We have to face an important and urgent problem: even though according to spectral detection, we cannot conclude that there is much water ice on the Moon as the prevailing theory claims. We might have overlooked the widespread presence of methanol on the Moon. After the interstellar methanol ice fell onto the Moon, the methanol in it was retained due to the strong adsorption of methanol in the carbon-rich lunar regolith and the water in it could be divided into two situations: one involved in catalytic reactions with methanol on lunar surface and another one escaped to the deep space because of harsh environment. The rest of methanol might still be widespread on lunar surface. M3 is unable to distinguish between hydroxyl radicals from water ice and hydroxyl groups from methanol because the absorption strengths of the two are all 2.9 μm, and there are no established methods to distinguish them using the 2.9μm band. Thus, most of the lunar water detected by M3 might be lunar methanol. Attention should be paid to previous misreading of the spectrum. The so-called surficial water illogically appeared at lunar equator, seriously shaking the credibility of M3 spectra data analysis. The vast quantities of hydrogen found in lunar polar craters should be hydrogen ice, which easy to confuse with water ice. The author has also made a preliminary study of the physical / chemical process chains on lunar surface. It is necessary to conduct in-depth research in this field in the future.

Extratropical influences on tropical sea surface temperature (SST) have implications for decadal predictability. We implement a cloud-locking technique to highlight the critical role of clouds in shaping tropical SST response to extratropical thermal forcing. With heating imposed over either extratropical Northern Atlantic or Pacific, Hadley Cells respond similarly that the trades strengthen south of the rainband. The wind-evaporation-SST (WES) feedback leads to cooling over the southern subtropics, which is enhanced in the southeastern Pacific due to the positive feedback between SST and stratiform clouds. This cooling is further extended toward the central Pacific via a WES effect associated with zonally contrasting cloud-radiative-SST feedbacks in the tropics, which is observed in both slab-ocean and dynamical-ocean experiments. We propose that the meridional and zonal SST gradients are tightly linked via WES effects and the cloud-radiative-SST feedbacks, which are largely determined by the climatological rainband position and the spatial distribution of cloud properties.

Structure of the quasi-2-day wave (Q2DW) in the mesosphere and lower thermosphere (MLT) was compared between the northern and southern hemispheres, employing temperature and geopotential height data obtained from the Microwave Limb Sounder (MLS) onboard NASA’s Earth Observing System (EOS) Aura satellite. The Q2DW in horizontal winds was derived using balance equations with MLS geopotential height data. Amplitudes were maximized at ~40° in summer with larger amplitudes in the meridional wind than the zonal wind in both hemispheres, but with much larger amplitudes in the southern hemisphere and a longer duration of enhancements in the northern hemisphere. Weaker enhancements were exhibited in winter in both hemispheres, but maximized at higher latitudes only in the southern hemisphere meridional component. Responses were moderately enhanced from late April to early May only in the southern hemisphere. The westward propagating zonal wavenumber 3 (W3) was largest in summer in both hemispheres, but the Q2DW comprised superposition with other modes in winter. Eliassen-Palm fluxes were derived for each mode. In the southern hemisphere, W3, W2, and W1 in January exhibited upward fluxes at lower latitudes, poleward fluxes at lower altitudes and equatorward fluxes at higher altitudes. A W3 mode in July in the northern hemisphere, on the other hand, exhibited upward and poleward fluxes in the entire altitude range. The Q2DW balance winds were compared with the radar winds. They agreed reasonably in amplitude and phase in summer in the southern hemisphere and lower latitudes in summer in the northern hemisphere and in winter hemispheres.

Soil organic matter (SOM), the accumulated, decaying debris of biota living on or in the soil, represents the largest of the active terrestrial C pools, holding about 1500 Pg C to a depth of 1 m. In aquatic ecosystems, SOM is a storehouse of inorganic nutrients which, after mineralization, are released to the stream and used by planktonic and benthic microorganisms. Here we present the results of a study designed to elucidate the controls on the spatial and temporal variations of the SOM distribution along the Clear Fork River, which drains a mixed urban-agricultural landscape in north-central Ohio. Fluvial bed sediments were sampled monthly (March to October) in eight stations along the river. Organic matter (OM) and carbonate content were determined by loss-on-ignition (LOI). Sediments from all stations were analyzed in triplicate to account for intrasample variation and to provide a measure of precision. Textural analysis was also performed in all samples. Results show OM content varying between 14 and 109 g kg-1, with highest values observed during spring, and lower values during summer. Sediments from stations where the stream flow is high generally presented lower OM concentration. In addition, stations located within urban landscapes presented the highest OM concentrations.

The elevation of the mountain rain-snow transition is critical for short-term hazard forecasting and longer-term water supply considerations. Despite the transition’s importance, direct in-situ observations are rare. Here we present two new methods that utilize “anomalous” snow observations to detect rainfall during rain-on-snow: (1) a mass fluctuation at snow pillow sites, and (2) inflated remotely sensed snow grain sizes. Using auxiliary data, we show snow pillows respond to rain-on-snow with distinct perturbations that appear as pulses, collapses and declines within the snow water equivalent. We use these responses to identify mountain-scale rain-snow transitions across California’s Sierra Nevada. We also show how a threshold approach (>200 mm) for remotely sensed snow grain size can identify rain-on-snow as snow grain sizes artificially inflate due to a liquid water film. While the methods are not predictive, if paired retroactively with hydrometeorological models, these new methods have the potential to improve predictive streamflow capabilities.

Sustainable concepts of ecologically functional rivers challenge engineers, researchers, and planners. Advanced numerical modeling techniques produce nowadays high-precision terrain maps and spatially explicit hydrodynamic data that aid river design. Because of their complexity, however, ecomorphological processes can only be reproduced to a limited extent in numerical models. Intelligent post-processing of hydrodynamic numerical model results still enables ecological river engineering measures to be designed sustainably. We have embedded state-of-the-art concepts in novel algorithms to effectively plan self-maintaining habitat-enhancing design features, such as vegetation plantings or the artificial introduction of streamwood, with high physical stability. The algorithms apply a previously developed lifespan mapping technique and habitat suitability analysis to terraforming and bioengineering river design features. The results not only include analytical synopses, but also provide actively created, automatically generated project plans, which are optimized as a function of an efficiency metric that describes “costs per m² net gain in seasonal habitat area for target species”. To make the benefits of these novel algorithms available to a wide audience, we have implemented the codes in an open-source program called River Architect. In this contribution, we present the novel design concepts and algorithms as well as a case study of their application to a river restoration project on the Yuba River in California (USA). With River Architect, we ultimately created an objective, parameter-based, and automated framework for the design of vegetative river engineering features. In addition, we are able to define a framework for stable and ecologically viable terraforming features, but part of the planning of earthworks is still left to expert assessment. Thus, improving the algorithms to plan terraforming of permanent, self-sustaining, and eco-morphodynamic riverbed structures based on site-specific parameters is one of the future challenges.

Earth observation (EO) offers a promising and necessary approach to addressing environmental issues and sustainable development from the city to the global scale. The full potential is currently untapped, as global harmonization is necessary for comparability and scalability, as well as streamlining EO integration into informed and efficient decision-making. Focusing specifically on city needs, local and national authorities regulate urban air pollution, while the UN SDG 11 indicator 11.6.2 explicitly targets air pollution accounting for population in “cities” and aggregating to the national level. EO brings forth novel monitoring methods to achieve this alongside more traditional ones. However, how a city is spatially defined is an ongoing area of research and policy activity where the definitions differ, which can greatly impact the estimation of exposure to air pollution. To address the varying definitions and move toward a harmonized global approach, the H2020 SMURBS/ERA-PLANET project has created a workflow and tool that adopts two well established definitions of cities to assess population-weighted particulate matter (PM) pollution for approximately 800 European cities. The workflow utilizes the Copernicus Atmospheric Monitoring Service (CAMS – regional ensemble reanalysis) data for PM2.5, an open and free European-wide source of air pollution data, overlaid with two European Commission acknowledged city boundary definitions: the Functional Urban Area and the JRC’s Degree of Urbanisation Urban Centre. These two approaches yield different results allowing stakeholders to comprehend the city boundary sensitivity. Statistical analysis on the results will highlight cases throughout Europe to showcase how important and potentially policy relevant the differences can be based on a city’s definition, especially if there is a divergence when aggregated to the national level. The GKH will disseminate the knowledge-based workflow and give prominence to the its global relevance, providing a much needed resource for developing countries and giving decision-makers an EO-based consistent tool to help meet societal challenges that are intertwined with urban growth.

Both shallow and deep groundwater flow mediates a variety of geologic processes. In the discharge zones of the nested groundwater flow systems, saltwater often emerges due to high evaporation (in endorheic drainage basin), tide surge, or marine transgression and regression (in coastal areas) or salt pollution (in streams). However, to our best knowledge there are limited studies that consider the impact of density flow in the discharge zone on the nested groundwater flow systems. In this study, nested groundwater flow systems are analyzed with saltwater infiltration in their discharge zones. To quantify the effects of saltwater concentration on the flow systems, seven scenarios with different saltwater concentrations in the discharge zones are modeled. It is found that the flow systems are most sensitive to the saltwater concentration of the discharge zones when the concentration is between 2.23 and 4 g/L, and the threshold saltwater concentration that starts to affect the flow systems is about 1.35 to 2.23 g/L for the specific aquifer configuration selected for this study. The results also show that the local flow systems retreat upward and the overall groundwater velocity of the entire flow systems is decreased with the increase of the saltwater concentration. This study may shed light on the control of salinization, evolution of saline lake basins, and seawater intrusion from a perspective of nested groundwater flow systems.

Based on direct measurement by the MMS spacecraft in the years of 2017 and 2018, we perform studies on the vorticity field () within the reconnection jet in the plasma sheet. A typical event on 26 July 2017 shows clearly the evolution of the field with the jet velocity: is weak in the decelerated BBF and strong in the fast BBF. The strongest -field is in the decaying BBF, around the dipolarization fronts. Despite the evolution of the BBF, the -field is characterized by the perpendicular vorticity (ω). Statistical results confirm the close correlation between BBF and . Higher means stronger . This accounts for the dawn-dusk asymmetry of the -field. The anisotropic is more significant in the V-dominating BBF than in the V-dominating BBF. The -field within the reconnection jet is β-dependence. The β-dependence -field tends to be stronger in super-M jet than in sub-M jet.

We present a new metric for braiding intensity to characterize multi-thread systems (e.g., braided and anastomosing rivers) called the Entropic Braiding Index, eBI. This metric is a generalization of the widely used Braiding Index (BI) which is simply the average count of intercepted channels per cross-section. The co-existence of diverse channels (widely different widths and discharges) within river cross-sections distorts the information conveyed by BI, since its value does not reflect the diversity and natural variability of the system. Moreover, the fact that BI is extremely sensitive to resolution (BI increases at higher resolution as smaller scale channels can be resolved) challenges its applicability. eBI, addresses these main drawbacks of BI. eBI is rooted in the concept of Shannon Entropy, and its value can be intuitively interpreted as the equivalent number of equally important (in terms of discharge) channels per cross-section. Thus, if the channels observed in a multi-thread system are all carrying the same amount of discharge, eBI has the same value of BI. On the other hand, if a very dominant channel in terms of discharge co-exists with much smaller channels, eBI would take a value slightly larger than 1 (note that the actual value would depend on the number of small channels and their relative size with respect to the dominant channel). We present a comparative study of BI and eBI for different multi-thread rivers obtained from numerical simulations and remote-sensing data and for different discharge stages. We also provide evidence of the robustness of eBI in contrast to BI when a given river system is studied under different resolutions. Finally, we explore the potential of eBI as a metric to characterize different types of multi-thread systems and their stability.

The precise location of the seismic source of Great Lisbon Earthquake is still uncertain. The aim of this work is to use the an onland sedimentary record in southern Portugal to test and validate seismic sources of the AD 1755 earthquake. To achieve this, tsunami deposit thicknesses from over 150 cores retrieved from Salgados (Portugal) were compared to the results of a tsunami sediment transport model (Delft3D-FLOW) which simulates tsunami propagation, inundation, erosion, and deposition. Seven different hypothetical seismic sources and varying bed roughness coefficients were used to determine which modeled sources better reproduce observed patterns of tsunami deposit thicknesses and also dune erosion at the studied site in southern Portugal. Modeled and observed historical tsunami arrival times were also used to test different earthquake sources. Based on these comparisons, four modeled earthquake sources were unable to reproduce the observed physical data, suggesting they should be disregarded as likely sources of the AD 1755 earthquake.

Deep-sea polymetallic sulfides formed by hydrothermal activity are considered a potential resource for economically valuable base and precious metals. The Southwest Indian Ridge (SWIR, Indian Ocean) hosts active and inactive hydrothermal systems. Inactive hydrothermal fields are more abundant but difficult to characterize. We report a self-potential investigation to locate inactive ore deposits at the Yuhuang hydrothermal field on the ultraslow-spreading SWIR. A horizontal array of 6 AgCl electrodes were attached to a dual towed transient electromagnetic system to record the electrical field at a height of 40 m above the seafloor. The observed electrical field strength near the known sulfide drills reaches 0.5 mV/m. Negative self-potential anomalies (~ -25 mV, obtained by integrating the electrical field) were observed. High electrical conductivities (up to 12 S/m) of sulfide samples measured in the laboratory and the oxidize sulfides recovered at the outcrop of the deposit suggest that the self-potential anomalies are due to sulfides mineralization and corrosion of the polymetallic sulfides. Tomography of the self-potential anomalies reveals a localized current source distribution with a thickness of ~65 m. Our field data demonstrate that the self-potential method is a useful exploration method to characterize seafloor sulfides localized in inactive hydrothermal fields at mid-ocean ridges.

Groundwater depletion in Central Wisconsin, due in part to agricultural high-capacity wells, has sparked an interest in precision irrigation to reduce groundwater pumping without a significant reduction in yield. A key challenge for bridging precision irrigation research and application is how best to monitor water stress in real-time. Aerial and satellite imagery are potential solutions. Drawbacks of these methods include cost, spatiotemporal resolution, and cloud interference, especially in humid regions. Recent advancements in remotely piloted aircrafts (RPAs) have made frequent, low-flying imagery collection more economical and feasible than ever before. We partnered with the Wisconsin Potato and Vegetable Grower Association to generate high-resolution maps of crop water stress using remotely sensed thermal and multi-spectral RPA imagery. Data were collected at a commercially irrigated potato field in the Central Sands region of Wisconsin from June to August 2019. Missions were flown weekly using a quadcopter RPA system instrumented with a newly released, combined multispectral/thermal camera developed for agricultural applications. Each mission included flights at 30, 60, and 90 m above ground level to assess tradeoffs between resolution, area, and flight time. We used biophysical data from an eddy covariance system installed within the flight domain to validate crop water stress maps generated from the remotely sensed RPA data. Ground measurements of surface temperature and soil moisture were collected throughout the domain within fifteen minutes of each mission. Ongoing results will be used to develop best practices for integrating RPAs into precision irrigation programs.

Long-term post-seismic gravity change (PGC) of the 2004 Sumatra-Andaman earthquake (Mw9.1-9.3) detected by GRACE + GRACE-FO is modeled sufficiently by an exponential function until the 2012 Indian-Ocean earthquake (Mw8.8) but gravity increasing became constant after that. An interpretation is PGC of the 2004 earthquake was almost completed in 2012 and that of the 2012 earthquake proceeded constantly. Assuming this, I calculate their spatial distributions. PGC of the 2012 earthquake was expanded along the faults of the 2004 earthquake and the peaks of PCGs of the two earthquakes appeared at a same location. This suggests another interpretation, namely, PGC of the 2004 earthquake has another long-term component expected by Burgers rheology and PGC of the 2012 earthquake is slight. Spatial distributions of PGC on this assumption support this interpretation. This is the first result showing Burgers rheology is appropriate to consider the viscosity of upper mantle based only on satellite gravimetry.

The Wang-Sheeley-Arge (WSA) model estimates the solar wind speed and interplanetary magnetic field polarity at any point in the inner heliosphere using global photospheric magnetic field maps as input. WSA employs the Potential Field Source Surface (PFSS) and Schatten Current Sheet (SCS) models to determine the Sun’s global coronal magnetic field configuration. The PFSS and SCS models are connected through two radial parameters, the source surface and interface radii, which specify the overlap region between the inner SCS and outer PFSS model. Though both radii are adjustable within the WSA model, they have typically been fixed to 2.5 R sol. Our work highlights how the solar wind predictions improve when the radii are allowed to vary over time. Data assimilation using particle filtering (sequential Monte Carlo) is used to infer the optimal values over a fixed time window. The Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model generates an ensemble of photospheric maps that are used to drive WSA. When the solar wind model predictions and satellite observations are used in a newly-developed quality-of- agreement metric, sets of metric values are generated. These metric values are assumed to roughly correspond to the probability of the two key model radii. The highest metric value implies the optimal radii. Data assimilation entails additional choices relating to input realization and timeframe, with implications for variation in the solar wind over time. We present this work in its theoretical context and with practical applications for prediction accuracy.

NASA’s 2021 STV Incubation Study Report lists vertical (horizontal, geolocation) accuracy as an associated SATM product parameter for all (most) identified Science and Application Knowledge Gaps. The presented generalized Polynomial Chaos Expansion (gPCE) based method has wide ranging applicability to improve positioning, geolocation uncertainty estimates for all STV disciplines, but is presented for the bathymetric lidar use case, due to added complexity introduced by wave structure, roughness, and entry angle. Most LiDARs, though precise, are vulnerable to position, pointing errors as deviations from the expected principal axis lead to projection errors on target. While fidelity of location/pointing solutions can be high, determination of uncertainty remains relatively basic. Currently, the standard approach is the calculation of the Total Propagated Uncertainty (TPU), which is often plagued by simplifying approximations and ignored covariances. Additionally, uncertainty sources are often exclusively modeled as Gaussian, inaccurately capturing some variable distributions. Prominently, wave behavior is better described by Gamma distributions (which are supported under gPCE). This research addresses specific knowledge gaps in bathy-LiDAR measurement uncertainty through a more complete description of total aggregated uncertainties, from system level to geolocation, by applying a gPCE uncertainty quantification approach. gPCE intrinsically accounts for covariance between variables to determine the uncertainty in a measurement, without manually constructing a covariance matrix, through a surrogate model of system response. Determining point-wise positioning uncertainty using gPCE is less computationally expensive than Monte Carlo methods and more tractable for most dimensionalities of interest (roughly from 3 to 20+). The method also does not rely on simplifying assumptions used in typical TPU methods. Additionally, a key attribute of this approach is that global sensitivity analysis (GSA), after obtaining gPCE coefficients, is trivial and nearly costless to compute. Furthermore, GSA of system configurations/uncertainty is a powerful tool to design and develop LiDAR systems with the measurement requirements integrated into the design solution.

We will present signal processing techniques based on shape analysis of the time-frequency signatures of chorus elements in the Van Allen Radiation Belts. Specifically, we will employ the Radon transform and the Distance Transform, which are well-known for isolating local shapes and patterns in the image processing literature, to achieve automated detection of the spectral morphology of chorus elements. In particular, we will introduce “shrink-wrapping” techniques that quantify the salient features defining the microstructure of chorus elements. We will present preliminary results based on case studies of the EMFISIS data from the Van Allen Radiation Belts mission.

The Unified Access Framework (UAF) project of the NOAA Global Earth Observation - Integrated Data Environment (GEO-IDE) in an on-going effort to provide access to NOAA-wide data in a way that is FAIR and meets PARR requirements. The first priority of UAF is to copy success. We recognize: data that follows the Climate and Forecast netCDF convention is readily used by working scientists; THREDDS Data Servers and ERDDAP servers are a popular ways to serve such data; these servers can be interrogated by software to determine that the data follows the conventions and the servers can be federated. To make the collection we construct a master “raw” catalog of candidate data set from THREDDS servers around NOAA and other organizations. The raw catalog is examined by custom software to eliminate large data collections which are not aggregated in time and organize the results into a “clean” catalog. The catalog is then examined by ERDDAP to provide ERDDAP GridDAP access and to verify that the data sources follow the CF convention. The gridded data sets are merged into a collection of TableDAP (netCDF Discrete Sampling Geometry) data sources. Currently the UAF ERDDAP server is home to 10,712 data sets. After the UAF ERDDAP server has examined the data collection, a Live Access Server (LAS) is configured to offer data analysis and visualization access to all the data sets. The final piece of the puzzle is to make the data FAIR and to achieve PARR compliance. This requires some tools that have been adapted and developed for this purpose. We resurrected the ncISO tool which can examine the contents of CF netCDF data sources and create ISO metadata and score the data according the the Unidata Attribute Convention for Data Discovery. We can help the centers hosting the data meet their PARR requirements by properly integrating the resulting metadata from ncISO into NOAA’s central data catalog. We have recently updated the templates which are used to generate the metadata to insure they are meeting the latest ISO and ADDC specifications. Work is underway at NOAA and Unidata to integrate the ncISO code back into the GitHub repository for the THREDDS Data Server. This will bring together two disparate ncISO implementations. UAF is a few people working a few hours a month to maintain and large and useful data collection and in this talk we’ll tell you how we do it.