No abstract

Satellite altimetry provides an immensely valuable source of operational significant wave height (Hs) data. Currently, altimeters on board Jason-1 and Envisat provide global Hs observations, available within 3–5 h of real time. In this work, Hs data from these altimeters are validated against in situ buoy data from the National Data Buoy Center (NDBC) and Marine Environmental Data Service (MEDS) buoy networks. Data cover a period of three years for Envisat and more than four years for Jason-1. Collocation criteria of 50 km and 30 min yield 3452 and 2157 collocations for Jason-1 and Envisat, respectively. Jason-1 is found to be in no need of correction, performing well throughout the range of wave heights, although it is notably noisier than Envisat. An overall RMS difference between Jason-1 and buoy data of 0.227 m is found. Envisat has a tendency to overestimate low Hs and underestimate high Hs. A linear correction reduces the RMS difference by 7%, from 0.219 to 0.203 m. In addition to wave height–dependent biases in the altimeter Hs estimate, a wave state–dependent bias is also identified, with steep (smooth) waves producing a negative (positive) bias relative to buoys. A systematic difference in the Hs being reported by MEDS and NDBC buoy networks is also noted. Using the altimeter data as a common reference, it is estimated that MEDS buoys are underestimating Hs relative to NDBC buoys by about 10%.

Almost 5 years after the 26 December 2004 Indian Ocean tragedy, the 10 August 2009 Andaman tsunami demonstrated that accurate forecasting is possible using the tsunami community modeling tool Community Model Interface for Tsunamis (ComMIT). ComMIT is designed for ease of use, and allows dissemination of results to the community while addressing concerns associated with proprietary issues of bathymetry and topography. It uses initial conditions from a precomputed propagation database, has an easy-to-interpret graphical interface, and requires only portable hardware. ComMIT was initially developed for Indian Ocean countries with support from the United Nations Educational, Scientific, and Cultural Organization (UNESCO), the United States Agency for International Development (USAID), and the National Oceanic and Atmospheric Administration (NOAA). To date, more than 60 scientists from 17 countries in the Indian Ocean have been trained and are using it in operational inundation mapping.

A formalism recently developed for determining the effects of sampling errors on objectively smoothed fields constructed from an irregularly sampled dataset is applied to investigate the relative merits of single and multiple satellite altimeter missions. For small smoothing parameters, the expected squared error of smoothed fields of sea surface height (SSH) varies geographically at any particular time and temporally at any particular location. The philosophy proposed here for determining the resolution capability of SSH fields constructed from altimeter data is to identify smoothing parameters that are sufficiently large to satisfy two criteria: 1) the expected squared errors of the estimates of smoothed SSH over the space-time estimation grid must be either spatially and temporally homogeneous to within some a priori specified degree of tolerance or smaller than some a priori specified threshold, and 2) the space-time estimation grid on which smoothed SSH estimates are constructed must satisfy the Nyquist criteria for the wavenumbers and frequencies included in the smoothed fields. The method is illustrated here by adopting a specified tolerance of 10% variability and a nominal expected squared error threshold of 1 cm 2 to determine the resolution capabilities of SSH fields constructed from 10 single and multiple combinations of altimeter measurements by TOPEX/Poseidon, the ERS Earth Resource Satellites, and Geosat. Because of the lack of coordination of the orbit configurations of these satellites (different repeat periods and different orbit inclinations), the mapping resolution capabilities of the combined datasets are not significantly better than those of fields constructed from TOPEX/Poseidon data alone. The benefits of coordinated multiple missions are demonstrated by consideration of several multiple combinations of 10-, 17-, and 35-day orbit configurations.

Long term datasets can be used to create climatologies and underpin return period analysis for engineering design (Ewans and Jonathan, 2020). Observations from in situ instrumentation such as wave buoys and radars can provide accurate data at high temporal resolutions; however, they are sparsely located in the southern hemisphere. Satellite altimeter wave data are