IGF



Geophysical laboratory I / II (Academic year 2025/2025)

Academic year: 2024/2025
Semester: winter/summer

LECTURE DESCRIPTION

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

Rules for Academic year 2023/2024 (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, Piotr Dziekan, Grzegorz Florczyk, Rayonil Gomes-Carneiro, Robert Grosz, Afwan Hafiz, Łucja Janicka, Paweł Jedrejko, Maciej Karasewicz, Camilla Kasar-Borges, Konrad Kossacki, Stanisław Król, Szymon Malinowski, Krzysztof Markowicz, Katarzyna Nurowska, 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 2024/2025: 
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 end of the wintertime exam session (9 February 2025) is the dedline for submiting initial reports;
while the end of the resit exam session (2 March 2025) is the deadline for submiting revised reports, if needed.

For GL-I,
note that the end of the sumertime exam session (29 June 2025) is the dedline for submiting initial reports;
while the end of the resit exam session (1-14 September 2025) is the deadline for submiting revised reports, if needed.

Tutors will assess and give mark ONLY to the reports that were submitted no later than 1 day BEFORE the specified deadline dates!

Tutors will not assess student work-progress/reports during period of summer holidays

IMPORTANT: For those 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 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 and they are not allower to do any plagiarism, including auto-plagiarism!  

STUDENTS in the submitted reports are obligated to add information: "Herewith, I declare that I have not performed this exercise in any of the previous semesters. Herewith, I declare that there is no plagiarism in this report".

TUTORS are obligated to check the reports 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; 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 (mark "2") 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
Large Eddy Simulation (LES) technique has become an important tool in the atmospheric turbulence research.
In this method the largest eddy structures are resolved on a numerical grid, while the effect of smaller
(subgrid) eddies is taken into account through a proper closure. John Hopkins Turbulence Database contains
datasets with results of Direct Numerical Simulations and Large Eddy Simulations of various test
cases, including geophysical rotating stratified turbulence and LES of the stably stratified atmospheric boundary layer.

Within this task a student will get acquainted with the basic data formats used to store the data and learn
about methods to download and post-process the data. The task is to calculate mean quantities like mean velocity,
mean temperature and fluxes from the given fields and plot them as a function of height. The student
will calculate the Obukhov length and study turbulence statistics in the region of the surface layer,
as well as identify the presence of the Ekman spiral at larger altitudes.
Lab
Within the task, the measurement data from the MOSAiC expedition (open data base), 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

Rain drops are formed through coalescence of smaller droplets, which is a consequence of collisions between droplets. Student task will be to model the collision-coalescence process using a probabilistic description. The goal is to quantify the number of "lucky" droplets, which are droplets that undergo a series of unlikely collisions and grow to much larger sizes than average droplets. Results will be compared with theoretical estimates. This exercise is intended as a follow-up to the exercise "Simple model of collision-coalescence in clouds".

Lab

Students will learn how to run and analyze numerical simulations of clouds. Simulations will be done using the University of Warsaw Lagrangian Cloud Model, a state-of-the-art model developed at IGF. Data analysis will make use of the Xarray Python package. Both simulations and data analysis will be done through a Jupyter Notebook ran on a supercomputing cluster. Basic knowledge of Python programming language is the only prerequisite for this laboratory.

Lab

The aim of the exercise is to analyse properties of biomass-burning aerosol. The goal 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.

Agnieszka Makulska, Hanna Pawłowska, Piotr Dziekan

Oct. 15, 2024, 2:32 p.m.

Class

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

Afwan Hafiz, Iwona Stachlewska

The exercise concerns development of simple version of an eye-safety lidar simulator. The task of the student is to design the methodology and come up with an algorithm for calculation of the eye-safety for a lidar with pulsed laser and vertically-aiming beam with respect to the overflying aircraft. The developed code should have several crucial parameters settable by user. The student need to decide which parameters must be considered, whereby both laser and aircraft characteristics need to be take into account in this case. As part of the report, student need to provide the guidelines on how to use the code.

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
Turbulence kinetic energy, dissipation rate and the integral length scale
are the basic physical quantities which characterize turbulence. They are used in various
turbulence models and parametrization schemes.
Within this exercise a student will analyze wind velocity data measured
during EUREC4A campaign and estimate the above mentioned quantities.
The student will investigate whether the Taylor law, which is a classical
relation between these three basic quantities is satisfied.
Lab

The aim of the exercise is to derive properties of minerat dust agigination if African or Asian deserts. The profiles of aerosol optical properties, depolarization ratio and relative humidity will be obtained, 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

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

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 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

The aim of the exercise is to derive the profiles 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 lidar measurements for different cases, e.g. Rayleigh atmosphere, air-mass of biomass combustion, and 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 diffrent cases. The feasibility of using the obtained information for aerosol typing will be assessed.

Lab

The aim of the exercise is retrieval of atmospheric boundary layer height (ABLH) using etastic scattering lidar signals in near-real-time (NRT) and/or offline, as well as comparative analysis of diurnal variability of ABLH at selected site (rural, urban, peri-urban, costal, peatland, mountain, industrial). Lidar observations conducted during different field campaigns with different lidars/ceilometers can be used. Three 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. Third one, it to compare the lidar-derived ABLH results with boundary layer derived form models (e.g. WRF, ECMWF, PALM).

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

Olga Zawadzka-Mańko, Emeka Ugboma, Iwona Stachlewska

The exercise aims to familiarize students with satellite remote sensing, widely used in atmospheric research. In this case, it is crucial to understand the design of the algorithms used for different detectors. As part of the classes, students will also conduct analyses of satellite data for a given case study (to be determined together with their supervisor) in terms of various parameters, such as atmospheric aerosols, cloudiness, and anthropogenic pollution.

Lab

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