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North Atlantic European (NAE) winter climate variability is strongly modulated through the stratospheric and tropospheric pathways, where El Niño-Southern Oscillation (ENSO) teleconnections play an important role. Recent studies showed intra-seasonal changes of the ENSO response in the NAE circulation anomalies from early to late winter. One mechanism for this behavior is that the Indian Ocean (IO) dominate over the direct ENSO teleconnections in early winter favoring an in-phase North Atlantic Oscillation (NAO) response over NAE region. On the other hand, the direct ENSO response dominates in latter half of winter, where it projects onto the opposite phase of the NAO. In present study, we analyze the early to late winter ENSO-NAE teleconnections in future climate projections by adopting the sixth assessment report Coupled Model Intercomparison Project (CMIP6) model datasets. During early winter, we noted an increase in the ENSO-induced precipitation variability in the Pacific as well as over western and central Indian Ocean, while decrease is noted over the eastern IO. Moreover, a strengthening of the ENSO and Indian connections are noted in almost all models except few, where these connections are not well represented in the present climate. Interestingly, the changes in ENSO forced wave train are noted, which may lead to the negative NAO like circulation anomalies over the NAE region in future compared to the present climate.

The Surface Air Temperature (SAT) variability over Western South Asia (WSA) is highest during the early summer (May-June) season, which leads to frequent seasonal heatwaves over the region. Therefore, it is important to understand the model’s ability in predicting the regional anomalous temperature conditions, which is the focus of this study using the European Centre for MediumRange Weather Forecast fifth generation (ECMWF-SEAS5) seasonal prediction system dataset for the period 1981-2022. The model skilfully predicts the El Niño-Southern Oscillation (ENSO) related interannual variability of the SAT over WSA compared to the reanalysis, mediated through the upper-level positive 200-hPa geopotential height anomalies, that lead to warm conditions over the regions during the negative ENSO phase. A negative ENSO-SAT relationship shows that warmer extreme temperature events are more frequent during La Niña, while the opposite may happen for El Niño years. The model shows a reasonable actual prediction skill of the SAT anomalies over the WSA region compared to the higher resolution observational and reanalysis datasets, while a low skill is noted for coarser resolutions, which shows that a choice of the observational dataset is important for the estimation of the model skill. Overall, the Potential Predictability of the SAT is comparable to its actual prediction skill over the WSA region. Moreover, the higher Potential Predictability of the SAT over WSA is noted during La Niña compared to El Niño, which is mainly contributed through the higher signal compared to the noise.

This paper assesses the skill of the Saudi-King Abdulaziz University coupled ocean–atmosphere Global Climate Model, namely Saudi-KAU CGCM, in forecasting the El Niño-Southern Oscillation (ENSO)-related sea surface temperature. The model performance is evaluated based on a reforecast of 38 years from 1982 to 2019, with 20 ensemble members of 12-month integrations. The analysis is executed on ensemble mean data separately for boreal winter (December to February: DJF), spring (March to May: MAM), summer (June to August: JJA), and autumn (September to November: SON) seasons. It is found that the Saudi-KAU model mimics the observed climatological pattern and variability of the SST in the tropical Pacific region. A cold bias of about 0.5–1.0 °C is noted in the ENSO region during all seasons at 1-month lead times. A statistically significant positive correlation coefficient is observed for the predicted SST anomalies in the tropical Pacific Ocean that lasts out to 6 months. Across varying times of the year and lead times, the model shows higher skill for autumn and winter target seasons than for spring or summer ones. The skill of the Saudi-KAU model in predicting Niño 3.4 index is comparable to that of state-of-the-art models available in the Copernicus Climate Change Service (C3S) and North American Multi-Model Ensemble (NMME) projects. The ENSO skill demonstrated in this study is potentially useful for regional climate services providing early warning for precipitation and temperature variations on sub-seasonal to seasonal time scales.

This study investigates precipitation variability over the Arabian Peninsula (AP) during its wet season. The wet season is split into winter (November – February) and spring (March and April) seasons, and early (1950–1986) and late (1986–2021) periods to understand sub-seasonal characteristics of precipitation variability and long-term changes in global teleconnections. The first three Empirical Orthogonal Functions explain ~70% of the interannual wet season precipitation variance, which shows an increase (decrease) in the late period winter (spring). Linear regression of the sea surface temperatures and geopotential height onto associated principal components reveals many oceanic and atmospheric variability patterns, which exhibit significant differences between winter and spring and early and late periods. Further, linear regressions of AP precipitation onto 14 natural modes of climate variability reveal a complex network of global teleconnections. El Niño-Southern Oscillation (ENSO) is one of the key contributors to precipitation variability but considering ENSO diversity is crucial to fully understand its influence. While the direct ENSO influence only becomes robust after the 1980s, its indirect effect persists through projection onto atmospheric modes, such as East Atlantic West Russia Pattern and East Atlantic Mode, or inter-basin interaction (e.g., via the Indian Ocean). The Northern Hemisphere atmospheric modes also mediate influences of other natural modes in tropical Indian and Atlantic oceans and extra-tropical regions over the AP. Several precipitation teleconnections exhibit a shift in the 1980s. Some may be related to the introduction of satellite data, but further investigations are warranted to understand the causes of these shifts.

This paper presents projected changes in extreme temperature and precipitation events by using Coupled Model Intercomparison Project phase 6 (CMIP6) data for mid-century (2036–2065) and end-century (2070–2099) periods with respect to the reference period (1985–2014). Four indices namely, Annual maximum of maximum temperature (TXx), Extreme heat wave days frequency (HWFI), Annual maximum consecutive 5-day precipitation (RX5day), and Consecutive Dry Days (CDD) were investigated under four socioeconomic scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5) over the entire globe and its 26 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions. The projections show an increase in intensity and frequency of hot temperature and precipitation extremes over land. The intensity of the hottest days (as measured by TXx) is projected to increase more in extratropical regions than in the tropics, while the frequency of extremely hot days (as measured by HWFI) is projected to increase more in the tropics. Drought frequency (as measured by CDD) is projected to increase more over Brazil, the Mediterranean, South Africa, and Australia. Meanwhile, the Asian monsoon regions (i.e., South Asia, East Asia, and Southeast Asia) become more prone to extreme flash flooding events later in the twenty-first century as shown by the higher RX5day index projections. The projected changes in extremes reveal large spatial variability within each SREX region. The spatial variability of the studied extreme events increases with increasing greenhouse gas concentration (GHG) and is higher at the end of the twenty-first century. The projected change in the extremes and the pattern of their spatial variability is minimum under the low-emission scenario SSP1-2.6. Our results indicate that an increased concentration of GHG leads to substantial increases in the extremes and their intensities. Hence, limiting CO2 emissions could substantially limit the risks associated with increases in extreme events in the twenty-first century.

The North Atlantic European (NAE) regional circulation anomalies variability and predictability during the boreal winter season is modulated through both stratospheric and tropospheric pathways on sub-seasonal to seasonal timescales. El Niño-Southern Oscillation (ENSO) through the atmospheric teleconnections is one of the dominating forcing that modulates the global climate variability and Predictability during the boreal winter season. However, recent studies indicate the intra-seasonality in the ENSO teleconnections, where through the inter-basin interactions the Indian Ocean (IO) bridges the ENSO response to the NAE region in the early winter, while the direct ENSO response dominates in latter half of the boreal winter. Therefore, in the current study we analyzed the predictability of the NAE circulation anomalies and the tropical Indian Ocean precipitation anomalies during the early winter season using the ECMWF System-5 seasonal (SEAS5) dataset. We noted the boreal Autumn Indian Ocean Dipole (IOD) conditions are the pre-courser for the early winter precipitation anomalies in the Tropical Western-Central Indian Ocean (TWCIO) region, which dominates the ENSO response to the IO precipitation anomalies during the earlier half of the winter season. These TWCIO precipitation anomalies are well predicted by the ECMWF-SEAS5 prediction system during early winter. Furthermore, we noted the positive TWCIO heating anomalies tend to favor the positive North Atlantic Oscillation (NAO) condition in the North Atlantic region. This leads to the above normal Surface Air temperature (SAT) conditions, indicating to the mild early winter conditions over the European continent. The ECMWF-SEAS5 system shows a significant prediction skill of the SAT anomalies over the NAE region.

In this study the role of an Indian Ocean heating dipole anomaly in the transition of the North Atlantic–European (NAE) circulation response to El Niño–Southern Oscillation (ENSO) from early to late winter is analyzed using a twentieth-century reanalysis and simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). It is shown that in early winter a warm (cold) ENSO event is connected through an atmospheric bridge with positive (negative) rainfall anomalies in the western Indian Ocean and negative (positive) anomalies in the eastern Indian Ocean. The early winter heating dipole, forced by a warm (cold) ENSO event, can set up a wave train emanating from the subtropical South Asian jet region that reaches the North Atlantic and leads to a response that spatially projects onto the positive (negative) phase of the North Atlantic Oscillation. The Indian Ocean heating dipole is partly forced as an atmospheric teleconnection by ENSO, but can also exist independently and is not strongly related to local Indian Ocean sea surface temperature (SST) forcing. The Indian Ocean heating dipole response to ENSO is much weaker in late winter (i.e., February and March) and not able to force significant signals in the North Atlantic region. CMIP5 multimodel ensemble reproduces the early winter Indian Ocean heating dipole response to ENSO and its transition in the North Atlantic region to some extent, but with weaker amplitude. Generally, models that have a strong early winter ENSO response in the subtropical South Asian jet region along with tropical Indian Ocean heating dipole also reproduce the North Atlantic response.

The present study focuses on the mechanism that controls the transition of the Euro-Atlantic circulation responses to El Niño–Southern Oscillation (ENSO) from early (December) to late winter (February) for the period 1981–2015. A positive phase of ENSO induces a precipitation dipole with increased precipitation in the western and reduced precipitation in the eastern tropical Indian Ocean; this occurs mainly during early winter (December) and less so in late winter (February). It is shown that these interbasin atmospheric teleconnections dominate the response in the Euro-Atlantic sector in early winter by modifying the subtropical South Asian jet (SAJET) and forcing a wavenumber-3 response that projects spatially onto the positive North Atlantic Oscillation (NAO) pattern. On the contrary, during late winter, the response in the Euro-Atlantic sector is dominated by the well-known ENSO wave train from the tropical Pacific region, involving extratropical anomalies that project spatially on the positive phase of the Pacific–North American (PNA) pattern and the negative phase of the NAO pattern. Numerical experiments with an atmospheric model (an AGCM) forced by an Indian Ocean heating dipole anomaly support the hypothesis that the Indian Ocean modulates the SAJET and enforces the Rossby wave propagation to the Euro-Atlantic region in early winter. These phenomena are also investigated using the ECMWF SEAS5 reforecast dataset. In SEAS5, the ENSO interbasin tropical teleconnections and the response of the Euro-Atlantic circulation anomalies and their change from early to late winter are realistically predicted, although the strength of the early winter signal originated from the Indian Ocean is underestimated.

The role of the Indian Ocean heating anomalies in the ENSO teleconnection to South Asia and North Atlantic/European regions are investigated in the early winter season. Using re-analysis data, CMIP5 simulations and idealized numerical model experiments it is shown that the ENSO teleconnections in early winter in these regions are dominated by an ENSO-induced heating dipole in the Indian Ocean region. The Indian Ocean heating dipole leads to a Gill-type response in the South Asian region through Sverdrup balance. For a warm ENSO event, this response is a cyclonic upper-level anomaly that shifts the subtropical South Asian jet southward and increases precipitation in the that region. The cyclonic anomaly is the starting point of a stationary Rossby wavetrain that traverses the North Pacific and North American region and eventually reaches the North Atlantic. Here transient eddy feedbacks are likely to strengthen a response that spatially projects on the positive phase of the NAO and negative phase of the Atlantic ridge patterns. For cold ENSO events these anomalies are roughly opposite. The importance of the Indian Ocean heating dipole decreases towards late Winter due to a southward shift of the Indian Ocean rainfall climatology and a more dominant direct wavetrain from the central Pacific region.

In the current study, we analyzed the predictability of the tropical Indian Ocean precipitation anomalies and the North Atlantic European (NAE) circulation anomalies during the boreal early winter season using the ECMWF System-5 seasonal (SEAS5) prediction dataset. The observational analysis show that the boreal Autumn Indian Ocean dipole (IOD) conditions are the pre-courser for the early winter precipitation anomalies in the Tropical Western-Central Indian Ocean (TWCIO) region, which is well represented in the ECMWF-SEAS5 prediction system. Moreover, the ECMWF-SEAS5 skillfully predicts the Indian Ocean (IO) precipitation anomalies with some biases during the early winter. These biases tend to weaken the IO teleconnections to the NAE Region during the boreal early winter, mimicking the prediction skill of the NAE circulation anomalies. Furthermore, the positive TWCIO heating anomalies tend to favor the above normal Surface Air temperature (SAT) conditions over the NAE region, indicating to the mild early winter conditions over the region. The ECMWF-SEAS5 system shows a significant prediction skill of the surface temperature anomalies over the NAE region.

We apply the Lagrangian-based moisture back trajectory method to two reanalysis datasets to determine the moisture sources for wet season precipitation over the Arabian Peninsula, defined as land on the Asian continent to the south of the Turkish border and west of Iran. To accomplish this, we make use of the evaporative source region between 65 degrees W-120 degrees E and 30 degrees S-60 degrees N, which is divided into twelve sub-regions. Our comparison of reanalyses and multiple observations allows us to validate datasets and highlight broad-scale similarities in characteristics, notwithstanding some inconsistencies in the southwest AP. The results indicate north-to-south spatiotemporal heterogeneity in the characteristics of dominant moisture sources. In the north, moisture for precipitation is mainly sourced from midlatitude land and water bodies, such as the Mediterranean and Caspian Seas. Areas further south are dependent on moisture transport from the Western Indian Ocean and parts of the African continent. The El Nino-Southern Oscillation (ENSO) exhibits an overall positive but sub-seasonally varying influence on the precipitation variability over the region, with noticeable moisture anomalies from all major source regions. A significant drying trend exists over parts of the Peninsula, which both reanalyses partially attribute to anomalies in the moisture advection from the Congo Basin and South Atlantic Ocean. However, considerable uncertainty in evaporation trends over the terrestrial evaporative sources in observations warrants additional modeling studies to further our understanding of key processes contributing to the negative trends., Climate Dynamics, ISSN:0930-7575, ISSN:1432-0894

The interannual precipitation variability over Western Himalaya–Karakoram–Hindukush (WHKH) region has a significant impact on the freshwater resources, energy and agriculture sectors. Midlatitude storms play the role of an atmospheric bridge between large-scale circulation patterns and regional precipitation distributions during the winter (December–April) season. In this study, we investigated long-term changes between El Nino Southern Oscillation (ENSO) and storm activity as well as between ENSO and for precipitation, over WHKH for the period 1950–2015. The Melbourne University Objective Cyclone Identification and Tracking Scheme is used to track the midlatitude storms. A non-linear relationship is identified between the storm track frequency and precipitation over the WHKH region. The correlation between the storm frequency and precipitation increases significantly (95%) after the 1980s and reaches a maximum value of 0.53. Furthermore, 21-year running correlations also show non-linear relationships between ENSO and WHKH’s precipitation as well as for storm tracks frequency. The simultaneous correlation between storm tracks frequency (precipitation) and Nino3.4 index was insignificant 0.03 (0.25) in the earlier period from 1950 to 1979, which surged to 0.47 (0.60) in recent 30-years period from 1986 to 2015. Composites and regression analysis illustrate that ENSO modulated the midlatitude storm tracks over the WHKH region, which in turns impact more precipitation anomalies in the recent 30-years period. Moreover, Saudi King Abdulaziz University Atmospheric General Circulation Model (Saudi-KAU AGCM) also confirms the change in the relationship between ENSO and WHKH precipitation variability during the winter season between the two periods. These findings may have important implications for the seasonal rainfall predictability of the WHKH region.

Central Southwest Asia (CSWA) is a region with the largest number of glaciers, outside the polar regions in its northeast and the Arabian desert to its southwest. The region receives precipitation from November to April period also known as the wet season, which contributes to the regional freshwater resources. Mainly, El Niño–Southern Oscillation (ENSO) modulates the wet season precipitation over CSWA, with a positive relationship. However, the intraseasonal characteristics of ENSO influence are largely unknown, which may be important to understand the regional sub-seasonal to seasonal hydroclimate variability. We noted that the ENSO‐CSWA teleconnection varies intraseasonally and is a combination of direct and indirect positive influences. The ENSO direct influence is through a Rossby wave‐like pattern in the tail months of the wet season, while the indirect influence is noted through an ENSO‐forced atmospheric dipole of diabatic heating anomalies in the tropical Indian Ocean (TIO), which also generates a Rossby wave‐like forcing and persists throughout the wet season. The stronger ENSO influence is found when both direct and indirect modes are in phase, while the relationship breaks down when the two modes are out of phase. Moreover, the idealized numerical simulations confirm and reproduce the observed circulation patterns. This suggests that improvements in sub-seasonal to seasonal scale predictability requires the better representation of intraseasonal variability of ENSO teleconnection, as well as the role of interbasin interactions in its propagation.

El Niño Southern Oscillation (ENSO) have a weak influence on the seasonal mean Euro-Atlantic circulation anomalies during the boreal winter (Dec-Feb) season. Therefore, monthly ENSO teleconnections to Euro-Atlantic region were studied during the boreal winter season for the period 1981-2015 using reanalysis and hindcast dataset. It is shown that the ENSO-forced signal to the Euro-Atlantic circulation anomalies does not persist throughout the boreal winter season. During earlier winter, a positive ENSO phase strongly enforces rainfall dipole anomalies in the tropical Indian Ocean, with increased rainfall over the western tropical Indian Ocean, and reduced in the eastern tropical Indian ocean. This Indian Ocean rainfall dipole weakens in late winter. During early winter, the Indian Ocean rainfall dipole modifies the subtropical South Asian jet (SAJET) which forces a wavenumber-3 response projecting spatially onto the positive North Atlantic Oscillation (NAO) pattern. On contrary, during late winter, the response in the Euro-Atlantic sector is dominated by the well-known ENSO wavetrain from the tropical Pacific region, involving Pacific North American (PNA) pattern anomalies that project spatially on the negative phase of the NAO. Atmospheric General Circulation Model (AGCM) numerical experiments forced with an Indian Ocean heating dipole anomaly support the hypothesis that the Indian Ocean modulates the SAJET that enforces the Rossby wave propagation to the Euro-Atlantic region in early winter. Moreover, the ECMWF-SEAS5 hindcast dataset reproduces the observed ENSO-forced inter-basin tropical teleconnections transition from early to late winter and their response to the Euro-Atlantic circulation anomalies quite well. Therefore, it is important to understand the tropical inter-basin transition, which may lead to improve the sub-seasonal to seasonal variability and predictability of the Euro-Atlantic circulation anomalies.

The El Nino Southern Oscillation (ENSO) phenomenon is considered to be responsible for rainfall predictability in many regions. Some of its regional teleconnections, such as over the Arabian Peninsula in boreal summer (June–August) season, are not well studied. Therefore, in this paper, the relationship between the summer seasonal mean rainfall and ENSO is analyzed with the aid of a 15-member ensemble of simulations using the Saudi-King Abdulaziz University (KAU) Atmospheric Global Climate Model (AGCM) for the period 1981–2015. The southwestern peninsula rainfall is linked to the Sea Surface Temperature (SST) anomalies in the central-eastern pacific region. This relationship is established through an atmospheric teleconnection which shows upper-level convergence anomalies over the southern Arabian Peninsula compensating the central-eastern Pacific upper-level divergence anomalies for the warm ENSO phase, and vice-versa for the cold Phase. The upper-level convergence over the southern Arabian Peninsula leads to sinking motion, low-level divergence and consequently to reduced rainfall in the warm phase, while reverse happens in the cold phase. The correlation coefficient between the observed area-averged Nino3.4 index and a Southwestern Arabian Peninsula Rainfall Index (SARI) is −0.43 (statistically significant at 95%). Overall, model shows a potential predictability (PP) of 0.53 for the SARI region. Predictability during El Nino is higher than during La Nina events. This is not only because of a stronger signal, but also noise reduction contributes to the increase of PP in El Nino compared to that of La Nina years. Drought conditions are particularly alarming for a water-scarce region like the Arabian Peninsula. Therefore, the prediction of regional rainfall is of utmost importance for the socio-economic sectors such as water and agricultural resources, so the policy makers can cope with drought situations. In the summer season, the Arabian Peninsula receives rainfall mostly in the southwestern region. El Nino Southern Oscillation (ENSO) strongly influences the southwestern peninsula rainfall and drives drought conditions in its warm phase. In this study it is shown that models are able to realize this potential, and Arabian Peninsula summer rainfall may be therefore predictable on a seasonal basis.

An assessment of the Extreme Precipitation Events (EPEs) is important because of their potential impacts on the local livelihood, ecosystem, and water resource management. In the present study, the EPEs are defined by applying a non-parametric (95th percentile) approach over different climatic regions of Saudi Arabia using observed daily precipitation data for the period 1984–2016 obtained from 27 meteorological stations. The frequency, composite and correlation analyses are performed to evaluate the statistics of EPEs and their teleconnections. During the wet season (Nov-Apr), the frequency of the EPEs (≥25 mm/day) are higher over northeastern, central and southwestern coastal parts of Saudi Arabia. The composites and correlation analyses show that the EPEs over Saudi Arabia are associated with mid-latitude circumglobal wave train (CGT), which evolves a few days before the onset of EPEs and decays afterwards. The CGT modulates the upper-level trough over the Arabian Peninsula (AP) along with the surface anomalous low-pressure system that enhances moisture convergence, favoring the occurrence of EPEs over the region. The EPEs over Saudi Arabia are also associated with El Nino Southern Oscillation (ENSO), which shows that during the positive (negative) ENSO phase the frequency of EPEs increases (decreases) over the country. Moreover, the El Nino (with positive CGT) enhances the EPEs frequency over Saudi Arabia while vice-versa happens for La Nina (with negative CGT) phase.

The potential predictability (PP) of seasonal-mean 200-hPa geopotential height (Z200) anomalies in the Pacific–North American (PNA) region is examined for El Niño and La Niña separately by using 50 ensemble members of twentieth-century AGCM simulations. Observed sea surface temperature (SST) is prescribed for the period 1870–2009, and 14 El Niño and La Niña years after 1900 are selected for the present study. The domain-averaged value of PP for Z200 in the PNA region, as measured by the signal-to-noise ratio, for El Niño is about 60% larger than that of La Niña. Such a large PP is mainly due to a larger signal and partly to less noise during El Niño compared to that during La Niña . The transient eddy feedback to the PNA circulation anomalies is stronger during El Niño events (about 50%) than that during La Niña, and this difference in the transients contributes significantly to the different Z200 signals in the PNA region. The noise variance of the transients during El Niño is about 17% smaller than during La Niña, and thus transients play an important role in the reduction of Z200 noise during El Niño. Idealized experiments with the same spatial pattern but different signs of SST anomalies confirm the results mentioned above. Moreover, these experiments with several different amplitudes of positive and negative phases of tropical Pacific SST anomalies show that signals of Z200 and transients are proportional to precipitation anomalies in the tropical Pacific, and noises of Z200 for El Niño cases are somewhat smaller than the corresponding values of La Niña.

Interannual winter rainfall variability and its predictability are analysed over the Arabian Peninsula region by using observed and hindcast datasets from the state-of-the-art European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal prediction System 4 for the period 1981–2010. An Arabian winter monsoon index (AWMI) is defined to highlight the Arabian Peninsula as the most representative region for the Northern Hemispheric winter dominating the summer rainfall. The observations show that the rainfall variability is relatively large over the northeast of the Arabian Peninsula. The correlation coefficient between the Nino3.4 index and rainfall in this region is 0.33, statistically significant at the 90% level, suggesting potentially some modest predictability, and indicating that El Nino increases and La Nina decreases the rainfall. Regression analysis shows that upper-level cyclonic circulation anomalies that are forced by El Nino Southern Oscillation (ENSO) are responsible for the winter rainfall anomalies over the Arabian region. The stronger (weaker) mean transient-eddy activity related to the upper-level trough induced by the warm (cold) sea-surface temperatures during El Nino (La Nina) tends to increase (decrease) the rainfall in the region. The model hindcast dataset reproduces the ENSO–rainfall connection. The seasonal mean predictability of the northeast Arabian rainfall index is 0.35, statistically significant at the 95% level. It is shown that the noise variance is larger than the signal over the Arabian Peninsula region, which tends to limit the prediction skill. The potential predictability is generally increased in ENSO years and is, in particular, larger during La Nina compared to El Nino years in the region. Furthermore, central Pacific ENSO events and ENSO events with weak signals in the Indian Ocean tend to increase predictability over the Arabian region.

The interannual variability of Indian summer monsoon is probably one of the most intensively studied phenomena in the research area of climate variability. This is because even relatively small variations of about 10% to 20% from the mean rainfall may have dramatic consequences for regional agricultural production. Forecasting such variations months in advance could help agricultural planning substantially. Unfortunately, a perfect forecast of Indian monsoon variations, like any other regional climate variations, is impossible in a long-term prediction (that is, more than 2 weeks or so in advance). The reason is that part of the atmospheric variations influencing the monsoon have an inherent predictability limit of about 2 weeks. Therefore, such predictions will always be probabilistic, and only likelihoods of droughts, excessive rains, or normal conditions may be provided. However, even such probabilistic information may still be useful for agricultural planning. In research regarding interannual Indian monsoon rainfall variations, the main focus is therefore to identify the remaining predictable component and to estimate what fraction of the total variation this component accounts for. It turns out that slowly varying (with respect to atmospheric intrinsic variability) sea-surface temperatures (SSTs) provide the dominant part of the predictable component of Indian monsoon variability. Of the predictable part arising from SSTs, it is the El Niño Southern Oscillation (ENSO) that provides the main part. This is not to say that other forcings may be neglected. Other forcings that have been identified are, for example, SST patterns in the Indian Ocean, Atlantic Ocean, and parts of the Pacific Ocean different from the traditional ENSO region, and springtime snow depth in the Himalayas, as well as aerosols. These other forcings may interact constructively or destructively with the ENSO impact and thus enhance or reduce the ENSO-induced predictable signal. This may result in decade-long changes in the connection between ENSO and the Indian monsoon. The physical mechanism for the connection between ENSO and the Indian monsoon may be understood as large-scale adjustment of atmospheric heatings and circulations to the ENSO-induced SST variations. These adjustments modify the Walker circulation and connect the rising/sinking motion in the central-eastern Pacific during a warm/cold ENSO event with sinking/rising motion in the Indian region, leading to reduced/increased rainfall.