Quasi 18 h wave activity in ground-based observed mesospheric H2O over Bern, Switzerland

Observations of oscillations in the abundance of middle-atmospheric trace gases can provide insight into the dynamics of the middle atmosphere. Long-term, high-temporal-resolution and continuous measurements of dynamical tracers within the strato- and mesosphere are rare but would facilitate better understanding of the impact of atmospheric waves on the middle atmosphere. Here we report on water vapor measurements from the ground-based microwave radiometer MIAWARA (MIddle Atmospheric WAter vapor RAdiometer) located close to Bern during two winter periods of 6 months from October to March. Oscillations with periods between 6 and 30 h are analyzed in the pressure range 0.02–2 hPa. Seven out of 12 months have the highest wave amplitudes between 15 and 21 h periods in the mesosphere above 0.1 hPa. The quasi 18 h wave signature in the water vapor tracer is studied in more detail by analyzing its temporal evolution in the mesosphere up to an altitude of 75 km. Eighteen-hour oscillations in midlatitude zonal wind observations from the microwave Doppler wind radiometer WIRA (WInd RAdiometer) could be identified within the pressure range 0.1–1 hPa during an ARISE (Atmospheric dynamics Research InfraStructure in Europe)-affiliated measurement campaign at the Observatoire de Haute-Provence (355 km from Bern) in France in 2013. The origin of the observed upper-mesospheric quasi 18 h oscillations is uncertain and could not be determined with our available data sets. Possible drivers could be low-frequency inertia-gravity waves or a nonlinear wave–wave interaction between the quasi 2-day wave and the diurnal tide

Long-term observation of midlatitude quasi 2-day waves by a water vapor radiometer

A mesospheric water vapor data set obtained by the middle atmospheric water vapor radiometer (MIAWARA) close to Bern, Switzerland (46.88°N, 7.46°E) during October 2010 to September 2017 is investigated to study the long-term evolution and variability of quasi 2-day waves (Q2DWs). We present a climatological overview and an insight on the dynamical behavior of these waves with the occurring spectrum of periods as seen from a midlatitude observation site. Such a large and nearly continuous measurement data set as ours is rare and of high scientific value. The core results of our investigation indicate that the activity of the Q2DW manifests in burst-like events and is higher during winter months (November–February) than during summer months (May–August) for the altitude region of the mesosphere (up to 0.02hPa in winter and up to 0.05hPa in summer) accessible for the instrument. Single Q2DW events reach at most about 0.8ppm in the H2O amplitudes. Further, monthly mean Q2DW amplitude spectra are presented and reveal a high-frequency variability between different months. A large fraction of identified Q2DW events (20%) develop periods between 38 and 40h. Further, we show the temporal evolution of monthly mean Q2DW oscillations continuously for all months and separated for single months over 7 years. The analysis of autobicoherence spectra gives evidence that Q2DWs are sometimes phase coupled to diurnal oscillations to a high degree and to waves with a period close to 18h

Drone-based photogrammetry combined with deep-learning to estimate hail size distributions and melting of hail on the ground

Hail is a major threat associated with severe thunderstorms and an estimation of the hail size is important for issuing warnings to the public. Operational radar products exist that estimate the size of the expected hail. For the verification of such products, ground based observations are necessary. Automatic hail sensors, as for example within the Swiss hail network, record the kinetic energy of hailstones and can estimate with this the hail diameters. However, due to the small size of the observational area of these sensors (0.2 m2) the estimation of the hail size distribution (HSD) can have large uncertainties. To overcome this issue, we combine drone-based aerial photogrammetry with a state-of-the-art custom trained deep-learning object detection model to identify hailstones in the images and estimate the HSD in a final step. This approach is applied to photogrammetric image data of hail on the ground from a supercell storm, that crossed central Switzerland from southwest to northeast in the afternoon of June 20, 2021. The hail swath of this intense right-moving supercell was intercepted a few minutes after the passage at a soccer field near Entlebuch (Canton Lucerne, Switzerland) and aerial images of the hail on the ground were taken by a commercial DJI drone, equipped with a 50 megapixels full frame camera system. The average ground sampling distance (GSD) that could be reached was 1.5 mm per pixel, which is set by the mounted camera objective with a focal length of 35 mm and a flight altitude of 12 m above ground. A 2D orthomosaic model of the survey area (750 m2) is created based on 116 captured images during the first drone mapping flight. Hail is then detected by using a region-based Convolutional Neural Network (Mask R-CNN). We first characterize the hail sizes based on the individual hail segmentation masks resulting from the model detections and investigate the performance by using manual hail annotations by experts to generate validation and test data sets. The final HSD, composed of 18209 hailstones, is compared with nearby automatic hail sensor observations, the operational weather radar based hail product MESHS (Maximum Expected Severe Hail Size) and some crowdsourced hail reports. Based on the retrieved drone hail data set, a statistical assessment of sampling errors of hail sensors is carried out. Furthermore, five repetitions of the drone-based photogrammetry mission within about 18 min give the unique opportunity to investigate the hail melting process on the ground for this specific supercell hailstorm and location

Significant decline of mesospheric water vapor at the NDACC site Bern in the period 2007 to 2018

The middle atmospheric water vapor radiometer MIAWARA is located close to Bern in Zimmerwald (46.88°N, 7.46°E, 907m) and is part of the Network for the Detection of Atmospheric Composition Change (NDACC). Initially built in the year 2002, a major upgrade of the instruments spectrometer allowed to continuously measure middle atmospheric water vapor since April 2007. Thenceforward to Mai 2018, a time series of more than 11 years has been gathered, that makes a first trend estimate possible. For the trend estimation, a robust multi-linear parametric trend model has been used. The trend model encompasses a linear term, a solar activity tracker, the El Niño–Southern Oscillation (ENSO) index, the quasi-biennial oscillation (QBO) as well as the annual and semi-annual oscillation. In the time period April 2007 to Mai 2018 we find a significant decline in water vapor by −0.6±0.2ppmdecade−1 between 61 and 72km. Below the stratopause level (~48km) a smaller reduction of H2O of up to −0.3±0.1ppmdecade−1 is detected

Trajectory mapping of middle atmospheric water vapor by a mini network of NDACC instruments

The important task to observe the global coverage of middle atmospheric trace gases like water vapor or ozone usually is accomplished by satellites. Climate and atmospheric studies rely upon the knowledge of trace gas distributions throughout the stratosphere and mesosphere. Many of these gases are currently measured from satellites, but it is not clear whether this capability will be maintained in the future. This could lead to a significant knowledge gap of the state of the atmosphere. We explore the possibilities of mapping middle atmospheric water vapor in the Northern Hemisphere by using Lagrangian trajectory calculations and water vapor profile data from a small network of five ground-based microwave radiometers. Four of them are operated within the frame of NDACC (Network for the Detection of Atmospheric Composition Change). Keeping in mind that the instruments are based on different hardware and calibration setups, a height-dependent bias of the retrieved water vapor profiles has to be expected among the microwave radiometers. In order to correct and harmonize the different data sets, the Microwave Limb Sounder (MLS) on the Aura satellite is used to serve as a kind of traveling standard. A domain-averaging TM (trajectory mapping) method is applied which simplifies the subsequent validation of the quality of the trajectory-mapped water vapor distribution towards direct satellite observations. Trajectories are calculated forwards and backwards in time for up to 10 days using 6 hourly meteorological wind analysis fields. Overall, a total of four case studies of trajectory mapping in different meteorological regimes are discussed. One of the case studies takes place during a major sudden stratospheric warming (SSW) accompanied by the polar vortex breakdown; a second takes place after the reformation of stable circulation system. TM cases close to the fall equinox and June solstice event from the year 2012 complete the study, showing the high potential of a network of ground-based remote sensing instruments to synthesize hemispheric maps of water vapor

Trajectory mapping of middle atmospheric water vapor by a mini network of NDACC instruments

The important task to observe the global coverage of middle atmospheric trace gases like water vapor or ozone usually is accomplished by satellites. Climate and atmospheric studies rely upon the knowledge of trace gas distributions throughout the stratosphere and mesosphere. Many of these gases are currently measured from satellites, but it is not clear whether this capability will be maintained in the future. This could lead to a significant knowledge gap of the state of the atmosphere. We explore the possibilities of mapping middle atmospheric water vapor in the Northern Hemisphere by using Lagrangian trajectory calculations and water vapor profile data from a small network of five ground-based microwave radiometers. Four of them are operated within the frame of NDACC (Network for the Detection of Atmospheric Composition Change). Keeping in mind that the instruments are based on different hardware and calibration setups, a height-dependent bias of the retrieved water vapor profiles has to be expected among the microwave radiometers. In order to correct and harmonize the different data sets, the Microwave Limb Sounder (MLS) on the Aura satellite is used to serve as a kind of traveling standard. A domain-averaging TM (trajectory mapping) method is applied which simplifies the subsequent validation of the quality of the trajectory-mapped water vapor distribution towards direct satellite observations. Trajectories are calculated forwards and backwards in time for up to 10 days using 6 hourly meteorological wind analysis fields. Overall, a total of four case studies of trajectory mapping in different meteorological regimes are discussed. One of the case studies takes place during a major sudden stratospheric warming (SSW) accompanied by the polar vortex breakdown; a second takes place after the reformation of stable circulation system. TM cases close to the fall equinox and June solstice event from the year 2012 complete the study, showing the high potential of a network of ground-based remote sensing instruments to synthesize hemispheric maps of water vapor

The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC) and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards) and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically  ∼  1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0–1 % yr−1. In particular, MLS shows a trend of between 0.5 % yr−1 and 0.7 % yr−1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr−1 (at Mauna Loa, Hawaii) and −0.1 % yr−1 (at Lauder, New Zealand)

Numerische Simulationen von langlebigen Kondensstreifen mit Lagrange'scher Mikrophysik

Der weltweit steigende Anspruch auf Mobilität, vor allem in den Entwicklungsländern, wird zwangsläufig zu wachsenden Verkehrsaufkommen f¨uhren. Man erwartet, dass es in der Flugverkehrssparte zu den größten Steigerungsraten kommt. Der Einfluss des Flug- verkehrs auf das globale Klimasystem ist nicht marginal. Die Emissionen von strahlungs-wirksamen Treibhausgasen (CO2, NOx, H2O, CH4) durch Verbrennungsprozesse in den Triebwerken stellen nur einen Aspekt des Problems dar. In bestimmten Luftschichten, die gen¨ugend kalt und feucht sind, kann ein durch die Triebwerke induzierter Wolken- bildungsprozess eingeleitet werden. Es entstehen zunächst linienförmige Kondensstreifen. Sie setzen sich aus Eispartikeln unterschiedlichster Formen zusammen. Wenn es die atmosphärischen Umgebungsbedingungen ermöglichen, können die Kondensstreifen (KS) über Stunden existieren und sich dabei verbreitern