HR: 09:45h
AN: OS31A-08    [Abstracts]
TI: Climate Trend Detection using Sea-Surface Temperature Data-sets from the (A)ATSR and AVHRR Space Sensors.
AU: * Llewellyn-Jones, D T
EM: dlj1@le.ac.uk
AF: University of Leicester, Space Research Centre Department of Physics & Astronomy University of Leicester University Road , LEICESTER, Lei LE1 7RH, United Kingdom
AU: Corlett, G K
EM: gkc1@le.ac.uk
AF: University of Leicester, Space Research Centre Department of Physics & Astronomy University of Leicester University Road , LEICESTER, Lei LE1 7RH, United Kingdom
AU: Remedios, J J
EM: jjr8@le.ac.uk
AF: University of Leicester, Space Research Centre Department of Physics & Astronomy University of Leicester University Road , LEICESTER, Lei LE1 7RH, United Kingdom
AU: Noyes, E J
EM: ejn2@le.ac.uk
AF: University of Leicester, Space Research Centre Department of Physics & Astronomy University of Leicester University Road , LEICESTER, Lei LE1 7RH, United Kingdom
AU: Good, S A
EM: simon.good@hotmail.co.uk
AF: University of Leicester, Space Research Centre Department of Physics & Astronomy University of Leicester University Road , LEICESTER, Lei LE1 7RH, United Kingdom
AB: Sea-Surface Temperature (SST) is an important indicator of global change, designated by GCOS as an essential Climate Variable (ECV). The detection of trends in Global SST requires rigorous measurements that are not only global, but also highly accurate and consistent. Space instruments can provide the means to achieve these required attributes in SST data. This paper presents an analysis of 15 years of SST data from two independent data sets, generated from the (A)ATSR and AVHRR series of sensors respectively. The analyses reveal trends of increasing global temperature between 0.13°C to 0.18 °C, per decade, closely matching that expected from some current predictions. A high level of consistency in the results from the two independent observing systems is seen, which gives increased confidence in data from both systems and also enables comparative analyses of the accuracy and stability of both data sets to be carried out. The conclusion is that these satellite SST data-sets provide important means to quantify and explore the processes of climate change. An analysis based upon singular value decomposition, allowing the removal of gross transitory disturbances, notably the El Niño, in order to examine regional areas of change other than the tropical Pacific, is also presented. Interestingly, although El Niño events clearly affect SST globally, they are found to have a non- significant (within error) effect on the calculated trends, which changed by only 0.01 K/decade when the pattern of El Niño and the associated variations was removed from the SST record. Although similar global trends were calculated for these two independent data sets, larger regional differences are noted. Evidence of decreased temperatures after the eruption of Mount Pinatubo in 1991 was also observed. The methodology demonstrated here can be applied to other data-sets, which cover long time-series observations of geophysical observations in order to characterise long-term change.
DE: 1616 Climate variability (1635, 3305, 3309, 4215, 4513)
DE: 1620 Climate dynamics (0429, 3309)
DE: 1635 Oceans (1616, 3305, 4215, 4513)
DE: 1640 Remote sensing (1855)
DE: 4594 Instruments and techniques
SC: Ocean Sciences [OS]
MN: 2007 Joint Assembly