ENSO Modoki Research Articles

A multi‐scalar evaluation of differential impacts of canonical ENSO and ENSO Modoki on drought in China

China has experienced alarming drought events during recent decades. In this study, we investigated monthly drought severity related to the eastern Pacific cooling (EPC), eastern Pacific warming (EPW), and central Pacific warming (CPW), and analysed the differential influence of canonical ENSO (c‐ENSO) and El Niño Modoki (ENSO_M) events on monthly droughts severity based on the SPEI at multiple timescales in China. The results show that (a) EPC episodes negatively affected 1‐ and 3‐month drought severity in southeast and northeast China with negative anomalies lower than −0.4 (<−0.4) during November–February the next year. EPW and CPW episodes significantly negatively affect drought severity in central north China (<−0.8) and the coastal areas of southeast China (<−0.6) during the most months, respectively. (b) La Niña negatively affected drought severity in the most parts of northeast China (<−0.2) and southeast China (<−0.4) during the most months, and La Niña Modoki caused dry conditions in the most parts of China (<−0.2) during a few months. Significant dry conditions were observed in central north China (<−0.8) in many months during El Niño, but dry conditions covered south China (<−0.4) in the most months during El Niño Modoki. (c) SST anomalies in Niño3 and ENSO_M regimes and wind anomalies might explain the spatial distribution of dry conditions across China during c‐ENSO and ENSO_M phases. The results could provide valuable information for predicting droughts associated with the c‐ENSO and ENSO Mokodi.

Impacts of the combined modes of the tropical Indo‐Pacific sea surface temperature anomalies on the tropical cyclone genesis over the western North Pacific

This work presents two combined modes of the summer sea surface temperature anomalies (SSTAs) in the tropical Indo‐Pacific Ocean during 1979–2015 and investigates their influences on the tropical cyclone (TC) genesis frequency (TCGF) over the western North Pacific (WNP). The first mode (referred to as ENSO‐IODM) features Indian Ocean dipole (IOD) SSTAs in the tropical Indian Ocean (TIO) and El Niño‐like SSTAs in the tropical Pacific Ocean (TPO) and often appears during the ENSO phase persistence summers. It usually triggers an anomalous cyclone and more TCs over the southeastern WNP together with an anomalous anticyclone and fewer TCs over the northwestern WNP. These are primarily attributed to the effect of the El Niño‐like SSTAs over the TPO. The second mode (referred to as ENM‐IOBM) is characterized by Indian Ocean basin (IOB) positive SSTAs in the TIO and La Niña Modoki‐like (ENSO Modoki; ENM) SSTAs in the TPO and often presents during the ENSO phase transition summers. The combined effects of the IOBM and ENM SSTAs induce an anomalous anticyclone over the WNP that significantly suppresses TC genesis over the central WNP.The impacts of the two combined modes on the WNP TCGF also reveal inter‐decadal changes with significant weakening of the ENSO‐IODM and strengthening of the ENM‐IOBM around the early 1990s. These are attributed to the weakened variability of the ENSO‐IODM and intensified variability of the ENM‐IOBM around the early 1990s, and show largely association with the changes in the ENSO cycle. Most of the ENSO events prior to the early 1990s show a long decaying phase with persistence features but exhibit a short decaying phase even with phase transition after the early 1990s. This brings more ENSO‐IODM structures in the summer TIPO SSTAs before the early 1990s and more ENM‐IOBM structures during the latter period, and thereby results in such above inter‐decadal changes.

Towards understanding the global and regional climatic impacts of Modoki magnitude

Abstract Earlier studies suggest that the frequency and the strength of ENSO Modoki events increased considerably since last few decades (1970–2010) resulting in a need to revisit the climatic impacts of varying magnitude of ENSO Modoki. Hence, to better understand the impact of ENSO Modoki amplitude over the tropical and extra-tropical regions, especially in the Pacific, Asian and African regions, we conducted ENSO Modoki sensitivity experiments using ICTP-AGCM (SPEEDY). One of the main interests of this study is to see how ICTP-AGCM can reproduce teleconnections induced by ENSO Modoki events and how sensitive is the global and regional climate to ENSO Modoki strength. SPEEDY model qualitatively reproduces the impact of ENSO Modoki over the Pacific, Atlantic, North and South America and African regions very well. However, it underestimates ENSO Modoki-induced teleconnection patterns and associated changes in South Asia, particularly in the Indian region. This study suggests a nonlinear climatic response to increased magnitude of ENSO Modoki. Our results reveal that like conventional ENSO, ENSO Modoki also induces considerable impact over North Pacific (Atlantic) region and initiates strong PNA (NAO) like response. ENSO Modoki-induced negative/positive NAO-like response and associated changes in Southern Europe and North Africa region get significantly strong following increased intensity of El Nino/La Nina Modoki in the boreal winter. We further find that ENSO Modoki magnitude significantly impacts tropical and high latitude circulation cells. The positive phase of ENSO (El Nino) overall strengthens Hadley Cell and a reverse is true for La Nina phase. ENSO Modoki-induced strengthening and weakening of Hadley Cell induce significant impact over South Asian and African ITCZ convective regions through modification of ITCZ/monsoon circulation system.

A new perspective of intensified impact of El Niño‐Southern Oscillation Modoki on tropical cyclogenesis over the western North Pacific around 1990s

Previous study detected an intensified impact of the El Niño‐Southern Oscillation (ENSO) Modoki sea surface temperature (SST) anomalies on the tropical cyclone (TC) activity over the western North Pacific (WNP) after the early 1990s and attributed it to an expansion in areal coverage of the equatorial central Pacific (ECP) SST anomalies. This study identifies the contribution of SST anomalies in several other regions to this inter‐decadal change in the relationship between ENSO Modoki SST and the WNP TC genesis. Before the early 1990s, the positive ECP SST anomalies induce an anomalous lower‐level cyclone and consequently an increase in the TC genesis frequency over the southern part of the WNP, and the positive ECP and tropical Indian Ocean SST anomalies together induce an anomalous lower‐level anticyclone and accordingly a decrease in the TC genesis frequency over the northern part of the WNP. As such, the relationship between the ECP SST and the WNP TC genesis frequency is weak. After the early 1990s, the positive ECP SST anomalies with a large areal coverage induce a large anomalous lower‐level cyclone covering most of the WNP and thus an increase in the TC genesis frequency over the WNP. Meantime, the tropical northern Atlantic and western South Pacific SST anomalies during spring enhance the succeeding summer–autumn WNP atmospheric circulation response to the ECP SST anomalies through an Atlantic–Pacific teleconnection and a wind‐evaporation positive feedback, respectively. This strengthens the relationship between the ECP SST and the WNP TC genesis frequency.

Relevance of Indian Summer Monsoon and its Tropical Indo-Pacific Climate Drivers for the Kharif Crop Production

While the Indian agriculture has earlier been dependent on the Indian summer monsoon rainfall (ISMR), a multifold increase in irrigation and storage facilities raise a question whether the ISMR is still as relevant. We revisit this question using the latest observational climate datasets as well as the crop production data and find that the ISMR is still relevant for the Kharif crop production (KCP). In addition, in the recent changes in the tropical Indo-Pacific driver evolutions and frequency, particularly more frequent occurrence of the ENSO Modokis in place of the canonical ENSOs, we carry out a correlation analysis to estimate the impact of the various Indo-Pacific climate drivers on the rainfall of individual Indian states for the period 1998–2013, for which crop production data for the most productive Indian states, namely West Bengal, Odisha, United Andhra Pradesh (UAP), Haryana, Punjab, Karnataka, Kerala, Madhya Pradesh, Bihar and Uttar Pradesh are available. The results suggest that the KCP of the respective states are significantly correlated with the summer monsoon rainfall at the 95–99% confidence levels. Importantly, we find that the NINO 3.4 and ENSO Modoki indices have a statistically significant correlation with the KCP of most of the Indian states, particularly in states such as UAP and Karnataka, through induction of anomalous local convergence/divergence, well beyond the equatorial Indian Ocean. The KCP of districts in UAP also has a significant response to all the climate drivers, having implication for prediction of local crop yield.

Intensified influence of the ENSO Modoki on boreal summer tropical cyclone genesis over the western North Pacific since the early 1990s

ABSTRACTThis study presents the inter‐decadal intensified impact of the ENSO Modoki (ENM) on tropical cyclone (TC) genesis over the western North Pacific (WNP) since the early 1990s. We find that this intensified impact may be largely attributed to the inter‐decadal change of the spatio‐temporal variability of the ENM, which includes an increasing period and expansive sea surface temperature (SST) anomaly over the central Pacific after the early 1990s. Because of the inter‐decadal change of the ENM, especially the expansive SST pattern, the response of large‐scale atmospheric circulation was enhanced and had expanded northwards and westwards since the early 1990s, which has led to significant TC genesis anomalies over a large fraction of the WNP. The spatial changes of the ENM may possibly be modulated by the inter‐decadal SST change over the Pacific.

Impact of ENSO regimes on developing- and decaying-phase precipitation during rainy season in China

Abstract. This study investigated the influence of five El Niño–Southern Oscillation (ENSO) types on rainy-season precipitation in China: central Pacific warming (CPW), eastern Pacific cooling (EPC), eastern Pacific warming (EPW), conventional ENSO and ENSO Modoki. The multi-scale moving t test was applied to determine the onset and withdrawal of rainy season. Results showed that the precipitation anomaly can reach up to 30 % above average precipitation during decaying CPW and EPW phases. Developing EPW could cause decreasing precipitation over large areas in China with 10–30 % lower than average precipitation in most areas. Conventional El Niño in the developing phase had the largest influence on ENSO-related precipitation among developing ENSO and ENSO Modoki regimes. Decaying ENSO also showed a larger effect on precipitation anomalies, compared to decaying ENSO Modoki. The difference between rainy-season precipitation under various ENSO regimes may be attributed to the combined influence of anti-cyclone in the western North Pacific and the Indian monsoon. Stronger monsoon and anti-cyclone are associated with enhanced rainy-season precipitation. The results suggest a certain predictability of rainy-season precipitation related to ENSO regimes.

ENSO Influence on Rainy Season Precipitation over the Yangtze River Basin

The paper explores the impact of El Niño-Southern Oscillation (ENSO) on rainy season precipitation properties over the Yangtze River Basin. The multi-scale moving t-test was used to determine the onset and withdrawal of the rainy season. Results showed the following: (1) Onset and withdrawal of the averaged rainy season over the Yangtze River Basin showed a similar distribution and both progressed northwards and westwards. There is a trend for delayed onset of rainy season precipitation over the Yangtze River Basin. A similar trend in the withdrawal of rainy season precipitation was not found. (2) The decaying Central and Eastern Pacific Warming are indicative of wet signals in the Yangtze River Basin, with precipitation anomalies up to 25% above normal. The decaying Eastern Pacific Cooling and developing Eastern Pacific Warming are indicative of dry signals over the Yangtze River Basin, with 5–20% lower than average precipitation (3) ENSO Modoki in the developing phase is more important than the developing ENSO when it comes to present wetter or drier signals. Conversely, the decaying ENSO shows more prominent wet or dry signals than the decaying ENSO Modoki.

Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model

Drought forecasting using standardized metrics of rainfall is a core task in hydrology and water resources management. Standardized Precipitation Index (SPI) is a rainfall-based metric that caters for different time-scales at which the drought occurs, and due to its standardization, is well-suited for forecasting drought at different periods in climatically diverse regions. This study advances drought modelling using multivariate adaptive regression splines (MARS), least square support vector machine (LSSVM), and M5Tree models by forecasting SPI in eastern Australia. MARS model incorporated rainfall as mandatory predictor with month (periodicity), Southern Oscillation Index, Pacific Decadal Oscillation Index and Indian Ocean Dipole, ENSO Modoki and Nino 3.0, 3.4 and 4.0 data added gradually. The performance was evaluated with root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (r2). Best MARS model required different input combinations, where rainfall, sea surface temperature and periodicity were used for all stations, but ENSO Modoki and Pacific Decadal Oscillation indices were not required for Bathurst, Collarenebri and Yamba, and the Southern Oscillation Index was not required for Collarenebri. Inclusion of periodicity increased the r2 value by 0.5–8.1% and reduced RMSE by 3.0–178.5%. Comparisons showed that MARS superseded the performance of the other counterparts for three out of five stations with lower MAE by 15.0–73.9% and 7.3–42.2%, respectively. For the other stations, M5Tree was better than MARS/LSSVM with lower MAE by 13.8–13.4% and 25.7–52.2%, respectively, and for Bathurst, LSSVM yielded more accurate result. For droughts identified by SPI≤−0.5, accurate forecasts were attained by MARS/M5Tree for Bathurst, Yamba and Peak Hill, whereas for Collarenebri and Barraba, M5Tree was better than LSSVM/MARS. Seasonal analysis revealed disparate results where MARS/M5Tree was better than LSSVM. The results highlight the importance of periodicity in drought forecasting and also ascertains that model accuracy scales with geographic/seasonal factors due to complexity of drought and its relationship with inputs and data attributes that can affect the evolution of drought events.

How distinct are the two flavors of El Niño in retrospective forecasts of Climate Forecast System version 2 (CFSv2)?

Two different flavors of El Nino-Southern Oscillation (ENSO, canonical east Pacific type and Modoki/central Pacific type) are reported in the recent decades and are found to influence the global climate in different ways. The success of a seasonal prediction system is dependent on its ability to capture these two ENSO flavors accurately, together with associated teleconnections. The present study analyses the ability of Climate Forecast System version 2 (CFSv2) in simulating the two El Nino flavors and their teleconnections. The study uses two versions of CFSv2 in which the atmospheric model horizontal resolutions are different (T126 at 100 km and T382 at 38 km) and are initialized from a calendar month, ranging from February to June. The canonical ENSO pattern is captured as prominent mode of tropical Pacific sea surface temperature (SST) by both resolutions of CFSv2. Even though the tri-polar structure of ENSO Modoki is simulated as second mode, it has some disagreement with observations. The canonical El Nino induced SST, rainfall and atmospheric circulation in the tropical Pacific in summer and fall seasons are comparable with observations in both models. Meanwhile, the teleconnections in the tropical Indian Ocean and Indian monsoon regions are close to observations in T382 only. Teleconnections associated with El Nino Modoki are proper in T382 hindcasts, in which SST bias in Indian Ocean is slightly warm and the cold bias in central Pacific is marginal (mainly for Feb IC hindcasts). The present study indicates that the distinction of ENSO flavors in summer is the major reason for the higher skill of Indian summer monsoon rainfall (ISMR) in CFSv2 T382 Feb IC hindcasts. However, teleconnections associated with two flavors of ENSO are not distinguishable in fall and winter seasons, even in higher resolution model due to the presence of strong cold SST bias in central Pacific and warm SST bias in extreme east Pacific. Thus present study confirms that, higher resolution CFSv2 is required to differentiate the flavors of ENSO and their teleconnections properly. It has better prediction skill for ISMR at a lead time of 4 months, which is significant for seasonal prediction of Indian summer monsoon.

Associations between malaria and local and global climate variability in five regions in Papua New Guinea.

BackgroundMalaria is a significant public health issue in Papua New Guinea (PNG) as the burden is among the highest in Asia and the Pacific region. Though PNG’s vulnerability to climate change and sensitivity of malaria mosquitoes to weather are well-documented, there are few in-depth epidemiological studies conducted on the potential impacts of climate on malaria incidence in the country.MethodsThis study explored what and how local weather and global climate variability impact on malaria incidence in five regions of PNG. Time series methods were applied to evaluate the associations of malaria incidence with weather and climate factors, respectively. Local weather factors including precipitation and temperature and global climate phenomena such as El Niño-Southern Oscillation (ENSO), the ENSO Modoki, the Southern Annular Mode, and the Indian Ocean Dipole were considered in analyses.ResultsThe results showed that malaria incidence was associated with local weather factors in most regions but at the different lag times and in directions. Meanwhile, there were trends in associations with global climate factors by geographical locations of study sites.ConclusionsOverall heterogeneous associations suggest the importance of location-specific approaches in PNG not only for further investigations but also public health interventions in repose to the potential impacts arising from climate change.Electronic supplementary materialThe online version of this article (doi:10.1186/s41182-016-0021-x) contains supplementary material, which is available to authorized users.

The atmospheric electrical index for ENSO modoki: Is ENSO modoki one of the factors responsible for the warming trend slowdown?

Like the southern oscillation index (SOI) based on the pressure difference between Tahiti (17.5°S, 150°W) and Darwin (12.5°S, 130°E), we propose the new atmospheric electrical index (AEI) taking the difference in the model calculated atmospheric electrical columnar resistance (Rc) which involves planetary boundary layer height (PBLH) and aerosol concentration derived from the satellite measurements. This is the first non-oceanic index capable of differentiating between the conventional and modoki La Niña and El Niño both and may be useful in the future air-sea coupling studies and as a complementary to the oceanic indices. As the PBLH variation over Darwin is within 10% of its long term mean, a strong rise in the Rc over Darwin during the modoki period supports modoki’s connection with aerosol loading. Our correlation results show that the intensity of El Niño (La Niña) event is almost independent (not independent) of its duration and the possibility of ENSO modoki being one of the factors responsible for the warming trend slowdown (WTS).

An analysis of high cloud variability: imprints from the El Niño–Southern Oscillation

Using data from the International Satellite Cloud Climatology Project (ISCCP), we examine how near-global (60°N–60°S) high cloud fraction varies over time in the past three decades. Our focus is on identifying dominant modes of variability and associated spatial patterns, and how they are related to sea surface temperature. By performing the principal component analysis, we find that the first two principal modes of high cloud distribution show strong imprints of the two types of El Nino–Southern Oscillation (ENSO)—the canonical ENSO and the ENSO Modoki. Comparisons between ISCCP data and 14 models from the Atmospheric Model Intercomparison Project Phase 5 (AMIP5) show that models simulate the spatial pattern and the temporal variations of high cloud fraction associated with the canonical ENSO very well but the magnitudes of the canonical ENSO vary among the models. Furthermore, the multi-model mean of the second principal mode in the AMIP5 simulations appears to capture the temporal behavior of the second mode but individual AMIP5 models show large discrepancies in capturing observed temporal variations. A new metric, defined by the relative variances of the first two principal components, suggests that most of the AMIP5 models overestimate the second principal mode of high clouds.

An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland.

A predictive model for streamflow has practical implications for understanding the drought hydrology, environmental monitoring and agriculture, ecosystems and resource management. In this study, the state-or-art extreme learning machine (ELM) model was utilized to simulate the mean streamflow water level (Q WL) for three hydrological sites in eastern Queensland (Gowrie Creek, Albert, and Mary River). The performance of the ELM model was benchmarked with the artificial neural network (ANN) model. The ELM model was a fast computational method using single-layer feedforward neural networks and randomly determined hidden neurons that learns the historical patterns embedded in the input variables. A set of nine predictors with the month (to consider the seasonality of Q WL); rainfall; Southern Oscillation Index; Pacific Decadal Oscillation Index; ENSO Modoki Index; Indian Ocean Dipole Index; and Nino 3.0, Nino 3.4, and Nino 4.0 sea surface temperatures (SSTs) were utilized. A selection of variables was performed using cross correlation with Q WL, yielding the best inputs defined by (month; P; Nino 3.0 SST; Nino 4.0 SST; Southern Oscillation Index (SOI); ENSO Modoki Index (EMI)) for Gowrie Creek, (month; P; SOI; Pacific Decadal Oscillation (PDO); Indian Ocean Dipole (IOD); EMI) for Albert River, and by (month; P; Nino 3.4 SST; Nino 4.0 SST; SOI; EMI) for Mary River site. A three-layer neuronal structure trialed with activation equations defined by sigmoid, logarithmic, tangent sigmoid, sine, hardlim, triangular, and radial basis was utilized, resulting in optimum ELM model with hard-limit function and architecture 6-106-1 (Gowrie Creek), 6-74-1 (Albert River), and 6-146-1 (Mary River). The alternative ELM and ANN models with two inputs (month and rainfall) and the ELM model with all nine inputs were also developed. The performance was evaluated using the mean absolute error (MAE), coefficient of determination (r (2)), Willmott's Index (d), peak deviation (P dv), and Nash-Sutcliffe coefficient (E NS). The results verified that the ELM model as more accurate than the ANN model. Inputting the best input variables improved the performance of both models where optimum ELM yielded R(2) ≈ (0.964, 0.957, and 0.997), d ≈ (0.968, 0.982, and 0.986), and MAE ≈ (0.053, 0.023, and 0.079) for Gowrie Creek, Albert River, and Mary River, respectively, and optimum ANN model yielded smaller R(2) and d and larger simulation errors. When all inputs were utilized, simulations were consistently worse with R (2) (0.732, 0.859, and 0.932 (Gowrie Creek), d (0.802, 0.876, and 0.903 (Albert River), and MAE (0.144, 0.049, and 0.222 (Mary River) although they were relatively better than using the month and rainfall as inputs. Also, with the best input combinations, the frequency of simulation errors fell in the smallest error bracket. Therefore, it can be ascertained that the ELM model offered an efficient approach for the streamflow simulation and, therefore, can be explored for its practicality in hydrological modeling.

Impacts of ENSO and ENSO Modoki+A regimes on seasonal precipitation variations and possible underlying causes in the Huai River basin, China

Spatiotemporal patterns of seasonal precipitation changes across the Huai River basin, China, were analyzed, using daily precipitation data from 35 meteorological stations for the period of 1961–2010. Seasonal precipitation changes in related to Eastern Pacific Warming (EPW), Central Pacific Warming (CPW), and Eastern Pacific Cooling (EPC) were investigated. Impacts of canonical ENSO (c-ENSO) and ENSO Modoki+A (EM+A) on seasonal precipitation variations were evaluated. Water vapor transport patterns were also examined to determine the possible mechanisms causing the impacts of ENSO regimes on seasonal precipitation changes. Results indicated that: (1) EPC is the main driver for the increase of spring and autumn precipitation and autumn/spring precipitation tends to decrease during CPW/EPW, respectively. However, EPW and CPW can result in an increase of the summer precipitation amount in the middle and upper basin, and EPC causes an increase of the spring precipitation amount, which may amplify flood risk in the basin; (2) c-ENSO regimes tend to increase the precipitation amount during spring and autumn, especially for the winter precipitation amount. However, c-ENSO and EM+A cause distinctly different impacts on the summer and autumn precipitation: a decrease of summer and autumn precipitation is observed during the EM+A periods while an increase during the c-ENSO periods; (3) In summer and spring, water vapor transport during the c-ENSO periods is more active than during the EM+A periods. Further, water vapor flux is more abundant during the warm episodes of c-ENSO events in spring and summer than during the cold episodes of c-ENSO, and hence higher spring and summer precipitation across the basin. Results of this study may help to understand the causes underlying spatiotemporal patterns of seasonal precipitation and can help in developing measures for the mitigation of floods and droughts hazards in a changing climate.

Impacts of IOD, ENSO and ENSO Modoki on the Australian Winter Wheat Yields in Recent Decades.

Impacts of the Indian Ocean Dipole (IOD), two different types of El Niño/Southern Oscillation (ENSO): canonical ENSO and ENSO Modoki, on the year-to-year winter wheat yield variations in Australia have been investigated. It is found that IOD plays a dominant role in the recent three decades; the wheat yield is reduced (increased) by −28.4% (12.8%) in the positive (negative) IOD years. Although the canonical ENSO appears to be responsible for the wheat yield variations, its influences are largely counted by IOD owing to their frequent co-occurrence. In contrast, the ENSO Modoki may have its distinct impacts on the wheat yield variations, but they are much smaller compared to those of IOD. Both the observed April-May and the predicted September-November IOD indices by the SINTEX-F ocean-atmosphere coupled model initialized on April 1st just before the sowing season explain ~15% of the observed year-to-year wheat yield variances. The present study may lead to a possible scheme for predicting wheat yield variations in Australia in advance by use of simple climate mode indices.

Impacts of the ENSO Modoki and other Tropical Indo-Pacific Climate-Drivers on African Rainfall.

The study diagnoses the relative impacts of the four known tropical Indo-Pacific drivers, namely, El Niño Southern Oscillation (ENSO), ENSO Modoki, Indian Ocean Dipole (IOD), and Indian Ocean Basin-wide mode (IOBM) on African seasonal rainfall variability. The canonical El Niño and El Niño Modoki are in general associated with anomalous reduction (enhancement) of rainfall in southern (northern) hemispheric regions during March-May season. However, both the El Niño flavours anomalously reduce the northern hemispheric rainfall during June-September. Interestingly, during boreal spring and summer, in many regions, the Indian Ocean drivers have influences opposite to those from tropical Pacific drivers. On the other hand, during the October-December season, the canonical El Niño and/or positive IOD are associated with an anomalous enhancement of rainfall in the Eastern Africa, while the El Niño Modoki events are associated with an opposite impact. In addition to the Walker circulation changes, the Indo-Pacific drivers influence the African rainfall through modulating jet streams. During boreal summer, the El Niño Modoki and canonical El Niño (positive IOD) tend to weaken (strengthen) the tropical easterly jet, and result in strengthening (weakening) and southward shift of African easterly jet. This anomalously reduces (enhances) rainfall in the tropical north, including Sahelian Africa.

Spatio-Temporal Variations of Rainfall and SST Anomaly over Indonesia during ENSO Modoki Event in 2010

Remote sensing application is one of the best data to observing spatial and temporal situation on earth surface. Application of Tropical Rainfall Measuring Mission (TRMM) and MODIS (Moderate Resolution Imaging Spectro-radiometer) are use for spatial and temporal analysis of rainfall and sea surface temperature (SST) anomaly over Indonesia in 2010. Spatial and temporal rainfall and SST anomaly data is important, especially during El Niño–Southern Oscillation (ENSO) Modoki events, because has wide effect of social and economy in Indonesia. Monthly rainfall data measured by the TRMM 3B43 over the course of 13 years and Monthly SST collected by the MODIS was employed to analyze anomaly of rainfall and SST over Indonesia during ENSO Modoki Event in 2010. In spatio-temporal seen confirmed during ENSO Modoki in 2010 indicate an anomaly has occurred on rainfall and SST over Indonesia. The result shows that increasing of rainfall anomaly begin from April in Nusa Tenggara archipelago and eastern of Java and finish in November in those region. Meanwhile, analysis result of MODIS satellite data for SST anomaly is shown at the beginning of 2010, SST anomaly begin occurred in western of Indonesia and the biggest was happen in southern of Indonesia at August to September and finish at November. Spatio-temporal analysis TRMM dan MODIS data shows that increasing of SST anomaly could affect increasing of rainfall anomaly in those same regions excepted in January to March.

A Theoretical Explanation of Anomalous Atmospheric Circulation Associated with ENSO Modoki during Boreal Winter

Based on a linear model, the present study provides analytical solutions for ideal triple forcing sources similar to sea surface temperature anomaly (SSTA) patterns associated with El Nino-Southern...

Skill evaluation of the CanCM4 and its MOS for seasonal rainfall forecast in Malaysia during the early and late winter monsoon periods

This study evaluates the forecast skill of the fourth version of the Canadian coupled ocean–atmosphere general circulation model (CanCM4) and its model output statistics (MOS) to forecast the seasonal rainfall in Malaysia, particularly during early (October–November–December) and late (January–February–March) winter monsoon periods. CanCM4 is the latest component of the Canadian Seasonal to Inter-annual Prediction System (CanSIPS), which is a multi-seasonal climate prediction system developed particularly for Canada but applicable globally. Generally, CanCM4's skill in reproducing the climatology during winter is not as good as in other seasons because of the model's inability to simulate the regional synoptic circulations over the western Maritime Continent. In particular, the model fails to forecast the cold surges and Borneo vortex circulations that play critical roles in moisture horizontal advection. Moreover, its forecast skill during the early winter monsoon period is poorer than during the late period. Interestingly, forecast skill is enhanced when MOS models are applied as the MOS utilizes the predictive signals in the quasi-global predictors from the CanCM4 forecast system. The predictability can be traced to the conventional El Nino–Southern Oscillation (ENSO) and ENSO Modoki signals that are present in the CanCM4 forecast MOS predictor fields. The quasi-global sea-surface temperature and quasi-global sea-level pressure fields are found to be the most useful predictors. Interestingly, CanCM4 forecast signals associated with the Indian Ocean Dipole also contribute to the skill. Skill enhancement is particularly significant for northern Borneo during early monsoon periods in medium- and long-lead forecasts when the CanCM4 has minimal direct skill in the region.