Zobrazeno 1 - 10 of 33 pro vyhledávání: '"Alicia Karspeck"'
1
Akademický článek
The use of ambient humidity conditions to improve influenza forecast.
Autor: Jeffrey Shaman, Sasikiran Kandula, Wan Yang, Alicia Karspeck
Publikováno v: PLoS Computational Biology, Vol 13, Iss 11, p e1005844 (2017)
Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves t
Externí odkaz: https://doaj.org/article/215a1316b22a4d0693d7ba812a21ef03
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2
Akademický článek
Comparison of filtering methods for the modeling and retrospective forecasting of influenza epidemics.
Autor: Wan Yang, Alicia Karspeck, Jeffrey Shaman
Publikováno v: PLoS Computational Biology, Vol 10, Iss 4, p e1003583 (2014)
A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. These methods have found application in a range of disciplines and settings, including engineering design and forecasting, and
Externí odkaz: https://doaj.org/article/54fcf6e0983244a09a262ff17fbec126
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3
A Hindcast Approach to Diagnosing the Equatorial Pacific Cold Tongue SST Bias in CESM1
Autor: Angela Cheska Siongco, Alicia Karspeck, Stephen A. Klein, Jeffrey L. Anderson, Hsi-Yen Ma, Shaocheng Xie, Kevin Raeder
Publikováno v: Journal of Climate. 33:1437-1453
An ensemble seasonal hindcast approach is used to investigate the development of the equatorial Pacific Ocean cold sea surface temperature (SST) bias and its characteristic annual cycle in the Community Earth System Model, version 1 (CESM1). In obser
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b1c5a56f8d541d3fe15a156bbcad7c7f
https://doi.org/10.1175/jcli-d-19-0513.1
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4
On the Correspondence between Seasonal Forecast Biases and Long-Term Climate Biases in Sea Surface Temperature
Autor: Jeffrey L. Anderson, Alicia Karspeck, Jiwoo Lee, A. Cheska Siongco, Shaocheng Xie, Joseph Tribbia, Hiroyuki Murakami, Ben P. Kirtman, Stephen A. Klein, Hsi-Yen Ma, William J. Merryfield, Kevin Raeder
Publikováno v: Journal of Climate. 34:427-446
The correspondence between mean sea surface temperature (SST) biases in retrospective seasonal forecasts (hindcasts) and long-term climate simulations from five global climate models is examined to diagnose the degree to which systematic SST biases d
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::868c5b9430fc8bfc67f3a729e6b9eb75
https://doi.org/10.1175/jcli-d-20-0338.1
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5
Reproducing Internal Variability with Few Ensemble Runs
Autor: Stefano Castruccio, Dorit Hammerling, Ziqing Hu, Alicia Karspeck, Benjamin M. Sanderson
Publikováno v: Journal of Climate. 32:8511-8522
While large climate model ensembles are invaluable tools for physically consistent climate prediction, they also present a large burden in terms of computational resources and storage requirements. A complementary approach to large initial-condition
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c21c1cac889837164e9f495e03ee5176
https://doi.org/10.1175/jcli-d-19-0280.1
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6
An EnOI‐Based Data Assimilation System With DART for a High‐Resolution Version of the CESM2 Ocean Component
Autor: Jonathan Hendricks, Frédéric Castruccio, Alicia Karspeck, Timothy J. Hoar, Nancy Collins, Jeffrey L. Anderson, Gokhan Danabasoglu
Publikováno v: Journal of Advances in Modeling Earth Systems, Vol 12, Iss 11, Pp n/a-n/a (2020)
An ensemble optimal interpolation (EnOI) data assimilation system for a high‐resolution (0.1° horizontal) version of the Community Earth System Model Version 2 (CESM2) ocean component is presented. For this purpose, a new version of the Data Assim
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59099151cf3c26171af8786588e2e6ea
https://doi.org/10.1029/2020ms002176
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8
Predicting Near-Term Changes in the Earth System: A Large Ensemble of Initialized Decadal Prediction Simulations Using the Community Earth System Model
Autor: Nan Rosenbloom, Matthew C. Long, Nicole S. Lovenduski, Gokhan Danabasoglu, Warren G. Strand, Gerald A. Meehl, Keith Lindsay, Alicia Karspeck, Stephen Yeager, Susan C. Bates, Haiyan Teng
Publikováno v: Bulletin of the American Meteorological Society. 99:1867-1886
The objective of near-term climate prediction is to improve our fore-knowledge, from years to a decade or more in advance, of impactful climate changes that can in general be attributed to a combination of internal and externally forced variability.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fab6fc2ab4e887861b149643f092aadb
https://doi.org/10.1175/bams-d-17-0098.1
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10
Predictability of 2-year La Niña events in a coupled general circulation model
Autor: Yuko M. Okumura, Clara Deser, Pedro N. DiNezio, Alicia Karspeck
Publikováno v: Climate Dynamics. 49:4237-4261
The predictability of the duration of La Nina is assessed using the Community Earth System Model Version 1 (CESM1), a coupled climate model capable of simulating key features of the El Nino/Southern Oscillation (ENSO) phenomenon, including the multi-
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::884d970bbbefab4766abc5bf9be53373
https://doi.org/10.1007/s00382-017-3575-3
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