We estimate the rise in global average sea level from satellite altimeter data for 1993–2009 and from coastal and island sea-level measurements from 1880 to 2009. For 1993–2009 and after correcting for glacial isostatic adjustment, the estimated rate of rise is 3.2 ± 0.4 mm year⁻¹ from the satellite data and 2.8 ± 0.8 mm year⁻¹ from the in situ data. The global average sea-level rise from 1880 to 2009 is about 210 mm. The linear trend from 1900 to 2009 is 1.7 ± 0.2 mm year⁻¹ and since 1961 is 1.9 ± 0.4 mm year⁻¹. There is considerable variability in the rate of rise during the twentieth century but there has been a statistically significant acceleration since 1880 and 1900 of 0.009 ± 0.003 mm year⁻² and 0.009 ± 0.004 mm year⁻², respectively. Since the start of the altimeter record in 1993, global average sea level rose at a rate near the upper end of the sea level projections of the Intergovernmental Panel on Climate Change’s Third and Fourth Assessment Reports. However, the reconstruction indicates there was little net change in sea level from 1990 to 1993, most likely as a result of the volcanic eruption of Mount Pinatubo in 1991.

TOPEX/Poseidon satellite altimeter data are used to estimate global empirical orthogonal functions that are then combined with historical tide gauge data to estimate monthly distributions of large-scale sea level variability and change over the period 1950–2000. The reconstruction is an attempt to narrow the current broad range of sea level rise estimates, to identify any pattern of regional sea level rise, and to determine any variation in the rate of sea level rise over the 51-yr period. The computed rate of global-averaged sea level rise from the reconstructed monthly time series is 1.8 ± 0.3 mm yr−1. With the decadal variability in the computed global mean sea level, it is not possible to detect a significant increase in the rate of sea level rise over the period 1950–2000. A regional pattern of sea level rise is identified. The maximum sea level rise is in the eastern off-equatorial Pacific and there is a minimum along the equator, in the western Pacific, and in the eastern Indian Ocean. A g... Abstract TOPEX/Poseidon satellite altimeter data are used to estimate global empirical orthogonal functions that are then combined with historical tide gauge data to estimate monthly distributions of large-scale sea level variability and change over the period 1950–2000. The reconstruction is an attempt to narrow the current broad range of sea level rise estimates, to identify any pattern of regional sea level rise, and to determine any variation in the rate of sea level rise over the 51-yr period. The computed rate of global-averaged sea level rise from the reconstructed monthly time series is 1.8 ± 0.3 mm yr−1. With the decadal variability in the computed global mean sea level, it is not possible to detect a significant increase in the rate of sea level rise over the period 1950–2000. A regional pattern of sea level rise is identified. The maximum sea level rise is in the eastern off-equatorial Pacific and there is a minimum along the equator, in the western Pacific, and in the eastern Indian Ocean. A g...

Despite widespread efforts to implement climate services, there is almost no literature that systematically analyzes users' needs. This paper addresses this gap by applying a decision analysis perspective to identify what kind of mean sea level rise (SLR) information is needed for local coastal adaptation decisions. We first characterize these decisions, then identify suitable decision analysis approaches and the sea level information required, and finally discuss if and how these information needs can be met given the state of the art of sea level science. We find that four types of information are needed: (i) probabilistic predictions for short‐term decisions when users are uncertainty tolerant; (ii) high‐end and low‐end SLR scenarios chosen for different levels of uncertainty tolerance; (iii) upper bounds of SLR for users with a low uncertainty tolerance; and (iv) learning scenarios derived from estimating what knowledge will plausibly emerge about SLR over time. Probabilistic predictions can only be attained for the near term (i.e., 2030–2050) before SLR significantly diverges between low and high emission scenarios, for locations for which modes of climate variability are well understood and the vertical land movement contribution to local sea levels is small. Meaningful SLR upper bounds cannot be defined unambiguously from a physical perspective. Low‐ to high‐end scenarios for different levels of uncertainty tolerance and learning scenarios can be produced, but this involves both expert and user judgments. The decision analysis procedure elaborated here can be applied to other types of climate information that are required for mitigation and adaptation purposes.