Abstract. Several ambient air quality records corroborate the severe and persistent degradation of air quality over northern India during the winter months, with evidence of a continued, increasing trend of pollution across the Indo-Gangetic Plain (IGP) over the past decade. A combination of atmospheric dynamics and uncertain emissions, including the post-monsoon agricultural stubble burning, make it challenging to resolve the role of each individual factor. Here we demonstrate the potential use of an atmospheric transport model, the Weather Research and Forecasting model coupled with chemistry (WRF–Chem) to identify and quantify the role of transport mechanisms and emissions on the occurrence of the pollution events. The investigation is based on the use of carbon monoxide (CO) observations from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite and the surface measurement network, as well as the WRF–Chem simulations, to investigate the factors contributing to CO enhancement over India during November 2018. We show that the simulated column-averaged dry air mole fraction (XCO) is largely consistent with TROPOMI observations, with a spatial correlation coefficient of 0.87. The surface-level CO concentrations show larger sensitivities to boundary layer dynamics, wind speed, and diverging source regions, leading to a complex concentration pattern and reducing the observation-model agreement with a correlation coefficient ranging from 0.41 to 0.60 for measurement locations across the IGP. We find that daily satellite observations can provide a first-order inference of the CO transport pathways during the enhanced burning period, and this transport pattern is reproduced well in the model. By using the observations and employing the model at a comparable resolution, we confirm the significant role of atmospheric dynamics and residential, industrial, and commercial emissions in the production of the exorbitant level of air pollutants in northern India. We find that biomass burning plays only a minimal role in both column and surface enhancements of CO, except for the state of Punjab during the high pollution episodes. While the model reproduces observations reasonably well, a better understanding of the factors controlling the model uncertainties is essential for relating the observed concentrations to the underlying emissions. Overall, our study emphasizes the importance of undertaking rigorous policy measures, mainly focusing on reducing residential, commercial, and industrial emissions in addition to actions already underway in the agricultural sectors.

Abstract. The response of water vapour (H2O) and noctilucent clouds (NLCs) to the solar cycle are studied using the Leibniz Institute for Middle Atmosphere (LIMA) model and the Mesospheric Ice Microphysics And tranSport (MIMAS) model. NLCs are sensitive to the solar cycle because their formation depends on background temperature and the H2O concentration. The solar cycle affects the H2O concentration in the upper mesosphere mainly in two ways: directly through the photolysis and, in time and place of NLCs formation, indirectly through temperature changes. We found that H2O concentration correlate positively with the temperature changes due to the solar cycle at altitudes above about 82 km, where NLCs form. The photolysis effect leads to an anti-correlation of H2O concentration and solar Lyman-α radiation, which gets even more pronounced at altitudes below ~83 km when NLCs are present. We studied the H2O response to Lyman-α variability for the period 1992 to 2018, including the two most recent solar cycles. The amplitude of Lyman-α variation decreased by about 40 % in the period 2005 to 2018 compared to the preceding solar cycle, resulting in a lower H2O response in the late period. We investigated the effect of increasing greenhouse gases (GHGs) on the H2O response throughout the solar cycle by performing model runs with and without increases in carbon dioxide (CO2) and methane (CH4). The increase of methane and carbon dioxide amplify the response of water vapour to the solar variability. The solar cycle response is reduced in the late solar cycle due to a smaller amplitude of Lyman-α variability in the second period. Applying the geometry of satellite observations, we find a missing response when averaging over altitudes of 80 to 85 km, where H2O has a positive and a negative response (depending on altitude) which largely cancel out. One main finding is that during NLCs the solar cycle response of H2O strongly depends on altitude. A negative correlation between H2O and Lyman-α is found in the NLC sublimation zone below an altitude of about 83 km, but a positive response is present at the altitudes above 83 km where NLCs form.

Abstract. The responses of water vapour (H2O) and noctilucent clouds (NLCs) to the solar cycle are studied using the Leibniz Institute for Middle Atmosphere (LIMA) model and the Mesospheric Ice Microphysics And tranSport (MIMAS) model. NLCs are sensitive to the solar cycle because their formation depends on background temperature and the H2O concentration. The solar cycle affects the H2O concentration in the upper mesosphere mainly in two ways: directly through the photolysis and, at the time and place of NLC formation, indirectly through temperature changes. We found that H2O concentration correlates positively with the temperature changes due to the solar cycle at altitudes above about 82 km, where NLCs form. The photolysis effect leads to an anti-correlation of H2O concentration and solar Lyman-α radiation, which gets even more pronounced at altitudes below ∼ 83 km when NLCs are present. We studied the H2O response to Lyman-α variability for the period 1992 to 2018, including the two most recent solar cycles. The amplitude of Lyman-α variation decreased by about 40 % in the period 2005 to 2018 compared to the preceding solar cycle, resulting in a lower H2O response in the late period. We investigated the effect of increasing greenhouse gases (GHGs) on the H2O response throughout the solar cycle by performing model runs with and without increases in carbon dioxide (CO2) and methane (CH4). The increase of methane and carbon dioxide amplifies the response of water vapour to the solar variability. Applying the geometry of satellite observations, we find a missing response when averaging over altitudes of 80 to 85 km, where H2O has a positive response and a negative response (depending on altitude), which largely cancel each other out. One main finding is that, during NLCs, the solar cycle response of H2O strongly depends on altitude.

<p>Noctilucent clouds (NLC) are often cited as potential indicators of climate change in the middle atmosphere. They owe their existence to the very cold summer mesopause region (~130K) at mid and high latitudes. We analyze trends derived from the Leibniz-Institute Middle Atmosphere Model (LIMA) and the MIMAS ice particle model (Mesospheric Ice Microphysics And tranSport model). We first concentrate on the years 1871-2008 and on middle, high and arctic latitudes, respectively. Model runs with and without an increase of carbon dioxide and water vapor (from methane oxidation) concentration are performed. Trends are most prominent after ~1960 when the increase of both carbon dioxide and water vapor accelerates. Negative trends of (geometric) NLC altitudes are primarily due to cooling below NLC altitudes caused by carbon dioxide increase. Increases of ice particle radii and NLC brightness with time are mainly caused by an enhancement of water vapor caused by the oxidation of methane. Several ice layer and background parameter trends are similar at high and arctic latitudes but are substantially smaller at middle latitudes. Ice particles are present nearly all the time at high and arctic latitudes, but are much less common at middle latitudes. Ice water content and maximum backscatter are highly correlated, where the slope depends on latitude. This allows to combine data sets from satellites and lidars. Furthermore, IWC and the concentration of water vapor at the altitude of maximum backscatter are also strongly correlated. Results from LIMA/MIMAS are consistent with observations. More recently, we have expanded our model runs into the future, namely up to the 2060s. We have used IPCC scenarios regarding future concentrations of carbon dioxide and methane. We find that all NLC parameters, such as occurrence rates and backscatter coefficients increase substantially in this time period. Furthermore, we have studied the extinction of solar radiation by NLC. We will present details regarding the (wavelength-dependent) extinction and the temporal and spatial distribution of this extinction. We will also present new results on the impact of solar cycle induced radiation variability on NLC.</p>