Satellite Oceanography for Ocean Forecasting
35
2.2.6 Real-time aspects
Real-time aspects are crucial for operational oceanography. Altimeter data (if
required during the mission design) can be acquired and processed in near-real
time (2 days) (e.g. ERS-1I2, Jason-l, ENVISAT). However, the data are less accurate because orbit computation requires environmental parameters which cannot be
obtained in real time. Dedicated processing is thus needed to correct the orbit error,
along with continuous comparison of real-time products with precision delayedtime products to assess accuracy. Results recently obtained with TIP and ERS-2
near-real time data are almost as accurate as with delayed-time data thanks to dedicated processing techniques (Boone and Le Traon, 1997; Cheney et al., 1997). TIP
data are now used in near-real time for El Nifio prediction for which they were
shown to be very useful (Cheney et al., 1997).
2.3 Prospects
Space oceanography provides unique tools for ocean forecasting. Some techniques are very mature (altimetry, SST) and Can be readily used in models. However, new space oceanography missions (e.g. for measuring salinity), and better
sampling of sea level and winds are required. Operationality for space oceanography missions is also not yet guaranteed (as it is for meteorological satellites),
although it is hoped that this may be achieved in the foreseeable future.
In the future, ocean forecasting, through data assimilation, will be an appropriate
and powerful means to assess the impact ofthe satellite (and in-situ) observing systems, to identify gaps and to improve the efficiency/effectiveness ofthe observing
system. A better use of space (and in-situ) data using effective data assimilation
techniques and a better assessment of the ocean observing system components are
among the main objectives of GODAE, the Global Ocean Data Assimilation
Experiment (Smith and Lefebvre, 1997; Le Traon et al., 1999).
35
2.2.6 Real-time aspects
Real-time aspects are crucial for operational oceanography. Altimeter data (if
required during the mission design) can be acquired and processed in near-real
time (2 days) (e.g. ERS-1I2, Jason-l, ENVISAT). However, the data are less accurate because orbit computation requires environmental parameters which cannot be
obtained in real time. Dedicated processing is thus needed to correct the orbit error,
along with continuous comparison of real-time products with precision delayedtime products to assess accuracy. Results recently obtained with TIP and ERS-2
near-real time data are almost as accurate as with delayed-time data thanks to dedicated processing techniques (Boone and Le Traon, 1997; Cheney et al., 1997). TIP
data are now used in near-real time for El Nifio prediction for which they were
shown to be very useful (Cheney et al., 1997).
2.3 Prospects
Space oceanography provides unique tools for ocean forecasting. Some techniques are very mature (altimetry, SST) and Can be readily used in models. However, new space oceanography missions (e.g. for measuring salinity), and better
sampling of sea level and winds are required. Operationality for space oceanography missions is also not yet guaranteed (as it is for meteorological satellites),
although it is hoped that this may be achieved in the foreseeable future.
In the future, ocean forecasting, through data assimilation, will be an appropriate
and powerful means to assess the impact ofthe satellite (and in-situ) observing systems, to identify gaps and to improve the efficiency/effectiveness ofthe observing
system. A better use of space (and in-situ) data using effective data assimilation
techniques and a better assessment of the ocean observing system components are
among the main objectives of GODAE, the Global Ocean Data Assimilation
Experiment (Smith and Lefebvre, 1997; Le Traon et al., 1999).