Ranking of CMIP6 based High-resolution Global Climate Models for India using TOPSIS

Thakur, Ritica; Manekar, V. L.

doi:10.1080/09715010.2021.2015462

Cited by 8 publications

(11 citation statements)

References 28 publications

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“…These projections were based on the general circulation model (GCM) MPI‐ESM1‐2‐HR and the global CO 2 emission scenario of ssp245 (~2.5 to ~3 CO 2 emissions from preindustrial baseline till 2100, with an expected decline by 2045). The GCM MPI‐ESM1‐2‐HR is recognised as one of the most suitable models for the Indian subcontinent (Thakur & Manekar, 2023).…”

Section: Methodsmentioning

confidence: 99%

Biophysical characteristics, distribution and conservation challenges of critically endangered Bhutan poppy (Papaver bhutanicum) in Jigme Dorji National Park, Bhutan

Dendup,

Kuenzang,

Dorji

et al. 2024

Integrative Conservation

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The occurrence of certain rare plant species in specific ecological habitats is intricately linked to a myriad of environmental conditions, encompassing both biotic and abiotic factors. The prioritisation of monitoring efforts becomes more impactful when conservationists possess a comprehensive understanding of the ecology and distribution of rare species within their designated habitats and across the entire range of the species. In September 2023, a study was conducted in Jigme Dorji National Park to assess the ecology, distribution and threats to the critically endangered Bhutan poppy. This survey, employing random sampling, covered approximately 87 ha across Tshophu, Tshophu base and Jichudrakey base in Soe Gewog and analysed 202 2 × 2 m plots. The survey revealed 57 plant species from 24 families, with Asteraceae (17.5%) and Papaveraceae (12.3%) dominating. Notably, 46% of families comprised a single species, and significant species richness differences were observed between Tshophu, Tshophu base and Jichudrakey base. Correlations between species richness and environmental variables, including slope, rock cover (%), bare soil cover (%) and herb cover (%), were identified as significant. The Bhutan poppy was positively and significantly associated with the southwest aspect, occupying 59% of surveyed plots. Species distribution modelling predicted a distribution area of approximately 37.29 square kilometres within the national park. However, future climate scenarios indicated a significant shift in the distribution of the Bhutan poppy. By 2041–2060, there is an anticipated decrease of 33% in its distribution area, with a shift towards the northeast. In the period from 2061 to 2080, the distribution is expected to increase by 8% from its current range, maintaining the northeast shift. The study identified three primary threats: grazing, trampling and harvesting, with livestock activities prevalent in 92% of plots and signs of harvesting in 45%. These findings provide crucial insights into the ecological dynamics, distribution patterns and potential conservation challenges facing the Bhutan poppy in Jigme Dorji National Park's alpine habitats, emphasising the need for informed conservation strategies amidst changing environmental conditions.

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Section: Methodsmentioning

confidence: 99%

Biophysical characteristics, distribution and conservation challenges of critically endangered Bhutan poppy (Papaver bhutanicum) in Jigme Dorji National Park, Bhutan

Dendup,

Kuenzang,

Dorji

et al. 2024

Integrative Conservation

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“…Initially, error metrics are weighted using the entropy method. These weights are subsequently employed as inputs in the TOPSIS methodology, as suggested by previous research 13,33 .…”

Section: Technique For Order Of Preference By Similarity To Ideal Sol...mentioning

confidence: 99%

Optimizing Multi-model Ensemble of CMIP6 GCMs for Climate Simulation: A Case Study over Bangladesh

Talukder,

Shaid,

Hwang

et al. 2024

Preprint

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This study aims to enhance the precision of climate simulations by optimizing a multi-model ensemble of General Circulation Models (GCMs) for simulating rainfall, maximum temperature (Tmax), and minimum temperature (Tmin). Bangladesh, with its susceptibility to rapid seasonal shifts and various forms of flooding, is the focal point of this research. Historical simulations of 19 CMIP6 GCMs are meticulously compared with ERA5 data for 1986–2014. The bilinear interpolation technique is used to harmonize the resolution of GCM data with the observed grid points. Seven distinct error metrics quantify the grid-to-grid agreement between GCMs and ERA5 data. The metrics are integrated into the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for seasonal and annual rankings of GCMs. Finally, the ensemble means of top-performing models are estimated using Bayesian Model Averaging (BMA) and Arithmetic Mean (AM) for relative comparison. The outcomes of this study underscore the variability in GCM performance across different seasons, necessitating the development of an overarching ranking system. Results reveal ACCESS.CM2 is the preeminent GCM for rainfall, while INM.CM4.8 excels in replicating Tmax and UKESM1.0.LL in replicating Tmin. In contrast, FGOALS.g3, KACE.1.0.G and CanESM5 are the most underperformed models in estimating rainfall, Tmx and Tmn, respectively. Overall, there are five models, ACCESS.ESM1.5, ACCESS.CM2, UKESM1.0.LL, MRI.ESM2.0, EC.Earth3 performed best in simulating both rainfall and temperature. The relative comparison of the ensemble means of the top five models revealed that the accuracy of BMA surpasses AM in capturing rainfall and temperature spatial patterns. This study offers invaluable insights into the selection of GCMs and ensemble methodologies for climate simulations in Bangladesh. Improving the accuracy of climate projections in this region can contribute significantly to climate science.

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“…The bioclimatic variables, precipitation, maximum and minimum temperatures of current and future data are downloaded from CMIP6-Worldclim 2.1 (Fick & Hijmans, 2017) with a resolution of 2.5 arc-minutes for 2050 for the shared socio-economic pathways 126, 345, and 585. According to (Thakur & Manekar, 2022), the global climate models (GCM) Hadgem3-GC31 and MPI-ESMI-2 are highly suitable for Indian domain for maximum temperature (Tmax) and minimum temperature (Tmin). The precipitation is downloaded from the output of GCM, MPI-ESMI-2 (Raju & Kumar, 2014).…”

Section: Datamentioning

confidence: 99%

“…The climatic parameters included to quantify the future geographical distribution of rice thrip includes the bioclimatic variables, minimum temperature, maximum temperature, and the precipitation. These parameters are downloaded from the global climate models HadGEM3 and MPI-ESM1-2-HR as these models can provide more accurate climatic parameters for Indian subcontinent among other GCMs (Raju & Kumar, 2014;Thakur & Manekar, 2022). In Fig.…”

Section: The Most In Uencing Climatic Parameter On Thripmentioning

confidence: 99%

Potential distribution of Rice Thrip (S.biformis) in India under climate change

Pushpalatha,

Gangadharan,

Roshni

et al. 2023

Preprint

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India’s economy is agro-based economy and in which rice is the major crop grown in the country. India is also one among the global leaders in the production of rice and is accounted for approximately 10% of nation’s economy. Present and future changes in the climate may challenge the crop production as the pest pressure in agriculture varies significantly with the elevated temperatures. The rice thrip (S.biformis) is the most challenging pest of rice and often causes yield reduction and significant economic loss. The climate change leads to variations in meteorological parameters, and it apparently affects the developmental rates and population dynamics of rice thrip. Monitoring its geographical distribution based on the climatic conditions can minimize crop yield losses. Therefore, the present study focused to quantify the temperature changes and eventually the population dynamics of rice thrip in India using projections from Hadgem3-GC31 and MPI-ESMI-2 under three emission scenarios (SSP126, SSP245 and SSP585) for the year 2050. The probability distribution from the MaxEnt species distribution model indicates the southern and north-eastern regions of India will be highly affected by rice thrip in 2050, and a total of 391 districts will be highly affected (locations where the predicted probability by the model is greater than 0.8) for the SSP126. The number of districts which will be highly affected by rice thrip for SSP245 and SSP585 are 418 and 435 respectively. The analysis shows that the most influencing climatic parameter for the geographical distribution of rice thrip is Tmax (quadratic relation) followed by bioclimatic variable and Tmin (positive relation). This suggests the regions with possibility to increase the maximum temperature will be highly suitable for its growth and distribution. Quantifying the dynamic population of rice thrip under climate change can facilitate and strategize integrated pest management practices to a sustainable food production by minimizing the risks.

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Ranking of CMIP6 based High-resolution Global Climate Models for India using TOPSIS

Cited by 8 publications

References 28 publications

Biophysical characteristics, distribution and conservation challenges of critically endangered Bhutan poppy (Papaver bhutanicum) in Jigme Dorji National Park, Bhutan

Biophysical characteristics, distribution and conservation challenges of critically endangered Bhutan poppy (Papaver bhutanicum) in Jigme Dorji National Park, Bhutan

Optimizing Multi-model Ensemble of CMIP6 GCMs for Climate Simulation: A Case Study over Bangladesh

Potential distribution of Rice Thrip (S.biformis) in India under climate change

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