Examined the India-China region through climate reanalysis products ERA5 & NCEP, and climate prediction models RCP 2.6 & 8.5.
We compared global and regional values of mean 2m temperature, sea-surface temperature, surface pressure and total precipitation. On a regional scale, we chose the South and West region of Asia (India-China area; lon = 60:140, lat = 0:57) as this region is heavily influenced by the South Asian monsoon. We found a low pressure anomaly over Tibet, attributed to the Tibetan thermal low, and a prominent trend of low precipitation over Tibet, due to the rainshadow effect of the Himalayas
The RCP 2.5 model indicated small changes from current trends, such as a rise in maximum temperature by ~1K. Running RCP 8.5 revealed the drastic rise in global minimum temperature by 27K, and intensification of temperatures, pressure and precipitation over the regional area.
We then ran comparisons between the ERA5 and NCEP reanalysis data, and found that NCEP has a much lower resolution and thus precision versus ERA5
This term project was heavily based on @royalosyin 's Python-Practical-Application-on-Climate-Variability-Studies Link: https://github.com/royalosyin/Python-Practical-Application-on-Climate-Variability-Studies