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- Author or Editor: Nathaniel L. Bindoff x
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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.
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.
Abstract
Ocean warming accounts for the majority of the earth’s recent energy imbalance. Historic ocean heat content (OHC) changes are important for understanding changing climate. Calculations of OHC anomalies (OHCA) from in situ measurements provide estimates of these changes. Uncertainties in OHCA estimates arise from calculating global fields from temporally and spatially irregular data (mapping method), instrument bias corrections, and the definitions of a baseline climatology from which anomalies are calculated. To investigate sensitivity of OHCA estimates for the upper 700 m to these different factors, the same quality-controlled dataset is used by seven groups and comparisons are made. Two time periods (1970–2008 and 1993–2008) are examined. Uncertainty due to the mapping method is 16.5 ZJ for 1970–2008 and 17.1 ZJ for 1993–2008 (1 ZJ = 1 × 1021 J). Uncertainty due to instrument bias correction varied from 8.0 to 17.9 ZJ for 1970–2008 and from 10.9 to 22.4 ZJ for 1993–2008, depending on mapping method. Uncertainty due to baseline mean varied from 3.5 to 14.5 ZJ for 1970–2008 and from 2.7 to 9.8 ZJ for 1993–2008, depending on mapping method and offsets. On average mapping method is the largest source of uncertainty. The linear trend varied from 1.3 to 5.0 ZJ yr−1 (0.08–0.31 W m−2) for 1970–2008 and from 1.5 to 9.4 ZJ yr−1 (0.09–0.58 W m−2) for 1993–2008, depending on method, instrument bias correction, and baseline mean. Despite these complications, a statistically robust upper-ocean warming was found in all cases for the full time period.
Abstract
Ocean warming accounts for the majority of the earth’s recent energy imbalance. Historic ocean heat content (OHC) changes are important for understanding changing climate. Calculations of OHC anomalies (OHCA) from in situ measurements provide estimates of these changes. Uncertainties in OHCA estimates arise from calculating global fields from temporally and spatially irregular data (mapping method), instrument bias corrections, and the definitions of a baseline climatology from which anomalies are calculated. To investigate sensitivity of OHCA estimates for the upper 700 m to these different factors, the same quality-controlled dataset is used by seven groups and comparisons are made. Two time periods (1970–2008 and 1993–2008) are examined. Uncertainty due to the mapping method is 16.5 ZJ for 1970–2008 and 17.1 ZJ for 1993–2008 (1 ZJ = 1 × 1021 J). Uncertainty due to instrument bias correction varied from 8.0 to 17.9 ZJ for 1970–2008 and from 10.9 to 22.4 ZJ for 1993–2008, depending on mapping method. Uncertainty due to baseline mean varied from 3.5 to 14.5 ZJ for 1970–2008 and from 2.7 to 9.8 ZJ for 1993–2008, depending on mapping method and offsets. On average mapping method is the largest source of uncertainty. The linear trend varied from 1.3 to 5.0 ZJ yr−1 (0.08–0.31 W m−2) for 1970–2008 and from 1.5 to 9.4 ZJ yr−1 (0.09–0.58 W m−2) for 1993–2008, depending on method, instrument bias correction, and baseline mean. Despite these complications, a statistically robust upper-ocean warming was found in all cases for the full time period.
The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that global warming is “unequivocal” and that most of the observed increase since the mid-twentieth century is very likely due to the increase in anthropogenic greenhouse gas concentrations, with discernible human influences on ocean warming, continental-average temperatures, temperature extremes, wind patterns, and other physical and biological indicators, impacting both socioeconomic and ecological systems. It is now clear that we are committed to some level of global climate change, and it is imperative that this be considered when planning future climate research and observational strategies. The Global Climate Observing System program (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) therefore initiated a process to summarize the lessons learned through AR4 Working Groups I and II and to identify a set of high-priority modeling and observational needs. Two classes of recommendations emerged. First is the need to improve climate models, observational and climate monitoring systems, and our understanding of key processes. Second, the framework for climate research and observations must be extended to document impacts and to guide adaptation and mitigation efforts. Research and observational strategies specifically aimed at improving our ability to predict and understand impacts, adaptive capacity, and societal and ecosystem vulnerabilities will serve both purposes and are the subject of the specific recommendations made in this paper.
The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that global warming is “unequivocal” and that most of the observed increase since the mid-twentieth century is very likely due to the increase in anthropogenic greenhouse gas concentrations, with discernible human influences on ocean warming, continental-average temperatures, temperature extremes, wind patterns, and other physical and biological indicators, impacting both socioeconomic and ecological systems. It is now clear that we are committed to some level of global climate change, and it is imperative that this be considered when planning future climate research and observational strategies. The Global Climate Observing System program (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) therefore initiated a process to summarize the lessons learned through AR4 Working Groups I and II and to identify a set of high-priority modeling and observational needs. Two classes of recommendations emerged. First is the need to improve climate models, observational and climate monitoring systems, and our understanding of key processes. Second, the framework for climate research and observations must be extended to document impacts and to guide adaptation and mitigation efforts. Research and observational strategies specifically aimed at improving our ability to predict and understand impacts, adaptive capacity, and societal and ecosystem vulnerabilities will serve both purposes and are the subject of the specific recommendations made in this paper.
