Modelling for Science, for a better future - some recent outcomes
Evaluation of a GCM in seasonal forecasting of extreme rainfall events over continental India
by K.C.Gouda, S.Nahak and P.Goswami
In recent decades, vulnerability to disasters due to Extreme Rainfall Events (ERE) has increased manifold over continental India during the south west monsoon season. It is a very important and challenging task for the advanced forecasting of such EREs on seasonal time scales which will provide enough lead time for the disaster management, smart agricultural practice and pro-active health care for example. Researchers around the world are looking at ways to improve the skill and reliability of forecasts of EREs on a range of time scales from daily to seasonal and General Circulation Models (GCMs) are now widely used to forecast EREs on a seasonal time scale. In the present study, a variable resolution general circulation model (VRGCM) is being configured and evaluated for the seasonal prediction of the number of EREs in three different categories depending upon the threshold of daily rainfall over the continental India during the monsoon (JJA) season for 16 years (i.e. 1998–2013). The skill of model prediction is evaluated by validating the simulated ERE counts with the high resolution gridded rainfall data available from the India Meteorological Department (IMD). The spatio-temporal analysis, seasonal cycle and the Interannual variability of the of EREs over continental India using GCM simulation and IMD observations shows good agreement and the model configuration has potential skill for the simulation of EREs in seasonal prediction mode and the present results provide the application of VRGCM for seamless prediction of EREs over India.
Source: https://www.sciencedirect.com/science/article/pii/S221209471730049X
Temperature dependent transmission potential model for chikungunya in India
by Satya GaneshKakarla, RajasekharMopuri, Srinivas Rao Mutheneni, Kantha Rao Bhimala, Sriram Kumaraswamy, Madhusudhan Rao Kadiri, Krushna Chandra Gouda and Suryanaryana Murty Upadhyayula
Chikungunya is a major public health problem in tropical and subtropical countries of the world. During 2016, the National Capital Territory of Delhi experienced an epidemic caused by chikungunya virus with >12,000 cases. Similarly, other parts of India also reported a large number of chikungunya cases, highest incidence rate was observed during 2016 in comparison with last 10 years of epidemiological data. In the present study we exploited R0 mathematical model to understand the transmission risk of chikungunya virus which is transmitted by Aedes vectors. This mechanistic transmission model is climate driven and it predicts how the probability and transmission risk of chikungunya occurs in India. The gridded temperature data from 1948 to 2016 shows that the mean temperatures are gradually increasing in South India from 1982 to 2016 when compared with data of 1948–1981 time scale. During 1982–2016 period many states have reported gradual increase in risk of chikungunya transmission when compared with the 1948–1981 period. The highest transmission risk of chikungunya in India due to favourable ecoclimatic conditions, increasing temperature leads to low extrinsic incubation period, mortality rates and high biting rate were predicted for the year 2016. The epidemics in 2010 and 2016 are also strongly connected to El Nino conditions which favours transmission of chikungunya in India. The study shows that transmission of chikungunya occurs between 20 and 34 °C but the peak transmission occurs at 29 °C. The infections of chikungunya in India are due to availability of vectors and optimum temperature conditions influence chikungunya transmission faster in India. This climate based empirical model helps the public health authorities to assess the risk of chikungunya and one can implement necessary control measures before onset of disease outbreak.
Source: https://www.sciencedirect.com/science/article/pii/S0048969718329577
Seismic hazard and probability assessment of Kashmir valley, northwest Himalaya, India
by Rakesh Chandra, Javid Ahmad Dar, Shakil Ahmad Romshoo, Irfan Rashid, Imtiyaz A. Parvez, Sareer Ahmad Mir and Midhat Fayaz
Seismic hazard analysis of the northwest Himalayan belt was carried out by using extreme value theory (EVT). The rate of seismicity (a value) and recurrence intervals with the given earthquake magnitude (b value) was calculated from the observed data using Gutenberg–Richter Law. The statistical evaluation of 12,125 events from 1902 to 2017 shows the increasing trend in their inter-arrival times. The frequency–magnitude relation exhibits a linear downslope trend with negative slope of 0.8277 and positive intercept of 4.6977. The empirical results showed that the annual risk probability of high magnitude earthquake M ≥ 7.7 in 50 years is 88% with recurrence period of 47 years, probability of M ≤ 7.5 in 50 years is 97% with recurrence period of 27 years, and probability of M ≤ 6.5 in 50 years is 100% with recurrence period of 4 years. Kashmir valley, located in the NW Himalaya, encompasses a peculiar tectonic and structural setup. The patterns of the present and historical seismicity records of the valley suggest a long-term strain accumulation along NNW and SSE extensions with the decline in the seismic gap, posing a potential threat of earthquakes in the future. The Kashmir valley is characterized by the typical lithological, tectono-geomorphic, geotechnical, hydrogeological and socioeconomic settings that augment the earthquake vulnerability associated with the seismicity of the region. The cumulative impact of the various influencing parameters therefore exacerbates the seismic hazard risk of the valley to future earthquake events.
Source: https://link.springer.com/article/10.1007/s11069-018-3362-4
More Articles...
- Moisture Supply from the Western Ghats Forests to Water Deficit East Coast of India
- India plate angular velocity and contemporary deformation rates from continuous GPS measurements from 1996 to 2015
- Parameterization of water vapor using high-resolution GPS data and empirical models
- Structural insights from geodetic Global Positioning System measurements in the Darjiling-Sikkim Himalaya
- Seismic hazard and risk assessment based on Unified Scaling Law for Earthquakes: thirteen principal urban agglomerations of India