Shearer, Eric J.; Nguyen, Phu; Sellars, Scott L.; Analui, Bita; Kawzenuk, Brian; Hsu, Kuo-Lin; Sorooshian, Soroosh (2020). The Atmospheric River-CONNected objECT (AR-CONNECT) algorithm applied to the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA V2) - 1983 to 2016. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0D21W00

This collection contains the lifecycles of global atmospheric river (AR) objects. This data was produced by isolating regions of enhanced IVT transport events by applying the Atmospheric River-CONNected objECT (AR-CONNECT) algorithm. AR-CONNECT is a four-dimensional (4D) object-oriented algorithm, adapted from the CONNECT algorithm developed by a team of researchers from the University of California, Irvine [Sellars et al., 2013, 2015, 2017]. The algorithm uses a seeded region growing segmentation technique to segment AR lifecycles according to their high-intensity cores. AR-CONNECT determines the lifecycles of an AR by using a flood-filling algorithm to group discrete AR timeslices where they are contiguous over time and space. Each object has a unique ID and a set of selected characteristics.

• 2018 to 2020

• 2020

• Analui, Bita
• Hsu, Kuo-Lin
• Kawzenuk, Brian K.
• Nguyen, Phu
• Sellars, Scott L.
• Shearer, Eric J.
• Sorooshian, Soroosh

This research was partially supported by Cooperative Institute for Climate and Satellites (CICS) program (#NA14NES4320003), National Science Foundation (#1331915), Department of Energy (#DE-IA0000018), California Energy Commission (#300-15-005), Ridge to Reef NSF Research Traineeship (#DGE-1735040), and University of California (#4600010378 TO#15 Am 22).

• Global

• Atmospheric river
• Atmospheric River-CONNected objECT (AR-CONNECT) algorithm
• Hydrologic cycle
• Integrated water vapor
• NASA Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA V2)
• Object-oriented programming

• data
• text

• English

Identifier: Bita Analui: http://orcid.org/0000-0003-4377-7453

Identifier: Brian K. Kawzenuk: http://orcid.org/0000-0003-1194-4296

Identifier: Eric J. Shearer: http://orcid.org/0000-0001-5997-2806

Identifier: Kuo-Lin Hsu: http://orcid.org/0000-0002-3578-3565

Identifier: Phu Nguyen: http://orcid.org/0000-0002-9055-2583

Identifier: Scott L. Sellars: http://orcid.org/0000-0003-0778-8964

Identifier: Soroosh Sorooshian: http://orcid.org/0000-0001-7774-5113

Doi: https://doi.org/10.6075/J0D21W00

Primary associated publication

• Sellars, S. L., Kawzenuk, B., Nguyen, P., Ralph, F. M. & Sorooshian, S. (2017). Genesis, Pathways, and Terminations of Intense Global Water Vapor Transport in Association with Large-Scale Climate Patterns. Geophysical Research Letters, 44. https://doi.org/10.1002/2017GL075495

Previous version

• Sellars, Scott L.; Nguyen, Phu; Kawzenuk, Brian (2017). The CONNected objECT, or CONNECT algorithm applied to National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA V2) - Integrated Water Vapor from 1980 to 2016. UC San Diego Library Digital Collections. https://doi.org/10.6075/J01834P8

Reference

• Gelaro, R., W. McCarty, M.J. Suárez, R. Todling, A. Molod, L. Takacs, C.A. Randles, A. Darmenov, M.G. Bosilovich, R. Reichle, K. Wargan, L. Coy, R. Cullather, C. Draper, S. Akella, V. Buchard, A. Conaty, A.M. da Silva, W. Gu, G. Kim, R. Koster, R. Lucchesi, D. Merkova, J.E. Nielsen, G. Partyka, S. Pawson, W. Putman, M. Rienecker, S.D. Schubert, M. Sienkiewicz, and B. Zhao, 2017: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1
• Sellars, S., Gao, X., & Sorooshian, S. (2015). An Object-Oriented Approach to Investigate Impacts of Climate Oscillations on Precipitation: A Western United States Case Study. Journal of Hydrometeorology, 16(2), 830–842. https://doi.org/10.1175/JHM-D-14-0101.1
• Sellars, S., Nguyen, P., Chu, W., Gao, X., Hsu, K., & Sorooshian, S. (2013). Computational Earth Science: Big Data Transformed Into Insight. Eos, Transactions American Geophysical Union, 94, 277–278. https://doi.org/10.1002/2013EO320001

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2022-11-28