arXiv subjects

Michael Pritchard

Publications and source records attributed to Michael Pritchard.

22 records · Page 2Linked to original sources

arXiv2019

Comparing Convective Self-Aggregation in Idealized Models to Observed Moist Static Energy Variability near the Equator

Idealized convection-permitting simulations of radiative-convective equilibrium (RCE) have become a popular tool for understanding the physical processes leading to horizontal variability of tropical water vapor and rainfall. However, the applicability of idealized simulations to nature is still unclear given that important processes are typically neglected, such as lateral vapor advection by extratropical intrusions, or interactive ocean coupling. Here, we exploit spectral analysis to compactly summarize the multi-scale processes supporting convective aggregation. By applying this framework to high-resolution reanalysis data and satellite observations in addition to idealized simulations, we compare convective-aggregation processes across horizontal scales and data sets. The results affirm the validity of the RCE simulations as an analogy to the real world. Column moist static energy tendencies share similar signs and scale-selectivity in convection-permitting models and observations: Radiation increases variance at wavelengths above 1,000km, while advection damps variance across wavelengths, and surface fluxes mostly reduce variance between 1,000km and 10,000km.

physics.ao-ph↗

arXiv2019

Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling

Artificial neural-networks have the potential to emulate cloud processes with higher accuracy than the semi-empirical emulators currently used in climate models. However, neural-network models do not intrinsically conserve energy and mass, which is an obstacle to using them for long-term climate predictions. Here, we propose two methods to enforce linear conservation laws in neural-network emulators of physical models: Constraining (1) the loss function or (2) the architecture of the network itself. Applied to the emulation of explicitly-resolved cloud processes in a prototype multi-scale climate model, we show that architecture constraints can enforce conservation laws to satisfactory numerical precision, while all constraints help the neural-network better generalize to conditions outside of its training set, such as global warming.

physics.ao-ph↗

arXiv2018

Plan Interdiction Games

We propose a framework for cyber risk assessment and mitigation which models attackers as formal planners and defenders as interdicting such plans. We illustrate the value of plan interdiction problems by first modeling network cyber risk through the use of formal planning, and subsequently formalizing an important question of prioritizing vulnerabilities for patching in the plan interdiction framework. In particular, we show that selectively patching relatively few vulnerabilities allows a network administrator to significantly reduce exposure to cyber risk. More broadly, we have developed a number of scalable approaches for plan interdiction problems, making especially significant advances when attack plans involve uncertainty about system dynamics. However, important open problems remain, including how to effectively capture information asymmetry between the attacker and defender, how to best model dynamics in the attacker-defender interaction, and how to develop scalable algorithms for solving associated plan interdiction games.

cs.CR↗

arXiv2015

Development of a Burst Buffer System for Data-Intensive Applications

Modern parallel filesystems such as Lustre are designed to provide high, scalable I/O bandwidth in response to growing I/O requirements; however, the bursty I/O characteristics of many data-intensive scientific applications make it difficult for back-end parallel filesystems to efficiently handle I/O requests. A burst buffer system, through which data can be temporarily buffered via high-performance storage mediums, allows for gradual flushing of data to back-end filesystems. In this paper, we explore issues surrounding the development of a burst buffer system for data-intensive scientific applications. Our initial results demonstrate that utilizing a burst buffer system on top of the Lustre filesystem shows promise for dealing with the intense I/O traffic generated by application checkpointing.

cs.DC↗