Tiny tomato pollen has an outsized role in reproduction, providing essential cellular and genetic material for fertilization and fruit generation. Unfortunately, high temperatures reduce pollination efficiency, harm fruit set and size, and ultimately diminish yield. This project attempts to answer basic questions about pollen growth and function during normal and heat-stressed conditions. Pollen from ~200 genetically diverse tomato and wild relative accessions will be observed as it grows at various temperatures. High-throughput microscopy will be paired with computer vision to phenotype the thousands of image sequences generated by this experiment. By combining pollen growth phenotypes with genome sequence data for all accessions, we plan to identify relevant genomic regions to target for functional description and crop improvement.

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi-model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA-2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design.

The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) took place in January-February 2020. It was designed to understand the relationship between shallow convection and the large-scale environment in the trade-wind regime. Lagrangian large eddy simulations, following the trajectory of a boundary-layer airmass, can reproduce a transition of trade cumulus organization from “sugar” to “flower” clouds with cold pools, observed on February 2-3. The simulations were driven with reanalysis large-scale meteorology and ATOMIC in-situ aerosol data. During the transition, large-scale upward motion deepens the cloud layer. The total water path and optical depth increase, especially in the moist regions where flowers aggregate. This is due to mesoscale circulation that renders a net convergence of total water in the already moist and cloudy regions, strengthening the organization. An additional simulation shows that stronger large-scale upward motion reinforces the mesoscale circulation and accelerates the organization process by strengthening the cloud-layer mesoscale buoyant turbulence kinetic energy production.

Dislocation recovery experiments were conducted on predeformed olivine single crystals at temperatures of 1,450 to 1,760 K, room pressure, and oxygen partial pressures near the Ni-NiO buffer to determine the annihilation rate constants for [001](010) edge dislocations. The obtained rate constants were found to be comparable to those of previously determined [001] screw dislocations. The activation energies for the motion of both dislocations are identical. This result suggests that the motion of screw dislocations in olivine is not controlled by cross-slip but by the same rate-limiting process of the motion of edge dislocations, i.e., climb, under low-stress, high-temperature conditions. The diffusivity derived from dislocation climb indicates that dislocation recovery is controlled by Si pipe diffusion, rather than Si lattice diffusion. Our results suggest that the conventional climb-controlled model for olivine can be applied to motions of not only edge but also screw dislocations. Therefore, the previous proposed cross-slip model cannot explain the softness of asthenosphere.

Soluble and total trace metals were measured in 4 size fractionated aerosol samples collected over the tropical eastern Atlantic Ocean. In samples that were dominated by Saharan dust, the size distributions of total iron, aluminium, titanium, manganese, cobalt and thorium were very similar to one another and to the size distributions of soluble manganese, cobalt and thorium. Finer particle sizes (< ~3 µm) showed enhanced soluble concentrations of iron, aluminium and titanium, possibly as a result of interactions with acidic sulfate aerosol during atmospheric transport. The difference in fine particle solubility between these two groups of elements might be related to the hyperbolic increase in the fractional solubility of iron, and a number of other elements, during the atmospheric transport of Saharan dust, which is not observed for manganese and its associated elements. In comparison to elements whose solubility varies during atmospheric transport, the stability of thorium fractional solubility should reduce uncertainties in the use of dissolved concentrations of this element in seawater as a proxy for dust deposition, although this topic requires further work.

This paper proposes an interactive system called Andromeda1that enables users to interact with machine learning models to allow for exploratory sorting of images through a cognitive approach that uses a reduced dimension plot. In our system, a dimension reduction algorithm projects the images into a 2D space representing similarities between the images based on visual features extracted by a deep neural network. With Andromeda, users can alter the projection by dragging a subset of the images into groups according to their domain expertise. The underlying machine learning model learns the new projection by optimizing a weighted distance function in the feature space, and the model re-projects the images accordingly. The users can explore multiple custom projections to learn about the visual support for different groupings based on explainable-AI feedback. Our approach incorporates user preferences into machine learning model construction and allows transfer learning from pre-trained image processing models to accomplish new tasks based on user inputs. Using edamame pod images as an example, we interactively re-project the images into different groupings based on maturity and disease, and identify important visual features from the pixels highlighted by the model.

We present thermophysical, biological, and chemical observations of ice and brine samples from five compositionally diverse hypersaline lakes in British Columbia's interior plateau. Possessing a spectrum of magnesium, sodium, sulfate, carbonate and chloride salts, these low-temperature high-salinity lakes are analogs for planetary ice-brine environments, including the ice shells of Europa and Enceladus, and ice-brine systems on Mars. As such, understanding the thermodynamics and biogeochemistry of these systems can provide insight into the evolution, habitability, and detectability of high priority astrobiology targets. We show that biomass is typically concentrated in a layer near the base of the ice cover, but that chemical and biological impurities are present throughout the ice. Coupling bioburden, ionic concentration and seasonal temperature measurements, we demonstrate that impurity entrainment in the ice is directly correlated to ice formation rate and parent fluid composition. We highlight unique phenomena including brine supercooling, salt hydrate precipitation, and internal brine layers in the ice cover, important processes to consider for planetary ice-brine environments. These systems can be leveraged to constrain the distribution, longevity, and habitability of low-temperature solar system brines -- relevant to interpreting spacecraft data and planning future missions in the lens of both planetary exploration and planetary protection.

Climate-induced episodes of extensive tree mortality worldwide are leading to abrupt changes in forest carbon stocks. A severe frost in early February 2011 triggered widespread tree mortality in the lowland tropical dry forest (TDF) of northwestern Mexico. The studied landscape in southern Sonora is composed by a patchy matrix dominated by mature, secondary (originated in abandoned fields), and active agricultural fields. In this forest, we used allometric equations to assessed frost-induced changes in aboveground biomass (AGB) stocks in mature and secondary tropical dry forests. For AGB estimations we used 48 1-ha plots (24 plots per forest type) distributed within four distant subareas in our 83 230 ha study area. On each plot, we recorded all live/dead individuals, and a total of 11 205 woody plants were registered, of which 7 137 (with at least a stem DBH > 2.5 cm) were likely present before the frost, and the remaining smaller ones were considered as new recruits regenerated from seeds (4,068 individuals). From those plants present before the frost, 26 842 and 8 059 were live and dead stems, and 1 222 were dead individuals. All registered live and dead stems accounted for a total of 273.4 Mg of AGB in our study plots (4.8 ha). From this amount, 57.3 Mg was necromass (dead stems). Interestingly, only two out of a total of 74 registered species contributed with ca. 80% of this necromass. These highly sensitive species are the tree legumes Lysioma divaricatum and Acacia cochliacantha. On average, AGB in the studied mature and secondary TDF was 64.3 and 49.6 Mg ha-1, respectively. The corresponding necromass for these forests was 10.9 and 13 Mg ha, respectively. The 2011 frost induced a greater change from live biomass to necromass in secondary than mature forests, 26.2% and 16.9%, respectively, which can be explained by the higher abundance of individuals from sensitive species in secondary forests. Our results suggest that climate-induced shifts in carbon stocks are linked to previous land-use changes in tropical dry forests. Restoration plans of these degraded lands should consider the vulnerability of tropical dry forest species to climate extremes.

Although the nature of the early Martian climate is a matter of considerable debate, the presence of valley networks (VN) provides unambiguous evidence for the presence of liquid water on Mars’ surface. A subaerial fluvial origin of VN is at odds with the expected phase instability of near-surface water in the cold, dry Late Noachian climate. Furthermore, many observed geomorphometric properties of VN are inconsistent with surface water flow. Conversely, subglacial channels exhibit many of these characteristics and could have persisted beneath ice sheets even in a cold climate. Here we model basal melting beneath a Late Noachian Icy Highlands ice sheet and map subglacial hydrological flow paths to investigate the distribution and geomorphometry of subglacial channels. We show that subglacial processes produce enough melt water to carve Mars’ VN; that predicted channel distribution is consistent with observations; and corroborate geomorphometric measurements of VN consistent with subglacial formation mechanisms. We suggest that subglacial hydrology may have played a key role in the surface modification of Mars.

Phenotypic trait measurements have enabled breeders to link genomic information to phenotypic information and through this enhance crop performance by breeding for superior germplasm. Progress in this area has been hindered by the limited ability to capture agronomic traits of importance at a large field-based scale since traditional methods for measuring phenotypic traits in field are time and labor intensive and are limited in accuracy and consistency when implemented on large scale. Precision phenotyping efforts have enabled researchers at Corteva Agriscience to collect high quality datasets for important traits that programs had been unable to measure accurately or safely in the past. Specific applications of phenotyping technologies and how these have influenced data collection within Corteva breeding programs around the world will be presented. Technology is rapidly evolving, and by using this technology to develop novel precision phenotyping solutions, breeders are able to capture more high-quality data and gain unique insights.

The characterization of changes over the full distribution of precipitation intensities remains an overlooked and underexplored subject, despite their critical importance to hazard assessments and water resource management. Here, we aggregate daily in situ Global Historical Climatology Network precipitation observations within seventeen internally consistent domains in the United States for two time periods (1951-1980 and 1991-2020). We find statistically significant changes in wet day precipitation distributions in all domains – changes primarily driven by a shift from lower to higher wet day intensities. Patterns of robust change are geographically consistent, with increases in the mean (4.5-5.7%) and standard deviation (4.4-8.7%) of wet day intensity in the eastern U.S., but mixed signals in the western U.S. Beyond their critical importance to the aforementioned impact assessments, these observational results can also inform climate model performance evaluations.

One of the primary mechanisms of loss of Earth’s atmosphere is the persistent “cold” (T ≲ 20 eV) ion outflow that has been observed in the magnetospheric lobes over large volumes with dimensions of order several Earth radii. As the main source of this cold ion outflow, the polar cap F-region ionosphere and conditions within it have a disproportionate influence on these magnetospheric regions. Using 15 years of measurements of plasma density Ne made by the Swarm spacecraft constellation and the CHAMP spacecraft within the F region of the polar cap above 80° Apex magnetic latitude, we report evidence of several types of seasonal asymmetries in polar cap Ne. Among these, the transition between “winter-like” and “summer-like” median polar cap Ne occurs one week prior to local spring equinox in the Northern Hemisphere (NH), and one week after local spring equinox in the Southern Hemisphere (SH). Thus the median SH polar cap Ne lags the median NH polar cap Ne by approximately two weeks with respect to hemispherically local spring and fall equinox. From interhemispheric comparison of statistical distributions of polar cap plasma density around each equinox and solstice, we find that distributions in the SH are often flatter (i.e., less skewed and kurtotic) than in the NH. Perhaps of most significance to cold ion outflow, we find no evidence of an F-region plasma density counterpart to a previously reported hemispheric asymmetry whereby cold plasma density is higher in the NH magnetospheric lobe than in the SH lobe.

Numerical wave models are used for a wide range of applications, from the global ocean to coastal scales. Here we report on significant improvements compared to the previous hindcast by Rascle and Ardhuin (2013). This result was obtained by updating forcing fields, adjusting the spectral discretization and retuning wind wave growth and swell dissipation parameters. Most of the performance analysis is done using significant wave heights (Hs) from the recent re-calibrated and denoised satellite altimeter data set provided by the European Space Agency Climate Change Initiative (ESA-CCI), with additional verification using spectral buoy data. We find that, for the year 2011, using wind fields from the recent ERA5 reanalysis provides lower scatter against satellite H s data compared to historical ECMWF operational analyses, but still yields a low bias on wave heights that can be mitigated by re-scaling wind speeds larger than 20 m/s. Alternative blended wind products can provide more accurate forcing in some regions, but were not retained because of larger errors elsewhere. We use the shape of the probability density function of H s around 2 m to fine tune the swell dissipation parameterization. The updated model hindcast appears to be generally more accurate than the previous version, and can be more accurate than the ERA5 H s estimates, in particular in strong current regions and for Hs greater than 7 m.

We assess the effective radiative forcing due to ozone-depleting substances using models participating in the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). A large inter-model spread in this globally averaged quantity necessitates an “emergent constraint” approach whereby we link the radiative forcing to the amount of ozone depletion simulated during 1979-2000, excluding two volcanically perturbed periods. During this period ozone-depleting substances were increasing, and several merged satellite-based climatologies document the ensuing decline of total-column ozone. We use these analyses to come up with effective radiative forcing magnitudes. For all of these satellite climatologies we find an effective radiative forcing outside or on the edge of the previously published “likely” range given by the 5th Assessment Report of IPCC, implying an offsetting effect of ozone depletion and/or other atmospheric feedbacks of -0.4 to -0.25 Wm-2, which is in absolute terms is larger than the previous best estimate of -0.15 Wm-2.

Microcosm experiments using microbial mats can be useful at times to understand mineral precipitation induced by microorganisms and their extracellular polymeric substances (EPS). Currently, the existing knowledge limits our ability to elucidate the interactions between microbes, which form communities as microbial mats, and minerals that precipitate in natural environments (e.g., lagoons, rivers, springs, soils). Much of the prior research did not consider entire microbial communities, despite recent evidence that microorganisms interact in a community-based way. This is especially relevant in extreme environments where the entire microbial communities are not yet known despite their relevance to biosignatures exploration on other planets. Here, we grew microbial mats on natural substrates in the laboratory to monitor changes in mat texture and mineral paragenesis. Several analytical techniques were used to compare mineral paragenesis in association with and without microbes. This paragenesis included major phases of chemical sedimentary deposits, such as gypsum, calcium carbonate, and some silicates, whose formation is traditionally linked to evaporative processes but was not in these experiments. In addition, some of the phases only precipitated within microbial mat samples and there were differences in mineral fabrics between mat samples and abiotic controls.

A global, sun-blocking catastrophe like nuclear war, an asteroid strike, or super volcano eruption spells disaster for most aspects of life as we know it. There have been many studies on how differing magnitudes of sun-blocking catastrophes would affect the global climate, and many mention the effects of this cold, dark climate on forests and cropping systems. However, few studies have solely focused on the effects of nuclear winter on forests in terms of food, resources, and decomposition. Forests already provide over a billion people with food and fuel for their livelihoods. In this review we connect how prehistoric catastrophes affected the world's forests to how a current day catastrophe may affect forest health, forest resource availability, and wood decomposition rates. We briefly discuss how forest resources may be used in this post-catastrophe climate for food and fuel in an energy and fuel depleted world. We use this information to make policy and education suggestions to prepare for future catastrophes, build resilience from smaller local disasters, prepare for the many effects of climate change, and discourage nuclear weapon stockpiling.

High-quality aeromagnetic data are important in guiding new knowledge of the solid earth in frontier regions, such as Antarctica, where these data are often among the first data collected. The difficulties of data collection in remote regions often lead to less than ideal data collection, leading to data that are sparse and four-dimensional in nature. Standard aeromagnetic data collection procedures are optimised for the (nearly) 2D data that are collected in industry-standard surveys. In this work we define and apply a robust magnetic data correction approach that is optimised to these four dimensional data. Data are corrected in three phases, first with operations on point data, correcting for spatio-temporal geomagnetic conditions, then operations on line data, adjusting for elevation differences along and between lines and finally a line-based levelling approach to bring lines into agreement while preserving data integrity. For a large-scale East Antarctic survey, the overall median cross-tie error reduction error reduction is 93%, reaching a final median error of 5 nT. Error reduction is are spread evenly between phase 1 and phase 3 levelling operations. Phase 2 does not reduce error directly but permits a stronger error reduction in phase 3. Residual errors are attributed to limitations in the ability to model 4D geomagnetic conditions and also some limitations of the inversion process used in phase 2. Data have improved utility for geological interpretation and modelling, in particular quantitative approaches, which are enabled with less bias and more confidence.

Public health risks resulting from urban heat in cities are increasing due to rapid urbanisation and climate change, motivating closer attention to urban heat mitigation and adaptation strategies that enable climate-sensitive urban design and development. These strategies incorporate four key factors influencing heat stress in cities: the urban form (morphology of vegetated and built surfaces), urban fabric, urban function (including human activities), and background climate and regional geographic settings (e.g. topography and distance to water bodies). The first two factors can be modified and redesigned as urban heat mitigation strategies (e.g. changing the albedo of surfaces, replacing hard surfaces with pervious vegetated surfaces, or increasing canopy cover). Regional geographical settings of cities, on the other hand, cannot be modified and while human activities can be modified, it often requires holistic behavioural and policy modifications and the impacts of these can be difficult to quantify. When evaluating the effectiveness of urban heat mitigation strategies in observational or traditional modelling studies, it can be difficult to separate the impacts of modifications to the built and natural forms from the interactions of the geographic influences, limiting the universality of results. To address this, we introduce a new methodology to determine the influence of urban form and fabric on thermal comfort, by utilising a comprehensive combination of possible urban forms, an urban morphology data source, and micro-climate modelling. We perform 9814 simulations covering a wide range of realistic built and natural forms (building, roads, grass, and tree densities as well as building and tree heights) to determine their importance and influence on thermal environments in urban canyons without geographical influences. We show that higher daytime air temperatures and thermal comfort indices are strongly driven by increased street fractions, with maximum air temperatures increases of up to 10 and 15◦C as street fractions increase from 10% (very narrow street canyons and/or extensive vegetation cover) to 80 and 90% (wide street canyons). Up to 5◦C reductions in daytime air temperatures are seen with increasing grass and tree fractions from zero (fully urban) to complete (fully natural) coverage. Similar patterns are seen with the Universal Thermal Climate Index (UTCI), with increasing street fractions of 80% and 90% driving increases of 6 and 12◦C, respectively. We then apply the results at a city-wide scale, generating heat maps of several Australian cities showing the impacts of present day urban form and fabric. The resulting method allows mitigation strategies to be tested on modifiable urban form factors isolated from geography, topography, and local weather conditions, factors that cannot easily be modified.