High-throughput phenotyping (HTP) has the potential to revolutionize plant breeding by providing scientists with exponentially more data than was available through traditional observations. Even though data collection is rapidly increasing, the optimum use of this data and implementation in the breeding program has not been thoroughly explored. In an effort to apply HTP to the earliest stages of a plant breeding program, we extended field-based HTP pipelines to evaluate and extract data from spaced single plants. Using a panel of 340 winter wheat lines planted in full plots and grid-spaced single plants for two growing seasons, we evaluated relationships between single plants and full plot yields. Normalized difference vegetation index (NDVI) was collected multiple times through the growing season using an unmanned aerial vehicle. NDVI measurements during grain filling stage from both single plants and full plots were typically positively associated with their respective grain yield with correlation ranging from -0.22 to 0.74. The relationship between single plant NDVI and full plot yield, however, was variable between seasons ranging from -0.40 to 0.06. A genome wide association analysis (GWAS) identified the same significant markers for traits measured in both full plots and single plots, but also displayed variability between growing seasons. Strong genotype by environment interactions could impede selection on quantitative traits, yet these methods could provide an effective tool for plant breeding programs to quickly screen early-generation germplasm especially for qualitative traits. Effective use of early-generation, affordable HTP data could improve overall genetic gain in plant breeding.

Physical soil crusts will form on most soils during and after rainfall and it has important effects on the runoff and sediment on slopes. However, objective and effective methods for quantifying the characteristics of physical soil crusts (such as the thickness) are not currently available. We used a new method for determining the thickness of physical soil crusts based on X-ray computed tomography (CT) in order to quantify the thickness of the structural crust (SC) and depositional crust (DC) for two typical erosive soils comprising granite red soil (GRS) and Quaternary red clay (QRC) in the red soil region of southern China. The pores in the GRS and QRC were characterized as finely and densely spatially distributed, with an average porosity of 15.47% and a range of 1.66–28.83%. The soil porosity increased rapidly in the 0–3 mm depth, but the porosity of the SC and DC soil samples generally decreased or was stable in the 3–30 mm depth. The average thickness of the soil crust was 1.31 mm, and the average thicknesses of SC and DC were 1.16 and 1.46 mm, respectively. The thickness of SC of GRS decreased with the slope, whereas the thickness of DC of QRC generally increased with the slope. The thickness of SC increased with runoff yield and its contribution rate to the runoff cannot be neglected. The study provides a method for the objective quantification of physical soil crust and can deepen the research on slope erosion process and influencing factors.

Episodic volcanic eruptions are often either not considered in future climate projections, or represented in terms of a constant volcanic forcing. This conventional representation of volcanic eruptions in climate models does not account for how climate change might affect the dynamics of volcanic plumes and the stratospheric sulfate aerosol lifecycle and, ultimately, volcanic radiative forcing. The height of eruptive plumes is indeed sensitive to atmospheric conditions such as stratification and the strength of wind. In addition, climate change will affect tropopause height, the Brewer Dobson circulation and stratospheric temperatures which all govern volcanic sulfate aerosol cycle. A recent study showed that for tropical eruptions, these changes would either lead to a dampening or an amplification of volcanic forcing depending on the eruption intensity. In this study, to account for volcano-climate interactions in future climate projections, we present a new modelling approach through coupling a 1-D plume-rise model (Plumeria) with an Earth System model (UKESM). In this approach, each time a volcanic eruption of prescribed intensity (i.e., mass eruption rate) and SO2 mass occur, atmospheric conditions simulated by UKESM are passed interactively to Plumeria which then computes the corresponding height of eruptive plumes. Volcanic SO2 is then injected at the same height in UKESM stratospheric aerosol module. With this new methodology, plume heights are consistent with the climate conditions simulated by UKESM. Our study thus represents a first attempt to consider the impacts of climate change on volcanic eruptions in an Earth System model, which allows us to better evaluate the climate impacts of volcanoes under global warming.

Different functions are used to account for turbulence in the atmospheric boundary layer for different stability regimes. These functions are one of the sources for differences among different atmospheric models’ predictions and associated biases. Also, turbulence is underrepresented in some of the resistance formulations. To address these issues with dry deposition, firstly we take advantage of three-dimensional (3-D) aspects of turbulence in estimating resistances by proposing and validating a 3-D turbulence velocity scale that is relevant for different stability regimes of boundary layer. Secondly, we hypothesize and prove that 3-D sonic anemometer measured friction velocity, used in 0-D and 1-D models, can be effectively replaced by the new turbulence velocity scale multiplied by the von Karman constant. Finally, we (1) evaluate a set of resistance formulations for ozone (O3), based on the 3-D turbulence velocity scale; and (2) intercompare estimations of such resistances with those obtained using the existing formulations and also evaluate simulated O3 fluxes using a single-point dry deposition model against long-term observations of O3 fluxes at the Harvard Forest site. Results indicate that the new resistance formulations work very well in simulating surface latent heat and O3 fluxes when compared to respective existing formulations as well as measurements at decadal time scale. Findings from this research may help to improve the capability of dry deposition schemes for better estimation of dry deposition fluxes and create opportunities for the development of a community dry deposition model for use in regional/global air quality models.

An accurate assessment of hydrometeorological variables/ observations over an urban area is crucial to policy-makers and civic bodies to address an extensive range of water resources and environmental problems for informed decision-making related to the water distribution system and drainage networks. This necessitates the establishment of hydrometeorological monitoring networks that can efficiently obtain consistent and reliable information about the spatiotemporal variability of multiple hydrometeorological observations while being economically sustainable. However, the urban catchments especially in underdeveloped and developing countries are often subjected to spatial, environmental as well as monetary limitations which hinders the application of conventional approaches followed to set up the hydrometeorological networks. With this context, we propose a novel rationalization framework to record numerous hydrometeorological variables and acquire maximum information at an optimal cost. We have attempted to combine a multivariate statistical technique, Principal Component Analysis (PCA) with a multi-attribute decision-making method, Technique for Order of Preference by Similarity to Ideal Solutions (TOPSIS) to rank the significant hydrometeorological stations of an existing Automatic Weather Stations (AWS) network. It is observed that the set of rationalized AWS network obtained from this framework can capture the spatiotemporal information of the hydrometeorological variables considered in this study as efficiently as the entire AWS network. Additionally, the comparison of flood inundation and hazard maps derived from a 3-way coupled hydrodynamic flood modeling framework for the rationalized and original network also reflects its credibility to capture the flooding characteristics for the catchment. This proposed framework has been applied over Mumbai city, India, a major flood-prone area, and is characterized by high spatiotemporal variability of hydro-meteorological observations and space constraints due to dense population. This framework is generic and can be employed to reevaluate the prevailing hydro-meteorological networks in other catchments and help in the reduction of the maintenance cost while efficiently capturing the variability of observations.

Magnitude of atmospheric turbulence, a key driver of several processes that contribute to aerosol (i.e., particle) deposition, is typically underrepresented in current models. Various formulations have been developed to model particle dry deposition; all these formulations typically rely on friction velocity and some use additional ad hoc factors to represent enhanced impacts of turbulence. However, none were formally linked with the three-dimensional (3-D) turbulence. Here, we propose a set of 3-D turbulence-dependent resistance formulations for particle dry deposition simulation and intercompare the performance of new resistance formulations with that obtained from using the existing formulations and measured dry deposition velocity. Turbulence parameters such as turbulence velocity scale, turbulence factor, intensity of turbulence, effective sedimentation velocity, and effective Stokes number are newly introduced into two different particle deposition schemes to improve turbulence representation. For an assumed particle size distribution, the newly proposed schemes predict stronger diurnal variation of particle dry deposition velocity and are comparable to corresponding measurements while existing formulations indicate large underpredictions. We also find that the incorporation of new turbulence parameters either introduced or added stronger diurnal variability to sedimentation velocity and collection efficiencies values, making the new schemes predict higher deposition values during daytime and nighttime when compared to existing schemes. The findings from this research may help improve the capability of dry deposition schemes and help fostering the community dry deposition modeling system for use in regional and global models.

Serpentine minerals exert important controls on the physical properties of ultramafic rocks and have the potential to influence deformation phenomena in fault zones and to control the release of water in subducted slabs. Sheet serpentine generally, and lizardite and amesite specifically, can adopt alternative crystallographic stacking arrangements called polytypes. Polytypism has been extensively studied in fully ordered crystals, but it remains largely enigmatic in the more common semi-disordered crystals that in long-range analyses such as X-ray diffraction only exhibit random combinations of 0b and ±1/3b interlayer shifts. To date, atomic-resolution imaging to identify locally ordered polytypes has been precluded by the beam-sensitive nature of this hydrous magnesium silicate mineral. Here, we employed low-dose high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to study the polytypic structure of semi-disordered lizardite and amesite. Because the electron dose was as low as ~6000 e-/Å 2 , it was possible to directly resolve oxygen atomic columns and all the cations with a resolution of ~1 Å and reveal the short-range order. For lizardite, we identified long-period non-standard polytypes, including examples with 3, 4, 8 and 9 layers stemming from the ordering of the octahedral tilt along the a-axis. For amesite, we found short-range ordered polytypes with periodicities of up to 42 Å stemming from the ordering of interlayer shifts along the b-axis. The resolution was sufficient to determine the relative abundance of 6R 2 , 6R 1 , 2H 1 and 2H 2 polytypes in amesite to be 46.1%, 29.6%, 7.7% and 1.9% respectively. This is contrary to the expectation that the most common form of amesite is the 2H 2 polytype, which may be more likely to form macroscopic crystals suitable for conventional X-ray diffraction-based study. We conclude that HAADF-STEM methods open the way for characterization of beam sensitive minerals and to resolve the structural details of less well ordered (but possibly more abundant) minerals at unit-cell scale.

Topographic flexure in response to vertical loads reveals key lithospheric properties, including elastic thickness and the heat flow from the interior. Flexural stresses may also control volcano morphology. One previous study predicted that steep-sided domes on Venus usually form where the elastic thickness is ~15-40 km. We surveyed flexural signatures around steep-sided domes and confirmed this hypothesis. We determined elastic thickness from topographic profiles with a curve-fitting algorithm and a plate bending model in Cartesian and axisymmetric geometry. We used a yield stress envelope to convert elastic thickness and plate curvature into mechanical thickness and surface heat flow. The average elastic thickness for domes not near coronae is ~30 km, corresponding to a heat flow of ~60 mW/m2. Coronae on Venus are typically associated with elastic thicknesses of <10-15 km. Domes near coronae yielded elastic thicknesses in this range, and higher heat flows than domes not near coronae.

Topography is critical information for water resources management in lakes, and remote sensing provides a unique opportunity to estimate it in ungauged regions. We introduce here a new method which estimates near shore topography of water bodies based on a flood frequency map and time series of water levels by assuming the equivalence between flood frequency and water level exceedance probability at a given area. Test cases are performed for two lakes and 12 hydropower reservoirs in Brazil using the proposed Flood2Topo app. This new application generates the bottom level pixel by pixel and a level-area-active storage relationships directly from the topography map, without the need to fit functions. Flood extent estimates from the Landsat based JRC Global Surface Water (GSW) dataset, current state-of-the-art, were used to run Flood2Topo, together with water levels from satellite altimetry and in-situ gauges. Results show bottom level root mean square deviation (RMSD) values of 18.5 cm and 146 cm for Lake Poopó (Bolivia) and Lake Curuai (Amazon basin), respectively. For reservoir active storage, RMSD normalized values ranged from 2% to 11.09% for 11 reservoirs (average NRMSD of 6.39 %). The method can be applied to any area seasonally flooded, for instance, it is applicable in 35.8 % (86%) of the global water surface area mapped by occurrence map from GSW dataset, when considering the number of pixels with occurrence between 0 and 95% (99%) over 35 years. This is a promising tool for obtaining data for hydrodynamic simulations and monitoring of ungauged water bodies.

The Walker circulation (WC) responds to CO2 forcing at both short and long timescales. The fast response accounts for a substantial portion of the total responses, but its mechanisms, particularly those pertaining to air-sea interactions remain unclear. We found the initial land-sea warming contrast drives the anomalous easterlies (westerlies) in the Pacific warm pool (cold tongue) region. When the anomalous easterlies dominate, a Bjerknes feedback is triggered, leading to fast Equatorial Pacific cooling and WC strengthening. Otherwise, the Central and Eastern Pacific warms via the wind-SST-evaporation feedback and a weakened upwelling, leading to WC weakening. While the WC weakens and the equatorial Pacific warms eventually, the transition into the slow response differs among climate models. If initial cooling happens, the Equatorial warming emerges as the Bjerknes feedback wanes and the subsurface warm water accumulated in the warm pool migrates eastward via downwelling oceanic Kelvin waves.

Reliable climate projections are essential for adaptation and mitigation planning. We compare CMIP6 projections for temperature and precipitation to CMIP5 for northern Europe, central Europe and the Mediterranean. The CMIP6 ensemble shows an increased projected summer warming compared to CMIP5. Central Europe was also found to have a stronger drying trend in the summer months in CMIP6. We show that warmer projected summer temperatures are largely driven by CMIP6 sampling higher global climate sensitivities, with broadly similar regional responses to these. For those interested in central estimates of European changes, CMIP6 does not change the existing CMIP5 picture but better samples higher end change for more risk adverse users. However, regional sensitivity is important in central Europe where it accounts for roughly 40$\%$ of the differences between ensembles in projected regional temperature. This analysis raises an important question about whether CMIP6 can be considered to supersede CMIP5, or supplement it

The transport and accumulation of moisture played an essential role in the extremely heavy rainfall of July 2020 in Japan. To better understand this event in terms of moisture sources and transport routes, backward particle trajectory analysis was conducted. We found two major moisture sources: transport from the tropics and uptake from the subtropics. A narrow moisture channel was found along the edge of the western Pacific Subtropical High (WPSH), transporting the moisture to the Baiu front. However, most moisture from the tropics was lost due to precipitation, and their contributions were reduced to about 15%. In contrast, the subtropical regions contributed over 80% moisture via evaporation and lower tropospheric convection. Among those regions, the western Pacific contributed the most (33 %). This study highlights the role of WPSH in moisture transport, and also demonstrated the importance of the moisture uptake during the transport.

Shipping activities are a major source of air pollution in port cities with the expected high population of port workers and related workforce being chronically exposed to air pollutants such as carbon monoxide (CO) and suspended particulate matters (SPM: PM 10). These two priority air pollutants in addition to relative humidity (RH) and wind speed were monitored every month over a period of four years at Tin Can, Apapa Lagos, being the location of the busiest port in Nigeria. Results indicate that the highest monthly mean concentrations recorded throughout the study were 3.31 ppm and 258.6 µg/m 3 for CO and PM 10 respectively. While the value of CO was within the recommended threshold limits by the World Health Organization (WHO) and the Federal Ministry of Environment (FMEnv), the PM 10 exceeded the WHO specified limit of 50 µg/m 3 for a-24 h period of exposure. The ambient concentrations of the two air pollutants were higher in the dry season than their concentrations in rainy season. However, a significant seasonal variation was observed in the ambient concentrations of PM 10. Regression analysis shows that wind speed contributes significantly (p<0.05) to the detectable concentration of CO while RH had no significant influence on CO availability in the study area. Conversely, RH significantly influenced the concentration of PM 10 with a direct positive correlation between the climatic index and particulate matter while wind speed had no significant influence on suspended particles. The study established that there is no risk of acute human exposure to the air pollutants in the ports area. In spite of the low ambient concentrations recorded during the study, chronic exposure of workers or residents in port areas has its long-term health implications. Further study is required to monitor the indoor concentrations of these pollutants, which were possibly dispersed by wind from the lagoon and the ocean.

Understanding the global soil moisture (SM) dynamics and its governing controls beyond Darcy Scale is critical for various hydrologic, meteorological, agricultural, and environmental applications. In this study, we parameterize the pathways of the seasonal drydowns using global surface soil moisture (θ_RS) observation from SMAP satellite (between 2015 and 2019) at 36km X 36km. We develop a new data-driven non-parametric approach to identify the canonical shapes of θ_RS drydown, followed by a non-linear least-squares parameterization of the seasonal drydown pathways at each SMAP footprint. The derived parameters provide the effective soil water retention parameters (SWRPeff), land-atmospheric coupling strength, soil hydrologic regimes for SMAP footprint. Depending on footprint heterogeneity, climate and season, the characteristics curves comprising different drydown phases are discovered at SMAP footprints. Drydown curves respond to the within-footprint changes in the meteorological drivers, land-surface characteristics and the soil-vegetative and atmospheric dynamics. Drydown parameters display high inter-seasonal variability, especially in grasslands, croplands and savannah landscapes due to significant changes in the landscape characteristics and moisture patterns at the subgrid-scale. Soil texture exert influence on the characteristics soil water retention and drydown parameters only when the footprint mean θ_RS is low, specifically in arid and sparsely vegetated regions. The influence of soil texture on the inter-seasonal variability of SWRPeff is low compared to landuse and climate at RS-footprint scale. The global understanding of characteristics SM drydown features at SMAP footprints provides a significant step towards a scale-specific, effective soil hydrologic parameterization for various applications.

We identified 38 cyclonic eddies (CEs) using satellite altimetry that traversed Station ALOHA in the North Pacific Subtropical Gyre from 1993 to 2018. We separated CE-induced particle export, measured using free floating sediment traps deployed at 150 m, at the center versus the edge and with time since eddy evolution. The fluxes of particulate carbon, nitrogen and biogenic silica (PC, PN and BSi) varied significantly within and among individual eddies depending on season and age. On annual time scales, there was little to no significant PC (1.1-1.3-fold) or PN (1.1-1.2-fold) CE enhancement relative to non-eddy and non-bloom periods. In contrast, BSi fluxes were elevated by an average of 200 {plus minus} 80% (1.3-2.7-fold). Our results confirm that CEs more efficiently export BSi relative to C, suggesting that these elements, central to marine food webs, differ in their mechanisms of export to depth and may contribute to long term ecological change.

NASA launched its second Earth observing laser altimeter in 2018 with mission objectives of studying the changes in our climate by monitoring global elevations, particularly in the polar regions. Since the mission is focused on generating accurate elevations and elevation change, the geolocation (or geodetic position) of the measurements are of upmost importance to each of the scientific disciplines supported by these observations. Geolocation validation is required to ensure that the mission is meeting its objectives with the appropriate level of geolocation accuracy. One validation technique uses small optical reflectors placed in a specific pattern along one or more satellite ground-tracks. The optics provide a unique signal back to the satellite that can be used to compare the geolocation of these returns in the data to the known position on the surface. Results of the position comparison indicate the measurement locations are accurate to within 3.5 m with a standard deviation of 1.6 m. They also provide a method for determining a representative footprint diameter using geometric analysis, which resulted in an average value of 10.9 m ±2.1 m.

The Advanced Topographic Laser Altimetry System (ATLAS) onboard the NASA Ice, Cloud and land Elevation Satellite-2 (ICESat-2) is the newest and most recent Earth observing satellite for global elevation studies. The primary objectives for ICESat-2 follow that of its predecessor, ICESat, and focus on providing cryospheric measurements to determine ice sheet mass balance, and monitor both sea ice thickness and extent. However, the global observations support secondary science objectives such as biomass estimation, inland water elevation, sea state height and aerosol concentrations. In all, ATLAS measurements support 7 along-track geophysical products with multiple gridded products to provide regional and global change detection for seasonal and annual cycles. Since the launch of ICESat-2, the instrument has operated nominally and collected more than a trillion measurements. This paper provides an overview of the mission, a description of the operational components that support the altimeter products for science discovery and on-orbit observatory performance.

Earthquake clustering is a relevant feature of seismic catalogs, both in time and space. Several methodologies for earthquake cluster identification have been proposed in the literature in order to characterise clustering properties and to analyse background seismicity. We consider two recent data-driven declustering techniques, one is based on nearest-neighbor distance and the other on a stochastic point process. These two methods use different underlying assumptions and lead to different classifications of earthquakes into background events and secondary events. We investigated the classification similarities by exploiting graph representations of earthquake clusters and tools from network analysis. We found that the two declustering algorithms produce similar partitions of the earthquake catalog into background events and earthquake clusters, but they may differ in the identified topological structure of the clusters. Especially the clusters obtained from the stochastic method have a deeper complexity than the clusters from the nearest-neighbor method. All of these similarities and differences can be robustly recognised and quantified by the outdegree centrality and closeness centrality measures from network analysis.