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366 results on '"Wittenberg, Andrew T."'

3. Tropical cyclone sensitivities to CO2 doubling: roles of atmospheric resolution, synoptic variability and background climate changes

Author

Vecchi, Gabriel A, Delworth, Thomas L, Murakami, Hiroyuki, Underwood, Seth D, Wittenberg, Andrew T, Zeng, Fanrong, Zhang, Wei, Baldwin, Jane W, Bhatia, Kieran T, Cooke, William, He, Jie, Kapnick, Sarah B, Knutson, Thomas R, Villarini, Gabriele, van der Wiel, Karin, Anderson, Whit, Balaji, V, Chen, Jan–Huey, Dixon, Keith W, Gudgel, Rich, Harris, Lucas M, Jia, Liwei, Johnson, Nathaniel C, Lin, Shian-Jiann, Liu, Maofeng, Ng, Ching Ho Justin, Rosati, Anthony, Smith, James A, and Yang, Xiaosong

Subjects
Earth Sciences, Oceanography, Atmospheric Sciences, Climate Action, Physical Geography and Environmental Geoscience, Meteorology & Atmospheric Sciences, Atmospheric sciences, Climate change science
Abstract

Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.

Published
2019

5. Seasonal Prediction and Predictability of Regional Antarctic Sea Ice

Author

Bushuk, Mitchell, Winton, Michael, Haumann, F. Alexander, Delworth, Thomas, Lu, Feiyu, Zhang, Yongfei, Jia, Liwei, Zhang, Liping, Cooke, William, Harrison, Matthew, Hurlin, Bill, Johnson, Nathaniel C., Kapnick, Sarah B., McHugh, Colleen, Murakami, Hiroyuki, Rosati, Anthony, Tseng, Kai-Chih, Wittenberg, Andrew T., Yang, Xiaosong, and Zeng, Fanrong

Published
2021

6. EXPLAINING EXTREME EVENTS OF 2016 : From A Climate Perspective

Author

Herring, Stephanie C., Christidi, Nikolaos, Hoell, Andrew, Kossin, James P., Schreck, Carl J., Stott, Peter A., Webb, Robert S., Werner, Francisco E., Knutson, Thomas R., Kam, Jonghun, Zeng, Fanrong, Wittenberg, Andrew T., Brainard, Russell E., Oliver, Thomas, McPhaden, Michael J., Cohen, Anne, Venegas, Robert o, Heenan, Adel, Vargas-Ángel, Bernardo, Rotjan, Randi, Mangubhai, Sangeeta, Flint, Elizabeth, Hunter, Susan A., Oliver, Eric C. J., Perkins-Kirkpatrick, Sarah E., Holbrook, Neil J., Bindoff, Nathaniel L., Tett, Simon F. B., Falk, Alexander, Rogers, Megan, Spuler, Fiona, Turner, Calum, Wainwright, Joshua, Dimdore-Miles, Oscar, Knight, Sam, Freychet, Nicolas, Mineter, Michael J., Lehmann, Caroline E. R., Martins, Eduardo S. P. R., Coelho, Caio A. S., Haarsma, Rein, Otto, Friederike E. L., King, Andrew D., van Oldenborgh, Geert Jan, Kew, Sarah, Philip, Sjoukje, Vasconcelos, Francisco C., Cullen, Heidi, Jézéquel, Aglaé, Yiou, Pascal, Radanovics, Sabine, Vautard, Robert, Sippel, Sebastian, El-Madany, Tarek S., Migliavacca, Mirco, Mahecha, Miguel D., Carrara, Arnaud, Flach, Milan, Kaminski, Thomas, Otto, Friederike E. L., Thonicke, Kirsten, Vossbeck, Michael, Reichstein, Markus, Yuan, Xing, Wang, Linying, Wood, Eric F., Funk, Chris, Davenport, Frank, Harrison, Laura, Magadzire, Tamuka, Galu, Gideon, Artan, Guleid A., Shukla, Shraddhanand, Korecha, Diriba, Indeje, Matayo, Pomposi, Catherine, Macharia, Denis, Husak, Gregory, Nsadisa, Faka Dieudonne, Imada, Yukiko, Shiogama, Hideo, Takahashi, Chiharu, Watanabe, Masahiro, Mori, Masato, Kamae, Youichi, Maeda, Shuhei, Sun, Qiaohong, Miao, Chiyuan, Zhou, Chunlüe, Wang, Kaicun, Qi, Dan, Yuan, Xing, Wang, Shanshan, Hu, Zeng-Zhen, Qian, Cheng, Wang, Jun, Dong, Siyan, Yin, Hong, Burke, Claire, Ciavarella, Andrew, Dong, Buwen, Freychet, Nicolas, Lott, Fraser C., Tett, Simon F. B., Sun, Ying, Hu, Ting, Zhang, Xuebin, Wan, Hui, Stott, Peter, Lu, Chunhui, Christidis, Nikolaos, Manomaiphiboon, Kasemsan, Ciavarella, Andrew, Stott, Peter A., Hope, Pandora, Lim, Eun-Pa, Hendon, Harry, Wang, Guomin, Lewis, Sophie C., Mallela, Jennie, Grose, Michael R., Black, Mitchell, Risbey, James S., Uhe, Peter, Hope, Pandora K., Haustein, Karsten, Mitchell, Dann, Stott, Peter A., Christidis, Nikos, Herring, Stephanie C., Hoell, Andrew, Kossin, James P., and Schreck, Carl J.

Published
2018

13. Estimating Uncertainty in Simulated ENSO Statistics.

Author

Planton, Yann Y., Lee, Jiwoo, Wittenberg, Andrew T., Gleckler, Peter J., Guilyardi, Éric, McGregor, Shayne, and McPhaden, Michael J.

Subjects
GREENHOUSE gases, CLIMATE change models, OCEAN temperature, ATMOSPHERIC models, SQUARE root
Abstract

Large ensembles of model simulations are frequently used to reduce the impact of internal variability when evaluating climate models and assessing climate change induced trends. However, the optimal number of ensemble members required to distinguish model biases and climate change signals from internal variability varies across models and metrics. Here we analyze the mean, variance and skewness of precipitation and sea surface temperature in the eastern equatorial Pacific region often used to describe the El Niño–Southern Oscillation (ENSO), obtained from large ensembles of Coupled model intercomparison project phase 6 climate simulations. Leveraging established statistical theory, we develop and assess equations to estimate, a priori, the ensemble size or simulation length required to limit sampling‐based uncertainties in ENSO statistics to within a desired tolerance. Our results confirm that the uncertainty of these statistics decreases with the square root of the time series length and/or ensemble size. Moreover, we demonstrate that uncertainties of these statistics are generally comparable when computed using either pre‐industrial control or historical runs. This suggests that pre‐industrial runs can sometimes be used to estimate the expected uncertainty of statistics computed from an existing historical member or ensemble, and the number of simulation years (run duration and/or ensemble size) required to adequately characterize the statistic. This advance allows us to use existing simulations (e.g., control runs that are performed during model development) to design ensembles that can sufficiently limit diagnostic uncertainties arising from simulated internal variability. These results may well be applicable to variables and regions beyond ENSO. Plain Language Summary: Earth's climate naturally fluctuates on intraseasonal to interdecadal timescales, confounding the evaluation of climate models and the detection of trends linked to climate change. To tackle this challenge, scientists produce ensembles of simulations with identical external forcings (e.g., volcanic eruptions, greenhouse gas emissions) but plausibly different initial conditions. In this study, we analyze how these ensembles can be used to reduce the uncertainty of the simulated climate, to help guide the design of future ensembles and optimize the use of available computing resources. Key Points: Large ensembles of climate simulations are analyzed to characterize the sampling uncertainty of El Niño–Southern Oscillation statisticsAs expected, uncertainty of these statistics decreases with the square root of the number of simulated years provided by the ensembleA simple equation developed to predict the ensemble size required to limit this sampling uncertainty to within a given tolerance [ABSTRACT FROM AUTHOR]

Published
2024
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18. Objective Evaluation of Earth System Models: PCMDI Metrics Package (PMP) version 3

Author

Lee, Jiwoo, primary, Gleckler, Peter J., additional, Ahn, Min-Seop, additional, Ordonez, Ana, additional, Ullrich, Paul A., additional, Sperber, Kenneth R., additional, Taylor, Karl E., additional, Planton, Yann Y., additional, Guilyardi, Eric, additional, Durack, Paul, additional, Bonfils, Celine, additional, Zelinka, Mark D., additional, Chao, Li-Wei, additional, Dong, Bo, additional, Doutriaux, Charles, additional, Zhang, Chengzhu, additional, Vo, Tom, additional, Boutte, Jason, additional, Wehner, Michael F., additional, Pendergrass, Angeline G., additional, Kim, Daehyun, additional, Xue, Zeyu, additional, Wittenberg, Andrew T., additional, and Krasting, John, additional

Published
2023
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19. Supplementary material to "Objective Evaluation of Earth System Models: PCMDI Metrics Package (PMP) version 3"

Author

Lee, Jiwoo, primary, Gleckler, Peter J., additional, Ahn, Min-Seop, additional, Ordonez, Ana, additional, Ullrich, Paul A., additional, Sperber, Kenneth R., additional, Taylor, Karl E., additional, Planton, Yann Y., additional, Guilyardi, Eric, additional, Durack, Paul, additional, Bonfils, Celine, additional, Zelinka, Mark D., additional, Chao, Li-Wei, additional, Dong, Bo, additional, Doutriaux, Charles, additional, Zhang, Chengzhu, additional, Vo, Tom, additional, Boutte, Jason, additional, Wehner, Michael F., additional, Pendergrass, Angeline G., additional, Kim, Daehyun, additional, Xue, Zeyu, additional, Wittenberg, Andrew T., additional, and Krasting, John, additional

Published
2023
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23. Seasonal predictability of baroclinic wave activity

Author

Zhang, Gan, Murakami, Hiroyuki, Cooke, William F., Wang, Zhuo, Jia, Liwei, Lu, Feiyu, Yang, Xiaosong, Delworth, Thomas L., Wittenberg, Andrew T., Harrison, Matthew J., Bushuk, Mitchell, McHugh, Colleen, Johnson, Nathaniel C., Kapnick, Sarah B., Tseng, Kai-Chih, and Zhang, Liping

Published
2021
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24. Understanding ENSO Diversity

Author

Capotondi, Antonietta, Wittenberg, Andrew T, Newman, Matthew, Di Lorenzo, Emanuele, Yu, Jin-Yi, Braconnot, Pascale, Cole, Julia, Dewitte, Boris, Giese, Benjamin, Guilyardi, Eric, Jin, Fei-Fei, Karnauskas, Kristopher, Kirtman, Benjamin, Lee, Tong, Schneider, Niklas, Xue, Yan, and Yeh, Sang-Wook

Subjects
Astronomical and Space Sciences, Atmospheric Sciences, Physical Geography and Environmental Geoscience, Meteorology & Atmospheric Sciences
Abstract

Improved determination of ENSO predictability, teleconnections, and impacts requires a better understanding of event-to-event differences in ENSO spatial patterns and evolution.

Published
2015

28. OBSERVING AND PREDICTING THE 2015/16 EL NIÑO

Author

L’Heureux, Michelle L., Takahashi, Ken, Watkins, Andrew B., Barnston, Anthony G., Becker, Emily J., Di Liberto, Tom E., Gamble, Felicity, Gottschalck, Jon, Halpert, Michael S., Huang, Boyin, Mosquera-Vásquez, Kobi, and Wittenberg, Andrew T.

Published
2017

29. SUPPLEMENT : OBSERVING AND PREDICTING THE 2015/16 EL NIÑO

Author

L’Heureux, Michelle L., Takahashi, Ken, Watkins, Andrew B., Barnston, Anthony G., Becker, Emily J., Di Liberto, Tom E., Gamble, Felicity, Gottschalck, Jon, Halpert, Michael S., Huang, Boyin, Mosquera-Vásquez, Kobi, and Wittenberg, Andrew T.

Published
2017

37. 7. CMIP5 MODEL-BASED ASSESSMENT OF ANTHROPOGENIC INFLUENCE ON HIGHLY ANOMALOUS ARCTIC WARMTH DURING NOVEMBER-DECEMBER 2016: According to CMIP5 simulations, the highly anomalous Arctic warmth during November-December 2016, as estimated in five observed datasets, most likely would not have been possible without anthropogenic forcing

Author

Kam, Jonghun, Knutson, Thomas R., Zeng, Fanrong, and Wittenberg, Andrew T.

Subjects
Global warming -- Observations -- Models, Climate models -- Usage, Human-environment interactions -- Environmental aspects, Business, Earth sciences
Abstract

Introduction. Arctic surface temperatures during November-December 2016 were anomalously warm (Fig. 7.1a). An Arctic area-averaged temperature index (Fig. 7.1b and Fig. ES7.2) set a new high record in the GISS [...]

Published
2018

38. 3. CMIP5 MODEL-BASED ASSESSMENT OF ANTHROPOGENIC INFLUENCE ON RECORD GLOBAL WARMTH DURING 2016

Author

Knutson, Thomas R., Kam, Jonghun, Zeng, Fanrong, and Wittenberg, Andrew T.

Subjects
Global warming -- Research, Meteorological research, Climate models -- Usage, Human-environment interactions -- Models -- Research, Business, Earth sciences
Abstract

According to CMIP5 simulations, the 2016 record global warmth was only possible due to substantial centennial-scale anthropogenic warming. Natural variability made a smaller contribution to the JanuaryDecember 2016 annual-mean global [...]

Published
2018
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39. 4. THE EXTREME 2015/16 EL NINO, IN THE CONTEXT OF HISTORICAL CLIMATE VARIABILITY AND CHANGE

Author

Newman, Matthew, Wittenberg, Andrew T., Cheng, Linyin, Compo, Gilbert P., and Smith, Catherine A.

Subjects
Precipitation variability -- Research, Meteorological research -- Research, Business, Earth sciences
Abstract

Record warm central equatorial Pacific Ocean temperatures during the 2015/16 El Nino appear to partly reflect an anthropogenically forced trend. Whether they reflect changes in El Nino variability remains uncertain. [...]

Published
2018
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40. El Niño–Southern Oscillation complexity

Author

Timmermann, Axel, An, Soon-Il, Kug, Jong-Seong, Jin, Fei-Fei, Cai, Wenju, Capotondi, Antonietta, Cobb, Kim M., Lengaigne, Matthieu, McPhaden, Michael J., Stuecker, Malte F., Stein, Karl, Wittenberg, Andrew T., Yun, Kyung-Sook, Bayr, Tobias, Chen, Han-Ching, Chikamoto, Yoshimitsu, Dewitte, Boris, Dommenget, Dietmar, Grothe, Pamela, Guilyardi, Eric, Ham, Yoo-Geun, Hayashi, Michiya, Ineson, Sarah, Kang, Daehyun, Kim, Sunyong, Kim, WonMoo, Lee, June-Yi, Li, Tim, Luo, Jing-Jia, McGregor, Shayne, Planton, Yann, Power, Scott, Rashid, Harun, Ren, Hong-Li, Santoso, Agus, Takahashi, Ken, Todd, Alexander, Wang, Guomin, Wang, Guojian, Xie, Ruihuang, Yang, Woo-Hyun, Yeh, Sang-Wook, Yoon, Jinho, Zeller, Elke, and Zhang, Xuebin

Published
2018
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41. On the future zonal contrasts of equatorial Pacific climate: Perspectives from Observations, Simulations, and Theories

Author

Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Lee, Sukyoung, L’Heureux, Michelle, Wittenberg, Andrew T, Seager, Richard, O’Gorman, Paul A, Johnson, Nathaniel C, Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences, Lee, Sukyoung, L’Heureux, Michelle, Wittenberg, Andrew T, Seager, Richard, O’Gorman, Paul A, and Johnson, Nathaniel C

Abstract

AbstractChanges in the zonal gradients of sea surface temperature (SST) across the equatorial Pacific have major consequences for global climate. Therefore, accurate future projections of these tropical Pacific gradients are of paramount importance for climate mitigation and adaptation. Yet there is evidence of a dichotomy between observed historical gradient trends and those simulated by climate models. Observational records appear to show a “La Niña-like” strengthening of the zonal SST gradient over the past century, whereas most climate model simulations project “El Niño-like” changes toward a weaker gradient. Here, studies of these equatorial Pacific climate trends are reviewed, focusing first on data analyses and climate model simulations, then on theories that favor either enhanced or weakened zonal SST gradients, and then on notable consequences of the SST gradient trends. We conclude that the present divergence between the historical model simulations and the observed trends likely either reflects an error in the model’s forced response, or an underestimate of the multi-decadal internal variability by the models. A better understanding of the fundamental mechanisms of both forced response and natural variability is needed to reduce the uncertainty. Finally, we offer recommendations for future research directions and decision-making for climate risk mitigation.

Published
2023

49. Observing and predicting the 2015/16 El Nino

Author

L'Heureux, Michelle L., Takahashi, Ken, Watkins, Andrew B., Barnston, Anthony G., Becker, Emily J., Liberto, Tom E. Di, Gamble, Felicity, Gottschalck, Jon, Halpert, Michael S., Huang, Boyin, Mosquera-VAsquez, Kobi, and Wittenberg, Andrew T.

Subjects
Numerical weather forecasting -- Methods -- Environmental aspects, Southern oscillation -- Environmental aspects -- Methods, Business, Earth sciences
Abstract

ABSTRACT The El Nino of 2015/16 was among the strongest El Nino events observed since 1950 and took place almost two decades after the previous major event in 1997/98. Here, [...]

Published
2017
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