We evaluate the performance of a large ensemble of Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over South America for a recent past reference period and examine their projections of twenty-first century precipitation and temperature changes. The future changes are computed for two time slices (2040–2059 and 2080–2099) relative to the reference period (1995–2014) under four Shared Socioeconomic Pathways (SSPs, SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). The CMIP6 GCMs successfully capture the main climate characteristics across South America. However, they exhibit varying skill in the spatiotemporal distribution of precipitation and temperature at the sub-regional scale, particularly over high latitudes and altitudes. Future precipitation exhibits a decrease over the east of the northern Andes in tropical South America and the southern Andes in Chile and Amazonia, and an increase over southeastern South America and the northern Andes—a result generally consistent with earlier CMIP (3 and 5) projections. However, most of these changes remain within the range of variability of the reference period. In contrast, temperature increases are robust in terms of magnitude even under the SSP1–2.6. Future changes mostly progress monotonically from the weakest to the strongest forcing scenario, and from the mid-century to late-century projection period. There is an increase in the seasonality of the intra-annual precipitation distribution, as the wetter part of the year contributes relatively more to the annual total. Furthermore, an increasingly heavy-tailed precipitation distribution and a rightward shifted temperature distribution provide strong indications of a more intense hydrological cycle as greenhouse gas emissions increase. The relative distance of an individual GCM from the ensemble mean does not substantially vary across different scenarios. We found no clear systematic linkage between model spread about the mean in the reference period and the magnitude of simulated sub-regional climate change in the future period. Overall, these results could be useful for regional climate change impact assessments across South America.

This study examines decadal changes of the El Niñ o-Southern Oscillation (ENSO) influence on the interannual variability of northwest India winter precipitation (NWIWP). The analysis is based on correlations and regressions performed using India Meteorological Department (IMD) records based on station data and reanalysis fields from 1950 to 2008. The authors find that the interannual variability of NWIWP is influenced by the ENSO phenomenon in the recent decades. This conclusion is supported by a consistency across the different observational datasets employed in this study and confirmed by numerical modeling. A physical mechanism for such an influence is proposed, by which western disturbances (WDs) are intensified over northwest India because of a baroclinic response due to Sverdrup balance related to large-scale sinking motion over the western Pacific during the warm phase of ENSO. This response causes an upper-level cyclonic circulation anomaly north of India and a low-level anticyclonic anomaly over southern and central India. The cyclonic circulation anomaly intensifies the WDs passing over northwest India.

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 present study focuses on the mechanism that controls the transition of the Euro-Atlantic circulation responses to the 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 inter-basin 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 which projects 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 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 (AGCM) forced by an Indian Ocean heating dipole anomaly support the hypothesis that 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 re-forecast dataset. In SEAS5, the ENSO inter-basin 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 El Niño 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 Niño3.4 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 Niño is higher than during La Niña events. This is not only because of a stronger signal, but also noise reduction contributes to the increase of PP in El Niño compared to that of La Niña years.

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 Niño3.4 index and rainfall in this region is 0.33, statistically significant at the 90% level, suggesting potentially some modest predictability, and indicating that El Niño increases and La Niña decreases the rainfall. Regression analysis shows that upper‐level cyclonic circulation anomalies that are forced by El Niño 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 Niño (La Niña) 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 Niña compared to El Niño 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.

El Niño-Southern Oscillation (ENSO) modulates wet season (November-April) precipitation over Central Southwest Asia (CSWA), however, intraseasonal characteristics of its influence are largely unknown, which can be important for its subseasonal to seasonal hydroclimate predictability. Here we show that the ENSO-CSWA teleconnection varies intraseasonally and is a combination of direct and indirect positive influences. The direct influence is through a Rossby wave-like pattern in the tail months. The indirect influence is through an atmospheric dipole of diabatic heating anomalies in the tropical Indian Ocean (TIO) as a result of ENSO-forced response, which also generates a Rossby wave-like forcing and persists throughout the wet season. ENSO exerts its strongest influence when both direct and indirect modes are in phase, while the relationship breaks down when the two modes are out of phase. The atmospheric teleconnection through the atmospheric diabatic heating anomalies in the TIO is reproducible in numerical simulations. Plain Language Summary El Niño-Southern Oscillation (ENSO) exerts a strong positive influence on the precipitation variability over Central Southwest Asian (CSWA) region during the wet season that spans from November to April. We note that the ENSO influence varies intraseasonally and has two components, one directly through the equatorial Pacific region and one indirectly through the tropical Indian Ocean. In both cases, ENSO exerts its influence through Rossby wave-like atmospheric anomalies. When the two components are in phase, ENSO has the strongest influence while it is weakest when they are out of phase. These findings suggest that improvements in subseasonal 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.

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 (95 th 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 Niño Southern Oscillation (ENSO), which shows that during the positive (negative) ENSO phase the frequency of EPEs increases (decreases) over the country. Moreover, the El Niño (with positive CGT) enhances the EPEs frequency over Saudi Arabia while vice-versa happens for La Niña (with negative CGT) phase.