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This paper describes the projection of climate change scenarios under increased greenhouse gas emissions, using the results of atmospheric-ocean general circulation models in the Coupled Model Intercomparison Project phase 3 dataset. A score is given to every model based on global and regional performance. Four out of 20 general circulation models (GCMs) were selected based on skill in predicting observed annual temperature and precipitation conditions. The ensemble of these four models shows superiority over the individual model scores. These models were subjected to increases in future anthropogenic radiative forcings for constructing climate change scenarios. Future climate scenarios for Tamil Nadu were developed with MAGICC/SCENGEN software. Model results show both temperature and precipitation increases under increased greenhouse gas scenarios. Northeast and northwest parts of Tamil Nadu show a greater increase in temperature and precipitation. Seasonally, the maximum rise in temperature occurred during the MAM season, followed by DJF, JJA, and SON. Decreasing trends of precipitation were observed during DJF and MAM. [ABSTRACT FROM AUTHOR]

Climate variability is directly or indirectly affecting crop production and threatens the food security of livelihood. The Cauvery delta region (CDR) is the agricultural protective zone of Tamil Nadu state, the crop production in this region is vulnerable to climate change impacts. In this study, the future climate change impact of black gram yield has been assessed using the DSSAT-CROPGRO model in the CDR. The model was calibrated during the 2018 sowing period and validated during 2019 cultivation practices for determining the genetic coefficient of the black gram cultivar VBN6. The RMSE values of observed and simulated yield were 910 and 890 kg ha−1 respectively. RegCM4 model is used for the simulation of Vigna mungo yield under RCP 4.5 and 8.5 scenarios during the 1985–2015 (baseline), 2020–2039 (near-century), 2040–2069 (mid-century), and 2070–2099 (end-century). The results reveal that simulation of black gram yield change could be around 34%, 52%, and 25% during the near-century, mid-century, and end-century respectively for RCP 4.5 based on the baseline period. Adjusting the sowing date is evaluated as an adaptation option in future climate change scenarios, and results revealed that early sowing in the winter season could be the best suitable growing period for better yield in this region. [ABSTRACT FROM AUTHOR]

This study has been undertaken to examine the occurrence of climate change in Tamil Nadu, the southernmost state of India and its impact on rainfall pattern which is a primary constraint for agricultural production. Among the five sample stations examined across the state, the minimum temperature has increased significantly in Coimbatore while the same has decreased significantly in Vellore whereas both minimum and maximum temperatures have increased significantly in Madurai since 1969 with climate change occurring between late 1980s and early 1990s. As a result, the south-west monsoon has been disturbed with August rainfall increasing with more dispersion while September rainfall decreasing with less dispersion. Thus, September, the peak rainfall month of south-west monsoon before climate change, has become the monsoon receding month after climate change. Though there has been no change in the trend of the north-east monsoon, the quantity of October and November rainfall has considerably increased with increased dispersion after climate change. On the whole, south-west monsoon has decreased with decreased dispersion while north-east monsoon has increased with increased dispersion. Consequently, the season window for south-west monsoon crops has shortened while the north-east monsoon crops are left to fend against flood risk during their initial stages. Further, the incoherence in warming, climate change and rainfall impact seen across the state necessitates devising different indigenous and institutional adaptation strategies for different regions to overcome the adverse impacts of climate change on agriculture. [ABSTRACT FROM AUTHOR]