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Geophysical laboratory I / II (Academic year 2022/2023) - COPY (2023-10-04 15h03m28s)

Academic year: 2022/2023
Semester: winter/summer

LECTURE DESCRIPTION

Geophysical Laboratory  I (summer semester) / II (winter semester)

Rules for Academic year 2022/2023 (both semesters)

Field of study: Geophysics (Physics, II degree)

Organizational unit: Institute of Geophysics, Faculty of Physics, University of Warsaw

Coordinator: Iwona Stachlewska (iwona.stachlewska@fuw.edu.pl)

Tutors: Gustavo Abade, Daniel Albuquerque, Grzegorz Florczyk, Robert Grosz, Afwan Hafiz, Łucja Janicka, Konrad Kossacki, Stanisław Król, Maciej Karasewicz, Szymon Malinowski, Krzysztof Markowicz, Jakub Nowak, Katarzyna Nurowska, Pablo Ortiz-Amezcua, Hanna Pawłowska, Patryk Poczta, Iwona Stachlewska, Dominika Szczepanik, Artur Tomczak, Emeka Ugboma, Marta Wacławczyk, Dongxiang Wang, Olga Zawadzka-Mańko, Piotr Żmijewski.

Important information for students in academic year 2022/2023: 
This topic follows deadlines for the Academic calendar of University of Warsaw
http://informatorects.uw.edu.pl/en/info/academic-calendar/

For GL-II, note that the wintertime exam session ends on 12.02.2023 (dedline for submiting initial reports) and the resit exam session on 05.03.2023 (deadline for submiting revised reports, if needed).
For GL-I, note that the sumertime exam session ends on 09.07.2023 (dedline for submiting initial reports) and the resit exam session on 10.09.2023 (deadline for submiting revised reports, if needed)..

Students, please nothe that totors will not help in performing the exercize nor assess your work-progress/reports during the summer holidays 10.07.2022– 30.09.2023.

Thus tutors will assess and give mark ONLY to the reports that were submitted BEFORE the specified deadline dates!
For the students who performed the exerscize (confirmed by tutor) but did not submited the report the tutors will give mark 2.

Description:

The aim of the Laboratory is to familiarize students with experimental and theoretical methods and advanced analysis of geophysical data. The thematic scope of the proposed exercises includes topics in atmospheric physics, lithosphere physics and planetology.

The laboratory consists of performing three (GL II winter semester) or four (GL I semester) exercises.

Descriptions of the proposed exercises with names of tutors are listed below.

Literature is determined by tutors, according to the individual topic and scope of the exercise.

Assessment of the final grade is based on the student's reports on the selected exercises (3 for GL II and 4 for GL I). Each report is evaluated by the tutor. The final grade is the average of the ratings obtained from the individual reports. Lack of performing the given above the obligatory number of exercises results in failing the subject!

The laboratory is realized solely in English.

Student workload:
- preparation for exercises 30h (GL II), 40h (GL I)
- exercises 30h (GL II), 30h (GL I)
- preparation of results and preparation of reports 30h (GL II), 40h (GL I)

IMPORTANT NOTES:

Students that have performed a certain exercise in the previous semesters are not allowed to perform the same exercise in the current semester! In the submitted reports students are obligated to add information: "Herewith, I declare that I have not performed this exercise in any of the previous semesters".

Tutors are obligated to check for plagiarism and add information: "No plagiarism detected", along with the grade, date, and signature on the first page of each evaluated report. The scan/photo of this page has to be provided by the tutor to the coordinator asap.

Procedure:

1. The student selects the exercises from the list below and contacts the tutors to confirm that the exercise can be performed in a given semester.
2. Information about selected and confirmed exercises must be communicated by the student to the GL coordinator within 1 month of the beginning of the semester.
3. The student carries out each exercise under the tutor's supervision.
4. After completing the exercise, the student prepares a report and submits it for review by the tutor.
5. The coordinator receives an evaluated final report (with grade) from the student by the end of the exam session.
6. The report must contain the following information in the heather: Name of the laboratory: Geophysical Laboratory I (summer) or Geophysical Laboratory II (winter); academic year: 2022/2023; full title of the exercise; name and surname of tutor; name and surname of the student; student registration number at UW (USOS); date on which the first report is submitted to tutor, and if necessary - the date of the revision of the report.
7. The report must be written in the English language.
8. Failure to submit the graded report to the coordinator by the end of the exam session of a given semester means an unsatisfactory grade from the given exercise.
9. The final grade obtained by the student is the average of the ratings of the individual reports (3 grades for GL II and 4 grades for GL I, including the unsatisfactory grades.
10. The coordinator proposes the final grade to the student no later than one week before the end of the exam session.
11. The final grade is inserted to USOS on the last day of the exam session.
12. It is possible to improve each report until the end of the make-up session of a given semester.
13. The final grade is then the average of 3 (GLII) or 4 (GL I) grades (highest grade per exercise). 

COURSES MATERIALS
Lectures / Leader Lecture type

Both for numerical weather predictions as well as climate projections, it is crucial to represent well a thin layer of the atmosphere of the depth less than one kilometer right above the surface of the Earth, called the atmospheric boundary layer (ABL). The ABL takes two distinctive forms: a typical day-time state under sun, which is "convective", and a typical night-time state, which is "stable".

Within the task, the measurement data from the SHEBA Project (open data base available from: https://data.eol.ucar.edu/project?SHEBA/), will be studied. The student will first get acquainted with the basic data formats used to store the data and find in this database the measured mean wind, mean temperature, mean momentum and heat fluxes.

Next he/she will calculate gradients of the mean wind velocity and the mean temperature as well as the Obukhov length. By plotting the non-dimensional mean wind and mean temperature gradients against the non-dimensional vertical coordinate, he/she will determine the stability functions for the momentum and heat transport and compare them with the predictions of the standard Monin-Obukhov theory. The student will discuss and explain reasons for deviations of result from these predictions.

Lab

This exercise concerns the numerical calculation of scalar advection (temperature and water vapor) in a synthetic cloud flow. Condensation is performed using an instantaneous saturation adjustment scheme. This simple condensation model should provide reference results for testing and development of more sophisticated cloud microphysical schemes. Programming skills and basic knowledge of cloud physics are required.

Lab

The ground-based lidars data sets of the EMORAL lidar in Rzecin and the PollyXT and NARLa lidar data in Warsaw will be verified against the satellite Atmospheric Dynamics Mission Aeolus (ADM-Aeolus) of the European Space Agency (ESA). The ADM-Aeolus is the first satellite with equipment capable of performing global wind profile observation with aim to improve weather forecasting. It is capable of observing the wind profiles from the Earth surface up to the lower stratosphere (0-30 km). The wind-component profiles are measured by the Atmospheric LAser Doppler INstrument (ALADIN). As the basis of the measurement is Doppler effect the instrument is providing indirectly also an information of the aerosol load structure in the atmosphere.

In the frame of this task the student will perform the verification of the lidar data that are already evaluated by RS-Lab Team with the Single Calculus Chain of the ACTRIS. The task is covering data download for SCC and careful verification of the overpasses times against the calculate profiles (+/-1h availability), writing the profiles plotting routine to display the data, define the robust terms to assess their quality, and make a decision of their usefulness for the ADM-Aelous measurements verification.

Lab

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 model data.

Lab

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.

Lab

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.

Lab

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.

Lab

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.

Lab

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.

Lab

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.

Lab

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.

Lab

Aethalometer and Polar nephelometer are used to measure aerosol absorption and scattering coefficients. In case of both devices, due to the measurement methodology, determination of such quantities requires applying a series of corrections. As a part of the exercise, student will write the software to derive the single scattering albedo. The method is to be applied in urban polluted (Warsaw) and peri-urban (Vilnius) conditions.

Lab

The aim of the exercise is to retrieve the aerosol size distribution on the basis of spectral aerosol optical depth measurements by hand-held MICROTOPS sun photometer. The aerosol size distribution will be approximated by two log-normal distributions based on minimizing the cost function. During minimization, 2 or 4 parameters describing the size distribution are determined. The data can be obtained by the student using one of our instruments or use the observations form diferent field campaigns in Poland (Sopot, Kraków, Wrocław) and abraod (Vilnius, Orasac-Dubrovnik, Athens, Magurele-Bucharest, Ny-Alesund). 

Lab

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 rrural site versus urban and peri-urban sites using long-term measurements with AERONET sun-photometers.

Lab

The aim of the exercise is to estimate the aerosol radiation forcing on the basis of observation of surface solar flux and radiative transfer simulation of aerosol-free solar fluxes. In addition, the radiation budget at Earth’s surface will be determined, as well as the total energy budget, including sensible and latent heat fluxes.

Lab

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.

Lecture documents:
Instruction for the exercise: experiment ACE2
Instruction_microphysics_ACE2.pdf
ReadMe
ReadMe_ACE2.txt
Data from flight fr9721 ACE2
113747.2H0001
Data from flight fr9730 ACE2
121129.4H0001
Publication ACE2
Brenguier_etal_JGR_2003.pdf
Publication ACE2
Brenguier_etal_Tellus_2000_CloudyColumn.pdf
Publication ACE2
Pawlowska_etal_Tellus_2000.pdf
Publication ACE2
Raes_etal_Tellus2000_ACE2_overview.pdf
Instruction for the exercise: experiment RICO
Instruction_microphysics_RICO.pdf
ReadMe
ReadMe_RICO.txt
Data from flight RF06 RICO
RF06_hc0407_162400.0R0001
Data from flight RF07 RICO
RF07_hc0408_150000.0R0001
Publication RICO
Arabas_et_al_2009_GRL.pdf
Publication RICO
Rauber_etal_2007_RICO.pdf
Adiabatic Liquid Water Content
adiabaticLWC.pdf
Constants
constants.pdf
Lab

Maciej Karasewicz, Pablo Ortiz-Amezcua, Iwona Stachlewska

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 in Rzecin and/or at urban site in Warsaw.

Lab

The aim of the exercise if comparative analysis of atmospheric boundary layer (ABLH) form lidar observations conducted during different field campaigns with ESA MObile RAman Lidar (EMORAL). Two main tasks are to be done. First, a technical one is to derive ABLH using wavelet method with existing software. 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. and the diferent sites (rural, urban, peri-urban, costal, industrial).

Lab

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.

Lab

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.

Lab

The aim of the exercise is to derive the ofofiles of the aerosol depolarization (UV and VIS), water vapour mixing ratio, and fluorescence efficiency 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 or use an existing software  for the retrieval of the aforementioned profiles in the atmosphere, estimate the measurement uncertainties, and perform a comparative analysis of the three cases.

Lab

Olga Zawadzka-Mańko, Emeka Ugboma, Iwona Stachlewska

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.

Lab

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.

Lecture documents:
Measurement of cloud droplet size and concentration with shadowgraphy - instructions - Script for the classes
shadowgraph_intro_JN2020.pdf
Lab

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.

Lab

The ultrasonic anemometer installed ontop of the institute building records three components of the air flow velocity and virtual temperature at a rate up to 32 Hz. Measured fluctuations of velocity and virtual temperature allow for the calculation of turbulent fluxes of momentum and heat in the boundary layer of the atmosphere with the use of eddy correlation method. Relationship between those quantities determines, in turn, the dynamic stability in the layer, which is customarily expressed by the Monin-Obukhov length. Student’s tasks involve performing Reynolds decomposition of the recorded signals, calculating respective turbulent fluxes, deriving Monin-Obukhov length and analyzing its variability in the course of a few selected days.

Lab

The exercise aims at determining effects of relative humidity on optical and microphysical properties of aerosol in laboratory conditions. Measurements will be conducted using the aerosol condition system (ACS1000), which allows for applying controlled changes of relative humidity upon the air collceted using the inlet located on the measuring platform. The chamber consists of two measuring paths: one that contains dehumidified air with low relative humidity (approx. < 30%), while the other contains air that moves through a special moisturizing system enabling the setting of desired humidity value in the range from 40 to 90%. Both measurements take place simultaneously with the used of miniature OPC-N3 particle counters. This enables to determine changes in the particle size distribution and the scattering coefficient as the air humidity changes.

Lab

The aim of the exercise is Langley calibration of the Multifilter Rotating Shadowband Radiometer and deriving aerosol optical depth and Angstrom exponent. Student will work with data from MFR-7 mounted in Radiative Transfer Laboratory at the roof platfor of the Institute of Geophysics. During the exercise, the data processing will be done, including several corrections.

Lab

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