Showing papers by "Naval Postgraduate School published in 2022"

Improved BEC SMOS Arctic Sea Surface Salinity product v3.1

Abstract: Abstract. Measuring salinity from space is challenging since the sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) is low (about 0.5 K psu−1), while the SSS range in the open ocean is narrow (about 5 psu, if river discharge areas are not considered). This translates into a high accuracy requirement of the radiometer (about 2–3 K). Moreover, the sensitivity of the TB to SSS at cold waters is even lower (0.3 K psu−1), making the retrieval of the SSS in the cold waters even more challenging. Due to this limitation, the ESA launched a specific initiative in 2019, the Arctic+Salinity project (AO/1-9158/18/I-BG), to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product (Martínez et al., 2019) . The product consists of 9 d averaged maps in an EASE 2.0 grid of 25 km. The product is freely distributed from the Barcelona Expert Center (BEC, http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019). The major change in this new product is its improvement of the effective spatial resolution that permits better monitoring of the mesoscale structures (larger than 50 km), which benefits the river discharge monitoring.

Topographic Stabilization of Ocean Rings

Abstract: Coherent large-scale vortices in the open ocean can retain their structure and properties for periods as long as several years. However, the patterns of potential vorticity in such vortices suggest that they are baroclinically unstable and therefore should rapidly disintegrate. This study proposes a plausible explanation of the longevity of large-scale ocean rings based on bottom roughness, which restricts flow in the lower layer and thereby stabilizes the eddy. We perform a series of simulations in which topography is represented by the observationally derived Goff-Jordan spectrum. We demonstrate that topography stabilizes coherent vortices and dramatically prolongs their lifespan. In contrast, the same vortices in the flat-bottom model exhibit strong instability and fragmentation on the timescale of weeks. A critical depth variance exists that allows vortices to remain stable and circularly symmetric indefinitely. Our investigation underscores the essential role played by topography in the dynamics of large- and meso-scale flows.

Surprise is inevitable: How do we train and prepare to make our critical infrastructure more resilient?

Abstract: While current practices for infrastructure currently follow principles of reliability and risk, these are—by necessity—based on knowledge of past events. They are not suited to adapt infrastructure to dramatic change and/or future surprises. In this paper, we propose a research agenda for the development of novel training exercises that complement current approaches by drawing upon a theory of resilience that emphasizes adaptive response to surprise. We argue that experience with surprise in ‘realistic, yet fictitious’ infrastructure systems simulations can improve the capacity of infrastructure managers to sense, anticipate, adapt to, and learn from surprise in virtual crises gaming scenarios when trainees successfully integrate their experiences from simpler to more complex stages of expertise. Virtual platforms that are shareable and extensible to classroom and operational settings might speed this process of integration of experience, and improve success rates among infrastructure managers confronted with surprise.

Large-eddy simulations with ClimateMachine v0.2.0: a new open-source code for atmospheric simulations on GPUs and CPUs

Abstract: Abstract. We introduce ClimateMachine, a new open-source atmosphere modeling framework which uses the Julia language and is designed to be scalable on central processing units (CPUs) and graphics processing units (GPUs). ClimateMachine uses a common framework both for coarser-resolution global simulations and for high-resolution, limited-area large-eddy simulations (LESs). Here, we demonstrate the LES configuration of the atmosphere model in canonical benchmark cases and atmospheric flows using a total energy-conserving nodal discontinuous Galerkin (DG) discretization of the governing equations. Resolution dependence, conservation characteristics, and scaling metrics are examined in comparison with existing LES codes. They demonstrate the utility of ClimateMachine as a modeling tool for limited-area LES flow configurations.

A Class of Bounded and Partially Bounded Nonlinear Controllers for First and Second Order Dynamical Systems

Abstract: This letter proposes structurally simple, bounded and partially bounded nonlinear controllers that offer satisfactory performance, demonstrated by their application to first and second-order dynamical systems. This is done by taking advantage of the properties of a particular class of bounded sector nonlinear functions that can be parameterized in bound value and slope. In contrast to the classical methods of saturated control, the proposed controllers’ design can be defined as an explicit summation of sector nonlinear functions, whose Lyapunov global stability proof can be straightforwardly demonstrated for the single and double integrator dynamics. Thus, the proposed approach derives nonlinear controllers where each term is bounded (or partially bounded) by design. Although the stability proof is provided for single and double integrator dynamics, one of the controllers is tested in a first-order nonlinear system and another in a nonlinear second-order system, both to achieve tracking. The numerical results evidence good performance even for large initial errors, and without the further introduction of auxiliary dynamics, such as compensation terms or feedback linearization. This is done by only tuning the gains of each term, while maintaining boundedness (or partial boundedness) properties on the control input.

Algorithms for Artificial Intelligence

Abstract: Artificial intelligence and machine learning use a wide variety of algorithms. More than 60 years of research have shown that intelligent behavior requires a variety of methods. We discuss the major classes of algorithms and their uses.

On the High-Energy Consumption of Bitcoin Mining

Abstract: A well-known fact is that Bitcoin’s blockchain maintenance using proof-of-work mining consumes a lot of energy. This article explains how this energy expense is inherent to Bitcoin’s design whose purpose is to induce a truly distributed peer-to-peer currency ledger (the blockchain) that is nevertheless trustable.

Defense Installation Energy Resilience for Changing Operational Requirements

Abstract: We propose a methodology to determine the impact of different potential mission scenarios upon energy resilience for mission-critical loads attached to a military base’s microgrid infrastructure. The proposed methodology applies to any installation with changing operational states that has energy-resilience requirements. The proposed methodology may be used by energy managers to account for potential mission scenarios that a base may be part of, followed by assessing the microgrid energy resilience to supply the critical loads for said mission scenarios, especially where the external grid power may be unavailable and/or damage to microgrid components may be present. In the event a microgrid design is unable to provide sufficient electrical energy, distributed energy resources and energy storage systems including renewable energy resources may be added to improve energy resilience. A case study is conducted on a fictitious representative military base, microgrid design, and changing mission demands to demonstrate the application of the proposed methodology. This article contributes a methodology for energy managers to evaluate energy resilience using microgrids by accounting for potential mission scenarios, their energy requirements, resulting energy preparedness, and recommendations for improvement, as necessary.

A Lagrangian analysis of pockets of open cells over the southeastern Pacific

Abstract: Abstract. Pockets of open cells (POCs) have been shown to develop within closed-cell stratocumulus (StCu), and a large body of evidence suggests that the development of POCs result from changes in small-scale processes internal to the boundary layer rather than large-scale forcings. Precipitation is widely viewed as a key process important to POC development and maintenance. In this study, GOES-16 satellite observations are used in conjunction with MERRA-2 winds to track and compare the microphysical and environmental evolution of two populations of closed-cell StCu selected by visual inspection over the southeastern Pacific Ocean: one group that transitions to POCs and another comparison group (CLOSED) that does not. The high spatiotemporal resolution of the new GOES-16 data allows for a detailed examination of the temporal evolution of POCs in this region. We find that POCs tend to develop near the coast, last tens of hours, are larger than 104 km2, and often (88 % of cases) do not re-close before they exit the StCu deck. Most POCs are observed to form at night and tend to exit the StCu during the day when the StCu is contracting in area. Relative to the CLOSED trajectories, POCs have systematically larger effective radii, lower cloud drop number concentrations, a comparable conditional in-cloud liquid water path, and a higher frequency of more intense precipitation. Meanwhile, no systematic environmental differences other than boundary layer height are observed between POC and CLOSED trajectories. Interestingly, there are no differences in reanalysis aerosol optical depth between both sets of trajectories, which may lead one to the interpretation that differences in aerosol concentrations are not influencing POC development or resulting in a large number that re-close. However, this largely depends on the reanalysis treatment of aerosol–cloud interactions, and the product used in this study has no explicit handling of these important processes. These results support the consensus view regarding the importance of precipitation on the formation and maintenance of POCs and demonstrate the utility of modern geostationary remote sensing data in evaluating the POC life cycle.

Incidence‐data‐based species richness estimation via a Beta‐Binomial model

Abstract: Individual-based abundance data and sample-based incidence data are the two most widely used survey data formats to assess the species diversity in a target area, where the sample-based incidence data are more available and efficient for estimating species richness. For species individual with spatial aggregation, individual-unit-based random sampling scheme is difficult to implement, and quadrat-unit-based sampling scheme is more available to implement and more likely to fit the model assumption of random sampling. In addition, sample-based incidence data, without recording the number of individuals of a species and only recording the binary presence or absence of a species in the sampled unit, could considerably reduce the survey loading in the field. In this study, according to sample-based incidence data and based on a beta-binomial model assumption, instead of using the maximum likelihood method, I used the moment method to derive the richness estimator. The proposed richness estimation method provides a lower bound estimator of species richness for beta-binomial models, in which the new method only uses the number of singletons, doubletons and tripletons in the sample to estimate undetected richness. I evaluated the proposed estimator using simulated datasets generated from various species abundance models. For highly heterogeneous communities, the simulation results indicate that the proposed estimator could provide a more stable, less biased estimate and a more accurate 95% confidence interval of true richness compared to other traditional parametric-based estimators. I also applied the proposed approach to real datasets for assessment and comparison with traditional estimators. The newly proposed richness estimator provides different information and conclusions from other estimators.

Linear EnKF Update

Abstract: Abstract The Kalman filter or its ensemble version, the ensemble Kalman filter, is optimal for a linear model and -measurement operator. This chapter will comprehensively discuss the EnKF analysis scheme and its properties, focusing on an ensemble-subspace computation of the inverse.

Particle Flow for a Quasi-Geostrophic Model

Abstract: Abstract This chapter discusses the application of a particle-flow filter to a two-layer quasi-geostrophic model. The reasons for including this example are twofold. First, it shows that it is possible to apply fully nonlinear data assimilation to high-dimensional systems, even without localization.

Decision‐making challenges: Group dynamics and boundary spanning in the CyberStrike game

Abstract: Multirole online games offer advantages for learning in business schools, as students process information and coordinate with others while pursuing measurable goals. Gaming environments can be complex, and the choices and timing of players’ actions may have long-term effects on the state of the game. Team members practice communication skills as they exchange information and coordinate actions, and games provide objective feedback about their performance. Despite these advantages, integration of multiplayer online games into business courses can present technical and instructional challenges. This article introduces an online game, CyberStrike, in which student teams play roles of state or nonstate actors attempting to protect their own information systems while selectively attacking competitors’ information systems. The game can be useful in organizational behavior courses because it engages students in decision-making processes and inter-group dynamics that highlight relevant principles in action. As student teams try to foster cooperation within a competitive environment, consequences of their decision-making, strategy development, and boundary-spanning activities become apparent. Guidelines for teaching with CyberStrike are provided, along with suggestions for incorporating multirole online games into business school classes.

Arctic sea ice anomalies during the MOSAiC winter 2019/20

Abstract: Abstract. During the winter of 2019/2020, as the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project started its work, the Arctic Oscillation (AO) experienced some of its largest shifts, ranging from a highly negative index in November 2019 to an extremely positive index during January–February–March (JFM) 2020. The permanent positive AO phase for the 3 months of JFM 2020 was accompanied by a prevailing positive phase of the Arctic Dipole (AD) pattern. Here we analyze the sea ice thickness (SIT) distribution based on CryoSat-2/SMOS satellite-derived data augmented with results from the hindcast simulation by the fully coupled Regional Arctic System Model (RASM) from November 2019 through March 2020. A notable result of the positive AO phase during JFM 2020 was large SIT anomalies of up to 1.3 m that emerged in the Barents Sea (BS), along the northeastern Canadian coast and in parts of the central Arctic Ocean. These anomalies appear to be driven by nonlinear interactions between thermodynamic and dynamic processes. In particular, in the Barents and Kara seas (BKS), they are a result of enhanced ice growth connected with low-temperature anomalies and the consequence of intensified atmospherically driven sea ice transport and deformations (i.e., ice divergence and shear) in this area. The Davies Strait, the east coast of Greenland and the BS regions are characterized by convergence and divergence changes connected with thinner sea ice at the ice borders along with an enhanced impact of atmospheric wind forcing. Low-pressure anomalies that developed over the eastern Arctic during JFM 2020 increased northerly winds from the cold Arctic Ocean to the BS and accelerated the southward drift of the MOSAiC ice floe. The satellite-derived and simulated sea ice velocity anomalies, which compared well during JFM 2020, indicate a strong acceleration of the Transpolar Drift relative to the mean for the past decade, with intensified speeds of up to 6 km d−1. As a consequence, sea ice transport and deformations driven by atmospheric surface wind forcing accounted for the bulk of the SIT anomalies, especially in January 2020 and February 2020. RASM intra-annual ensemble forecast simulations with 30 ensemble members forced with different atmospheric boundary conditions from 1 November 2019 through 30 April 2020 show a pronounced internal variability in the sea ice volume, driven by thermodynamic ice-growth and ice-melt processes and the impact of dynamic surface winds on sea ice formation and deformation. A comparison of the respective SIT distributions and turbulent heat fluxes during the positive AO phase in JFM 2020 and the negative AO phase in JFM 2010 corroborates the conclusion that winter sea ice conditions in the Arctic Ocean can be significantly altered by AO variability.

Problem Formulation

Abstract: Abstract This chapter introduces the model-state- and parameter estimation problem from basic principles starting with Bayes’ theorem. We define the general problem formulation and introduce the concept of Bayes’ theorem solved recursively over a sequence of assimilation time windows.

Impact of initialization methods on the predictive skill in NorCPM: an Arctic–Atlantic case study

Abstract: Abstract The skilful prediction of climatic conditions on a forecast horizon of months to decades into the future remains a main scientific challenge of large societal benefit. Here we assess the hindcast skill of the Norwegian Climate Prediction Model (NorCPM) for sea surface temperature (SST) and sea surface salinity (SSS) in the Arctic–Atlantic region focusing on the impact of different initialization methods. We find the skill to be distinctly larger for the Subpolar North Atlantic than for the Norwegian Sea, and generally for all lead years analyzed. For the Subpolar North Atlantic, there is furthermore consistent benefit in increasing the amount of data assimilated, and also in updating the sea ice based on SST with strongly coupled data assimilation. The predictive skill is furthermore significant for at least two model versions up to 8–10 lead years with the exception for SSS at the longer lead years. For the Norwegian Sea, significant predictive skill is more rare; there is relatively higher skill with respect to SSS than for SST. A systematic benefit from more complex data assimilation approach can not be identified for this region. Somewhat surprisingly, skill deteriorates quite consistently for both the Subpolar North Atlantic and the Norwegian Sea when going from CMIP5 to corresponding CMIP6 versions. We find this to relate to change in the regional performance of the underlying physical model that dominates the benefit from initialization.

The Maxwell Effect and the Material Transport by Transient Eddies

Abstract: Mesoscale eddies—irregular time-dependent currents with lateral scales of 10–200 km—are ubiquitous in the World Ocean. They profoundly affect general circulation and actively redistribute oceanic heat, salt, biogeochemical tracers, and pollutants. The development of accurate parameterizations of eddy-induced transport remains one of the most pressing challenges in physical oceanography. Commonly used mesoscale parameterizations assume that the relation between eddy-induced fluxes and the large-scale property gradients is local and instantaneous. The present communication challenges this premise. We consider a closure that incorporates a delay in the adjustment of eddy fluxes to changing ambient distribution of properties. This model is inspired by the century-and-a-half-old idea of Maxwell, who argued that molecular dispersion necessarily involves a finite relaxation period. In our study, this principle is reinterpreted in the context of the turbulent transport problem. A series of simulations reveal marked improvements in eddy parameterizations brought by the inclusion of Maxwell's effect.

Systems abstractions

Abstract: Computing professionals use powerful abstractions to tame complexity in large software systems and distributed networks.

Assimilation of sea surface salinities from SMOS in an Arctic coupled ocean and sea ice reanalysis

Abstract: Abstract. In the Arctic, the sea surface salinity (SSS) plays a key role in processes related to water mixing and sea ice. However, the lack of salinity observations causes large uncertainties in Arctic Ocean forecasts and reanalysis. Recently the Soil Moisture and Ocean Salinity (SMOS) satellite mission was used by the Barcelona Expert Centre to propose an Arctic SSS product. In this study, we evaluate the impact of assimilating this data in a coupled ocean-ice data assimilation system. Using the Ensemble Kalman filter from July to December 2016, two assimilation runs assimilated two successive versions of the SMOS SSS product, on top of a pre-existing reanalysis run. The runs were validated against independent in situ salinity profiles in the Arctic. The results show that the biases and the Root Mean Squared Differences (RMSD) of SSS are reduced by 10 % to 50 % depending on areas and put the latest product to its advantage. The time series of Freshwater Content (FWC) further show that its seasonal cycle can be adjusted by assimilation of the SSS products, which is encouraging for its use in a long-time reanalysis to monitor the Arctic water cycle.

Introduction

Abstract: In the aftermath of the Second Gulf War, US intelligence managers and analysts were thinking long and hard about the 2002 Iraq National Intelligence Estimate (NIE), the one indicating that Baghdad was probably developing weapons of mass destruction. In November 2007, the moment of redemption had arrived. The National Intelligence Council issued an NIE, Iran’s Nuclear Intentions and Capabilities, a 150-page report containing 1500 footnotes on the scope and status of Iran’s clandestine effort to defy the international community and to ignore its Non-Proliferation Treaty obligations. As readers delve into the history and complex issues outlined by the symposium, they might keep in mind four observations drawn from the intelligence literature. The detection of clandestine programs to develop weapons of mass destruction is not just an historical artifact; it is an ongoing intelligence problem and national security issue of the highest importance.

Network Programming via Computable Products

Abstract: The User Plane Function (UPF) aims to provide network services in the 3GPP 5G core network. These services need to be implemented on demand inexpensively with provable properties. Existing network dataplane programming languages are not up to the task. A new software paradigm is presented for the UPF. It is inspired by model checking a concurrent reactive system where conceptually each component of the system is modeled as an extended finite-state machine and their product is verified. We show how such a product can be computed for one example of a UPF and how its state invariants can be inferred, thereby eliminating the need to formally verify the product separately. Code can be generated from the product and regenerated on the fly to remain optimal for the probability distribution of network traffic the UPF must process.