We analyzed correlations between solar, interplanetary-medium parameters, and geomagnetic-activity proxies in 27-day averages (a Bartels rotation) for the 2009 – 2016 time interval. We considered two new proxies: I) Bzs GSM (Geocentric Solar Magnetic), calculated as the daily percentage of the IMF southward component along the GSM z-axis and then averaged every 27 days; ii) four magnetospheric indices (T-indices), calculated from the local north-south (X) contributions of the magnetosphere’s cross-tail (TAIL), the symmetric ring current (SRC), the partial ring current (PRC), and the Birkeland current (FAC), derived from the Tsyganenko and Sitnov (J. Geophys. Res. 110, A03208, 2005: TS05) semi-empirical magnetospheric model. Our results suggest, among the parameters tested here, solar facular areas, interplanetary-magnetic field intensity and new proxies derived here could be taken into account in an empirical model, with a 27-day resolution, to explain geomagnetic activity felt on the Earth’s surface in terms of solar surface features and the IMF condition. We further retrieve a clear annual oscillation in series of 27-day-mean values of toward/away asymmetries of geomagnetic-activity indices, which can be interpreted in the light of the Russell–McPherron hypothesis for the semiannual variation of geomagnetic activity (Russell, C.T., and R. L. McPherron (1973), J. Geophys. Res., 78, 92 – 108).

Subduction zones are essential for mantle convection through the recycling of oceanic lithosphere, however, asthenospheric flow at convergent margins is not uniform. Deformation of the asthenosphere can be driven by subduction processes such as, viscous entrainment to plate motions, slab rollback-induced toroidal flow, and mantle wedge dynamics. These mechanisms are critical to understanding volcanism, margin evolution, and lithosphere-asthenosphere coupling. The easternmost Alaska subduction zone has been extensively studied showing evidence from seismic anisotropy for large-scale toroidal flow around the slab edge. Westward however, near the Shumagin Gap, few observations have been made. Along-strike changes in oceanic plate fabric, steepening slab dip, proximity to the slab edge, plate motion, and hydration of the mantle may all influence anisotropy and mantle flow in this region. Here, we evaluate models using independent offshore shear-wave splitting measurements acquired using data from the Alaska Amphibious Community Seismic Experiment (AACSE). We compare our splitting observations to forward models that consider the distribution of anisotropy and the backazimuthal dependence of observations. The models we test include viscously entrained flow due to oceanic plate motion (~310° CW North), anisotropic fabric variations, anisotropy related to bending faults and mantle serpentinization, and changes in frozen anisotropy in the oceanic lithosphere. Onshore shear-wave splitting observations show fast-axis directions ~55° CW North, inconsistent with 2D mantle wedge flow, assuming A-type olivine, but it is consistent with B-type fabric or trench-parallel flow as suggested by previous studies. Offshore splitting observations appear to vary along-strike. Here, two distinct oceanic plate fabrics exist, one developed from a northeast-spreading direction and the other from an east-spreading direction. Frozen anisotropy in the oceanic lithosphere may play a significant role in the splitting signal produced offshore and may be an important contributor to the distribution of seismic anisotropy. By synthesizing onshore and offshore observations here with our understanding of flow at the eastern slab edge, we can build a more complete model of mantle dynamics for the Alaskan subduction zone.

Flood events are influenced by terrestrial factors including land cover, land and water management, watershed physiographic features, and hydro-climatic components including snowmelt and precipitation. In Canada, flooding is a frequent and prominent natural disaster, which is modulated by different flood-generating mechanisms. In this study, we assess the intensity and frequency of three flood-generating mechanisms including Rain on Snow (ROS), intense rainfall, and snowmelt-driven flood events over the Assiniboine-Red River basin, which is one of the most flood-prone regions in Canada and located in the Lake Winnipeg watershed. We downscale and bias correct seven Global Climate Models (GCMs) that participated in CMIP6 using two methods of Bias Correction/Constructed Analogues with Quantile mapping (BCCAQ) (BCCAQ) and Multivariate Bias Correction (MBC). The observed and downscaled climate variables (precipitation and temperature) are used to drive a process-based distributed snow model to evaluate the changes in flood-generation mechanisms in the historical and future periods. The projected future changes are analyzed under policy-relevant global mean temperature (GMT) increases from 1.0 °C to 3.0 °C above the pre-industrial period. Overall, all models project higher regional temperature increases compared to the global mean with warmer and wetter winters. The snow model results indicate future decreases in the snow cover duration, snowmelt rate, and snow water equivalent (SWE), and earlier shifts in the maximum SWE timing. Moreover, both the intensity and frequency of ROS events increase in all seasons except summers. However, the increases in the rain and snowmelt events are mostly projected to occur in the spring.

Building design codes recommend using nonlinear dynamic analysis for an appropriate assessment of the seismic response of several types of structures. To perform nonlinear dynamic analysis, the recorded ground motion time histories of past events with a certain seismic intensity level compatible with the regional seismological characteristic are usually scarce. Therefore, alternative selection and scaling methods on the previously recorded ground motion data set are commonly employed to overcome this issue. However, the type of method and also the random characteristics of earthquake ground motion data induce variability in the estimation of structural response. In this paper, the effect of code-based ground motion selection approaches is investigated in predicting the seismic demand of masonry structures. The dynamic behavior of the masonry prototype is simulated through a 3D numerical model. The material non-linearities are taken into account by adopting a proper constitute law. The data set of PEER is used as the pool for selection and scaling based on alternative codes, including American standard and Eurocode. Results showed that alternative code-based selection approaches reach various seismic demand levels. Keywords: Ground motion records, PEER data set, Scaling, Code-based selection, Masonry structures, Incremental dynamic analysis

Processes and timescales of magmas: U-series, 40Ar/39Ar chronology, and ternary feldspars, for the Quaternary Suswa volcano, Central Kenya Peralkaline Province, East African Rift Vanessa V. Espejel-García a, Elizabeth Y. Anthony b, Peter A. Omenda c, Alan L. Deino d, John C. White e a Facultad de Ingeniería, Universidad Autónoma de Chihuahua, Circuito No. 1, Campus Universitario 2, C.P. 31125, Chihuahua, Chih., México. b University of Texas at El Paso, El Paso, TX 79968, USA c Scientific and Engineering Power Consultants, P.0. Box 38991, Nairobi, Kenya d Berkeley Geochronology Center, Ridge Road, Berkeley, CA, 94709, USA. e Eastern Kentucky University, Richmond, KY 40475, USA Corresponding author. Vanessa V. Espejel-García, [email protected], Tel. (52) 614 221 7549. ORCID a 0000-0002-0486-8726 b 0000-0001-7951-1724 c —- d 0000-0002-0099-9382 e 0000-0001-5107-6847 Suswa is a Late Pleistocene to recent volcano in the axis of the East African Rift. Early activity saw construction of a trachytic shield volcano, followed by mafic-felsic magma mixing, explosive volcanism, and caldera collapse. Recent activity includes drawn down of the magma chamber to create a second, inner caldera, a resurgent dome, and eruption of phonolites (White et al., 2012, Lithos, 152, 88-104). 40Ar/39Ar ages for the initial shield volcano are ca. 110 ka. Formation of the outer caldera occurred at ca. 46 ka, and initial post-caldera eruptions followed soon thereafter at 32.5 ka. Final eruptions are ca. 11 ka to “zero age”. 230Th/232Th confirms simultaneity of mafic eruptions in the peripheral fields and the youthfulness of the final events. The 203Th/232Th data also demonstrate that depth for initial magma generation lies below the spinel peridotite field within garnet peridotite. Ground deformation includes deflation of 4.6 cm from 1997 to 2000 (Biggs et al., 2009) and subsequent inflation of 4.3 +/- 0.8 cm/yr from 2015 to 2020 (Albino and Biggs, 2021, G3). Alkali feldspar from pre- and most syn-caldera has a limited compositional range. Feldspars in mingled lavas include bimodal distribution of these alkali feldspar and plagioclase identical in composition to similar-age cinder cones and fissure flows adjacent to the volcano. Alkali feldspar shifts to greater An content in the post-caldera phonolite. Oscillatory and tabular textures record rapid crystal growth and turbulence in the phonolite magma chamber. However, neither the textures nor the composition range necessitate renewed addition of mafic material.

The frequency of major flooding events continues to increase, fueling the already growing concern in numerous fields about quantifying the inequitable distribution of flood hazards. Our previous work of overlaying high resolution flood exposure data with social vulnerability information has already begun to highlight how different communities experience varying levels of risk. However, this fails to capture the complex nature by which flooding affects interconnected infrastructure and service networks which further have an impact on an individual and community’s risk. Our goal is to quantitatively define an individual’s vulnerability to flooding, encompassing how both pluvial and fluvial inundation impacts an individual’s place of residence and disrupts their access to critical resources, including flood, gas, healthcare, and emergency services, while still considering an individual’s socioeconomic standing. With the goal of estimating household level disruption of access to critical resources in near real time, our approach relies on a multilayer network of social vulnerability, transportation infrastructure, essential resources, and emergency services. To estimate inundation in near real time, we utilize the Heigh Above Nearest Drainage (HAND) method and a topographic depression hierarchy algorithm to estimate fluvial and pluvial flooding. Using a minimum cost flow algorithm, we determine an individual’s relative cost to access resources before, during, and after a major flooding event. Combining technical and social information leads to the identification of communities that are more vulnerable to the physical, economical, and social components of floods. This model will be useful in future descriptive and prescriptive analytical frameworks by identifying critical nodes across networks and providing actionable knowledge on at risk communities. Our model will inform agencies involved in flood management, urban planning, and emergency response on where they can best apply resources to increase the resiliency of communities and the infrastructure they rely on.

Floating photovoltaic solar energy (FPV) are solar photovoltaic systems that float on bodies of water. They are a rapidly expanding renewable energy source emerging as an alternative to land-intensive ground-mounted solar arrays. The applications of this technology are commonly explored through technical potential assessments; a vital step in the development of renewable energy resources that allow for the identification of feasible installation sites and provide an estimation of costs, power generation, and capacity (Lee and Roberts 2018). These assessments are carried out to aid planners, policymakers, and other decision-makers in predicting and achieving goals related to the development of renewable energy; however, some considerations may be overlooked. Assessing the technical potential of solar energy without a standardized methodological framework for site selection may lead to an inconsistent range of generation outcomes, adding to the confusion and lack of confidence that has been a significant barrier to the growth of renewable energy in recent years (Seetharaman 2019) This study systematically reviewed criteria in the published literature emphasizing assessment of FPV technical potential and related siting studies, especially those using geographic technologies. The systematic review was performed in alignment with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Preliminary findings of this systematic review suggest that FPV site selection criteria can be categorized into economic, social, environmental, and technical considerations. We aim to elucidate which criteria within each classification are important to include in an FPV siting study based on the current literature. Results from this analysis will inform the standardization of a site-selection framework used in future technical potential studies, which may, in turn, improve the accuracy of generation estimates and offer a meaningful and realistic idea of how FPV installations could transform the direction of renewable energy science and development.

Hydrologic and water quality models are often used to understand and simulate non-point source nutrient inputs to receiving waterbodies afflicted by eutrophication. The most widely used hydrologic-water quality model for estimating non-point source nutrient loads from agricultural uplands is the Soil and Water Assessment Tool (SWAT). SWAT uses the QUAL-2E 1-dimensional steady-state model to simulate in-stream processes that govern the transport of nutrients through channels and rivers. However, the instream-solute transport routine within SWAT is limited in predicting phosphorus cycling and algal dynamics. In this study, we improve the in-stream module of SWAT+, a restructured version of SWAT. We apply the modified SWAT+ to the Western Lake Erie Basin to examine how improved representation of the in-stream module influences nutrient dynamics from the edge-of-field through streams and to the watershed outlet. Our source code modifications focus on improving the representation of phosphorus exchange between the stream bed and the water column. This phosphorus exchange is governed by the equilibrium phosphorus concentration (EPC), which determines whether the stream bed is a phosphorus source or sink, and a phosphorus transformation coefficient which determines the rate of P exchange. These improvements to the in-stream routine within SWAT+ will aid decision-makers in understanding the time lags and management levers needed to achieve water quality targets for large basins.

Abstract The repetitive narrative that, “Tsunami waves and receded coastal water initiated by an earthquake are closely related,” is analyzed through the sequential events that followed the earthquake; a mechanism based on the interaction of receded water with magma is suggested to explain the amplification of Tsunami wave deep beneath the ocean floor (Fig.1), where earthquake occurred under the seabed’s or in coastline; the mechanism explained how the water is amplified into steam in the magma chamber, as its volume increased 1,700 times, the transformed water encompass the tremendous force that uplifted the ocean water endowed it with such destructive force; the mechanism explained characteristics related to Tsunami wave, including relation with earthquake and volcano, receding costal water, the foams, inundation, runup, the nature of the great force of Tsunami, ideas to calculate the magnitude of Tsunami force and energy, volume of receded water, volume of tsunami wave, the repetition of its wave; these and related issues are stated; the idea is derived based on the continual flow of lava from earth’s interior and the existence of magma reservoir bellow earth’s surface in places like Yellowstone in USA and hotspot beneath Hawaii, such magma chamber when existed under seabed, if opened by crack during earthquake, can easily lead to an interaction between receded water and the magma, resulted in the suggested mechanism, all is based on logical analyses and deep thinking to attained the Tsunami Mechanism in response to 2004 and 2011 human tragedies; thus understanding this mechanism will help laying measures to counter the phenomenon, which will reflect positively in saving lives and mitigate its destructive force and reduce consequences of its impact on local societies and above all to understand its true mechanism.

The most simple representation of the dynamics of the global energy budget is the 0-dimensional energy balance model (EBM) introduced by Budyko (1965). Budyko’s EBM assumes a linear relationship between the Earth’s radiative response and the global surface temperature such that the dynamics of the global energy budget reads CdTs/dt = N = F - λ Ts, where Ts is the global surface temperature, N is the Earth Energy Imbalance, C is the ocean heat capacity and λ is the constant climate feedback parameter. Such simple conceptual model depicts reasonably well the centennial time scale response of the steady state preindustrial global energy budget under an anomalous forcing such as the increase of atmospheric greenhouse gases concentrations. For this reason it has served as the basis for the definition of the effective climate sensitivity to atmospheric CO2 concentrations. However recent studies identified limitations to Budyko’s EBM. Indeed climate model simulations show that the radiative response of the Earth not only depends on the global surface temperature but also on its geographical pattern: the so-called “pattern effect”. It arises from changes in the mix of radiative forcings, lag-dependent responses to forcings, or unforced variability and it leads to an apparent time variation in λ. This time variation must be accounted for in Budyko’s EBM to represent the longer term response of the global energy budget under increased CO2 concentrations. Here, a simple theory is developed to account for the time dependency of λ in the global energy budget. The resulting differential equation accurately reproduces the long term response (i.e. >200 years) of climate under abrupt changes in CO2 concentrations as simulated in the longrunmip experiment. Analysis of the asymptotic form of the differential equation yields a new expression of the climate sensitivity which not only depends on the climate feedback parameter but also on its temporal change. We evaluate this new climate sensitivity for all runs of the longrunmip experiment and show how it relates with the classical effective climate sensitivity from Gregory et al. (2004). We find that the spread in climate sensitivity among climate models of the longrunmip experiment is essentially due to different temporal changes in λ (and thus different pattern effect) among models.

Martian dust, which likely formed by non-aqueous chemical weathering [Huguenin, 1976] following broad-based support from recent Mars mission data, is susceptible to rapid diagenesis when exposed to macro-seepage from the sub-permafrost aqueous aquifer system on Mars . The modeled silicate components of the dust, derived from the non-aqueous weathering of primarily olivine and pyroxene, are Mg2HSiO4(OH) and Mg(HSiO3)(OH). These are M-S-H compounds, counterparts to the C-H-S compounds that form the commercial binder in concrete, forming an Mg3Si2O5(OH)4 counterpart binder on Mars upon exposure to liquid H2O macro-seepage from the aquifer below. Macro-seepage, triggered largely by geothermally heated water near impact sites, magmatic intrusions and volcanoes, is proposed to rapidly cement layers of regolith dust and fines into layers of M-S-H counterpart “concrete.” The matrix binder on Mars is predicted to be a member of the serpentine family (Mg/Si = 5), possibly having disordered Antigorite T structure. Layered sedimentary rock formations could have formed throughout geologic history up to the present time. Materials from the aquifer, transported by and introduced from the macro-seepage, including organic matter, may be contemporary rather than ancient. This contradicts the prevailing assumption that the sedimentary rocks were formed early in the planet’s history.

Multiphysics urban flood models are commonly used for urban infrastructure development planning and evaluating risk due to climate change and sea level rise. However, these integrated flood models rely on several parameters that are hard to measure directly, and the resulting uncertainty in model prediction needs to be quantified, often without observable data. As a part of the Urban Flooding Open Knowledge Network (UFOKN) project, in this study we quantify parametric uncertainty in urban flood models. UFOKN incorporates flood model predictions in combination with machine learning, data and computer science, epidemiology, socioeconomics, and transportation and electrical engineering to minimize economic and human losses from future urban flooding in the United States. As a case study, we choose the Interconnected Channel and Pond Routing (ICPR) numerical model to simulate flooding in the city of Minneapolis in response to the design storms (e.g., 100-year rainfall). Through a sensitivity study, we reduce the number of uncertain model parameters to the Manning’s roughness coefficient and vertical hydraulic conductivity of soil, and construct the distributions of these parameters using open databases. We employ the multilevel Monte Carlo (MLMC) method that combines a small number of high-resolution ICPR simulations with a larger number of low-resolution simulations to reduce the computational cost of computing the key statistics of the quantities of interest describing the urban flooding. Our results show that the uncertainty in the flood predictions (as described by the coefficient of variation of the flood water depth) is distributed highly non-uniformly in the urban area with the coefficient of variation exceeding 0.5 limited to a relatively few computational elements in the ICPR model. Our results demonstrate that urban flood models such as ICPR can provide reliable flood predictions and can be used for a targeted data acquisition to further reduce the parametric uncertainty.

Our prior analysis of a coupled tropical cyclone (TC) air-sea model (HWRF-B) revealed three cases in the 2020 Atlantic hurricane season where coastal downwelling - developing ahead of a TC - contributed to the intensification of each TC as it approached landfall. Coastal downwelling is a specific oceanographic mechanism: we briefly consider other mechanisms potentially contributing to this “shelf effect”, including coastal trapped waves and near-surface advection. We then present preliminary results from a further analysis of HWRF-B forecasts from the 2017-2020 Atlantic and east Pacific hurricane seasons, evaluating the prevalence of the shelf effect for TCs interacting with continental and insular coasts in these two ocean basins. We explore mechanisms linking shelf SST sustenance with inner core convective development and storm intensification, using both a detailed energy budget and Lagrangian tracking experiments within the boundary layers of case study storms. Finally, we briefly discuss the implications these findings hold for evaluating new coupled TC forecast modeling systems currently being developed as a part of the Hurricane Forecast Improvement Program (HFIP).

Mars present-day middle and upper atmosphere, above ~100 km, connects the deep atmosphere to the Martian space environment. This region is important to understand for many reasons, including for more general insights into the evolution of atmospheres, as a comparison to other planetary atmospheres, and for current and future mission development and interpretation. The middle/upper atmosphere is greatly influenced by the physics of the lower atmosphere (water cycle, dust cycle, waves, etc.) and the solar environment (solar magnetic activity, solar events). It contains the upper branch of the overturning meridional circulation and the transitional point of the main heating source from near-IR to UV radiation. These influences feed on a primitive property of an atmosphere: temperature. This work will break down the radiative processes that drive the Martian’s thermal structure above ~100 km as a function of latitude and season. We demonstrate the on-going work on extending the NASA Ames Mars Global Climate Model (MGCM), now using the NOAA/GFDL FV3 dynamical core. The MGCM nominally extends from the surface up to ~80 km but new physics packages will extend the MGCM’s vertical domain up to ~250 km. We present the heating and cooling mechanisms that dominate this atmospheric region, discuss the parametrizations used, the state of the seasonal/diurnal thermal structure, and finally, we discuss the work in progress for the development and implementation of physics schemes in our model.

The high energetic plasma and the embedded magnetic field of coronal mass ejections interact with planetary magnetospheres giving rise to transient perturbations such as geomagnetic storms. Predicting the geomagnetic impact of such interplanetary coronal mass ejections (ICME) is of utmost importance for the protection of our technological infrastructure that is affected by space weather. We use 3D compressible magnetohydrodynamic simulation of a star-planet system to model and study an ICME-Earth interaction event of 20th November 2003. In the modelled interaction, we observe a change in magnetopause shape and stand-off distance on ICME impact, day and night side reconnections and induction of high currents in the magnetosphere. We also notice the formation of a ring of strong equatorial current around the Earth, leading to a reduction of the geomagnetic field. We calculate the simulated reduction in the magnetic field and compare that to the observed geomagnetic indices in order to establish a predictive approach for geomagnetic storms. These simulations are expected to illuminate the physical processes that result in space weather impacts of stellar magnetic storms in planetary and exoplanetary systems.

Are the Sermilik Fjord glaciers terminus-controlled, runoff-controlled, or runoff-adapting? Decomposition of glacier speed maps at Helheim, Fenris, Midgard, and Pourquoi-Pas Glaciers Previous research has identified three common seasonal patterns (“types”) of ice flow at Greenland glaciers (Moon et al., 2014; Vijay et al., 2019). Some glaciers have a consistent type, while others change from year to year. Neighboring glaciers may have the same or different type. Previously, types were identified by examining flow at a single point. This limitation may affect the inferred variability. We use principal component (PC) / empirical orthogonal function (EOF) analysis to decompose maps of ice speed (Joughin et al., 2018; Joughin, 2021; Howat, 2020; Scambos et al., 206; Rosenau et al., 2015; Solgaard & Kusk, 2021) at four glaciers feeding Sermilik Fjord over 2014-2021. This improves on the previous single-point method by yielding temporal patterns (PCs), which allow types to be identified, plus their associated spatial patterns (EOFs). Helheim Glacier shows the most spatial and temporal heterogeneity of the four glaciers. PC #1 (95% of the variance in 2014-2021 speed) suggests primarily terminus control (p=0.003) but also some runoff control (p=0.05). PC #2 (1% of the variance in 2014-2021 speed) shows only runoff control (p=0.006). Previous work found that Helheim can be either terminus- or runoff-controlled. Fenris Glacier is runoff-adapting (PC #1, 66% of the variance in 2014-2021 speed). This disagrees with previous work that classified it as terminus-controlled. On Midgard Glacier, PC #1 (79% of the variance in 2014-2021 speed) is consistent with runoff-adapting behavior (p<0.0001). EOF #2 shows that the lowest 4 km is more runoff-controlled (p<0.00001) or terminus-controlled (p=0.04) than the upstream area. Our conclusion agrees with previous work that classified Midgard as runoff-adapting. Since separating from Midgard in 2009, Pourquoi Pas Glacier has slowed near the terminus while accelerating upstream. EOF #1 shows this pattern (67% of the variance in 2014-2021 speed); its PC shows runoff control. Previous work classified Pourquoi Pas as terminus-controlled. Overall, these results agree moderately with previous, simpler analyses. Thus, application of EOF/PC analysis to the popular “glacier type” problem holds some promise in the quest to discover what controls the seasonal flow patterns of Greenland glaciers.

OpenET is a software system that makes satellite-based multi-model estimates of evapotranspiration (ET) accessible at multiple spatial and temporal scales over the U.S. Large-scale ET estimates fill a critical data-gap for irrigation management, water resources management, and hydrological modeling and research. We present the methods and results of the second phase of an intercomparison and accuracy assessment between OpenET satellite-based models (ALEXI/DisALEXI, eeMETRIC, PT-JPL, geeSEBAL, SIMS and SSEBop) and a benchmark ground-based ET dataset with data from nearly 200 eddy covariance towers across the contiguous U.S. Processing steps for the benchmark dataset included gap-filling, energy balance closure correction, calculation of closed and unclosed daily ET, and multiple levels of data QA/QC. The dataset was split into three groups, phase I and II of the intercomparison and a reserve dataset for future studies. To sample satellite-based ET pixels, static flux footprints were generated at each station based on dominant wind speed and direction. Where data allowed, two dimensional flux footprints that are weighted by hourly ETo were developed and used for ET pixel sampling. A wide range of visual and statistical comparisons between satellite and ground-based ET were conducted at each station and against stations grouped by land cover type. Based on key performance metrics including bias, coefficient of determination, and root mean square error, model results show promising agreement at many flux sites considering the inherent uncertainty in station data. Remote sensing models show the highest agreement with closed station ET in irrigated annual cropland settings whereas locations of native vegetation with high aridity and some forested stations show relatively less agreement. The benchmark ET dataset was used to explore different approaches to computing a single ensemble estimate from the six model ensemble, with the goal of reducing the influence of model outliers and selection of weighting and data sampling schemes to reduce the influence of flux stations with sparse or extensive data records. We present the results from the model intercomparison and accuracy assessment and discuss model performance relative to accuracy requirements from the OpenET user community.

Coarsening a numerical mesh using methods of multiphase flow property upscaling is essential in almost any modeling application due to computational limits. In CO2 storage modeling, after injection wells have been shut off or far away from the wells, CO2 migrates upwards under the influence of gravity and capillary forces. Upscaling permeability (k), relative permeability (kr) and capillary pressure (Pc) is required for grid coarsening these models. However, it has been shown that this is a difficult problem and using conventional upscaling methods such as the common capillary limit upscaling approach leads to large modeling errors. This work presents a new upscaling method based on an effective property formula for k, power law averaging in the capillary limit for kr, and an optimization approach for Pc. The new method is tested on various example cases and coarse-grid simulations are shown to match fine-grid ones with sufficient accuracy. The challenge of upscaling the flows is found to be related to entry pressure trapping and the optimization upscaled Pc is shown to have a unique structure allowing to model the trapping. The method is global, requiring a fine-grid simulation for calibration of the optimized parameters. However, we show that the method reduces computational time dramatically if calibrated parameters are used in similar cases in which the fine-grid solution is unknown, such as for varying k realizations.