A5050498512- Atmospheric and Environmental Gas Dynamics
- Climate variability and models
- Soil Geostatistics and Mapping
- Distributed and Parallel Computing Systems
- Meteorological Phenomena and Simulations
- Air Quality Monitoring and Forecasting
- Atmospheric chemistry and aerosols
- Scientific Computing and Data Management
- Advanced Data Compression Techniques
- Advanced Data Storage Technologies
- Algorithms and Data Compression
- Reservoir Engineering and Simulation Methods
- Remote Sensing in Agriculture
- Atmospheric Ozone and Climate
- Geochemistry and Geologic Mapping
- demographic modeling and climate adaptation
- Wind and Air Flow Studies
- Gaussian Processes and Bayesian Inference
- Statistical Methods and Inference
- CO2 Sequestration and Geologic Interactions
- Tropical and Extratropical Cyclones Research
- Spatial and Panel Data Analysis
- Remote Sensing and LiDAR Applications
- Simulation Techniques and Applications
- Sports Performance and Training
Colorado School of Mines
2018-2025
The University of Texas at Austin
2023-2025
Applied Mathematics (United States)
2020-2022
Texas A&M University
2021
Carnegie Mellon University
2020
Mississippi State University
2020
NSF National Center for Atmospheric Research
2015-2019
Brigham Young University
2018
University of Michigan–Ann Arbor
2011-2015
Tsinghua University
2015
The Gaussian process is an indispensable tool for spatial data analysts. onset of the "big data" era, however, has lead to traditional being computationally infeasible modern data. As such, various alternatives full that are more amenable handling big have been proposed. These methods often exploit low-rank structures and/or multi-core and multi-threaded computing environments facilitate computation. This study provides, first, introductory overview several analyzing large Second, this...
We develop a multiresolution model to predict two-dimensional spatial fields based on irregularly spaced observations. The radial basis functions at each level of resolution are constructed using Wendland compactly supported correlation function with the nodes arranged rectangular grid. grid finer increases by factor two and scaled have constant overlap. coefficients associated distributed according Gaussian Markov random field (GMRF) take advantage fact that is organized as lattice. Several...
Abstract. The rationale for using multi-model ensembles in climate change projections and impacts research is often based on the expectation that different models constitute independent estimates; therefore, a range of allows better characterisation uncertainties representation system than single model. However, it known groups share literature, ideas representations processes, parameterisations, evaluation data sets even sections model code. Thus, nominally might have similar biases because...
Satellite observations of CO 2 offer new opportunities to improve our understanding the global carbon cycle. Using such infer maps atmospheric and their associated uncertainties can provide key information about distribution dynamic behavior , through comparison distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with transport models. Ideally, these should be at temporal resolutions that are short enough represent capture synoptic dynamics ....
Methane mitigation from the oil and gas (O&G) sector represents a key near-term global climate action opportunity. Recent legislation in United States requires updating current methane reporting programs for facilities with empirical data. While technological advances have led to improvements emissions measurements monitoring, overall effectiveness of strategies rests on quantifying spatially temporally varying more accurately than approaches. In this work, we demonstrate quantification,...
Government policies and corporate strategies aimed at reducing methane emissions from the oil gas sector increasingly rely on measurement-informed, site-level emission inventories, as conventional bottom-up inventories poorly capture temporal variability heavy-tailed nature of emissions. This work is based an 11-month measurement campaign production sites. We find that operator-level top-down measurements are lower during end-of-project phase than baseline phase. However, gaps persist...
We propose a modular framework for methane emission detection, localization, and quantification on oil gas production sites that uses concentration wind data from point-in-space continuous monitoring systems. The leverages gradient-based spike detection algorithm to estimate start end times (event detection) pattern matches simulated observed concentrations source location (localization) rate (quantification). was evaluated month of non-blinded, single-source controlled releases ranging 0.50...
Abstract. High-resolution Earth system model simulations generate enormous data volumes, and retaining the from these often strains institutional storage resources. Further, exceedingly large requirements negatively impact science objectives, for example, by forcing reductions in output frequency, simulation length, or ensemble size. To lessen volumes Community System Model (CESM), we advocate use of lossy compression techniques. While does not exactly preserve original (as lossless does),...
January 2009 saw the successful launch of first space‐based mission specifically designed for measuring greenhouse gases, Japanese Greenhouse gases Observing SATellite (GOSAT). We present global land maps (Level 3 data) column‐averaged CO 2 concentrations (X CO2 ) derived using observations from GOSAT ACOS retrieval algorithm, July through December 2009. The applied geostatistical mapping approach makes it possible to generate at high spatial and temporal resolutions that include uncertainty...
Abstract. Climate simulation codes, such as the Community Earth System Model (CESM), are especially complex and continually evolving. Their ongoing state of development requires frequent software verification in form quality assurance to both preserve code instill model confidence. To formalize simplify this previously subjective computationally expensive aspect process, we have developed a new tool for evaluating climate consistency. Because an ensemble simulations allows us gauge natural...
We compare continuous monitoring systems (CMS) from three different vendors on six operating oil and gas sites in the Appalachian Basin using several months of data. highlight similarities differences between CMS solutions when deployed field their output to concurrent top-down aerial measurements site-level bottom-up inventories. Furthermore, we vendor-provided emission rate estimates an open-source quantification algorithm applied raw concentration This experimental setup allows us...
The rapid growth of weather and climate datasets is increasing the pressure on data centres hinders scientific analysis distribution. For example, kilometre-scale models can generate 20 gigabytes per second when run operationally, making it generally infeasible to store all output unless advanced compression applied. To address this challenge, novel lossy techniques, including recently so-called neural compressors which learn smaller representations data, have been proposed with...
Abstract This study presents climate change results from the North American Regional Climate Change Assessment Program (NARCCAP) suite of dynamically downscaled simulations for monsoon system in southwestern United States and northwestern Mexico. The focus is on changes precipitation processes driving projected regional their coupled atmosphere–ocean global models. effect known biases projections also examined. Overall, there strong ensemble agreement a large decrease during season; however,...
Abstract Space‐borne observations of CO 2 are vital to gaining understanding the carbon cycle in regions world that difficult measure directly, such as tropical terrestrial biosphere, high northern and southern latitudes, developing nations China. Measurements from passive instruments GOSAT OCO‐2, however, constrained by solar zenith angle limitations well sensitivity presence clouds aerosols. Active measurements those development for Sensing Emissions over Nights, Days Seasons (ASCENDS)...
Large, complex codes such as earth system models are in a constant state of development, requiring frequent software quality assurance. The recently developed Community Earth System Model (CESM) Ensemble Consistency Test (CESM-ECT) provides an objective measure statistical consistency for new CESM simulation runs, which has greatly facilitated error detection and rapid feedback model users developers. CESM-ECT determines based on ensemble simulations that represent the same model. Its...
Abstract While large climate model ensembles are invaluable tools for physically consistent prediction, they also present a burden in terms of computational resources and storage requirements. A complementary approach to initial-condition is train stochastic generator on fewer runs. simulations from statistical cannot capture the complexity runs, can address some specific scientific questions interest, such as sampling variability regional trends. We demonstrate this potential by comparing...
Addressing methane emissions across the liquefied natural gas (LNG) supply chain is key to reducing climate impacts of LNG. Actions address have emphasized importance use measurement-informed inventories, given systematic underestimation in official GHG emission inventories. Despite significant progress field measurements chain, no detailed at US liquefaction terminals are publicly available. In this work, we conduct multiscale, periodic and carbon dioxide two LNG over a 16-month campaign....
Methane measurements at liquefied natural gas (LNG) facilities play an important role in characterizing methane emissions from the supply chain. The large size and complexity of LNG make quantifying with ground-based monitoring systems challenging, making aerial platforms one preferred methods for these sites. However, typically provide a snapshot given instance, necessitating further analytical steps to infer both annualized range possible different instants time. This study uses two...
Abstract Applying lossy data compression to climate model output is an attractive means of reducing the enormous volumes generated by models. However, because does not exactly preserve original data, its application scientific must be done judiciously. To this end, a collection measures being developed evaluate various aspects quality on output. Given importance visualization scientists interacting with output, any suite include assessing whether images from compressed are noticeably...