Can Multi-Mission Altimeter Datasets Accurately Measure Long-Term Trends in Wave Height?

A long-duration, multi-mission altimeter dataset is analyzed to determine its accuracy in determining long-term trends in significant wave height. Two calibration methods are investigated: altimeter-buoy calibration and altimeter-altimeter calibration. The altimeter-altimeter approach shows larger positive trends globally, but both approaches are subject to temporal non-homogeneity between altimeter missions. This limits the accuracy of such datasets to approximately +/- 0.2 cm/year in determining trends in significant wave height. The sampling pattern of the altimeters is also investigated to determine if under-sampling impacts the ability of altimeters to measure trends for higher percentiles. It is concluded that, at the 99th percentile level, sampling issues result in a positive bias in values of trend. At lower percentiles (90th and mean), the sampling issues do not bias the trend estimates significantly.

Automated summary

A long-duration, multi-mission altimeter dataset was analyzed to evaluate its accuracy in measuring long-term trends in significant wave height. Two calibration methods were investigated, with the altimeter-altimeter approach showing larger positive trends globally. However, both methods are affected by temporal non-homogeneity between altimeter missions. The study concluded that the accuracy in determining trends in significant wave height is limited to approximately +/- 0.2 cm/year. The sampling pattern of the altimeters was also examined, and it was found that under-sampling can bias trend estimates at the 99th percentile level, but not significantly at lower percentiles (90th and mean).