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Susan E. Wijffels, Josh Willis, Catia M. Domingues, Paul Barker, Neil J. White, Ann Gronell, Ken Ridgway, and John A. Church

Abstract

A time-varying warm bias in the global XBT data archive is demonstrated to be largely due to changes in the fall rate of XBT probes likely associated with small manufacturing changes at the factory. Deep-reaching XBTs have a different fall rate history than shallow XBTs. Fall rates were fastest in the early 1970s, reached a minimum between 1975 and 1985, reached another maximum in the late 1980s and early 1990s, and have been declining since. Field XBT/CTD intercomparisons and a pseudoprofile technique based on satellite altimetry largely confirm this time history. A global correction is presented and applied to estimates of the thermosteric component of sea level rise. The XBT fall rate minimum from 1975 to 1985 appears as a 10-yr “warm period” in the global ocean in thermosteric sea level and heat content estimates using uncorrected data. Upon correction, the thermosteric sea level curve has reduced decadal variability and a larger, steadier long-term trend.

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Véronique Lago, Susan E. Wijffels, Paul J. Durack, John A. Church, Nathaniel L. Bindoff, and Simon J. Marsland

Abstract

The ocean’s surface salinity field has changed over the observed record, driven by an intensification of the water cycle in response to global warming. However, the origin and causes of the coincident subsurface salinity changes are not fully understood. The relationship between imposed surface salinity and temperature changes and their corresponding subsurface changes is investigated using idealized ocean model experiments. The ocean’s surface has warmed by about 0.5°C (50 yr)−1 while the surface salinity pattern has amplified by about 8% per 50 years. The idealized experiments are constructed for a 50-yr period, allowing a qualitative comparison to the observed salinity and temperature changes previously reported. The comparison suggests that changes in both modeled surface salinity and temperature are required to replicate the three-dimensional pattern of observed salinity change. The results also show that the effects of surface changes in temperature and salinity act linearly on the changes in subsurface salinity. Surface salinity pattern amplification appears to be the leading driver of subsurface salinity change on depth surfaces; however, surface warming is also required to replicate the observed patterns of change on density surfaces. This is the result of isopycnal migration modified by the ocean surface warming, which produces significant salinity changes on density surfaces.

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Gabriele C. Hegerl, Emily Black, Richard P. Allan, William J. Ingram, Debbie Polson, Kevin E. Trenberth, Robin S. Chadwick, Phillip A. Arkin, Beena Balan Sarojini, Andreas Becker, Aiguo Dai, Paul J. Durack, David Easterling, Hayley J. Fowler, Elizabeth J. Kendon, George J. Huffman, Chunlei Liu, Robert Marsh, Mark New, Timothy J. Osborn, Nikolaos Skliris, Peter A. Stott, Pier-Luigi Vidale, Susan E. Wijffels, Laura J. Wilcox, Kate M. Willett, and Xuebin Zhang

Abstract

Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time series over land, but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols and because of the large climate variability presently limits confidence in attribution of observed changes.

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Molly Baringer, Mariana B. Bif, Tim Boyer, Seth M. Bushinsky, Brendan R. Carter, Ivona Cetinić, Don P. Chambers, Lijing Cheng, Sanai Chiba, Minhan Dai, Catia M. Domingues, Shenfu Dong, Andrea J. Fassbender, Richard A. Feely, Eleanor Frajka-Williams, Bryan A. Franz, John Gilson, Gustavo Goni, Benjamin D. Hamlington, Zeng-Zhen Hu, Boyin Huang, Masayoshi Ishii, Svetlana Jevrejeva, William E. Johns, Gregory C. Johnson, Kenneth S. Johnson, John Kennedy, Marion Kersalé, Rachel E. Killick, Peter Landschützer, Matthias Lankhorst, Tong Lee, Eric Leuliette, Feili Li, Eric Lindstrom, Ricardo Locarnini, Susan Lozier, John M. Lyman, John J. Marra, Christopher S. Meinen, Mark A. Merrifield, Gary T. Mitchum, Ben Moat, Didier Monselesan, R. Steven Nerem, Renellys C. Perez, Sarah G. Purkey, Darren Rayner, James Reagan, Nicholas Rome, Alejandra Sanchez-Franks, Claudia Schmid, Joel P. Scott, Uwe Send, David A. Siegel, David A. Smeed, Sabrina Speich, Paul W. Stackhouse Jr., William Sweet, Yuichiro Takeshita, Philip R. Thompson, Joaquin A. Triñanes, Martin Visbeck, Denis L. Volkov, Rik Wanninkhof, Robert A. Weller, Toby K. Westberry, Matthew J. Widlansky, Susan E. Wijffels, Anne C. Wilber, Lisan Yu, Weidong Yu, and Huai-Min Zhang
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