A5021491059- Meteorological Phenomena and Simulations
- Climate variability and models
- Precipitation Measurement and Analysis
- Tropical and Extratropical Cyclones Research
- Oceanographic and Atmospheric Processes
- Hydrological Forecasting Using AI
- Ionosphere and magnetosphere dynamics
- Advanced Computational Techniques and Applications
- Ocean Waves and Remote Sensing
- Cryospheric studies and observations
- Environmental Monitoring and Data Management
- Flood Risk Assessment and Management
- Oil Spill Detection and Mitigation
- Streptococcal Infections and Treatments
- Pneumonia and Respiratory Infections
- Hydrology and Watershed Management Studies
- Geophysics and Gravity Measurements
- Hydrology and Drought Analysis
- Calibration and Measurement Techniques
- Vector-borne infectious diseases
- Big Data Technologies and Applications
- COVID-19 epidemiological studies
- Atmospheric and Environmental Gas Dynamics
- Bacterial Infections and Vaccines
- Health disparities and outcomes
University of California, Irvine
2019-2025
Center For Remote Sensing (United States)
2025
U.S. Army Engineer Research and Development Center
2024
Pusan National University
2024
Orange County Healthcare Agency
2022-2023
UC Irvine Health
2022
Samueli Institute
2021
United States Army Corps of Engineers
2019
Scripps Institution of Oceanography
2019
University of California, San Diego
2019
Abstract The Center for Hydrometeorology and Remote Sensing (CHRS) has created the CHRS Data Portal to facilitate easy access three open data licensed satellite-based precipitation datasets generated by our Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) system: PERSIANN, PERSIANN-Cloud Classification System (CCS), PERSIANN-Climate Record (CDR). These have potential widespread use various researchers, professionals including engineers,...
Abstract Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component the hydrologic cycle as they responsible for much poleward transport and result in precipitation, sometimes extreme intensity. Despite their importance, uncertainty remains detection atmospheric rivers large datasets such reanalyses century scale climate simulations. To understand this uncertainty, River Tracking Method Intercomparison Project (ARTMIP) developed tiered...
The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes ARTMIP Tier 2 experimental design and initial results using Coupled Model (CMIP) Phases 5 6 multi-model ensembles. We show that statistics given ARDT in CMIP5/6 historical simulations compare remarkably well with MERRA-2 reanalysis. In future simulations, most...
Abstract This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. dataset provides hourly, quasi-global, infrared-based estimates at 0.04° × spatial resolution with a short latency (15–60 min). It is intended to supersede PERSIANN–Cloud Classification System (PERSIANN-CCS) previously produced as product of PERSIANN family. We first provide brief description...
Abstract Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation local climates. Understanding ARs in a warming climate is problematic because the AR response to change tied how feature defined. The River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) common data set...
Abstract Precipitation measurements with high spatiotemporal resolution are a vital input for hydrometeorological and water resources studies; decision-making in disaster management; weather, climate, hydrological forecasting. Moreover, real-time precipitation estimation precision is pivotal the monitoring managing of catastrophic hydroclimate disasters such as flash floods, which frequently transpire after extreme rainfall. While algorithms that exclusively use satellite infrared data...
* CURRENT AFFILIATIONS: T. A. O'Brien—Earth and Atmospheric Sciences, Indiana University, Bloomington, Indiana; Patricola—Geological Iowa State Ames, Iowa; J. O'Brien—National Center for Research, Boulder, Colorado© 2020 American Meteorological Society. For information regarding reuse of this content general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).Corresponding author: Travis O'Brien, obrienta@iu.edu
Abstract Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth's hydroclimate. However, there is no one quantitative definition what constitutes atmospheric river, leading to uncertainty quantifying how these systems respond global change. This study seeks better understand different AR detection tools (ARDTs) changes climate states utilizing single‐forcing model...
Abstract Tracking atmospheric rivers (ARs) across their lifecycles is a field of recent interest with multitude emerging methodologies. The CONNected‐objECT (CONNECT) algorithm adapted for the tracking global midlatitude AR and associated precipitation by implementing seeded region growing segmentation algorithm, creating AR‐CONNECT algorithm. To facilitate permissiveness methodology, without hard‐coded geometric criteria yet still shown to extract synoptic‐scale elongated objects >99.99%...
Abstract Background Spatial variability of COVID-19 cases may suggest geographic disparities social determinants health. analyses population-level data provide insight on factors that contribute to transmission, hospitalization, and death. Methods Generalized additive models were used map risk from March 2020 February 2021 in Orange County (OC), California. We geocoded analyzed 221,843 OC census tracts within a Poisson framework while smoothing over tract centroids. Location was randomly...
Earth and Space Science Open Archive This work has been accepted for publication in Journal of Geophysical Research - Atmospheres. Version RecordESSOAr is a venue early communication or feedback before peer review. Data may be preliminary. Learn more about preprints. preprintOpen AccessYou are viewing the latest version by default [v4]Increases Future AR Count Size: Overview ARTMIP Tier 2 CMIP5/6 ExperimentAuthorsTravis AllenO'BrieniDMichael FWehneriDAshley E.PayneiDChristine...
Flea-borne typhus (FBT), also referred to as murine typhus, is an acute febrile disease in humans caused by the bacteria Rickettsia typhi. Currently, cases of FBT are reported for public health surveillance purposes (i.e., detect incidence and outbreaks) a few U.S. states. In California, healthcare providers testing laboratories mandated report their respective local jurisdictions whenever R. typhi or antibodies reactive detected patient, who then state department. this study, we...
Abstract Increases in precipitation rates and volumes from tropical cyclones (TCs) caused by anthropogenic warming are predicted climate modeling studies have been identified several high intensity storms occurring over the last half decade. However, it has difficult to detect historical trends TC at time scales long enough overcome natural variability because of limitations existing observations. We introduce an experimental global high-resolution data record produced using infrared...
Summary Although word recognition tests continue to be widely employed by teachers, the application of out‐of‐date norms and varying methods administration scoring seriously reduce usefulness these tests. Largely as a result approaches from it was decided undertake large‐scale restandardization Burt‐Vernon Schonell produce reliable standardize procedures. The opportunity also taken record data in such way enable production revised orders words on both reflect contemporary usage, relate...
Abstract Most heavy precipitation events and extreme flooding over the U.S. Pacific coast can be linked to prevalent atmospheric river (AR) conditions. Thus, reliable quantitative estimation with a rich spatiotemporal resolution is vital for water management early warning systems of landslides these regions. At same time, high-quality near-real-time measurements AR remain challenging due complex topographic features land surface meteorological conditions region: specifically, orographic...
Earth and Space Science Open Archive This work has been accepted for publication in Journal of Geophysical Research - Atmospheres. Version RecordESSOAr is a venue early communication or feedback before peer review. Data may be preliminary. Learn more about preprints. preprintOpen AccessYou are viewing an older version [v3]Go to new versionIncreases Future AR Count Size: Overview the ARTMIP Tier 2 CMIP5/6 ExperimentAuthorsTravis AllenO'BrieniDMichael FWehneriDAshley E.PayneiDChristine...
The Forecast Informed Reservoir Operations (FIRO) initiative, led by the United States Army Corps of Engineers (USACE) in collaboration with multiple agencies and university partners, marks a significant shift integrating advanced weather hydrologic forecasting into reservoir management, particularly on US West Coast. At heart FIRO is utilization predictability atmospheric river (AR) landfall over multi-day timescales. However, challenges remain fully understanding predicting interactions...
Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth's hydroclimate. However, there is no one quantitative definition what constitutes atmospheric river, leading to uncertainty quantifying how these systems respond global change. This study seeks better understand different AR detection tools (ARDTs) changes climate states utilizing single-forcing model experiments...
Abstract Increases in precipitation rates and volumes from tropical cyclones (TCs) caused by anthropogenic warming are predicted climate modeling studies have been identified several high intensity storms occurring over the last half decade. However, it has difficult to detect historical trends TC at time scales long enough overcome natural variability because of limitations existing observations. Using a new global high-resolution data record precipitation, we identify general increases...
The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) and climate models impact our scientific understanding of ARs. This study describes ARTMIP Tier 2 experimental design initial results using Coupled Model (CMIP) Phases 5 6 multi-model ensembles. We show that statistics given ARDT in CMIP5/6 historical simulations compare remarkably well with reanalyses. In future...
In 2016, a team of earth scientists directly engaged computer to identify cyberinfrastructure (CI) approaches that would speed up an science workflow. This paper describes the evolution workflow as two teams bridged CI and image segmentation algorithm do large scale research. The Pacific Research Platform (PRP) Cognitive Hardware Software Ecosystem Community Infrastructure (CHASE-CI) resources were used significantly decreased workflow's wall-clock time from 19.5 days 53 minutes. improvement...
Abstract In this study, the Precipitation Estimates from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)-Dynamic Infrared Rain-rate model (PDIR) product, a consistently measured 40-year archive of satellite-measured cloud-top infrared temperature data with spatiotemporal resolution 0.04° and 3-hourly as forcing data, is used to investigate trends in TC precipitation 1980 2019 robust linear fitting over multi-year moving averages accumulations volume rates. Trend...
Abstract Background Association of serious bacterial infections (SBI) and preceding respiratory viral illness (RVI) has been described. Social distancing, (masking lockdowns), in response to pandemic resulted > 95% decrease RVI, specifically influenza (Flu). Invasive Streptococcus pneumoniae (iSpneumo) pyogenes (iGABHS) have substantial morbidity mortality. Decrease culture (Cx) proven iSpneumo during COVID reported. We used PCR empyema fluid for enhanced SBI microbiologic diagnosis....