Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

Bal, Prasanta Kumar; Ramachandran, A.; Ramkumar, Geetha; Bhaskaran, B.; Thirumurugan, P.; Indumathi, J.; Jayanthi, N.

doi:10.1007/s00704-014-1367-9

Cited by 31 publications

(12 citation statements)

References 17 publications

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“…It was found that the data is comparable and very well describes the magnitude and frequency of temperature indices such as heat waves, cold waves temperature anomalies. Several researchers have employed this data made available through National Data Centre, Pune in a variety of applications 93–95 . Similarly, the soil moisture values were extracted from the widely used Climate Prediction Centre (CPC) data sets prepared by the Earth System Research Laboratory of National Oceanic Atmospheric Administration (ESRL-NOAA) (http://www.esrl.noaa.gov/psd/data/gridded/data.cpcsoil.html).…”

Section: Methodsmentioning

confidence: 99%

Assessment of Risk and Resilience of Terrestrial Ecosystem Productivity under the Influence of Extreme Climatic Conditions over India

Jha

Goyal

2019

Sci Rep

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Analysing the link between terrestrial ecosystem productivity (i.e., Net Primary Productivity: NPP) and extreme climate conditions is vital in the context of increasing threats due to climate change. To reveal the impact of changing extreme conditions on NPP, a copula-based probabilistic model was developed, and the study was carried out over 25 river basins and 10 vegetation types of India. Further, the resiliency of the terrestrial ecosystems to sustain the extreme disturbances was evaluated at annual scale, monsoon, and non-monsoon seasons. The results showed, 15 out of 25 river basins were at high risks, and terrestrial ecosystems in only 5 river basins were resilient to extreme climatic conditions. Moreover, at least 50% area under 4 out of 10 vegetation cover types was found to be facing high chances of a drastic reduction in NPP, and 8 out of 10 vegetation cover types were non-resilient with the changing extreme climate conditions.

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Section: Methodsmentioning

confidence: 99%

Assessment of Risk and Resilience of Terrestrial Ecosystem Productivity under the Influence of Extreme Climatic Conditions over India

Jha

Goyal

2019

Sci Rep

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“…Recently, a majority of researchers around the world have used the 5th assessment report to study climate change under new scenarios of emission in different regions [6][7][8]. e fifth report models have higher resolution and use newer scenarios than previous ones.…”

Section: Introductionmentioning

confidence: 99%

Joint Modeling of Precipitation and Temperature Using Copula Theory for Current and Future Prediction under Climate Change Scenarios in Arid Lands (Case Study, Kerman Province, Iran)

Mesbahzadeh

Miglietta

Mirakbari

et al. 2019

Advances in Meteorology

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Precipitation and temperature are very important climatic parameters as their changes may affect life conditions. Therefore, predicting temporal trends of precipitation and temperature is very useful for societal and urban planning. In this research, in order to study the future trends in precipitation and temperature, we have applied scenarios of the fifth assessment report of IPCC. The results suggest that both parameters will be increasing in the studied area (Iran) in future. Since there is interdependence between these two climatic parameters, the independent analysis of the two fields will generate errors in the interpretation of model simulations. Therefore, in this study, copula theory was used for joint modeling of precipitation and temperature under climate change scenarios. By the joint distribution, we can find the structure of interdependence of precipitation and temperature in current and future under climate change conditions, which can assist in the risk assessment of extreme hydrological and meteorological events. Based on the results of goodness of fit test, the Frank copula function was selected for modeling of recorded and constructed data under RCP2.6 scenario and the Gaussian copula function was used for joint modeling of the constructed data under the RCP4.5 and RCP8.5 scenarios.

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“…Dynamical downscaling from RCM outputs is important in understanding the temperature and rainfall variability at a regional scale. A number of studies have been conducted in which the response of the summer monsoon to the enhanced greenhouse gases over the Asian domain has been reported by using outputs from different global climate models (GCMs) or through dynamical downscaling using high-resolution RCMs driven with many GCMs as the boundary conditions (Rupa Kumar and Ashrit 2001;Kripalani et al 2007;Mukhopadhyay et al 2010;Bhaskaran et al 2012;Bal et al 2015Bal et al , 2016Partha Sarathi et al 2015;Sooraj et al 2015;Anubhav and Domri 2017;Iqbal et al 2017). Results from their studies show that the high-resolution RCMs are able to capture the distribution of monsoon rainfall in the spatial and temporal scales over the Asian domain and the model compares well with the observation.…”

Section: Introductionmentioning

confidence: 99%

Summer monsoon climate simulations over BIMSTEC countries using RegCM4 regional climate model

Bal

Mitra

2019

J Earth Syst Sci

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Regional climate models are useful by downscaling from global climate model simulations for climate studies and climate applications at a regional scale. The South Asian monsoon region is one of the most challenging regions towards understanding the monsoon variability by implementing various climate simulations. A model version of the RegCM4 regional climate model provided by the International Centre for Theoretical Physics (ICTP) is used in this study to simulate the climate of Bay of Bengal Initiative for

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Climate change projections for Tamil Nadu, India: deriving high-resolution climate data by a downscaling approach using PRECIS

Cited by 31 publications

References 17 publications

Assessment of Risk and Resilience of Terrestrial Ecosystem Productivity under the Influence of Extreme Climatic Conditions over India

Assessment of Risk and Resilience of Terrestrial Ecosystem Productivity under the Influence of Extreme Climatic Conditions over India

Joint Modeling of Precipitation and Temperature Using Copula Theory for Current and Future Prediction under Climate Change Scenarios in Arid Lands (Case Study, Kerman Province, Iran)

Summer monsoon climate simulations over BIMSTEC countries using RegCM4 regional climate model

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