river basins are evidence to why one has to consider the impacts of climate change.
These assessments will leverage policymakers to identify adaption and mitigation
strategies to strengthen agriculture and other allied sectors to safeguard the livelihood of deprived communities.
Maximum Temperature Projections over the Bhima Sub-Basin
Maximum temperature over the Bhima sub-basin is downscaled using the ACF
method. The climate data obtained from five climate models of GCMs and IMD
observed data regridded (because temperature data have a spatial resolution of 1
0
Â
1
0 ) to size 0.25
0
 0.25
0 gridded locations using a two-dimensional linear interpolation technique. The change factors of all the IMD gauge stations in the Bhima
basin are calculated by applying the additive CF method for four different RCP
scenarios with respect to different time series data for 2021–2040, 2041–2060,
2061–2080, and 2081–3100. The projected daily maximum temperature over the
basin for five GCMs in four RCP scenarios (2.6, 4.5, 6.0, 8.5) is expressed in terms
of the multimodel ensemble (averaged), the percentage change over average daily
maximum temperature for the different RCP scenarios with respect to the historical
(1986–2005) observation period. The spatial map of the historical period
(1986–2005) refers to the average daily maximum temperature data for the entire
Bhima basin (Fig. 2.5). It can be inferred that the Upper Bhima (K5) region during
1986–2005 experienced a relatively lower record of daily maximum temperature as
Fig. 2.4 Performance of the CF method over the daily observed rainfall data of IMD during the SW
monsoon season (June–September)
28
N. S. Patil and R. S. Laddimath
These assessments will leverage policymakers to identify adaption and mitigation
strategies to strengthen agriculture and other allied sectors to safeguard the livelihood of deprived communities.
Maximum Temperature Projections over the Bhima Sub-Basin
Maximum temperature over the Bhima sub-basin is downscaled using the ACF
method. The climate data obtained from five climate models of GCMs and IMD
observed data regridded (because temperature data have a spatial resolution of 1
0
Â
1
0 ) to size 0.25
0
 0.25
0 gridded locations using a two-dimensional linear interpolation technique. The change factors of all the IMD gauge stations in the Bhima
basin are calculated by applying the additive CF method for four different RCP
scenarios with respect to different time series data for 2021–2040, 2041–2060,
2061–2080, and 2081–3100. The projected daily maximum temperature over the
basin for five GCMs in four RCP scenarios (2.6, 4.5, 6.0, 8.5) is expressed in terms
of the multimodel ensemble (averaged), the percentage change over average daily
maximum temperature for the different RCP scenarios with respect to the historical
(1986–2005) observation period. The spatial map of the historical period
(1986–2005) refers to the average daily maximum temperature data for the entire
Bhima basin (Fig. 2.5). It can be inferred that the Upper Bhima (K5) region during
1986–2005 experienced a relatively lower record of daily maximum temperature as
Fig. 2.4 Performance of the CF method over the daily observed rainfall data of IMD during the SW
monsoon season (June–September)
28
N. S. Patil and R. S. Laddimath