non-ENSO Years Research Articles

Oxygen and irradiance constraints on visual habitat in a changing ocean: The luminoxyscape

Oxygen and irradiance constraints on visual habitat in a changing ocean: The luminoxyscape

Demonstrating the asymmetry of the Indian Ocean Dipole response in regional earth system model of CORDEX-SA

An accurate representation of the Indian Ocean Dipole (IOD) is crucial for the reliable projection of Indian summer monsoon rainfall, making it necessary to improve the understanding of the response of the IOD in the warming climate. For the first time, a high-resolution regional earth system model (RESM) over the CORDEX-SA domain is used to investigate the IOD characteristics. The model performance is evaluated in simulating the IOD and associated mechanism. RESM shows a good resemblance in simulating IOD phases (positive and negative). However, the systematic discrepancy is observed in magnitude. Additionally, RESM well represented the positive IOD's inter-event variability. For example, the stronger event dominated by significant cold anomalies over Sumatra with enhanced westward-extended while a moderate event shows weak cooling confined to the region of Sumatra. Additionally, RESM shows potential to distinguish the ENSO and non-ENSO years with more remarkable skill in representing the spatial pattern of SST over IOD region during non-ESNO years than ENSO years. The RESM realistically simulated the IOD amplitude with greater skill than CMIP5/6 models reported in the earlier studies, indicating reliability towards the projection of the Indian summer monsoon. The weaker IOD-ENSO relationship is caused by producing the more significant number of IOD during non-ENSO years. Despite this reliable fidelity, IOD's slightly earlier peak is driven by the early establishment of low-level equatorial easterly wind. This study provided valuable insight into the IOD's different phases, responsible forcings, and limitations of the RESM in accounting for the role of internal climate variability that can be useful for further improvement in the model physics.

Effect of depth gradient and temperature on Zostera marina vegetative and reproductive phenology in the first year of the 1997–1998 El Niño

Does Zostera marina exhibit phenotypic plasticity, maximizing fitness in traits responding to environmental factors, i.e., depth and temperature? We compared the vegetative and sexual phenology and reproductive effort of Z. marina by analyzing vegetative and reproductive shoot density, biomass, and reproductive stages to determine structural features of vegetative and reproductive shoots from subtidal and intertidal environments in San Quintín Bay, Baja California, a year before and after the 1997–1998 El Niño/Southern Oscillation (ENSO). We found significant differences in vegetative and reproductive biomass between intertidal and subtidal environments driven by temperature differences between ENSO and non-ENSO years. Subtidal plants had lower density of long reproductive shoots and a shorter reproductive cycle. Seed release occurred from May to October in the subtidal environment, and from May to November in the intertidal environment. Maximal recorded values were 219.5 (±45.8) seeds per reproductive shoot in the subtidal environment and 151.3 (±21.5) in the intertidal environment. We observed higher sexual activity and lower vegetative biomass in the intertidal environment, the most stressful environment. Both vegetative and reproductive biomass were affected by the increase in temperature during ENSO, but vegetative and reproductive shoot densities were not affected.

Comparison of seasonal climate in China during the cold and warm phases of ENSO

El Niño-Southern Oscillation (ENSO) events have serious impacts on weather patterns, agriculture and ecosystems, and play an important role in predicting regional and global climate. A 2-tailed Student’s t-test was used to analyze the differences of seasonal air temperature and rainfall between ENSO years (El Niño/La Niña years) and non-ENSO years in China, and the results indicate that summer temperature was lower, and winter, spring and autumn rainfall was higher in El Niño years, while in La Niña years, winter temperature was lower and summer rainfall was higher in China as a whole. There were significant regional differences in seasonal temperature and rainfall between ENSO and non-ENSO years. In El Niño years, summer temperatures in most regions of China were lower than those in non-ENSO years. Summer and autumn rainfall was higher in the mid-lower reaches of the Yangtze River but lower in North China, and winter rainfall was lower in southern China. In La Niña years, winter temperatures were lower in the mid-lower reaches of the Yangtze River and South China, and summer rainfall was higher in Northeast China, North China, the mid-lower reaches of the Yangtze River and Southwest China than those in non-ENSO years. We conclude that the impacts of ENSO on rainfall are more obvious than those on temperature, and the responses of seasonal temperature and rainfall to El Niño are more obvious than those to La Niña events in China.

Does ENSO strongly affect rice yield and water application in Northeast China?

Northeast China (NEC) has recently become one of the largest commercial rice production regions in China. However, the increased production combined with increasingly frequent climate oscillations is severe competing for fresh water with the non-agricultural sectors in this region and is threatening national food security. In this study, the ORYZA (v3) crop model was used to estimate the rice yields and water applications under three management regimes, continuous flooded irrigation (CF), alternate wetting and drying (AWD), and rain-fed (RF), in the full nutrient supply and biotic-stress-free conditions in NEC from 1961 to 2016. The predicted average rice yields in these three production regimes were 12.7, 12.7 and 10.6 t ha−1. El Niño events reduced yields by 2.5% and 2.4% (P < 0.05) in the CF and AWD regimes, respectively, compared with those in Neutral years. The simulated total water application in the CF, AWD and RF regimes were 1437.3, 706.1 and 523.7 mm, respectively. The total water application decreased 50.9% and 63.6% in the AWD and RF regimes compared with the CF regime, respectively. El Niño events decreased water application by 1.7% and 1.2% in the CF and AWD, respectively (P < 0.05). In addition, the sea surface temperature (SST) impacts on rice yield varied among water management regimes in NEC. El Niño events decreased rice yield under CF and AWD, implying that El Niño may hammer rice production in NEC and impact China’s food security in the future. In addition, AWD management significantly decrease rice water application during both ENSO and non-ENSO years and is a water-saving technology for local government and producers to address the challenge of increasing water application from non-agriculture sectors.

Investigating the Interannual Variability of the Boreal Summer Water Vapor Source and Sink over the Tropical Eastern Indian Ocean-Western Pacific

Using the four-times daily and monthly-mean reanalysis datasets of NCEP/NCAR for the 1958 to 2018 period, we investigate the interannual variability of the June-July-August (JJA)–mean water vapor source and sink over the tropical eastern Indian Ocean-Western Pacific (TEIOWP) and the underlying mechanism. It is found that the two major modes (EOF1 and EOF2) of the water vapor source and sink anomalies over the TEIOWP present a southwest-northeast oriented dipole and a southwest-northeast oriented tripole. Specifically, when the western maritime continent shows an anomalous water vapor source, the northwestern Pacific is characterized by anomalous water vapor sink and source in EOF1 and EOF2 modes, respectively. The EOF1 and EOF2 modes are primarily driven by a single and a double meridional cell anomaly, which corresponds to the in-phase and out-of-phase linkage between evaporation anomalies over the western maritime continent and precipitation anomalies over the northwestern Pacific, respectively. Furthermore, the EOF1 mode is regulated by the quick transition of the El Niño-Southern Oscillation (ENSO) phase, whereas the EOF2 mode probably originates from internal atmospheric variability. Considering that the standard deviation of PC1 is much higher during ENSO years than that during non-ENSO years, it is probable that the water source and sink anomalies over the TEIOWP tend to be dominant by EOF1 mode during ENSO years. In contrast, the EOF2 mode may play an important role in the water source and sink anomalies over the TEIOWP during non-ENSO years. Accordingly, the water vapor source and sink anomalies over the TEIOWP may be well predicted based on the ENSO state in the previous December-January-February. These results are useful for understanding the predictability of water vapor source and sink anomalies over the TEIOWP.

VARIABILITY OF CHLOROPHYLL-A DISTRIBUTION AROUND BELITUNG ISLAND WATERS OBSERVED BY AQUA-MODIS SATELLITE DATA

&lt;p&gt;Belitung Island has a strategic geographical location, which is directly bordered with Sumatera and Kalimantan also Karimata and Malacca Straits. Those conditions make the waters productivity being high due to the support from the biogeochemical cycle, nutrient runoff, and upwelling. This study aims to determine the seasonal variability of chlorophyll-a (Chl-a) around Belitung waters. The method used in this study was spatial analysis with IDW (inverse distance weighted) to interpolate the Chl-a surface distribution. Sea Surface Temperature (SST) acquired from Aqua-MODIS were retrieved from NASA (National Aeronautics and Space Administration) and wind data were obtained from ECMWF (European Centre for Medium-Range Weather Forecasts), data were analyzed statistically and spatially. The Chl-a concentration in the northeast monsoon ranged 0.38-3.5 mg.m-3, in the southwest monsoon ranged 0.15-18.7 mg.m-3, and in the transitional season ranged 0.29-9.04 mg.m-3. The Chl-a concentration during southwest and 1st transitional monsoons were higher due to the maximum sunlight intensity stimulating photosynthesis of autotroph biota. The condition of SST is indicating the upwelling event that involves wind-driven motion of dense, cooler, and usually nutrient-rich water towards the ocean surface. Seasonal SST variability ranged 22.6-28.3oC, 27.3-32.1oC, 30.7-32.3oC, and 29.1-32.8oC during northeast, 1st transitional, southwest, and 2nd transitional monsoons respectively. The existence of ENSO (El-Nino Southern Oscillation) contributes to enhance the Chl-a concentration. During ENSO years, the Chl-a concentration was higher than non-ENSO years due to the great impact of ENSO inducing upwelling and higher nutrient availability. Chl-a and SST conditions can be used to predict fishing ground and upwelling area. &lt;/p&gt;

Loss of predictive skill of indian summer monsoon rainfall in NCEP CFSv2 due to misrepresentation of Atlantic zonal mode

Observational and modeling studies have identified an El Nino Southern Oscillation (ENSO) like Ocean-Atmospheric coupled phenomenon in the tropical Atlantic during the boreal summer season, popularly known as Atlantic Zonal Mode (AZM). The atmospheric teleconnection between the AZM and Indian Summer Monsoon Rainfall (ISMR) is significant especially in non-ENSO years. Hence, realistic simulation of AZM and its teleconnection with ISMR in coupled Ocean-Atmospheric models is important in improving the predictive skill of ISMR. Here, we analyzed the outputs of nine-month hindcast simulations of a coupled ocean-atmospheric model (NCEP CFSv2) in estimating the prediction skill of AZM and its teleconnection with ISMR. It is found that the AZM prediction skill in CFSv2 hindcasts initialized in the month of February (FebIC) is poor and it simulates an unrealistic teleconnection with ISMR. The CFSv2 FebIC hindcasts are unable to forecast the correct phase of the low level wind anomalies over western Atlantic basin, which leads to an error in the forecast of AZM. It is shown here that the error in the prediction of AZM and its erroneous teleconnection with ISMR leads to a loss of prediction skill of ISMR in CFSv2 FebIC hindcasts. It is further noted that the shorter lead time forecast of CFSv2 initialized in the month of May (MayIC hindcasts) shows improved prediction skill of AZM and its associated teleconnection with ISMR compared to the longer lead time forecast (FebIC hindcasts). However, the prediction skill of ISMR is low in MayIC hindcasts compared to FebIC hindcasts. We find that the low prediction skill of ISMR in May IC hindcasts is due to the misrepresentation of the teleconnection between ENSO and ISMR. A notable improvement in the prediction skill of ISMR in CFSv2 can be achieved by combining the ENSO induced ISMR from FebIC hindcasts and AZM induced ISMR from MayIC hindcasts. These results aid in improving the ISMR seasonal forecast in CFSv2. Besides, this study highlights the need to improve the Atlantic variability and its teleconnection with ISMR in the pursuit of improving prediction skill of ISMR in coupled climate models.

Differences in Leaf Temperature between Lianas and Trees in the Neotropical Canopy

Leaf temperature (Tleaf) influences photosynthesis and respiration. Currently, there is a growing interest in including lianas in productivity models due to their increasing abundance and their detrimental effects in the carbon stock of tropical ecosystems. Therefore, understanding the differences of Tleaf between lianas and trees is important for future predictions of productivity. Here, we determined the displayed leaf temperature (Td = Tleaf − air temperature) of several species of lianas and their host trees during El Niño-Southern Oscillation (ENSO) and non-ENSO years to evaluate if the presence of lianas affects the Td of their host trees, and if leaves of lianas and their host trees exhibit differences in Td. Our results suggest that close to midday, the presence of lianas does not affect the Td of their host trees; however, lianas tend to have higher values of Td than their hosts across seasons, in both ENSO and non-ENSO years. Although lianas and trees tend to have similar physiological-temperature responses, differences in Td could lead to significant differences in rates of photosynthesis and respiration based on temperature response curves. Future models should thus consider differences in leaf temperature between these two life forms to achieve robust predictions of productivity.

Cyclone-track based seasonal prediction for South Pacific tropical cyclone activity using APCC multi-model ensemble prediction

This study aims to predict the seasonal TC track density over the South Pacific by combining the Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC) multi-model ensemble (MME) dynamical prediction system with a statistical model. The hybrid dynamical-statistical model is developed for each of the three clusters that represent major groups of TC best tracks in the South Pacific. The cross validation result from the MME hybrid model demonstrates moderate but statistically significant skills to predict TC numbers across all TC clusters, with correlation coefficients of 0.4 to 0.6 between the hindcasts and observations for 1982/1983 to 2008/2009. The prediction skill in the area east of about 170°E is significantly influenced by strong El Nino, whereas the skill in the southwest Pacific region mainly comes from the linear trend of TC number. The prediction skill of TC track density is particularly high in the region where there is climatological high TC track density around the area 160°E–180° and 20°S. Since this area has a mixed response with respect to ENSO, the prediction skill of TC track density is higher in non-ENSO years compared to that in ENSO years. Even though the cross-validation prediction skill is higher in the area east of about 170°E compared to other areas, this region shows less skill for track density based on the categorical verification due to huge influences by strong El Nino years. While prediction skill of the developed methodology varies across the region, it is important that the model demonstrates skill in the area where TC activity is high. Such a result has an important practical implication—improving the accuracy of seasonal forecast and providing communities at risk with advanced information which could assist with preparedness and disaster risk reduction.

ENSO and IOD analysis on the occurrence of floods in Pakistan

Different techniques have been used to discuss the existence of significant relation between the El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Various studies present their interaction and influence on the natural disasters (i.e. drought, flood, etc.) over large parts of the globe. This study uses a Markov chain method to investigate the relation between the ENSO and IOD for the period of 62 years (1950–2011) and aggregates their influence on the occurrence of floods in Pakistan. Both data sets show similarities in the formation of transition matrices and expected number of visits from one state to another. The strong values of 2-dimensional correlation and high self-communication of the transition states confirm the existence of a possible relation between ENSO and IOD data. Moreover, significant values of dependency and stationary test endorse the applicability of the Markov chain analyses. The independent analysis shows that strong events of both data sets are co-occurred in the same flood years. During the study period maximum number of floods was observed during summer monsoon season. However, further analysis shows that after 1970, Pakistan observed the highest percentage of floods occurred per year during El Nino, Non-ENSO and positive IOD years. These observations and results demonstrate that climate variability especially ENSO and IOD should be incorporated into disaster risk analyses and policies in Pakistan.

Seasonal Prediction of Winter Precipitation Anomalies over Central Southwest Asia: A Canonical Correlation Analysis Approach

Central southwest Asia (CSWA; 20°–47°N, 40°–85°E) is a water-stressed region prone to significant variations in precipitation during its winter precipitation season of November–April. Wintertime precipitation is crucial for regional water resources, agriculture, and livelihood; however, in recent years droughts have been a notable feature of CSWA interannual variability. Here, the predictability of CSWA wintertime precipitation is explored based on its time-lagged relationship with the preceding months’ (September–October) sea surface temperature (SST), using a canonical correlation analysis (CCA) approach. For both periods, results indicate that for CSWA much of the seasonal predictability arises from SST variations in the Pacific related to El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO). Additional sources of skill that play a weaker predictive role include long-term SST trends, North Atlantic variability, and regional teleconnections. CCA cross-validation skill shows that the regional potential predictability has a strong dependency on the ENSO phenomenon, and the strengthening (weakening) of this relationship yields forecasts with higher (lower) predictive skill. This finding is validated by the mean cross-validated correlation skill of 0.71 and 0.38 obtained for the 1980/81–2014/15 and 1950/51–2014/15 CCA analyses, respectively. The development of cold (warm) ENSO conditions during September–October, in combination with cold (warm) PDO conditions, is associated with a northward (southward) shift of the jet stream and a strong tendency of negative (positive) winter precipitation anomalies; other sources of predictability influence the regional precipitation directly during non-ENSO years or by modulating the impact of ENSO teleconnection based on their relative strengths.

Tropical rainforest carbon sink declines during El Niño as a result of reduced photosynthesis and increased respiration rates.

Changes in tropical forest carbon sink strength during El Niño Southern Oscillation (ENSO) events can indicate future behavior under climate change. Previous studies revealed ˜6MgCha-1 yr-1 lower net ecosystem production (NEP) during ENSO year 1998 compared with non-ENSO year 2000 in a Costa Rican tropical rainforest. We explored environmental drivers of this change and examined the contributions of ecosystem respiration (RE) and gross primary production (GPP) to this weakened carbon sink. For 1998-2000, we estimated RE using chamber-based respiration measurements, and we estimated GPP in two ways: using (1) the canopy process model MAESTRA, and (2) combined eddy covariance and chamber respiration data. MAESTRA-estimated GPP did not statistically differ from GPP estimated using approach 2, but was ˜28% greater than published GPP estimates for the same site and years using eddy covariance data only. A 7% increase in RE (primarily increased soil respiration) and a 10% reduction in GPP contributed equally to the difference in NEP between ENSO year 1998 and non-ENSO year 2000. A warming and drying climate for tropical forests may yield a weakened carbon sink from both decreased GPP and increased RE. Understanding physiological acclimation will be critical for the large carbon stores in these ecosystems.

South Asian Summer Monsoon Rainfall Variability and Trend: Its Links to Indo-Pacific SST Anomalies and Moist Processes

The warm (cold) phase of El Nino (La Nina) and its impact on all Indian Summer Monsoon rainfall (AISMR) relationship is explored for the past 100 years. The 103-year (1901–2003) data from the twentieth century reanalysis datasets (20CR) and other major reanalysis datasets for southwest monsoon season (JJAS) is utilized to find out the simultaneous influence of the El Nino Southern Oscillation (ENSO)-AISMR relationship. Two cases such as wet, dry monsoon years associated with ENSO(+) (El Nino), ENSO(−) (La Nina) and Non-ENSO (neutral) events have been discussed in detail using observed rainfall and three-dimensional 20CR dataset. The dry and wet years associated with ENSO and Non-ENSO periods show significant differences in the spatial pattern of rainfall associated with three-dimensional atmospheric composite, the 20CR dataset has captured the anomalies quite well. During wet (dry) years, the rainfall is high (low), i.e. 10 % above (below) average from the long-term mean and this wet or dry condition occur both during ENSO and Non-ENSO phases. The Non-ENSO year dry or wet composites are also focused in detail to understand, where do the anomalous winds come from unlike in the ENSO case. The moisture transport is coherent with the changes in the spatial pattern of AISMR and large-scale feature in the 20CR dataset. Recent 50-year trend (1951–2000) is also analyzed from various available observational and reanalysis datasets to see the influence of Indo-Pacific SST and moist processes on the South Asian summer monsoon rainfall trend. Apart from the Indo-Pacific sea surface temperatures (SST), the moisture convergence and moisture transport among India (IND), Equatorial Indian Ocean (IOC) and tropical western pacific (WNP) is also important in modifying the wet or dry cycles over India. The mutual interaction among IOC, WNP and IND in seasonal timescales is significant in modifying wet and dry cycles over the Indian region and the seasonal anomalies.

Seasonality in Prediction Skill and Predictable Pattern of Tropical Indian Ocean SST

Abstract Seasonality of sea surface temperature (SST) predictions in the tropical Indian Ocean (TIO) was investigated using hindcasts (1982–2009) made with the NCEP Climate Forecast System version 2 (CFSv2). CFSv2 produced useful predictions of the TIO SST with lead times up to several months. A substantial component of this skill was attributable to signals other than the Indian Ocean dipole (IOD). The prediction skill of the IOD index, defined as the difference between the SST anomaly (SSTA) averaged over 10°S–0°, 90°–110°E and 10°S–10°N, 50°–70°E, had strong seasonality, with high scores in the boreal autumn. In spite of skill in predicting its two poles with longer leads, CFSv2 did not have skill significantly better than persistence in predicting IOD. This was partly because the seasonal nature of IOD intrinsically limits its predictability. The seasonality of the predictable patterns of the TIO SST was further explored by applying the maximum signal-to-noise (MSN) empirical orthogonal function (EOF) method to the predicted SSTA in March and October, respectively. The most predictable pattern in spring was the TIO basin warming, which is closely associated with El Niño. The basin mode, including its associated atmospheric anomalies, can be predicted at least 9 months ahead, even though some biases were evident. On the other hand, the most predictable pattern in fall was characterized by the IOD mode. This mode and its associated atmospheric variations can be skillfully predicted only 1–2 seasons ahead. Statistically, the predictable IOD mode coexists with El Niño; however, the 1994 event in a non-ENSO year (at least not a canonical ENSO year) can also be predicted at least 3 months ahead by CFSv2.

Assessment of the sensitivity of vegetation to El-Niño/Southern Oscillation events over China

This research explores the sensitivity of vegetation in China to El-Niño/Southern Oscillation (ENSO) events from 1982 to 2006. The ENSO events are defined by the Multivariate ENSO Index (MEI), and variation in vegetation cover is captured by the Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI). Pearson’s χ2 test was used to identify the areas where the variation in vegetation was sensitive to El Niño and La Niña events. The difference in the sensitivity of various ecosystems was investigated using the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product in 2000. Composite NDVI graphs during El Niño, La Niña and non-ENSO years were also produced to investigate the ENSO relationship with the six vegetation ecosystems during El Niño, La Niña and normal phases. The results show that most of the ENSO-sensitive land in China is only affected by one of the two phases of ENSO events, and the area of El Niño-sensitive vegetation is much larger than that of La Niña-sensitive vegetation. North China and the Hengduan Mountains are the two cores of the El Niño-sensitive areas, while the La Niña-sensitive areas are mainly distributed in the central, northwest and northeast regions of China. The sensitivity of vegetation varies across ecosystems: grassland and shrubland had the largest share of El Niño-sensitive areas, and sparse vegetation and savanna were the most sensitive to La Niña events. Overall, the impacts of El Niño events on vegetation in China had regular seasonal variation, while the impacts of La Niña events had regular zonal distribution.

VARIABILITY OF CHLOROPHYLL-A CONCENTRATION AND SEA SURFACE TEMPERATURE OF NATUNA WATERS

&lt;p&gt;Variability of chlorophyll-a concentration and sea surface temperature (SST) in Natuna waters were analyzed using satellite data Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR). SeaWiFS data with a resolution of 9×9 km2 and AVHRR with a resolution of 4×4 km2 were the monthly average data downloaded from NASA website. Chlorophyll-a concentrations and SST were estimated using OC4v4 and MCSST algorithms. In general, the concentration of chlorophyll-a in Natuna waters ranged between 0.11-4.92 mg/m3 with an average of 0.56 mg/m3 during the west season and 0.09-2.93 mg/m3 with an average of 0.66 mg/m3 during the east season. Chlorophyll-a concentrations were relatively high seen in coastal areas, especially around the mouth of the Kapuas, Musi, and Batang Hari rivers allegedly caused by the high nutrient intake from the mainland. SST variability in Natuna waters ranged from 23.46-30.88 °C during the west season and tended to be lower than that the east season (27.91-31.95 °C). In addition, the SST values tended to be lower in the offshore than that inshore. During the west season (Nov-Feb) and the transitional season (Apr) in the years of Elnino Southern Oscillation (ENSO), the concentration of chlorophyll-a and the SST in Natuna waters was generally higher than that in non-ENSO years. The results of wind analyses showed that ENSO caused the change of direction and speed of wind from its normal conditions.&lt;/p&gt;&lt;p&gt;Keywords: Sea surface temperature, chlorophyll-a, Natuna waters, ENSO, SeaWiFS, AVHRR&lt;/p&gt;

VARIABILITY OF CHLOROPHYLL-A CONCENTRATION AND SEA SURFACE TEMPERATURE OF NATUNA WATERS

Variability of chlorophyll-a concentration and sea surface temperature (SST) in Natuna waters were analyzed using satellite data Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR). SeaWiFS data with a resolution of 9×9 km2 and AVHRR with a resolution of 4×4 km2 were the monthly average data downloaded from NASA website. Chlorophyll-a concentrations and SST were estimated using OC4v4 and MCSST algorithms. In general, the concentration of chlorophyll-a in Natuna waters ranged between 0.11-4.92 mg/m3 with an average of 0.56 mg/m3 during the west season and 0.09-2.93 mg/m3 with an average of 0.66 mg/m3 during the east season. Chlorophyll-a concentrations were relatively high seen in coastal areas, especially around the mouth of the Kapuas, Musi, and Batang Hari rivers allegedly caused by the high nutrient intake from the mainland. SST variability in Natuna waters ranged from 23.46-30.88 °C during the west season and tended to be lower than that the east season (27.91-31.95 °C). In addition, the SST values tended to be lower in the offshore than that inshore. During the west season (Nov-Feb) and the transitional season (Apr) in the years of Elnino Southern Oscillation (ENSO), the concentration of chlorophyll-a and the SST in Natuna waters was generally higher than that in non-ENSO years. The results of wind analyses showed that ENSO caused the change of direction and speed of wind from its normal conditions.Keywords: Sea surface temperature, chlorophyll-a, Natuna waters, ENSO, SeaWiFS, AVHRR

Carryover Effects Associated with Winter Location Affect Fitness, Social Status, and Population Dynamics in a Long-Distance Migrant

We used observations of individually marked female black brant geese (Branta bernicla nigricans; brant) at three wintering lagoons on the Pacific coast of Baja California-Laguna San Ignacio (LSI), Laguna Ojo de Liebre (LOL), and Bahía San Quintín (BSQ)-and the Tutakoke River breeding colony in Alaska to assess hypotheses about carryover effects on breeding and distribution of individuals among wintering areas. We estimated transition probabilities from wintering locations to breeding and nonbreeding by using multistratum robust-design capture-mark-recapture models. We also examined the effect of breeding on migration to wintering areas to assess the hypothesis that individuals in family groups occupied higher-quality wintering locations. We used 4,538 unique female brant in our analysis of the relationship between winter location and breeding probability. All competitive models of breeding probability contained additive effects of wintering location and the 1997-1998 El Niño-Southern Oscillation (ENSO) event on probability of breeding. Probability of breeding in non-ENSO years was 0.98 ± 0.02, 0.68 ± 0.04, and 0.91 ± 0.11 for females wintering at BSQ, LOL, and LSI, respectively. After the 1997-1998 ENSO event, breeding probability was between 2% (BSQ) and 38% (LOL) lower than in other years. Individuals that bred had the highest probability of migrating the next fall to the wintering area producing the highest probability of breeding.

Seasonal Prediction of Thermal Stress Accumulation for Coral Bleaching in the Tropical Oceans

Abstract Mass coral bleaching, associated with anomalously warm ocean temperatures over large regions, poses a serious threat to the future health of the world coral reef systems. Seasonal forecasts from coupled ocean–atmosphere models can be a valuable resource for reef management, providing early warning of potential bleaching conditions, allowing for a proactive management response. Here, the ability of a dynamical seasonal forecast model (Predictive Ocean Atmosphere Model for Australia, POAMA) to forecast degree heating months (DHMs) in the tropical oceans is assessed, with particular focus on the 1997/98 El Niño–Southern Oscillation (ENSO) and associated global bleaching events. The model exhibits useful skill in forecasting sea surface temperatures (SSTs) across the tropical oceans for 1982–2006 and reproduced both the magnitude and distribution of DHM values observed during the 1997/98 ENSO event. In general, observed teleconnections between ENSO indices and tropical SST at various lags are well captured by the model. In particular, strong observed correlations between peak ENSO indices and SST in the Caribbean in the following summer were reproduced. The model also shows skill in predicting ocean conditions conducive to bleaching in non-ENSO years, capturing the anomalously warm conditions in the Caribbean region in 2005. Probabilistic forecasts of DHM values above certain thresholds for the Caribbean show useful skill and could be valuable in the assessment of the likelihood of bleaching for the region.