The term “weather whiplash” was recently coined to describe abrupt swings in weather conditions from one extreme to another, such as from a frigid cold spell to anomalous warmth or from drought to prolonged precipitation. These events are often highly disruptive to agriculture, ecosystems, and daily activities. In this study we propose and demonstrate a novel metric to identify weather whiplash events (WWEs) and track their frequency over time. We define a WWE as a transition from one persistent large-scale circulation regime to another distinctly different one, as determined using an objective pattern cluster analysis called self-organizing maps (SOMs). We focus on the domain spanning North America and the eastern N. Pacific Ocean. A matrix of representative atmospheric patterns in 500-hPa geopotential height anomalies is created. We analyze the occurrence of WWEs originating with long-duration events (defined as lasting 4 or more days) in each pattern, as well as the associated extremes in temperature and precipitation. A WWE is detected when the pattern two days following a long-duration event is substantially different, measured using internal matrix distances and thresholds. Changes in WWE frequency are assessed objectively based on reanalysis and climate model output, and in the future with climate model projections. Temporal changes in the future under RCP 8.5 forcing are more robust than those during recent decades, with consistent increases (decreases) in WWEs originating in patterns with an anomalously warm (cold) Arctic.

We exploit novel “string-of-pearls” configuration of NASA’s Magnetospheric Multiscale mission to investigate properties of structures within the Earth’s magnetosheath that are short in duration but carry intense currents. Previous work has shown that the j.E energy conversion within current structures processes of order 10% of the total energy flux incident at the bow shock. This makes these events important contributors to the overall shock energy budget and ongoing thermalization within the magnetosheath. The present study, under very similar solar wind conditions and bow shock geometries, reveals significant qualitative differences from the previous study. Moreover, we find only modest, if any coherence, on scales <1000 km. We explore the implication of these observations in terms of both bow shock and turbulence energy transfer and dissipation.

The academic literature is the primary source for current developments in science. But limited access to journals as well as the widespread use of technical jargon can inhibit the dissemination of new knowledge to scientists from other fields and to non-scientists. These serve as major barriers to interdisciplinary collaboration with non-geoscientists and to efforts to further public understanding of geoscience research. Meanwhile, traditional science news focuses on topics of obvious interest to the public, such as geohazards or climate change. While engaging with non-geoscientists on these topics is important, the majority of geoscience research lacks a mechanism for generating public interest. “Bites” sites, originally introduced in the astronomy community, are blogs dedicated to communicating new developments in science to a broad audience. Each bite is an engaging, short (400-700 word) summary that explains an exciting new scientific paper and discusses its importance in the field. Bites are typically written by graduate students and other early career scientists about recently published articles that have not been picked up by more traditional science news outlets. These sites serve three key purposes: 1) to keep the interested public – especially university students who may consider careers in geoscience – up to date with recent developments in the field, 2) to generate attention for new work that traditional science media outlets may miss, and 3) to give early career scientists practice with public-facing writing and editing, which are critical skills both within and beyond academia. Here we present the new site Geobites, targeted at communicating new geoscience (broadly defined) research to the public. We show examples of articles on Geobites, diagram the structure of a good article, present initial site analytics, and solicit feedback from the geoscience communication community.

Mass loss from the Greenland Ice Sheet (GrIS) is a primary contributor to sea level rise, but substantial uncertainty exists in estimates of future ice sheet losses. Surface mass balance (SMB) models, the current leading approach to sea level rise projection, anticipate continued dominance of runoff as a mass loss pathway. Despite their preeminence, SMB models in vulnerable northern environments lack adequate field validation, particularly for error-sensitive runoff estimates. We have installed a cluster of high quality field instruments at the Minturn Elv, a proglacial river site in Inglefield Land, NW Greenland to provide discharge and weather datasets for the validation and refinement of climate/SMB runoff models. The instrument cluster has meteorological, hydrological, and time lapse camera instrumentation, including a vented water level stage recorder, single shot and scanning lidars, time lapse cameras, and in situ ADCP discharge and terrestrial scanning lidar measurements. The instrument suite provides novel flow and weather datasets with the opportunity to evaluate experimental approaches to stage measurement in adverse, high-latitude areas. Inglefield is a uniquely advantaged location because proglacial runoff is dominated by SMB processes operating on the ice surface without interference from subglacial hydrology. Overall, our hydrometeorological instrument cluster at Inglefield Land will provide one of the few validation datasets for regional climate models outside of Southwest Greenland.

Greater public, and research, focus on oceanic and atmospheric oxygen budgets is needed. Oceans are “losing their breath”; there has been a 1-2% loss, 77-154 gigatons (GT) of total oceanic oxygen (O2) 7,700GT (est.), over the last 50 years. Low O2 ocean areas occur more frequently and more widely; O2 minimum zone (OMZ) depths are rising; and sulphidic events are more common. Where is lost ocean oxygen ‘gO2ing’? Oxygen (O2) is recharged by phototropic O2 producing organisms in both the oceans and on land. Pre-human activity, O2, and CO2 (190-260ppm.) levels likely oscillated within a relatively stable band, for 800,000 years or more. Thus, O2 usage by volcanism, fires, and soil and sea biomes, must have balanced ocean and land based photosynthetic O2 production, as cyclically regulated by ‘Gaian’ feedback. Therefore, additive anthropogenic related increases in CO2 production, must result in net atmospheric O2 loss, including ocean outgassing. Importantly, exchange of oxygen between the oceans and atmosphere is determined by ‘Henry’s Law’, as influenced by oceanic temperature change (warmer waters dissolve less oxygen), and also salinity. Undissolved oxygen concentrations within upper ocean layers, will be higher due to the water pressure gradient, so less oxygen being dissolved at lower pressures. Thus, subject to usage by sea life forms; and thermoclines and haloclines; will likely be replenished from below, tending to surface saturation, even if the OMZs are rising so decreasing in depth? Henry’s law dictates, as anthropogenic reduction of atmospheric O2 reduces partial pressure, dissolved ocean oxygen will equilibrate, releasing stored oxygen to the atmosphere. Thus, over time, if atmospheric O2 continues to fall due to anthropogenic usages, irrespective of other factors, oceanic O2 will arguably be diminished year on year; ultimately will oceans become sufficiently anoxic to be unstable? Research suggests risk of species extinction type events of varying severity strongly correlate to anoxic ocean events. Due to Henry’s Law; will continued anthropogenic oxygen including fossil fuel use, inevitably lead to oceanic oxygen outgassing depletion, and absent change, ultimately an extinction event risk? Is a global Manhattan type project needed to find viable non-carbon-based, non-oxygen using, energy sources?

The Rochester and Adna 7.5 minute quadrangles in the Washington forearc of the Cascadia subduction zone encompass the Doty fault, a large forearc fault crossing the I-5 corridor south of Centralia. We have begun a cooperative geological and geophysical study of the area to assess the seismic hazard to a water retention facility that has been proposed to mitigate flooding along the Chehalis River and the I-5 corridor. This region between Olympia and Portland is undergoing north-south compression, clockwise rotation, and regional uplift associated with both subduction processes and the northward migration of the forearc block. Past studies identified multiple faults that strike NW-SE and E-W in the northern and southern parts of the study area, respectively. The Kopiah, Scammon Creek, Salzer Creek and Doty faults all interact within our study area, in ways that are poorly understood. An integrated geophysical investigation will assist the State-Federal cooperative mapping program called STATEMAP efforts to produce detailed 1:24,000 scale geologic maps of the area. Geophysical field work in the summer of 2018 includes a roughly 15 x 32 km gravity grid with ~2 km station spacing. Station spacing along known geologic structures is ~1 km to provide greater resolution. Results from our coarse gravity grid will provide targets for additional high resolution profiles. A high resolution ground magnetic grid also extends across both quadrangles, and preliminary results demonstrate its efficacy at elucidating structure. Seismic profiles acquired by the USGS across the Doty fault will constrain our geophysical modeling, which will combine the high resolution gravity and magnetic profiles in a geologic model of the subsurface to support the mapping efforts of the STATEMAP program. The data and models will provide insight about total offset across these faults, precisely identify locations of faults that are not exposed at the surface, and allow us to better understand the structure of these faults. These interpretations will allow us to more accurately understand the potential seismic risk these faults pose to nearby population centers and infrastructure.

Seagrasses provide a multitude of ecosystem services: they alter water flow, cycle nutrients, stabilize sediments, support the food web structure, and provide a critical habitat for many animals. However, due to threats to seagrass meadows and their associated ecosystems, these habitats are declining globally. Acoustical methods can be a powerful remote sensing tool to efficiently monitor seagrass meadows, alleviating the problem of space and time aliasing associated with traditional spot measurements. The acoustic field is highly sensitive to the presence of gas bubbles in liquids, which result in acoustic dispersion, absorption, and scattering. The biological processes and physical characteristics associated with seagrass result in trapped gases, which are present in the aerenchyma of seagrass leaves, roots, and rhizomes as well as in freely floating bubbles in the water. To investigate the use of acoustical methods to monitor ecosystem health, an experiment was conducted in the Lower Laguna Madre where the seabed was covered by a dense growth of Thalassia testudinum. During the experiment, a combustive sound source was used to produce broadband signals at ranges of 25 m to 400 m from an array of receivers. The data were collected over a period of one day to assess the diurnal effects of photosynthetic activity on the acoustic measurements. An additional set of measurements were collected in a nearby sparsely vegetated site to provide a baseline data set for comparison. Supporting measurements of irradiance, dissolved oxygen, and water temperature were acquired at the experiment site. The acoustic data were analyzed for the purposes of inferring environmental parameters in the seagrass meadow, including the gas volume present in the environment. An effective medium model for gas bubbles in liquids was used to characterize the frequency-dependency of sound speed and attenuation in the waveguide. [Work sponsored by ARL:UT IR&D and ONR.]

The Kairei and Yokoniwa hydrothermal fields are hosted in mafic as well as ultramafic rocks distributed at an off-axis volcanic knoll of the Central Indian Ridge. Despite intensive investigations, their geological and geophysical background is still debated. Here, we show results of near-seafloor magnetic field measurements using a submersible. We investigated crustal magnetization of the hydrothermally altered zone and surrounding lava flows, and evaluated their intensities compared to previously reported values at axial areas of a spreading environment. The Kairei hydrothermal field is characterized by low coherence between observed and modeled anomalies and low values of magnetization. This result suggests that magnetic minerals within basaltic lava flows were likely altered by hydrothermal fluid circulation. The variation pattern in the observed magnetic anomalies above the lava flows is in phase with that of modeled magnetic anomalies for a simple assumption with a magnetization direction parallel to the geomagnetic field. This result suggests that these lava flows preserve normal magnetic polarity corresponding to the Brunhes chron. The estimated magnetization intensity reaches 20 A/m in this area, which is clearly greater than that of the general off-axis crustal magnetization. This study provides new insight into the distribution of highly magnetized lava flows and indicates the distribution of recent off-axis volcanic activity, which is potentially linked to sub-seafloor hydrothermal circulation.

The paper inspects the effects of a G2 class geomagnetic storm that occurred during 27 February- 1 March, 2014 on the equatorial ionization. This storm is observed following a Coronal Mass Ejection (CME) from a sunspot AR1967 on 26 February. An enhancement of solar wind speed is observed on 27 February, 2014 (483 km/sec). The maximum southward component of Interplanetary Magnetic Field (IMF) is observed around 21 UT of 27 February (12 nT). This interconnects with Earth’s magnetic field and develops the main phase of a geomagnetic storm on the same day. The storm continues through 28 February and quiet-time ionospheric condition is recovered on 1 March. The effects of the storm on equatorial ionization is observed at Brasilia (15.95°S, 47.88°W geographic; 9.40°N, 21.13°E geomagnetic), Addis Ababa (9.04°N, 38.77°E geographic; 0.18°N, 110.47°E geomagnetic) and Colombo (6.89°N, 79.87°E geographic; 1.57°S, 151.57°E geomagnetic). An enhancement of TEC is observed during main phase of the geomagnetic storm at these stations. Increment in diurnal peak is observed on 28 February (14 TECU at 10 UT at Addis Ababa) while a decrement of diurnal peak TEC is observed during the recovery phase of the storm (15 TECU at 10 UT at Addis Ababa). Post-sunset ionospheric scintillation is inhibited at Brasilia on 28 February.

The unambiguous 2-dimensional (2D) maps of OI 135.6 nm radiance retrieved from the Global Observation of Limb and Disk (GOLD) after sunset are compared with the total electron content (TEC) maps measured by GPS receivers in the America sector. The OI 135.6 nm radiance observed by GOLD is an indicator of the peak electron density of the ionosphere, while the TEC depends on the total electron density in the column. The comparisons show that both of them are able to capture the large structures in the equatorial ionization anomaly (EIA) well, and sometimes they both also capture bubbles. Both show that the ionosphere after sunset is quite dynamic and has strong day-to-day variability. A statistical study has also been carried out to check the occurrence rate of bubbles and the apparent EIA structure between Oct 17, 2018 to May 31, 2019. GOLD is able to image the areas where it is difficult to situate GPS receivers such as the ocean, while TEC data covers the full-diurnal cycle. In all, the GOLD and TEC have valuable synergy to allow us to gain a better understanding of the equatorial ionosphere.

As fundamental parameters of the Sun, the Alfv\’en radius and angular momentum loss determine how the solar wind changes from sub-Alfv\’enic to super-Alfv\’enic and how the Sun spins down. We present an approach to determining the solar wind angular momentum flux based on observations from Parker Solar Probe (PSP). A flux of about $0.15\times10^{30}$ dyn cm sr$^{-1}$ near the ecliptic plane and 0.7:1 partition of that flux between the particles and magnetic field are obtained by averaging data from the first four encounters within 0.3 au from the Sun. The angular momentum flux and its particle component decrease with the solar wind speed, while the flux in the field is remarkably constant. A speed dependence in the Alfv\’en radius is also observed, which suggests a “rugged” Alfv\’en surface around the Sun. Substantial diving below the Alfv\’en surface seems plausible only for relatively slow solar wind given the orbital design of PSP. Uncertainties are evaluated based on the acceleration profiles of the same solar wind streams observed at PSP and a radially aligned spacecraft near 1 au. We illustrate that the “angular momentum paradox” raised by R\’eville et al. can be removed by taking into account the contribution of the alpha particles. The large proton transverse velocity observed by PSP is perhaps inherent in the solar wind acceleration process, where an opposite transverse velocity is produced for the alphas with the angular momentum conserved. Preliminary analysis of some recovered alpha parameters tends to agree with the results.

The magnitude of Hurricane Harvey significantly altered flood frequency statistics in the region that it hit, but hurricane path projections indicate that it could have made landfall in numerous other regions along the Gulf coast. While current flood frequency methods restrict analysis to floods that occur within a specific region, due to the effects of climate change and immense size of Harvey, it is important to determine the impact that Harvey would have had if it hit other regions within its probabilistic landfall path. Therefore, this study investigates the impact that Harvey would have had on flood frequency statistics and regional flood frequency analysis if it had made landfall elsewhere. To this end, spatial rainfall data was shifted to two probabilistic landfall regions in the central and southern Gulf coast of Texas. This shifted rainfall data was then paired with synthetic unit hydrographs to create simulated Hurricane peak flows at USGS streamflow stations in each region. With few exceptions, Log Pearson III analyses of records containing simulated Harvey peak flows resulted in 2-, 5-, 10-, 25-, 50- and 100-year peak flows that were higher than Log Pearson III analyses of the original peak flow records. These increases in peak flows were larger for longer return periods – 100-year peak flows increased by an average of 63.9% in the southern coast region and 21.4% in the central coast region, while 2-year peak flows increased by an average of 9.38% in the southern coast region and 1.51% in the central coast region. These return period peak flows were then applied to regional flood frequency analysis to predict peak flows based upon drainage area and basin shape factor. Application of the equations to example watersheds in the central coast region increased estimated peak flows by up to 75%. This case study shows that moving Hurricane Harvey to different regions within its probabilistic landfall path would have a significant impact on flood frequency statistics and regional flood frequency equations. Therefore, because of the growing impact of climate change on hurricane intensity, it may be important to consider the impact that current and future extreme hurricanes like Harvey have on flood frequency statistics in other regions within their probabilistic landfall path.

The authors implemented the Regional Ocean Modelling System (ROMS) to coastal waters on the west coast of Ireland. The Connemara model has c.200 m horizontal resolution and has 20 vertical sigma levels and stretches from 10.8oW to 8.9oW and from 52.95oN to 53.73oN. It has three open ocean boundary conditions in the north, south and west, and several rivers are included at the head of Galway Bay. Both 3D and 2D configurations have been set up; with the aim of the 2D configuration being the prediction of storm surges. The 3D configuration has been running in the operational forecasting mode for approximately the last decade and produce weekly hindcasts and 3-day forecasts. Details of the operational system will be presented. Most recent developments include the implementation of wetting/drying algorithm with a critical depth of 0.25 m. It has undergone a testing phase and the authors will report on the findings in terms of the computational efficiency and in terms of the changes to the model skill. Details of the set-up of each configuration, as regards the forcing functions, the choice of boundary conditions, atmospheric forcing, advection schemes, turbulence schemes, will be presented. The predictive skill of various configurations have been assessed by means of root mean square error (RMSE) differences and correlations with data collected from the Marine Institute’s observational network in Galway Bay. The observational platforms comprise of 5 tide gauges, 4 x ADCPs and temperature and salinity sensors. The harmonic analysis has been carried out on the data from the tide gauges and the corresponding model predictions in order to validate the tidal signal. The tidal signal in the Sea Surface Height (SSH) data is dominated by three semi-diurnal constituents (i.e. constituents with a period of approx. 12 to 12.5 hours), M2, S2 and N2, and three diurnal constituents, K1, O1 and Q1. At Galway Port tide gauge, the M2 magnitude error between the model and data is 0.07 m. The surge component is calculated for observed and modelled data at the locations of tide gauges. The authors will present the skill of the model as regards the prediction of storm surges to include the comparison between a 3D and 2D configuration.

The mechanisms by which time-dependent wind stress anomalies at mid-latitudes can force variability in the meridional overturning circulation at low latitudes are explored. It is shown that winds are effective at forcing remote variability in the overturning circulation when forcing periods are near the mid-latitude baroclinic Rossby wave basin-crossing timescale. Remote overturning is required by an imbalance in the mid-latitude mass storage and release resulting from the dependence of the Rossby wave phase speed on latitude. A heuristic theory is developed that predicts the strength and frequency-dependence of the remote overturning well when compared to a two-layer numerical model. The theory indicates that the variable overturning strength, relative to the anomalous Ekman transport, depends primarily on the ratio of the meridional spatial scale of the anomalous wind stress to its latitude. For strongly forced systems, a mean deep western boundary current can also significantly enhance the overturning variability at all latitudes. For sufficiently large thermocline displacements, the deep western boundary current alternates between interior and near-boundary pathways in response to fluctuations in the wind, leading to large anomalies in the volume of North Atlantic Deep Water stored at mid-latitudes and in the downstream deep western boundary current transport.

Maize (Zea mays L.) is one of the most consumed grains in the world and improving maize yield is of great importance for food security, especially under global climate change and more frequent severe droughts. However, traditional phenotyping methods relying on manual assessment are time-consuming and prone to human errors. Recently, the application of unmanned aerial vehicles (UAVs) has gained increasing attention in plant phenotyping due to their efficiency in data collection. Moreover, hyperspectral sensors integrated with UAVs can offer data streams with high spectral and spatial resolutions, which are essential for estimating plants’ physiological and biochemical traits. In this study, we developed machine learning models to estimate grain yield and flowering time of maize breeding lines using multi-temporal UAV-based hyperspectral imagery. The performance of multiple machine learning models and the efficacy of different hyperspectral features were evaluated on Genomes to Fields (G2F) experimental sites in Wisconsin. Results showed that ridge regression is the most robust model in estimating grain yield and flowering time, compared to random forest and support vector regression models. Furthermore, the ridge regression model achieved a correlation coefficient (r) of 0.551 for yield, 0.906 for days to silking, and 0.914 for days to anthesis when using the full-bands spectra features for estimation. In addition, we assessed the modeling performance using data acquired from different growing stages. The best time of applying the UAV survey was also identified in order to reduce the data collection efforts.

Our knowledge of glacial history of the western (Norwegian) part of the Barents Sea has greatly improved during the last decades, notably due to the high-resolution multibeam swath bathymetry data. In contrast, published seafloor data from the eastern part of the Barents Sea and the Kara Sea are much more sparse. This study presents new geophysical/geological evidence for reconstructing glacial dynamics of the eastern part of the Barents-Kara Ice Sheet during the Last Glacial Maximum and subsequent deglaciation. Archival data used in this study include more than 300,000 km of sparker and high-resolution Parasound profiles verified by boreholes drilled with continuous core recovery to 50-100 m below sea bed. This dataset was used to construct continuous geological cross-sections and a series of maps, including detailed bathymetry (in 10-m isobaths) and sediment thickness maps of major seismo-stratigraphic units. Based on the bathymetric and sediment thickness data we map megascale glacial lineations, drumlin-like ridges up to 50 m high and subglacial channels up to 100 m deep, as well as accumulations of glacial deposits (basal, lateral and end moraines) and ice-proximal acoustically transparent bodies (ATBs). Spatial and stratigraphic analysis of these bedforms enables us to put forward a new hypothesis that ice moved on the shelf from the Arctic Ocean along the Saint Anna Trough (SAT). Further south, near the northern tip of the Novaya Zemlya islands, the ice flow split into three major lobes moving to the southwest into the Barents Sea and to the south and southeast into the Kara Sea. Deglaciation in the study area progressed with several ice stillstands and subsequent readvances marked by end-moraines and accumulation of ice-proximal sediments. During deglaciation events, when the SAT became ice free due to iceberg calving, the ice flow reversed its direction toward the SAT, forming a fluting and a massive ATB on the western SAT slope. The exact timing and mechanisms of the ice transgression(s) from the Arctic Ocean are not well understood. Additional high-resolution data such as multibeam bathymetry surveys are needed to verify the spatiotemporal distribution of glaciogenic bedforms, and glaciological modeling is required to comprehend the ice dynamics and put it in the pan-Arctic context.

Sanbon Chaka Gosa1, Bogale Abebe Gebeyo12, Ravitejas Patil1, Ramón Mencia1, Dani Zamir1, Menachem Moshelion1# 1 The R.H. Smith Institute of Plant Sciences and Genetics in Agriculture, The R.H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, 76100 Israel 2 Current address: Department of Horticulture, College of Agriculture and Natural Resource, Dilla University, Dilla, Ethiopia #Corresponding Author Abstract Plant productivity in general and under stress, in particular, is a complex and comlitative trait largely influenced by environmental conditions. Among the most important traits are the whole-plant water-balance regulation mechanisms that dynamically change in order to maximize the metabolic activity of the plant. Due to the difficulty of high-throughput phenotyping of these physiological traits (e.g. transpiration, stomatal conductance, and photosynthesis), they are usually measured in static conditions or modeled based on only a few measuring points (low resolution). To overcome this challenge, we utilized a high-throughput gravimetric functional-phenotyping platform (PlantArray) along with a practical reverse phenotyping approach. We selected 30 tomato lines from multiple years of field yield data and functionally phenotyped them for their dynamic response curves using a variety of stress scenarios implemented using drought conditions (each plant received irrigation based on the amount of water it transpired). Our results show that resilient and tolerable traits, in the field, are associated with stomatal plastic conductance, i.e., maximum under well-irrigation, yet the rapid response to changes in environmental conditions (soil and atmospheric). The plastic traits of the idiotype lines were shown to increase water use efficiency (momentarily), thus maximizing yield in water deficit conditions. Based on manual characterizations of the idiotypes, it has been found that their abaxial surfaces have a greater density of stomata and a higher aperture during the early morning. Additionally, these lines showed rapid recovery after a drought. Our study concluded that reverse functional phenotyping can significantly reduce the pre-breading processes for yield-related traits. Keywords: Functional phenotyping, crops yield, —dynamic response, drought stress, stomatal conductance, reverse phenomics

Before complex analysis of oceanographic or any earth science data can occur, it must be placed in the proper domain of computing and software resources. In the past this was nearly always the scientist’s personal computer or institutional computer servers. The problem with this approach is that it is necessary to bring the data products directly to these compute resources leading to large data transfers and storage requirements especially for high volume satellite or model datasets. In this presentation we will present a new technological solution under development and implementation at the NASA Jet Propulsion Laboratory for conducting oceanographic and related research based on satellite data and other sources. Fundamentally, our approach for satellite resources is to tile (partition) the data inputs into cloud-optimized and computation friendly databases that allow distributed computing resources to perform on demand and server-side computation and data analytics. This technology, known as NEXUS, has already been implemented in several existing NASA data portals to support oceanographic, sea-level, and gravity data time series analysis with capabilities to output time-average maps, correlation maps, Hovmöller plots, climatological averages and more. A further extension of this technology will integrate ocean in situ observations, event-based data discovery (e.g., natural disasters), data quality screening and additional capabilities. This particular activity is an open source project known as the Apache Science Data Analytics Platform (SDAP) (https://sdap.apache.org), and colloquially as OceanWorks, and is funded by the NASA AIST program. It harmonizes data, tools and computational resources for the researcher allowing them to focus on research results and hypothesis testing, and not be concerned with security, data preparation and management. We will present a few oceanographic and interdisciplinary use cases demonstrating the capabilities for characterizing regional sea-level rise, sea surface temperature anomalies, and ocean hurricane responses.