publications

2025

1. Coastal storm-induced flooding risk of the New York City subway amid climate change

   Yuki Miura, Christine Y. Blackshaw, Michelle S. Zhang, Kyle T. Mandli, and George Deodatis

   Transportation Research Part D: Transport and Environment, 2025

   Abs DOI

   Coastal areas face worsening storm-induced flooding due to climate change, threatening critical below-ground infrastructure like subway systems, as seen from Hurricane Sandy’s catastrophic impact on New York City (NYC)’s subway system in 2012. Stakeholders must urgently address these risks to protect infrastructure and assets. Simulating future flood scenarios is crucial for estimating flood risk and damage efficiently and for identifying reliable and effective protective measures. This article uses the GIS-based Subdivision-Redistribution (GISSR) methodology, a high-speed, physics-based flood estimation tool, that is now extended to model subway system flooding and associated economic impacts. It identifies flooded tunnels and stations and quantifies indirect economic losses from subway inoperability using an input–output model. The model is validated against observed subway flooding during Hurricane Sandy. Each analysis, covering both above- and below-ground flooding in Lower Manhattan, takes less than 90 s on a single 4-core Intel Core i7-13620H CPU machine. Scenario analyses were conducted with NYC stakeholders, incorporating sea level rise projections and various protective measures. Results, benchmarked against NYC’s ongoing resiliency projects, demonstrate the effectiveness of adaptation/protective strategies, particularly when subway system-specific and coastal measures are combined, highlighting the model’s value as a practical guide for stakeholders.

2. Assessment of Caribbean Coastal Hazard Posed by Tropical Cyclones

   Mona Hemmati, Chia-Ying Lee, Kyle T. Mandli, Adam H. Sobel, Suzana J. Camargo, and 1 more author

   Journal of Applied Meteorology and Climatology, 2025

   DOI
3. Impacts of barrier-island breaching on mainland flooding during storm events applied to Moriches, New York

   Catherine R. Jeffries, Robert Weiss, Jennifer L. Irish, and Kyle Mandli

   Natural Hazards and Earth System Sciences, 2025

   Abs DOI

   Barrier islands can protect the mainland from flooding during storms through reduction of storm surge and dissipation of storm-generated wave energy. However, the protective capability is reduced when barrier islands breach and a direct hydrodynamic connection between the water bodies on both sides of the barrier island is established. Breaching of barrier islands during large storm events is complicated, involving nonlinear processes that connect water, sediment transport, dune height, and island width, among other factors. In order to assess how barrier-island breaching impacts flooding on the mainland, we used a statistical approach to analyze the sensitivity of mainland storm surge to barrier-island breaching by randomizing the location, time, and extent of a breach event. We created a framework that allows breaching to develop during the course of a simulation and imposes a breach in an approximation of a Gaussian bell curve that deepens over time. We show that simulating a storm event and varying the size, location, and number of breaches in the barrier island that mainland storm surge and horizontal inundation is affected by breaching; total inundation has a logarithmic relationship with total breach area which tapers off after the entire island is removed. Breach location is also an important predictor of inundation and bay surge. The insights we have gleaned from this study can help prepare shoreline communities for the differing ways that breaching affects the mainland coastline. Understanding which mainland locations are vulnerable to breaching, planners and coastal engineers can design interventions to reduce the likelihood of a breach occurring in areas adjacent to high flood risk.

4. Tapestries of Knowledge: Using Convergence Science to Weave Indigenous Science and Wisdom with other Scientific Approaches to Climate Challenges

   Julie Maldonado, Heather Lazrus, Lilia Davis, Stephanie Herring, Carlos Martinez, and 19 more authors

   Bulletin of the American Meteorlogical Society, 2025

   DOI

   
5. Coupling Coastal and Hydrologic Models through Next Generation National Water Model Framework

   Ebrahim Hamidi, Hart Henrichsen, Abbie Sandquist, Hongyuan Zhang, Hamed Moftakhari, and 4 more authors

   Journal of Hydrologic Engineering, 2025

   DOI

2024

1. Climate Change Contributions to Increasing Compound Flooding Risk in New York City

   Ali Sarhadi, Raphaël Rousseau-Rizzi, Kyle Mandli, Jeffrey Neal, Michael P Wiper, and 2 more authors

   Bulletin of the American Meteorological Society, 2024

   Abs DOI

   

   Abstract Efforts to meaningfully quantify the changes in coastal compound surge- and rainfall-driven flooding hazard associated with tropical cyclones (TCs) and extratropical cyclones (ETCs) in a warming climate have increased in recent years. Despite substantial progress, however, obtaining actionable details such as the spatially and temporally varying distribution and proximal causes of changing flooding hazard in cities remains a persistent challenge. Here, for the first time, physics-based hydrodynamic flood models driven by rainfall and storm surge simultaneously are used to estimate the magnitude and frequency of compound flooding events. We apply this to the particular case of New York City. We find that sea level rise (SLR) alone will increase the TC and ETC compound flooding hazard more significantly than changes in storm climatology as the climate warms. We also project that the probability of destructive Sandy-like compound flooding will increase by up to 5 times by the end of the century. Our results have strong implications for climate change adaptation in coastal communities.

2023

1. Episodic Magma Hammers for the 15 January 2022 Cataclysmic Eruption of Hunga Tonga‐Hunga Ha’apai

   Yingcai Zheng, Hao Hu, Frank J. Spera, Melissa Scruggs, Glenn Thompson, and 6 more authors

   Geophysical Research Letters, 2023

   Abs DOI

   Understanding the forces and magma system dynamics on timescales of seconds to minutes remains challenging. In the January 2022 phreatoplinian Hunga Tonga‐Hunga Ha’apai eruption, four remarkably similar seismic subevents within a 5‐min interval occurred during the intensifying early eruptive phase. The subevents are similar in waveforms and durations (∼25 s each). Each subevent begins with an unusual negative P‐wave polarity which is inferred, using full‐wave seismic modeling, to be caused by an upward single‐force mechanism at the volcano created by a magma hammer likely in response to magma flow blockage/constriction during the early part of the eruption as discharge rapidly increased over orders of magnitude with concomitant conduit geometry evolution and instability. Our proposed episodic magma hammer model is consistent with thermodynamic and phase properties of the magmatic mixture, and yields an estimate of conduit mass flow in agreement with vent discharge rates derived from satellite imagery of plume heights. The seismic record of the 15 January 2022 Hunga Tonga‐Hunga Ha’apai explosive eruption exhibited a remarkably regular pattern, recording repeating volcanic processes. Within an interval of ∼300 s during an early eruptive phase, four strong seismic subevents occurred and were recorded by global seismic stations. Detailed seismic analyses showed that each of these subevents is similar in waveform and duration and is characterized by a sequence of four forces: upward, downward, upward, and downward. We suggest that the first upward seismic force at the volcano was likely created by an ascending magma colliding with a blockage or conduit constriction that occurred during and because of the ongoing eruption. We attribute the other forces to upward magma backflow and piston motion in the conduit, owing to their similar time durations. The magma hammer mechanism allows us to estimate the magma flow rate in the subsurface conduit, which is consistent with the vent discharge rate observed by satellite imagery. The 15 January 2022 Hunga Tonga‐Hunga Ha’apai eruption had four episodic seismic subevents with similar waveforms within ∼300 s An unusual upward force jump‐started each subevent A magma hammer explains the force and estimates the subsurface magma mass flux which fits the vent discharge rate based on satellite data The 15 January 2022 Hunga Tonga‐Hunga Ha’apai eruption had four episodic seismic subevents with similar waveforms within ∼300 s An unusual upward force jump‐started each subevent A magma hammer explains the force and estimates the subsurface magma mass flux which fits the vent discharge rate based on satellite data

2. Advances in Morphodynamic Modeling of Coastal Barriers: A Review

   Steven W.H. Hoagland, Catherine R. Jeffries, Jennifer L. Irish, Robert Weiss, Kyle Mandli, and 3 more authors

   Journal of Waterway, Port, Coastal, and Ocean Engineering, 2023

   Abs DOI

   As scientific understanding of barrier morphodynamics has improved, so has the ability to reproduce observed phenomena and predict future barrier states using mathematical models. To use existing models effectively and improve them, it is important to understand the current state of morphodynamic modeling and the progress that has been made in the field. This manuscript offers a review of the literature regarding advancements in morphodynamic modeling of coastal barrier systems and summarizes current modeling abilities and limitations. Broadly, this review covers both event-scale and long-term morphodynamics. Each of these sections begins with an overview of commonly modeled phenomena and processes, followed by a review of modeling developments. After summarizing the advancements toward the stated modeling goals, we identify research gaps and suggestions for future research under the broad categories of improving our abilities to acquire and access data, furthering our scientific understanding of relevant processes, and advancing our modeling frameworks and approaches.

3. Coastal Sediments 2023, The Proceedings of the Coastal Sediments 2023

   Ping Wang, Elizabeth Royer, Julie D Rosati, MEGAN A BEEVER, JENNIFER L IRISH, and 3 more authors

   In Coastal Sediments 2023, 2023

   Abs DOI

   This paper will discuss the beginnings of a sensitivity analysis of barrier island breaching. The study area of Mantoloking, New Jersey, USA is used as the barrier island breached significantly during Hurricane Sandy in 2012. The numerical model XBeach is used to conduct this study. The study investigates the affects that back-bay currents, water-level timing, and barrier-island configuration have on barrier island breaching. The results will lead to a better understanding of how certain parameters such as dune geometry and channelization of the back-bay contribute to the short-term morphological process of breaching during coastal storm events.

4. Manifold Approximations via Transported Subspaces: Model Reduction for Transport-Dominated Problems

   Donsub Rim, Benjamin Peherstorfer, and Kyle T. Mandli

   SIAM Journal on Scientific Computing, 2023

   Abs DOI

   This work presents a method for constructing online-efficient reduced models of large-scale systems governed by parametrized nonlinear scalar conservation laws. The solution manifolds induced by transport-dominated problems such as hyperbolic conservation laws typically exhibit nonlinear structures, which means that traditional model reduction methods based on linear approximations are inefficient when applied to these problems. In contrast, the approach introduced in this work derives reduced approximations that are nonlinear by explicitly composing global transport dynamics with locally linear approximations of the solution manifolds. A time-stepping scheme evolves the nonlinear reduced models by transporting local approximation spaces along the characteristic curves of the governing equations. The proposed computational procedure allows an offline/online decomposition and is online-efficient in the sense that the complexity of accurately time stepping the nonlinear reduced model is independent of that of the full model. Numerical experiments with transport through heterogeneous media and the Burgers equation show orders of magnitude speedups of the proposed nonlinear reduced models based on transported subspaces compared to traditional linear reduced models and full models.

2022

1. Extreme Water Level Simulation and Component Analysis in Delaware Estuary during Hurricane Isabel

   Dongxiao Yin, David F. Muñoz, Roham Bakhtyar, Z. George Xue, Hamed Moftakhari, and 2 more authors

   JAWRA Journal of the American Water Resources Association, 2022

   Abs DOI

   Sea level rise and intense hurricane events make the East and Gulf Coasts of the United States increasingly vulnerable to flooding, which necessitates the development of computational models for accurate water level simulation in these areas to safeguard the coastal wellbeing. With this regard, a model framework for water level simulation over coastal transition zone during hurricane events is built in this study. The model takes advantage of the National Water Model’s strength in simulating rainfall–runoff process, and D‐Flow Flexible Mesh’s ability to support unstructured grid in hydrodynamic processes simulation with storm surges/tides information from the Advanced CIRCulation model. We apply the model on the Delaware Estuary to simulate extreme water level and to investigate the contribution of different physical components to it during Hurricane Isabel (2003). The model shows satisfactory performance with an average Willmott skill of 0.965. Model results suggest that storm surge is the most dominating component of extreme water level with an average contribution of 78.16%, second by the astronomical tide with 19.52%. While the contribution of rivers is mainly restricted to the upper part of the estuary upstream of Schuylkill River, local wind‐induced water level is more pronounced with values larger than 0.2 m over most part of the estuary.

2. A Novel Framework for Parametric Analysis of Coastal Transition Zone Modeling

   Taher Chegini, Gustavo de Almeida Coelho, John Ratcliff, Celso M. Ferreira, Kyle Mandli, and 2 more authors

   JAWRA Journal of the American Water Resources Association, 2022

   Abs DOI

   Vulnerability of coastal regions to extreme events motivates an operational coupled inland‐coastal modeling strategy focusing on the coastal transition zone (CTZ), an area between the coast and upland river. To tackle this challenge, we propose a top‐down framework for investigating the contribution of different processes to the hydrodynamics of CTZs with various geometrical shapes, different physical properties, and under several forcing conditions. We further propose a novel method, called tidal vanishing point (TVP), for delineating the extent of CTZs through the upland. We demonstrate the applicability of our framework over the United States East and Gulf coasts. We categorize CTZs in the region into three classes, namely, without estuary (direct river–coast connection), triangular‐, and trapezoidal‐shaped estuary. The results show that although semidiurnal tidal constituents are dominant in most cases, diurnal tidal constituents become more prevalent in the river segment as the discharge increases. Also, decreasing the bed roughness value promotes more significant changes in the results than increasing it by the same value. Additionally, the estuary promotes tidal energy attenuation and consequently decreases the reach of tidal signals through the upland. The proposed framework is generic and extensible to any coastal region.

3. Under the surface: Pressure-induced planetary-scale waves, volcanic lightning, and gaseous clouds caused by the submarine eruption of Hunga Tonga-Hunga Ha’apai volcano

   David A. Yuen, Melissa A. Scruggs, Frank J. Spera, Yingcai Zheng, Hao Hu, and 9 more authors

   Earthquake Research Advances, 2022

   Abs DOI

   We present a narrative of the eruptive events culminating in the cataclysmic January 15, 2022 eruption of Hunga Tonga-Hunga Ha’apai Volcano by synthesizing diverse preliminary seismic, volcanological, sound wave, and lightning data available within the first few weeks after the eruption occurred. The first hour of eruptive activity produced fast-propagating tsunami waves, long-period seismic waves, loud audible sound waves, infrasonic waves, exceptionally intense volcanic lightning and an unsteady volcanic plume that transiently reached—at 58 ​km—the Earth’s mesosphere. Energetic seismic signals were recorded worldwide and the globally stacked seismogram showed episodic seismic events within the most intense periods of phreatoplinian activity, and they correlated well with the infrasound pressure waveform recorded in Fiji. Gravity wave signals were strong enough to be observed over the entire planet in just the first few hours, with some circling the Earth multiple times subsequently. These large-amplitude, long-wavelength atmospheric disturbances come from the Earth’s atmosphere being forced by the magmatic mixture of tephra, melt and gasses emitted by the unsteady but quasi-continuous eruption from 0402±1–1800 UTC on January 15, 2022. Atmospheric forcing lasted much longer than rupturing from large earthquakes recorded on modern instruments, producing a type of shock wave that originated from the interaction between compressed air and ambient (wavy) sea surface. This scenario differs from conventional ideas of earthquake slip, landslides, or caldera collapse-generated tsunami waves because of the enormous (∼1000x) volumetric change due to the supercritical nature of volatiles associated with the hot, volatile-rich phreatoplinian plume. The time series of plume altitude can be translated to volumetric discharge and mass flow rate. For an eruption duration of ∼12 ​h, the eruptive volume and mass are estimated at 1.9 ​km3 and ∼2 900 ​Tg, respectively, corresponding to a VEI of 5–6 for this event. The high frequency and intensity of lightning was enhanced by the production of fine ash due to magma—seawater interaction with concomitant high charge per unit mass and the high pre-eruptive concentration of dissolved volatiles. Analysis of lightning flash frequencies provides a rapid metric for plume activity and eruption magnitude. Many aspects of this eruption await further investigation by multidisciplinary teams. It represents a unique opportunity for fundamental research regarding the complex, non-linear behavior of high energetic volcanic eruptions and attendant phenomena, with critical implications for hazard mitigation, volcano forecasting, and first-response efforts in future disasters.

4. Advancing Interdisciplinary and Convergent Science for Communities: Lessons Learned through the NCAR Early-Career Faculty Innovator Program

   Anamaria Bukvic, Kyle Mandli, Donovan Finn, Talea Mayo, Gabrielle Wong-Parodi, and 8 more authors

   Bulletin of the American Meteorological Society, 2022

   Abs DOI

   Abstract The authors introduce the National Center for Atmospheric Research’s Early-Career Faculty Innovator Program and present lessons learned about advancing interdisciplinary and convergent science with and for society. The Innovator Program brings together faculty and students from the social sciences with NCAR researchers to conduct interdisciplinary and convergent research on problems motivated by societal challenges in the face of climate change and environmental hazards. This article discusses aspects of program structure and the research being conducted. The article also emphasizes the challenges and successes of the research collaborations within the Innovator Program, along with lessons learned about engaging in highly interdisciplinary, potentially convergent work, particularly from the early-career perspective. Many projects involve faculty PIs from racially, ethnically, or otherwise minoritized groups, and minority serving institutions (MSIs), or those who engage with marginalized communities. Hence, the Innovator Program is contributing to the development of a growing research community pursuing science with and for society that also broadens participation in research related to the atmospheric sciences.

5. Inter‐Model Comparison of Delft3D‐FM and 2D HEC‐RAS for Total Water Level Prediction in Coastal to Inland Transition Zones

   David F. Muñoz, Dongxiao Yin, Roham Bakhtyar, Hamed Moftakhari, Zuo Xue, and 2 more authors

   JAWRA Journal of the American Water Resources Association, 2022

   Abs DOI

   Hydrodynamic models play a key role in simulating total water level (TWL), that is, a combination of river flow, tide, surge, wind and wave‐induced water level, and representing flood inundation dynamics in coastal areas. An appropriate selection of two‐dimensional (2D) models that integrate riverine and estuarine interactions with ocean dynamics is crucial to generate accurate TWL predictions and assist stakeholders and federal agencies in decision making and flood emergency responses. In this study, we compare the performance of two widely used hydrodynamic models (e.g., 2D HEC‐RAS and Delft3D‐Flexible Mesh [FM]) with respect to their ability of predicting TWL in Delaware Bay, United States. Based on a previously established model configuration, we simulate Hurricane Sandy and Isabel that affected the Bay and led to considerable damages and economic losses. We then evaluate model capabilities with tidal analysis, compare observed vs. simulated TWL and analyze spatiotemporal variations of TWL through scenario‐based simulations. Our results suggest that atmospheric forcing input in Delft3D‐FM significantly improves TWL predictions as compared to those of 2D HEC‐RAS. Furthermore, model simulations with Delft3D‐FM can be faster than 2D HEC‐RAS by a factor of 6–10. Despite these advantages, 2D HEC‐RAS (version 5.07) is a noncommercial software easier to implement and can be a simpler alternative for modeling extreme events when atmospheric forcing is not relevant in the model domain.

6. Moving from interdisciplinary to convergent research across geoscience and social sciences: challenges and strategies

   Donovan Finn, Kyle Mandli, Anamaria Bukvic, Christopher A Davis, Rebecca Haacker, and 6 more authors

   Environmental Research Letters, 2022

   DOI

   

2021

1. Numerical Considerations for Quantifying Air–Water Turbulence with Moment Field Equations

   Colton J. Conroy, Kyle T. Mandli, and Ethan J. Kubatko

   Water Waves, 2021

   Abs DOI

   We investigate energy transfer of air–water interactions and develop a numerical method that captures its temporal variability and generates and tracks the short waves that form in the water surface as a result of the air–water turbulence. We solve a novel system of balance equations derived from the Navier–Stokes equations known as moment field equations. The main advantage of our approach is that we do not assume a priori that the stochastic random variables that quantify the turbulent energy transfer between air and water are Gaussian. We generate non-conservative multifractal measures of turbulent energy transfer using a recursive integration process and a self-affine velocity kernel. The kernel exactly satisfies the (duration limited) kinetic equation for waves as well as invariant scaling properties of the Navier–Stokes equations. This allows us to derive source terms for the moment field equations using a turbulent diffusion operator. The operator quantifies energy transfer along a space time path associated with pressure instabilities in the air–sea interface and transfers the statistical shape (or fractal dimension) of the atmosphere to the wind-sea. Because we use observational data to begin the recursive integration process, the ocean–atmosphere interaction is inherently built into the model. Numerical results from application of our methods to air–sea turbulence off the coast of New Jersey and New York indicate that our methods produce measures of turbulent energy transfer that match theory and observation, and, correspondingly, significant wave heights and average wave periods predicted by our model qualitatively match buoy data.

2. An \h\-Box Method for Shallow Water Equations Including Barriers

   Jiao Li and Kyle T Mandli

   SIAM Journal on Scientific Computing, 2021

   DOI
3. Optimization of Coastal Protections in the Presence of Climate Change

   Yuki Miura, Philip C. Dinenis, Kyle T. Mandli, George Deodatis, and Daniel Bienstock

   Frontiers in Climate, 2021

   Abs DOI

   It is generally acknowledged that interdependent critical infrastructure in coastal urban areas is constantly threatened by storm-induced flooding. Due to changing climate effects, such as sea level rise (SLR), the occurrence of catastrophic events will be more frequent and may trigger an increased likelihood of severe hazards. Planning a protective measure or mitigation strategy is a complex problem given the constraints that it must fit within a prescribed and limited fiscal budget and be beneficial to the community it protects both socially and economically. This article proposes a methodology for optimizing protective measures and mitigation strategies for interdependent infrastructures subjected to storm-induced flooding and climate change impacts such as SLR. Optimality is defined in this methodology as a maximum reduction in overall expected losses within a prescribed budget (compared to the expected losses in the case of doing nothing for protection/mitigation). Protective measures can include seawalls, barriers, artificial dunes, restoration of wetlands, raising individual buildings, sealing parts of the infrastructure, strategic retreat, insurance, and many more. The optimal protective strategy can be a combination of several protective measures implemented over space and time. The optimization process starts with parameterizing the protective measures. Storm-induced flooding and SLR, and their corresponding consequences, are estimated using a GIS-based subdivision-redistribution methodology (GISSR) developed by the authors for finding a rough solution in the first brute-force iterations of the optimization loop. A storm surge computational model called GeoClaw is subsequently used to simulate ensembles of synthetic storms in order to fine-tune and achieve the optimal solution. Damage loss, including economic impacts, is quantified based on calculated flood estimates. The suitability of the potential optimal solution is examined and assessed with input from stakeholders’ interviews. It should be mentioned that the results and conclusions provided in this work depend on the assumptions made about future sea level rise (SLR). The authors acknowledge that there are other, more severe predictions for sea level rise (SLR), than the one used in this paper.

4. A methodological framework for determining an optimal coastal protection strategy against storm surges and sea level rise

   Yuki Miura, Huda Qureshi, Chanyang Ryoo, Philip C. Dinenis, Jiao Li, and 5 more authors

   Natural Hazards, 2021

   Abs DOI

   

   Interdependent critical infrastructures in coastal regions, including transportation, electrical grid, and emergency services, are continually threatened by storm-induced flooding. This has been demonstrated a number of times, most recently by hurricanes such as Harvey and Maria, as well as Sandy and Katrina. The need to protect these infrastructures with robust protection mechanisms is critical for our continued existence along the world’s coastlines. Planning these protections is non-trivial given the rare-event nature of strong storms and climate change manifested through sea level rise. This article proposes a framework for a methodology that combines multiple computational models, stakeholder interviews, and optimization to find an optimal protective strategy over time for critical coastal infrastructure while being constrained by budgetary considerations.

5. Quantifying air–water turbulence with moment field equations

   Colton J. Conroy, Kyle T. Mandli, and Ethan J. Kubatko

   Journal of Fluid Mechanics, 2021

   Abs DOI

   Energy transfer in turbulent fluids is non-Gaussian. We quantify non-Gaussian energy transfer between the atmosphere and bodies of water using a turbulent diffusion operator coupled with temporally self-affine velocity distributions and a recursive integration method that produce multifractal measures. The measures serve as input to a system of moment field equations (derived from Navier–Stokes) that generate and track high-frequency gravity waves that propagate through the water surface (as a result of the air–water interactions). The dimension of the support of the air–water turbulence produced by our methods falls within the range of theory and observation, and correspondingly, hindcast statistical measures of the water-wave surface such as significant water-wave height and wave period are well correlated to observational buoy data. Further, our recursive integration method can be used by spectral resolving phase-averaged models to interpolate temporal wind data to smaller scales to capture the non-Gaussian behaviour of the air–water interaction.

6. A new tropical cyclone surge index incorporating the effects of coastal geometry, bathymetry and storm information

   Md. Rezuanul Islam, Chia-Ying Lee, Kyle T. Mandli, and Hiroshi Takagi

   Scientific Reports, 2021

   Abs DOI

   This study presents a new storm surge hazard potential index (SSHPI) for estimating tropical cyclone (TC) induced peak surge levels at a coast. The SSHPI incorporates parameters that are often readily available at real-time: intensity in 10-min maximum wind speed, radius of 50-kt wind, translation speed, coastal geometry, and bathymetry information. The inclusion of translation speed and coastal geometry information lead to improvements of the SSHPI to other existing surge indices. A retrospective analysis of SSHPI using data from 1978–2019 in Japan suggests that this index captures historical events reasonably well. In particular, it explains \textbackslashtextasciitilde 66% of the observed variance and \textbackslashtextasciitilde 74% for those induced by TCs whose landfall intensity was larger than 79-kt. The performance of SSHPI is not sensitive to the type of coastal geometry (open coasts or semi-enclosed bays). Such a prediction methodology can decrease numerical computation requirements, improve public awareness of surge hazards, and may also be useful for communicating surge risk.

7. Continental Scale Heterogeneous Channel Flow Routing Strategy for Operational Forecasting Models

   Ehab Meselhe, Maryam A. Lamjiri, Kelly Flint, Sean Matus, Eric D. White, and 1 more author

   JAWRA Journal of the American Water Resources Association, 2021

   Abs DOI

   The benefits of operational forecasting models to the general public are numerous. They support water management decisions, provide the opportunity to mitigate the impacts of weather‐ and flood‐related disasters and potentially save lives and properties. Channel flow routing is a key component of these models and affects their ability to forecast flood depth, duration, and extent. Continental scale channel flow routing within the operational forecasting environments encounters a broad spectrum of hydraulic characteristics. Deploying computationally demanding approaches, such as the dynamic wave, should be limited in time and space to conditions where the inertia terms are significant (typically in low‐gradient environments and whenever backwater effects are prominent); otherwise, efficient and robust methods, e.g., Kinematic, Muskingum‐Cunge or diffusive waves should be the default. The heterogeneous routing approach presented here provides a framework to evaluate the balance between friction, inertia, and pressure and strategically triggers the appropriate wave approximation. The strategy recommended here is to activate the appropriate wave approximation based on the ambient hydraulic conditions, and smoothly transitions among these approximations. This strategy, if successfully implemented, would strike a balance among the performance metrics of operational forecasting models, namely, computational efficiency, accuracy, and minimization of computational instabilities. Research Impact Statement: A heterogeneous routing strategy, driven by the surrounding hydraulic conditions, activates terms in the momentum equation as needed to strike a balance between computational speed and accuracy.

8. High-Speed GIS-Based Simulation of Storm Surge–Induced Flooding Accounting for Sea Level Rise

   Yuki Miura, Kyle T Mandli, and George Deodatis

   Natural Hazards Review, 2021

   DOI

2020

1. Modeling and Simulation of Tsunami Impact: A Short Review of Recent Advances and Future Challenges

   Simone Marras and Kyle T. Mandli

   Geosciences, 2020

   Abs DOI

   Tsunami modeling and simulation has changed in the past few years more than it has in decades, especially with respect to coastal inundation. Among other things, this change is supported by the approaching era of exa-scale computing, whether via GPU or more likely forms of hybrid computing whose presence is growing across the geosciences. For reasons identified in this review, exa-scale computing efforts will impact the on-shore, highly turbulent régime to a higher degree than the 2D shallow water equations used to model tsunami propagation in the open ocean. This short review describes the different approaches to tsunami modeling from generation to impact and underlines the limits of each model based on the flow régime. Moreover, from the perspective of a future comprehensive multi-scale modeling infrastructure to simulate a full tsunami, we underline the current challenges associated with this approach and review the few efforts that are currently underway to achieve this goal. A table of existing tsunami software packages is provided along with an open Github repository to allow developers and model users to update the table with additional models as they are published and help with model discoverability.

2019

1. Tropical cyclone hazard to Mumbai in the recent historical climate

   Adam H. Sobel, Chia-Ying Lee, Suzana J. Camargo, Kyle T. Mandli, Kerry A. Emanuel, and 2 more authors

   Monthly Weather Review, 2019

   Abs DOI

   The hazard to the city of Mumbai, India from a possible severe tropical cyclone under the recent historical climate is considered. The authors first determine, based on a review of primary sources, that the Bombay cyclone of 1882, documented in a number of print and internet sources and claimed to have caused 100,000 or more deaths, did not occur. Two different tropical cyclone hazard models, both of which generate large numbers of synthetic cyclones using environmental data - here taken from reanalyses in the satellite era - as input, are then used to quantify the hazard, in conjunction with historical observations. Both models indicate that a severe cyclone landfall at or near Mumbai is possible, though unlikely in any given year. Return periods for wind speeds exceeding 100 kt (the threshold for category 3 in the Saffir-Simpson scale) at Mumbai itself are estimated to be in the range of thousands to greater than ten thousand years, while the return period for a storm with maximum wind speed of 100 kt or greater passing within 150 km of Mumbai (possibly close enough to generate a substantial storm surge at the city) is estimated to be around 500 years. Return periods for winds exceeding 65 kt (hurricane intensity on the Saffir-Simpson scale) are estimated to be around 200 years at Mumbai itself, 50–90 years within 150 km. Climate change is not explicitly considered in this study, but the hazard to the city is likely to be increasing due to sea level rise as well as changes in storm climatology.

2. Teaching and Learning with Jupyter

   Lorena A. Barba, Lecia J. Barker, Douglas S. Blank, Jed Brown, Allen B. Downey, and 11 more authors

   Dec 2019

2018

1. Evolution and Controls of Large Glacial Lakes in the Nepal Himalaya

   Umesh K. Haritashya, Jeffrey S. Kargel, Dan H. Shugar, Gregory J. Leonard, Katherine Strattman, and 5 more authors

   Remote Sensing, Dec 2018

   Abs DOI

   Glacier recession driven by climate change produces glacial lakes, some of which are hazardous. Our study assesses the evolution of three of the most hazardous moraine-dammed proglacial lakes in the Nepal Himalaya—Imja, Lower Barun, and Thulagi. Imja Lake (up to 150 m deep; 78.4 × 106 m3 volume; surveyed in October 2014) and Lower Barun Lake (205 m maximum observed depth; 112.3 × 106 m3 volume; surveyed in October 2015) are much deeper than previously measured, and their readily drainable volumes are slowly growing. Their surface areas have been increasing at an accelerating pace from a few small supraglacial lakes in the 1950s/1960s to 1.33 km2 and 1.79 km2 in 2017, respectively. In contrast, the surface area (0.89 km2) and volume of Thulagi lake (76 m maximum observed depth; 36.1 × 106 m3; surveyed in October 2017) has remained almost stable for about two decades. Analyses of changes in the moraine dams of the three lakes using digital elevation models (DEMs) quantifies the degradation of the dams due to the melting of their ice cores and hence their natural lowering rates as well as the potential for glacial lake outburst floods (GLOFs). We examined the likely future evolution of lake growth and hazard processes associated with lake instability, which suggests faster growth and increased hazard potential at Lower Barun lake.

2. Displacement Interpolation Using Monotone Rearrangement

   Donsub Rim and Kyle T. Mandli

   SIAM/ASA Journal on Uncertainty Quantification, Nov 2018

   Abs DOI

   When approximating a function that depends on a parameter, one encounters many practical examples where linear interpolation or linear approximation with respect to the parameters proves ineffective. This is particularly true for responses from hyperbolic partial differential equations (PDEs) where linear, low-dimensional bases are difficult to construct. We propose the use of displacement interpolation, where the interpolation is done on the optimal transport map between the functions at nearby parameters, to achieve an effective dimensionality reduction of hyperbolic phenomena. We further propose a multidimensional extension by using the intertwining property of the Radon transform. This extension is a generalization of the classical translational representation of Lax and Phillips [P. D. Lax and R. S. Phillips, Bull. Amer. Math. Soc., 70 (1964), pp. 130–142].

3. Dynamically adaptive data-driven simulation of extreme hydrological flows

   Pushkar Kumar Jain, Kyle Mandli, Ibrahim Hoteit, Omar Knio, and Clint Dawson

   Ocean Modelling, Jan 2018

   Abs DOI

   Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

4. Vectorization of Riemann solvers for the single- and multi-layer shallow water equations

   Chaulio R Ferreira, Kyle T Mandli, and Michael Bader

   In , Jan 2018

   Abs DOI

   We discuss vectorization of normal and transverse Riemann solvers for the single- and multi-layer shallow water equations. Our approach is simple and portable, as it is based on auto-vectorization by the compiler, aided by OpenMP 4.0 directives. Despite the high complexity of the solver routines, the Intel Fortran Compiler proved itself able to successfully vectorize loops containing calls to these solvers, after only a few small changes in their code. We evaluate the performance of the vectorized Riemann solvers within the context of GeoClaw, a software designed for simulation of geophysical flows with finite volume methods. Our performance studies consider two platforms with different sets of SIMD instructions: a dual-socket Haswell system with the AVX2 instruction set (256-bit) and an Intel Xeon Phi (Knights Landing) with AVX-512 instructions (512-bit). The experimental results indicate performance im- provements of up to 2.1x on the former platform and up to 6.5x on the latter (with double-precision arithmetic). We also show that these speedups can easily compensate for the overhead introduced by the rearrangement of the simulation data structures, which might be necessary to achieve efficient vectorization.

5. hp discontinuous Galerkin methods for parametric, wind-driven water wave models

   Colton J. Conroy, Ethan J. Kubatko, Angela Nappi, Rachel Sebian, Dustin West, and 1 more author

   Advances in Water Resources, Sep 2018

   Abs DOI

   We recast the parametric, wind-driven water wave modeling paradigm into a weak form that is advantageous to discontinuous Galerkin (DG) methods and demonstrate some advantages of polynomial refinement versus standard mesh refinement. Hindcast studies performed over Lake Erie indicate that this simplified parametric approach, when paired with advanced numerics, produces similar error measures to the well-established spectral wave model known as SWAN while executing significantly faster in terms of CPU time.

6. Surrogate-based parameter inference in debris flow model

   Maria Navarro, Olivier P. Le Maître, Ibrahim Hoteit, David L. George, Kyle T. Mandli, and 1 more author

   Computational Geosciences, Aug 2018

   Abs DOI

   This work tackles the problem of calibrating the unknown parameters of a debris flow model with the drawback that the information regarding the experimental data treatment and processing is not available. In particular, we focus on the evolution over time of the flow thickness of the debris with dam-break initial conditions. The proposed methodology consists of establishing an approximation of the numerical model using a polynomial chaos expansion that is used in place of the original model, saving computational burden. The values of the parameters are then inferred through a Bayesian approach with a particular focus on inference discrepancies that some of the important features predicted by the model exhibit. We build the model approximation using a preconditioned non-intrusive method and show that a suitable prior parameter distribution is critical to the construction of an accurate surrogate model. The results of the Bayesian inference suggest that utilizing directly the available experimental data could lead to incorrect conclusions, including the over-determination of parameters. To avoid such drawbacks, we propose to base the inference on few significant features extracted from the original data. Our experiments confirm the validity of this approach, and show that it does not lead to significant loss of information. It is further computationally more efficient than the direct approach, and can avoid the construction of an elaborate error model.

2017

1. Hybrid analog-digital solution of nonlinear partial differential equations

   Yipeng Huang, Ning Guo, Mingoo Seok, Yannis Tsividis, Kyle Mandli, and 1 more author

   In , Oct 2017

   Abs DOI

   … ACM ISBN 978-1-4503-4952-9/17/10... 15.00 https://doi.org/ 10.1145 / 3123939.3124550 ACM Reference format: Yipeng Huang, Ning Guo, Mingoo Seok, Yannis Tsividis, Kyle Mandli, and Simha Sethumadhavan. 2017 … https://doi.org/ 10.1145 / 3123939.3124550  …

2. Quantifying uncertainties in fault slip distribution during the Tōhoku tsunami using polynomial chaos

   Ihab Sraj, Kyle T. Mandli, Omar M. Knio, Clint N. Dawson, and Ibrahim Hoteit

   Ocean Dynamics, Oct 2017

   Abs DOI

   An efficient method for inferring Manning’s n coefficients using water surface elevation data was presented in Sraj et al. (Ocean Modell 83:82–97 2014a) focusing on a test case based on data collected during the Tōhoku earthquake and tsunami. Polynomial chaos (PC) expansions were used to build an inexpensive surrogate for the numerical model GeoClaw, which were then used to perform a sensitivity analysis in addition to the inversion. In this paper, a new analysis is performed with the goal of inferring the fault slip distribution of the Tōhoku earthquake using a similar problem setup. The same approach to constructing the PC surrogate did not lead to a converging expansion; however, an alternative approach based on basis pursuit denoising was found to be suitable. Our result shows that the fault slip distribution can be inferred using water surface elevation data whereas the inferred values minimize the error between observations and the numerical model. The numerical approach and the resulting inversion are presented in this work.

3. Bayesian inference of earthquake parameters from buoy data using a polynomial chaos-based surrogate

   Loïc Giraldi, Olivier P. Le Maître, Kyle T. Mandli, Clint N. Dawson, Ibrahim Hoteit, and 1 more author

   Computational Geosciences, Apr 2017

   Abs DOI

   This work addresses the estimation of the parameters of an earthquake model by the consequent tsunami, with an application to the Chile 2010 event. We are particularly interested in the Bayesian inference of the location, the orientation, and the slip of an Okada-based model of the earthquake ocean floor displacement. The tsunami numerical model is based on the GeoClaw software while the observational data is provided by a single DARTⓇ buoy. We propose in this paper a methodology based on polynomial chaos expansion to construct a surrogate model of the wave height at the buoy location. A correlated noise model is first proposed in order to represent the discrepancy between the computational model and the data. This step is necessary, as a classical independent Gaussian noise is shown to be unsuitable for modeling the error, and to prevent convergence of the Markov Chain Monte Carlo sampler. Second, the polynomial chaos model is subsequently improved to handle the variability of the arrival time of the wave, using a preconditioned non-intrusive spectral method. Finally, the construction of a reduced model dedicated to Bayesian inference is proposed. Numerical results are presented and discussed.

2016

1. Clawpack: building an open source ecosystem for solving hyperbolic PDEs

   Kyle T Mandli, Aron J Ahmadia, Marsha Berger, Donna Calhoun, David L George, and 4 more authors

   PeerJ Computer Science, Aug 2016

   Abs DOI

   

   Clawpack is a software package designed to solve nonlinear hyperbolic partial differential equations using high-resolution finite volume methods based on Riemann solvers and limiters. The package includes a number of variants aimed at different applications and user communities. Clawpack has been actively developed as an open source project for over 20 years. The latest major release, Clawpack 5, introduces a number of new features and changes to the code base and a new development model based on GitHub and Git submodules. This article provides a summary of the most significant changes, the rationale behind some of these changes, and a description of our current development model.

2015

1. Visualizing uncertainties in a storm surge ensemble data assimilation and forecasting system

   Thomas Höllt, M. Umer Altaf, Kyle T. Mandli, Markus Hadwiger, Clint N. Dawson, and 1 more author

   Natural Hazards, Jan 2015

   Abs DOI

   We present a novel integrated visualization system that enables the interactive visual analysis of ensemble simulations and estimates of the sea surface height and other model variables that are used for storm surge prediction. Coastal inundation, caused by hurricanes and tropical storms, poses large risks for today’s societies. High-fidelity numerical models of water levels driven by hurricane-force winds are required to predict these events, posing a challenging computational problem, and even though computational models continue to improve, uncertainties in storm surge forecasts are inevitable. Today, this uncertainty is often exposed to the user by running the simulation many times with different parameters or inputs following a Monte-Carlo framework in which uncertainties are represented as stochastic quantities. This results in multidimensional, multivariate and multivalued data, so-called ensemble data. While the resulting datasets are very comprehensive, they are also huge in size and thus hard to visualize and interpret. In this paper, we tackle this problem by means of an interactive and integrated visual analysis system. By harnessing the power of modern graphics processing units for visualization as well as computation, our system allows the user to browse through the simulation ensembles in real time, view specific parameter settings or simulation models and move between different spatial and temporal regions without delay. In addition, our system provides advanced visualizations to highlight the uncertainty or show the complete distribution of the simulations at user-defined positions over the complete time series of the prediction. We highlight the benefits of our system by presenting its application in a real-world scenario using a simulation of Hurricane Ike.

2014

1. Adaptive mesh refinement for storm surge

   Kyle T. Mandli and Clint N. Dawson

   Ocean Modelling, Jan 2014

   Abs DOI

   

   An approach to utilizing adaptive mesh refinement algorithms for storm surge modeling is proposed. Currently numerical models exist that can resolve the details of coastal regions but are often too costly to be run in an ensemble forecasting framework without significant computing resources. The application of adaptive mesh refinement algorithms substantially lowers the computational cost of a storm surge model run while retaining much of the desired coastal resolution. The approach presented is implemented in the GeoClaw framework and compared to ADCIRC for Hurricane Ike along with observed tide gauge data and the computational cost of each model run.

2. Uncertainty quantification and inference of Manning’s friction coefficients using DART buoy data during the Tōhoku tsunami

   Ihab Sraj, Kyle T. Mandli, Omar M. Knio, Clint N. Dawson, and Ibrahim Hoteit

   Ocean Modelling, Jan 2014

   Abs DOI

   Tsunami computational models are employed to explore multiple flooding scenarios and to predict water elevations. However, accurate estimation of water elevations requires accurate estimation of many model parameters including the Manning’s n friction parameterization. Our objective is to develop an efficient approach for the uncertainty quantification and inference of the Manning’s n coefficient which we characterize here by three different parameters set to be constant in the on-shore, near-shore and deep-water regions as defined using iso-baths. We use Polynomial Chaos (PC) to build an inexpensive surrogate for the GeoClaw model and employ Bayesian inference to estimate and quantify uncertainties related to relevant parameters using the DART buoy data collected during the Tōhoku tsunami. The surrogate model significantly reduces the computational burden of the Markov Chain Monte-Carlo (MCMC) sampling of the Bayesian inference. The PC surrogate is also used to perform a sensitivity analysis.

2013

1. ForestClaw: Hybrid forest-of-octrees AMR for hyperbolic conservation laws

   Carsten Burstedde, Donna A Calhoun, Kyle Mandli, and Andy R Terrel

   In , Jan 2013

   Abs DOI

   We present a new hybrid paradigm for parallel adaptive mesh refinement (AMR) that combines the scalability and lightweight architecture of tree-based AMR with the computational efficiency of patch-based solvers for hyperbolic conservation laws. The key idea is to interpret each leaf of the AMR hierarchy as one uniform compute patch in Rd with md degrees of freedom, where m is customarily between 8 and 32. Thus, computation on each patch can be optimized for speed, while we inherit the flexibility of adaptive meshes. In our work we choose to integrate with the p4est AMR library since it allows us to compose the mesh from multiple mapped octrees and enables the cubed sphere and other nontrivial multiblock geometries. We describe aspects of the parallel implementation and close with scalings for both MPI-only and OpenMP/MPI hybrid runs, where the largest MPI run executes on 16,384 CPU cores.

2. A numerical method for the two layer shallow water equations with dry states

   Kyle T. Mandli

   Ocean Modelling, Jan 2013

   Abs DOI

   A numerical method is proposed for solving the two layer shallow water equations with variable bathymetry in one dimension based on high-resolution f-wave-propagation finite volume methods. The method splits the jump in the fluxes and source terms into waves propagating away from each grid cell interface. It addresses the required determination of the system’s eigenstructure and a scheme for evaluating the flux and source terms. It also handles dry states in the system where the bottom layer depth becomes zero, utilizing existing methods for the single layer solution and handling single layer dry states that can exist independently. Sample results are shown illustrating the method and its handling of dry states including an idealized ocean setting.

2012

1. ManyClaw: Slicing and dicing Riemann solvers for next generation highly parallel architectures

   Andy R Terrel and Kyle T Mandli

   In , Feb 2012

   Abs

   Next generation computer architectures will include order of magnitude more intra-node parallelism; however, many application programmers have a difficult time keeping their codes current with the state- of-the-art machines. In this context, we analyze Hyperbolic PDE solvers, which are used in the solution of many important applications in science and engineering. We present ManyClaw , a project intended to explore the exploitation of intra-node parallelism in hyperbolic PDE solvers via the Clawpack software package for solving hyperbolic PDEs. Our goal is to separate the low level parallelism and the physical equations thus providing users the capability to leverage intra-node parallelism without explicitly writing code to take advantage of newer architectures.

2. PyClaw: Accessible, Extensible, Scalable Tools for Wave Propagation Problems

   David I. Ketcheson, Kyle Mandli, Aron J. Ahmadia, Amal Alghamdi, Manuel Quezada de Luna, and 3 more authors

   SIAM Journal on Scientific Computing, Nov 2012

   Abs DOI

   

   Development of scientific software involves tradeoffs between ease of use, generality, and performance. We describe the design of a general hyperbolic PDE solver that can be operated with the convenience of MATLAB yet achieves efficiency near that of hand-coded Fortran and scales to the largest supercomputers. This is achieved by using Python for most of the code while employing automatically wrapped Fortran kernels for computationally intensive routines, and using Python bindings to interface with a parallel computing library and other numerical packages. The software described here is PyClaw, a Python-based structured grid solver for general systems of hyperbolic PDEs [K. T. Mandli et al., PyClaw Software, Version 1.0, http://numerics.kaust.edu.sa/pyclaw/ (2011)]. PyClaw provides a powerful and intuitive interface to the algorithms of the existing Fortran codes Clawpack and SharpClaw, simplifying code development and use while providing massive parallelism and scalable solvers via the PETSc library. The package is further augmented by use of PyWENO for generation of efficient high-order weighted essentially nonoscillatory reconstruction code. The simplicity, capability, and performance of this approach are demonstrated through application to example problems in shallow water flow, compressible flow, and elasticity.

2011

1. Finite Volume Methods for the Multilayer Shallow Water Equations with Applications to Storm Surges

   Kyle T Mandli

   Nov 2011

   Abs

   Coastal hazards related to strong storms such as hurricanes and typhoons are one of the most frequently recurring and wide spread hazards to coastal communities. Storm surges are among the most devastating effects of these storms, and their prediction and mitigation is of great interest to coastal communities that need to plan for the subsequent rise in sea level during these storms. Past efforts to model storm surge have usually focused on the single-layer shallow water equations, due to the ease of com- puting a simulation on the relevant scales and domains relative to three-dimensional modeling. The drawback to this approach is that the primary generating mechanism for storm surge is the wind-momentum transfer to the ocean. This boundary layer phenomenon is not well-represented by the shallow water equations, especially in the deep ocean. An alternative is to use the two-layer shallow water equations, with a shallow upper layer driven by the wind and an abyssal layer representing the rest of the water column. The focus of this thesis is on the development of a finite volume method for the multi-layer shallow water equations that is appropriate for application to storm surges. This has been done in the context of the GeoClaw framework, a code designed to handle the single-layer shallow water equations with adaptive mesh refinement al- gorithms, and uses many of the capabilities available to GeoClaw that are pertinent to storm surges. Approximations to the system are also discussed and tested along with methods for handling dry-states and inundation. Finally, idealized storm surge test cases comparing the single-layer and two-layer shallow water equations are explored.

2. The GeoClaw software for depth-averaged flows with adaptive refinement

   Marsha J. Berger, David L. George, Randall J. LeVeque, and Kyle T. Mandli

   Advances in Water Resources, Nov 2011

   Abs DOI

   

   Many geophysical flow or wave propagation problems can be modeled with two-dimensional depth-averaged equations, of which the shallow water equations are the simplest example. We describe the GeoClaw software that has been designed to solve problems of this nature, consisting of open source Fortran programs together with Python tools for the user interface and flow visualization. This software uses high-resolution shock-capturing finite volume methods on logically rectangular grids, including latitude–longitude grids on the sphere. Dry states are handled automatically to model inundation. The code incorporates adaptive mesh refinement to allow the efficient solution of large-scale geophysical problems. Examples are given illustrating its use for modeling tsunamis and dam-break flooding problems. Documentation and download information is available at www.clawpack.org/geoclaw.