The Asian Tropopause Aerosol Layer (ATAL) has emerged in recent decades to play a prominent role in the upper troposphere and lower stratosphere above the Asian monsoon. Although ATAL effects on surface and top-of-atmosphere radiation budgets are well established, the magnitude and variability of ATAL effects on radiative transfer within the tropopause layer remain poorly constrained. Here, we investigate the impacts of various aerosol types and layer structures on clear-sky shortwave radiative heating in the Asian monsoon tropopause layer using reanalysis products and offline radiative transfer simulations. ATAL effects on shortwave radiative heating based on the MERRA-2 aerosol reanalysis are on the order of 10% of mean clear-sky radiative heating within the tropopause layer, although discrepancies among recent reanalysis and forecast products suggest that this ratio could be as small as ~5% or as large as ~25%. Uncertainties in surface and top-of-atmosphere flux effects are also large, with values spanning one order of magnitude at the top-of-atmosphere. ATAL effects on radiative heating peak between 150 hPa and 80 hPa (360 K–400 K potential temperature) along the southern flank of the anticyclone. Clear-sky and all-sky shortwave heating are at local minima in this vertical range, which is situated between the positive influences of monsoon-enhanced water vapor and the negative influence of the ‘ozone valley’ in the monsoon lower stratosphere. ATAL effects also extend further toward the west, where diabatic vertical velocities remain upward despite descent in pressure coordinates.

Pure metallic reflectarray antennas have good power efficiency and low fabrication cost, which were limited to single band operation. A dual-band reflectarray antenna is developed for two directional beams by two feeds. The reflecting elements are metal waveguides, and have novel properties of both resonant and non-resonant modes at the two frequency bands. The low and high frequency bands can be easily separated by the cutoff frequency of waveguide modes. The phase changing mechanisms via ray optics and fundamental waveguide modes, respectively provide simple formulations for elemental structure design of directional beams. Radiation characteristics of the linear and circular polarizations are cross-examined with good performance by full-wave simulations using HFSS, FEKO and CST at 28 and 60 GHz bands for 5G front-haul network applications.

Studies of element partitioning between suspended sediment and water with increased seawater mixing are sparse, particularly in Bangladesh. However, these studies are important for understanding elemental cycling, pollutant transport, and impacts on aquaculture and sensitive ecosystems in estuaries and tidal deltas such as the Sundarbans mangrove forest in Southwest Bangladesh. Thus, water samples collected within the upper 1m of the water column along a transect of well-mixed tidal channels in Southwest Bangladesh during the dry season were analyzed for dissolved and suspended sediment element concentrations and other geochemical parameters. While most elements in the suspended load were close to or depleted relative to upper continental crust (UCC), several trace elements such as Sb, As, Cd and Se were slightly enriched. Additionally, most trace elements in the dissolved load were well above world average riverine concentrations, particularly Se and As. Dissolved load Ba and Se displayed mostly conservative mixing trends with seawater. Barium was likely originally sourced from sediment desorption and groundwater exfiltration, while Se may have been anthropogenically sourced from the city of Khulna or farther upstream. Dissolved As did not display conservative mixing trends, and may ultimately be geogenic in origin, possibly from groundwater. Ni and Co show trends consistent with desorption from competitive seawater cation exchange along the transect, similar to a study in the nearby Hooghly Estuary in West Bengal. Collectively, our results show that combined anthropogenic and natural influences on trace element distributions in coastal environments are important to quantify for continual protection of natural areas and better understanding of trace element discharge to global oceans.

The detection and rapid characterisation of earthquake parameters such as magnitude are important in real time seismological applications such as Earthquake Monitoring and Earthquake Early Warning (EEW). Traditional methods, aside from requiring extensive human involvement can be sensitive to signal-to-noise ratio leading to false/missed alarms depending on the threshold. We here propose a multi-tasking deep learning model – the Convolutional Recurrent model for Earthquake Identification and Magnitude Estimation (CREIME) that: (i) detects the earthquake signal from background seismic noise, (ii) determines the first P-wave arrival time and (iii) estimates the magnitude using the raw 3-component waveforms from a single station as model input. Considering, that speed is essential in EEW, we use up to two seconds of P-wave information which, to the best of our knowledge, is a significantly smaller data window compared to the previous studies. To examine the robustness of CREIME we test it on two independent datasets and find that it achieves an average accuracy of 98\% for event-vs-noise discrimination and can estimate first P-arrival time and local magnitude with average root mean squared errors of 0.13 seconds and 0.65 units, respectively. We compare CREIME with traditional methods such as short-term-average/ long-term-average (STA/LTA) and show that CREIME has superior performance, for example, the accuracy for signal and noise discrimination is higher by 4.5\% and 11.5\% respectively for the two datasets. We also compare the architecture of CREIME with the architectures of other baseline models, trained on the same data, and show that CREIME outperforms the baseline models.

We show that an ion-ion cross-field streaming instability between cold newborn cometary ions and heated heavy ions that were picked up upstream is likely a contributing source of observed lower hybrid (LH) waves in the inner coma of comet 67P/Churyumov-Gerasimenko. Electric field oscillations in the LH frequency range are common here, and have previously been attributed mainly to the lower-hybrid drift instability (LHDI), driven by gradients associated with observed local density fluctuations. However, the observed wave activity is not confined to such gradients, nor is it always strongest there. Thus, other instabilities are likely needed as well to explain the observed wave activity. Several previous works have shown the existence of multiple populations of cometary ions in the inner coma of 67P, distinguished by differences in mass, energy and/or flow direction. We here examine two selected time intervals in October and November 2015, with substantial wave activity in the lower hybrid frequency range, where we identify two distinct cometary ion populations: a bulk population of locally produced, predominantly radially outflowing ions, and a more tenuous population picked up further upstream and accelerated back towards the comet by the solar wind electric field. These two populations exhibit strong relative drifts ($\sim$20 km/s, or about 5 times the pickup ion thermal velocity), and we perform an electrostatic dispersion analysis showing that conditions should be favorable for lower hybrid wave generation through the ion-ion cross-field instability.

Determining paleotemperatures in terrestrial environments are much more challenging than those in the ocean because of stratigraphic inconsistencies, strong spatial and temporal variations in temperature, and a paucity of well-tested methods. Here we utilize the ganoine scales of gars from the family Lepisosteidae to calibrate a new terrestrial paleothermometer. Gars are widespread both in the modern and in the past, as they are a freshwater fish lineage that extends back into the Cretaceous (100 Ma) and have remained relatively unchanged during that time span. Gars constantly record water temperatures, whose yearly average is closely related to mean annual temperature, in their body tissues, including scales. These scales grow continuously throughout life, are >95% hydroxyapatite and thus are highly resistant to diagenetic alteration. Oxygen isotopes in both biogenic phosphates and carbonates have been used to reconstruct environments on land with varying degrees of success. Phosphate-oxygen isotopes are more resistant to post-mortem alteration as the phosphorus-oxygen bond is stronger than the carbon-oxygen bond. We investigate the application of phosphate oxygen isotopes to gar scales by collecting scales from modern individuals from a north-south transect across the United States, exploiting the latitudinal temperature gradient in mean annual temperatures, measuring δ18Ophosphate of those scales, and comparing these values to the average δ18Owater and temperature of each locality. We compare our δ18Ophosphate calibration to previously published curves. Our work demonstrates that the δ18Ophosphate values of gar scales are robust recorders of temperature and δ18Owater.

The riverine flux of terrigenous dissolved organic matter (tDOM) to the ocean is a significant contributor to the global carbon cycle. In response to anthropogenic drivers such as land-use change the flux is expected to increase, and this may impact both the availability of sunlight in coastal ecosystems, and the seawater carbonate system and coastal CO2 fluxes. Yet despite its biogeochemical and ecological significance, there are few long-term and high-resolution time series of tDOM parameters. Corals incorporate fluorescent tDOM molecules from the chromophoric dissolved organic matter (CDOM) pool in their skeletons, and the resulting luminescence variability in coral skeleton cores has traditionally been used to reconstruct hydroclimate variation. Here, we use two replicate coral cores and concurrent in-situ biogeochemical data from the Sunda Sea Shelf in Southeast Asia, where coastal peatlands supply high tDOM inputs, to show that variability in coral luminescence green-to-blue ratios (coral G/B) can be used to quantitatively reconstruct the concentration of terrigenous dissolved organic carbon (tDOC). Moreover, coral G/B can be used to reconstruct the full absorption spectrum of CDOM from 230–550 nm, as well as the specific ultraviolet absorbance at 254 nm (SUVA254) of the DOM pool. Comparison to a core from Borneo shows that there may be site-specific offsets in the G/B–CDOM absorption relationship, but that the slope of the relationship is very similar, validating the robustness of the proxy. By demonstrating that coral cores can be used to estimate past changes in coastal tDOC and CDOM, we establish a method to study natural and anthropogenic drivers of land–ocean tDOM fluxes and their ecological consequences in tropical coastal seas over decadal to centennial time scales.

The DNA molecules are stable but easily fragmented by ionization radiation, which challenges DNA integrity in searching for evidence for extraterrestrial life on icy satellites. The objective was to estimate the highest value of the attenuation effect of freezing temperature on the efficacy of gamma-radiation in fragmenting dsDNA. A bacterial 16S rRNA gene inserted in a vector as a lyophilized crude cell lysate was irradiated (60Co) under the liquid nitrogen conditions (-195.8oC). The outcome was tested in a specific PCR, generating the MAIN (~600bp) as well as EXTRA “mis-primed” small-sized (~70bp) amplicons. At the ambient temperature, the main PCR product entirely disappeared upon the doze 7.5kGy while at -195.8oC, it withstood ~750kGy (~100 times difference). Vise-verse, the EXTRA short amplicon reached the maximum outcome at the dose ~400kGy and continued to persist until the tested dose 840kGy. By extrapolation, the given product could be generated upon irradiating target DNA at a dose of more than 1mGy. Such a find opens a chance (and time window of more than 25 years) to pick up freshly flushed out sub-ice-ocean microbes/DNA and get frozen as inclusions in water matrices on the Jovian Europa to verify the extraterrestrial life.

The development of mobile profiling facilities at the University of Alabama in Huntsville has led to the formation of the Mobile Atmospheric Profiling Network (MAPNet), which is now available to the broader scientific community as part of the NSF supported Community Instruments and Facilities (CIF). The MAPNet consists of the following four mobile platforms (commercially available instruments are defined within parentheses): MIPS – Mobile Integrated Profiling System (915 MHz Doppler wind profiler, X-band Profiling Radar, Microwave Profiling Radiometer, lidar ceilometer); RaDAPS – Rapidly Deployable Atmospheric Profiling System (915 MHz Doppler wind profiler, Micro-Rain Radar, Microwave Profiling Radiometer, and lidar ceilometer); MoDLS – Mobile Doppler Lidar and Sounding System (Doppler wind lidar, Microwave Profiling Radiometer); and MAX – Mobile Alabama X-band scanning dual polarization radar. All four systems include near-surface in situ measurements of state variables and balloon sounding capabilities. This presentation will review the measurement capabilities of each instrument, and the research capabilities of the MAPNet. A unique concept of this suite of platforms is the combination of sensors that can provide high temporal-resolution (<5 min) profiles of wind, temperature, humidity, aerosols, cloud base, and precipitation over a broad range of conditions. Therefore, both boundary layer and precipitation research can be supported. Examples of measurements will include the following: Utilization of the MAPNet in a network mode to document the spatiotemporal variability of boundary layer and associated stratocumulus clouds preceding cool season, severe quasi-linear systems; Comparisons of wind profiles and vertical motion among the individual instruments; Measurements of bores and gust fronts within the planetary boundary layer; Integration of data from disparate profiling systems to promote understanding of complex boundary layer evolution within precipitation, including landfalling hurricanes; Examples of educational deployments that have utilized the MAPNet in the past, and may serve as a prototype for educational deployments in the future.

We quantify the volume transport and watermass transformation rates of the global ocean circulation using the Estimating the Circulation and Climate of the Ocean version 4 release 4 (ECCOv4r4) reanalysis product. Our results support large rates of intercell exchange between the mid-depth and abyssal cells, in agreement with modern theory and observations. However, the present-day circulation in ECCO cannot be interpreted as a near-equilibrium solution. A dominant portion of the apparent diapycnal transport of watermasses within the deep ocean is not associated with irreversible watermass transformation. Instead up- and down-welling is associated with isopycnal volume changes, reflecting trends in the deep ocean density structure. Our results reveal disagreement between ECCO’s representation of the overturning circulation and associated watermass transformations, and prevailing equilibrium theories of the overturning circulation.

The thickness of the lunar regolith has been previously estimated using seismic, radar, and crater morphology data to be on the order of tens of meters. In this study, we use rock abundance measurements from the Diviner radiometer aboard the Lunar Reconnaissance Orbiter (LRO) to provide new estimates of rock-free regolith thickness in recently-formed impact craters. Diviner cold spots have been shown to last no longer than a few 100 kyr, and thereby point to fresh craters on the moon. Trends in Diviner data also show that deeper cold spot craters have rockier ejecta. We employ statistical analyses to show that cold spot craters in the lunar mare have rockier ejecta at smaller excavation depths when compared to those in the highlands. We estimate that the average rock-free regolith is 12.6 m thick in the mare and 18.5 m thick in the highlands, which is consistent with previous estimates. We expect these values will be highly variable due to differences in regolith development and overturn across the moon.

This study investigates aerosol “sensitivity regimes” to explore the effectiveness of abating gaseous precursors to mitigate aerosols over the Indo-Gangetic Plain (IGP). A new mechanistic insight is proposed by integrating ISORROPIA-II thermodynamical model with high-resolution simultaneous measurements of precursor gases (HCl, HNO3, and NH3) and inorganic constituents of PM1 and PM2.5, monitored for the first time in India using MARGA-2S instrument. The estimated aerosol acidity (pH) of PM1 and PM2.5 was 4.49±0.53 and 4.58±0.48, respectively. The sensitivity of phase-partitioning (ε) of Cl-, NO3-, and NH4+ to pH, ALWC, HCl, HNO3, and NH3 showed that fine aerosols fall in the ”HCl and HNO3 sensitive regime”, emphasizing that HCl and HNO3 reductions would be the most effective pathway to reduce aerosols in NH3-rich IGP. Since existing mitigation strategies over IGP are random and ineffective, this novel insight is the first step in providing a thermodynamically consistent “roadmap” to mitigate aerosols effectively.

Data is the lifeblood of the geosciences. The acquisition, processing and interpretation of data all depend on established specifications describing the systems and procedures that were used in producing, describing and distributing that data. It can be said that technical standards underpin the entire scientific endeavour. This is becoming ever truer in the era of Big Data and Open, Transdisciplinary Science. It takes the dedicated efforts of many individuals to create a viable standard. This presentation will describe the experiences and status of standards development activities related to geoscience remote sensing technologies which are being carried out under the auspices of the IEEE Geoscience and Remote Sensing Society (GRSS). While the value and viability of community-developed principles and specifications have been amply demonstrated, a Standards Development Organization (SDO) exists to provide the environment, rules and governance that are needed to ensure the fair and equitable development of a standard, and to assist in the distribution and maintenance of the resulting standard. The GRSS sponsors projects with the IEEE Standards Association (IEEE-SA), which, like other SDOs such as ISO and OGC, has well-defined policies and procedures that help ensure the openness and integrity of the standards development process. Each participant in a standards working group typically brings specific interests as a producer, consumer or regulator of a product, process or service. Creating an environment that makes it possible to find consensus among competing interests is a primary role of an SDO. This presentation will include highlights and insights gained from the seven standards projects that the GRSS has initiated. These projects involve hyperspectral imagers, the spectroscopy of soils, data from synthetic aperture radars and GNSS reflectometry, calibration of microwave radiometers, and the characterization of radio frequency interference in protected geoscience bands.

HiRISE-based mapping reveals five landform assemblages in western Jezero crater, each defined by a landform association interpretable using Earth-based landsystem models and well-understood Earth analogues. 1) The northwestern assemblage hosts boulder hills rimmed by lobate ridges, mounds and mesas on a valley floor, and valley-bounding ridges superposed by striations (= parallel boulder-bearing ridges and grooves). 2) A trough zone hosts variously shaped depressions, intra-trough islands, linear and curvilinear boulder ridges, and highland strips topped by striated surfaces and rimmed by boulder-bearing ridges. 3) The steep-sided fan-shaped plateau (“western Jezero delta”) hosts mesas, highland-rim boulder ridges, depressions, linear and curvilinear ridges, and a plain superposed by radially trending striations. 4) The crater-margin assemblage hosts a steep-sided ridged and pitted hummocky terrain, a terrace-like capping surface, and mounds surrounded by radially trending boulder ridges. 5) The crater-floor assemblage hosts a polished and striated terrain that displays fold-like and streamlined ridges, hummocky landforms dominated by quasi-circular depressions with raised rims, mesas exposing fold-thrust strata, flat-topped steep-sided ridges with U-shaped map traces, polygonal-grooved plains, and unconsolidated boulder mounds and ridges. Although any aforementioned landform unit could be explained by multiple formative mechanisms, the spatiotemporal relationships mapped in this study within and among the assemblages place stringent constraints for any self-consistent interpretation. A model capable of explaining the mapping results involves northeast-flowing glaciation, ice-sheet collapse with ice-fracture patterns controlling the formation of polygonal grooves via crevasse filling and ice pressing, and minor aeolian modification. In the model, the plateau and crater-margin assemblages were formed by ice-walled subglacial deposition, the trough zone by subglacial flooding, the northwestern and basin-floor assemblages by glacial deformation and deposition, circular depressions with raised rims by melt out and down pressing of spherical dead-ice blocks (i.e., thermal karsts and kettle holes), mesas by kame formation, and striations by glacial fluting.

This paper exploits the Asymmetric Gaussian curve and its tangent space for the first time. We develop a new method of discriminating overlapping absorption bands. We then use the Asymmetrical Gaussian curve to derive a Master Equation to fit two overlapping bands. We then demonstrate the use of the Asymmetric Gaussian curve to fit four overlapping Gaussian bands, and show how this is relevant to the olivine family spectral complex at 1 μm. We report which olivine endmember is easiest to fit using an asymmetric curve. The limitations of the asymmetric band fitting method and a critical assessment of three commonly used numerical minimization methods are also provided.

Introduction We compare the CNN model against a simple logistic regression model to learn the benefits of simple models. For extracting features, we use the tsfresh package. We find that logistic regression detects five events compared to six by CNN on an untrained data. It also takes lesser time to train compared to CNN. Method 1.Data selection and pre-processing We have used seismic records from the G- network of the Groningen area for detecting low magnitude earthquakes. It comprises 70 borehole stations, each containing 5 sensors; one is a surface accelerometer and the other four are velocity sensors installed at 50m depth intervals. We use data from 47 events recognized in the KNMI catalog between October 1, 2017 and February 28, 2018. For training and validating, we use the lowest depth velocity sensor at five stations (G19, G23, G24, G29, G67) over the 5-months. For testing, we use a separate four-hour dataset. 2.Feature extraction and analysis Tsfresh lets us identify and extract relevant features using various statistical computations like approximate entropy, skewness, variance, standard deviation etc. It calculated 293 relevant features. We use univariate selection and correlation analysis to find the best possible combination and selected top 20 features. 3.Different models used We have compared the performance of logistics regression and CNN models. The CNN model consists of 3 convolutional layers, each followed by a max-pooling layer. Then we flatten the output of last pooling-layer and pass it into two fully connected layers followed by an output layer which determines whether the input is signal or noise. For CNN, the Adam optimizer is used with binary cross entropy as the loss function. Result Two events were already picked in the KNMI catalogue ( at 00:12:28 and at 00:57:46.) of M1.9 and M2.2 for the test data. Table 1 shows the list of operations from which we calculate the top 20 features. Table 2 shows the number of correct predictions, training time, and the time-stamps of uncatalogued events detected for both models. Both models were able to detect the events listed in the catalogue in addition to other uncatalogued events. Conclusion Simple models are easier to understand, debug, train and interpret than the complex black box models. A detailed study on diverse data is needed to improve our understanding.

Large-scale river hydrodynamic model act as fundamental tool for many scientific applications related to water cycle, biogeochemistry, and carbon cycle. Even though process representation in the physically based hydrodynamic models has improved significantly in recent times, due to many error sources the uncertainty reduction and evaluation remains a key issue. Previously most of the research focused on the evaluation of hydrodynamic model considering single variable only i.e., discharge due limitations related to models and data availability. The recent advances in hydrodynamic modelling and remote sensing helped to overcome limitation. Some recent studies performed calibration and validation considering multiple variables but were unable to integrate them into a single evaluation score due to different spatial and temporal dimension of variables and thus make it hard to judge the overall performance. Here, we have evaluated the performance of Catchment-based Macroscale Floodplain (CaMa-Flood) hydrodynamic model over Amazon basin considering multiple variables i.e., discharge (Q), water surface elevation (WSE) and flooded area (FA) for a topography data multi-error removed improved terrain (MERIT) DEM. We proposed an evaluation method and introduced a metric “overall basin skill score” (OSK) to integrate the performances due to multiple (three here) variables considering their spatial distribution via a sub-basin approach and provide the evaluation on a scale of 0 to 1. The integrated method showed the robustness in the method and able to detect the best river channel depth parameter set with maximum OSK of 0.57, whereas the evaluation using single variable proved inadequate due to different sensitivity of variables and maximum metric score were obtained for many parameters sets. The proposed method enables a balanced evaluation of different variables and proved useful to integrated multivariable model evaluation with reducing the chances of getting the right results due to wrong reasons. Preprint related to this work: https://doi.org/10.1002/essoar.10506596.1

The study aims at differentiating lithologic units, general structural trends and orogenic implications of crystalline rocks within part of Oban Massif, Southeastern Nigeria. Field study involve geological mapping, rock description and structural measurement, while laboratory analysis covered photomicrograph. Field observation and microscopic analysis reveal five petrological units; gneisses, schists, granodiorite, pegmatite and quartz veins. The rocks are generally siliceous and quartzo-feldspathic. The schist show foliation planes trending ma-jorly in the NE-SW direction. The gneisses were highly fractured, indicative of a polyphase deformation. Structural elements such as joints, fractures, foliations and veins show series of deformational episodes that affected the area. Rose diagram plot for these structures show the NE-SW direction indicative of the Pan-African orogeny (600±150 Ma) and interpreted as the most recent event affecting the area. NW and NE trending joints are considered to be tectonic in origin based on their alignments with major structures of the area. Furthermore, the structures also showed weak NW-SE and E-W trends, an imprint of older (Kibaran orogeny) deformational episodes.