Climate change is expected to alter the conditions in which plants develop. The mechanisms by which plants can adapt to changing conditions must be studied in terms of the magnitude of their response and the implications for productivity. Recognizing wheat as a main crop sustaining global livelihoods as well as the need for long-term adaptation strategies to climate change, this work assesses the response of wheat stomatal conductance (gs) to changes in vapor pressure deficit (VPD) associated with global warming in three future scenarios from the Coupled Model Inter-comparison Project phase 6 (CMIP6). We used multiple datasets and a modeling approach to estimate gs as a function of atmospheric variables only over global wheat areas. The results show a sustained increase in both temperature and VPD in the historical period and future CMIP6 scenarios, and a generalized decrease in wheat gs that becomes clear from around the year 2040. The pattern of change is spatially divergent, with areas that present increases in relation to the historical average, which mostly concentrate towards high latitudes. Negative trends in gs area mainly observed in North America, Southern Europe, North Africa and Asia. Notwithstanding, the proportion of areas of positive change in gs tend to decrease in warmer climate scenarios. gs is more sensitive to changes in VPD than to global warming, which implies that the areas of negative trends in gs could expand to higher latitudes. These results may assist the regional focus of long-term wheat adaptation programs to climate change.

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Large-scale convection associated with the Madden-Julian Oscillation (MJO) initiates over the Indian Ocean and propagates eastward across the Maritime Continent (MC). Over the MC, MJO events are generally weakened due to complex interactions between the large-scale MJO and the MC landmass. The MC barrier effect is responsible for the dissipation of 40-50\% of observed MJO events and is often exaggerated in weather and climate models. We examine how MJO propagation over the MC is affected by two aspects of the MC - its land-sea contrast and its terrain. To isolate the effects of mountains and land-sea contrast on MJO propagation, we conduct three high-resolution coupled atmosphere-ocean model experiments: 1) control simulation (CTRL) of the 2011 November-December MJO event, 2) flattened terrain without MC mountains (FLAT), and 3) no-land simulation (WATER) in which the MC islands are replaced with 50 m deep ocean. CTRL captures the general properties of the diurnal cycle of precipitation and MJO propagation across the MC. The WATER simulation produces a more intense and smoother-propagating MJO compared with that of CTRL. In contrast, the FLAT simulation produces much more convection and precipitation over land (without mountains) than CTRL, which results in a stronger barrier effect on MJO propagation. The land-sea contrast induced land-locked convection weakens the MJO’s convective organization. The land-locked convective systems over land in FLAT are more intense, grow larger, and last longer, which is more detrimental to MJO propagation over the MC, than the mountains that are present in CTRL.

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In light of the increased availability of massive point cloud data, acquired by advanced remote sensing techniques, software tools for their efficient representation and processing are needed. Triangulated Irregular Networks (TINs) are an effective way to represent point clouds without the need to interpolate them into raster-based terrain models. However, GISs tools have limited support for TINs due to large storage costs. For this reason, we present the Terrain Trees Library (TTL), a library for terrain analysis based on a new scalable data structure named Terrain trees. A Terrain tree relies on a hierarchical spatial index where each leaf block encodes the minimum amount of connectivity information for the TIN. Connectivity relations among the elements of the TIN are extracted locally within each leaf block at run-time and discarded when no longer needed. Moreover, the hierarchical domain decomposition makes the library well-suited for parallel processing. TTL contains a kernel for connectivity and spatial queries, and modules for extracting morphological features, including edge and triangle slopes, roughness, curvature. It also contains modules for extracting topological structures, like critical point, critical net, watershed segmentation, based on the discrete Morse gradient, and a technique for multivariate data visualization, which enables the analysis of multiple scalar fields defined on the same terrain. To evaluate the effectiveness and scalability of TTL, we compared it against the most compact state-of-the-art data structure for TINs, the IA data structure. When encoded by Terrain trees, a TIN requires 36% less storage than when encoded by the IA data structure. Beyond this storage reduction, Terrain trees also show better performance than the IA data structure in most terrain analysis operations. This speedup is obtained since Terrain trees enable 57% to 72% faster extraction of the triangles incident in a vertex. Extracting the triangles incident in vertices as well as the adjacent vertices on the mesh is a key task in most terrain feature extraction operations on a TIN. Using Terrain trees, we achieved 36% to 55% less time consumption computing morphological features and 20% less time consumption computing the discrete Morse gradient than using the IA data structure.

Some oceanic and atmospheric flows may be modelled as equivalent-barotropic systems, in which the horizontal fluid velocity varies in magnitude at different vertical levels while keeping the same direction. The governing equations at a specific level are identical to those of a homogeneous flow over an equivalent depth, determined by a pre-defined vertical structure. Most oceanic studies using the equivalent-barotropic approach are focused on steady, linear formulations. In this work, the nonlinear, time-dependent model with variable topography is examined. To include nonlinear terms, we assume suitable approximations and evaluate the associated error in the dynamical vorticity equation. The model is solved numerically to investigate the equivalent-barotropic dynamics in comparison with a purely barotropic flow. We consider two problems in which the behaviour of homogeneous flows has been well-established either experimentally or analytically in past studies. First, the nonlinear evolution of cyclonic vortices around a topographic seamount is examined. It is found that the vortex drift induced by the mountain is modified according to the vertical structure of the flow. When the vertical structure is abrupt, the model effectively isolates the surface flow from both inviscid and viscous topographic effects (due to the shape of the solid bottom and Ekman friction, respectively). Second, the wind-driven flow in a closed basin with variable topography is studied (for a flat bottom this is the so-called Stommel problem). For a zonally uniform, negative wind-stress curl in the homogeneous case, a large-scale, anticyclonic gyre is formed and displaced southward due to topographic effects at the western slope of the basin. The flow reaches a steady state due to the balance between topographic, β, wind-stress and bottom friction effects. However, in the equivalent-barotropic simulations with an abrupt vertical structure, such an equilibrium cannot be reached because the forcing effects at the surface are enhanced, while bottom friction effects are reduced. As a result, the unsteady flow is decomposed as a set of planetary waves.

Imagery from the GOES series has been a key element of U.S. operational weather forecasting for four decades. While GOES observations are used extensively by human forecasters for situational awareness, there has been limited usage of GOES imager data in numerical weather prediction (NWP), and operational data assimilation (DA) has ignored cloud and precipitating pixels. The motivation of this project is to bring the benefits of GOES-R Series enhanced capabilities to advance convective-scale DA for improving convective-scale forecasts. We have developed a convolutional neural network (CNN) prototype, dubbed “GOES Radar Estimation via Machine Learning to Inform NWP (GREMLIN)” that fuses GOES-R Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) information to produce maps of synthetic composite radar reflectivity. We find that the ability of CNNs to utilize spatial context is essential for this application and offers breakthrough improvement in skill compared to traditional pixel-by-pixel based approaches. Making use of ABI spatial information potentially provides benefits over radiance assimilation approaches that are limited by saturation of radiances in pixels with precipitation. This presentation will briefly describe the GREMLIN model and characterize its performance across meteorological regimes. We are developing a dense neural network (DNN) to produce vertical profiles of radar reflectivity and latent heating based on the two-dimensional fields output from GREMLIN. The resulting three-dimensional fields of latent heating will be used to initialize NWP simulations of convective-scale phenomena. Another DNN will be developed to produce uncertainty estimates of latent heating for each pixel. Our approach for data assimilation will be described and is innovative in being the first-time machine learning (ML) will be used for the nonlinear latent heating observation operator in the NOAA hybrid Gridpoint Statistical Interpolation (GSI) and/or JEDI systems. The approach will provide all the elements of the Jacobian needed for GSI DA and has the advantage of automatically maintaining the tangent linear and adjoint models through finite difference mathematics.

We present a new open-source tool for magnetospheric computations, that is modelling of cosmic ray propagation in the geomagnetosphere, named the “Oulu - Open-source geomagneToSphere prOpagation tool” (OTSO). A tool of this nature is required in order to interpret experiments and study phenomena within the cosmic ray research field. Within this work OTSO is applied to the investigation several ground level enhancement events. Here, we demonstrated several applications of OTSO, namely computation of asymptotic directions of selected cosmic ray stations, effective rigidity cut-off across the globe at various conditions within the design, general properties, including the magnetospheric models employed. A comparison and validation of OTSO with older widely used tools such as MAGNETOCOSMICS was performed and good agreement was achieved. An application of OTSO for providing the necessary background for analysis of two notable ground level enhancements is demonstrated and the their spectral and angular characteristics are presented.

Sediment flows generate ground vibrations by exerting basal force fluctuations on the riverbed, which motivates the use of seismology to indirectly measure flow properties. Linking the force fluctuations and properties of highly concentrated sediment flows, however, remains particularly challenging due to complexities that arise from grain-to-grain interactions. Here we conduct downscaled flume experiments designed to investigate the influence of grain scale processes on the generation of force fluctuations for stratified sediment flows associated with significant grain sorting. We demonstrate that, under such flow conditions, the amplitude of force fluctuations decreases as the volumetric solid concentration increases. We suggest that this dependency reflects the negative relationship between volumetric solid concentration and particle agitation, which in turn controls the amplitude of force fluctuations. We therefore advance that volumetric solid should be incorporated in seismic models as a key parameter describing the particle agitation of highly concentrated sediment flows.

Low soil temperature stress is a critical factor affecting the root water uptake (RWU) rate of plants. In current land surface models, the RWU amount is determined by the soil water extracted from different soil layers, which calculates by the relative soil water availability and the root fraction of each layer in the rooting zone. The effect of low soil temperature stress is not considered, which may produce biases in the simulation of transpiration. In this study, with the utilization of the in-situ observation data from three FLUXNET sites, we introduced three functions to represent the low soil temperature stress in the Common Land Model (CoLM) and evaluated their effects on the energy fluxes simulation. Then the three low soil temperature stress functions were also evaluated in the global offline simulations by using the FLUXNET-MTE (multi-tree ensemble) data. Results show that the default CoLM overestimates the latent heat flux but underestimates the sensible heat flux in the local spring and early summer at three study sites. By incorporating the low soil temperature stress function into CoLM, the bias in energy flux simulation is significantly reduced. The global offline simulations indicate that considering the effect of low soil temperature stress can improve the model performance on the simulating of the latent heat flux in those high latitude areas. Therefore, we recommend incorporating the effect of low soil temperature stress into land surface models, which is beneficial to increasing the reliability of the models’ results, especially over the cold regions.

Interferometric synthetic-aperture radar (InSAR) interferograms contain valuable information about the fault systems hidden beneath the surface of the Earth. In a new approach, we aim to fit InSAR ground deformation data using a volumetric distribution of multiple seismic point sources whose parameters are found by a genetic algorithm. The resulting source distribution could provide another useful tool in solving the difficult problem of accurately mapping earthquake faults. To test the algorithm, we first apply it to synthetic data, followed by applications to an ALOS-2 InSAR interferogram. We report first results and discuss advantages and disadvantages of this approach.

We conducted systematic elements and boron isotope studies on the tourmalines from a single pegmatite vein of the Qinghe pegmatite field (NW China), aiming to reveal its magmatic-hydrothermal evolution and implications for Li mineralization. The pegmatite vein is barren, intruded into the Paleozoic mica schists, and texturally divided into a border zone, a transition zone and a core zone. Tourmalines occur in all these zones, and they commonly have late-stage hydrothermal tourmaline overgrowths. All tourmalines belong to the alkali group, but show varied Mg/(Mg+Fe) ratios (0.39-0.66), with the border and transition zone tourmalines belonging to schorl, while the core zone and hydrothermal tourmalines to dravite. Most tourmalines follow the (Na+Mg) (Al+Xvac)-1, FeMg-1 and MnMg-1 exchange vectors. The core zone tourmalines, however, show positively correlated FeOt and MgO, and negatively correlated FeOt and Al2O3, suggesting a Fe3+Al-1 substitution for them, which could be related to a rise of fO2. Thus, tourmaline FeAl-1 correlation could be reflective of the redox state of pegmatite system. The elevated fO2 can be linked to concentration of aqueous fluid during pegmatite evolution. Moreover, the core zone tourmalines differ from other tourmalines by their positive Eu anomalies, reflecting an increased polymerization of Eu2+-Al-Si complexing in the zone. The border zone tourmalines have δ11B = -14.0 ~ -12.7‰, similar to the transition zone (-13.9 ~ -12.1‰). The core zone and hydrothermal tourmalines show slightly lower δ11B values (-14.4‰ ~ -13.3‰). The commonly light B, along with low Li (<120 ppm), of the tourmalines from barren pegmatite are in contrast to the relatively heavy B (-6.0 ~ -9.0‰) and high Li (>6000 ppm) of tourmalines from global Li-mineralized pegmatite, which is significant in Li mineralization prospect.

This study presents an improved approach to common-conversion point stacking of converted body waves that incorporates scattering kernels, accurate and efficient measurement of stack uncertainties, and an alternative method for estimating free surface seismic velocities. To better separate waveforms into the P and SV components to calculate receiver functions, we developed an alternative method to measure near surface compressional and shear wave velocities from particle motions. To more accurately reflect converted phase scattering kernels in the common-conversion point stack, we defined new weighting functions to project receiver function amplitudes only to locations where sensitivities to horizontal discontinuities are high. To better quantify stack uncertainties, we derived an expression for the standard deviation of the stack amplitude that is more efficient than bootstrapping and can be used for any problem requiring the standard deviation of a weighted average. We tested these improved methods on Sp phase data from the Anatolian region, using multiple bandpass filters to image velocity gradients of varying depth extents. Common conversion point stacks of 23,787 Sp receiver functions demonstrate that the new weighting functions produce clearer and more continuous mantle phases, compared to previous approaches. The stacks reveal a positive velocity gradient at 80-150 km depth that is consistent with the base of an asthenospheric low velocity layer. This feature is particularly strong in stacks of longer period data, indicating it represents a gradual velocity gradient. At shorter periods, a lithosphere-asthenosphere boundary phase is observed at 60-90 km depth, marking the top of the low velocity layer.

Because of their limited spatial resolution, numerical weather prediction and climate models have to rely on parameterizations to represent atmospheric turbulence and convection. Historically, largely independent approaches have been used to represent boundary layer turbulence and convection, neglecting important interactions at the subgrid scale. Here we build on an eddy-diffusivity mass-flux (EDMF) scheme that represents all subgrid-scale mixing in a unified manner, partitioning subgrid-scale fluctuations into contributions from local diffusive mixing and coherent advective structures and allowing them to interact within a single framework. The EDMF scheme requires closures for the interaction between the turbulent environment and the plumes and for local mixing. A second-order equation for turbulence kinetic energy (TKE) provides one ingredient for the diffusive local mixing closure, leaving a mixing length to be parameterized. A new mixing length formulation is proposed, based on constraints derived from the TKE balance. It expresses local mixing in terms of the same physical processes in all regimes of boundary layer flow. The formulation is tested at a range of resolutions and across a wide range of boundary layer regimes, including a stably stratified boundary layer, a stratocumulus-topped marine boundary layer, and dry convection. Comparison with large eddy simulations (LES) shows that the EDMF scheme with this diffusive mixing parameterization accurately captures the structure of the boundary layer and clouds in all cases considered.

The climatology of atomic oxygen (O) in the MLT (mesosphere and lower thermosphere) is balanced by O production via photodissociation in the lower thermosphere and recombination in the upper mesosphere. The motivation here is to establish the intra-annual variation in the eddy diffusion coefficients and eddy velocity in the MLT based on the constituent climatology of the region. The analysis method, originally developed in the 60’s (Colegrove et al. 1965), was refined for a study of MLT global inter-annual variations in global mean values (Swenson et al. 2018, 2019, respectively) ,(S19). In the this study, the intra-annual cycle was divided into twenty-six (two-week) periods for each of three zones, the northern hemisphere (NH, 15 to 55 degrees ), southern hemisphere (SH, -15 to -55 degrees ), and the equatorial region (EQ, 15 to -15 degrees ). Sixteen years of SABER O density measurements (2002-2018) and MSIS 2.0 model N , O and T profiles (80-96 km) were determined for each of the periods and zones for determination of O eddy diffusion velocities and fluxes. Atomic oxygen diffusive fluxes ([O]*v, 80-96 km) are balanced by the continuity of chemical loss, but the intra-annual variation of k$_{zz}$ (determined from v ) and [O] are determined separately. The major findings include: 1) A dominant AO below 87 km in the NH and SH zones, with the largest variation in amplitude between winter and summer at 83 km. 2) A dominant SAO at all altitudes (80-96 km) in the EQ zone. 3) Intra-annual variability in the global average [O] and k$_{zz}$ contribute to variability of O eddy transport in the MLT.

Large earthquakes transfer stress from the shallow lithosphere to the underlying viscoelastic lower crust and upper mantle, inducing transient creep during the postseismic interval. Recent experiments on olivine have provided a new rheological model for this transient creep based on accumulation and release of back stresses among dislocations. Here, we test whether natural rocks preserve dislocation-induced stress heterogeneity consistent with the back-stress hypothesis by mapping olivine from the palaeosubduction interface of the Oman-UAE ophiolite with high-angular resolution electron backscatter diffraction. The olivine preserves heterogeneous residual stresses that vary in magnitude by several hundred megapascals over length scales of a few micrometres. Large stresses are commonly spatially associated with elevated densities of geometrically necessary dislocations within subgrain interiors. These spatial relationships, along with characteristic probability distributions of the stresses, confirm that the stress heterogeneity is generated by the dislocations and records their long-range elastic interactions. Images of dislocations decorated by oxidation display bands of high and low dislocation density, suggesting that dislocation interactions contributed to organisation of the substructure. These results support the applicability of the back-stress model of transient creep to deformation in the mantle portion of plate-boundary shear zones. The model predicts that rapid stress changes, such as those imposed by large earthquakes, can induce order-of-magnitude changes in viscosity that depend nonlinearly on the stress change, consistent with inferences of mantle rheology from geodetic observations.

High resolution maps of seismic attenuation parameters in Taiwan have been obtained by using a modified ”Multiple Lapse Time Window Analysis’ (MLTWA). At most of the stations in porous sedimentary and highly faulted areas in Taiwan, the conventional modeling of MLTWA based on the scalar theory of radiative transfer in a half-space with isotropic scattering fails to explain the spatio-temporal distribution of the whole S wavetrain. Using Monte Carlo simulations of wave transport, we demonstrate that this anomalous energy distribution in the coda may be modelled by multiple anisotropic scattering of seismic waves. In addition to the scattering quality factor Qsc, we introduce a parameter g (independant of Qsc) which determines the angular redistribution of energy upon scattering (scattering anisotropy). We determine the attenuation parameters Qsc-1, Qi-1 and g in three frequency bands (1-2, 2-4 and 4-8Hz). Overall, Taiwan is more attenuating than most orogens with a mean effective scattering loss (Qsc*)-1=Qsc-1(1-g) about 0.025 and a mean intrinsic absorption Qi-1 about 0.009 at 1.5Hz. Scattering loss (Qsc*)-1 varies over more than one order of magnitude across Taiwan while absorption fluctuations are about 30%. The more attenuating zones are the Coastal Range and the Coastal Plain where scattering dominates over absorption at low frequency, and inversely at high frequency. These regions are also characterized by strong backscattering (g<-0.85) at 1.5Hz and rather high VP/VS ratio. We speculate that the observed strong back-scattering at low frequency is related to strong impedance fluctuations in the crust induced by the presence of fluids.

Precise modeling of surface water quality requires transport theory consistent with observed data. Efforts to achieve model fits to river tracer test breakthrough curves (BTCs) have led to different approaches to the one-dimensional modeling of river corridor transport at the macroscale. The memory function model form practically generalizes most current approaches including the transient storage (TSM), multirate mass transfer, decoupled continuous time random walk, and time-fractional advection dispersion models. An alternative formulation of the memory function approach is the phase exposure-dependent exchange (PhEDEx) model, which is the TSM model that includes residence-time dependence of the rate coefficient for mass exchange from the hyporheic zone to the river. Using temporal moment analysis and numerical simulations, we explore the general consistency of the PhEDEx model with observed BTC data. With this approach the moments of the memory function can be estimated without requiring any prior information about the memory function form. We also examine means of estimating river/transport process parameters using the results of temporal moments analysis. The results show the failure of the PhEDEx model, and therefore the memory function approach, in capturing in particular the observed constancy of the BTC coefficient of skewness (CSK). The temporal moments equations can be applied as a useful tool to estimate some river/tracer test parameters such as the ratio of HZ cross-sectional area to the main flow cross-sectional area, which are time/cost consuming to measure. The applications of the analyses are demonstrated with some case studies.