NDVI anomaly patterns over Africa during the 1997/98 ENSO warm event

Normalized Difference Vegetation Index (NDVI) departure patterns for Africa during the 1997/98 El Niño/Southern Oscillation (ENSO) warm event show two dominant patterns. Over equatorial Eastern Africa, above normal NDVI anomalies persisted from October 1997 through the normal dry season (December-February) and into the long rains season in March-May. Over Southern Africa the spatial NDVI anomaly shows a dry western half and a relatively greener than normal eastern half. Correlations between the temporal NDVI anomalies with ENSO indices shows that the anomalous conditions over Eastern Africa were a direct result of anomalous warming of sea surface temperatures (～+3°C) in the western equatorial Indian Ocean (WIO) and a lagged response to the warming in the eastern Pacific Ocean (+4°C). We suggest that this anomalous warming of the WIO and the equatorial eastern Atlantic Ocean basin dampened the normal severe drought response pattern over Southern Africa where mild drought conditions were experienced. The overall continental response pattern shows a meridional dipole pattern, with above normal NDVI straddling the equator between 10° N and 10° S and normal to slightly below normal NDVI south of 15° S, predominantly over south-western Africa.     

ENSO drought onset prediction in northeast Brazil using NDVI

El Niño Southern Oscillation (ENSO) indices and satellite-recorded Normalized Difference Vegetation Index (NDVI) were used to construct a drought onset prediction model for northeast Brazil (NEB) using a multiple linear regression technique. Monthly NDVI and ENSO indices anomaly data for the period January 1981 to December 1993 were used to develop the model, while those of 1951 to 1998 were used to simulate the NDVI anomaly time series for model validation. Three different regression models were constructed using the NDVI anomaly as dependent variable and various ENSO indices anomalies including: Sea Surface Temperature in the Pacific Ocean area (5°N-5°S and 120°W-170°W, called Niño3.4), Southern Oscillation Index (SOI), North Atlantic Sea Surface Temperature (NATL), South Atlantic Sea Surface Temperature (SATL) and Dipole 2 (DIP2=SATL-NATL), as independent variables. Model 1 was constructed using 12-month NDVI data while Models 2 and 3 used data from only four months (September to December). The results showed that R 2 values of 0.38, 0.62 and 0.79 at a significance level of 1% were obtained for Model 1, Model 2 and Model 3 respectively. Simulated NDVI anomaly values agreed quite well with observed values for all three models but Model 3 had a better intensity estimate. The simulated dynamic evolution of the NDVI anomaly of 1951 to 1998 showed that the predicted NDVI anomalies coincided with historical ENSO induced drought events reported in the literature. It is concluded that the use of satellite-recorded NDVI instead of rainfall data improved the correlation with ENSO indices. Drought onset Model 3, based on the dataset with high anomaly values of NDVI and ENSO indices, predicted drought onset in NEB four months before its occurrence with reasonable success (68%). Combined use of ENSO indices and NDVI inferred drought may provide a better alternative to the construction of an ENSO drought onset prediction model for other regions. Further studies will be carried out to investigate the ENSO drought and flood onsets in the southeastern South America.     

Strong 2015–2016 El Niño and implication to global ecosystems from space data

During 2015, sea surface temperature (SST) in the central tropical Pacific (TP) was warmer than normal, what indicated about the potential for the development of El Niño Southern Oscillation (ENSO). By December 2015, El Niño intensified when SST anomaly in the Niño-3.4 tropical Pacific area reached +2.9 °C, which indicated about the strongest event of the past 36 years. El Niño normally impacts weather, ecosystems, and socioeconomics (agriculture, fisheries, energy, human health, water resource etc.) on all continents. However, the current El Niño is much stronger than the recent strong 1997–1998 event. Therefore, this paper investigates how the strength of El Niño impacts world ecosystems and which areas are affected. The vegetation health (VH) method and 36-year of its data have been used as the criteria of the impact. Specifically, the paper investigates VH-ENSO teleconnection, focusing on estimation of vegetation response to El Niño intensity and transition of the impact from boreal winter to spring and summer. Two types of ecosystem response were identified. In boreal winter, ecosystems of northern South America, southern Africa, eastern Australia, and Southeast Asia experienced strong vegetation stress, which will negatively affect agriculture, energy, and water resources. In Argentina, southeastern USA and the Horn of Africa ecosystem response is opposite. One of the worst disasters associated with ENSO is drought. The advantages of this study are in derivation of vegetation response to moisture, thermal, and combined conditions including an early detection of drought-related stress. For the first time, ENSO impact was evaluated based on all events with |SSTa|> 0.5 ºC and >2.0 ºC. The current strong El Niño has already triggered drought in Brazil, southern Africa, southeastern Asia, and eastern Australia during December–February. Such conditions will be transitioned from boreal winter to spring but not to summer 2016, except for two regions: northern Brazil and southeastern Asia.     

Exploring relationships between ENSO and vegetation vigour in the south-east USA using AVHRR data

This research explores the relationship between El Nino/Southern Oscillation (ENSO), captured by equatorial Pacific Ocean Sea Surface Temperature (SST), and interannual variation in vegetation vigour in the southeast USA, captured by Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI), for the period 1982-1992. The moving average and 'baseline' methods (anomaly from the long term mean) were used to extract interannual patterns in the NDVI signature for croplands, deciduous forests and evergreen forests. The ENSO cycle was measured using mean SST anomalies and the percentage of SST cells above certain threshold values (e.g. 1.0° C above the long term mean). The baseline method indicated a weak, yet persistent, negative correlation between ENSO warm phase events and vegetation vigour in the south-east USA. The moving average method yielded similar results but produced higher correlation values (-0.45 to-0.76, significant at the 0.01 level). Use of the 2.0° C threshold SST anomaly was found to yield the highest correlation values as it captures not only the presence but also the intensity of ENSO warm phase events. These results indicate that there is a clear and recognizable, though inconsistent, relationship between ENSO and vegetation vigour in the south-east USA.     

A classified El Niño index using AVHRR remote-sensing SST data

A process-orientated El Niño index (PEI) is constructed to determine the detailed classification of two major types of El Niño events during 1985–2009 from remote-sensing monthly sea surface temperature (SST) anomaly data sets. Four revised Niño regions are defined in the tropical Pacific, and the index uses SST anomalies and their duration in each region. Based on their varying evolution, the index allows eastern Pacific (EP) El Niño events to be either weak or strong EP type, and central Pacific (CP) El Niño events to be either weak CP, strong CP, or mixed EPCP type. The El Niño types identified by this index are compared to those obtained using previously published methods, and the differences are examined and discussed. The results suggest that the PEI is optimal for monitoring El Niño events of weaker amplitude and shorter duration. The PEI is focused on the development process of El Niño events, providing a novel perspective for classifying El Niño types. Analysis of the SST evolution of the El Niño events identified here reveals several misclassifications in previous studies, stressing the disadvantage of relying solely on single areas or short time periods. Existing EP and CP El Niño events in the study period were reclassified by the PEI into weak, strong, and mixed events. The listing of El Niño types produced here can be used for selecting El Niño events for further study of their dynamics and climatic impacts.     

Two types of El Niño and extratropical sea-level pressure variations

This study applies the nonlinear canonical correlation analysis (NLCCA) to explore the nonlinear relationship between the sea-level pressure (SLP) anomalies over the extratropical North Pacific and sea surface temperature (SST) anomalies in the tropical Pacific during 1985–2009. Our results suggest that the asymmetry between the warm eastern Pacific (EP) El Niño–Aleutian Low mode and the cool EP La Niña–anti-phase of the Aleutian Low mode is exhibited in the first NLCCA mode. Nonlinearity of the first NLCCA SST field is enhanced after 1998, and vice versa for the SLP field. The second NLCCA SST mode reveals weak nonlinearity representing the nonlinear central tropical Pacific (CP) El Niño–CP La Niña modes, while the second SLP field depicts the North Pacific Oscillation and anti-phase with the Aleutian Low phases. The nonlinearity of the second SST and SLP NLCCA modes is found to decrease gradually with time. During 1985–1997, the SST field exhibits linearity, while the SLP field shows weak nonlinearity. During 1997–2009, the SST and SLP fields both display weak linearity. Nonlinearity between the extratropical SLP and SST fields is further weakened from the first period. The Aleutian Low pattern could be excited by both EP and CP El Niños. Moreover, the CP El Niños have more connections with the North Pacific Oscillation state rather than the EP El Niños. Conclusively, this study reveals the asymmetric modes between the SLP and SST by the nonlinear method, and contributes to the understanding of the extratropical SLP variability response to two types El Niño events.     

Comparative study of the 1982–1983 and 1997–1998 El Niño events over different types of vegetation in South America

This work presents results which help to understand the behaviour of the Normalized Difference Vegetation Index (NDVI) anomalies over the South America continent during the two strongest El Niño events of the last century (1982–1983 and 1997–1998). The data used are parts of a long-term series (July 1981 to December 1999) of calibrated NDVI data derived from National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA AVHRR) datasets. Special emphasis has been given to the analysis of the response of the major Brazilian vegetation types. This paper introduces an approach that enhances NDVI anomalies relative to the long-term climatology of the region. We find a negative NDVI anomaly for most of the region during the 1982–1983 event, whereas for the 1997–1998 event positive NDVI anomalies were observed over most regions. Only the ‘Nordeste’ region showed a similar vegetation response for both events. We identify three possible factors that may play a role in the different NDVI responses to the two El Niño events. Firstly, poor intercalibration of sensors may account for some, but not all of the differences. Secondly the response of the vegetation may depend upon the climate conditions prior to the El Niño events. Thirdly, the difference in the onset date and the duration of the mature phase of the two El Niño events, associated with very different Atlantic surface temperatures are shown to have dynamical consequences which may impact upon the vegetation.     

Interannual variability of NDVI over Africa and its relation to El Niño/Southern Oscillation

The array of Normalized Difference Vegetation Index (NDVI) products now being derived from satellite imagery open up new opportunities for the study of short and long-term variability in climate. Using a time series analysis procedure based on the Principal Components transform, and a sequence of monthly Advanced Very High Resolution Radiometer (AVHRR)-derived NDVI imagery from 1986 through 1990, we examine trends in variability of vegetation greenness for Africa for evidence of climatic trends. In addition to the anticipated seasonal trends, we identify signals of interannual variability. The most readily identified is one that periodically affects Southern Africa. It is shown that the temporal loadings for this component exhibit a very strong relationship with the El Nino/Southern Oscillation (ENSO) Index derived from atmospheric pressure patterns in the Pacific, Pacific sea surface temperature (SST) anomalies, and with anomalous Outgoing Longwave Radiation (OLR). However, we have also detected a second interannual variation, affecting most particularly East Africa and the Sahel, that does not exhibit a consistent ENSO relationship. The results show the teleconnection patterns between climatic conditions in the Pacific Ocean basin and vegetation conditions at specific regional locations over Africa. The comprehensive spatial character and high temporal resolution of these data offer exciting prospects for deriving a land surface index of ENSO and mapping the impacts of ENSO activity at continental scale. This study illustrates that vegetation reflectance data derived from polar orbiting satellites can serve as good proxy for the study of interannual climate variability.     

Interannual variations in vegetation activities and climate variability caused by ENSO in tropical rainforests

Interannual variations in terrestrial carbon cycle over tropical rainforests affect the global carbon cycle. Terrestrial ecosystem models show the interannual relationship between climate changes due to El Niño‐Southern Oscillation (ENSO) and net primary production over tropical rainforests. However, we need an independent analysis using satellite‐based vegetation index and climate parameters. In the present study, we extracted the ENSO‐related interannual variations from time‐series in Normalized Difference Vegetation Index (NDVI) and climate data from 1981 to 2000, and analysed their relevance. We detected relationships among NDVI, ENSO, and climate parameters from long‐term data with negative NDVI–ENSO, NDVI–temperature, and positive NDVI–precipitation relations. These correlations suggest that interannual variability in vegetation activities over tropical rainforests could be extracted from NDVI time‐series despite noise components in NDVI data, and that interannual changes in precipitation and temperature caused by ENSO play a more important role in vegetation activities over tropical rainforests than in incoming surface solar radiation.     

Seasonal evolution of the interannual variability of chlorophyll-a concentration and its forcing factors in the northwestern Pacific from 1998 to 2010

The northwestern Pacific Ocean is a complex region with significant biological spatial variations on a seasonal timescale. To investigate the joint variation patterns on both seasonal and interannual timescales, a season-reliant empirical orthogonal function (S-EOF) analysis was applied to seasonal mean chlorophyll-a concentration (chl-a) anomalies in the northwestern Pacific Ocean during the period 1998–2010. The first two dominant modes accounted for nearly 31% of the total interannual variance, with the second S-EOF mode (S-EOF2) lagging behind the first S-EOF mode (S-EOF1) by one year. S-EOF1 featured a strong variation pattern to the north of 30° N, with maximum chl-a in winter and minimum chl-a in summer. However, S-EOF2 indicated an opposite seasonally evolving pattern compared with S-EOF1, with chl-a increasing along the Kuroshio and extension current from boreal winter to autumn. Both these modes revealed significant relationships with climate-related indices. The two modes corresponded to the central Pacific (CP) La Niña developing episodes and the turnaround from eastern Pacific (EP) La Niña to CP El Niño, respectively. Both modes were associated with the cold phase of the Pacific Decadal Oscillation, which played an important role in prolonging the impact of the El Niño/Southern Oscillation on chl-a seasonal evolution from 1998 to 2010. In addition, we discuss the possible factors dominating chl-a seasonal variation, in terms of the subregions of the northwestern Pacific Ocean. In the subtropical northwestern Pacific Ocean (15° N – 30° N), the chl-a growth was primarily nutrient-limited, whereas in the mid-latitude northwestern Pacific Ocean (35° N – 50° N), the chl-a growth was mainly light-limited.     

Interannual variations in global SST deviations through SMMR from 1978 to 1987

We study variability of global sea surface temperature (SST) utilizing the data of scanning multichannel microwave radiometer (SMMR) on board the NASA Nimbus 7 satellite from 1978 to 1987. First, we model, and then remove from the SMMR SST data, the seasonal cycle by using an intercept, a trend and first five harmonics of the annual cycle to fit the data at each grid point by the method of least squares. A general negative nine‐year trend was observed. In order to analyse the deviations in the global SSTs, we calculate and remove zonally averaged temperatures. We then show Hoffmueller diagrams for the deviations along paths in different oceanic regions over the globe. These paths include a quadrangle in the south Pacific and paths in the north Pacific, Atlantic and along the equatorial Pacific. Both 1983 and 1987 El Niño events as well as the 1984–85 La Niña event are clearly depicted. During these events, the SSTs in the equatorial Pacific and Atlantic are completely out of phase. We also demonstrate spatial propagation of SST waves over interannual scales. In particular, a wave of a period of about 3–4 years following the North Pacific Current will be shown.     

Galapagos indicator of El Niño using monthly SST from NASA Giovanni system

One geographical point could be sufficient to track El Niño Southern Oscillation (ENSO). This paper describes an approach to such tracking based on environmental modeling of sea surface temperature (SST). The key model of the approach is the most anomalous indicator of SST as a point near Isabella Island, Galapagos. This point can be computed using monthly SST data from NASA Giovanni system. Comparison with most popular indices demonstrates that such Galapagos indicator can clear indicate both El Niño and La Niña events.     

Interannual variability of convective activity over the tropical Indian Ocean during the El Niño/La Niña events

Convection over the tropical Indian Ocean is important to the global and regional climate. This study presents the monthly climatology of convection, inferred from the outgoing longwave radiation (OLR), over the tropical Indian Ocean. We also examine the impact of El Niño/La Niña events on the convection pattern and how variations in convection over the domain influence the spatial rainfall distribution over India. We used 35 recent years (1974–2008) of satellite-derived OLR over the area, the occurrence of El Niño/La Niña events and high resolution grid point rainfall data over India. The most prominent feature of the annual cycle of OLR over the domain is the movements of convection from south-east to north and north-west during the winter to the summer monsoon season. This feature represents the movement of the inter-tropical convergence zone (ITCZ). The climatology of OLR during the winter months (December–February) over the domain is characterized by high subsidence over central India with a decrease of OLR values towards the north and south. Moderate convection is also seen over the Himalayan Range and the south-east Indian Ocean. In contrast, during the summer (June–September) the OLR pattern indicates deep convection along the monsoon trough and over central India, with subsidence over the extreme north-west desert region. The annual march of convection over the Arabian Sea and Bay of Bengal sector shows that the Arabian Sea has a limited role, compared to the Bay of Bengal, in the annual cycle of the convection over the tropical Indian Ocean. The composite OLR anomalies for the El Niño cases during the summer monsoon season show suppressed convection over all of India and moderate convection over the central equatorial Indian Ocean and over the northern part of the Bay of Bengal. Meanwhile in La Niña events the OLR pattern is nearly opposite to the El Niño case, with deep convection over entire Indian region and adjoining seas and subsidence over the northern Bay of Bengal and extreme north-west region. The spatial variability of the 1°?×?1° summer monsoon rainfall data over India is also examined during El Niño/La Niña events. The results show that rainfall of the summer monsoon season over the southern peninsular of India and some parts of central India are badly affected during El Niño cases, while the region lying along the monsoon trough and the west coast of India have received good amounts of rainfall. This spatial seasonal summer monsoon rainfall distribution pattern seems to average out the influence of El Niño events on total summer monsoon rainfall over India. It seems that, in El Niño events, the convection pattern over the Bay of Bengal remains unaffected during summer monsoon months and thus this region plays an important role in giving good summer monsoon rainfall over the northern part of India, which dilutes the influence of El Niño on seasonal scale summer monsoon rainfall over India. These results are also confirmed by using a monthly bias-corrected OLR dataset.     

Association between ENSO and extremes in total ozone content over northern India

Using daily station total ozone column (TOC) data from the Total Ozone Mapping Spectrometer (TOMS) onboard the Nimbus-7 satellite, an association between the El Niño–Southern Oscillation (ENSO) and extremes in TOC content has been revealed during the period 1979–1993 over northern India in the winter season. From lag-simultaneous correlations of extremes in ozone with Niño 3.4 sea surface temperatures (SSTs), it is seen that, during this season, the highest TOC values show a strong positive relationship at the beginning of the preceding year with the occurrence of the highest values for all the stations. A weak relationship is observed up to the month of July and its sign is then reversed. The negative but weak relationship continues until the occurrence of the event, becoming positive again afterwards. On the contrary, the occurrence of the lowest values shows opposite features. The analysis indicates that the increase in SSTs during the first half of the preceding year is favourable for an increase in the highest values occurring over different stations while the increase in SSTs during the latter half of the preceding year is favourable for an increase in the lowest values of ozone. The lag-simultaneous correlations of the low/high ozone days and the mean TOC values occurring during the winter season also suggest a significant positive relationship for the frequency of the high ozone days at the beginning of the preceding year, becoming weaker as time progresses. Although both features show that the relationship is statistically significant for only a few months of the preceding year, it gives a broad indication of the association between ENSO and the extremes in the TOC amount in addition to local/geographical factors.     

Interannual waves in the sea surface temperatures of the Pacific Ocean

Various oscillatory modes of sea surface temperatures (SSTs) observed over a period of 8.8 years with the NASA Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) and for 13 years with the NOAA Advanced Very High Resolution Radiometer (AVHRR), the latter sensing in the thermal infrared band, are described for the Pacific Ocean. The various modes are isolated by a combination of techniques designed also to accommodate non-stationary phenomena. After detrending and removing the seasonal cycle from each grid map element of the data, singular value decomposition (SVD) is used to separate the data into spatial and temporal parts to facilitate the modal analysis. Empirical Mode Decomposition is then used to separate the temporal parts of the data into approximately seven intrinsic modal functions (IMFs) for the temporal parts of the first five principal components (PCs) resulting from the SVD. A filtered time sequence of SST grids is then obtained by selecting IMFs with periods longer than 1.5 years and then reconstructing the SST grid maps from the filtered PCs. The time sequence of SMMR SSTs in the Pacific Ocean shows El Niño Southern Oscillation (ENSO) oscillations not only along the Equator, but also in both the North and South Pacific, with, in fact, even larger amplitudes than along the Equator. A similar analysis was applied to the SST record from the AVHRR instrument. During the period of overlap with the SMMR record, similarities occur in the equatorial region, but the records are by no means identical. The AVHRR SSTs do not show any strong oscillations in the South Pacific.     

Sea surface temperature simulation and forecast

Unconventional computing of sea surface temperature (SST) was once featured by NASA as a unique merger of science and art. Our approach led to a discovery that just one geographical point could be sufficient to track global anomalies of SST based on El Niño Southern Oscillation (ENSO). Such single point in the Pacific Ocean off of the island of Isabella in the Galapagos Islands was named the Galapagos indicator. Now we show that a single point in the Baltic Sea off of the coast of Göteborg could be also sufficient to track ENSO. We propose to name it the Baltic indicator. We also demonstrate that two crisis falls of oil price in 2008 and 2014 followed just after the local maximums of Baltic indicator. However, Baltic and Galapagos indicators do not show any evident trend in settling the global warming from the beginning of this century.     

Remote sensing of the Indo-Pacific region: ocean colour,sea level,winds and sea surface temperatures

The 1997–1998 ENSO (El Niño-Southern Oscillation) was not only the largest event of the century but also the most comprehensively observed. Satellite data were employed for ocean colour, sea level, winds, sea surface temperature (SST), and outgoing longwave radiation (OLR) were used to describe the response of the surface marine ecosystem associated with the ENSO event. Some of the large-scale anomalies in ocean colour include elevated biological activity to the north of the Equator in the Pacific coincident with lower sea levels associated with the classic ENSO-horseshoe pattern ecosystem response to the anomalous upwelling in the eastern Indian Ocean caused by the 1997–1998 dipole event, and the dramatic eastward propagating feature in the Equatorial Pacific in response to the La Niña dynamics. Ocean general circulation model (OGCM) experiments show that capturing the high-frequency wind changes is crucial for simulating the La Niña and the coupled biological–physical model (OBGCM) runs clearly show that higher frequency winds are also important for capturing the mean upwelling and nutrient supply into the euphotic zone. Thus, the QuickSCAT winds are expected to play a major role in ecosystem modelling in the future. This study shows the utility of satellite data for understanding not only ocean circulation but also the coupled ecosystem variability. Morcover, it is also shown that spatio-temporal resolution of the satellite winds will directly affect the accuracy of oceanic and ecosystem simulations.     

Changing patterns of global‐scale vegetation photosynthesis, 1982–1999

The primary objective of this research was to assess changes in global vegetation photosynthesis between 1982 and 1999. Global‐scale Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data from the Pathfinder AVHRR Land (PAL) and Global Inventory Modeling and Mapping Studies (GIMMS) datasets were analysed for 96% of the non‐Antarctic land area of the Earth. The results showed that between 1982 and 1999 over 30% of the Earth's land surface increased and less than 5% decreased in annual average photosynthesis greater than 4%. Although both the PAL and GIMMS datasets produced broadly similar patterns of change, there were distinct differences between the two datasets. Changes in vegetation photosynthesis were occurring in spatial clusters across the globe and were being driven by climate change, El Niño–Southern Oscillation (ENSO) events and human activity.     

Analysis of teleconnections between AVHRR-based sea surface temperature and vegetation productivity in the semi-arid Sahel

Vegetation productivity across the Sahel is known to be affected by a variety of global sea surface temperature (SST) patterns. Often climate indices are used to relate Sahelian vegetation variability to large-scale ocean-atmosphere phenomena. However, previous research findings reporting on the Sahelian vegetation response to climate indices have been inconsistent and contradictory, which could partly be caused by the variations in spatial extent/definitions of climate indices and size of the region studied. The aim of this study was to analyze the linkage between climate indices, pixel-wise spatio-temporal patterns of global sea surface temperature and the Sahelian vegetation dynamics for 1982-2007. We stratified the Sahel into five subregions to account for the longitudinal variability in rainfall. We found significant correlations between climate indices and the Normalized Difference Vegetation Index (NDVI) in the Sahel, however with different magnitudes in terms of strength for the western, central and eastern Sahel. Also the correlations based on NDVI and global SST anomalies revealed the same East-West gradient, with a stronger association for the western than the eastern Sahel. Warmer than average SSTs throughout the Mediterranean basin seem to be associated with enhanced greenness over the central Sahel whereas colder than average SSTs in the Pacific and warmer than average SSTs in the eastern Atlantic were related to increased greenness in the most western Sahel. Accordingly, we achieved high correlations for SSTs of oceanic basins which are geographically associated to the climate indices yet by far not always these patterns were coherent. The detected SST-NDVI patterns could provide the basis to develop new means for improved forecasts in particular of the western Sahelian vegetation productivity.     

Abnormal features of the Pacific wind system during the 1997-1998 El Niño

The 1997-1998 El Niño, the strongest in recorded history, manifested itself with a number of unusual features associated with the Pacific wind system. These features include: (1) an annual cycle of an east-west migration of a weakened wind speed zone between 2° N-9° N; (2) an asymmetric see-saw process of trade wind variations between the two hemispheres in terms of relative intensity and central position; and (3) an 18-month cycle of meridional oscillations of the Pacific doldrums and trade wind belts. In addition, the commonly-used argument of trade wind relaxation in association with El Niños appears to be partly introduced, at least for the present case, by the 'tilt effect' of the Pacific zonal winds. These novel findings, revealed by the newly available multi-year TOPEX altimeter data, may help to improve existing theories on El Niño formation, and may also contribute to its future prediction.