The spatio-temporal characteristics of the observed warming of the Indian Ocean (IO) surface temperature and its statistical link to the IO Warm Pool (IOWP) are still unclear. This study discriminates the basin-wide monotonic warming mode of the IO surface from the internally and remotely forced variability. The trend pattern reported in this study reveals a radically different warming signal. It shows that the monotonic warming in the observed sea surface temperature (SST) has the spatial pattern of summer-mean SST and the Warm Pool as its most conspicuous feature. The highest warming (0.17∘C per decade) is in IOWP and not in the other IO regions identified in the previous studies. By 2070, IOWP will cover about 80% of tropical IO at the current latitudinal expansion rates. The mean states of equatorial SST, wind, and surface pressure are shifting towards an endless summer. Irrespective of the season, SST near Indonesia would remain above 31∘C by 2080 and beyond (i.e., more than 2.2∘C rise since 1950). This would substantially increase local rainfall intensity and frequency. Thus, IO is poised to play a more significant role in climate change. We also argue that the basin-wide warming is due to anthropogenic forces’ rectification by coupled processes in ocean-atmosphere mixed layers.
The COVID-19 pandemic has created a major threat to human beings and huge losses over the globe. In order to control the pandemic spread, almost all parts of the world imposed lockdown. The imposed lockdown drastically impacted on reduction in the atmospheric pollutions and also resulted in net decrease in aerosol optical depth (AOD) in the atmosphere. In this study, the reduction in the AOD during the COVID-19 lockdown over the Indian subcontinent is being assessed using the moderate resolution imaging spectroradiometer (MODIS) satellite data available in Giovanni version 4.34 developed by NASA. The long-term mean analysis is computed considering 20 years (i.e., 2000–2019) data on Terra platform with a temporal resolution of daily and monthly and spatial resolution of 1 degree. The dataset of AOD with a temporal resolution of monthly was used for investigation of AOD anomaly for March, April and May 2020, and the seasonal variation (March to May 2020) is also assessed. Similarly, the daily scale dataset was used to investigate the percentage change in AOD during pre-lockdown and lockdown period with respect to long-term mean. The key findings in the present study show that reduction in AOD level over Indian subcontinent is approximately 14.75% during the lockdown period with spatial variation in the magnitude from region to region. The level of AOD is greatly reduced in the northern part of India (~ 22.53%), whereas changes in the southern part of India are much less (~ -0.31%); this may be due to ongoing anthropogenic activities during the lockdown period in this region. Furthermore, a positive AOD anomaly was observed in the eastern and central regions of India (i.e., over the states of Odisha, Chhattisgarh, Telangana, Jharkhand, West Bengal, Part of Maharashtra and Karnataka). However, negative AOD anomaly was observed in the north and northwest regions of India, whereas not much change in the AOD anomaly in other parts of the country. The overall assessment of the AOD level shows a net decrease over the Indian subcontinent during the lockdown period, i.e., March to May 2020. This kind of assessment study will surely help the government for the sustainable policy decisions for atmospheric pollution control by implementing proper lockdown procedures over various parts of the country.
by T. C. Sunilkumar, Anil Earnest, Silpa K and Ronia Andrews
Unlike the other Himalayan plate boundary segments, the eastern Nepal to Bhutan Himalayan region is not known to have generated prominent shallow thrust faulting earthquakes, typical of the ongoing convergence. This region has unusual strike‐slip earthquake occurrences over the depth ranges of 40‐120 km, possibly indicating intraslab deformation. Here, we present for the first time a slip distribution model for the largest ever recorded intraslab strike‐slip earthquake in this region, the Mw 6.9 Sikkim event that occurred on 18th September 2011. Relying on kinematic source process modeling, our results indicate a NE‐SW trending, steeply dipping sinistral source zone within the underthrusting Indian slab. The rupture propagated radially, with a low rupture velocity of 1.7 km/s, breaking a large asperity of 20×20 km2 with a maximum slippage of 1.6 m. The rupture nucleated at a depth of 45 km and reached upper mantle depths. The computed co‐seismic stress drop value is 13.6 MPa. We suggest that most of the aftershocks occurred on the conjugate plane, possibly due to stress triggering. Stress inversion of focal mechanisms indicates a transpressive stress regime throughout the crust and pure strike‐slip regime in the upper mantle. We observed a unimodal distribution of earthquakes beneath the Higher Himalaya. This indicates a strong, brittle Indian slab and unravels a scenario of an eventual break‐up of the lithosphere; the key trigger might be variation in the convergence rates along the Himalayan arc.
by Smrutishree Lenka, Rani Devi, Chennemkeril Mathew Joseph & Krushna Chandra Gouda
There are several important large-scale oceanic and atmospheric processes like El Niño-Southern Oscillation (ENSO), Madden–Julian Oscillation (MJO), and Indian Ocean Dipole (IOD) which have significant impact on global weather and climate system. This article reviews the mechanism and dynamics of ENSO, MJO, and IOD processes and their impact on global and regional weather and climate particularly the Indian summer monsoon rainfall. Generally, these processes are coupled ocean–atmosphere phenomenon and associated dynamics control the global weather and climate system. Sea surface temperature (SST) anomaly in the central and equatorial pacific region respectively results the warm (El Niño) and cold (La Niña) events and it has strong impacts globally. Similarly, MJO is a dominant phase of intra-seasonal variability in the tropical region and also has significant impacts on the global system like strong wind, convective waves, extreme rainfall, cyclones, and ENSO. The IOD is often termed as the counterpart of pacific El Niño and La Niña in Indian Ocean which mainly measures the SST gradient between Arabian Sea and the eastern Indian Ocean. IOD also linked to ENSO and the shifting warm/cool pool results in the summer monsoon rainfall variability in the India Ocean as well as continental Indian region. All these phenomena have direct impact on the Indian monsoon circulation system, so in this work, these impacts are quantified using the India Meteorological Department (IMD) observed rainfall data over Indian subcontinent as a case study. This work also provides the review of the studies using observation and modelling to understand the dynamics of all the three processes. This review and analysis work will help in understanding the process feedback on the regional rainfall distribution and there is a need of near-future modelling research on these processes and their impacts on weather and climate system and associated sectors.
by Jagat Dwipendra Ray, M Sithartha Muthu Vijayan and Ashok Kumar
Accurate geodetic crustal deformation estimates with realistic uncertainties are essential to constrain geophysical models. A selection of appropriate noise model in geodetic data processing based on the characteristics of the geodetic time series being studied is the key to achieving realistic uncertainties. In this study, we report noise characteristics of a 12-yr long global positioning system (GPS) geodetic time series (2002–2013) obtained from 22 continuous mode GPS stations situated in north-east India, Nepal and Bhutan Himalayas which are one of the most complex tectonic regimes influenced by the largest hydrological loading and impacted with a load of the largest inland glaciers. A comparison of the maximum log likelihood estimates of three different noise models – (i) white plus power law (WPL), (ii) white plus flicker law (WFL) and (iii) white plus random walk noise – adopted to process the GPS time series reveals that among the three models, ∼74% of the time series can be better described either by WPL or WFL model. The results further showed that the horizontals in Nepal Himalayas and verticals in north-east India are highly correlated with time. The impact analysis of noise models on velocity estimation shows that the conventional way of assuming time uncorrelated noise models (white noise) for constraining the crustal deformation of this region severely underestimates rate uncertainty up to 14 times. Such simplistic assumption, being adopted in many geodetic crustal deformation studies, will completely mislead the geophysical interpretations and has the potential danger of identifying any inter/intra-plate tectonic quiescence as active tectonic deformation. Furthermore, the analysis on the effect of the time span of observations on velocity uncertainties suggests 3 yr of continuous observations as a minimum requirement to estimate the horizontal velocities with realistic uncertainties for constraining the tectonics of this region.
Ray, J. D., M. S. M. Vijayan, and A. Kumar (2019), Noise characteristics of GPS time series and their influence on velocity uncertainties, J. Earth Syst. Sci., 128(6), 146, doi:10.1007/s12040-019-1179-5.
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