ice moved on the shelf from the Arctic Ocean along the Saint Anna Trough (SAT). Further south, near the northern tip of the Novaya Zemlya islands, the ice flow split into three major lobes moving to the southwest into the Barents Sea and to the south and southeast into the Kara Sea. Deglaciation in the study area progressed with several ice stillstands and subsequent readvances marked by end-moraines and accumulation of ice-proximal sediments. During deglaciation events, when the SAT became ice free due to iceberg calving, the ice flow reversed its direction toward the SAT, forming a fluting and a massive ATB on the western SAT slope. The exact timing and mechanisms of the ice transgression(s) from the Arctic Ocean are not well understood. Additional high-resolution data such as multibeam bathymetry surveys are needed to verify the spatiotemporal distribution of glaciogenic bedforms, and glaciological modeling is required to comprehend the ice dynamics and put it in the pan-Arctic context.

The structure of the bottom boundary layer (BBL) in aquatic flows influences a range of biophysical processes, including sediment transport, hyporheic exchange, and biofilm formation. While the structure of BBL above bare sediment beds has been well studied, little is known about the complex near-bed flow structure within canopies of aquatic vegetation. In this study, we used high-resolution laboratory measurements and numerical Large Eddy Simulations to investigate the near-bed mean and turbulent flow properties within staggered-ordered emergent canopies under a wide range of flow and canopy conditions. There is strong horizontal variability of key near-bed flow characteristics on the scale of the vegetation elements. Measurement locations that provide single-point flow characteristics closest to the spatially-averaged values were identified. The spatially-averaged BBL thickness is influenced strongly by canopy density. This impact of canopy density is engendered through its direct control of near-bed turbulent kinetic energy (TKE), which in turn is negatively correlated with BBL thickness, both locally in a given flow and across the range of flow conditions studied here. A model based on the near-bed TKE is developed to predict the BBL thickness and, ultimately, the bed shear stress. The strong agreement between model predictions and experimental data may explain why both TKE and bed shear stress may be seen as drivers of sediment transport processes in vegetated flows. These findings provide new insights into the physical links between near-bed flow variables and therefore contribute to the understanding of some of the complex biophysical processes present in vegetated flows

The CF (Climate and Forecast) Conventions are a community-developed metadata standard for storing and describing Earth system science data in the netCDF binary data format. Numerous existing FOSS (Free and Open Source Software) and commercial software tools can explore, analyze, and visualize data that is encoded using the CF Conventions. The CF community holds annual workshops to develop, refine, and review enhancements to the CF Conventions and to manage the CF governance and processes. The EarthCube netCDF-CF project worked with the CF community on the development of extensions to netCDF-CF. Several of these have been accepted into the CF Conventions. Work on these extensions involved broad participation by members of the existing netCDF-CF community as well as members of science domains not traditionally represented in the netCDF-CF community. This presentation will provide an update of recent work and an overview of CF plans and future activities.

The lapse-rate feedback is the dominant driver of stronger warming in the Arctic than the Antarctic in simulations with increased CO2. While Antarctic surface elevation has been implicated in promoting a weaker Antarctic lapse-rate feedback, the mechanisms in which elevation impacts the lapse-rate feedback are still unclear. Here we suggest that weaker Antarctic warming under CO2 forcing stems from shallower, less intense climatological inversions due to limited atmospheric heat transport above the ice sheet elevation and elevation-induced katabatic winds. In slab ocean model experiments with flattened Antarctic topography, stronger climatological inversions support a stronger lapse-rate feedback and annual-mean Antarctic warming comparable to the Arctic under CO2 doubling. Unlike the Arctic, seasonality in warming over flat Antarctica is mainly driven by a negative shortwave cloud feedback which exclusively dampens summer warming, with a smaller contribution from the winter-enhanced lapse-rate feedback.

Basal properties beneath ice streams and glaciers are known to be a control for ice flow dynamics, hence knowledge of them is crucial for predicting sea level due to changes in glacial dynamics. Basal properties, processes and topography also drive the formation of subglacial landforms. Bed properties beneath Rutford Ice Stream (West Antarctica) have previously been described using seismic acoustic impedance measurements at a sparse spatial coverage. Here, we derive bed properties in a 15 x 17 km grid of surface radar data with coverage and sampling much higher than previous seismic studies. Bed reflection amplitudes in surface radar data were calibrated using sediment porosities (ranging from 0.4 – 0.5) derived from seismic acoustic impedance. We find the bed properties are spatially variable, consisting of low porosity material in some areas and soft sediment in other areas. Comparison of seismic and surface radar data imply the low porosity material to be a consolidated sediment or sedimentary rock. Mega-scale glacial lineations (MSGLs) are ubiquitous on the bed and consist of soft, high porosity, probably deforming sediment, consistent with previous interpretations of MSGLs. We find some MSGLs have high reflectivity on their crest, interpreted as water bodies overlying high porosity sediment, whereas the trough around and the upstream end of some landforms consist of low porosity material. Integrating these different observations, we place constraints on possible explanations for the occurrence of water on the crest of landforms.

Here we test the precursory enhancement in ionospheric total electron content (TEC) which has been reported by Heki (2011) and numerous Global Navigation Satellite System (GNSS) TEC observational studies before the 2011 Mw9.0 Tohoku-Oki and many great earthquakes. We verify the frequency of this TEC enhancement via analysis of a two-month vertical TEC (VTEC) time series that includes the Tohoku-Oki Earthquake using the procedure, based on Akaike’s information criterion, and threshold of Heki and Enomoto (2015). The averaged occurrence rate of the TEC enhancement is much larger than that reported by Heki and Enomoto (2015) when all of the visible GPS satellites at a given station are taken into account. We cannot rule out the possibility that the pre-seismic VTEC changes before the great earthquakes that were reported by Heki and Enomoto (2015) are not precursors but just a product of chance. We also analyze the spatial distribution of the pre-seismic TEC enhancement and co-seismic TEC depletion for the Tohoku-Oki Earthquake with the data after reducing inter-trace biases. We observe significant post-seismic depletion that lasted at least 2 h after the earthquake and extended at least 500 km around the center of the large-slip area. This means that evaluation of the enhancements using reference curves which was adopted by Heki 2011 and even by the recent papers (e.g. He and Heki 2016, 2017, 2018) is in danger of mistaking a large and long-lasting post-seismic TEC depletion for a pre-seismic enhancement.

River bathymetry is an important parameter for hydrodynamic modeling; however, it is associated with large bias because direct large-scale measurements are impractical. Recent studies adjusted river bathymetry data based on assessment of the difference between modeled and observed water surface elevation (WSE); however, river discharge model uncertainties can lead to unintended errors in the correction. In this study, we propose a simple but robust correction method using the WSE bias, based on stage–discharge rating curves rather than time series data. The rating curve represents only the characteristics of the river section, and is not sensitive to instantaneous errors. Our results showed that the “corrected river bathymetry” converged among discharge experiments driven by noise-corrupted runoff forcing. Given the difficulty of eliminating discharge errors, a method for correcting river bathymetry that is free from discharge errors is important for improving hydrodynamic modeling.

This work presents 30-year observations of dust chemical composition by the IMPROVE network in the United States. Analysis of 1,253 large dust storms detected at the IMPROVE sites shows that dust PM2.5 (particles less than 2.5 micrometers in fresh dust plumes) crustal materials (64%), organic matter (13%), sulfate (7%), nitrate (2%), Cl, Br, and heavy metals. Dust composition stays relatively stable during near source transport. There are distinct spatial variations in dust composition, including high carbon and sulfate in Oklahoma, high Cl in Washington, and high fractions of heavy metals in Arizona. Compared to the Earth’s crust, dust PM2.5 contains less crustal elements but more OC, EC, sulfate, nitrate, and halogen elements due to influence by human activities and biogeochemical processes. This rich pool of dust composition data provides useful information to study the roles played by dust in the Earth system and its effects on human society.

The Underwater Vision Profiler (UVP) provides abundant in situ data of the marine particle size distribution (PSD) on global scales and has been used for a diversity of applications, but the uncertainty associated with its measurements has not been quantified. Here we use a global compilation of UVP (version 5) observations of the PSD to assess the sampling uncertainty associated with the UVP’s sampling characteristics. We model UVP sampling uncertainty using Bayesian Poisson statistics and provide formulae for the uncertainty associated with a given sampling volume and observed particle count. We also model PSD observations using a power law with an exponential cutoff to better match the low concentration associated with rare large particles as seen by the UVP. We use the two shape parameters from this statistical model to describe changes in the PSD shape across latitude band, season, and depth. The UVP sampling uncertainty propagates into an uncertainty for modeled carbon flux exceeding 50%. The statistical model is used to extend the size interval used in a PSD-derived carbon flux model, revealing a high sensitivity of the PSD-derived flux model to the inclusion of small particles (80-128 microns). We close with recommendations on how to revise the carbon flux model, and we provide avenues to address additional uncertainties associated with UVP-derived carbon flux calculations.

The origin of the Mediterranean Outflow is investigated by deploying six millions virtual Lagrangian parcels at the Strait of Gibraltar, and tracing them backward in time using velocity estimates from an eddy-permitting reanalysis. The Lagrangian parcels are followed until they intercept one of three sections. The hypothesis is that each section is associated with distinct water masses: the Gulf of Lions, related to Western Mediterranean Deep Water and Western Intermediate Water, carries 86\% of the Outflow’s transport; the Northern Tyrrhenian, related to Tyrrhenian Deep and Intermediate Waters, carries 1\% of the transport; the Strait of Sicily, related to Levantine Intermediate Waters, carries 13\% of the transport. The median transit times from the sections to the Strait of Gibraltar range from 5 years (Gulf of Lions) to 8 years (Strait of Sicily).

Using the Global-scale Observations of the Limb and Disk (GOLD) and the Global Ultraviolet Imager (GUVI), we examine the impact of sudden stratospheric warmings (SSWs) on the changes of thermospheric composition during the 2018-2019 and 2020-2021 Arctic SSWs and the 2019 Antarctic SSW. Contributions of planetary waves, gravity waves, and migrating tides are assessed by performing numerical experiments with the NSF National Center for Atmospheric Research (NCAR) vertically extended version of the Whole Atmosphere Community Climate Model (WACCM-X). The wind evolution simulated in WACCM-X aligns well with the quasi-geostrophic wind derived from Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) geopotential height measurements during Arctic and Antarctic SSWs. The variations in column integrated O and N2 density ratio (∑𝑂/N2) are generally similar among WACCM-X, GOLD, and GUVI observations. Following the onset of SSWs, ∑𝑂/N2 is reduced by ~10% over 50°S-50°N and enhanced by ~20% at higher latitudes. The ∑𝑂/N2 changes are associated with the reversals of the mean meridional circulation in the lower thermosphere, mainly driven by westward-travelling planetary waves. The results highlight that planetary wave activity during SSWs can significantly impact the mean state of the thermosphere.

Heliophysics data analysis often involves combining diverse science measurements, many of them captured as time series. Although there are now only a few commonly used data file formats, the diversity in mechanisms for automated access to and aggregation of such data holdings can make analysis that requires inter-comparison of data from multiple data providers difficult. The Heliophysics Application Programmer’s Interface (HAPI) is a recently developed standard for accessing distributed time-series data to increase interoperability. The HAPI specification is based on the common elements of existing data services, and it standardizes the two main parts of a data service: the request interface and the response data structures. The interface is based on the REpresentational State Transfer (REST) or RESTful architecture style, and the HAPI specification defines five required REST endpoints. Data are returned via a streaming format that hides file boundaries; the metadata is detailed enough for the content to be scientifically useful, e.g., plotted with appropriate axes layout, units, and labels. Multiple mature HAPI-related open-source projects offer server-side implementation tools and client-side libraries for reading HAPI data in multiple languages (IDL, Java, MATLAB, and Python). Multiple data providers in the US and Europe have added HAPI access alongside their existing interfaces. Based on this experience, data can be served via HAPI with little or no information loss compared to similar existing web interfaces. Finally, HAPI has been recommended as a COSPAR standard for time series data delivery.

The extent of the fault damage zone remains an outstanding challenge confounding attempts to assess rock mass physical and mechanical properties, the effects on landscape evolution and slope stability, and to delineate safe places for human occupation and infrastructure development. Quantifying the relationship between faulting and the spatial geometrical and mechanical characteristics of a rock mass controlled by faulting is difficult, mainly because of varying lithology and rock mass characteristics, the effects of topography and vegetation and local erosion of weaker rock mass. Recent technological developments including Unmanned Aerial Vehicles, terrestrial laser scanning, photogrammetry and point cloud analysis software tools greatly enhance our ability to investigate the issues using the Yarlung Tsangpo (YLTP) Fault of southern Tibet as a case study where ideal geological conditions exist to investigate the relationship. In this study, the procedures, investigation approaches, evidence and criteria for defining the threshold distance for damage zones of YLTP Fault of southern Tibet were studied quantitatively by combining the spatial variations of fracture density, rock mass strength, rockfall inventory and previous thermal evidence. The results have been compared with published data from the evidence of thermal effects related to the exactly the same fault and show a good match between internal thermal action and rock mass physical and mechanical properties controlled by the same faulting. The extent of threshold distance of damage zone of the YLTP Fault is estimated as 5.9±0.6km. Within the damage zone, fracture density and cohesion of the rock mass show power curve relations with distance from the YLTP Fault. The internal dynamic action of fault controls rock mass physical and mechanical properties in the study area. The fault first affects the characteristics of rock mass structures, and then the orientation of the rock structures influences the stability of slope leading to rockfall.

Many ocean and climate models output ocean variables (like velocity, temperature, oxygen concentration etc.) in depth space. Property transport in the ocean generally follows isopycnals, but isopycnals often move up and down in depth space. A small difference in the vertical location of isopycnals between experiments can cause a large apparent difference in ocean properties when the experiments are compared in depth space. As a result, it is often useful to compare ocean variables in density space. This work compares two algorithms for plotting ocean properties in density coordinates, one written in FORTRAN with a python wrapper (xlayers), and one written in python (xarrayutils). Both algorithms conserve total salt content in the vertical, and both algorithms are easily parallelizable to enable plotting large datasets in density coordinates. We apply these algorithms to plot salinity in density space in some of the CMIP-6 models. In general, areas with net precipitation today experience increasing precipitation in higher greenhouse-gas scenarios, and areas with net evaporation today experience a further reduction in net precipitation in higher greenhouse-gas scenarios. By plotting salinity in density space, we visualize how changes in evaporation and precipitation at the surface propagate along isopycnals to influence salinity concentrations in the ocean interior.

The current approaches have known limitations to understanding the coupling of terrestrial ecosystem evapotranspiration (ET) and photosynthesis (referred to as gross primary productivity, GPP). To better characterize the relationship between ET and GPP, we developed a novel remote sensing (RS)-driven approach (RCEEP) based on the underlying water use efficiency (uWUE). RCEEP partitions transpiration (T) from ET using a RS vegetation index (VI)-derived ratio of T to ET (VI-fT) and then links T and GPP via RS VI-derived Gc (VI-Gc) rather than leaf-to-air vapor pressure difference. RCEEP and other two uWUE versions (VI-T or VI-G), which only incorporate VI-fT or VI-Gc , were evaluated and compared with the original uWUE model in terms of their performances (Nash-Sutcliffe efficiency, NSE) in estimating GPP from ET over 180 flux sites covering 11 biome types over the globe. Results revealed better performances of VI-T and VI-G compared to the original uWUE, implying remarkable contributions of VI-fT and VI-Gc to a more meaningful relationship between ET and GPP. RCEEP yielded the best performances with a reasonable mean NSE value of 0.70 (0.76) on a daily (monthly) scale and across all biome types. Further comparisons of RCEEP and approaches modified from recent studies revealed consistently better performances of RCEEP and thus, positive implications of introducing VI-fT and VI-Gc in bridging ecosystem ET and GPP. These results are promising in view of improving or developing algorithms on coupled estimates of ecosystem ET and GPP and understanding the GPP dynamics concerning ET on a global scale.