Abstract. Gravity waves are an important driver for the atmospheric circulation and have substantial impact on weather and climate. Satellite instruments offer excellent opportunities to study gravity waves on a global scale. This study focuses on observations from the Atmospheric Infrared Sounder (AIRS) onboard the National Aeronautics and Space Administration Aqua satellite and the Infrared Atmospheric Sounding Interferometer (IASI) onboard the European MetOp satellites. The main aim of this study is an intercomparison of stratospheric gravity wave observations of both instruments. In particular, we analyzed AIRS and IASI 4.3 µm brightness temperature measurements, which directly relate to stratospheric temperature. Three case studies showed that AIRS and IASI provide a clear and consistent picture of the temporal development of individual gravity wave events. Statistical comparisons based on a 5-year period of measurements (2008)(2009)(2010)(2011)(2012) showed similar spatial and temporal patterns of gravity wave activity. However, the statistical comparisons also revealed systematic differences of variances between AIRS and IASI that we attribute to the different spatial measurement characteristics of both instruments. We also found differences between day-and nighttime data that are partly due to the local time variations of the gravity wave sources. While AIRS has been used successfully in many previous gravity wave studies, IASI data are applied here for the first time for that purpose. Our study shows that gravity wave observations from different hyperspectral infrared sounders such as AIRS and IASI can be directly related to each other, if instrument-specific characteristics such as different noise levels and spatial resolution and sampling are carefully considered. The ability to combine observations from different satellites provides an opportunity to create a long-term record, which is an exciting prospect for future climatological studies of stratospheric gravity wave activity.

Sulfur dioxide (SO2) emissions from strong volcanic eruptions are an important natural cause for climate variations. We applied our new Lagrangian transport model Massive‐Parallel Trajectory Calculations to perform simulations for three case studies of volcanic eruption events. The case studies cover the eruptions of Grímsvötn, Iceland, Puyehue‐Cordón Caulle, Chile, and Nabro, Eritrea, in May and June 2011. We used SO2 observations of the Atmospheric Infrared Sounder (AIRS/Aqua) and a backward trajectory approach to initialize the simulations. Besides validation of the new model, the main goal of our study was a comparison of simulations with different meteorological data products. We considered three reanalyses, i.e., ERA‐Interim, Modern‐Era Retrospective Analysis for Research and Applications (MERRA), and National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) Reanalysis Project as well as the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational analysis. Qualitatively, the SO2 distributions from the simulations compare well not only with the AIRS data but also with Cloud‐Aerosol Lidar with Orthogonal Polarization and Michelson Interferometer for Passive Atmospheric Sounding aerosol observations. Transport deviations and the critical success index (CSI) are analyzed to evaluate the simulations quantitatively. During the first 5 or 10 days after the eruptions we found the best performance for the ECMWF analysis (CSI range of 0.25–0.31), followed by ERA‐Interim (0.25–0.29), MERRA (0.23–0.27), and NCAR/NCEP (0.21–0.23). High temporal and spatial resolution of the meteorological data does lead to improved performance of Lagrangian transport simulations of volcanic emissions in the upper troposphere and lower stratosphere.

Abstract. An inverse transport modeling approach based on the concepts of sequential importance resampling and parallel computing is presented to reconstruct altitude-resolved time series of volcanic emissions, which often cannot be obtained directly with current measurement techniques. A new inverse modeling and simulation system, which implements the inversion approach with the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) is developed to provide reliable transport simulations of volcanic sulfur dioxide (SO2). In the inverse modeling system MPTRAC is used to perform two types of simulations, i.e., unit simulations for the reconstruction of volcanic emissions and final forward simulations. Both types of transport simulations are based on wind fields of the ERA-Interim meteorological reanalysis of the European Centre for Medium Range Weather Forecasts. The reconstruction of altitude-dependent SO2 emission time series is also based on Atmospheric InfraRed Sounder (AIRS) satellite observations. A case study for the eruption of the Nabro volcano, Eritrea, in June 2011, with complex emission patterns, is considered for method validation. Meteosat Visible and InfraRed Imager (MVIRI) near-real-time imagery data are used to validate the temporal development of the reconstructed emissions. Furthermore, the altitude distributions of the emission time series are compared with top and bottom altitude measurements of aerosol layers obtained by the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite instruments. The final forward simulations provide detailed spatial and temporal information on the SO2 distributions of the Nabro eruption. By using the critical success index (CSI), the simulation results are evaluated with the AIRS observations. Compared to the results with an assumption of a constant flux of SO2 emissions, our inversion approach leads to an improvement of the mean CSI value from 8.1 to 21.4 % and the maximum CSI value from 32.3 to 52.4 %. The simulation results are also compared with those reported in other studies and good agreement is observed. Our new inverse modeling and simulation system is expected to become a useful tool to also study other volcanic eruption events.

Abstract. In this study we compared temperatures and horizontal winds of meteorological analyses in the Antarctic lower stratosphere, a region of the atmosphere that is of major interest regarding chemistry and dynamics of the polar vortex. The study covers the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis, the ERA-Interim reanalysis, the Modern-Era Retrospective analysis for Research and Applications version 1 and 2 (MERRA and MERRA-2), and the National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis. The comparison was performed with respect to long-duration observations from 19 superpressure balloon flights during the Concordiasi field campaign in September 2010 to January 2011. Most of the balloon measurements were conducted at altitudes of 17–18.5 km and latitudes of 60–85° S. We found that large-scale state temperatures of the analyses have a mean precision of 0.5–1.4 K and a warm bias of 0.4–2.1 K with respect to the balloon data. Zonal and meridional winds have a mean precision of 0.9–2.3 m s−1 and a bias below ±0.5 m s−1. Standard deviations related to small-scale fluctuations due to gravity waves are reproduced at levels of 15–60 % for temperature and 30–60 % for the horizontal winds. Considering the fact that the balloon observations have been assimilated into all analyses, except for NCEP/NCAR, notable differences found here indicate that other observations, the forecast models, and the data assimilation procedures have a significant impact on the analyses as well. We also used the balloon observations to evaluate trajectory calculations with our new Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC), where vertical motions of simulated trajectories were nudged to pressure measurements of the balloons. We found relative horizontal transport deviations of 4–12 % and error growth rates of 60–170 km day−1 for 15-day trajectories. Dispersion simulations revealed some difficulties with the representation of subgrid-scale wind fluctuations in MPTRAC, as the spread of air parcels simulated with different analyses was not consistent. However, although case studies suggest that the accuracy of trajectory calculations is influenced by meteorological complexity, diffusion generally does not contribute significantly to transport deviations in our analysis. Overall, evaluation results are satisfactory and compare well to earlier studies using superpressure balloon observations.

Abstract. The accuracy of trajectory calculations performed by Lagrangian particle dispersion models (LPDMs) depends on various factors. The optimization of numerical integration schemes used to solve the trajectory equation helps to maximize the computational efficiency of large-scale LPDM simulations. We analyzed global truncation errors of six explicit integration schemes of the Runge-Kutta family, which we implemented in the Massive-Parallel Trajectory Calculations (MPTRAC) advection module. The simulations were driven by wind fields from operational analysis and forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) at T1279L137 spatial resolution and 3 h temporal sampling. We defined separate test cases for 15 distinct regions of the atmosphere, covering the polar regions, the midlatitudes, and the tropics in the free troposphere, in the upper troposphere and lower stratosphere (UT/LS) region, and in the middle stratosphere. In total, more than 5000 different transport simulations were performed, covering the months of January, April, July, and October for the years 2014 and 2015. We quantified the accuracy of the trajectories by calculating transport deviations with respect to reference simulations using a fourth-order Runge-Kutta integration scheme with a sufficiently fine time step. Transport deviations were assessed with respect to error limits based on turbulent diffusion. Independent of the numerical scheme, the global truncation errors vary significantly between the different regions. Horizontal transport deviations in the stratosphere are typically an order of magnitude smaller compared with the free troposphere. We found that the truncation errors of the six numerical schemes fall into three distinct groups, which mostly depend on the numerical order of the scheme. Schemes of the same order differ little in accuracy, but some methods need less computational time, which gives them an advantage in efficiency. The selection of the integration scheme and the appropriate time step should possibly take into account the typical altitude ranges as well as the total length of the simulations to achieve the most efficient simulations. However, trying to summarize, we recommend the third-order Runge-Kutta method with a time step of 170 s or the midpoint scheme with a time step of 100 s for efficient simulations of up to 10 days of simulation time for the specific ECMWF high-resolution data set considered in this study. Purely stratospheric simulations can use significantly larger time steps of 800 and 1100 s for the midpoint scheme and the third-order Runge-Kutta method, respectively.