PO.DAAC

The animation illustrates the evolution of sea surface temperature (SST) and sea surface height (SSH) anomalies* (relative to the respective normal state, i.e., seasonal climatology) associated with the 2009-10 El Nino in the Pacific Ocean.  SST and SSH anomalies reflect the heat content in the mixed layer (approximately upper 50 m) and the upper ocean (approximately upper 150 m) respectively. They provide complimentary views of the oceanic signature of climate variability El Nino.

The animation illustrates the evolution of sea surface temperature (SST) and sea surface height (SSH) anomalies (relative to the respective normal state, i.e., seasonal climatology) associated with the 2010-11 La Niña in the Pacific Ocean.  SST and SSH anomalies reflect the heat content in the mixed layer (approximately upper 50 m) and the upper ocean (approximately upper 150 m) respectively.  Warm/cold SST anomalies often are associated with high/low SSH anomalies.

The Multi-Scale Ultra-High Resolution (MUR) Sea Surface Temperature (SST) Data Set combines data from the Advanced Very High Resolution Radiometer (AVHRR), Moderate Imaging Spectroradiometer (MODIS) Terra and Aqua, and Advanced Microwave Spectroradiometer-EOS (AMSR-E) instruments in an optimal way to produce 1 km global maps of SST.  Noticeable in the animation from 1 January 2010 to 31 December 2011 are the high energy regions associated with the Western Boundary Currents of the Gulf Stream and the Kuroshio.  Additionally one can see the major upwelling areas of the worl

The Ocean is essential to life on Earth. Most of Earth's water is stored in the ocean. Although 40 percent of Earth's population lives within, or near coastal regions- the ocean impacts people everywhere. Without the ocean, our planet would be uninhabitable. This animation helps to convey the importance of Earth's oceanic processes as one component of Earth's interrelated systems.

Water is the fundamental ingredient for life on Earth. Looking at our Earth from space, with its vast and deep ocean, it appears as though there is an abundance of water for our use. However, only a small portion of Earth's water is accessible for our needs. How much fresh water exists and where it is stored affects us all. This animation uses Earth science data from a variety of sensors on NASA Earth observing satellites as well as cartoons to describe Earth's water cycle and the continuous movement of water on, above and below the surface of the Earth.

Beginning in 1978 with the first Earth orbiting ocean observing satellite, Seasat, continuing with Geosat, ERS-1,TOPEX/Poseidon, ERS-2, Jason-1, Envisat and Jason-2 missions and looking ahead to the Surface Water and Ocean Topography (SWOT) mission scheduled to launch in 2020, the improvement of the spatial resolution in NASA and partners altimetric missions is dramatic. This animation illustrates this progression of improved data resolution.

Using data from several satellite altimeters, a finer picture of the ever-changing height of the oceans is revealed. Swirling currents called eddies pepper the global ocean. Like small pock-marks in sea surface height, these eddies are found in every major ocean basin. Near the Equator, the eddies give way to fast moving features called Kelvin Waves. When they build up in the Pacific, these waves can usher in a phenomenon known as El Nino, which happens when warm water and high sea levels move into the Eastern Pacific along the Equator.

The Argo Array of profiling floats is the first attempt to monitor the global subsurface ocean temperature and salinity fields in real time. The first floats were deployed in late 1999 and it took another 8 years to reach the global target of 3,000 operating floats delivering data every 10 days. This animation shows daily float locations overlayed on the 150 m depth salinity field from an eddy resolving ocean model. While 3,000 floats seems like a lot, on a daily basis the ocean is still very undersampled.

The IPRC Surface Currents Diagnostic (SCUD) model is used to simulate evolution of debris field, drifting from the shores of Japan, affected by the 11 March 2011 tsunami. The model is on 1/4° grid. Daily surface velocities are diagnosed using the mean dynamic topography, AVISO anomalies of geostrophic velocities and satellite winds. Local coefficients of the model are tunes to best reproduce concurrent velocities of near-surface drifters.