Indian Summer Monsoon Variability

Indian Summer Monsoon Variability: El Niño-Teleconnections and Beyond presents the improved understanding of Indian Monsoon teleconnections (ENSO and Non-ENSO), new advances, and preferred future steps. Special emphasis is given to non-ENSO teleconnections which have been poorly understood for decades. With growing monsoon rainfall extremes across the Indian Subcontinent, a new understanding of monsoon environmental factors that are driven remotely through teleconnections is a trending topic. Finally, the book reviews current understanding ofthe observational and modeling aspects of Indian monsoon teleconnections. This is a must-read for researchers and graduate students in atmospheric science and meteorology. Presents teleconnections associated with the Indian summer monsoon from a global perspective Discusses new pathways that connect the remote drivers to Indian summer monsoon variability Covers a wide range of mechanisms, processes, and science questions in relation to monsoon variability from interannual, decadal to climate change time scales

Indian Summer Monsoon Variability: El Niño-Teleconnections and Beyond presents the improved understanding of Indian Monsoon teleconnections (ENSO and Non-ENSO), new advances, and preferred future steps. Special emphasis is given to non-ENSO teleconnections which have been poorly understood for decades. With growing monsoon rainfall extremes across the Indian Subcontinent, a new understanding of monsoon environmental factors that are driven remotely through teleconnections is a trending topic. Finally, the book reviews current understanding of the observational and modeling aspects of Indian monsoon teleconnections. This is a must-read for researchers and graduate students in atmospheric science and meteorology. Presents teleconnections associated with the Indian summer monsoon from a global perspective Discusses new pathways that connect the remote drivers to Indian summer monsoon variability Covers a wide range of mechanisms, processes, and science questions in relation to monsoon variability from interannual, decadal to climate change time scales

The interest and level of research into climate variability has risen dramatically in recent years, and major breakthroughs have been achieved in the understanding and modelling of seasonal to interannual climate variability and prediction. At the same time, the documentation of longer term variability and its underlying mecha nisms have progressed considerably. Within the European Commission's Environment and Climate research programs several important projects have been supported in these areas - including the "Dec adal and Interdecadal Climate variability Experiment" (DICE) which forms the basis of this book. Within the EC supported climate research, we see an increasing importance of research into climate variability, as is evidenced in the upcoming Fifth Framework Programme's Key Action on Global Change, Climate and Biodi versity. This is because of the obvious potential socio-economic benefits from sea sonal to decadal scale climate prediction and equally important for the fundamental understanding of the climate system to help improve the quality and reliability of future climate change and mankind's current interference with it. The DICE group has performed important and pioneering work, and we hope this book will receive the wide distribution and recognition it deserves. We wel come the contributions from distinguished researchers from US, Japan and Canada to the EC's DICE group towards completing the scope of the book and as an exam ple of international cooperation which is essential in such a high-level scientific endeavor.

Variability of the Indian summer monsoon has increased significantly since the 1950s. For several regions across India, this means an increase in long dry periods with low or no rainfall, intermittent with short, intense spells of rainfall. These changes are particularly significant for the western, central and eastern states of India where more than 55% of the cultivated area is largely rainfed and where the adaptive capacity is the lowest. The large-scale secular changes in monsoon rainfall are attributed to the increase in global emissions of greenhouse gases and air pollutants. At the same time, local changes through urbanization, land use changes and deforestation have brought in a non-uniform response in these rainfall trends. Changes in the onset, duration and intensity of the rainfall call for a reassessment of the crop calendar and climate resilient measures for the food-water-energy sectors of the country. Global warming has also altered the relationship between sea surface temperatures and other predictors of monsoon rainfall, introducing increasing challenges and uncertainties in the monsoon forecasts. Climate projections indicate a further increase in the monsoon variability and a shortening of the rainy season in the future, though there is considerable disagreement between model simulations.

The Multiscale Global Monsoon System is the 4th and most up-to-date edition of the global monsoon book series produced by a group of leading international experts invited by the World Meteorological Organization's Working Group on Tropical Meteorology Research. The contents reflect the state of the knowledge of all scales of monsoon in the world's monsoon regions. It includes 31 chapters in five parts: Regional Monsoons, Extreme Weather, Intraseasonal Variations, Climate Change, and Field Experiments.

The Asian Summer Monsoon: Characteristics, Variability, Teleconnections and Projection focuses on the connections between the Indian Summer and East Asian Summer Monsoons, also including the South China Sea Summer Monsoon. While these systems have profound differences, their interactions have significant impacts on the climatic regimes in the region and throughout the world. In summer, the ASM engine pumps moisture transported across thousands of miles from the Indian and Pacific Oceans to the monsoon regions, producing heavy rains over south and east Asia and its adjacent marginal seas. This book reviews the different subsystems and their impact, providing guidance to enhance prediction models. Synthesizes the connections between the East Asian Summer Monsoon, the Indian Summer Monsoon and the Asian Summer Monsoon system Includes subsections on holistic characteristics, sub-seasonal and interannual variability, teleconnection patterns, and projections of future change Connects current theory and practice on Asian Monsoon forecasting, providing researchers with new skills and information to use in climate and weather forecasting

The role of the Indian and Pacific sea surface temperature (SST) variability in the intraseasonal and interannual variability of the Indian summer monsoon rainfall is examined by performing a set of regionally coupled experiments with the Climate Forecast System (CFS), the latest and operational coupled general circulation model (CGCM) developed at the National Centers for Environmental Prediction (NCEP). The intraseasonal and interannual variability are studied by isolating oscillatory and persistent signals, respectively, from the unfiltered daily rainfall anomalies using multi-channel singular spectrum analysis (MSSA). This technique identifies nonlinear oscillations, its variance and period without preconditioning the data with a filter and also helps to separate the intraseasonal and low frequency climate signals from the daily variability. It is found that, although the model has large amount of daily variance in rainfall, the combined variance of coherently propagating intraseasonal oscillations is only about 7% while the corresponding number in the observations is 11%. The model has three intraseasonal oscillations with periods around 106, 57 and 30 days. The 106-day mode has a characteristic large-scale pattern extending from the Arabian Sea to the West Pacific with northward and eastward propagations. These features are similar to the northeastward propagating 45-day mode found in the observations except for the longer period. The 57-day mode is more dominant in the region, 60[degrees]E-100[degrees]E and is strictly northward-propagating. The 30-day mode appears to be equivalent to the northwestward propagating oscillation in the observations. The dominant low frequency persistent signal in the region is due to the El Niño-Southern Oscillation (ENSO). The ENSO-related rainfall anomalies, however fail to penetrate into the Extended Indian Monsoon Rainfall (EIMR) region, and therefore, the ENSO-monsoon relationship in the model is weak. Regionally coupled simulations of the CFS have revealed that the northeastward propagating 106-day mode exists in the model with weak amplitude and reduced variance even when the air-sea interaction over the Indian Ocean is suppressed. However, this mode was not obtained when the Indian Ocean SST variability is reduced to climatology. The spatial structure and propagation of the 106-day mode appear to be unaffected by the Pacific SST variability; i.e., a simulation with climatological SST in the Pacific reproduced this mode. The 30-day northwestward propagating mode showed little change with respect to the Indian Ocean SST, but is dependent on the air-sea interactions over the west Pacific. Simulations using prescribed SST in the Indian Ocean showed that the spatial structure of the ENSO mode in the Indian Ocean is dependent on the air-sea interaction in that region. It is argued that the western Indian Ocean in this model is over-sensitive to atmospheric momentum fluxes and therefore cools down quickly in response to the ENSO-induced circulation anomalies. Further, this process creates a dipole pattern with cool (warm) western and warm (cool) eastern Indian Ocean during a La Niña (El Niño) event. This dipole prevents the ENSO anomalies from reaching the EIMR region and causes the incorrect ENSO-monsoon relationship. It is also found that such a dipole pattern, although with less variance is present even in the absence of the ENSO variability. The monsoon rainfall variability in the absence of the ENSO could be dictated by internal dynamics in this model.

Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.