Multivariate Sea Level Reconstruction for Historical and Near Real-Time Ocean and Climate Monitoring
- (University of Colorado, Boulder)
Long-duration, accurate sea level mapping before the advent of satellite altimetry is needed to differentiate between natural and anthropogenic variations in sea level associated with climate change. Accurately estimating climate signals from sea level maps reconstructed solely by fitting to sea level measured by tide gauges before 1950 is very difficult; however, initial tests of multivariate reconstruction techniques for estimating sea level show significantly improved performance. For example, the combination of in situ sea surface temperature observations and sea level from tide gauges improves estimation of the sea level signals associated with El Niño Southern Oscillation (ENSO) by accurately reconstructing both the canonical Eastern Pacific ENSO and the more recently described Modoki or Central Pacific ENSO variability. The multivariate reconstruction also captures Pacific multidecadal variability, including the Interdecadal Pacific Oscillation (IPO) and Pacific Decadal Oscillation (PDO), that has tentatively been identified as contributing to increased rates of global mean sea level rise in the 1940s and regional sea level rise in the western tropical Pacific in both the 1940s and 1960s. Rates of sea level rise during those historical time periods are comparable to the rates observed over the current altimeter record. In the proposed research program, we will use multivariate reconstruction techniques to combine the best aspects of the modern satellite record with historical ocean observations to produce a gridded sea level record with formal mapping errors spanning 1850 to the present for use by the ocean and climate research communities. From 1993 onward, the gridded product will be estimated using the NASA MEaSUREs Integrated Multi-Mission Altimeter Data for Climate Research produced at NASA GSFC. Near real-time products will be produced from the NASA/JPL OSTM GPS based orbit and SSHA OGDR. The proposed datasets will contribute to scientific studies of seasonal/annual, interannual, and decadal/multidecadal signals in the global ocean identified using the extended sea level data record and analyzed using sea level based historical and near real-time indices for monitoring ocean and climate signals. Our primary scientific objective will focus will be on quantifying the contribution of Pacific-related multidecadal signals to global and regional sea level variations and relating those variations to forcing by other climate variables derived from satellite and in situ observations. The proposed work will support ocean and climate studies utilizing Jason-series mission data, provide historical and near real-time data and data product to support operational applications such as climate monitoring and forecasting, and potentially help with the calibration and validation of the baseline sea level measurements from the Jason-3 mission.