RESUMO
Proposed in the early 1970's, the Gaia hypothesis suggests that our planet earth has a self-regulating ability to maintain a stable condition for life. Tropical cyclone (TC) is one of the earth's most hazardous disasters; it is intriguing to explore whether 'Gaia-like' processes may exist in nature to regulate TC activities. El Niño can shift the forming position of the Western Pacific typhoons away from land. This shift enables typhoons to travel longer distances over ocean and is known to be a positive process to promote TCs to achieve higher intensity. What is neglected, however, is that there co-exists a negative process. Here we show that during El Niño, typhoons intensify over region undergoing strong ocean subsurface shoaling where upper ocean heat content can drop by 20-50%. This 'worsen' ocean pre-condition can effectively reduce ocean's energy supply for typhoon intensification during typhoon-ocean interaction. We find this an elegant, 'Gaia-like' process demonstrating nature's self-regulating ability. Though during El Niño, typhoons can take advantage of the longer travelling distance over ocean to achieve higher intensity, nature is also providing a damper to partially cancel this positive impact. Without the damper, the situation could be even worse.
RESUMO
Multi-sensor data from different satellites are used to identify an upwelling area in the sea off northeast Taiwan. Sea surface temperature (SST) data derived from infrared and microwave, as well as sea surface height anomaly (SSHA) data derived from satellite altimeters are used for this study. An integration filtering algorithm based on SST data is developed for detecting the cold patch induced by the upwelling. The center of the cold patch is identified by the maximum negative deviation relative to the spatial mean of a SST image within the study area and its climatological mean of each pixel. The boundary of the cold patch is found by the largest SST gradient. The along track SSHA data derived from satellite altimeters are then used to verify the detected cold patch. Applying the detecting algorithm, spatial and temporal characteristics and variations of the cold patch are revealed. The cold patch has an average area of 1.92 × 10(4) km(2). Its occurrence frequencies are high from June to October and reach a peak in July. The mean SST of the cold patch is 23.8 °C. In addition to the annual and the intraseasonal fluctuation with main peak centered at 60 days, the cold patch also has a variation period of about 4.7 years in the interannual timescale. This implies that the Kuroshio variations and long-term and large scale processes playing roles in modifying the cold patch occurrence frequency.
RESUMO
Satellite altimeter data from 1993 to 2005 has been used to analyze the seasonal variation and the interannual variability of upper layer thickness (ULT) in the South China Sea (SCS). Base on in-situ measurements, the ULT is defined as the thickness from the sea surface to the depth of 16°C isotherm which is used to validate the result derived from satellite altimeter data. In comparison with altimeter and in-situ derived ULTs yields a correlation coefficient of 0.92 with a slope of 0.95 and an intercept of 6 m. The basin averaged ULT derived from altimeter is 160 m in winter and 171 m in summer which is similar to the in-situ measurements of 159 m in winter and 175 m in summer. Both results also show similar spatial patterns. It suggests that the sea surface height data derived from satellite sensors are usable for study the variation of ULT in the semi-closed SCS. Furthermore, we also use satellite derived ULT to detect the development of eddy. Interannual variability of two meso-scale cyclonic eddies and one anticyclonic eddy are strongly influenced by El Niño events. In most cases, there are highly positive correlations between ULT and sea surface temperature except the periods of El Niño. During the onset of El Niño event, ULT is deeper when sea surface temperature is lower.
