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a Leading EOF pattern of summer ENSO based on the sea surface temperature for JA 1948-2002 over the region 20°S-20°N, 120E-90°W b Pattern of the summer NAO based on the leading EOF of mean sea level pressure for JA 1948-2002 over the region 25-70°N, 70°W-50°E. c One-point correlation maps showing the
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The effects of extratropical dynamics on the interannual variations in South-Asian Monsoon (SAM) are examined. Based on NCEP/NCAR
reanalysis and CRU precipitation data, a conditional maximum covariance analysis is performed on sea level pressure, 200hPa
geopotential heights and the SAM rainfall by removing the linear effects of El-Niño Southern Osc...
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... summer ENSO index is defined as the normalized principal component of the Leading EOF (explained vari- ance 57.5%) of SST over the region 20°S-20°N, 120°E- 90°W (Fig. 1a). We followed Ding and Wang (2005) and defined CGT index by taking the interannual variability of the mean JA 200-hPa geopotential heights averaged over the reference area to the northwest of India (Central Asia) (35°-40°N, 60°-70°E). Thus, the sign of CGT is positive during months when a ridge sits over west-central ...
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... structure of one-point correlation of CGT index and 200 hPa geopotential heights is shown in Fig. ...
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... defined the summer NAO index as in Folland et al. (2009), as the leading EOF (explained variance 28.1%) of MSLP over the region 25°-70°N, 70°W-50°E (Fig. ...
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... CGT cells used for the classification are the are shown in Fig. 1c as gray shaded rectangles covering the ...
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... leading mode of CMCA heterogeneous correlation maps, between mean sea level pressure over Europe and north Atlantic (bigger rectangle), the same domain used in construction of SNAO index Fig. 1b, following Folland et al. (2009) and precipitation over south Asia (smaller rectangle) is shown in Fig. 7. The correlation between the EC of MSLP and precipitation for leading mode of the CMCA is 0.68 with SCF of ...
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... structure in the MSLP is similar to Fig. 1b and the correlation between the EC of MSLP and SNAO index is 0.93, confirming that the structure is indeed SNAO. Again we see a north south structure in precipitation over northern Europe, Mediterranean and Sahel. There is also increased precipitation over Pakistan and western India and decreased precipitation over central India. ...
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... physical mechanism for the SNAO influence on SAM rainfall is similar to the CGT influence: In the southeastward extension of the teleconnection pattern towards South Asia there are upper-level ridges in the positive phases of CGT and SNAO (see Figs 1c and 2). 6 The ratio of variances after and before removing the linear effects of ENSO for a 200 hPa geopotential heights b precipitation ...
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... maps showing Fig. 9b. SNAO appeared as the second EOF (explained variance 21.5%) of MSLP over the region 25°-70°N, 70°W-50°E (Fig. 9a). To examine the response of SNAO on the upper atmosphere, the positive minus negative composites of 200 hPa geopotential heights for the years above (below) ?1 (-1) standard deviation of SNAO INDEX are shown in Fig. 10 for the Eurasian region. The structure is very similar to obser- vations and the cell over central Asia is also significant at the 95% confidence ...
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... precipitation composites of SNAO (Fig. 11) shows a dipole structure in precipitation over SA, which is similar to the structure seen in the CMCA Fig. 5 and also in PP case in the classification of CGT (Fig. 4). CGT composites of precipitation shows increased precipitation over Paki- stan and western India similar to the pattern seen in the CMCA Fig. 5. The EC-Earth simulations ...
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... The dry entrainment in the lower atmosphere, the strong westerlies in the upper atmosphere over WSA (Fig. 2), and the low heat budget in the adjacent Arabian Sea make conditions unfavorable for rain-producing weather systems (7 ). Several factors -such as atmospheric wave activity triggered by distant teleconnections, circumglobal wave patterns, or jet stream anomalies -can overcome this unfavorable background environment and provide conditions conducive to above-normal monsoons (8)(9)(10)(11). However, it is yet to be determined how much of a role these factors have played in recent extremes. ...
The monsoons in Pakistan have been exceptionally harsh in recent decades, resulting in extraordinary drought conditions and record flooding events. The changing frequency of extreme events is widely attributed to climate change. However, given this region's long history of floods and droughts, the role of natural climate variability cannot be rejected without a careful diagnosis. Here, we examine how oceanic and atmospheric variability has contributed to unusual precipitation distributions in West South Asia. Variations in sea surface temperatures in the tropical Pacific and northern Arabian Sea, and internal atmospheric variability related to the circumglobal teleconnection pattern and the subtropical westerly jet stream, explain more than 70% of monthly summer precipitation variability in the 21st century. Several of these forcings have co-occurred with record strength during episodes of extreme monsoons, which have exacerbated the overall effect. Climate change may have contributed to increased variability and the in-phase co-occurrences of the identified mechanisms, but further research is required to confirm any such connection.
... In addition, other aspects of subseasonal variability unrelated to the monsoon might be involved. For example, the NAO has been shown to modulate upper-level circulation over Eurasia (Di Capua et al., 2020a;Syed et al., 2012;Wang et al., 2018). Finally, the amplified wave pattern in Figure 3g was not produced in our causal maps, which suggests that perhaps local mechanisms (e.g., land-atmosphere or precipitation feedback processes) are involved (Dirmeyer et al., 2003;Guo et al., 2011;Jong et al., 2021;Koster et al., 2004Koster et al., , 2006. ...
Long‐range U.S. summer rainfall prediction skill is low. Monsoon variability, especially over the West North Pacific Monsoon (WNPM) and/or East Asian Monsoon (EAM) region, can influence U.S. Great Plains hydroclimate variability via a forced Rossby wave response. Here, we explored subseasonal monsoon variability as a source of predictability for Great Plains rainfall. The boreal summer intraseasonal oscillation (BSISO) is related to Great Plains convection and Great Plains low‐level jet (LLJ) anomalies as well as a cross‐Pacific wave train. Using a causal effect network, we found that the time between BSISO‐related geopotential height anomalies and Great Plains rainfall anomalies is about 2 weeks; therefore, BSISO convection may be a valuable forecast of opportunity for subseasonal prediction of Great Plains convection anomalies. More specifically, causal link patterns/maps revealed that the above‐normal weekly EAM rainfall, rather than WNPM rainfall or general geopotential height activity over the East Asia, was causally linked to Great Plains LLJ strengthening and active Great Plains convection the following week.
... IOD SRP Correlation 0.42*** 0.41*** Partial correlation 0.45*** 0.44*** the relationship between the IOD and Indian summer rainfall requires further study. Extratropical drivers, such as the shift of the jet stream over the North Atlantic (Chang et al., 2001;Chowdary et al., 2021b), the summer North Atlantic Oscillation (Bhatla et al., 2016;Syed et al., 2011), the Silk Road Pattern (SRP; Wang et al., 2021a) or circum-global teleconnection (CGT; Ding and Wang, 2005) can also significantly affect Indian summer rainfall. The SRP is an arch-shaped atmospheric teleconnection pattern along the upper-tropospheric Asian westerly jet (Ding and Wang, 2005;Enomoto, 2004;Lu et al., 2002;Wang et al., 2017) and resembles the CGT over the Eurasian continent (Zhou et al., 2019). ...
Variations in Indian summer rainfall pose a threat to water security that can cause widespread socio-economic impacts. Summer rainfall is affected by both tropical and extratropical circulation anomalies owing to India’s particular geographical location. Using observational, reanalysis, and CMIP6 model datasets, this study reveals the individual and joint effects of the Indian Ocean Dipole (IOD) and Silk Road Pattern (SRP) on the interannual variability of Indian rainfall during the summer to autumn transition (i.e., September). The results indicate that there is a consistent positive correlation between the IOD and SRP and the second mode of the Indian rainfall anomaly, which features a north–south inverse dipole pattern. During the positive phase of the IOD, the zonal sea surface temperature anomaly (SSTA) gradient of warm west and cold east in the equatorial Indian Ocean drives a Gill-type response, with an anticyclonic anomaly over southern India. This suppresses local convection and results in precipitation deficit across southern India. The SRP exhibits a baroclinic structure over west-central Asia, with an upper (lower) tropospheric anticyclonic (cyclonic) anomaly over west-central Asia (northern India) during its positive phase. This lower-level cyclonic anomaly is drastically amplified under the easterly vertical shear condition, favoring stronger moisture convergence and increased precipitation over northern India. The joint effect of the IOD and SRP explains nearly 29% of the Indian rainfall anomaly, higher than the individual contributions of the IOD (17%) or SRP (12%). These results highlight the need to consider the joint effects of tropical and mid-latitude anomalous drivers on precipitation patterns and provide the basis for more accurate simulation and prediction of Indian rainfall.
... The ISMI's intra-seasonal variability is linked to changes in the Tropical Convergence Zone (Pathak et al., 2017). On interannual time scales the South Asian monsoon is controlled by El-Niño Southern Oscillation (Fasullo and Webster, 2002;Syed et al., 2012;Webster and Yang, 1992). However, according to Syed et al. (2012), the two prevailing modes in the extra-tropics responsible for primary interannual variability in South-Asian Monsoon are Circumglobal teleconnection and Summer NAO. ...
... On interannual time scales the South Asian monsoon is controlled by El-Niño Southern Oscillation (Fasullo and Webster, 2002;Syed et al., 2012;Webster and Yang, 1992). However, according to Syed et al. (2012), the two prevailing modes in the extra-tropics responsible for primary interannual variability in South-Asian Monsoon are Circumglobal teleconnection and Summer NAO. According to (Ali et al., 2019b) All the regions shared significant inter-annual coherences with ENSO, however, R-II and IV shared prominent coherences ( Figure 6). ...
... The spring NAO activity, in particular, is accompanied with a meridional shift in the Atlantic jet stream, while positive phase of NAO is also linked to a poleward shift in the Atlantic jet stream in south Asia (Kim and Ha, 2021). According to Syed et al. (2012), the physical mechanism for the Summer NAO effect on the South Asian Monsoon is comparable to the Circumglobal Teleconnection (CGT) influence, since there are upper-level ridges in the positive phases of both the CGT and the Summer NAO. It has been observed, however, that North Atlantic SST creates a memory in the ocean, allowing the winter-spring NAO to influence the Indian summer monsoon and precipitation in the surrounding areas (Yu et al., 2021). ...
Monsoon and its teleconnection with earth system internal processes affect the spatiotemporal distribution of precipitation and water resources. In this paper, the wavelet coherence analysis has been utilized, a time and frequency domain methodology for comparing the spectral features of two independent time series superior to linear approaches. This technique is used to capture the significant modes of variabilities in the Indian Summer Monsoon Index (ISMI) and large‐scale climate indices (CIs) between ocean–atmosphere oscillations, like Indian Ocean Dipole (IOD), El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and Arctic Oscillation (AO) over Pakistan. Precipitation time series during 1960–2016 revealed significant interannual coherences with ISMI, whereas the remaining CIs (IOD, ENSO, PDO, SOI, NAO, AMO, and AO) revealed interannual, decadal and interdecadal coherences. However, AO revealed strongest coherences in R‐II, III, and VI at interdecadal scales among all CIs. Overall, the interannual cycles on ISMI are 2.8 years, IOD 1–5.3 years, PDO 0–5.3 years, SOI 1–5.3 years, NAO 0–5 years, AO 0–5 years, and AMO 0–8.3 years. Whereas, the remaining CIs shared interdecadal coherences over particular regions. The ISMI displayed coherences (except in the UIB) with the large‐scale CIs over various homogenous regions on an interannual scale. The dominant influence of ISMI is observed in R‐II and III; the significant coherences in R‐II ranged from ~8 to 32 months (~0.8–2.8 years). The IOD and NAO have major coherences than the remaining large‐scale CIs ranging from ~16 to 64 months (1.3–5.3 years). The AO has the most significant coherences observed in R‐II, III, and VI on the decadal/interdecadal scale from 128 months and above (almost 10–15 years). On a 1.0‐year timescale, all homogenous regions demonstrated strong intermittent coherence with ISMI, IOD, ENSO, PDO, SOI, NAO, AMO, and AO. These findings have substantial implications for decision‐makers and scientists in Pakistan looking to enhance water resource planning and operations in the face of future climate uncertainties.
... We note that the AMO modulates the SAMI directly through the interhemispheric multi-decadal bipolar see-saw set up by the north Atlantic (NA) SST associated with the AMO (Wang et al. 2015). Also, the multi-decadal modulation of the ISMR directly by the AMO through a stationary Rossby wave train set up by the NA SST during boreal summer (Syed et al. 2012;Krishnamurthy and Krishnamurthy 2016;Rajesh and Goswami 2020) is established. Therefore, there is an indirect pathway through which the AMO could produce a multi-decadal variability of the SAMI-ISMR relationship. ...
While the El Niño-Southern Oscillation and Indian Summer Monsoon Rainfall (ISMR) relationship is weak in recent years, a strong correlation between May Southern Annular Mode Index (SAMI) and June–July (JJ) ISMR is a southern hemispheric source of ISMR predictability. Here, using observed and reanalysis data, we find that the SAMI–ISMR relationship is non-stationary with a potential multi-decadal variability. Both during high/low correlation periods (1980–2010)/(1949–1979), a Southern Indian Ocean Dipole (SIOD) pattern of JJ sea surface temperature anomaly is found to reverse sign during strong and weak SAMI years. The changes in the strength and location of the northern pole of SIOD during the two time blocks are consistent with corresponding changes in the cross equatorial flow and monsoon south-westerlies together with change in SAMI–ISMR correlations. Our analysis indicates teleconnection pathways through which the Atlantic Multidecadal Oscillation (AMO) may be responsible for the multi-decadal swings of SAMI–ISMR correlations through modulation of the SIOD.
... For establishing the same, first, we need a physical mechanism connecting the NA SST and ISMR. A framework for such a physical teleconnection mechanism has emerged from several recent studies 28,31,32,[54][55][56] . According to it, positive (negative) NA SST drives a large-scale anticyclonic (cyclonic) barotropic vorticity over it on intraseasonal timescales and sets up an upper level zonal-wave number four Rossby wave-train that produce significant upper level anticyclonic (cyclonic) vorticity over the Indian region that in turn strengthen (weaken) low-level cyclonic vorticity associated with the Indian monsoon. ...
In the backdrop of overwhelming evidences of associations between North-Atlantic (NA) sea-surface temperature (SST) and the Indian summer Monsoon Rainfall (ISMR), the lack of a quantitative nonlinear causal inference has been a roadblock for advancing ISMR predictability. Here, we advance a hypothesis of teleconnection between the NA-SST and ISMR, and establish the causality between the two using two different nonlinear causal inference techniques. We unravel that the NA-SST and the El Nino and Southern Oscillation (ENSO) are two independent drivers of ISMR with the former contributing as much to ISMR variability as does the latter. Observations and climate model simulations support the NA-SST–ISMR causality through a Rossby wave-train driven by NA-SST that modulates the seasonal mean by forcing long active (break) spells of ISMR.
... Goswami et al. (2006a) proposed that the NA SST associated with the AMO sets up a stationary wave and influences the ISMR through modulating the tropospheric temperature gradient (TTG) over the Indian monsoon region, a mechanism that was supported by a number of modeling studies (Lu et al. 2006;Li et al. 2008). The nature of the stationary wave has been elucidated in the form of a Rossby wave train in some recent studies (Syed et al. 2012;Krishnamurthy and Krishnamurthy 2016). A couple of recent studies (Borah et al., 2020;Rajesh and Goswami, 2020) elucidated how the stationary Rossby wave train during June-September (JJAS) associated with the AMO influences the ISMR through its sub-seasonal evolution. ...
The significant multi-decadal mode (MDM) of the Indian summer monsoon rainfall (ISMR) during the past two millennia provides a basis for decadal predictability of the ISMR and has a strong association with the North-Atlantic (NA) variability with the Atlantic Multi-decadal Oscillation (AMO) as a potential external driver. It is also known that the annual cycles and interannual variability of ISMR and sea surface temperatures (SST) over the tropical Indian Ocean (IO) are strongly coupled. However, the role of local air–sea interactions in maintaining or modifying the ISMR MDM remains unknown. A related puzzle we identify is that the IO SST has an increasing trend during two opposite phases of the ISMR MDM, namely during an increasing phase of ISMR (1901–1957) as well as a decreasing phase of ISMR (1958–2007). Here, using a twentieth-century reanalysis (20CR), we examine the role of air-sea interactions in maintaining two opposite phases of the ISMR MDM and unravel that the Bjerknes feedback is at the heart of maintaining the ISMR MDM but cannot explain the increasing trend of SST in the tropical IO during the opposite phases. Large-scale low-level vorticity influence on SST and net heat flux changes through circulation and cloudiness changes associated with the two phases of the ISMR MDM together contribute to the SST trends. The decreasing trend of low-level wind convergence during the period between 1958 and 2007 is a determining factor for the decreasing trend of ISMR in the backdrop of an increasing trend of atmospheric moisture content. Consistent with the lead of the AMO with respect to ISMR by about a decade, the AMO drives the transition from one phase of ISMR MDM to another by changing its phase first and setting up low-level equatorial zonal winds conducive for the transition.
... Zhang & Delworth, 2006). The atmospheric bridge through which the NA SST influences the ISMR operates via a stationary Rossby wave train (Krishnamurthy & Krishnamurthy, 2016;Syed et al., 2012). Episodic barotropic vorticity over the NA facilitated by local SST drive sub-seasonal Rossby wave train that anchors long active (break) spells over the Indian monsoon region, thereby strengthening (weakening) the seasonal mean ISMR (Borah et al., 2020;Rajesh & Goswami, 2020). ...
How the Indian summer monsoon rainfall (ISMR) would change in future is of broader scientific interest and critical for adaptation to climate change and sustainable development for the vulnerable population of the region. An Emergent Constraint (EC), to correct the projections of ISMR by the Coupled Model Inter‐comparison Project‐6 (CMIP6) models for systematic model biases is urgently needed but has been lacking. Founded on an observed association between the multi‐decadal variability (MDV) of ISMR and North Atlantic (NA) sea surface temperature (SST), here we unravel a strong correlation between future changes in ISMR and biases in simulating the present‐day ISMR MDV. The new emergent constraint renders a 32% reduction in the multi‐model ensemble mean of projected ISMR increase, making the corrected future ISMR change (3.64 ± 2.5) %/K. The estimate based on this EC is robust and more reliable than previous estimates for basing policy interventions toward adaptation and mitigation.
... Global warming is influencing weather patterns (see, for instance, Syed et al. 2012;Latif et al. 2017). According to Climatic Research Unit in University of East Anglia (UEA) of UK, global temperatures are dramatically changing (Brohan et al. 2006). ...
... On the other hand, several attributes of DS events in other dust storm-prone regions of the world have been invested recently employing multiple techniques (see for instance, Ebrahimi-Khusfi et al. 2020, 2021aXu et al. 2020;Baltaci 2021;Labban and Butt 2021;Modarres 2021). In Pakistan, some climate change impacts are already established in the form of changes in temperature and precipitation patterns, and frequency of extreme weather events including floods and droughts on both seasonal and annual timescales (see for instance, Syed et al., 2012, Latif et al., 2017, and Adnan et al. 2020. In the scenario of changing precipitation rates and increasing fluctuations in temperatures, lack of new literature on DS activity in the country has created a research gap. ...
Diversified topography and uneven distribution of both temperature and precipitation contribute to formation of suitable synoptic conditions for incidents of dust storm (DS). This study presents time series plots of the parameters and spatial distribution of climatological means of seasonal and annual DS frequency (number of DS days) over Pakistan and its association with that of temperature and precipitation for the period 1986–2015. Monthly observational data of DS frequency recorded at 25 synoptic stations in the study area and gridded data of both temperature and precipitation gathered from Climatic Research Unit (CRU) for the period 1986–2015 are analyzed. It is found that DS frequency is the highest in pre-monsoon. Both the highest mean seasonal temperature and lowest mean seasonal precipitation in this season are one possible reason for it. It is also noticed that the number of stations which show positive correlation of DS frequency with temperature and negative correlation with precipitation is always considerably greater than the number of remaining stations in almost every season and annually. Moreover, based on results on correlations and trends of the three parameters, out of 25 stations, 12, 6, 2, and 10 are identified that would face increase in DS frequency in near future in pre-monsoon, monsoon, winter, and on annual timescale, respectively.
... A few of studies have highlighted both the importance of a WTV-like circulation anomaly in this location in summer and its relationship with the interplay and mutual feedbacks between mid-latitude westerly and South Asian summer monsoon systems (e.g., Ding and Wang 2005;Krishnan et al. 2009;Saeed et al. 2011;Syed et al. 2012;Mölg et al. 2017). In particular, the WTV in summer shows marked similarities with the west-central Asian centre of action in a northern hemisphere summer CGT, which is principally located within a waveguide associated with the westerly jet stream (Ding and Wang 2005). ...
The Western Tibetan Vortex (WTV) is a large-scale circulation pattern identified from year-to-year circulation variability, which was used to understand the causal mechanisms for slowdown of the glacier melting over the western Tibetan Plateau (TP). A recent argument has suggested the WTV is the set of wind field anomalies resulting from variability in near-surface air temperatures over the western TP (above 1500 m), which, in turn, is likely driven by the surface net radiation. This study thereby evaluates the above putative thermal-direct mechanism. By conducting numerical sensitivity experiments using a global atmospheric circulation model, SAMIL, we find a WTV-like structure cannot be generated from a surface thermal forcing imposed on the western TP. A thermally-direct circulation generated by the surface or near surface heating is expect to cause upward motions and a baroclinic structure above it. In contrast, downward motions and a quasi-barotropic are observed in the vertical structure of the WTV. Besides, we find variability of the surface net radiation (sum of the surface shortwave and longwave net radiation) over the western TP can be traced back to the WTV variability based on ERA5 data. The anticyclonic (cyclonic) WTV reduces (increases) the cloudiness through the anomalous downward (upward) motions, causes more (less) input shortwave net radiation and thereby more (less) surface net radiations, resulting in the warmer (cooler) surface and near-surface air temperature over the western TP. The argument is constructive in encouraging examination of the radiative balance processes that complements previous studies.
