Datasets supporting "Changing PM2.5 and related meteorology over India from 1950-2014: A new perspective from a chemistry-climate model ensemble"

Abstract

These datasets are the basis for the figures in, "Changing PM2.5 and related meteorology over India from 1950-2014: A new perspective from a chemistry-climate model ensemble." The abstract of the manuscript reads as follows: Surface PM2.5 concentrations in India have increased dramatically as emissions have risen in recent years. The role of meteorological factors in this increase is unclear, mainly due to a lack of long-term observations over the region. A 12-member ensemble of historical (1950-2014) simulations from the Community Earth System Model version 2-Whole Atmosphere Community Climate Model version 6 (CESM2-WACCM6) offers an unprecedented opportunity to examine simulated daily PM2.5 and meteorology for 20th century climates that can arise due to “climate noise” under the same historical greenhouse gas and air pollutant emission trajectories. CESM2-WACCM6 includes interactive aerosol and gas-phase chemistry in the atmosphere coupled to ocean-sea ice-land models, and each ensemble member differs only in its initial conditions of the climate state. We systematically examine, decade-by-decade, the changes in PM2.5 and associated meteorology, including wind speed, surface temperature inversions, boundary layer height, precipitation, and relative humidity in four cities in India: Chennai, Kolkata, Mumbai, and New Delhi. Forced changes clearly emerge in meteorological variables from 1950 to 2014, including increases in both relative humidity and temperature inversion strength, and decreases in boundary layer height and average surface wind speed. The timing of these changes varies by city: boundary layer heights decrease most over New Delhi in the premonsoon season (ensemble average decrease of 400m), but over Mumbai in the postmonsoon season (ensemble average decrease of 100m). PM2.5 concentrations increase across India regardless of climate variability, with an almost threefold increase from 1950 to 2014 over New Delhi. Analysis of dimensionless variables shows that PM2.5 exhibits larger ensemble mean trends and smaller variability than the trends in the meteorological variables, enabling us to infer that the increase in PM2.5 is predominantly controlled by rises in anthropogenic emissions, rather than climate variability. Overall, our simulations corroborate the dominant role of air pollutant emissions on poor air quality in India.