सीएसआईआर-राष्ट्रीय डेटा विज्ञान एवं कृत्रिम बुद्धिमत्ता संस्थान

by Ramees R. Mir, Imtiyaz A. Parvez, Gabi Laske & Vinod K. Gaur 

This paper presents estimated misorientation angles of broadband seismic sensors of the Kashmir-Zanskar network and their effects on anisotropy determinations and great-circle-path deviations. The misorientations were calculated from the difference between backazimuths of Rayleigh waves and those of the great-circle-arcs connecting the source and receiver. Waveforms of global Rayleigh waves extracted from the records of 13 broadband seismographs in the Kashmir-Zanskar region of Northwestern Himalaya, and 3 others around the region, were used to evaluate misorientation errors in each of these sensor installations. Three of the 16 were found to have orientation errors between ± 5 and 10° with respect to the geographic north, 4 between 10 and 16° and the remainder with <5°. These misalignments had resulted in leakage of a substantial amount of energy in the transverse component receiver functions which, after correction, led to sharper amplitudes and polarities. Indeed, the SKS-derived azimuths of the fast component were found to be quite sensitive to instrument misalignment, suffering ~ 16° shift from a ~ 15.5° error in orientation. A notable observation revealed by misalignment corrections was the substantial, up to 20°, off-great-circle arc deviations even along shorter path arrivals from regional events, offering a qualitative ordination of the region’s heterogeneities. The paper also presents probability distribution functions of the estimated power spectral density of ambient noise at each station compared with global high and low-noise models and near-source earthquake models. The results provide a first-order assessment of small earthquake detection capability of this network, down to M1.0, also confirmed by some of the smallest events located.

Source: https://doi.org/10.1007/s10950-022-10090-z

by C. Neethu & K. V. Ramesh 

Heat waves are increasing in frequency and exhibit high spatial variability in their distribution over India. There are limited studies focused on thermal indices over India due to the nonavailability of high-resolution (HR) climate data. Here we develop dynamically downscaled HR (4 × 4 km) daily climate information for the months of April to June during 2001–2016 using a regional climate model called Weather Research and Forecasting (WRF) Model, which are validated with station observations. The thermal comfort, heat stress, and its spatiotemporal variability and change over India are quantified in terms of indices like excessive heat factor (EHF), the heat index (HI), humidex, apparent temperature (AT), and wet bulb globe temperature (WBGT). The results show that there is an increasing trend in annual heat waves coverage (22,240 km2/year), annual frequency (0.07 days/year), and average intensity (0.04 °C/year) during 2001–2016. The spatial distribution of indices exhibits high spatial and temporal variability. The days with the severe threshold of indices are significantly increasing over north India at the rate of EHF (15.9%), HI (14.9%), humidex (15.9%), AT (13.4%), and WBGT (13.8%). The heat waves’ most vulnerable hotspots are on the parts of Rajasthan, Uttar Pradesh, Madhya Pradesh, and the coastal regions of Andhra Pradesh and Odisha. During heat waves, prolonged exposure under the sun will lead to adverse health impacts, and it is mostly observed over severe heat wave zone. These findings stress the need for developing suitable mitigation strategies for a sustainable ecosystem with minimum impact.

Source: https://link.springer.com/article/10.1007/s00704-022-03987-9 

by Adithya Samanth, V Rakesh, Smrati Purwar, S M Gavaskar, B Jagadeesha Pai & G N Mohapatra 

Karnataka, a state in south India with nearly 80% of the cultivated land under rainfed farming, is very much dependent on rainfall for agricultural productivity. The spatio-temporal variability in observed rainfall over Karnataka is investigated using various data analytical techniques such as parametric and non-parametric methods, rotated empirical orthogonal function (REOF), clustering and spectral analysis. The observed data used for studying rainfall variability is the daily taluk-wise telemetric rain gauge data for a period of 1960–2016. A similar pattern in trend is observed in annual and south-west monsoon (SWM) rainfall over Karnataka such that taluks in the western and northern parts showed a decreasing trend, whereas the south interior part showed an increasing trend. A significant increasing trend in rainfall was found during pre-monsoon seasons whereas the northeast monsoon (NEM) rainfall showed a decreasing trend. The REOF analysis also indicated an upward (downward) trend in SWM and annual over the northern (southern) Karnataka and a weakening trend in the NEM rainfall. Using the hierarchical clustering method, six homogeneous rainfall clusters were identified over Karnataka based on distribution and variability of rainfall. The spectral analysis over different clusters showed significant oscillations in the annual and SWM rainfall in the 1970s and recent decades except the Western Ghat region where oscillations were much weaker during recent decades. The pre-monsoon and NEM rainfall also showed strong variability with a periodicity of 2–4 years in recent decades. The findings of this study can have implications while designing water resource management strategies across various sectors in Karnataka.

Source: https://link.springer.com/article/10.1007/s12040-022-01810-7

by Rameshan Kallummal

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.

Source: https://doi.org/10.1007/s00382-022-06181-9