Geophysical laboratory I / II (Academic year 2020/2021)

Magnetic survey is a near-surface experimental geophysics method broadly used in environmental investigations. Magnetometers measure disturbances in the Earth's magnetic field. The exercise aims at introducing students to the subject of the magnetic research, which is one of the most important and broadly applied geophysical methods. A magnetometer will be used to detect features which may induce local variations of the magnetic field. The magnetometer data will be acquired and processed by the student with the use of a dedicated software. The data will be visualized, analyzed and interpreted. 

Retrieval of atmospheric boundary layer top using lidar and/or ceilometer data in NRT. Analyses of diurnal variability of boundary layer at urban and rural site. Comparisons with boundary layer derived form models (WRF, ECMWF).

The finite inertia of droplets in a turbulent fluid causes droplets to diverge from regions of high vorticity and to converge preferentially in regions of low vorticity. This creates strong deviations from uniformity in droplet concentration. The aim of the exercise is to simulate the motion of droplets (modeled as point-particles) in a synthetic turbulent flow under the influence of gravity. Simulation results should explain to what extent droplet inertia, gravity, and turbulence affect droplet spatial distribution.

The aim of this exercise is to study processes of formation and evolution of cloud droplets. It will be realized using an existing numerical parcel model (https://github.com/igfuw/parcel). Main tasks include:  getting acquainted with the model documentation, installation of the model, running of a set of numerical simulations. Results obtained will have to be thoroughly analyzed in order to identify parameters having impact on droplet size distribution. Realization of this exercise will result in effective understanding of parcel model as a tool used in numerical simulations of cloud processes, and also deeper understanding of cloud microphysical processes.

The rate of sublimation is commonly calculated using simple Hertz-Knudsen equation. This equation was derived ignoring microstructure of material and assuming equilibrium distribution of the velocities of molecules condensing on the surface and leaving it. Thus, is it gives only approximate result. It can be corrected using temperature dependent sublimation coefficient (e.g. Kossacki et al. 1999; Gundlach et al. 2011; Kossacki et al. 2017). 

Exercise: Sublimation of ice is investigated in laboratory, using cooled vacuum chamber. Measured parameters are: position of the surface and the temperature. Student is expected to perform measurement and derive the temperature dependent rate of sublimation.

This exercise is dedicated to advanced student.

Note that, due to the COVID-19 situation, the student will receive raw measurement data for analysis.

The exercise is aimed at determination of the thermal conductivity of granular ice, or natural snow (if it is available) without sampling the test material. The measurement is made using linear probe technology. It is used in practice in situations when taking a sample of the material is inexpedient or technically impossible. This method is applied to investigate directly (in-situ) properties of cosmic bodies using automatic landing probes, e.g. comet Churyumov-Gerasimenko (mission Rosetta, experiment MUPUS).

Idea is the following: changes of the temperature of a long thin heater inserted in a solid material is a function of its thermal conductivity. When the heating power is known it is sufficient to register  changes of the temperature. The latter can be done automatically. 

Student is expected to perform 2 -3 measurements and analyze the source data. 

This exercize is dedicated to advanced student.

Note that, due to the COVID-19 situation, the student will receive raw measurement data for analysis.

The purpose of the exercise is to analyze EMORAL lidar measurement data collected during field campaign over the Natura 2000 peatland in Rzecin. The profiles of particle extinction and backscattering coefficients, depolarization ratio and water vapor mixing ratio will be derived. The student will use available lidar measurements and a set of calibration measurements for this purpose. He will write numerical programs for calculation of profiles and estimate measurement errors. Finally he/she will interpret the obtained results.

The aim of the exercise is to derive profiles of aerosol optical properties, depolarization ratio and relative humidity, so as to characterize the atmosphere using the signals of ADR-PollyXT lidar and NARLa lidar. The student will use available lidar observations in combination with weather profiling of radiosounding and photometric measurements. The data will be processed using available numerical programs, including estimates of measurement errors. For the analysis and interpretation of the processed data, the student will use the methodology proposed by him/herself.

The exercise is to define a methodology for synergistic data analysis of the ESA EMORAL lidar and the LATMOS BASTA cloud radar profiles to predict the tempo-spatial distribution of aerosol and clouds in the atmosphere. The key issue here will be (a) correctly calibrating the measurements taken by both devices and b) setting and optimising signal thresholds to distinguish different types of aerosol and clouds.

The AERONET (AErosol RObotic NETwork) program is a federation of ground-based remote sensing aerosol networks established by NASA and LOA-PHOTONS (CRNS) and provides a long-term, continuous and readily accessible public domain database of aerosol optical, microphysical and radiative properties. The standardization of instruments, calibration, and processing by the network allows for directly comparing aerosol properties from different environments. This exercise is intended to focus on the characterization of aerosol load, optical and physical properties as well as on their temporal variability over a rural site versus Warsaw urban site using long-term measurements with AERONET sun-photometers.

NOTE: This topic is open for realization only for students who already have experience with atmospheric physics!

The exercise aims at familiarizing students with the basic microphysical properties of clouds (concentration and size of cloud droplets), their variability in space, and their dependence on the type of cloud. The exercise will involve the analysis of the measurement data from the ACE2 (Second Aerosol Characterization Experiment, Canary Islands) and the RICO (Rain in Cumulus over the Ocean; Caribbean, 2004-2005) experiments carried out in Stratocumulus and Cumulus clouds, respectively. The implementation of this exercise will allow students to effectively learn the basic (and more advanced) parameters characterizing clouds, understand and remember which are the most important processes that govern clouds.

Data files of the CHM15k Lufft ceilometer and C318 CIMEL photometer need to bee looked at from the perispective of use for the calculations of the atmospheric correction. The data collected during the Atmo-FLEX campaign will be evaluated in terms of deriving boundary layer and optical depth. Comparative study will follow.

Doppler lidar system allows for obtaining vertical profiles of wind vector within the atmospheric boundary layer with high spatial and temporal resolution for atmospheric applications. The aim of this exercise is to be able to filter and process the data to properly represent, understand and interpret different patterns observed with Doppler lidar (e.g. related to nocturnal jets or daytime convection). The analysis will cover several examples measured over a peatland site close to Rzecin (Poland).

The aim of the exercise if comparative analysis of atmospheric boundary layer (ABLH) form lidar observations conducted during one of the field campaigns with ESA MObile RAman Lidar (EMORAL) in Poland. Two main tasks are to be done. First, a technical one is to derive ABLH using wavelet method. Second, a scientific one is to explain the differences in ABLH in terms of the nocturnal (NL) and residual (RL) layers at night and the well-mixed (WML) layer at daytime. 

Mixed-phase clouds are three-phase systems consisting of water vapor,
ice particles and supercooled liquid droplets. In this exercise the
student will model and simulate the phase partitioning of water
condensate in mixed-phase clouds using a bulk microphysical
approach. Simulations will be made for the adiabatic cloud parcel
model. We plan the following course of the exercise: learning the
model equations and the thermodynamics of mixed-phase systems, developing
the numerical code and conducting calculations for various model
parameters. The simple modeling approach used in this exercise should
provide reference results for testing and development of more
sophisticated microphysical schemes.

The exercise is aimed at determination of the thermal conductivity of sand without sampling the test material. The measurement is made by linear probe technology. It is used in practice in situations when taking a sample of the material is inexpedient or technically impossible. This method is applied to investigate directly (in-situ) properties of cosmic bodies using automatic landing probes, e.g. comet Churyumov-Gerasimenko (mission Rosetta, experiment MUPUS).

Idea is the following: changes of the temperature of a long thin heater inserted in a solid material is a function of its thermal conductivity. When the heating power is known it is sufficient to register changes of the temperature. The latter can be done automatically.

Student is expected to perform 2 -3 measurements and analyze the source data.

Alternatively, student may process the existing source data.

This exercise is dedicated for beginner student.

The aim of the exercise is to derive the aerosol depolarization profiles (UV and VIS) and the water vapour mixing ratio from the European Space Agency Mobile Aerosol Raman EMORAL lidar signals. Student will use available lidar measurements for three cases: 1) Rayleigh atmosphere, 2) air-mass of biomass combustion, and 3) air mass of mineral dust. She/He will write numerical programs for the retrieval of water vapor profiles and depolarization in the atmosphere, estimate the measurement uncertainties, and perform a comparative analysis of the three cases.

The exercise aims at familiarizing students with the topics of satellite remote sensing, widely used in atmospheric research. As part of the classes, student will conduct analyses of satellite data for a given case study (to be determined together with supervisor), in terms of various parameters, such as atmospheric aerosols, cloudiness, anthropogenic pollution.

Size distribution of droplets and their concentration in a unit volume are basic microphysical properties characterizing the cloud. Knowing both, one can also calculate total liquid water content. The goal of the exercise is to introduce the method of measuring those parameters with shadowgraphy. Student’s tasks include the lab measurement of droplet sizes and concentrations in the streams generated by a few different devices (e.g. pond mist maker, household humidifier, flower sprayer, nasal hygiene spray), comparing the properties of the obtained size distributions and estimating total liquid water content.

For ambitious: The second goal of the exercise is to introduce optical techniques for measuring size distribution and fall velocity of rain drops, as well as rainfall rate. Student task’s involve selecting the proper experiment time based on weather forecast, measuring rain drop sizes and velocities at the roof of the institute building with shadowgraphy technique and comparing the results with routine observations performed with a disdrometer.

Turbulent Kinetic Energy (TKE) dissipation rate is a key physical quantity characterizing turbulent air motions present in the atmosphere. According to Kolmogorov’s theory, its value can be derived from velocity fluctuations, measured e.g. with a stationary ultrasonic anemometer or various airborne instruments. The goal of the exercise is to learn several approaches for estimation of TKE dissipation rate (power spectrum, structure functions, number of crossings), apply them for the velocity data collected routinely at the top of the institute building and compare the results for the period of a few days.