- Abteilung Optische Sondierungen und Höhenforschungsraketen
- Abteilung Radarsondierungen
- Abteilung Modellierung atmosphärischer Prozesse
- Abteilungsübergreifende Zusammenarbeit
Remote Sensing Techniques (Feb-2017)
RS1: Mesospheric turbulence estimation based on VHF radar observations of Polar Mesospheric Echoes
Supervisors: Ralph Latteck, Prof. Jorge L. Chau
Polar mesosphere summer echoes (PMSE) are strong at altitudes between about 80 and 95 km at polar latitudes during summer. PMSE are caused by inhomogeneities in the electron density resulting from neutral air turbulence in combination with the effect of negatively charged aerosol or ice particles. VHF radar echoes have also been observed from the mid-mesosphere (about 55 to 85 km altitude) during winter times (PMWE) at both northern and southern latitudes and could be attributed to Bragg scattering from fluctuations that were due to neutral air turbulence, too. MAARSY (Middle Atmosphere Alomar Radar System), a VHF radar system at the polar latitude, has the capability to resolve the temporal and spatial features of such echoes and their corresponding spectral components. Since the width of the Doppler spectrum of a VHF radar signal contains information about the intensity of atmospheric turbulence, mesospheric observations obtained by MAARSY using a variety of radar techniques, can be used to characterize mesospheric turbulence at different horizontal scales within the observed volume. The study will be complemented by in-situ turbulence measurements from existing and upcoming rocket campaigns. The selected candidate is expected to gain an in-depth understanding of MAARSY, to work on existing and new radar techniques that would require familiarity with statistical inverse theory as well as radio propagation, to participate in field campaigns, and to become acquainted with atmospheric turbulence and dynamics.
RS2: Improving a meteor radar temperature retrieval algorithm
Supervisors:Prof. Jorge L. Chau
Meteors entering the Earth’s atmosphere form an ambipolar plasma trail, which diffuses into the ambient atmosphere. The diffusive decay time is proportional to the pressure, temperature, and aerosol concentration at the altitude of the observation. There are some semi-empirical approaches to estimate a mean temperature from a large collection of meteors in the altitude range between 80-100 km based on this diffusive decay time. The goal of this project is to obtain a more reliable mesospheric temperature measurement using lidar and satellite observations. The selected candidate will improve these existing temperature estimations by applying statistical inverse methods that have the capability to separate the different contributions to the temperature.
RS3: Horizontally resolved mesospheric waves
Supervisors: Prof. Jorge L. Chau
Recently, IAP developed a new approach to resolve the spatial and temporal features of the wind field at mesospheric altitudes, called MMARIA (Multistatic/Multifrequency Agile Radar for Investigations of the Atmosphere). The MMARIA approach consists of using multi-static configurations of meteor radars, either by adding receive-only stations to existing monostatic systems, combining closely-located monostatic systems, or by adding transmitters-only stations with pseudo-random coded capabilities, around receive-stations. Such configurations have been deployed in northern Germany and northern Norway. One of the main goals of MMARIA is to exploit the 4D (zonal, meridional, vertical, and temporal) variability of the mesospheric neutral. The estimation of the winds and their uncertainties requires statistical inverse theory approaches. To validate such approaches and to explore the newly obtained dynamics, the study would be complemented by airglow images obtained at four different mesospheric altitudes (filters). Given that results from airglow imagers will be limited to clear night conditions, the combined studies will focus on special events, e.g., bores, fronts, etc. The selected candidate is expected to get an in-depth knowledge of MMARIA, to get familiar with statistical inverse theory, to participate in field-campaigns, to gain a good understanding of atmospheric waves and other related measurement techniques.