by Rani Devi, K. C. Gouda & Smrutishree Lenka
By exploring the multifaceted physical mechanisms underlying hot extreme events, the way for informed strategies to mitigate their impacts and enhance the nation's resilience in the wake of a changing climate can be paved. The long-term spatio-temporal variability of hot extremes analysis found an increasing trend (0.001 °C) of DMXT over whole Indian region except the eastern parts (Indo-Gangetic plains). The hot day is noted when DMXT > 40 °C, DMXT > 37 °C, DMXT > 35 °C and also DMXT is above the 90th percentile at each grid point in the plains, hilly, coastal region of India. The temperature tendency equation has been computed to identify the role of various physical processes driving the local extreme temperature changes in India. The analysis showed that the surface adiabatic warming found to be one of the prominent drivers of hot extreme events over India. The impact of El Niño-Southern Oscillation (ENSO) phases on the frequency of hot extreme days at local scale in India are quantified. The linear trend of hot days has been found increasing at a rate of 0.14/year, 0.08/year and 0.06/year in El Niño, La Niña and neutral years respectively. Similarly, the DMXT anomaly found to be 0.4 °C higher in El Niño phase as compared to La Niña phase. The results infers that the chances of hot days occurrence are increased (decreased) by 38% (16% and 8%) in El Niño (La Niña and neutral) period. The advection of hot air by westerlies into the Indian region leads to an increase in temperature. The composite elevated (dropped) geopotential height at 500 hPa showed the presence of high (low) pressure systems which leads to hot days occurrence over western, southern and central (northern, north western) India, where winds are westerlies (easterlies) in El Niño (La Niña) phase of ENSO. This reversal of wind is linked with the movement of warm sea surface temperature from western to eastern Pacific Ocean. Comprehending the dynamics of hot extremes in the India is vital for the development of strategies to mitigate the adverse impacts on various sectors, including agriculture, health, water resources, and infrastructure.
Source: https://doi.org/10.1007/s00477-024-02744-w
by Bishnupada Sethi, Krushna Chandra Gouda, Sarat Chandra Sahu, Manas Kumar Mallick, Amrutanshu Panigrahi & Satish Kumar Samal
In the recent years, extreme temperature i.e. cold in winter and warm in summer has been observed in the coastal Odisha state in the east part of India. Hydro-meteorological disasters such as floods, droughts, heat waves and cold spells being experienced nowadays are unprecedented in living memory. In this work the climate variability over the coastal Odisha region is quantified considering the temperature parameter. A climate departure index (CDI) of three versions (simple, absolute and least-square) are calculated using monthly, annually and seasonally maximum, minimum as well as mean temperature form seven stations in the costal Odisha for the period 1969 to 2018 for assessing the degree of normal/unusual/extreme of a particular year in compared to the long-term average for the specific coast under consideration. Temperature time series data for the period 1969 to 2018 are homogenized by using the relative comparison between station observations and composite reference series by calculating CDI. Results indicates that CDI values of least-square on all cases are comparatively greater than simple and absolute CDIs. Least-square method is the appropriate method for determining the category of a year or a month or a season in terms of the temperature variation. Analysis based on mean temperature infers that only twenty extreme seasons are observed in monsoon season while three normal are observed during the month of October i.e., in post-monsoon season over the coastal Odisha. The relationship of climatic event including El Nino or La Nina feature of a particular year with respect to CDI is also investigated. The climatic variability is very high on some of the years based on analysis of index values of annual average of the temperatures (maximum, minimum and mean) over a region.
Source: https://doi.org/10.1007/s00024-024-03465-5
by Iranna Gogeri & Krushna Chandra Gouda
The road transport sector in India is a significant contributor to the country’s GHG emissions inventories, so it is essential to develop a comprehensive database of emission inventories to inform the design and implementation of suitable technologies and policies for appropriate mitigation measures. The development of an inventory using all available data can be useful in developing policies and technologies for reduced GHG emissions from the road sector. The paper seeks to develop an inventory of GHG emissions from the India’s road transport sector and analyse the fuel consumptions usage during the recent decade period, i.e. 2011 to 2021. In this study, IPCC guideline Tier-I and Tier-II were adopted for the emission estimation. Country-specific emission factor (EFCS) was developed based on carbon content and corresponding net calorific value (NCV) of country-specific fuel usage. The CO2eq emissions are also measured and compared with the corresponding global warming potentials (GWP). It appears that emissions of CO2 equivalent emission (CO2eq) from multiple greenhouse gases have significantly increased from 2011 to 2021. Estimation based on carbon country-specific emission factor shows nearly 165.09 Mt in 2011, increasing to about 241.20 Mt in 2021. Hence, it has been observed nearly 4.39% of reduction in CO2eq emissions using EFCS in the year 2021. Similar decreasing trends have also been observed for other gases like CH4 and N2O. The development of a comprehensive national GHG inventory for the road transport sector in India is a critical step towards achieving the country’s climate change goals and ensuring a sustainable future for generations to come.
Source: https://doi.org/10.1007/s12647-024-00738-1
by Rameshan Kallummal
Current perspectives on lower frequency variations and secular warming have predominantly been shaped by traditional anomalies that assume an annual cycle (AC) with a time-invariant amplitude. However, this anomaly framework falls short in capturing the complexity of multiple periodic modes with intricate waveforms and time dependent amplitude—the traits, in general, shared by externally forced responses of complex dynamical systems. By allowing interannual amplitude modulation of ACs, we show that the monotonic amplitude increases of the first AC of Sea Surface Temperature (SST) are manifested as the basin-wide secular warming of the ocean surface. Notably, the first SST-AC exhibits significant interannual variances and the largest linear warming rates in the Pacific Warm Pool. While the linear warming pattern mirrors that of a long-term mean SST, it depicts an entirely different warming pattern on the surface of the tropical Pacific Ocean compared to those reported so far. Moreover, all interannual warm (El Niño) and cold (La Niña) events in tropical Pacific regions are abnormal interannual modulations in the third and fourth ACs of SST, respectively. Specifically, a strong El Niño event occurs when a positive amplitude modulation leads to the overlap of two consecutive positive phases of the third AC of SST. Conversely, the absence of such overlaps during negative amplitude modulations significantly contributes to the positive skewness of SST anomalies. No systematic decadal changes in the zonal propagation characteristics of SST in the eastern Pacific (EP) and central Pacific (CP) regions were detected. These findings underscore that the secular warming and low-frequency events in EP and CP are intrinsic to three distinct ACs.
by Rani Devi, K C Gouda and Smrutishree Lenka
The Madden-Julian Oscillation (MJO) is an important tropical atmospheric phenomenon that plays a significant role in modulating weather patterns across India. Heat Waves (HW) are extreme weather events that have severe impacts on human health, agriculture, and various socio-economic sectors. This research paper aims to investigate the dynamical relationship between MJO phases, as measured by the Real-time Multivariate MJO (RMM) index, and the occurrence of HW in India, as defined by the Indian Meteorological Department. This paper demonstrated the relationship among three aspects, i.e., intensity, duration, frequency of HW during the different MJO phases. The differential dynamics associated for about two-fold rise in the HW occurrence in the South East, Eastern and North West India in the MJO active phase. Inactive phase witnessed enhancement (suppression) of HW during wet (dry) over the regions. The novel finding of this paper is that, the weaker the MJO, the higher probability of HW occurrence in respective regions depending on the position of the MJO convection center. The maximum duration is observed to be significantly decreased by about 2 days in the active MJO phase over NW and north central parts of the country. It is also inferred from this study that there is a significantly decrease of 0.5 °C in HW intensity during the active wet phase of MJO over the NW India. To explain the linkage of HW with MJO, geopotential height (GPH), wind circulation, velocity potential (VP), sea surface temperature (SST) and outgoing longwave radiation (OLR) composite anomalies have been computed and used in the analysis. It is observed that all these parameters have a direct impact on the evolution, strength and spread of the HW in India. This dynamical study mechanism can be prescribed in the numerical weather prediction models for the improved prediction of such extreme weather events during summer for proactive disaster management.
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