Abstract

AbstractKnowledge of vertical crustal movement is fundamental to quantify absolute sea level changes at tide gauge locations as well as for satellite altimetry calibration validations. While GPS measurements at collocated tide gauge stations fulfill this need, currently only few hundred tide gauge stations are equipped with GPS, and their measurements do not span a long period of time. In the past, several studies addressed this problem by calculating relative and geocentric trends from the tide gauge and satellite altimetry measurements respectively, and then difference the two trends to calculate the rate of changes at the tide gauge stations. However, this approach is suboptimal. This study offers an optimal statistical protocol based on themethod of condition equations with unknown parameters. An example solution demonstrates the proposed mathematical and statistical models’ optimality in estimating vertical crustal movement and its standard error by comparing them with the results of current methods. The proposed model accounts for the effect of autocorrelations in observed tide gauge and satellite altimetry sea level time series, adjusts observed corrections such as inverted barometer effects, and constraints tide gauge and satellite altimeter measurement to close. The new model can accommodate estimating other systematic effects such as pole tides that are not eliminated by differencing.

Highlights

  • Knowledge of vertical motion is fundamental to quantify absolute sea level changes at tide gauge (TG) locations, and for satellite altimetry (SA) calibration validations

  • While global positioning system (GPS) measurements at collocated tide gauge stations ful ll this need, currently only few hundred tide gauge stations are equipped with GPS, and their measurements do not span a long period of time

  • This study o ered an optimal statistical protocol for estimating vertical crustal movement (VCM) at TG stations using TG, SA and Inverted Barometer (IB) time series data using the method of condition equations with unknown parameters

Read more

Summary

Introduction

Knowledge of vertical motion is fundamental to quantify absolute sea level changes at tide gauge (TG) locations, and for satellite altimetry (SA) calibration validations. The following model is used to estimate the linear rate of change in sea level rise hfor both TG and SA time series, ht =ht + h (t − t ) + α cos π PAnnual (t − t ) With this a priori understanding regarding the autocorrelated error properties of the SA and TG time series, the trend model given by Eq (3) can be expressed as, Fig. 5.

Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call