Articles written in Journal of Earth System Science
Volume 117 Issue 2 April 2008 pp 169-178
The variability in the long-term temperature and sea level over the north Indian Ocean during the period 1958–2000 has been investigated using an Ocean General Circulation Model, Modular Ocean Model version 4. The model simulated fields are compared with the sea level observations from tide-gauges, Topex/Poseidon (T/P) satellite,
Volume 127 Issue 4 June 2018 Article ID 0046
In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative)TBO is associated with La Ni~na (El Ni~no) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Ni˜no-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysissuggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.
Volume 130 All articles Published: 18 March 2021 Article ID 0055 Research article
In this study, we have assessed the skill of decadal prediction of boreal spring (March–May) and summer (June–September) Surface Air Temperature (SAT) over India and its relation with Sea Surface Temperature (SST) in the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2) coupled model. The skill of CFSv2 is compared with CNRM (Centre National de Recherches Météorologiques) coupled model, which is the best among the selected CMIP5 (Coupled Model Intercomparison Project 5) models for long-lead forecasts (6–9 years) of global SSTs (with high skill). It is found that both models show significant skill in predicting 4-year mean SAT over central and southern peninsular India at 1–5 year leads in spring. During summer, significant skills for SAT over the northwest and southeast India are seen in CFSv2, whereas CNRM displayed significant skills over the north and central India at 1–5 years lead. The first Empirical Orthogonal Function (EOF) mode of SAT variability over India indicates a country-wide warming/cooling pattern in both observations and models for spring and summer. The analysis reveals that the decadal variability of SAT (EOF-1) over India is highly related to SST variations over the Indo-Pacific and North Atlantic regions. The strong convergence of low-level winds over the equatorial Indian Ocean and maritime continent accompanied by warm SST anomalies drive the northerly dry winds over India and favour warm SAT in both spring and summer. Further, changes in shortwave radiation also contributed to SAT variability over India. In general, the SAT relationship with SST in different parts of tropical and sub-tropical regions is underestimated in CFSv2 compared to the observations and CNRM in both boreal spring and summer. The models are able to represent the changes in the atmospheric circulation and related Indo-Western Pacific SST patterns reasonably well at the 1–5 years lead with some discrepancy. However, both models showed relatively low skills in capturing the relationship between SAT over India and equatorial Pacific SSTs. This might limit the skills of models in predicting decadal variations of SAT over India.
$\bullet$ Decadal prediction skill of the spring and summer Surface Air temperature (SAT) over India is examined in CFSv2 and CNRM models.
$\bullet$ Decadal variability of SAT over India is highly related to SST variations over the Indo-Pacific and North Atlantic regions.
$\bullet$ The models are able to represent the changes in the atmospheric circulation and related Indo-Western Pacific SST patterns reasonably well at the 1–5 years lead with some discrepancy.
$\bullet$ Models have low skills in capturing the relationship between SAT over India and equatorial and southern Pacific SSTs and this might limit the skills of models.
Volume 131, 2022
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