सीएसआईआर-राष्ट्रीय डेटा विज्ञान एवं कृत्रिम बुद्धिमत्ता संस्थान

by Shantikumar S.Ningombam, Sethulakshmy E.S, SrideviJade, T.S.Shrungeshwara, Chiranjeevi G.Vivek, Dorje Angchuk, T.P.Prabhu and Tashi Tshering Mahay

The present work reports atmospheric opacity at 220 GHz over Indian Astronomical Observatory (IAO)-Hanle during 2006 to 2018. The opacity data were derived from the radiometric measurement of sky-brightness temperature as a function of zenith angle for every 10 min during day and night. Since the operating frequency range is not completely opaque during rainfall or cloudy atmosphere, observations are performed even during rainfall or cloudy sky conditions. The minimum opacities observed at the site varied from 0.06-0.07 at 1st quartile and 0.08-0.09 at 2nd quartile during December-January. Opacity at Hanle is linearly correlated with high temporal resolution GPS (Global Positioning System) Precipitable Water Vapor (PWV) with a correlation coefficient of about 0.8. The observed median opacity at Hanle has increased by 44% during the best observing months (October–March) and 24% over the annual data (October-September) with reference to the opacity observed during 2000–2003. Such increasing opacity trends are apparently due to effects of the dynamics of the regional and global hydrological cycle. In order to assess the impacts of the regional and global hydrological cycle, PWV obtained from AErosol RObotic NETwork (AERONET), satellite and reanalysis data were studied at nine high-altitude astronomical observatories spread spatially across the globe such as Atacama desert in Chile, Mauna Loa Observatory in Hawaii, Hanle and Merak in India, Ali and Yangbajing Observatories in Tibet, LLAMA in Argentina, and Dome A and Dome C in the Antarctic Plateau during 2003-2018. On an average, PWV trend over Atacama desert is increasing by 0.01 to 0.03 mm per year and at IAO-Hanle, Merak and Ali by 0.01 to 0.05 mm per year, indicating non uniform dynamic hydrological cycles. Interestingly, there is no noticeable PWV trend for the sites located in the Antarctic Plateau. During the four best observing months, PWV observed at Hanle, Merak and Ali sites have values lower than the Mauna Loa observatory by 0.14 mm and 0.56 mm at 1st and 2nd quartiles, respectively.

Source: https://doi.org/10.1016/j.jastp.2020.105404

by Rekha Bharali Gogoi, Govindan Kutty, V. Rakesh & Arup Borogain 

The impact of deploying a flow-dependent ensemble error covariance in Weather Research and Forecasting (WRF) three-dimensional variational (3DVAR) data assimilation (DA) system is examined for short-range rainfall forecasts during an Indian summer monsoon season. The flow-dependent background error covariance (BEC) is generated using a 50-member ensemble, which is further updated using the ensemble transform Kalman filter (ETKF). Assimilation is performed using a Hybrid variational-ensemble (“Hybrid”) and traditional 3DVAR DA system during the 4 weeks of July 2013. The forecasted wind, temperature, and rainfall from the assimilation experiments are verified against corresponding observations. The results indicate that the flow-dependent ensemble background error covariance in 3DVAR has systematically improved the forecasted wind and temperature when compared to the traditional 3DVAR. Similarly, rainfall forecast skill is superior in the Hybrid experiments relative to that of 3DVAR. Convection-permitting resolution rainfall forecast is validated against 746 telemetric rain gauge observations over the state of Karnataka. The Hybrid experiments show higher quantitative precipitation forecast skill than 3DVAR, particularly towards the later stages of data assimilation cycling. Spatially, the 3DVAR experiment shows a dry bias over the upper peninsular regions and a slight wet bias over the central and the northern Indian regions, while the magnitude of such wet and dry biases is smaller in forecasts from Hybrid analysis. Additionally, the westerly wind over the peninsular Indian landmass analyzed by 3DVAR is considerably weaker than that analyzed by the Hybrid experiments. This is proposed as a possible reason for the reduced dry bias in rainfall forecasts over the Indian landmass in Hybrid versus 3DVAR experiments.

Source: https://link.springer.com/article/10.1007/s00024-020-02537-6

by Satya Ganesh Kakarla, Kantha Rao Bhimala, Madhusudhan Rao Kadiri, Sriram Kumaraswamy and Srinivasa Rao Mutheneni

Abstract: Dengue fever is mosquito borne viral disease caused by dengue virus and transmitted by Aedes mosquitoes. In recent years the dengue has spread rapidly to several regions and it becomes a major public health menace globally. Dengue transmission is strongly influenced by environmental factors such as temperature and rainfall. In the present study, a climate driven dengue model was developed and predicted areas vulnerable for dengue transmission under the present and future climate change scenarios in India. The study also projected the dengue distribution risk map using representative concentration pathways (RCP4.5 and RCP8.5) in India in 2018–2030 (forthcoming period), 2031–2050 (intermediate period) and 2051–2080 (long period).

The dengue cases assessed in India from 1998 to 2018 and found that the dengue transmission is gradually increasing year over year. The temperature data from 1980 to 2017 shows that, the mean temperatures are raising in the Southern region of India. During 2000–2017 periods the dengue transmission is steadily increasing across the India in compare with 1980–1999 periods. The dengue distribution risk is predicted and it is revealed that the coastal states have yearlong transmission possibility, but the high transmission potential is observed throughout the monsoon period. Due to the climate change, the expansion two more months of dengue transmission risk occurs in many regions of India. Both RCP4.5 and RCP8.5 scenarios revealed that dengue outbreaks might occur at larger volume in Southern, Eastern, and Central regions of India. Furthermore a sensitivity analysis was performed to explore the impact of climate change on dengue transmission. These results helps to suggest appropriate control measures should be implemented to limit the spread in future warmer climates. Besides these, a proper plan is required to mitigate greenhouse gas emissions to reduce the epidemic potential of dengue in India.

Source: https://www.sciencedirect.com/science/article/pii/S0048969720338584

by Ramees R. Mir & Imtiyaz A. Parvez 

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.

Source: https://link.springer.com/article/10.1007/s11069-020-04068-8