Throughout history, pomologists have developed various trainings systems for temperate fruit trees to improve light interception, fruit yield, and fruit quality. To achieve this, these training systems enforce certain branch and canopy morphologies upon the tree. Quantifying architecture could aid the selection for trees that require less pruning or naturally excel in specific growing/training system conditions. Tree architecture is also directly associated with resource optimization, funneling what nutrients the plant absorbs into the most efficient, high-yielding configuration possible. In peaches [Prunus persica (L.) Batsch], branching indices (BIs) have been developed in attempts to quantify tree architecture. BIs can effectively focus on a particular area of tree architecture (e.g., an index focused on branching density, or BDi), producing quantitative measurements that can accurately represent a tree’s unique architecture. However, the required branching data to develop these indices is hard to collect. Historically, branching data has been collected manually. Often this process is tedious, time-consuming, and prone to human error. These barriers can be circumnavigated by utilizing 3D remote imaging technology, such as terrestrial LiDAR scanning (tLiDAR). To test this, young peach trees were scanned with 3D scanners and modeled using TreeQSM. This allowed us to collect branching data with which to calculate BDi values. Statistical analyses of BDi measurements from the 4 young trees will create a methodological pipeline with which mature and complex trees architectures may be simulated. These BDi values, either in young or adult trees, will be used to better phenotype trees’ architecture and to better select trees for further breeding and selection (i.e. future genomic studies - GWAS and novel QTL identification). Keywords: Plant Breeding, Computational Biology, Phenomics, Phenotyping, Bioinformatics, 3D modelling, tLiDAR

Critical research questions such as how geomorphic and sedimentary systems modulate sediment movements and what are the timing, controls, and duration of significant sediment transport and deposition over submillennial to millennial timescales are still poorly understood, especially in the semi-arid Southern California. Although several sediment tracing and chronometric methods are available to address these questions, we still do not know well about the dominant controls and durations of sediment transport from the upper catchment source to the downstream sink. To examine this issue, here we used luminescence ages from K-feldspar sand grains from the range-front nested alluvial fans to the ~12-km-downstream in the flood plains of the Mission Creek catchment, Southern California. From a total of 29 sediment samples with >1,400 single grain (175–215 µm sizes) luminescence ages, we identified at least six depositional periods both in the upstream and downstream deposits in the catchment with no significant lag during the Holocene. Additional six significant depositional periods are also identified during the late Pleistocene (since the last ~100 ka) in the upstream alluvial fan deposits. These depositional periods correspond reasonably well with the late Pleistocene and Holocene intervals of wetter-than-average climate conditions based on hydroclimatic proxies from nearby locations. We, therefore, reinforces the concept that climate, especially wetter intervals, likely plays the first-order control on significant sediment deposition on submillennial to millennial timescales in the Mission Creek catchment. We also applied a detailed multi-elevated-temperature post-IR IRSL (MET-pIRIR) dating and bleaching experiment to examine whether sediment migration from the upstream to the downstream produces any significant changes in luminescence measurement (equivalent dose) signals. Any substantial changes in MET-pIRIR signals will be used to quantify the sediment movement characteristics (i.e., repeated flooding and burial events) within the catchment system.

Joanmarie Del Vecchio1,2, Simon Zwieback3, Joel C. Rowland4, Roman A. DiBiase5,6, Marisa C. Palucis11Department of Earth Science, Dartmouth College, Hanover, NH, USA2Neukom Institute for Computational Science, Dartmouth College, Hanover, NH USA3Department of Geosciences, University of Alaska Fairbanks, Fairbanks, AK USA4Earth and Environmental Sciences Division, Los Alamos National Laboratory, NM USA5Department of Geosciences, Pennsylvania State University, University Park, Pennsylvania 16803, USA6Earth and Environmental Systems Institute, Pennsylvania State University, University Park, Pennsylvania 16803, USACorresponding author: Joanmarie Del Vecchio ([email protected])Key Points:Seasonal and long-term permafrost thaw change hillslope hydrology and erodibilitySatellites observe surface displacements concentrated in certain landscape positionsA conceptual model is proposed for hillslope-channel coupling in permafrost landscapes mediated by water tracksAbstractThe Arctic is experiencing rapid climate change, and the effect on hydrologic processes and resulting geomorphic changes to hillslopes and channels is unclear because we lack quantitative models and theory for landscape evolution in thawing permafrost. The presence of permafrost modulates water infiltration and flow and the stability of soil-mantled slopes, implying there should be a topographic “signature” of permafrost processes, including warming-driven disturbance. To inform predictions of hillslope-channel dynamics under changing climates, we examined soil-mantled hillslopes within a ~ 300 km2 area of the Seward Peninsula, western Alaska, where discontinuous permafrost is particularly susceptible to thaw and rapid landscape change. In this study we pair high-resolution topographic and satellite data to multiannual observations of InSAR-derived surface displacement over a five-year period to quantify spatial variations in topographic change across an upland landscape. We find that neither basin slope nor the presence of knickzones controls the magnitude of recent surface displacements within the study basin, as may be expected under conceptual models of temperate hillslope evolution. Rather, the highest displacement magnitudes tended to occur at the broad hillslope-channel transition zone. In this study area this zone is occupied by water tracks which are zero-order ecogeomorphic features that concentrate surface and subsurface flow paths. Our results suggest that water tracks, which we hypothesize occupy hillslope positions between saturation and incision thresholds, are vulnerable to warming-induced subsidence and incision. We expect gullying within water tracks to outpace infilling by hillslope processes, resulting in growth of the channel network under future warming.

We have equipped the unstructured-mesh global sea-ice and ocean model FESOM2 with a set of physical parameterizations derived from the single-column sea-ice model Icepack. The update has substantially broadened the range of physical processes that can be represented by the model. The new features are directly implemented on the unstructured FESOM2 mesh, and thereby benefit from the flexibility that comes with it in terms of spatial resolution. A subset of the parameter space of three model configurations, with increasing complexity, has been calibrated with an iterative Green’s function optimization method to test fairly the impact of the model update on the sea-ice representation. Furthermore, to explore the sensitivity of the results to different atmospheric forcings, each model configuration was calibrated separately for the NCEP-CFSR/CFSv2 and ERA5 forcings. The results suggest that a complex model formulation leads to a better agreement between modeled and the observed sea-ice concentration and snow thickness, while differences are smaller for sea-ice thickness and drift speed. However, the choice of the atmospheric forcing also impacts the agreement of FESOM2 simulations and observations, with NCEP-CFSR/CFSv2 being particularly beneficial for the simulated sea-ice concentration and ERA5 for sea-ice drift speed. In this respect, our results indicate that the parameter calibration can better compensate for differences among atmospheric forcings in a simpler model (i.e. sea-ice has no heat capacity) than in more energy consistent formulations with a prognostic ice thickness distribution.

There has been possible evidence from ground based telescopes for plumes of water emanating from Europa’s ice shell. Because of their potential connection to the subsurface ocean these plumes are of significant interest as targets for the in-situ instruments on upcoming NASA and ESA missions to the Jovian system. Their potential similarity to tidally-modulated plumes observed at Enceladus have led to speculation that the occurrence of these plumes could be predicted accurately enough to plan in-situ sampling. However, the plumes could be the result of stochastic processes releasing near surface water from the ice shell and may not occur during the missions at all. Better observational constraints on plume distribution, predictability, and character would provide critical information for planning operations and measurements on the upcoming missions to Europa. The aim of this study is to demonstrate capability of the Gemini Planet Imager (GPI) for this task, modeling the detectability of Enceladus-like plumes on the surface of Europa using polarimetry. The polarized signal from an Encleadus sized plume is approximated by Mie scattering from micron-scale ice particulates at 1.5 - 1.8 µm. Ground-based observations with a nearly automated facility such as GPI could allow daily searches for plumes and enable dramatically more informed mission planning, increasing the potential for habitability characterization and even potentially life detection.

Mountain ranges in seismically active regions often present vast numbers of deep-seated and voluminous landslides. In general, the comprehension of factors contributing to such slope failures can help better understand the dynamic history of a region. Here, we present the outcomes of our studies in the Buzau-Vrancea seismic region in the Romanian Carpathian Mountains, where massive slides are marked by “softened” hummocky morphologies that result from weathering and aging. The latter factors make it more difficult to understand the circumstances of slope failure development and to trace the limits between in-situ and displaced material. In particular, the uncertain subsurface structure of those large mass movements suggests the application of geophysical methods. We used several geophysical techniques, which allowed us to overcome limitations in terms of investigation depth and lateral resolution of single methods. Electrical resistivity measurements can be used to obtain lithological information, and to characterise the water content of the landslide deposits and of in situ rocks. On most sites, we combined electrical surveys with seismic methods: actively triggered seismic energy used for seismic refraction surveys - analyzed as 2D P-wave tomography (SRT) and as 1D MASW – together with passive methods using ambient noise, i.e. small-aperture seismic array and single station HVNR measurements. In contrast to P-wave velocity prospections, surface and shear wave velocity measurements are able to reveal deeper and lateral contrasts that are independent of the soils water content and thus useful to define the mechanical properties of complex slope deformations. Ambient noise array methods, in addition, generally allow very deep sounding. With this approach, we are able to distinguish the basal shearing horizon of the studied landslide, their volume, geometry, and general geomechanical parameters. The main focus of this work is on the combination of these methods, and on the advantage of interpreting these results in a full 3D geomodel of study sites based on the collected surface (UAV flights, LiDAR-DEMs) and geophysical subsurface data. The 3D geomodel will further be used as a basis for numerical calculations aiming at a back-analysis of the landslide development (in a static and possibly dynamic domain).

Recent studies have documented that the Madden-Julian Oscillation (MJO) has impacts in extreme dry/wet conditions over tropical regions and in atmospheric state. They are based, however, in correlation analysis, and therefore do not consider non-linear interactions nor they establish cause-effect relationships.In this study we introduce a generalization of the non-linear Granger causality (GC) test to identify causal relations between MJO and hydrological extremes. The method is able to identify causal relations under noisy, nonlinear and non-stationary scenarios. A probabilistic extension is also introduced where the causal test operates directly on the marginal likelihood (also called evidence) of the observations, which is analytic. We apply our proposed method to MJO and satellite-based soil moisture (SM) data, and revisit the global teleconnection patterns induced by MJO events. Since El Ni\~no Southern Oscillation (ENSO) is a modulating factor that can result in abnormal SM global distributions, we also include it in the analysis as a potential driver of SM variability. Including ENSO allows us to differentiate the effect of the MJO and ENSO on the global SM anomalies and to learn the causal graph of their cause-effect relationships, and also the mutual relation between MJO and ENSO extreme events.

The C isotopic composition in macroalgae (δ13C) is highly variable and its prediction is very complex relative to terrestrial plants. To contribute to the knowledge on the variations and determinants of δ13C-macroalgal, we analyzed a large stock of specimens varying in taxa and morphology and inhabiting shallow marine habitats from the Gulf of California Ecoregion featured by distinctive environmental conditions. A large δ13C variability (-34.61‰ to -2.19‰) was observed, mostly explained on the life form (taxonomy, morphology and structural organization), and modulated by the interaction between habitat features and environmental conditions. The intertidal zone specimens had less negative d13C values than in subtidal zone. Except pH, environmental conditions of the seawater do not contribute to the δ13C variability. Specimens of the same taxa showed δ13C similar patterns, to increase or decrease, with latitude (21º-30°N). d13C-macroalgal provides information on the inorganic carbon source used for photosynthesis (CO2 diffusive entry vs HCO3- active uptake). Most species showed a δ13C belong into a range that indicates a mix of CO2 and HCO3- uptake; the HCO3- uptake by active transport is widespread among GCE macroalgae. About 20-34% species depending on cutoff limits for CCM presence showed at least one specimen with δ13C>-10‰, suggesting that potentially could have highly efficient CCM. Ochrophyta presented a high number of species with d13C>-10‰, suggesting widespread HCO3- use by non-diffusive mechanisms. Few species belonging to Rhodophyta relied on CO2 diffusive entry (d13C<-30‰) exclusively. δ13C provides useful information about the physiological and environmental status of macroalgae.

Years of the Maritime Continent or YMC was designed to improve our knowledge of the weather-climate systems over the MC and their numerical simulation and prediction skill. Since its first field campaign in November 2017, many intensive observations have been carried out under the coordination with the MC countries. Although currently some observations have been postponed due to COVID-19 pandemic, field campaigns are expected to continue beyond 2021. Up to now, some key information could be obtained, which suggest future approaches. In particular, diurnal cycle of rain near the coast is one of major targets, as they are dominant component of precipitation in this region. Some studies suggest the important role of temperature contrast between land and ocean, and inaccurate initial sea surface temperature conditions might cause a delay of offshore propagation of rainfall region. This fact provides a clue to improve simulation of precipitation behavior over the MC. In addition, during the campaign, several new observation tools have been introduced. For example, autonomous surface vehicle (ASV) had been deployed and measured surface meteorology as well as sea surface condition. Besides, GNSS-derived water vapor measurement was successfully carried out. Those results suggest that such ASVs equipped with new tools can be used to monitor accurate sea surface condition without significant cost and time. However, usually those instruments are not allowed to operate freely in the MC. Thus, based on collaboration with the MC countries, researchers in the MC are highly expected to take this role as regional representative. In this presentation, we will also show other results which provide tips for future direction.

Surface broadband shortwave and longwave irradiance are key components of the surface energy budget and give insight on atmospheric constituents like clouds and aerosols as well as provide useful information for model evaluation. Surface irradiance measurements are particularly difficult to make over the ocean where few measurement platforms exist, and where the motion of ships and buoys makes the accuracy of the measurements challenging. During the US DOE ARM Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign, new shipborne broadband radiation systems (SHIPRAD) were deployed for the first time to test correction. The systems include pyrgeometer measurements for measuring longwave irradiance, an unshaded pyranometer to measure shortwave irradiance, a navigation system measuring pitch/roll/heading, and an SPN1 shortwave radiometer that measures direct and diffuse components with no moving parts. A tilt correction methodology was used to correct 1 second temporal resolution shortwave irradiance data for ship motion, designed to correct tilts of 10 degrees or less to within 10 W/m2. Two SHIPRAD systems were deployed on the port and starboard sides of the ship, and the measurements were combined in order to be able to eliminate measurements shaded by ship structures. The new methodology allows for high-temporal resolution irradiance measurements with higher accuracy. Results will be presented on the accuracy of the tilt correction methodology and the irradiance measurement results throughout the campaign.

Sensitivity analysis in Earth and environmental systems modelling typically demands an onerous computational cost. This issue coexists with the reliance of these algorithms on ad-hoc designs of experiments, which hampers making the most out of the existing datasets. We tackle this problem by introducing a method for sensitivity analysis, based on the theory of variogram analysis of response surfaces (VARS), that works on any sample of input-output data or pre-computed model evaluations. Called data-driven VARS(D-VARS), this method characterizes the relationship strength between inputs and outputs by investigating their covariograms. We also propose a method to assess ‘robustness’ of the results against sampling variability and numerical methods’ imperfectness. Using two hydrologic modelling case studies, we show that D-VARS is highly efficient and statistically robust, even when the sample size is small. Therefore, D-VARS can provide unique opportunities to investigate geophysical systems whose models are computationally expensive or available data is scarce.

River-influenced areas are very important coastal ecosystems, due to their influence on nutrients and the structure of planktonic and benthic communities. Many studies have focused on the interaction between river runoff, wind and river plume characteristics, by means of observations and modeling. This study aimed to improve our understanding about the circulation and seasonal pattern of river plumes in Central Chile, using the Regional Ocean Modeling System (ROMS). Results were in reasonable agreement with observations. The plumes exhibit a minimal area during summer-fall, with a northwest orientation caused by southwesterly winds and lower river discharges. A larger plume area is developed during June-September, as result of higher winter precipitations. The orientation of the plumes during winter is westward, driven by higher river discharge and wind from the northwest. An interesting feature reproduced by the model was the trend to coalesce as observed in satellite imagery.

A linear theory of the generalized Rayleigh-Taylor instability (GRTI) is derived which includes ion inertia and acceleration forces, as well as E region drivers: the zonal neutral wind and plasma drift. This is in contrast to the F region drivers aside from gravity: the meridional neutral wind and the meridional/vertical plasma drifts. Both a local theory and a flux-tube integrated theory are presented with application to the onset of ionosphere irregularities associated with equatorial spread F. Inertia and acceleration forces do not affect the growth rate of the GRTI for nominal ionospheric conditions, but the E region zonal drifts can significantly increase or decrease the growth rate of the GRTI in the equatorial and mid-latitude ionosphere depending on their direction.

Radiance measurements from several types of passive microwave (PMW) sensors are combined in the Global Precipitation Measurement mission (GPM) to increase the temporal and spatial coverage of precipitation observations. The measurements of these sensors are converted to precipitation estimates by the GPM Profiling Algorithm (GPROF). High frequency PMW-channels are used to retrieve precipitation estimates over land, as these frequencies can measure the radiance scattered by ice particles in rain clouds. Scattering related to shallow and low-intensity precipitation events, however, is limited. Hence, radiometric signals associated with these events are hard to distinguish from the naturally emitted radiation from the Earth’s surface, especially since this so-called background radiation is dependent on the surface type. A better understanding of the physical processes that occur during precipitation events can help to identify possible weaknesses in the GPROF algorithm. Hence, this study couples overpasses of GPM radiometers over the Netherlands to two dual-polarization radars from the Royal Netherlands Meteorological Institute (KNMI) in 2019. All rainy overpasses (>0.1 mm/hr) within a 75 km radius around one of the radars are selected. This coupling provides the opportunity to relate GPROFs performance to physical characteristics of precipitation events, such as the vertical reflectivity profile and dual-polarization information on the melting layer. Additionally, simultaneous observations from both the PMW sensor and the dual-frequency precipitation radar (DPR, used as a-priori database in GPROF) aboard the GPM core satellite are available. Hence, space-based and ground-based reflectivity profiles can be compared and coupled to discrepancies of the GPROF algorithm.

Vertical resolution is an often overlooked parameter in simulations of convection. We explore the sensitivity of simulated deep convection to vertical resolution in the System for Atmospheric Modeling (SAM) convection resolving model. We analyze simulations run in tropical radiative convective equilibrium with 32, 64, 128, and 256 vertical levels in a small (100 km) and large domain (1500 km). At high vertical resolution, the relative humidity and anvil cloud fraction are reduced, which is linked to a reduction in both fractional and volumetric detrainment. This increases total atmospheric radiative cooling at high resolution, which leads to enhanced surface fluxes and precipitation, despite reduced column water vapor. In large domains, convective aggregation begins by simulation day 25 for simulations with 64 and 128 levels, while onset is delayed until simulation day 75 for the simulation with 32 vertical levels. Budget analyses reveal that mechanisms involved in the generation and maintenance of convective aggregation for the 32-level simulation differ from those for the 64- and 128-level simulations. Weaker cold pools in the 32-level simulation allow the boundary layer in dry regions to become extremely dry, which leads to an aggregated state with very strong spatial gradients in column-integrated moist static energy. Understanding both the triggering and maintenance of convective aggregation and its simulated sensitivity to model formulation is a necessary component of atmospheric modeling. We show that vertical resolution has a strong impact on the mean state and convective behavior in both small and large domains.

Changes in the concentration of greenhouse gases within the atmosphere lead to changes in radiative fluxes throughout the atmosphere. The value of this change, called the instantaneous radiative forcing, varies across climate models, due partly to differences in the distribution of clouds, humidity, and temperature across models, and partly due to errors introduced by approximate treatments of radiative transfer. This paper describes an experiment within the Radiative Forcing Model Intercomparision Project that uses benchmark calculations made with line-by-line models to identify parameterization error in the representation of absorption and emission by greenhouse gases. The clear-sky instantaneous forcing by greenhouse gases to which the world has been subject is computed using a set of 100 profiles, selected from a re-analysis of present-day conditions, that represent the global annual mean forcing with sampling errors of less than 0.01 \si{\watt\per\square\meter}. Six contributing line-by-line models agree in their estimate of this forcing to within 0.025 \si{\watt\per\square\meter} while even recently-developed parameterizations have typical errors four or more times larger, suggesting both that the samples reveal true differences among line-by-line models and that parameterization error will be readily resolved. Agreement among line-by-line models is better in the longwave than in the shortwave where differing treatments of the water vapor vapor continuum affect estimates of forcing by carbon dioxide and methane. The impacts of clouds on instantaneous radiative forcing are roughly estimated, as are adjustments due to stratospheric temperature change. Adjustments are large only for ozone and for carbon dioxide, for which stratospheric cooling introduces modest non-linearity.

Adjoint tomography (i.e., full-waveform inversion) has been recently applied to ambient seismic noise and teleseismic P waves separately to unveil fine-scale lithospheric structures beyond the resolving ability of traditional ray-based traveltime tomography. In this study, we propose a joint inversion scheme that alternates between frequency-dependent traveltime inversions of ambient noise surface waves and waveform inversions of teleseismic P waves to take advantage of their complementary sensitivities to the Earth’s structure. We apply our method to ambient noise empirical Green’s functions from 60 virtual sources, direct P and scattered waves from 11 teleseismic events recorded by a dense linear array (～ 7 km station spacing) and other regional stations (～ 40 km average station spacing) in central California. To evaluate the performance of the method, we compare tomographic results from ambient noise adjoint tomography, full-waveform inversion of teleseismic P waves, and the joint inversion of the two data sets. Both applications to practical field data sets and synthetic checkerboard tests demonstrate the advantage of the joint inversion over individual inversions as it combines the complementary sensitivities of the two independent data sets towards a more unified model. The 3D model from our joint inversion not only shows major features of velocity anomalies and discontinuities in agreement with previous studies. but also reveals small-scale heterogeneities which provide new constraints on the geometry of the Isabella Anomaly and mantle dynamic processes in central California. The proposed joint inversion scheme can be applied to other regions with similar array deployments for high-resolution lithospheric imaging.

The nature of the relationship between soil-moisture and subsequent precipitation is debated. Past studies have indicated that it varies by location, but there have been disagreements on feedback sign, strength and statistical significance over the same locations even while using the same data sets due to differences in statistical approaches. Here we re-evaluate estimates of feedback strength using Granger causality (following Tuttle and Salvucci 20016) for SMOS and AMSR-2soil moisture products and find that there is evidence both of there being a positive feedback over the entire nation (SMOS) and of there being a west-to-east gradient of positive to negative values (AMSR-2, similar to what was found by Tuttle). This project has demonstrated that differences arise using identical statistical estimation techniques with different satellite estimates of soil moisture. The passive microwave AMSR-E and AMSR-2 data produce a gradient of positive to negative impact factors across the U.S. while the SMOS data set yields a mostly positive impact factor over the entirety of the U.S. Here we explain this discrepancy by noting that the areas where the sign of the impact differ are areas where the soil moisture perturbations of SMOS and AMSR-2 are anticorrelated, and also that these areas coincide with areas of high vegetation cover, which are well known to challenge remote sensing estimates of moisture.