Application of altimeter observation to El Niño prediction

A new version of the Lamont forecast model is used to assess the impact of TOPEX/POSEIDON altimeter data on predicting short-term climate change, with emphasis on the 1997/98 El Niño and subsequent La Niña. As compared to forecasts initialized with only wind data, the model's predictive accuracy was improved when the altimeter sea level data are used for model initialization. This is due to the effectiveness of sea level data in correcting the model ocean state. For this particular application, the effect of altimeter sea level observations is comparable to that of tide gauge measurements.     

A nonlinear time series model of El Niño

A smooth transition autoregressive model is estimated for the Southern Oscillation Index, an index commonly used as a measure of El Niño events. Using standard measures there is no indication of nonstationarity in the index. A logistic smooth transition autoregressive model describes the most turbulent periods in the data (these correspond to El Niño events) better than a linear autoregressive model. The estimated nonlinear model passes a battery of diagnostic tests. A generalised impulse response function indicates local instability, but as deterministic extrapolation from the estimated model converges, the nonlinear model may still be useful for forecasting the El Niño Southern Oscillation a few months ahead.     

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.     

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.     

Effects of El Niño on spring phenology of the highest mountain in north-east Asia

Normalized difference vegetation index (NDVI) data on the highest mountain in north-east Asia were analysed to understand their temporal variability and response to large-scale El Niño–Southern Oscillation (ENSO) events. We demonstrated that El Niño events played an important role in determining the phenology conditions in the Mt Baekdu area in north-east Asia. The analysis confirmed that the onset of phenological spring was earlier during ENSO years. This was evident from a negative trend of about??16 days for each increase of 1 in the ENSO index in year-to-year variations in spring timing and those in ENSO magnitudes. Over two decades, the phenological phases were negatively correlated with air temperature variations under atmospheric warming at the mountain. However, such changes in NDVI are not likely to be affected by changes in local precipitation, as inferred from the analysis of forest types in this area. On the basis of NDVI changes during ENSO years, the results of this study emphasized the importance of the elevation effect and forest types on the ecological response. Moreover, we addressed a significant remote connection between local phenology at the highest mountain in north-east Asia and large-scale atmospheric and oceanic phenomena.     

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.     

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.     

Time-series analysis of chlorophyll-a,sea surface temperature,and sea surface height anomalies during 2003–2014 with special reference to El Niño,La Niña,and Indian Ocean Dipole (IOD) Years

The present study was carried out to find the variability of chlorophyll-a (chl-a) concentration, sea surface temperature (SST), and sea surface height anomalies (SSHa) during 2003–2014, covering the Bay of Bengal (BoB) and Arabian Sea (AS) waters. These parameters were linked with El Niño, La Niña, and Indian Ocean Dipole (IOD) years. The observed results during 2003–2014 were evaluated and it was found that the monthly mean value for 12-year data ranged as follows: chl-a (0.11–0.46 mg m^?3), SST (27–31 °C), and SSHa (?0.2 to 20 cm). The annual mean range of chl-a for 12-year data was 0.1–0.23 mg m^?3, the SST range was 27–28 °C, and the SSHa range was 2.14–13.91 cm. It has been observed that with the SST range of 27–28 °C and the SSHa range of 7–9 cm, the chl-a concentration enhanced to 0.20–0.23 mg m^?3. With a higher SST range of 28–29 °C and with a positive SSHa range of 11–14 cm, the chl-a concentration appeared to be low (0.17–0.18 mgm^?3). During normal years, SSHa was positive with the >5 to <10 cm range during the months of April–June, which coincided with an increase in SST, >2 to <4 °C. During the normal years, SSHa (>?0.2 to a concentration (>0.3 to <0.5 mg m^?3) was noticed during December–February in the BoB and AS. Compared to the BoB chl-a range (<0.4 mg m^?3), a high chl-a concentration was observed in AS (>0.4 mg m^?3). However, during the phenomenon years, the study area had experienced low chl-a (<0.2 mg m^?3), high SST (>5 °C), and more positive SSHa (>10 to <20 cm) during January–March and October–December in AS and BoB. The present study infers that a positive IOD leads to low chl-a concentration (<2 mg m^?3) and low primary productivity in AS. El Niño caused the down-welling process, it results in a low chl-a concentration (<1 mg m^?3) in BoB and AS. La Niña caused the upwelling process, and it results in a high chl-a concentration (>2.0 mg m^?3) in BoB and AS. In the recent past years (2003–2014), the intensity and frequency of El Niño, La Niña, and IOD have been increasing, evidenced with few studies, and have impacts on the Indian Ocean climate. Therefore, the influences of the relative changes of these phenomena on the BoB and AS need to be understood for productivity assessment and ocean state monitoring.     

Change detection using remote sensing in a reef environment of the UAE during the extreme event of El Niño 2015–2016

ABSTRACT

Coral reefs of the United Arab Emirates (UAE) are living in the world’s hottest sea. Recently, corals harbouring Symbiodinium thermophilum, a thermotolerant microalgae, were found to be prevalent among UAE reefs and were reported to endure extreme sea-surface temperatures. Late 2015–early 2016 was marked with the strongest El Niño on record worldwide, which caused massive coral bleaching (loss of symbiotic microalgae from reef-building corals). In September 2015, the waters flanking UAE coasts were identified to be among the areas facing a thermal stress reaching its highest level liable to cause massive coral bleaching. However, the effect of this thermal stress on UAE corals remained largely unknown. Here, multi-temporal DubaiSat-2 satellite images were used to show that changes in the reef environment of Dalma Island, UAE, between 2014 and 2016, occurred in macroalgae-dominant habitats, whereas live corals remained unaltered. Furthermore, extending the study to a larger area helped in discovering a continuum of live and pristine corals, which was not reported or studied before. While sea-surface temperature anomalies of 1°C were reported to significantly damage coral reefs around the world, the live coral habitat was observed to exhibit no-change despite four consecutive months of +2°C to 3°C anomalies reported during the study period. These findings point to the tolerance of UAE live corals faced with extreme climate conditions.     

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 cirrus clouds in the tropics in El Niño Southern Oscillation (ENSO) regions based on International Satellite Cloud Climatology Project (ISCCP) satellite data

The percentage of the interannual variance of cirrus clouds, explained by the variability of the El Niño Southern Oscillation (ENSO), the Quasi-biennial Oscillation (QBO) and solar activity over the tropics, is presented in this article. Analysis is focused on the eastern and western tropical Pacific Ocean, which is strongly affected by the ENSO. It is shown that over the eastern tropical Pacific Ocean, the amplitude of the ENSO in cirrus-cloud cover (CCC) is about 8.0%. The amplitude of the annual cycle is about 0.8% and the amplitudes of the QBO, solar cycle and long-term trends are the order of 1.0%, 0.1% and 0.3%, respectively. Using as an index of convective activity in the upper troposphere the vertical velocities at 300 hPa, we have calculated a vertical velocity related to cloud component. It is shown that the total contribution, from all related cloud components examined explains about 65% of the variance in cirrus clouds over the eastern Pacific and about 50% of the variance in cirrus clouds over its western part.