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Karumuri Ashok, Hisashi Nakamura, and Toshio Yamagata

Abstract

Impacts of the ENSO and Indian Ocean dipole (IOD) phenomena on winter storm-track activity over the Southern Hemisphere are examined on the basis of the observed and reanalysis data for 1979–2003. The partial correlation technique is utilized to distinguish the impact of one phenomenon from that of the other. During an El Niño event, the subtropical jet stream tends to strengthen substantially, enhancing the jet bifurcation and thereby reducing storm-track activity over the midlatitude South Pacific and to the south of Australia. During a positive IOD event, the westerlies and storm-track activity also tend to weaken over southern Australia and portions of New Zealand. Thus both the positive IOD and, to a lesser extent, El Niño events act to reduce winter rainfall significantly over some portions of South Australia and New Zealand. Precipitation over the southeastern portion of the continent and over the northern portions of the two main islands of New Zealand is more sensitive to IOD. Significant reduction in precipitation associated with an El Niño event is seen over Tasmania. Over midlatitude South America, in contrast, the enhancement of the westerlies and storm-track activity tends to be more significant in a positive IOD event than in an El Niño event. It is demonstrated that despite the dominant influence of the Southern Hemispheric Annular Mode from a hemispheric viewpoint, the remote influence of ENSO and/or IOD on local storm-track activity can be detected in winter as a significant signal in particular midlatitude regions, including South Australia and New Zealand.

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Dandu Govardhan, Vadlamudi Brahmananda Rao, and Karumuri Ashok

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In this paper, the authors suggest a dynamical mechanism involved in the revival of the summer monsoon after breaks. In this context, the authors carry out a diagnostic analysis using the datasets from National Centers for Environmental Prediction Reanalysis 2 for the period 1979–2007 to identify a robust mechanism that typifies breaks and subsequent revival of monsoon. The authors find during the peak of significant breaks an anomalous southward shift of the subtropical westerly jet stream, which is invariably accompanied by an anomalous northward shift of a stronger-than-normal easterly jet. These major changes during a break facilitate an instability mechanism, which apparently leads to formation of a synoptic disturbance. Formation of such a disturbance is critical to the subsequent revival of the summer monsoon in 61% of the observed break-to-active revivals.

Computations of energetics and correlation analysis carried out suggest an increase in the eddy kinetic energy at the expense of the mean kinetic energy during the breaks, in agreement with the formation of the synoptic disturbance. This demonstrates that barotropic instability in the presence of a monsoon basic flow is the primary physical mechanism that controls the revival of the summer monsoon subsequent to the break events.

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Doo Young Lee, Joong-Bae Ahn, and Karumuri Ashok

Abstract

The authors propose the use of a “climate filter” concept to enhance prediction skill of a multimodel ensemble (MME) suite for the East Asian summer monsoon (EASM) precipitation and temperature at 850 hPa. The method envisages grading models on the basis of the degree of reproducibility of the association of EASM variability with a few relevant climate drivers with the respective model hindcasts for the period 1981–2003. The analysis identifies the previous winter Niño-3.4 and spring North Atlantic Oscillation indices as the most suitable climate drivers in designing a climate filter for evaluating models that replicate the observed teleconnections to EASM well. The results show that the hindcast skills of a new MME with the better-performing models are significantly higher than those from the nonperforming models or from an all-inclusive operational MME.

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Hongwen Kang, Chung-Kyu Park, Saji N. Hameed, and Karumuri Ashok

Abstract

A pattern projection downscaling method is applied to predict summer precipitation at 60 stations over Korea. The predictors are multiple variables from the output of six operational dynamical models. The hindcast datasets span a period of 21 yr from 1983 to 2003. A downscaled prediction was made for each model separately within a leave-one-out cross-validation framework. The pattern projection method uses a moving window, which scans globally, in order to seek the most optimal predictor for each station. The final forecast is the average of six model downscaled precipitation forecasts using the best predictors and will be referred to as “DMME.” It is found that DMME significantly improves the prediction skill by correcting the erroneous signs of the rainfall anomalies in coarse-resolution predictions of general circulation models. Although Korea’s precipitation is strongly influenced by local mountainous terrain, DMME performs well at 59 stations with correlation skill significant at the 95% confidence level. The improvement of the prediction skill is attributed to three steps: coupled pattern selection, optimal predictor selection, and the multimodel downscaled precipitation ensemble. This study indicates that the large-scale circulation variables, which are predicted by the current operational dynamical models, if selected, can be used to make skillful predictions of the local precipitation by using appropriate statistical downscaling methods.

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Karumuri Ashok, Zhaoyong Guan, N. H. Saji, and Toshio Yamagata

Abstract

The relative influences of the ENSO and Indian Ocean Dipole (IOD) events on the Indian summer rainfall were studied using observational data and an atmospheric general circulation model (AGCM). The composite analysis of rainfall anomalies demonstrates that the IOD, while significantly influencing the Indian summer monsoon rainfall, also significantly reduces the impact of ENSO on the Indian summer rainfall whenever these events with the same phase co-occur.

The AGCM experiments have shown that during an El Niño event, the Walker circulation over the tropical Indo–Pacific region is modulated; a low-level anomalous divergence center over the western Pacific and an anomalous convergence zone over the equatorial Indian Ocean are induced. Furthermore, an anomalous zone of convergence over the Myanmar and south China regions is induced during an El Niño event. These zones of anomalous convergence are complemented by anomalous divergence over the Indian region, causing anomalous subsidence and weakened rainfall. When a strong positive IOD event simultaneously occurs with El Niño, the latter's influence on the Indian monsoon is reduced by both poles of the IOD through the following mechanism: an anomalous divergence center, as compared to the summers when an El Niño alone occurs, is introduced in the eastern tropical Indian Ocean. From this center, the anomalous divergent flow crosses the equator, and this air, while weakening the El Niño–induced divergence over the western Pacific, also leads to convergence over the Indian monsoon region. This results in the reduction of the ENSO-induced subsidence and the related rainfall deficit over the eastern flank of the Indian monsoon trough region and adjoining regions to the east. On the other hand, over the western part of the tropical Indian Ocean sector, part of the anomalous ascending motion from the warm pole of the positive IOD event subsides just to the north of the equator, moves northward, ascends, and causes surplus rainfall. This reduces the ENSO-induced rainfall deficit over western India, the western part of the monsoon trough, and parts of Pakistan. The AGCM experiments also demonstrate that positive IOD events amplify the ENSO-induced dryness over the Indonesian region.

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Sushil K. Dash, Saroj K. Mishra, Sandeep Sahany, V. Venugopal, Karumuri Ashok, and Akhilesh Gupta
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Ibrahim Hoteit, Yasser Abualnaja, Shehzad Afzal, Boujemaa Ait-El-Fquih, Triantaphyllos Akylas, Charls Antony, Clint Dawson, Khaled Asfahani, Robert J. Brewin, Luigi Cavaleri, Ivana Cerovecki, Bruce Cornuelle, Srinivas Desamsetti, Raju Attada, Hari Dasari, Jose Sanchez-Garrido, Lily Genevier, Mohamad El Gharamti, John A. Gittings, Elamurugu Gokul, Ganesh Gopalakrishnan, Daquan Guo, Bilel Hadri, Markus Hadwiger, Mohammed Abed Hammoud, Myrl Hendershott, Mohamad Hittawe, Ashok Karumuri, Omar Knio, Armin Köhl, Samuel Kortas, George Krokos, Ravi Kunchala, Leila Issa, Issam Lakkis, Sabique Langodan, Pierre Lermusiaux, Thang Luong, Jingyi Ma, Olivier Le Maitre, Matthew Mazloff, Samah El Mohtar, Vassilis P. Papadopoulos, Trevor Platt, Larry Pratt, Naila Raboudi, Marie-Fanny Racault, Dionysios E. Raitsos, Shanas Razak, Sivareddy Sanikommu, Shubha Sathyendranath, Sarantis Sofianos, Aneesh Subramanian, Rui Sun, Edriss Titi, Habib Toye, George Triantafyllou, Kostas Tsiaras, Panagiotis Vasou, Yesubabu Viswanadhapalli, Yixin Wang, Fengchao Yao, Peng Zhan, and George Zodiatis

Abstract

The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.

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