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Eric C. J. Oliver and Neil J. Holbrook

Abstract

Spatially and temporally homogeneous measurements of ocean temperature variability at high resolution on the continental shelf are scarce. Daily estimates of large-scale ocean properties are readily available from global ocean reanalysis products. However, the ocean models that underpin these reanalysis products tend not to have been designed for the simulation of complex coastal ocean variability. Hence, across-shelf values are often poorly represented. This study involved developing a statistical approach to more accurately and robustly represent SST on the continental shelf informed by large-scale satellite observations and reanalysis data or model output. Using the southeastern Australian shelf region as a case study, this paper demonstrates that this statistical model approach generates more accurate estimates of the inshore SST using (i) offshore SST from Bluelink Reanalysis (BRAN) and (ii) the statistical relationship between inshore and offshore SST in observations from the Advanced Very High Resolution Radiometer. SST is separated into the mean, seasonal cycle, and residual variability, and separate models are developed for each component. The offshore locations used to inform the model are determined by taking into account (i) the quality of BRAN at each location, (ii) the strength between the inshore and offshore variability, and (iii) the proximity of the inshore and offshore locations. Model predictions are made for the continental shelf around southeastern Australia. The role of the mean circulation in providing connectivity between the shelf and the offshore regions is discussed, and how this information can be used to better inform the choice of model predictor locations, leading to a hybrid statistical–connectivity model.

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Philip J. Klotzbach and Eric C. J. Oliver

Abstract

The Madden–Julian oscillation (MJO) has been demonstrated to play a role in tropical cyclone (TC) activity around the globe in a number of recent studies. While the impact of the MJO on TCs in the Atlantic basin since the mid-1970s has been well documented, a newly developed 107-yr-long index for the MJO allows for additional analysis of the impacts of the MJO on Atlantic TC activity. TC activity in the Atlantic increases when MJO-related convection is enhanced over Africa and the Indian Ocean, while TC activity in the Atlantic is suppressed when the MJO enhances convection over the western Pacific. This long-term record of the MJO also allows for the analysis of how the MJO’s impacts may be modulated by other climate modes, such as the El Niño–Southern Oscillation (ENSO) over interannual time scales and the Atlantic multidecadal oscillation (AMO) over multidecadal time scales. When climatologically unfavorable conditions such as an El Niño event or a negative AMO phase are present, even TC-favorable MJO conditions are not enough to generate statistically significant increases in TC activity from the long-term average across the Atlantic basin. However, climatologically favorable conditions during a La Niña event or a warm AMO phase act to enhance the modulation of TC activity over the Atlantic basin by the MJO.

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Eric C. J. Oliver and Keith R. Thompson

Abstract

The most widely accepted characterization of the Madden–Julian oscillation (MJO) is the bivariate index developed by Wheeler and Hendon. This index relies in part on satellite-based observations of outgoing longwave radiation and thus is not defined for the presatellite era. The MJO is known to have a strong signature in surface pressure, and daily measurements of this variable are available as far back as the late nineteenth century. This study undertakes a statistical reconstruction of the Wheeler and Hendon MJO index from 1905 to 2008 based on tropical surface pressures estimated recently by the twentieth-century reanalysis project. The temporal and spectral properties of the reconstructed index are first shown to be consistent with the Wheeler and Hendon index over the common period (1979–2008). The reconstructed index is then validated over the earlier period (1905–1978) by examining its relationship with cloud cover, surface wind, precipitation, and sea level. These relationships are shown to be consistent with corresponding results obtained from the Wheeler and Hendon index over the shared period and stable over the earlier period. Finally, a simple damped harmonic oscillator model is used to gain new insights into the predictability of the MJO index and also demonstrate consistency between the reconstructed index and the Wheeler and Hendon index. These results give confidence in the validity of the historical reconstruction of the MJO index over the last century.

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Philip J. Klotzbach, Eric C. J. Oliver, Ronald D. Leeper, and Carl J. Schreck III

Abstract

The winter of 2014/15 brought record snow totals to portions of southeastern New England. Additionally, over 90% of Boston Logan Airport snowfall during the winter fell during phases 7 and 8 of the Madden–Julian oscillation (MJO) index. This motivated the authors to investigate potential connections between intense southeastern New England snowstorms and the MJO in the historical record. It was found that southeastern New England snowfall, measured since the 1930s at several stations in the region, recorded higher than average winter snowfalls when enhanced MJO convection was located over the western Pacific and the Western Hemisphere (phases 7–8). Similarly, snowfall was suppressed when enhanced MJO convection was located over the Maritime Continent (phases 4–5). The MJO also modulates the frequency of nor’easters, which contribute the majority of New England’s snowfall, as measured by reanalysis-derived cyclone tracks. These tracks were more numerous during the same MJO phases that lead to enhanced snowfall, and they were less common during phases with less snowfall.

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Eric C. J. Oliver, Simon J. Wotherspoon, Matthew A. Chamberlain, and Neil J. Holbrook

Abstract

Ocean climate extremes have received little treatment in the literature, aside from coastal sea level and temperatures affecting coral bleaching. Further, it is notable that extremes (e.g., temperature and precipitation) are typically not well represented in global climate models. Here, the authors improve dynamically downscaled ocean climate model estimates of sea surface temperature (SST) extremes in the Tasman Sea off southeastern Australia using satellite remotely sensed observed extreme SSTs and the simulated marine climate of the 1990s. This is achieved using a Bayesian hierarchical model in which the parameters of an extreme value distribution are modeled by linear regression onto the key marine climate variables (e.g., mean SST, SST variance, etc.). The authors then apply this fitted model, essentially a form of bias correction, to the marine climate projections for the 2060s under an A1B emissions scenario. They show that the extreme SSTs are projected to increase in the Tasman Sea in a nonuniform way. The 50-yr return period extreme SSTs are projected to increase by up to 2°C over the entire domain and by up to 4°C in a hotspot located in the central western portion of the Tasman Sea, centered at a latitude ~500 km farther south than the projected change in mean SST. The authors show that there is a greater than 50% chance that annual maximum SSTs will increase by at least 2°C in this hotspot and that this change is significantly different than that which might be expected because of random chance in an unchanged climate.

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Eric C. J. Oliver, Sarah E. Perkins-Kirkpatrick, Neil J. Holbrook, and Nathaniel L. Bindoff
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Zeya Li, Neil J. Holbrook, Xuebin Zhang, Eric C. J. Oliver, and Eva A. Cougnon

Abstract

Recent marine heatwave (MHW) events in the Tasman Sea have had dramatic impacts on the ecosystems, fisheries, and aquaculture off Tasmania’s east coast. However, our understanding of the large-scale drivers (forcing) and potential predictability of MHW events in this region off southeast Australia is still in its infancy. Here, we investigate the role of oceanic Rossby waves forced in the interior South Pacific on observed MHW occurrences off southeast Australia from 1994 to 2016, including the extreme 2015/16 MHW event. First, we used an upper-ocean heat budget analysis to show that 51% of these historical Tasman Sea MHWs were primarily due to increased East Australian Current (EAC) Extension poleward transports through the region. Second, we used lagged correlation analysis to empirically connect the EAC Extension intensification to incoming westward-propagating sea surface height (SSH) anomalies from the interior South Pacific. Third, we dynamically analyzed these SSH anomalies using simple process-based baroclinic and barotropic Rossby wave models forced by wind stress curl changes across the South Pacific. Finally, we show that associated monthly SSH changes around New Zealand may be a useful index of western Tasman Sea MHW predictability, with a lead time of 2–3 years. In conclusion, our findings demonstrate that there is potential predictability of advection-dominated MHW event likelihoods in the EAC Extension region up to several years in advance, due to the deterministic contribution from baroclinic and barotropic Rossby waves in modulating the EAC Extension transports.

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Philip J. Klotzbach, Carl J. Schreck III, Gilbert P. Compo, Steven G. Bowen, Ethan J. Gibney, Eric C. J. Oliver, and Michael M. Bell

Abstract

The 1933 Atlantic hurricane season was extremely active, with 20 named storms and 11 hurricanes including 6 major (category 3+; 1-min maximum sustained winds ≥96 kt) hurricanes occurring. The 1933 hurricane season also generated the most accumulated cyclone energy (an integrated metric that accounts for frequency, intensity, and duration) of any Atlantic hurricane season on record. A total of 8 hurricanes tracked through the Caribbean in 1933—the most on record. In addition, two category 3 hurricanes made landfall in the United States just 23 h apart: the Treasure Coast hurricane in southeast Florida followed by the Cuba–Brownsville hurricane in south Texas. This manuscript examines large-scale atmospheric and oceanic conditions that likely led to such an active hurricane season. Extremely weak vertical wind shear was prevalent over both the Caribbean and the tropical Atlantic throughout the peak months of the hurricane season, likely in part due to a weak-to-moderate La Niña event. These favorable dynamic conditions, combined with above-normal tropical Atlantic sea surface temperatures, created a very conducive environment for hurricane formation and intensification. The Madden–Julian oscillation was relatively active during the summer and fall of 1933, providing subseasonal conditions that were quite favorable for tropical cyclogenesis during mid- to late August and late September to early October. The current early June and August statistical models used by Colorado State University would have predicted a very active 1933 hurricane season. A better understanding of these extremely active historical Atlantic hurricane seasons may aid in anticipation of future hyperactive seasons.

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Jennifer A. MacKinnon, Zhongxiang Zhao, Caitlin B. Whalen, Amy F. Waterhouse, David S. Trossman, Oliver M. Sun, Louis C. St. Laurent, Harper L. Simmons, Kurt Polzin, Robert Pinkel, Andrew Pickering, Nancy J. Norton, Jonathan D. Nash, Ruth Musgrave, Lynne M. Merchant, Angelique V. Melet, Benjamin Mater, Sonya Legg, William G. Large, Eric Kunze, Jody M. Klymak, Markus Jochum, Steven R. Jayne, Robert W. Hallberg, Stephen M. Griffies, Steve Diggs, Gokhan Danabasoglu, Eric P. Chassignet, Maarten C. Buijsman, Frank O. Bryan, Bruce P. Briegleb, Andrew Barna, Brian K. Arbic, Joseph K. Ansong, and Matthew H. Alford

Abstract

Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.

Open access
Sara H. Knox, Robert B. Jackson, Benjamin Poulter, Gavin McNicol, Etienne Fluet-Chouinard, Zhen Zhang, Gustaf Hugelius, Philippe Bousquet, Josep G. Canadell, Marielle Saunois, Dario Papale, Housen Chu, Trevor F. Keenan, Dennis Baldocchi, Margaret S. Torn, Ivan Mammarella, Carlo Trotta, Mika Aurela, Gil Bohrer, David I. Campbell, Alessandro Cescatti, Samuel Chamberlain, Jiquan Chen, Weinan Chen, Sigrid Dengel, Ankur R. Desai, Eugenie Euskirchen, Thomas Friborg, Daniele Gasbarra, Ignacio Goded, Mathias Goeckede, Martin Heimann, Manuel Helbig, Takashi Hirano, David Y. Hollinger, Hiroki Iwata, Minseok Kang, Janina Klatt, Ken W. Krauss, Lars Kutzbach, Annalea Lohila, Bhaskar Mitra, Timothy H. Morin, Mats B. Nilsson, Shuli Niu, Asko Noormets, Walter C. Oechel, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Karina V. R. Schäfer, Hans Peter Schmid, Narasinha Shurpali, Oliver Sonnentag, Angela C. I. Tang, Masahito Ueyama, Rodrigo Vargas, Timo Vesala, Eric J. Ward, Lisamarie Windham-Myers, Georg Wohlfahrt, and Donatella Zona

Abstract

This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from −0.2 ± 0.02 g C m–2 yr–1 for an upland forest site to 114.9 ± 13.4 g C m–2 yr–1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m–2 yr–1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average ±1.6 g C m–2 yr–1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.

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