by A. K. Nekrasova, V. G. Kossobokov, I. A. Parvez and X. Tao
Abstract
The distribution of the number of seismic events by magnitudes—the Gutenberg–Richter frequency–magnitude relation—is of paramount importance for seismic hazard assessment of a territory. The generalization of the Gutenberg–Richter relation—the Unified Scaling Law for Earthquakes (USLE) proposed in 1988 makes it possible to take into account the pattern of epicentral distribution of seismic events when changing the spatial scale of the analysis. This is extremely important for adequate downscaling of the frequency of occurrence into a smaller area within the territory under study (e.g., in the megalopolis). In 2002, Per Buck suggested a dual formulation of USLE where, instead of the number of earthquakes over a certain period of time, the reciprocal of their frequency of occurrence—the time between seismic events—is used. The same year, the Institute of Earthquake Prediction Theory and Mathematical Geophysics of the Russian Academy of Sciences developed a modified algorithm for robust estimation of USLE parameters referred to as Scaling Coefficients Estimation (SCE) for producing seismic hazard maps of territories prone to seismic effects. This brief review is focused on the use of the USLE approach to the assessment of seismic hazard and associated risk.
There have been many studies on iron as a limiting nutrient for productivity in the World Ocean, but only a few studies have been done in the Arabian Sea on iron limitation. Sensitivity of primary productivity, chlorophyll, nitrate, pCO2 and carbon Cux in the Arabian Sea to one of the parameters related to iron limitation has been investigated using a three-dimensional coupled biogeochemical model (TOPAZ) embedded in Modular Ocean Model (MOM) in the global domain, for climatology and interannual variability. Initially, the model results are evaluated for many of the biogeochemical components using data from World Ocean Atlas, satellites and cruises in the Arabian Sea. It is noticed that model results capture spatial and temporal variations of some of the biogeochemical components and Cuxes in the north Indian Ocean. Subsequently, it is shown that micronutrient iron plays a significant role on the growth of phytoplankton, utilization of nutrients, pCO2 in the ocean and carbon Cux across the air–sea interface in north and north-west regions of the Arabian Sea.
Ten-year climatology of physical properties of convective echoes during pre-monsoon season over south peninsular India and neighborhood are studied using Precipitation Radar dataset onboard Tropical Rainfall Measuring Mission satellite. Attenuation corrected radar reflectivity (Ze) is used to define an intense convective echo (ICE) which is a group of two or more contiguous convective pixels with Ze exceeding 30 dBZ. Height distribution of ICE is right skewed, single modal with mean and median as 7.8 and 7.3 kms. The ICE with area in range of more than 102 to 103 km2 (C) are most frequent (58.5%) followed by smallest scale (D) having area ≤ 102 km2 (37.2%). Large ICE’s (B/C scale) are less frequent (4.2%). Mean areas of ICE’s in D, C and B/C scales are 72.7, 279 and 1932 km2, respectively. The relation between height and area is linear indicating that taller ICE’s are broader. The mean top heights of D, C and B/C scales are 5.5, 8.7 and 14.2 km, respectively. Frequency distributions of the height of 30 and 40 dBZ show single peaks at 5.5 and 4.75 km. Mean heights of 30 dBZ and 40 dBZ are 5.7 and 4.8 km while median heights are 5.5 and 4.7 km. Their cumulative frequency distribution shows that 6 and 3% of ICE cross 10 km height. Reflectivity structures of ICE show that systems over land are intense compared to that over ocean.
Many applications, from agricultural planning (such as crop choice) to estimation of hydro-power and surface water availability require quantitative precipitation forecasts (QPF). While a large number of studies have addressed the problem of forecasting seasonal Indian summer monsoon (ISM) rainfall over the decades, the emphasis generally has been on simulation and forecasting of rainfall anomalies from long-period mean. However, given the trends in monsoon rainfall, the procedure of considering anomalies has inherent errors; thus reconstruction of actual rainfall from the anomalies does not necessarily provide accurate information. Most QPF have been attempted at short-range forecasts, with a variety of techniques like model output statistics. This work represents evaluation of an atmospheric Variable Resolution General Circulation Model (VRGCM) for QPF during monsoon season. The VRGCM, with variable grid resolution provides relatively high (~ 50 km) resolution over the ISM region, has been validated over all India as well as in different regions like Central and North India, South India, North East India for seasonal forecast of monsoon rainfall. VRGCM simulated QPF appears to provide comparable information as that of anomaly forecasts of monsoon over different regions in India. The forecast skill is appreciable, with significant correlation at all India, South India and North East India regions. The Root Mean Square Error of VRGCM in forecasting quantitative rainfall overall India and Central North India is very low and bit high over South and North East region of India. The performance of VRGCM in forecasting the rainfall in extreme (deficit or excess) monsoon years is also very high with phase synchronisation of 89% in the inter annual variability of rainfall during monsoon at all India scale while the value is about 57%, 76% and 55% over Central North, South and North East India region, respectively.
Abstract: This study presents estimates of bedrock level peak ground motion at 2346 sites on a regular grid of 0.2° × 0.2° in northwestern (NW) Himalaya from 543 simulated sources, using the stochastic finite-fault, dynamic corner frequency method, with particular emphasis on Kashmir Himalaya. The earthquake catalogue used for simulating synthetic seismograms is compiled by including both pre-instrumental and instrumental era earthquakes of magnitude Mw ≥ 5, dating back to 260 AD. Acceleration time series thus generated are then integrated to obtain velocity and displacement time series, which are all used to construct a suite of hazard maps of the region. Expected PGA values for the Kashmir Himalaya and Muzaffarabad are found to be ~ 0.3–0.5 g and for the epicentral region of the 1905 Kangra event, to be 0.35 g. These values are consistent with other reported results for these areas e.g., Khattri et al. (Tectonophysics 108:93–134, 1984) and Parvez et al. (J Seismol, 2017. https://doi.org/10.1007/s10950-017-9682-0). The PGA values estimated in this study are in general found to be higher than those implied by the official seismic zoning map of India produced by the Bureau of Indian Standards (BIS in Indian Standard criteria for earthquake resistant design of structures part 1 general provisions and buildings (Fifth Revision), vol 1, no 5. Indian Standard, 2002). Even the acceleration-derived intensities for most regions are found to be higher compared with those observed, which apparently is due to the use of a longer duration catalogue (260 AD–2016) for simulation not covered by the observed intensity catalogue and higher magnitude ascribed to historical events. Major events in Kashmir Himalayas, such as those of 1555, 1885 and 2005, are simulated individually to allow comparison with available results. Simulated pseudo-acceleration and velocity response spectra for three sites near the 2005 Kashmir earthquake for which site conditions were available (Okawa in Strong earthquake motion recordings during the Pakistan, 2005/10/8, Earthquake, 2005. https://iisee.kenken.go.jp) are compared with observed spectra. This study provides a first-order ground motion database for safe design of buildings and other infrastructure in the NW Himalayan region.
To synergize the Transdisciplinary Pan-CSIR expertise and build a unified platform that embodies a rich set of big data enabling technologies and services with optimized performance to facilitate data intensive scientific discovery in the country.
Mission:
To Pioneer data driven interdisciplinary research in diverse fields through state-of-the-art data science ecosystem and impactful industrial partnerships for the betterment of Society.
Mandate:
To develop cutting edge data science products as a horizontal across the CSIR Themes and position as an Institute of Excellence in Bigdata and Artificial Intelligence.
Student Programme for Advancement in Research Knowledge (SPARK)
SPARK is intended to provide a unique opportunity to bright and motivated students of reputed Universities to carry out their major project/thesis work and advance their research knowledge in mathematical modelling and simulation of complex systems. The programme is intended to increase the interaction between scientists and faculty members of academic institutes along with their students towards a long term research collaboration. Click here to apply for SPARK.
