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The Indian Institute of Tropical Meteorology (IITM) has generated seasonal and extended range hindcast products for 1981–2008 and 2003–2016, respectively, using the IITM-Climate Forecast System (IITM-CFS) coupled model at various resolutions and configurations. Notably, our observational analysis suggests that for the 1981–2008 period, the tropical Indo-Pacific drivers, namely, the canonical El Niño-Southern Oscillation (ENSO), ENSO Modoki, and Indian Ocean Dipole (IOD). are significantly associated with the observed Kharif rice production (KRP) of various rice-growing Indian states. In this paper, using the available hindcasts, we evaluate whether these state-of-the-art retrospective forecasts capture the relationship of the KRP of multiple states with the local rainfall as well as the tropical Indo-Pacific drivers, namely, the canonical ENSO, ENSO Modoki, and the IOD. Using techniques of anomaly correlation, partial correlation, and pattern correlation, we surmise that the IITM-CFS successfully simulate the observed association of the tropical Indo-Pacific drivers with the local rainfall of many states during the summer monsoon. Significantly, the observed relationship of the local KRP with various climate drivers is predicted well for several Indian states such as United Andhra Pradesh, Karnataka, Odisha, and Bihar. The basis seems to be the model's ability to capture the teleconnections from the tropical Indo-Pacific drivers such as the IOD, canonical and Modoki ENSOs to the local climate, and consequently, the Kharif rice production. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to analyze the trends and variability in extreme temperature indices and its impact on rice-wheat productivity over two districts of Bihar, India, which is part of the middle Indo-Gangetic Basin. Mann-Kendall non-parametric test was employed for detection of trend and Sen slope was determined to quantify the magnitude of such trends. We have analyzed 10 extreme temperature indices for monthly and seasonally. The influence of extreme temperature indices on rice-wheat productivity was determined using correlation analysis. As far as Patna is concerned, if the number of cool days during September ≥10, the rice productivity will increase due to the availability of sufficient duration to fill up the grain. However, higher warm days during all the months except June will affect the productivity. A significant negative correlation was noticed between maximum value of minimum temperature during September and rice productivity. Highly significant positive correlation was noticed between number of cool days during September with rice productivity while it was highly significant negative correlation in the case of number of warm days during the same month. As far as Samastipur is concerned, a negative correlation was noticed between wheat productivity and maximum value of maximum temperature (TXx) during February, but not statistically significant. The higher temperature may affect the kernel weight and thereby yield. It is seen that a critical value of TXx ≥29.2 °C will be harmful to wheat crop during February. A significant positive correlation of number of cool nights with wheat productivity also supports the above relationship. The critical values of extreme temperature indices during rice and wheat growing months provide an indicator to assess the vulnerability of rice-wheat productivity to temperature for Patna and Samastipur districts and there is a need to prepare an adaptive strategy and also develop thermo-insensitive rice-wheat high yielding varieties suitable for this region to sustain rice-wheat productivity under projected climate change situation. [ABSTRACT FROM AUTHOR]

Land suitability analysis is a necessity to achieve sustainable agricultural productivity with the optimum utilization of the available resources. Lack of proper knowledge on the best combination of factors that suit production of rice and wheat has contributed to low production in the Sone river command, Bihar. The aim of this study is to develop land suitability maps for rice and wheat crop based on physical, chemical and climatic factors of production using a multi-criteria evaluation (MCE) and Geographic Information System (GIS) approach. Biophysical variables of soil, climate and topography have been considered for suitability analysis. This work also evaluates the impact of climate change (CC) on cropland suitability for rice and wheat crops. Climatic variable scenarios of rainfall were obtained from four GCMs (CAN-ESM2, MPI-ESM-MR, CSIRO, CMCC-CMS) for three future time slices (2011–2040, 2041–2070, 2071–2100) of representative concentration pathways (RCP) RCP 2.6, RCP 4.5 and RCP 8.5 scenarios. The observation data (1985–2011) from IMD Pune from 8 meteorological stations were used as the current baseline climatic data of rainfall, which is used to validate the cropland suitability model. The results of CC indicate that there is a significant variability in the distribution of rainfall in the projected period 2011–2100 with respect to the baseline period. The results also show a concomitant increase in the projected crop suitability area of wheat from 17 to 35% and decrease in area for rice from 31 to 21% when compared with baseline for highly suitable area. [ABSTRACT FROM AUTHOR]