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Future extreme sea level seesaws in the tropical Pacific.

Widlansky MJ, Timmermann A, Cai W - Sci Adv (2015)

Bottom Line: Global mean sea levels are projected to gradually rise in response to greenhouse warming.Using present-generation coupled climate models forced with increasing greenhouse gas concentrations and subtracting the effect of global mean sea level rise, we find that climate change will enhance El Niño-related sea level extremes, especially in the tropical southwestern Pacific, where very low sea level events, locally known as Taimasa, are projected to double in occurrence.Additionally, and throughout the tropical Pacific, prolonged interannual sea level inundations are also found to become more likely with greenhouse warming and increased frequency of extreme La Niña events, thus exacerbating the coastal impacts of the projected global mean sea level rise.

View Article: PubMed Central - PubMed

Affiliation: International Pacific Research Center, University of Hawai'i at Mānoa, 1680 East-West Road, Honolulu, HI 96822, USA.

ABSTRACT
Global mean sea levels are projected to gradually rise in response to greenhouse warming. However, on shorter time scales, modes of natural climate variability in the Pacific, such as the El Niño-Southern Oscillation (ENSO), can affect regional sea level variability and extremes, with considerable impacts on coastal ecosystems and island nations. How these shorter-term sea level fluctuations will change in association with a projected increase in extreme El Niño and its atmospheric variability remains unknown. Using present-generation coupled climate models forced with increasing greenhouse gas concentrations and subtracting the effect of global mean sea level rise, we find that climate change will enhance El Niño-related sea level extremes, especially in the tropical southwestern Pacific, where very low sea level events, locally known as Taimasa, are projected to double in occurrence. Additionally, and throughout the tropical Pacific, prolonged interannual sea level inundations are also found to become more likely with greenhouse warming and increased frequency of extreme La Niña events, thus exacerbating the coastal impacts of the projected global mean sea level rise.

No MeSH data available.


Related in: MedlinePlus

Observed nonlinear relationship of sea surface height variability and its future change under greenhouse warming.(A) Nonlinear and lagged (8-month) relationship between the first and second EOF projection time series of sea surface height anomalies. The inset shows the correlation coefficient between the first and second EOF projections as a function of lag in months (EOF2 lags EOF1 by 8 months, r = 0.57). The critical value (P > 95%) for the correlation coefficient is 0.39 based on the autocorrelation decay time scales of the projections. The solid green box encloses the prolonged sea level drops for the tropical southwestern Pacific (Taimasa; 13 months observed when both EOF1 and EOF2 projections exceed 2 SDs). Prolonged interannual coastal inundation of similar magnitude and duration has not been observed (dashed green box). (B) Projected future change (RCP8.5 minus historical; color scale) and 20th-century (historical; dashed and solid black contours) multimodel probability of occurrence (%) for the principal variability patterns of sea surface height (EOF2 lags EOF1 by 8 months). Contour intervals are nonlinear: 10−3, 10−2, 10−1 (dashed), and 1 (solid). A kernel smoothing function (normal distribution; bin width of 1 SD) is applied to the bivariate distribution. An increase in Taimasa events (380 versus 875 simulated-months) and prolonged coastal inundation (18 versus 98 simulated-months) from the historical to future period is projected (months when both EOF1 and EOF2 projections exceed ±2 SDs; blue circles, historical; red dots, RCP8.5).
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Figure 4: Observed nonlinear relationship of sea surface height variability and its future change under greenhouse warming.(A) Nonlinear and lagged (8-month) relationship between the first and second EOF projection time series of sea surface height anomalies. The inset shows the correlation coefficient between the first and second EOF projections as a function of lag in months (EOF2 lags EOF1 by 8 months, r = 0.57). The critical value (P > 95%) for the correlation coefficient is 0.39 based on the autocorrelation decay time scales of the projections. The solid green box encloses the prolonged sea level drops for the tropical southwestern Pacific (Taimasa; 13 months observed when both EOF1 and EOF2 projections exceed 2 SDs). Prolonged interannual coastal inundation of similar magnitude and duration has not been observed (dashed green box). (B) Projected future change (RCP8.5 minus historical; color scale) and 20th-century (historical; dashed and solid black contours) multimodel probability of occurrence (%) for the principal variability patterns of sea surface height (EOF2 lags EOF1 by 8 months). Contour intervals are nonlinear: 10−3, 10−2, 10−1 (dashed), and 1 (solid). A kernel smoothing function (normal distribution; bin width of 1 SD) is applied to the bivariate distribution. An increase in Taimasa events (380 versus 875 simulated-months) and prolonged coastal inundation (18 versus 98 simulated-months) from the historical to future period is projected (months when both EOF1 and EOF2 projections exceed ±2 SDs; blue circles, historical; red dots, RCP8.5).

Mentions: The leading two patterns of sea level variability exhibit an asymmetric, nonlinear relationship (Fig. 4A) between PC1 and the 8-month lagged PC2 (Fig. 4A, inset), which is dominated by extreme values in positive PC1 and PC2 that correspond to the El Niño Taimasa events (8). Similar extreme values for La Niña events are absent. The fact that extreme amplitudes of the EOF2 projection lag EOF1 prolongs sea level anomalies in those regions of the Pacific where the EOF patterns are of the same sign (see Fig. 3, insets), potentially enhancing local impacts from El Niño such as low sea level stands and coral die-offs. The opposite pattern combination (EOF1 and EOF2 projections <−2 SDs) has never been observed, but such an event—should one ever occur—would be associated with prolonged coastal inundations in the same regions affected by Taimasa. Such sea level high stands (that is, summing the opposite of the leading patterns of sea level variability shown in Fig. 3, insets) are perceivable should future changes occur in the wind stress curl associated with the orientation of the SPCZ, perhaps influenced by future extreme La Niña events (24) combined with changing mean sea surface temperatures (30). The nonlinear relationship between the zonal and meridional seesaw modes (Fig. 4A) is also reminiscent of similar characteristics for the rainfall variability in the Pacific (18, 23) and equatorial wind stress (fig. S5).


Future extreme sea level seesaws in the tropical Pacific.

Widlansky MJ, Timmermann A, Cai W - Sci Adv (2015)

Observed nonlinear relationship of sea surface height variability and its future change under greenhouse warming.(A) Nonlinear and lagged (8-month) relationship between the first and second EOF projection time series of sea surface height anomalies. The inset shows the correlation coefficient between the first and second EOF projections as a function of lag in months (EOF2 lags EOF1 by 8 months, r = 0.57). The critical value (P > 95%) for the correlation coefficient is 0.39 based on the autocorrelation decay time scales of the projections. The solid green box encloses the prolonged sea level drops for the tropical southwestern Pacific (Taimasa; 13 months observed when both EOF1 and EOF2 projections exceed 2 SDs). Prolonged interannual coastal inundation of similar magnitude and duration has not been observed (dashed green box). (B) Projected future change (RCP8.5 minus historical; color scale) and 20th-century (historical; dashed and solid black contours) multimodel probability of occurrence (%) for the principal variability patterns of sea surface height (EOF2 lags EOF1 by 8 months). Contour intervals are nonlinear: 10−3, 10−2, 10−1 (dashed), and 1 (solid). A kernel smoothing function (normal distribution; bin width of 1 SD) is applied to the bivariate distribution. An increase in Taimasa events (380 versus 875 simulated-months) and prolonged coastal inundation (18 versus 98 simulated-months) from the historical to future period is projected (months when both EOF1 and EOF2 projections exceed ±2 SDs; blue circles, historical; red dots, RCP8.5).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4643769&req=5

Figure 4: Observed nonlinear relationship of sea surface height variability and its future change under greenhouse warming.(A) Nonlinear and lagged (8-month) relationship between the first and second EOF projection time series of sea surface height anomalies. The inset shows the correlation coefficient between the first and second EOF projections as a function of lag in months (EOF2 lags EOF1 by 8 months, r = 0.57). The critical value (P > 95%) for the correlation coefficient is 0.39 based on the autocorrelation decay time scales of the projections. The solid green box encloses the prolonged sea level drops for the tropical southwestern Pacific (Taimasa; 13 months observed when both EOF1 and EOF2 projections exceed 2 SDs). Prolonged interannual coastal inundation of similar magnitude and duration has not been observed (dashed green box). (B) Projected future change (RCP8.5 minus historical; color scale) and 20th-century (historical; dashed and solid black contours) multimodel probability of occurrence (%) for the principal variability patterns of sea surface height (EOF2 lags EOF1 by 8 months). Contour intervals are nonlinear: 10−3, 10−2, 10−1 (dashed), and 1 (solid). A kernel smoothing function (normal distribution; bin width of 1 SD) is applied to the bivariate distribution. An increase in Taimasa events (380 versus 875 simulated-months) and prolonged coastal inundation (18 versus 98 simulated-months) from the historical to future period is projected (months when both EOF1 and EOF2 projections exceed ±2 SDs; blue circles, historical; red dots, RCP8.5).
Mentions: The leading two patterns of sea level variability exhibit an asymmetric, nonlinear relationship (Fig. 4A) between PC1 and the 8-month lagged PC2 (Fig. 4A, inset), which is dominated by extreme values in positive PC1 and PC2 that correspond to the El Niño Taimasa events (8). Similar extreme values for La Niña events are absent. The fact that extreme amplitudes of the EOF2 projection lag EOF1 prolongs sea level anomalies in those regions of the Pacific where the EOF patterns are of the same sign (see Fig. 3, insets), potentially enhancing local impacts from El Niño such as low sea level stands and coral die-offs. The opposite pattern combination (EOF1 and EOF2 projections <−2 SDs) has never been observed, but such an event—should one ever occur—would be associated with prolonged coastal inundations in the same regions affected by Taimasa. Such sea level high stands (that is, summing the opposite of the leading patterns of sea level variability shown in Fig. 3, insets) are perceivable should future changes occur in the wind stress curl associated with the orientation of the SPCZ, perhaps influenced by future extreme La Niña events (24) combined with changing mean sea surface temperatures (30). The nonlinear relationship between the zonal and meridional seesaw modes (Fig. 4A) is also reminiscent of similar characteristics for the rainfall variability in the Pacific (18, 23) and equatorial wind stress (fig. S5).

Bottom Line: Global mean sea levels are projected to gradually rise in response to greenhouse warming.Using present-generation coupled climate models forced with increasing greenhouse gas concentrations and subtracting the effect of global mean sea level rise, we find that climate change will enhance El Niño-related sea level extremes, especially in the tropical southwestern Pacific, where very low sea level events, locally known as Taimasa, are projected to double in occurrence.Additionally, and throughout the tropical Pacific, prolonged interannual sea level inundations are also found to become more likely with greenhouse warming and increased frequency of extreme La Niña events, thus exacerbating the coastal impacts of the projected global mean sea level rise.

View Article: PubMed Central - PubMed

Affiliation: International Pacific Research Center, University of Hawai'i at Mānoa, 1680 East-West Road, Honolulu, HI 96822, USA.

ABSTRACT
Global mean sea levels are projected to gradually rise in response to greenhouse warming. However, on shorter time scales, modes of natural climate variability in the Pacific, such as the El Niño-Southern Oscillation (ENSO), can affect regional sea level variability and extremes, with considerable impacts on coastal ecosystems and island nations. How these shorter-term sea level fluctuations will change in association with a projected increase in extreme El Niño and its atmospheric variability remains unknown. Using present-generation coupled climate models forced with increasing greenhouse gas concentrations and subtracting the effect of global mean sea level rise, we find that climate change will enhance El Niño-related sea level extremes, especially in the tropical southwestern Pacific, where very low sea level events, locally known as Taimasa, are projected to double in occurrence. Additionally, and throughout the tropical Pacific, prolonged interannual sea level inundations are also found to become more likely with greenhouse warming and increased frequency of extreme La Niña events, thus exacerbating the coastal impacts of the projected global mean sea level rise.

No MeSH data available.


Related in: MedlinePlus