Intensification of the Agulhas Leakage (AL) during glacial terminations has long been proposed as a necessary mechanism for reverting the Atlantic Meridional Overturning Circulation (AMOC) to its interglacial mode. However, lack of records showing the downstream evolution of AL signal and substantial temporal differences between AL intensification and resumption of deep‐water convection have cast doubt on the importance of this mechanism to the AMOC. Here, we analyze a combination of new and previously published data relating to Mg/Ca‐derived temperatures and ice volume‐corrected seawater δ18O records (δ18OIVC‐SW, as a proxy for relative changes in ocean salinity), which demonstrate propagation of AL signal via surface and thermocline waters to the western South Atlantic (Santos Basin) during Termination II and the early Last Interglacial. The saline AL waters were temporally stored in the upper subtropical South Atlantic until they were abruptly released in two stages into the North Atlantic via surface and thermocline waters at ca. 129 and 123 ka BP, respectively. Accounting for age model uncertainties, these two stages are coeval with the resumption of convection in the Labrador and Nordic seas during the Last Interglacial. We propose a mechanism whereby both active AL and a favorable ocean‐atmosphere configuration in the tropical Atlantic were required to allow flux of AL waters into the North Atlantic, where they then contributed to enhancing the AMOC during the Last Interglacial period. Our results provide a framework that connects AL strengthening to the AMOC intensifications that followed glaciations.

The 4 July 2019 Mw 6.4 Earthquake and 5 July Mw 7.1 Earthquake struck near Ridgecrest, California. Caltech-Jet Propulsion Laboratory Advanced Rapid Imaging and Analysis (ARIA) project automatically processed synthetic aperture radar (SAR) images from Copernicus Sentinel-1A and -1B satellites operated by the European Space Agency, and products were delivered to the US and California Geological Surveys to aid field response. We integrate geodetic measurements for the three-dimensional vector field of coseismic surface deformation for thee two events and measure the early postseismic deformation, using SAR data from Sentinel-1 satellites and the Advanced Land Observation Satellite-2 (ALOS-2) satellite operated by Japanese Aerospace Exploration Agency. We combine less precise large-scale displacements from SAR images by pixel offset tracking or matching, including the along-track component, with the more precise SAR interferometry (InSAR) measurements in the radar line-of-sight direction and intermediate-precision along-track InSAR to estimate all three components of the surface displacement for the two events together. InSAR coherence and coherence change maps the surface disruptions due to fault ruptures reaching the surface. Large slip in the Mw 6.4 earthquake was on a NE-striking fault that intersects with the NW-striking fault that was the main rupture in the Mw 7.1 earthquake. The main fault bifurcates towards the southeast ending 3 km from the Garlock Fault. The Garlock fault had triggered slip of about 15 mm along a short section directly south of the main rupture. About 3 km NW of the Mw 7.1 epicenter, the surface fault separates into two strands that form a pull-apart with about 1 meter of down-drop. Further NW is a wide zone of complex deformation. We image postseismic deformation with InSAR data and point measurements from new GPS stations installed by the USGS. Initial analysis of the first InSAR measurements indicates the pull-apart started rebounding in the first weeks and the main fault had substantial afterslip close to the epicenter where the largest coseismic slip occurred. Slip on a NE-striking fault near the northern end of the main rupture in the first weeks, in the same zone as large and numerous aftershocks along NE-striking and NW-striking trends shows complex deformation.

In November 2017, the High Resolution Ensemble Forecast version 2 (HREFv2) system was implemented by the U.S. National Oceanic and Atmospheric Administration (NOAA). The HREFv2 is NCEP’s first operational convection-allowing model (CAM) ensemble and runs twice daily at ~3-km horizontal grid spacing. Coinciding with the operationalization of the HREFv2, the NOAA National Weather Service’s Storm Prediction Center (SPC) launched its HREF Ensemble Viewer (https://www.spc.noaa.gov/exper/href), a public web display for real-time HREF data. In addition to products traditionally used in operational forecasting, the HREF Ensemble Viewer also employs post-processing and visualization techniques which leverage the convective structures explicitly modeled in CAM ensembles. This presentation describes and illustrates products from the SPC viewer unique to CAM ensembles which are targeted at forecasting convective storm coverage, intensity, and evolution. A key aspect of HREF’s ensemble design is membership diversity with respect to model cores and parameterization schemes, in conjunction with a time-lagging approach. Verification is performed on ensemble fields related to explicitly modeled convection for various modified configurations of the HREF membership, illustrating how each dimension of membership diversity contributes to the system’s skill in forecasting convective evolution. These results help to illuminate potential tradeoffs entailed in configuring future HREF iterations beyond version 2 as CAMs using new dynamical cores and parameterization schemes become available.

This study reports on the development and implementation of the HydroLearn online platform that supports active learning in the field of hydrology and water resources engineering. The platform is designed to serve the following two main purposes: to enable instructors to collaboratively develop and share active-learning resources, and to enhance student learning in fundamental and emerging topics in the field (e.g., rainfall-runoff processes, design of flood protection measures, flood forecasting, water-energy-food nexus). Using open-source technology, the HydroLearn platform supports customization of pre-developed learning modules and allows instructors to share components of their learning resources with other interested users. HydroLearn is inspired by the need to address challenges in adoption, scalability, and sustainability identified by research on educational innovations. HydroLearn utilizes research-based active learning methods (e.g., Problem-based Learning; Collaborative and Cooperative Learning) to create authentic online learning modules. The modules engage students in real-world hydrologic problems and provide unique opportunities to expose undergraduate students to modern hydrologic analysis tools that are at the forefront of hydrologic research and engineering practice. The platform includes tools that scaffold instructors’ implementation of sound pedagogical practices. The platform includes wizards and pre-populated templates on how to develop student-centered learning outcomes that ensure constructive alignment with the learning content. The platform also includes guidance for instructors on how to develop assessment rubrics to enhance student achievement through communicating the expected performance levels. The study will also share results on the implementation of a pilot learning module on flood protection. Thirty-six undergraduate students were surveyed before and after the implementation to determine their level of learning engagement. The survey measured their skills engagement, emotional engagement, participation, and performance engagement. The presentation will also report on efforts to engage the community through a fellowship program that aims to develop a network of educators who aspire to adopt active learning approaches and enhance hydrology education.

One of the key measurements from the Clouds and the Earth’s Radiant Energy System (CERES) satellite is Earth emitted or longwave (LW) radiation. The CERES Ocean Validation Experiment (COVE), located at Chesapeake Light Station, approximately 25 kilometers east of Virginia Beach, Virginia (coordinates: 36.90N, 75.71W) had provided surface validation for the CERES satellite measurements for many years. Upwelling LW radiation was one of the measurements made at COVE but was complicated due to the Light Station tower being in the upwelling LW instruments field of view. According to our estimates, the Light Station tower alters 15% of the upwelling LW radiation. An unwanted consequence of the tower being in the field of view was the tower radiating effect, particularly noticeable on clear, sunny days. During these days, the tower would radiate extra heat energy by as much as 3% (15 W/m^2) that was measured by the upwelling LW instrument. COVE follows the Baseline Surface Radiation Network requirements and their target uncertainty is 2%. To resolve this issue, we obtain a different upwelling longwave value using data from an infrared radiation thermometer (IRT) and a pyrgeometer that retrieves sea surface temperature (SST) and downwelling longwave respectively. Using an IRT allows conversion from SST to a water emission value and the pyrgeometer provides the reflected flux of the downward longwave radiation. By determining the extent of the undesirable obstruction in the field of view of the upwelling longwave instrument and determining its emissivity could allow others with similar issues to obtain the proper values of upwelling longwave measurements.

Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth’s radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This poster presents the outcome of an international workshop and subsequent review paper, which quantify the likely range of aerosol radiative forcing over the industrial era based on multiple lines of evidence, including modelling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes narrow the range of the forcing from aerosol-radiation interactions compared to the latest assessment by the Intergovernmental Panel on Climate Change (IPCC). A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction and on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to total aerosol radiative forcing ranges that are of similar width to the last IPCC assessment but more clearly based on physical arguments.

Atmospheric drag describes the main perturbing force of the atmosphere on the orbital trajectories of near-Earth orbiting satellites. The ability to accurately model atmospheric drag is critical for precise satellite orbit determination and collision avoidance. Assuming we know atmospheric winds and satellite velocity, area and mass, the primary sources of uncertainty in atmospheric drag include mass density of the space environment and the spacecraft drag coefficient, CD. Historically, much of the focus has been on physically or empirically estimating mass density, while CD is treated as a fitting parameter or fixed value. Presently, CD can be physically modeled through energy and momentum exchange processes between the atmospheric gas particles and the satellite surface. However, physical CD models rely on assumptions regarding the scattering and adsorption of atmospheric particles, and these responses are driven by atmospheric composition and temperature. Modifications to these assumptions can cause CD to change by up to ~40%. The nature and magnitude of these changes also depend on the shape of the spacecraft. We can check the consistency of the CD model assumptions by comparing densities derived from satellite drag measurements and computed CD values for satellites of different shapes orbiting in the same space environment. Since all of the satellites should see the same density, offsets in the derived densities should be attributable to inconsistencies in the CD model. Adjusting the CD model scattering assumptions can improve derived density consistency among the different satellites and inform the physics behind CD modeling. In turn, these efforts will help to reduce uncertainty in CD, leading to improved atmospheric drag estimates.

Estimation of the ionospheric conductance is a crucial step in coupling the magnetosphere & ionosphere (MI). Since the high-latitude ionosphere closes magnetospheric currents, conductance in this region is pivotal to examine & predict MI coupling dynamics, especially during extreme events. In spite of its importance, only recently have impacts of key magnetospheric & ionospheric contributors affecting auroral conductance (e.g., particle distribution, ring current, anomalous heating, etc.) been explored using global models. Addressing these uncertainties require new capabilities in global magnetosphere - ionosphere - thermosphere models, in order to self-consistently obtain the multi-scale, dynamic sources of conductance. This work presents the new MAGNetosphere - Ionosphere - Thermosphere (MAGNIT) auroral conductance model, which delivers the requisite capabilities to fully explore the sources of conductance & their impacts. MAGNIT has been integrated into the Space Weather Modeling Framework to couple dynamically with the BATSRUS magnetohydrodynamic (MHD) model, the Rice Convection Model (RCM) of the ring current, the Ridley Ionosphere Model (RIM) & the Global Ionosphere Thermosphere Model (GITM). This new model is used to address the precise impact of diverse conductance contributors during geomagnetic events. First, the coupled MHD-RIM-MAGNIT model is used to establish diffuse & discrete precipitation using kinetic theory. The key innovation is to include the capability of using distinct particle distribution functions (PDF) in a global model: in this study, we explore precipitation fluxes estimated using isotropic Maxwellian & Kappa PDFs. RCM is then included to investigate the effect of the ring current. Precipitating flux computed on closed field lines by RCM is compared against MAGNIT results, to show that expected results are alike. Lastly, GITM is coupled to study the impact of the ionosphere thermosphere system. Using the MAGNIT model, aforementioned conductance sources are progressively applied in idealized simulations & compared against the OVATION Prime Model. Finally, data-model comparisons against SSUSI, AMPERE & SuperMAG measurements during the March 17, 2013 Storm are shown. Results show remarkable progress of conductance modeling & MI coupling layouts in global models.

Clouds in the tropical western Pacific are dominated by reflective deep convective cores with gradually thinning trailing anvil clouds, which play a crucial role in determining tropical cloud radiative effects. The microphysical controls of the thinning process and its changes when subjected to a future warmer climate are still very uncertain.We use the high resolution version of the Exascale Earth System Model (E3SM) to study the thinning process in present day and future climate. We apply Lagrangian forward trajectories starting at peaks of convective activity of the detected mesoscale convective systems (MCS) and track detrained ice crystals to better understand the processes controlling the transition of a thick detrained anvil cloud into a thin cirrus cloud. The trajectories are computed offline from the 1-hourly model-calculated velocity fields and ice crystal sedimentation velocities. The modeled MCS in present day climate have a comparable time evolution to those observed by Himawari geostationary satellite data, with an average lifetime of about 10-15 hours, which accounts only for the optically thick part of the cold cloud shield. However, E3SM fails to simulate the strongest storms, which is reflected by an underestimation of albedo and overestimation of outgoing longwave radiation. The analysis of ice sources (detrainment, vapor deposition, new nucleation events) and sinks (sublimation, aggregation, sedimentation) along trajectories highlights the crucial role of the balance between depositional growth and precipitation formation for the maintenance of aging anvil clouds. Interestingly, deposition of ice on detrained ice crystals contributes to the majority of the upper tropospheric ice mass. On the other hand, about 80% of the initial cloud mass is removed in the form of precipitation within the first 10 hours of the detrainment event, changing its radiative effect from net negative to net positive. The future climate simulation shows an increase in storm frequency and intensity, an increase in ice water content and albedo in convective cores and thick anvils. The trajectory calculations reveal a 15% decrease in cloud lifetime due to climate change, suggesting a decrease in thin high clouds due to a higher precipitation efficiency and a shift to more negative net cloud radiative effects.

Within a year of its launch date, the ATLAS altimeter on board ICESat-2 is already providing a wealth of critical data of interest across and beyond the cryospheric sciences. With the satellite returning nearly 1 TB of raw data per day, traditional practices of individual research groups downloading large granules of data and then subsetting, processing, and storing them locally are ultimately impractical. We are leading the development of icepyx (formerly icesat2py), an open source Python library designed to easily query, filter, download, and pre-process ICESat-2 datasets. The project’s documentation will include interactive Jupyter Notebook examples, providing a starting point for researchers to create and customize workflows to address their research questions. We actively invite contributions from the community to ensure the project develops in a way that meets a wide range of research needs. The project aims to leverage existing libraries that enable easy parallelization and can be run locally or on cloud-based platforms. As a result, researchers will ultimately download and store minimally-sized subsets of ICESat-2 data and have the opportunity to contribute their code to an established open science project. This presentation will serve to introduce icepyx to the cryosphere community and encourage early adoption of the library by researchers with all levels of coding experience.

Using web standards including Schema.org and JSON-LD, the GeoCODES project extends Schema.org with Project 418's geoscience specific vocabulary. By embedding properly formatted and populated JSON-LD files in web sites serving geolocated datasets, search engines such as Google and Bing are able to parse and index these data sets and then to provide information concerning these datasets via standard web search tools. Due to the difficult nature of properly formatting and populating these JSON-LD structures, the GeoCODES User Interface was created to guide data providers through the process of describing the data and validating the descriptions against standard vocabularies. The result is user friendly and easily extensible web based, mobile device ready tool for automatically generating JSON-LD metadata for organizations and datasets. This ultimately allows the original data to be found and used by both scientists and the public.

The Australian seasonal snowpack can be classified as a marginal maritime snowpack with a temperature near 0 °C throughout the snow season. Subtle changes in atmosphere – snow energetics therefore result in rapid change in snowpack properties, which occur against a background of a warming climate. This has been attributed to a 40% decline in spring snow depths in the past 40 yrs. and geologic records suggest the seasonal snowpack is now near a 2000 yr. minimum. Modelled future snow cover predicts further decline by 57 % to 78 % of current maximum snow depth by the 2040s. Such research primarily attributes this decline in snow cover to global warming. However, the past decline in Australian snow cover can also be attributed to change in synoptic wintertime precipitation patterns that have resulted in a dramatic increase in proportional winter and spring precipitation of tropical origin since the 1950s. Tropical moisture is predominantly transported into southeast Australia during negative phases of the Indian Ocean Dipole (IOD) by northwest cloud bands – visible expressions of atmospheric rivers coupling tropical moisture sources northwest of Australia to the Australian Alps. Here we present a case study of one such event that occurred from the 21 to 23 July 2016 when 118 mm of rain-on-snow over a 12 hr period led to near complete ablation of the snowpack. While predictions of future variability of the IOD due to global warming remain uncertain, we suggest that warming atmospheric temperatures increase the risk of such extreme rain–on-snow events during negative IOD events. Combined with reduced snow cover in response to warmer ambient wintertime temperatures, such rain-on-snow events may further accelerate the reduction in seasonal snow cover in the Australian Alps, possibly on occasions after which the snowpack does not recover before spring. These conditions would present significant challenges to the Australian snow sports industry which is worth $2 billion annually and lead to change in snow dependent ecosystems and alpine hydrology.

Image feature tracking with medium-resolution optical satellite imagery (e.g., Landsat-8) offers measurements of glacier surface velocity on a global scale. However, for slow-moving glaciers (<0.1 m/day), the larger pixel sizes (~15-30 m) and longer repeat intervals (minimum of 16 days, assuming no cloud cover) limit temporal sampling, often precluding analysis of sub-annual velocity variability. As a result, detailed records of short-term glacier velocity variations are limited to a subset of glaciers, often from dedicated SAR image tasking and/or field observations. To address these issues, we are leveraging large archives of very-high-resolution (~0.3-0.5 m) DigitalGlobe WorldView/GeoEye imagery with ~monthly repeat interval and high-resolution (~3-5 m) Planet PlanetScope imagery with ~daily-weekly repeat interval for the period from 2014 to 2019. We are using automated, open-source tools to develop corrections for sensor geometry and image geolocation, and integrating new, high resolution DEMs for improved orthorectification, reducing the uncertainty of short-term (monthly to seasonal) velocity measurements. These temporally dense records will be integrated with other velocity products (e.g., NASA ITS_LIVE), which will allow us to study the evolution of glacier dynamics, and its relationships with local climatology, geomorphology, and hydrology on a regional scale. In this study, we present initial results for surface velocity mapping for glaciers in Khumbu Himalaya, Nepal and Mt. Rainier, USA. We are using high-performance computing environments to scale this analysis to larger glacierized regions in High Mountain Asia and Continental U.S.

Scattering of longwave radiation by cloud particles has been regarded unimportant and hence commonly neglected in global climate models. However, it has been demonstrated by recent studies that cloud longwave scattering plays an unignorable role in modulating the energy budget of the Earth System. Offline radiative transfer calculation showed that excluding cloud longwave scattering could overestimate outgoing longwave radiation and underestimate downward irradiance to the surface, and thus impose excessive cooling onto the atmosphere column. How this physical process interacts with other processes in the Arctic climate system, however, has not been thoroughly evaluated yet. Given the fact that the melting of ice and snow that cover the vast surface of the Arctic region is sensitive to energy budget, and such melting may trigger further feedback mechanisms, the neglection of cloud longwave scattering could bias the regional climate simulations to a considerable extent. We have incorporated cloud longwave scattering into the NCAR CESM and the DoE E3SM and this study analyzed the impact on the simulated polar climates in both earth system models. Cloud longwave scattering leads to a warmer surface air temperature in both models, especially over the wintertime. A detailed surface energy budget analysis is performed, for both the mean state and the temporal variability. Preliminary results suggest that the leading change is downward longwave flux and upward longwave flux, followed by the changes of turbulent heat flux. How the longwave scattering treatments can couple with cloud microphysics and precipitation physics to affect Arctic precipitation is further explored.

A high-resolution model of exospheric temperatures has been developed, with the objective of predicting the global values of exospheric temperatures with greater accuracy. From these temperatures, the neutral densities in the thermosphere can be calculated. This model is derived from measurements of the neutral densities on the CHAMP, GRACE, and Swarm satellites. These data were sorted into 1620, triangular cells on a spherical, polyhedral grid, using coordinates of geographic latitude and local solar time (longitude). A least-error fit of the data is used to obtain a separate set of regression coefficients for each grid cell. Several versions of model functions have been tested, using parameters such as the day-of-year, Universal Time, solar indices, and emissions from nitric oxide in the thermosphere, as measured with the SABER instrument on the TIMED satellite. Accuracy is improved with the addition of parameters that use the total Poynting flux flowing into the Northern and Southern hemispheres. This energy flux is obtained from the solar wind velocity and interplanetary magnetic, using an empirical model. Given a specific date, time, and other inputs, a global map of the exospheric temperature is obtained. These maps show significant variability in the polar regions, that are strongly modulated by the time-of-day, due to the rotation of the magnetic poles around the geographic pole. Values at specific locations are obtained using a triangular interpolation of these results. Comparisons of the exospheric temperatures from the model with neutral density measurements are shown to produce very good results.

From inside the stemflow research community, the past decade’s progress might look great: 1) the number of papers published on stemflow per year has doubled; 2) citations of stemflow publications have more than doubled; and 3) the number of research sites monitoring stemflow is on the rise. However, from a broader perspective, a brief Web of Science bibliometric analysis of the past decade reveals issues with these trends: 1) annual publication numbers have increased year-to-year for most topics in natural science, but stemflow publication trends are lower than related and broader disciplines; 2) self-citation is significantly higher for stemflow research than other disciplines (e.g., 26% compared to 2% for all hydrology); and, most importantly, 3) we may have more stemflow data, but we still lack a clear understanding of stemflow’s mechanistic importance. This creates ambiguities as to whether and how stemflow processes can be incorporated into hydrological models and concepts. In this presentation, I argue that we should progress from using metrics that are exclusively used by those who work on stemflow (e.g., unitless metrics such as funneling and enrichment ratios) towards using scaled flux-per-unit-area metrics that may support better integration into hydrological and ecological models (e.g., water or chemical yield per unit canopy area). While the magnitudes of funneling and enrichment ratios from individual plants have effectively conveyed to broader audiences the possibility for stemflow to play important roles in ecosystem functioning, I argue that we need to now move onto mechanistic investigations of stemflow’s impact on specific processes at ecohydrologically relevant scales. Dimensionless (often individual plant-scale) funneling-type metrics may not be useful in this regard, as they tell us nothing about where stemflow goes or what roles stemflow may play in the ecosystem. They also rely on an estimate of infiltration area, which has rarely been observed to date. Their use is further limited to falling liquid-phase rain, which prevents comparison of stemflow observations/processes under occult precipitation (fog, condensation) or mixed and solid-phase precipitation (snow, rime, etc). Please view the “Make Stemflow Unit-ed Again” companion video on YouTube: https://youtu.be/4vPk9m45V0c

Critical freshwater resources lying within mid-latitude mountain glaciers are vulnerable to a rapidly changing climate. The Lehman Rock Glacier is the only extant glacier mapped within the Great Basin National Park in Nevada. As part of an effort to understand this specialized alpine environment, we have been studying this area and conducting observations with annual student research visitations since 2005. Deploying mixed methods including an embedded sensor network, paleoclimate reconstructions, hydrological observations, and unmanned aerial system (UAS) operations, our team has documented diverse evidence of climate change over interannual to millennial scales. Starting in 2015, we conducted annual surveys of the rock glacier to measure topographic changes. Initially, we used balloon-borne photogrammetry, capturing 600+ images over about 0.1 km2 at an altitude of 500m above ground level (AGL). Despite impartial terrain coverage (50-80%) caused by limited control of the balloon rig in the air, digital elevation modeling (DEM) differencing resolved a net volume loss of 5,300m3 between 2015 and 2016. Submission of a Certification Of Approval (COA) granted our team permission to fly a UAV for the first time within the National Park in 2018 and 2019 to map the rock glacier. UAS surveying over successive days in August with > 80% horizontal and vertical overlap helped achieved 100% coverage with 900+ photos. Using previous year’s DEMs, we have optimized autonomous flight planning at 80m AGL and 168m AGL at 8.5mh and 20kmh, respectively. We will present our most recent computations of the glacier changes from years 2018 and 2019 and discuss how UAS instrumentation techniques are helping us observe changing glacier conditions at centimeter-scale resolution, better understand ecosystem relationships, and improve capabilities to model future landscapes all while mitigating mountain safety issues.

Axial Seamount is the most active submarine volcano in the NE Pacific Ocean, and is monitored by instruments connected to a cabled observatory (the US Ocean Observatories Initiative Cabled Array), supplemented by autonomous battery-powered instruments on the seafloor (at ~1500 m depth). Axial is a basaltic hot spot volcano superimposed on the Juan de Fuca spreading ridge, giving it a robust and apparently continuous magma supply. It has had three effusive eruptions in the last 21 years: in 1998, 2011, and 2015. Deformation measurements have been conducted at Axial Seamount since the late 1980’s with bottom pressure recorders (BPRs) that can detect vertical movements of the seafloor with a resolution of ~1 cm. This monitoring has produced a 22+ year time-series including co-eruption rapid deflation events of 2.5-3.2 meters, separated by continuous gradual inter-eruption inflation at variable rates between 15-80 cm/yr. The overall pattern appears to be inflation-predictable, with eruptions triggered at or near a critical level of inflation. Using this pattern, the 2015 eruption was successfully forecast within a one-year time window, 7 months in advance. As of December 2019, Axial Seamount has re-inflated 1.98 m (~78%) of the 2.54 m it deflated during the 2015 eruption. We are exploring several methods to forecast the next eruption, including daily extrapolation of the average rate of inflation from OOI BPR data during the last 3 months forward in time until it intersects the threshold reached before the 2015 eruption. Using this method with the difference in inflation between two OOI BPR instruments located 3.5 km apart removes noise from tidal residuals and oceanographic signals that are common to both instruments. This method suggests the next eruption is likely between 2020 and 2024. However, this simple method is complicated by uncertainties in the next inflation threshold (the volcano inflated 20 cm higher before the 2015 eruption compared to 2011), changes in the rate of inflation with time, and by intermittent pauses in the inflation (and seismicity) observed since 2015 that have lasted from a week to several months.