We present the first high-resolution measurements of pollutant trace gases in the Asian summer monsoon upper troposphere and lowermost stratosphere (UTLS) from the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) during the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) campaign based in Kathmandu, Nepal, 2017. Measurements of peroxyacetyl nitrate (PAN), acetylene (C2H2), and formic acid (HCOOH) show strong local enhancements up to altitudes of 16 km. More than 500 pptv of PAN, more than 200 pptv of C2H2, and more than 200 pptv of HCOOH are observed. Air masses with increased volume mixing ratios of PAN and C2H2 at altitudes up to 18 km, reaching to the lowermost stratosphere, were present at these altitudes for more than 10 d, as indicated by trajectory analysis. A local minimum of HCOOH is correlated with a previously reported maximum of ammonia (NH3), which suggests different washout efficiencies of these species in the same air masses. A backward trajectory analysis based on the models Alfred Wegener InsTitute LAgrangian Chemistry/Transport System (ATLAS) and TRACZILLA, using advanced techniques for detection of convective events, and starting at geolocations of GLORIA measurements with enhanced pollution trace gas concentrations, has been performed. The analysis shows that convective events along trajectories leading to GLORIA measurements with enhanced pollutants are located close to regions where satellite measurements by the Ozone Monitoring Instrument (OMI) indicate enhanced tropospheric columns of nitrogen dioxide (NO2) in the days prior to the observation. A comparison to the global atmospheric models Copernicus Atmosphere Monitoring Service (CAMS) and ECHAM/MESSy Atmospheric Chemistry (EMAC) has been performed. It is shown that these models are able to reproduce large-scale structures of the pollution trace gas distributions for one part of the flight, while the other part of the flight reveals large discrepancies between models and measurement. These discrepancies possibly result from convective events that are not resolved or parameterized in the models, uncertainties in the emissions of source gases, and uncertainties in the rate constants of chemical reactions.
The impact of aerosols on cloud properties is one of the largest uncertainties in the anthropogenic radiative forcing of the climate. Significant progress has been made in constraining this forcing using observations, but uncertainty remains, particularly in the magnitude of cloud rapid adjustments to aerosol perturbations. Cloud liquid water path (LWP) is the leading control on liquid-cloud albedo, making it important to observationally constrain the aerosol impact on LWP. Previous modelling and observational studies have shown that multiple processes play a role in determining the LWP response to aerosol perturbations, but that the aerosol effect can be difficult to isolate. Following previous studies using mediating variables, this work investigates use of the relationship between cloud droplet number concentration (Nd) and LWP for constraining the role of aerosols. Using joint-probability histograms to account for the non-linear relationship, this work finds a relationship that is broadly consistent with previous studies. There is significant geographical variation in the relationship, partly due to role of meteorological factors (particularly relative humidity). The Nd–LWP relationship is negative in the majority of regions, suggesting that aerosol-induced LWP reductions could offset a significant fraction of the instantaneous radiative forcing from aerosol–cloud interactions (RFaci). However, variations in the Nd–LWP relationship in response to volcanic and shipping aerosol perturbations indicate that the Nd–LWP relationship overestimates the causal Nd impact on LWP due to the role of confounding factors. The weaker LWP reduction implied by these “natural experiments” means that this work provides an upper bound to the radiative forcing from aerosol-induced changes in the LWP.
The number concentration of cloud particles is a key quantity for understanding aerosol–cloud interactions and describing clouds in climate and numerical weather prediction models. In contrast with recent advances for liquid clouds, few observational constraints exist regarding the ice crystal number concentration (Ni). This study investigates how combined lidar–radar measurements can be used to provide satellite estimates of Ni, using a methodology that constrains moments of a parameterized particle size distribution (PSD). The operational liDAR–raDAR (DARDAR) product serves as an existing base for this method, which focuses on ice clouds with temperatures Tc<-30 ∘C. Theoretical considerations demonstrate the capability for accurate retrievals of Ni, apart from a possible bias in the concentration in small crystals when Tc≳−50 ∘C, due to the assumption of a monomodal PSD shape in the current method. This is verified via a comparison of satellite estimates to coincident in situ measurements, which additionally demonstrates the sufficient sensitivity of lidar–radar observations to Ni. Following these results, satellite estimates of Ni are evaluated in the context of a case study and a preliminary climatological analysis based on 10 years of global data. Despite a lack of other large-scale references, this evaluation shows a reasonable physical consistency in Ni spatial distribution patterns. Notably, increases in Ni are found towards cold temperatures and, more significantly, in the presence of strong updrafts, such as those related to convective or orographic uplifts. Further evaluation and improvement of this method are necessary, although these results already constitute a first encouraging step towards large-scale observational constraints for Ni. Part 2 of this series uses this new dataset to examine the controls on Ni.