The evolution of subduction zones influences the rise and demise of forearc and back-arc basins on the overriding plate. We conducted 2D elasto-visco-plastic numerical models of oceanic subduction and subsequent continental collision which include erosion, sedimentation, and hydration processes. The models show the evolution of wedge-top and retro-forearc basins in the continental overriding plate, separated by a forearc high. These forearc regions are affected by repeated compression and extension phases. Higher subsidence rates are recorded in the syncline structure of the retro-forearc basin when the slab dip angle is higher and the subduction interface is stronger and before the slab reaches the 660 km upper-lower mantle discontinuity. The 3-4 km negative residual topographic signal is produced by the gradually steepening slab, which drags down the overlying upper plate. Extensional back-arc basins are either formed along inherited crustal or lithospheric weak zones at large distance from the arc region or are created above the hydrated mantle wedge originating from arc rifting. Back-arc subsidence is primarily governed by crustal thinning controlled by slab roll-back. Onset of collision and continental subduction is linked to the rapid uplift of the forearc basins; however, the back-arc region records ongoing extension during the initial phase of soft collision. Finally, during subsequent hard collision both the forearc and back-arc basins are ultimately affected by compression. Our modelling results provide insights into the evolution of Mediterranean subduction zones and propose that the Western-Eastern Alboran, Paola-Tyrrhenian, Transylvanian-Pannonian Basins should be considered as genetically connected forearc –back-arc basins, respectively.

The Mars2020 Perseverance Rover landed successfully on the Martian surface on the Jezero Crater floor (18.44°N, 77.45°E) at Martian solar longitude, $L_s$, $\sim$5 in February 2021. Since then it has produced highly valuable environmental measurements with a versatile scientific payload including the MEDA (Mars Environmental Dynamics Analyzer) suite of environmental sensors. One of the MEDA systems is the PS pressure sensor system which weighs 40 grams and has an estimated absolute accuracy of better than 3.5 Pa and a resolution of 0.13 Pa. We present initial results from the first 414 sols of Martian atmospheric surface pressure observations by the PS whose performance was found to meet its specifications. Observed sol-averaged atmospheric pressures follow an anticipated pattern of pressure variation in the course of the advancing season and are consistent with data from other landing missions. The observed diurnal pressure amplitude varies by $\sim$2-5 \% of the sol-averaged pressure, with absolute amplitude 10-35 Pa in an approximately direct relationship with airborne dust. During a regional dust storm, which began at $L_s~135^\circ$ the diurnal pressure amplitude roughly doubles. The diurnal pressure variations were found to be remarkably sensitive to the seasonal evolution of the atmosphere. In particular analysis of the diurnal pressure signature revealed diagnostic information likely related to the regional scale structure of the atmosphere. Comparison of Perseverance pressure observations to data from other landers reveals the global scale seasonal behaviour of Mars’ atmosphere.

Ertel’s potential vorticity theorem is essentially a clever combination of two conservation principles. The result is a conserved scalar q that accurately reflects vorticity values that fluid parcels can possess and acts as a tracer for fluid flow. While true at large horizontal scales in the ocean and atmosphere, at increasingly smaller scales and in sharply curved fronts, its accuracy breaks down. This is because Earth’s rotation imparts angular momentum to fluid parcels and the conservation of absolute angular momentum L restricts the range of centripetal accelerations possible in balanced flow; this correspondingly restricts vorticity. To address this discrepancy, we revisit Ertel’s derivation and obtain a new conserved scalar Lq that more properly reflects the vorticity of fluid parcels at these small horizontal scales. Although limited to flows on the f plane, this theorem nevertheless highlights a fundamental principle applicable to all geophysical fluids: at sufficiently small horizontal scales such that L can appropriately be conserved, centripetal accelerations-or curvature-can modify the vorticity of fluid parcels observed on the sphere.

Laboratory measurements of reflectance spectra of rocks and minerals at multiple viewing geometries are important for interpreting spacecraft data of planetary surfaces. However, efficiently acquiring such measurements is challenging, as it requires a custom goniometer that can accommodate multiple, bulky samples beneath a movable light source and detector. Most spectrogoniometric laboratory work to date has focused on mineral mixtures and particulates, yet it is also critical to characterize natural rock surfaces to understand the influence of texture and alteration. We designed the Three-Axis N-sample Automated Goniometer for Evaluating Reflectance (TANAGER) specifically to rapidly acquire spectra of natural rock surfaces across the full scattering hemisphere. TANAGER has its light source and the spectrometer’s fiber optic mounted on motorized rotating and tilting arcs, with a rotating azimuth stage and six-position sample tray, all of which are fully motorized and integrated with a Malvern PanAnalytical ASD FieldSpec4 Hi-Res reflectance spectrometer. Using well-characterized color calibration targets, we have validated the accuracy and repeatability of TANAGER spectra. We also confirm that the system introduces no discernable noise or artifacts. All design schematics and control software for TANAGER are open-source and available for use and modification by the larger scientific community.

On October 28th 2021 the Sun released a large Coronal Mass Ejection (CME) in Earth’s direction. An X1.0 class solar flare and a rare ground level enhancement (GLE) were observed, along with bright solar radio bursts. Here we examine data from the near-Earth environment to investigate the terrestrial response to this solar event, as a typical example of Sun-Earth interactions. The CME arrival is tracked at $\sim$1 AU from Wind radio observations and the interplanetary magnetic field (IMF) and solar wind dynamic pressure by \textit{in-situ} measurements of OMNI spacecraft. Geomagnetic activity is studied with indices including SYM-H while the auroral response is monitored by remote Wind radio measurements of Auroral Kilometric Radiation (AKR) and SSUSI UV observations. We quantify the timeline for solar wind-magnetosphere coupling via exploration of the dayside reconnection rate and polar cap voltages and address the visibility of AKR sources for a dayside radio observatory.

Malaria poses a great challenge for the maintenance of good public health and sustenance of human wellbeing in many parts of the world. Apparently, the anthropogenic global warming has expanded the spatio-temporal extent of the disease; incidences are now reported beyond tropics and in non-endemic seasons. This emerging trend of climate change has increased the malaria risk factor for millions more across the globe. While global warming remains a key factor to address the future adaptations and mitigation measures, the existing association between climate and malaria prevalence needs careful observations and analyses besides the non-climatic factors. Such a climate association is investigated here with the available malaria case counts in the northeastern districts of South Africa. It is found that the regional variations in seasonal rainfall and temperature, that primarily control mosquito population and thereby infection rates, are linked with a basin-scale climate phenomenon manifested as a dipole pattern in the interannual anomalies of sea surface temperature (SST) of southwestern Indian Ocean. In addition to the year-to-year variations, partly related to the basin warming, a decadal shift in the SST dipole pattern, and associated decrease in seasonal rainfall, leads to decreasing number of case counts in recent years as indicated by the malaria records.

Field-aligned currents (FACs), or the system of currents flowing along Earth’s magnetic field lines, are the dominant form of energy and momentum exchange between the magnetosphere and ionosphere. FACs are ubiquitous across the high-latitude region and have unique characteristics depending on the magnetospheric or solar wind source mechanism, and, therefore, mapping location in the ionosphere (i.e. auroral zone, polar cap, cusp). Further complicating the picture, FACs also exhibit a large range of spatial and temporal scales. In order to create new understanding of FAC spatial and temporal scales, their cross-scale effects, and the impact on the polar region, including on critical technologies, new data analysis approaches are required. This talk addresses a coherent progression of investigation in three parts: 1) an exploration of the characteristics, controlling parameters, and relationships of multiscale FACs using a rigorous, comprehensive analysis across multiple spacecraft observations; 2) augmentation of these statistical results with detailed case studies, fusing observations from diverse platforms and incorporating critical information about the high-latitude electrodynamics across scales; and 3) a quantitative investigation of the impact on Global Navigation Satellite System (GNSS) signals. We find that the relationships between FAC scales are complex and reveal new information about the connection between multiscale FACs and irregular space weather activity. Additionally, there are observable signatures of multiscale FACs and resultant electrodynamic activity in ionospheric data from GNSS signals, suggesting that these signals are affected distinctly according to scale size of the coupling process. Our results indicate that GNSS data may be a powerful source of information about the multiscale near Earth space environment.

Under persistent eutrophication of European water bodies and a changing climate, there is an increasing need to evaluate mitigation measures for reducing nutrient losses from agricultural catchments. In this study, we set up a daily discharge and water quality model in Hydrological Predictions of the Environment for two contrasting agricultural catchments in Sweden to forecast the impacts of future climate trajectories on nutrient loads. The model predicted a slight increase in inorganic nitrogen (IN) and total phosphorus (TP) loads under RCP2.6, likely due to precipitation-driven mobilisation. Under RCP4.5 and RCP8.5, the IN loads were forecasted to decrease from 16%-26% and 21%-50% respectively, most likely due to temperature-driven increases in denitrification and evapotranspiration. No distinct trends in TP loads were observed. A 50% decrease in nutrient loads, as targeted by the European Green Deal, was backcasted using a combination of mitigation scenarios, including i) a 20% reduction in mineral fertiliser, ii) introducing cover crops, and iii) stream mitigation by increasing the size of floodplains and wetlands. Target TP load reductions could only be achieved by stream mitigation, which is likely due to legacy effects and secondary mobilisation within agricultural streams. Target IN load reductions were backcasted with a combination of stream mitigation, fertiliser reduction, and cover crops, wherein the required measures depended on the climate. Overall, the diverging responses of nutrients to climate change and mitigation scenarios indicate that water quality management needs to be tailored to the catchment characteristics, and to the spatial and time specific effects of climate change.

Compound event research has gained significant momentum over the past few years. Traditionally risk assessment studies considered either one climatic driver or process at a time. However, it is now being recognised that it is the combination of multiple drivers and their statistical dependencies that lead to aggravated, non-linear impacts. We aim to identify hotspots for SM-P coupling over India from 2004 to 2020 using Event Coincidence Analysis (ECA) and an extremal tail dependence measure. We further characterise how these complex interconnected interactions can lead to more significant flash floods and landslide risk. The analysis is done at different temporal scales to pinpoint a location prone to floods during the year. High precursor coincidence rates (>60%) were obtained for traditional flash flood-prone areas over India, indicating the robustness of the approach. ECA results were compared with the probabilistic extreme value approach, and a similar pattern was observed in both. The increase in hotspots from 2004 to 2020 matches the observed increase in flood-prone districts reported by earlier studies. We also used the trigger coincidence rate to identify areas where soil moisture anomalies can trigger extreme precipitation. The seasonal variations in precursor coincidence rates are observed to be the same as those usually expected due to changing atmospheric circulation patterns. Our results will complement the traditional flood risk assessment studies and have implications for better understanding the dynamic, ever-evolving nature of compound preconditioned flooding events worldwide.

In 2013, the Office of Science and Technology Policy (OSTP) issued a memorandum directing Federal agencies with over $100 million in annual research and development expenditures to develop a plan to support increased access to federally funded research results. In response, the US Geological Survey developed a Public Access Plan and published four new data management policies. The policies focus on review and approval of scientific data supporting scholarly conclusions, requirements for metadata, preservation, and data management planning. The new policies, in conjunction with the Public Access Plan, represent a shift in culture in how the USGS manages and provides access to its science data. The USGS recognizes that successful implementation of these new policies requires multiple pillars of support, from USGS leadership and staff buy-in, to effective tools. Active community engagement in the Bureau is stimulated through the Community for Data Integration (CDI), an open forum for community discussion and engagement, and an important component creating buy-in and contributing to the success of the new policies. Also critical are a suite of tools available to scientists to ensure their ability to implement the policies. Finally, support from leadership that manifests in the Fundamental Science Practices Advisory Council (FSPAC), a committee of representatives from across the Bureau who preside over policies and guidance is a critical component. While far from complete, the USGS has shifted its approach to science data management by engaging the community, offering tools to support policy, and providing leadership support for the quality and scientific integrity of USGS science data.

The Great Salt Lake (UT) is a hypersaline terminal lake in the US Great Basin, and the remnant of the late glacial-pluvial Lake Bonneville. During the Holocene, hydroclimate variations have been more subtle in the basin. These variations can be investigated by organic geochemical methods within the sediment core GLAD1-GSL00-1B, cored in 2000 and recently well-dated by radiocarbon for the Holocene section (Bowen et al., 2019) with 11 meters representing 8 ka to present. Sediment samples every 30 cm (~200 years) were extracted and the total lipid extracts were analyzed by HPLC-MS to detect the full suite of microbial membrane lipids, including those responsive to temperature and salinity. Modern samples were also collected to provide local calibration for the archaeol-caldarchaeol ecometric (ACE) salinity proxy, where ACE = archaeol/(archaeol + caldarchaeol). ACE detects the increase in lipids of halophilic archaea, relative to generalists, as salinity increases. From currently analyzed data and calibrations, we find Holocene lake salinity estimates ranged from 239 to 283 psu, suggesting persistent hypersalinity with < 50 psu variability across 8 kyr. For comparison, the modern salinity of the lake ranges from 100 to 160 psu in the southern half, and 240 to 270 psu in the north. From ~7-6 ka, salinity estimates were relatively high at 270 to ~280 psu. Following 6 ka, salinity decreases and reaches its lowest value of 239 psu at 4.8 ka. Afterwards, salinity increases and varies between ~250 to ~270 psu, remaining at 270 psu in the last 1 kyr. This new salinity record is compared to available shoreline reconstructions and regional climate records. The temperature proxy, MBT’5Me,­ as calibrated by BayMBT, suggests mean annual air temperature estimates ranged from 12°C to 24°C (compared to modern mean temperature of 13°C). This indicates a substantial, variable complication from salinity in this consistently hypersaline lake, as recently reported for the MBT’5Me­ proxy.

Today with the advancement in remote sensing technology, very high resolution imaging together with the capability of stereo data acquisition has greatly enhanced the disaster management of high hazardous and inaccessible mountainous terrain. The Rishiganga valley in the Chamoli district of Uttarakhand (North India) was impacted by sudden flash floods triggered due to a massive rockslide, caused by wedge failure on 7th February, 2021. This event caused loss of more than 200 lives besides widespread damage to hydropower projects downstream. Due to the high altitude of the terrain, huge flow of mud and debris down the valley and disruption of road connectivity, made the disaster site inaccessible through conventional means. Therefore most of the preliminary and subsequent studies carried out to assess the impact and the causes of the rockslide have heavily relied on the space based observations. The Indian Space Agency (ISRO) activated (Call Id-803) the International Charter “Space and Major Disasters” (ICSMD) to image the area of the disaster in Uttarakhand. The ICSMD is a consortium of space faring members having a constellation (61 as on date) of highly agile, multi-sensor and multi-resolution of satellite resources, which can be tasked based on type of disaster and requirement, very rapidly over the disaster affected areas to collect information on being activated. These satellite datasets are provided freely by the space agencies under ICSMD platform to serve humanitarian response for the disaster affected sites, keeping aside the commercial interests. The present study is carried out with two objectives first highlighting the role of space data in quick satellite based disaster response for this particular event which assisted the Uttarakhand State Disaster Management Agency (USDMA), Govt. of Uttarakhand to take immediate steps to mitigate the problem. The second objective tries to do an assessment and review of major studies published in peer reviewed journal between February and July, 2021 on this disaster globally to have a synthesised understanding of the event. The pre and post multi-temporal and multi-sensor and multi-resolution satellite data from ICSMD over Rishiganga and Dhauliganga valleys provided first-hand information on the chronology of the events, causes and process mechanism of this unique event and identifying locations impacted downstream. The high resolution images were useful in providing in depth understanding of the damage to hydropower projects, changes in the river geomorphology and the river impoundment due to the obstruction in the flow of one of the tributaries of the Rishiganga joining from the northeast. The satellite based inputs proved to be valuable source of information during this event for the state machinery. From all the analysis it has emerged that the satellite images have unequivocally allowed researchers to determine and quantify various terrain parameters (volume, ele

Coupled climate simulations that span several hundred years cannot be run at a high-enough spatial resolution to resolve mesoscale ocean dynamics. These mesoscale dynamics backscatter to macroscales. Recently, several studies have considered Deep Learning to parameterize subgrid forcing within macroscale ocean equations using data from idealized simulations. In this manuscript, we present a stochastic Deep Learning parameterization that is trained on data generated by CM2.6, a high-resolution state-of-the-art coupled climate model with nominal resolution 1/10° . We train a Convolutional Neural Network for the subgrid momentum forcing using macroscale surface velocities from a few selected subdomains. At each location and each time step of the coarse grid, rather than predicting a single number, we predict the mean and standard deviation of a Gaussian probability distribution. This approach requires training our neural network to minimize a negative log-likelihood loss function rather than the Mean Square Error, which has been the standard in applications of Deep Learning to the problem of parameterizations. Each prediction of the mean subgrid forcing can be associated with an uncertainty estimate and can form the basis for a stochastic subgrid parameterization. Offline tests show that our parameterization generalizes well to the global oceans, and a climate with increased CO2 levels, without further training. We test our stochastic parameterization in an idealized shallow water model. The implementation is stable and improves some statistics of the flow. Our work demonstrates the potential of combining Deep Learning tools with a probabilistic approach in parameterizing unresolved ocean dynamics.

Non-polarized electrodes are used to measure the potential differences between two points of ionic conductors. They have been widely used in geoelectric measurements,e.g., magnetotelluric (MT), induced polarization (IP), and spontaneous potential (SP). In practical applications, non-polarized electrodes have the following shortcomings: (1) Regular maintenance is required, and the electrodes must be placed in a special solution after use. (2)The working life is limited due to improper maintenance (3)The electrode is large and generally weighs more than 0.5kg. (4) The electrode temperature coefficient is usually 0.1~1mv/℃ which is required to be buried deep (>1m) for long-term observation. We have developed a maintenance-free solid Pb-PbCl2 non-polarized electrode. The electrode has the following advantages. (1) No maintenance is required, the bottom of the electrode is sealed with a rubber sheath. (2)The potential of electrodes is stable, with a monthly drift of less than 50 μV. (3)The temperature coefficient is 10-20 μV/℃. (4) For 100m electrode distance, the signal-to-noise ratio relative to the natural induced electric field is >20 dB at periods of 10,000 s and 10 dB at periods of 100,000 s, comparing 10 dB and -10 dB for PMS 9000 electrodes, respectively. We developed five types of electrodes for different measurements. The smallest diameter is 2.5cm and 10cm in height, and the weight is 0.1 kg which can be also used in the lab. All types of electrodes are waterproof and can be used for the measurement of the electric field in waters, e.g., lake bottom. The field test shows that our electrode can significantly improve the data quality at dead-band (0.1-10 s) and low-frequency for MT measurement, e.g., one can obtain smooth MT impedance with a period of more than 50,000 s for a month acquisition.

Monsoons emerge over a range of land surface conditions and exhibit varying physical characteristics over the seasonal cycle, from onset to withdrawal. Systematically varying the moisture and albedo parameters over land in an idealized modeling framework allows one to analyze the physics underlying the successive stages of monsoon development. To this end we implement an isolated South American continent with reduced heat capacity but no topography in an idealized moist general circulation model. Irrespective of the local moisture availability, the seasonal cycles of precipitation and circulation over the South American monsoon sector are distinctly monsoonal with the default surface albedo. The dry land case (zero evaporation) is characterized by a shallow overturning circulation with vigorous lower-tropospheric ascent, transporting water vapor from the ocean. By contrast, with bucket hydrology or unlimited land moisture the monsoon features deep moist convection that penetrates the upper troposphere. A series of land albedo perturbation experiments indicates that the monsoon strengthens with the net column energy flux and the near-surface moist static energy with all land moisture conditions. When the land-ocean thermal contrast is strong enough, inertial instability alone is sufficient for producing a shallow but vigorous circulation and converging a large amount of moisture from the ocean even in the absence of land moisture. Once the land is sufficiently moist, convective instability takes hold and the shallow circulation deepens. These results have implications for monsoon onset and intensification, and may elucidate the seasonal variations in how surface warming impacts tropical precipitation over land.

A number of insitu and passive microwave satellite sensors have observed Arctic sea ice and Greenland Ice Sheet (GrIS) mass loss trends over recent decades. Along with sea and land ice declines, above-freezing, near-surface air temperatures are observed earlier in boreal spring and later in autumn thus extending periods of melt beyond the core of summer (JJA). Little is known about whether lengthening periods of open ocean proximate to the ice sheet, for instance, demonstrably effect unseasonal GrIS melt events. Here, a new Baffin Bay sea ice advance dataset is utilized to determine dates of sea ice growth along Greenland’s west coast for the 2011-2015 period. Preceding, multi-scale ocean-atmospheric conditions, including at the Baffin-GrIS interface, are analyzed and linked to unseasonal melt events observed at a series of on-ice automatic weather stations (AWS) along the K-transect in southwest Greenland. The local marine versus synoptic influence on the above and below freezing surface air temperature events is assessed through analyses involving AWS winds, pressure, and humidity observations. These surface observations are further compared against Modele Atmospherique Regional (MAR), Regional Atmospheric Climate Model (RACMO), and ERA-Interim reanalysis fields to understand the airmass origins and (thermo)dynamic drivers of the melt events. Results suggest that the K-transect transition season melt events, primarily in the ablation zone, are strongly affected by ridging atmospheric circulation patterns that transport warm, moist air from lower latitude land-ocean areas toward west Greenland. While local conduction of oceanic surface heat appears to impact coastal air temperatures, consistent with previous studies, marine air incursions from Baffin waters onto the ice sheet are likely obstructed by barrier flows and the pressure gradient-driven katabatic regime off of central Greenland.

The significance of groundwater is likely to grow in the coming years because of the need to mitigate the negative consequences of climate change. Adaptive capacity becomes important as more frequent and intense rainfall variability would quickly increase the possibility of large reduction in the amount of sustainable surface water supplies while aquifers will be affected considerably more slowly by anticipated climate change. On the other hand, the combined effects of population growth, irrigation demand, and climate change will continue to put pressure on the groundwater resource in the future. Against this backdrop, the abstraction-induced recharge (AI-R) concept should be regarded as a future adaptation option for some likely sites in Bangladesh to solve unmet water concerns. The inherent concept of the AI-R is that the sub-surface storage can rapidly be filled during the wet season and consume during the following dry season. Variable thickness in subsurface geology, aquifer system and inconsistent response to monsoon rainfall as well as flooding made Bangladesh incompatible for large basin wide AI-R concept. As a result, this research thoroughly observed the reaction to rainfall events, aquifer condition, historical water level and other factors in two case studies that have the potential to be used in AI-R operations. High-resolution (hourly) in-situ recordings of co-located groundwater level and rainfall data are compared to low-frequency (daily rainfall and weekly groundwater level) observations in this study. Historical groundwater conditions, as well as rapid groundwater response to both diffuse and concentrated recharge, were found to be favorable to AI-R at one place (Bhuapur, Ishwarganj). Nearby ponds which store huge monsoon water and have low aquitard thickness can play potential role in induced recharge in this place. On the other place (Bochaganj, Dinajpur), groundwater response to rainfall is complicated and groundwater level shows decreasing trend in recent years which can get worsen if AI-R concept is implemented here. So, this type of fine resolution field inquiry is at the very least need to be observed on possible AI-R piloting locations. Multi-isotope studies are also advised for assessing long-term effects.

The Monsoon Asia region is home to ten of the world’s biggest rivers, supporting the lives of 1.7 billion people who rely on streamflow for water, energy, and food. Yet, a synthesized understanding of multi-centennial streamflow variability for this region is lacking. To fill this gap, we produce the first large scale streamflow reconstruction over Monsoon Asia (62 stations in 16 countries, 813 years of mean annual flow). In making this reconstruction, we develop a novel, automated, climate-informed, and dynamic reconstruction framework that is skillful over most of the region. We show that streamflow in Monsoon Asia is spatially coherent, owing to common drivers from the Pacific, Indian, and Atlantic Oceans. We also show how these oceanic teleconnections change over space and time. By characterizing past and present hydroclimatic variability, we provide a platform for assessing the impact of future climatic changes and informing water management decisions.