Abstract
Abstract. Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over central India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. It is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate.
Highlights
Observational evidences show that globally averaged annual mean surface temperature has increased by about 0.85 ◦C between 1880 and 2012, with rapid warming in the recent past decades (IPCC AR5, Stocker et al, 2013)
Halder et al.: Investigating the impact of land-use/land-cover change (LULCC) on Indian summer monsoon to Allen and Ingram (2002), the increase in mean precipitation is expected to be much less than the extremes as it is constrained by the net rate of cooling of the troposphere, which in turn depends on its temperature and presence of greenhouse gases (GHGs) and aerosols
It is intriguing to note that seasonal and regional or local changes in extreme weather events can be of different magnitude and sign than global changes due to complex regional feedbacks associated with the GHGs, clouds, aerosols and other anthropogenic activities such as land-use/land-cover change (LULCC)
Summary
Observational evidences show that globally averaged annual mean surface temperature has increased by about 0.85 ◦C between 1880 and 2012, with rapid warming in the recent past decades (about 0.72 ◦C after 1951) (IPCC AR5, Stocker et al, 2013). S. Halder et al.: Investigating the impact of LULCC on Indian summer monsoon to Allen and Ingram (2002), the increase in mean precipitation is expected to be much less than the extremes as it is constrained by the net rate of cooling of the troposphere, which in turn depends on its temperature and presence of greenhouse gases (GHGs) and aerosols. Due to observational uncertainty, challenges in modeling and natural variability proper detection and attribution of the regional climate changes often becomes difficult. Quantification of the changes in regional climate as well as proper attribution are both very important
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