Impact of Climate Change on Hydrometeorological Variables in a River Basin in India for IPCC SRES Scenarios

Anandhi, Aavudai; Srinivas, V. V.; Kumar, D. Nagesh

doi:10.1061/9780784412718.ch12

Cited by 9 publications

(4 citation statements)

References 47 publications

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“…This increase in R H , temperature (Anandhi et al 2009), and cloud cover (Anandhi 2008), observed at a smaller scale in this basin in India, is in agreement with the results in Dai (2006). Dai (2006) also showed an increase in R H over India during the period 1976-2004 and attributed it to the increase in the surface specific humidity coupled with moderate warming and increase in low clouds over these regions.…”

Section: Assessment Of Trend In the Downscaled Predictandsupporting

confidence: 92%

Daily relative humidity projections in an Indian river basin for IPCC SRES scenarios

Anandhi

Srinivas

Kumar

et al. 2011

Theor Appl Climatol

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A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R H in a river basin at monthly scale. Uncertainty in the future projections of R H is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R H are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R H is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.

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Section: Assessment Of Trend In the Downscaled Predictandsupporting

confidence: 92%

Daily relative humidity projections in an Indian river basin for IPCC SRES scenarios

Anandhi

Srinivas

Kumar

et al. 2011

Theor Appl Climatol

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“…For each month, the change factors are estimated multiplicatively for precipitation for each GCM/run number for each of the five time slices. The procedure to calculate a CF, multiplicatively, is for a single time slice is explained in this sub-section [28]. The first step is to estimate the mean values of GCM simulated baseline (GCMb) and future (GCMf) climates (equations 3.1 and 3.2).…”

Section: Global Climate Model (Gcm) Simulations For Future Precipitatmentioning

confidence: 99%

Present and Future Climate Change in Indian Cardamom Hills: Implications for Cardamom Production and Sustainability

Murugan¹,

Shetty²,

Anandhi³

et al. 2013

BJECC

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Aims: This paper examines the interactions between climate parameters and cardamom capsule yield and its sustainability in Indian Cardamom Hills. Methodology: Temporal trends were evaluated at annual, seasonal and monthly time scale using Mann-Kendall method. Significant trends were identified at annual, seasonal and monthly scale using two tailed Z-Test. The temporal trends were evaluated using the non-parametric Mann-Kendall test. To quantify the slope we used Sen's non-parametric estimator of slope. The significance of the test was evaluated using two tailed Z-Test. A p value of <0.05 was used to indicate statistical significance, using two tailed Z test. Results: Climate warming was significant in the recent decades in the Indian Cardamom Hills, which is recognized as one of the ecologically sensitive and biologically diverse areas. Considerable and significant spatial and temporal variations have occurred in the main climatic elements like air temperature, rainfall and relative humidity in the hill region. Significant positive trend in day-night time temperature has been observed and the trend differed from one station to another. Significant increasing trend was also observed for minimum temperature than maximum temperature and this had caused decline in diurnal temperature. Both winter and summer monsoon rainfall as well as high relative humidity

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“…Four types of climate scenarios have been adapted in impact assessments (Mearns et al 2001;Anandhi 2007), namely: incremental scenarios, analogue scenarios, a general category of "other scenarios," and scenarios based on the outputs from climate models. The most commonly used scenario type is based on outputs from climate models.…”

Section: Types Of Scenariosmentioning

confidence: 99%

Future Climate Change Scenarios for Florida

Kirtman¹,

Misra²,

Anandhi³

et al. 2017

Florida’s Climate: Changes, Variations, &Amp; Impacts

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Impact of Climate Change on Hydrometeorological Variables in a River Basin in India for IPCC SRES Scenarios

Cited by 9 publications

References 47 publications

Daily relative humidity projections in an Indian river basin for IPCC SRES scenarios

Daily relative humidity projections in an Indian river basin for IPCC SRES scenarios

Present and Future Climate Change in Indian Cardamom Hills: Implications for Cardamom Production and Sustainability

Future Climate Change Scenarios for Florida

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