A5040434659- Meteorological Phenomena and Simulations
- Climate variability and models
- Precipitation Measurement and Analysis
- Scientific Computing and Data Management
- Distributed and Parallel Computing Systems
- Cryospheric studies and observations
- Computational Physics and Python Applications
- Tropical and Extratropical Cyclones Research
- Hydrology and Watershed Management Studies
- Atmospheric chemistry and aerosols
- Water resources management and optimization
- Water Quality and Resources Studies
- Transboundary Water Resource Management
- Smart Materials for Construction
- Hydrology and Drought Analysis
- Hydrological Forecasting Using AI
- Arctic and Antarctic ice dynamics
- Spectroscopy and Chemometric Analyses
- Environmental Monitoring and Data Management
- Oceanographic and Atmospheric Processes
- Rangeland Management and Livestock Ecology
- Soil Moisture and Remote Sensing
- Cloud Computing and Resource Management
- Electric Power System Optimization
- Soil and Environmental Studies
University of California, San Diego
2018-2020
Qualcomm (United States)
2019-2020
Scripps Institution of Oceanography
2016-2018
University of California, Irvine
2012-2015
Irvine University
2012-2014
UC Irvine Health
2013
University of California System
2011-2012
Abstract. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification tracking algorithms literature with a wide range of techniques conclusions. ARTMIP strives provide community information different methodologies guidance most appropriate for given question or region interest. All...
Abstract Atmospheric rivers (ARs) are now widely known for their association with high‐impact weather events and long‐term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify track of ARs—a necessary step analyses on gridded data sets, objective attribution impacts ARs. These different been answer specific research questions hence use criteria (e.g., geometry, threshold values key variables, time dependence). Furthermore,...
More than ever in the history of science, researchers have at their fingertips an unprecedented wealth data from continuously orbiting satellites, weather monitoring instruments, ecological observatories, seismic stations, moored buoys, floats, and even model simulations forecasts. With just internet connection, scientists engineers can access atmospheric oceanic gridded time series observations, seismographs around world, minute‐by‐minute conditions near‐Earth space environment, other...
Abstract The CONNected objECT (CONNECT) algorithm is applied to global Integrated Water Vapor Transport data from the NASA's Modern‐Era Retrospective Analysis for Research and Applications – Version 2 reanalysis product period of 1980 2016. generates life‐cycle records in time space evolving strong vapor transport events. We show five regions, located midlatitudes, where events typically exist (off coast southeast United States, eastern China, South America, off southern tip Africa,...
Typhoon Haiyan, which struck Southeast Asia in November 2013, might be the strongest storm on record, with a 10‐minute sustained wind speed of 230 kilometers per hour. In Philippines alone, damage was immense—the killed more than 6000 and completely leveled cities towns, particularly island Leyte.
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 This manuscript introduces a novel computational science approach for studying the impact of climate variability on precipitation. The uses an object-oriented connectivity algorithm that segments gridded near-global satellite precipitation data into four-dimensional (4D) objects (longitude, latitude, time, and intensity). These systems have distinct spatiotemporal properties are counted, tracked, described, stored in searchable database. A case study western United States is...
* ORCID: 0000-0003-0778-8964© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).CORRESPONDING AUTHOR: Scott L. Sellars, scottsellars@ucsd.edu
Abstract. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification tracking algorithms literature with a wide range of techniques conclusions. ARTMIP strives provide community information different methodologies guidance most appropriate for given question or region interest. All...
Abstract Extreme precipitation events, commonly associated with “Atmospheric Rivers,” are projected to increase in frequency and severity western North America; however, the intensity landfall position difficult forecast accurately. As isotopic signature of has been widely utilized as a tracer hydrologic cycle could potentially provide information about key physical processes, we utilize both climate isotope data investigate these events California from 2001 2011. Although individual have...
The advances in data, computing and networking over the last two decades led to a shift many application domains that includes machine learning on big data as part of scientific process, requiring new capabilities for integrated distributed hardware software infrastructure. This paper contributes workflow-driven approach dynamic data-driven development top kind networked Cyberinfrastructure called CHASE-CI. In particular, we present: 1) architecture CHASE-CI, network fast GPU appliances...
IVT-UCSD derived 3-hourly versus IVT-MERRA-provided 1hourlyComparing the 1-h to 3-h MERRA-2 provided time-averaged data suggests that there are only very small differences between two, meaning is little value added using data.Figure S1 shows difference average IVT magnitude for February 2017 computed with those two frequencies.Note magnitudes of colorbar.
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...