Global maps of maximum bottom particle concentration, benthic nepheloid layer thickness, and integrated particle mass in benthic nepheloid layers (BNL) based on 2412 global profiles collected using the Lamont Thorndike nephelometer from 1964-1984 are compared with maps of those same properties compiled from 6,392 global profiles measured by transmissometers from 1979 to 2016. Outputs from both instruments were converted to particulate matter concentration (PM). We present here a visual global comparison of the location and intensity of BNLs measured with these two independent instruments over slightly overlapping decadal time periods and combine the data sets in order to expand the time scale of global in situ measurements of BNLs, and to gain insight about the factors creating/sustaining BNLs. The similarity between general locations of high and low particle concentration BNLs during the two time periods indicates that the driving forces of erosion and resuspension of bottom sediments are spatially persistent during recent decadal time spans, though in areas of strong BNLs, intensity is highly episodic. Topography and well-developed current systems play a role. These maps can be used to better understand deep ocean sediment dynamics, linkage with upper ocean dynamics, the potential for scavenging of adsorption-prone elements near the seafloor, and provide a comprehensive comparison of these data sets on a global scale. During both time periods, BNLs are weak or absent in most of the Pacific, Indian, and Atlantic basins away from continental margins. High surface eddy kinetic energy is associated with the Kuroshio Current east of Japan. Both data sets show weak BNLs south of the Kuroshio, but no transmissometer data have been collected beneath the Kuroshio itself. Sparse nephelometer data show moderate BNLs just north of the Kuroshio Extension, but with much lower concentrations than beneath the Gulf Stream. Strong BNLs are found in areas where eddy kinetic energy in overlying waters, mean kinetic energy near bottom, and energy dissipation within the bottom boundary layer are high. Areas of strongest BNLs include the Western North Atlantic, Argentine Basin, areas around South Africa tied to the Agulhas Current region, and somewhat random locations in the Antarctic Circumpolar Current of the Southern Ocean.

The Plankton, Aerosol, Cloud, and Ocean Ecosystem (PACE) mission is NASA’s next great investment in Earth Science, continuing NASA’s legacy of over forty years of satellite ocean color measurements. PACE, expected to launch in 2023, will advance our Earth-observing and monitoring capabilities through hyperspectral imaging and multi-angle polarimetric observations of ocean, atmosphere, and land ecosystems. PACE will give us an unprecedented view of our home planet and will support user-driven environmental applications through research and applied science to address societal challenges and inform decision-making. The PACE Applications program seeks to strengthen the ties between science and decision-making through programming such as the Early Adopter initiative, workshops and focus sessions, and information-sharing and co-production activities. Practical applications of PACE data include waterborne pathogen monitoring and prediction, harmful algal bloom species discrimination and early-detection, support for best-management practices for estuary and watershed health, as well as sustainable fishery and aquaculture practices. Hyperspectral and polarimetric PACE data will provide water resource managers and decision-makers with highly accurate ocean color and atmospheric observations that will directly improve their operational products and applied technologies, ultimately fulfilling real-world needs. This presentation will highlight PACE’s novel hyperspectral and polarimetric capabilities, introduce PACE’s standard and exploratory data products, outline the PACE Applications Program, share real-world coastal applications of PACE data, and summarize the results of the 2021 PACE Applications Water Quality Focus Session and the 2021 PACE Applications Workshop as they relate to community engagement and capacity development. Finally, we will share the revamped PACE Applications Outreach Strategy and how it will be used to promote partnerships within the existing user communities of practice and new user communities of potential for greater societal benefit.

Arctic summer sea ice has decreased dramatically over the last few decades, with a substantial part of this decline attributed to internal variability. However, models show large differences in their simulated internal variability, increasing projection uncertainty and complications with model-observation comparisons. Here we will present results that aim to quantify the contribution of internal variability in different models which provide large ensemble simulations, and compare them with estimates from observations. In particular, we are comparing five models from the CLIVAR multi-model large ensemble (CanESM2, CESM1, CSIRO MK36, GFDL ESM2M, and MPI ESM1) with observations. So far, we have found a large range in simulated pan-Arctic sea ice area standard deviation from 0.35 million km2 (CSIRO MK36) to 0.74 million km2 (CESM1) for mean September areas between 4.00-4.25 million km2. Spatially, the detrended standard deviation in the central Arctic is consistently over-represented in models compared to observations. Conversely, the marginal seas are simulated to have slightly below to several times below observed detrended standard deviation. Further analysis on a more regional scale will be done over the coming months to further characterize the realism of simulated internal variability in Arctic sea ice.

Seismic source locations provide fundamental information on earthquakes and lay the foundation for seismic monitoring at all scales. Subsurface engineering operations, such as hydraulic fracturing, usually generate abundant microseismic events with low signal-to-noise ratios, thus raising a higher demand on the reliability and computational efficiency of seismic location methods. Stacking-based method involves reconstructing and focusing the radiated seismic source energy with a certain stacking operator, for example, the diffraction stacking operator or the cross-correlation stacking operator. They are noise-resistant, automatic, and data-driven. The source locations are resolved as images instead of discrete dots, offering more insights into source processes and surrounding structures. In this work, we conduct the performance evaluation and influential factor analysis with synthetic examples, to further improve the understanding of the method. Three categories of factors are investigated, including the velocity model, array geometry, and waveform complexity. Each of the three factors consists of several detailed factors, such as different array types and noise levels. Multiple parameters are considered for the performance evaluation, including location error/bias, imaging resolution, signal alignment with time shifts, and the computational cost. The proposed scheme is also applied to field microseismic datasets to demonstrate its feasibility. This study will be conducive to the design and evaluation of surface monitoring projects.

Sap flow observations provide a basis for estimating transpiration and understanding forest water use dynamics and plant-climate interactions. This study developed a continental modeling approach using Long Short-Term Memory networks (LSTMs) to predict hourly tree-level sap flow across Europe based on the SAPFLUXNET database. We developed models with varying levels of training sets to evaluate performance in unseen conditions. The average Kling-Gupta Efficiency was 0.77 for gauged models trained on 50 % of time series across all forest stands and was 0.52 for ungauged models trained on 50 % of the forest stands. Continental models matched or exceeded performance of specialized and baseline models for all genera and forest stands, demonstrating the potential of LSTMs to generalize hourly sap flow across tree, climate, and forest types. This work highlights hence the potential of deep learning models to generalize sap flow for enhancing tree to continental ecohydrological investigations.

This study was conducted to assess effect of tillage and mulch on soil erosion control in typical agroecological conditions of Benin. In addition, it involved also the assessment of soil moisture and runoff. The experiment was conducted on two sites in Central Benin during the short rain season of 2018. The effect of three tillage practices (contour ridging: CR; slope ridging: SR and no-tillage: NT) and three mulch doses (0 t.ha-1; 3 t.ha-1; and 7 t.ha-1) on soil erosion under maize was investigated at small experimental plots (21 m2). The 7Be method was used to assess the erosion rates, runoff was measured by total collection and soil moisture content was determined by thermo-gravimetric method. The results showed a significant decrease in runoff coefficient and soil loss while increase soil moisture under no-tillage and contour ridges compared to slope ridges. This effect was pronounced with greatest. 3 and 7 tha-1. Highest runoff coefficient and soil loss and the lowest soil moisture were observed under slope ridging without mulch (i.e. SR0M). The 7Be measurement showed high soil losses under SR0M (-10.19 t ha-1) at Dan and under NT0M (-7.36 t ha-1) at Za-zounmè. The treatments NT7M (0.80 t ha-1); SR7M (0.69 t ha-1); IR3M (2.07 t ha-1) and CR7M (4.05 t ha-1) showed deposition at Dan while SR7M (0.23 t ha-1) and CR7M (3.93 t ha-1) showed deposition at Za-zounmè. This study revealed useful information to be taken into consideration when developing soil and water conservation management strategies in Benin.

Contemporary Earth system models mostly ignore the sub-grid scale (SGS) heterogeneous coupling between the land surface and atmosphere. To aid in the development of coupled land and atmosphere SGS parameterizations for global models, we present a study of different aspects of highly-realistic sub-100 km scale land-surface heterogeneity. The primary experiment is a set of simulations of September 24, 2017 over the Southern Great Plains (SGP) site using the Weather Research and Forecasting (WRF) model with 100-m horizontal resolution. The overall impact of land-surface heterogeneity is evaluated by comparing cloud and turbulent kinetic energy (TKE) production in large-eddy simulations (LESs) using heterogeneous and homogeneous surface fields (namely sensible and latent heat fluxes) specified by an offline field-scale resolving land-surface model (LSM). The heterogeneous land surface leads to significantly more cloud and TKE production. We then isolate specific sources of heterogeneity by using selectively domain-wide averaged fields in the LSM. It is found that heterogeneity in the land surface created by precipitation is effectively responsible for the increases in cloud and TKE production, while rivers and soil type have a negligible impact and land cover has only a small impact. Additional experiments modify the Bowen ratio in the surface fields and the initial wind profile of the heterogeneous case to clarify the results seen. Finally two additional days at the SGP site are simulated showing a similar increase in cloud production in heterogeneous cases.

The Enriquillo-Plantain Garden Fault (EPGF), one of two left-lateral transforms that define the Caribbean-North American plate boundary in Haiti, plunges beneath Lake Azuei in the eastern part of the country. In 2017, we acquired 220 km of sub-bottom and multichannel seismic reflection profiles (CHIRP and MCS) in a 1.2 km grid pattern across the lake. The two seismic methods achieved subbottom penetration of up to 15 m and 200 m, respectively. CHIRP and MCS data reveal folded turbidites across the expected extension of the EPGF fault zone at the south end of the lake, although direct evidence for faulting is lacking. Along the west side of the lake, however, MCS data image a broad NW-SE monoclinal fold whose geometry is compatible with an underlying SW-dipping blind thrust fault. CHIRP profiles image patches of soft- sediment deformations above the monoclinal fold; they also image a distinctive 11 m-deep paleoshoreline all around the lake that is uplifted by 1-2 m above that fold. These results are compatible with a scenario where some large slip event(s) on the presumed blind thrust occurred after formation of the paleoshoreline, locally uplifting the lakebed and causing liquefaction. Two short sediment cores sampled a layer correlatable to a reflection in the CHIRP profiles. That reflection extends laterally below the 11m shoreline, and thus predates its formation. On-going 14C dating of material from the two cores are expected to provide a maximum age for the shoreline, and thus for some hypothetical slip event(s) on the presumed blind thrust fault. The prominent character of the paleoshoreline suggests that it was stable, something best achieved if the lake level was controlled by the sill depth of an outlet. Presently, no such outlet exists and the lake level fluctuates. Pending results from radiometric dating, we propose that, earlier in the Holocene, the lake overflowed eastward into adjacent Lake Enriquillo along the narrow valley marking the extension of the EPGF fault zone - a valley that is presently blocked by an alluvial fan. Regardless of the relevance of that model, the uplifted shoreline implies a significant uplift rate on a structure extending up to 10 km north of the EPGF fault zone and striking oblique to it, confirming that transpressional tectonics is partitioned over an area at least as broad as Lake Azuei.

This study examines how the congestus mode of tropical convection is expressed in numerical simulations of radiative-convective equilibrium (RCE). We draw insights from the ensemble of cloud-resolving models participating in the RCE Model Intercomparison Project (RCEMIP) and from a new ensemble of two-dimensional RCE simulations. About half of the RCEMIP models produce a congestus circulation that is distinct from the deep and shallow circulation modes. In both ensembles, congestus strength is associated with large-scale convective aggregation. Aggregation dries out the upper troposphere, which allows moist congestus outflow to undergo strong radiative cooling. The cooling generates divergence that promotes continued congestus overturning (a positive feedback). This mechanism is fundamentally similar to the driving of shallow circulations by radiative cooling at the top of the surface boundary layer. Aggregation and congestus invigoration are also associated with enhanced static stability throughout the troposphere. Changes in entrainment cooling are found to play an important role in stability enhancement, as has been suggested previously. A modeling experiment shows that enhanced stability is not necessary for congestus invigoration; rather, invigoration itself contributes to midlevel stability enhancement via its impact on the vertical profile of radiative cooling. When present, congestus circulations have a large impact on the mean RCE atmospheric state; for this reason, their inconsistent representation in models and their impact on the real tropical atmosphere warrant further scrutiny.

This first paper of the two-part series focuses on demonstrating the predictability of a hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutions including 0.01 degree (∼ 1-km) and 0.25 degree (∼ 25-km). The assessment is conducted via comparisons against ground-based observations and satellite-derived reference products. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent, and total runoff. In the evaluation against ground-based measurements, the superiority of the 0.01 degree estimates are mostly demonstrated across relatively complex terrain. Specifically, hyper-resolution modeling improves the skill in meteorological forcing estimates (except precipitation) by 9% relative to coarse-resolution estimates. The model forced by downscaled forcings in its entirety yields the highest predictability skill in model output states as well as precipitation, which improves the skill obtained by coarse-resolution estimates by 7%. These findings, on one hand, corroborate the importance of employing the hyper-resolution versus coarse-resolution modeling in areas characterized by complex terrain. On the other hand, by evaluating four sets of model simulations forced with different precipitation products, this study emphasizes the importance of accurate hyper-resolution precipitation products to drive model simulations.

Sustainable agriculture and forestry is an important topic under climate change. This is a potential route for increasing long-term soil and biomass carbon storage, soil water retention capacity and for reducing water and wind erosion risks. This study uses the Styrian Raab and Enns catchment regions in Southeastern Austria as showcase regions for exploring sustainable whole-system options for climate change adaptation and mitigation under increased hot-dry conditions in agriculture and forestry. Based on dense data of the WegenerNet observing network and further hydrometeorological data, combined with hydrological modelling (WaSiM), the current hydrological disturbance potential in the Southeastern Austria focus regions is assessed. Furthermore, downscaled IPCC climate change scenarios are used for future projections and the results are evaluated for increasing heat and drought risks. This work provides the hydrological context for modelling the soil water and carbon storage enhancement options that farming, forestry and land-use practices might apply. A first key study aspect in this context is the sustainable potential of bioenergy crops. Using the local-scale WegenerNet data combined with Harmonized World Soil Database (HWSD) soil data, potential yields for bioenergy from lignocellulosic biomass (forest and Miscanthus, willow and poplar) is modelled using MiscanFor, SalixFor, PopFor and DAYCENT models for representative local areas in the showcase regions. Using DAYCENT biogeochemical modelling with different agricultural, forest management, and land use practices under climate change, sustainable system options under different future climate change scenarios are developed. These results will be used in turn to develop whole-system options, namely to jointly achieve increase of soil carbon and robustness of soil water retention capacity, increase of soil quality, reduction of soil erosion and degradation, reduced compaction, stabilisation of slopes, sustainability and resilience in the soil as well as the agricultural and forest production system. Sustainable whole-system options for farmers and forest managers are the major study focus and will supply data for local estimates in the chosen representative areas in the showcase regions as well as for upscaling to country level.

This study aims to establish an inverse model for reconstructing properties of turbidity currents from their deposits. Although several attempts of in-situ measurements have been succeeded, flow properties of large-scale turbidity currents that build submarine fans remain unclear. Recurrence interval of turbidites in natural levees or lobes of submarine fans is generally 100s years, while in-situ observation in modern submarine canyons reported yearly to monthly occurrence of turbidity currents. That is, turbidity currents that substantially form submarine fans may be extremely low frequency and large-scale than currently observed. To understand the behavior of fan-building flows occurring with sub-millennial scale recurrence interval, the quantitative reconstruction of flow conditions from geologic records is required. However, inversion of flow properties in natural scale has been impractical because the heavy computational load of 2D or 3D models of turbidity currents has prevented to perform inversion requiring iteration of calculations. To this end, we propose a method using 2D shallow-water model with the deep-learning neural network (DNN). In this method, a horizontal 2D shallow-water model of turbidity currents was employed as the forward model. Numerical simulation was repeated to obtain horizontal distribution of thickness of turbidites under various initial conditions, and then this synthetic data set was used for supervised training of DNN. After the training phase finished, DNN properly estimated initial conditions of turbidity currents (e.g. initial flow height, velocity, etc.) from artificial test data set that was also produced from the forward model. In previous methods, the computational cost of 2D model was too high to be employed as the forward model for turbidite inversion, while our methodology can reconstruct initial conditions of turbidity currents instantaneously. Although production of the training data set requires 1000s times repetition of calculation, all calculation of forward model can be perfectly parallelized, so that the problem of calculation efficiency can be easily solved by using PC cluster. Future application of our method to actual deposits will contribute to understand the development processes of submarine channels or lobes in the long term.

Microbial processing of fresh carbon inputs is recognized as a key step in the formation of mineral-associated organic matter. Low molecular weight (LMW) compounds comprise a notable fraction of these inputs and are rapidly assimilated and metabolized by the microbial community. In this work, we employ ecophysiological studies of microbial isolates to better understand the role of substrate identity as a control on preferences, uptake kinetics, and carbon use efficiencies (CUE) across a gradient of phylogenetic differences (gram negative, gram positive, and fungal). Soil-extracted, solubilized organic matter (SESOM) derived from the Oa horizon of a hemlock-hardwood forest stand and synthetic media based off of this extract were chosen as liquid media for batch growth studies. A combination of exometabolomic techniques (1H NMR, UHPLC-MS) were used to quantify 35 LMW substrates in the original extract (0.4 – 195 μM), comprising 19.5% of total C and 39.9% of total N. Consumption of these substrates by microbial isolates accounted for a substantial amount of total C and N assimilated during growth, representing 43-75% and 58-74%, respectively. Time resolved sampling allowed modeling of sigmoidal uptake curves and the comparison of the midpoint of consumption (Th, hr) and 90% usage windows (ranging from 0.18 – 2.29 hr). Complementary experiments were conducted using synthetic media with all substrates at equimolar concentrations (25 μM) to better constrain the impact of initial concentration. We use stable isotope probing to determine CUE for five different LMW substrates of interest (glucose, acetate, formate, glycine, and valine). Ultimately, we are interested in whether unifying trends can be observed across the physiological gradient and how the metabolic transformations of these inputs may impact the organo-mineral formation process.

Improving the accuracy of coupling of water and carbon cycles in land surface models has been emphasised in recent studies as a major priority for research. Reliable quantification of carbon and water balances is required in order to effectively estimate gross primary production (GPP) and evapotranspiration (ET) across space and time. The P model (for ‘production’) is grounded in plant functional ecology and links the carbon and water cy- cles via a theory of stomatal optimization and photosynthetic acclimation. It has the mathematical form of a LUE model while being traceable to first principles, including the standard model of photosynthesis, for the prediction of GPP. The model has only three free parameters, of which two are estimated from independent observations on leaf stable carbon isotopes and leaf-level electron transport capacity. The model requires only elevation, CO2 concentration, solar radiation, vapour pressure deficit (VPD) and temperature as input. We will present a demonstration application of the P model using a novel approach that extends the algo- rithm to create a prototype of a universal transpiration (T) product using Sentinel 3 data. Both GPP and T outputs will be evaluated against FLUXNET observations. Stomatal conductance will be calculated based on the model’s predictions of GPP and the ratio of internal to external CO2 partial pressure, allowing transpiration to be calculated from VPD. The P model has many advantages, including its strong theoretical and empirical basis, extremely parameter-sparse nature, and the fact that it does not require the prior specification of plant functional types or land cover types. The research presented here will extend its application from primary production monitoring to include carbon-water cycle coupling and water resources assessment.

We present a study of the potential impact of deepening the Corpus Christi Ship Channel through Aransas Pass; in particular, we study the effect on the transport of red drum fish larvae due to the change in channel depth. The study is conducted by high resolution simulation of the circulation of the seawater entering and exiting the pass for the current and proposed Ship Channel depths. The computer model incorporates tides and meteorological forcing and includes the entire Gulf of Mexico and the North American Atlantic coast. The corresponding transport of larvae modeled as passive particles due to the sea water circulation is established by releasing particles in the nearshore region outside Aransas Pass and subsequently tracking their trajectories. Both models are implemented in supercomputers at the Texas Advanced Computing Center (TACC). Accuracy of the circulation model computations is validated through comparisons to data collected from tidal gauges in the fall of 2020. We compare the difference in the number of larvae that successfully reach appropriate nursery grounds inside Aransas Pass for four distinctive initial larvae positions in the nearshore region. Our results indicate that the change in channel depth does not significantly alter the number of red drum larvae that reach suitable see a net increase of 0.5%.

Searches for phosphine in Venus’ atmosphere have sparked a debate. Cordiner et al. 2022 analyse spectra from the Stratospheric Observatory For Infrared Astronomy (SOFIA) and infer <0.8 ppb of PH3. We noticed that some spectral artefacts arose from non-essential calibration-load signals. By-passing these signals allows simpler post-processing and a 5.7σ candidate detection, suggesting ~3 ppb of PH3 above the clouds. Compiling six phosphine results hints at an inverted abundance trend: decreasing above the clouds but rising again in the mesosphere from some unexplained source. However, no such extra source is needed if phosphine is undergoing destruction by sunlight (photolysis), to a similar degree as on Earth. Low phosphine values/limits are found where the viewed part of the super-rotating Venusian atmosphere had passed through sunlight, while high values are from views moving into sunlight. We suggest Venusian phosphine is indeed present, and so merits further work on models of its origins.

Atmospheric isotopologues of water vapor (e.g., HDO) are important tracers for understanding Earth’s hydrological cycles. Most remote sensing measurements of these isotopologues, however, are column averaged values and sparse in space and time. Measurements targeting the planetary boundary layer (PBL) are much rarer. In this study, we retrieved HDO and H from CLARS-FTS observations (2011-2019). The isotopological abundance δD, which represents the relative difference of the HDO/H2O ratio to a standard abundance ratio, is also calculated. The averaged δD retrievals are (−156.1±60.0)‰ with an uncertainty of (6.1±10.2)‰ for LA Basin Survey m and (−344.7±95.0)‰ with an uncertainty of (42.4±31.6)‰ for Spectralon Viewing Observation mode. In LA, the δD shows a seasonal cycle that is primarily driven by the change of atmospheric humidity. The temporal variabilities in δD data between CLARS-FTS and a collocated Total Carbon Column Observing Network (TCCON) observatory are highly correlated. The difference between CLARS and TCCON δD retrievals can primarily be attributed to the difference in their observation geometries. We conclude that the HDO and δD measurements from CLARS-FTS provide high spatial and temporal resolution datasets for further study of hydrological processes in the LA megacity.

Subtropical anticyclones and midlatitude storm tracks are key components of the large-scale atmospheric circulation. Focusing on the southern hemisphere, the seasonality of the three dominant subtropical anticyclones, situated over the South Pacific, South Atlantic and South Indian Ocean basins, has a large influence on local weather and climate within South America, Southern Africa and Australasia, respectively. Generally speaking, sea level pressure within the southern hemisphere subtropics reaches its seasonal maximum during the winter season when the southern hemisphere Hadley Cell is at its strongest. One exception to this is the seasonal evolution of the South Pacific subtropical anticyclone. While winter maxima are seen in the South Atlantic and South Indian subtropical anticyclones, the South Pacific subtropical anticyclone reaches its seasonal maximum during local spring with elevated values extending into summer. In this study we investigate the hypothesis that strength of the austral summer South Pacific subtropical anticyclone is largely due to heating over the South Pacific Convergence Zone. Using reanalysis data, and AGCM added cooling and heating experiments to artificially change the strength of diabatic heating over the South Pacific Convergence Zone, our results show that increased heating triggers a Rossby wave train over the Southern Hemisphere mid-latitudes by increasing upper-level divergence. The propagating Rossby wave train creates a high-low sea level pressure pattern that projects onto the center of the South Pacific Subtropical Anticyclone to intensify its area and strength. The southern hemisphere storm tracks also shift poleward due to increased heating over the South Pacific Convergence Zone.