On the relationship between ENSO patterns and winter precipitation over North and Central India

Yadav, Ramesh Kumar; Ramu, Dandi A.; Dimri, A. P.

doi:10.1016/j.gloplacha.2013.04.006

Cited by 53 publications

(33 citation statements)

References 31 publications

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“…Notice that El Niño and La Niña—as opposite phases of the same underlying phenomenon—tend to yield similar patterns but with opposite signals, although there are some exceptions; e.g., the Malay Archipelago and Northern Australia are teleconnected in MAM with La Niña but not with El Niño. Overall, the results are in agreement with previous studies [see, e.g., Ropelewski and Halpert , ; van Oldenborgh et al , ; Kayano et al , ; Shaman and Tziperman , ; Zhang et al , ; Yadav et al , ; Zhang et al , ].…”

Section: Enso‐driven Skillsupporting

confidence: 93%

Validation of 40 year multimodel seasonal precipitation forecasts: The role of ENSO on the global skill

Manzanas

Frías

Cofiño

et al. 2014

J. Geophys. Res. Atmos.

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The skill of seasonal precipitation forecasts is assessed worldwide-grid point by grid point-for the 40 year period 1961-2000, considering the ENSEMBLES multimodel hindcast and applying a tercile-based probabilistic approach in terms of the relative operating characteristic skill score (ROCSS). Although predictability varies with region, season, and lead time, results indicate that (1) significant skill is mainly located in the tropics-20 to 40% of the total land areas; (2) overall, September-October (March-May) is the most (least) skillful season; and (3) the skill weakens (with respect to the 1 month lead case) at 4 months lead-especially in June-August-although the ROCSS spatial patterns are broadly preserved-particularly in Northern South America and the Malay Archipelago. The contribution of El Niño-Southern Oscillation (ENSO) events to this 40 year skill is also analyzed, based on the idea that the seasonal predictability may be mainly driven by El Niño and La Niña precipitation teleconnections and, consequently, limited by the ability of the different seasonal forecasting models to accurately reproduce them. Results show that the ROCSS spatial patterns for (1) the full period 1961-2000 and (2) El Niño and La Niña events are highly correlated-over 0.85. Moreover, the observed teleconnection patterns are properly simulated (predicted)-with spatial correlations around 0.8-by most of the models at both 1 and 4 months lead time.

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Section: Enso‐driven Skillsupporting

confidence: 93%

Validation of 40 year multimodel seasonal precipitation forecasts: The role of ENSO on the global skill

Manzanas

Frías

Cofiño

et al. 2014

J. Geophys. Res. Atmos.

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“…Central Pacific ENSO events (also called ENSO Modoki events) are characterized by the maximum of the SST anomaly being located in the central Pacific, farther west than during canonical ENSO events. These two types of ENSO events lead to different effects on circulation and climate variability [ Weng et al ., ; Ashok and Yamagata , ; Feng et al ., , ; Feng and Li []; Xie et al ., ; Gouirand et al ., ; Tedeschi et al ., ; Yadav et al ., ]. Ashok et al .…”

Section: Introductionmentioning

confidence: 99%

Simulation of tropical tropospheric ozone variation from 1982 to 2010: The meteorological impact of two types of ENSO event

et al. 2016

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The effects of two types of ENSO events on tropical ozone (O3) variations from 1982 to 2010, and the mechanisms underlying these effects, were analyzed using observations and model simulations. Tropospheric column O3 anomalies (TCOA) during canonical El Niño were different from El Niño Modoki. Absolute TCOA values are larger during canonical El Niño than during El Niño Modoki in most regions. La Niña events were not separated into the different types because of their similarity in terms of sea surface temperature patterns. TCOA in La Niña showed a reversed dipole from canonical El Niño. During canonical El Niño, anomalous downward motion together with suppressed convection weakened O3 outflow from the troposphere, causing an increase in tropospheric O3 over western Pacific. Over central and eastern Pacific, decreased O3 concentrations resulted primarily from a change in net chemical production of O3. The change in net O3 chemical production relates to increased levels of HOx under wetter condition. During El Niño Modoki, transport and chemical fluxes were similar but weaker than during canonical El Niño. During La Niña, O3 anomalies and transport fluxes were the opposite of those during the El Niño Modoki. Stratospheric O3 played a key role in the development of O3 anomaly above 250 hPa during ENSO events, contributing >30% to the O3 anomalies. The change in free tropospheric O3 affected the O3 anomaly from 850 hPa to 200 hPa (60% of O3 anomaly). The contribution of O3 from planetary boundary layer was concentrated at the surface, with a contribution of <15%.

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“…During a warm ENSO event, a cyclonic upper‐level circulation anomaly is induced in the subtropical Asian region, which shifts the subtropical jet stream southward and strengthens the western disturbances passing across the Arabian region towards the east (e.g. Syed et al , ; Dimri, ; Yadav et al , ); this tends to increase the rainfall (Niranjan Kumar and Ourada, ; Kang et al , ). Therefore, the ENSO relationship with the region's rainfall also determines seasonal mean predictability, which is assessed in the current study.…”

Section: Introductionmentioning

confidence: 99%

Interannual rainfall variability and ECMWF‐Sys4‐based predictability over the Arabian Peninsula winter monsoon region

Abid

Kucharski

Almazroui

et al. 2015

Quart J Royal Meteoro Soc

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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.

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On the relationship between ENSO patterns and winter precipitation over North and Central India

Cited by 53 publications

References 31 publications

Validation of 40 year multimodel seasonal precipitation forecasts: The role of ENSO on the global skill

Validation of 40 year multimodel seasonal precipitation forecasts: The role of ENSO on the global skill

Simulation of tropical tropospheric ozone variation from 1982 to 2010: The meteorological impact of two types of ENSO event

Interannual rainfall variability and ECMWF‐Sys4‐based predictability over the Arabian Peninsula winter monsoon region

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