Variations of Energy Fluxes with ENSO, IOD and ISV of Indian Summer Monsoon Rainfall over the Indian Monsoon Region
Introduction
Indian summer monsoon (ISM), a dominant feature in south Asia, significantly affects the world population and socioeconomic status, has shown a predominant inter-annual variability. The variability of ISM rainfall rainfall (ISMR) and associated features are studied by several researchers using observations and model simulations. Several features such as the changes in the global circulation and sea surface temperature, movement of the Intra-Tropical Convergence Zone (ITCZ), direct and indirect effects of aerosols, global teleconnections, air-sea interactions, topography etc. plays an important role on ISMR variability (Gadgil et al. 2003; Lau and Kim, 2010; Boos and Kuang 2010; Bollasina et al. 2011; Sanap and Pandithurai, 2015; Karri et al., 2018; Mishra et al., 2018). Further, the heat and moisture sources from the Arabian Sea, Bay of Bengal, and Indian Ocean are crucial for the ISMR variability (Mohanty et al., 2005; Bhatla et al., 2011). The phases of El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events also plays dominant role on the strength and variability of the ISMR (Gadgil et al., 2003, Gadgil et al., 2004, Maity and Kumar, 2006; Xavier et al., 2007; Krishna Kumar et al., 2006; Raajevan and Pai, 2007; Kumar et al., 2007, Ramesh and Kamra, 2012; Roy and Collins, 2015; Azad and Rajeevan, 2016; Sahany et al., 2018; Srivastava et al., 2019).
El Niño (La Niña) is generally associated with a weak (strong) monsoon over the south Asia region (Webster and Yang, 1992; Larkin and Harrison, 2002). Warmer (colder) western (eastern) Pacific due to El Niño conditions are beneficial to ISMR due to the shift in convection from the west to eastern Pacific and the La Niña conditions involve the opposite features (Krishnamurthi et al., 1989; Deser and Wallace, 1990; Philander, 1990; Joseph et al., 1994; Harrison and Larkin, 1996, Harrison and Larkin, 1998; Okumura and Deser, 2010).
Further, the IOD events also influence the ISMR (Saji et al., Webster et al., 1999; Xiang et al., 2011). The positive IOD events in summer monsoon season bring more (less) rainfall over the Indian subcontinent (Indonesia and Australia) due to the warming (colder) of western (eastern) Indian Ocean (Xiang et al., 2011). Conversely, negative IOD with the warmer (colder) conditions over the tropical eastern (western) Indian Ocean obstructs the ISMR progression (Saji et al., 1999; Webster et al., 1999; Behera et al., 1999; Ashok et al., 2001).
The variability of different radiative fluxes over Indian subcontinent during the ISMR season is important to understand (Mohanty and Mohan, 1990; Krishnamurti et al., 1990; Mohanty et al., 2016 and many others). The rainfall variability over Indian subcontinent during monsoon season is highly dependent on the changes in outgoing long wave radiation (OLR), sea surface temperature (Krishnamurti et al., 1990). The relationship between the ISMR variability and the changes in heat budget over Indian Ocean studied by Mohanty et al. (1996). A band of low OLR over the southern India during the onset of monsoon reported by Sikka and Gadgil (1980). The latent heat release is the primary heat source to drive the ISMR circulation (Yanai et al., 1992; Li and Yanai, 1996). The low precipitation regions, such as the Arabian Peninsula and middle east, are associated with the regions of high OLR flux (Arkin et al., 1989).
Several studies estimated the heat sources and changes in the energy budget over the tropical oceans to assess the impact on climate change (Schaack and Johnson, 1994; Mohanty et al., 1994; Mohanty and Mohan, 1998; Shahi et al., 2011; Boucharel et al., 2015; Goswami et al., 2017). Several studies have also pointed that the ENSO-induced circulation anomalies would change the radiative flux and turbulence over South Asia during the monsoon season (Lau and Nath, 1996; Klein et al., 1999; Lau and Nath, 2000; Shinoda et al., 2004; Mayer et al., 2013, Mayer et al., 2014, Mayer et al., 2016; Boucharel et al., 2015). ENSO leads strong changes of the atmosphere-ocean energy budget more significantly in the tropical Pacific Ocean (Mayer et al., 2016). A movement of the heat across the Pacific and then to pole wards within the ocean is seen during the El Niño event indicate that the ENSO variability largely influenced by the sea surface temperature anomalies and heat flux changes in the tropical oceans (Shahi et al., 2011). However, it is unclear about the large-scale and high spatiotemporal variability of energy fluxes over the tropical oceans. In this context, very few studies have focused on the ENSO and IOD induced radiative fluxes variations over the Indian subcontinent at a broader scale during the summer monsoon season. Therefore, there is a need of understanding the spatiotemporal variability of the energy fluxes and the implication towards climate change for the Indian subcontinent and their relationship with the ISMR variability. In this study, we have tried to quantify the composites of surface fluxes anomalies based on ENSO and IOD events during the recent past years over the South Asian region by focusing the Indian region during southwest monsoon season.
This paper examines the changes in the absorbed short wave radiation at the top of the atmosphere (TOA), OLR at TOA, surface absorbed short wave downward solar radiation, surface thermal radiation downwards, surface net thermal radiation flux, surface Latent Heat (LH) flux, surface Sensible Heat (SH) flux, and their relationship with the changes in ISM seasonal rainfall i.e. June through September (JJAS). Further, we explain the role of monsoon teleconnections on the energy budget over a period of 35 years (1979 to 2013).
The reminder of this paper is organized as follows. Section 2 provides the details of the data sets used in this study. The results are presented in Section 3. The summary and conclusions are discussed in Section 4.
Section snippets
Methodology
The changes in heat budget components during the period 1979 to 2013 are being computed using Era-interim reanalysis data sets (Dee et al., 2011). We used different atmospheric variables such as LH, SH, surface net solar radiation flux, OLR at TOA, surface absorbed short wave downwards-solar radiation, surface thermal radiation downwards, surface net thermal radiation flux, TOA incident solar radiation and total precipitation. Based on the previous records (http://www.bom.gov.au/climate/iod/),
Results
The changes in energy flux components are examined for the years associated with El ENSO (Niño, La Niña), IOD events (positive and negative) and for the active and break phases of ISMR. The variations in fluxes and changes in precipitation with respect to normal years are presented and discussed.
Summary and conclusions
In this study, we report the changes in energy fluxes during the Indian summer monsoon (ISM) period (June to September) and its associated linkage to the ENSO & IOD events and active & break phases of ISM rainfall (ISMR).
Our results indicate that the absorbed short-wave radiation, net thermal radiation flux at the surface is increasing over Indian region, Arabian Sea, Bay of Bengal and Indian Ocean with maximum over eastern equatorial Indian Ocean, further, absorbed solar radiation flux and OLR
Data availability
The ECMWF data sets are available in https://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/ which is freely accessible. We have used different atmospheric variables such as LH, SH, surface net solar radiation flux, OLR at TOA, surface absorbed short wave downwards-solar radiation, surface thermal radiation downwards, surface net thermal radiation flux, TOA incident solar radiation and total precipitation. The description of the data used in present study are given in methodology
Authors statement
This is to state that during the revision process, we have got some technical help from two of our co authors (Popat salunke and Ruchi singh parihar). So we have included their names in the revised paper.
Declaration of Competing Interest
The authors declare that they do not have any conflict of interest.
Acknowledgements
We acknowledge the European Centre for Medium-Range Weather Forecasts (ECMWF) for making available the observational datasets. We wish to thank Dr. Saroj Kanta Mishra who suggested to work on this research problem, and helped us in the analyses. We also thank Abhishek Anand for some technical help in generating Fig. 1 of the paper. The referees provided very constructive and insightful suggestions, which led to substantial improvements in the final version. We also thank the editor for taking
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