The main goal of this study is to update a simple global mean, zero-dimensional, climate model developed by University of Reading and to run simulation to estimate the optimal model parameters. This two layer aqua planet model solve two differential equations for mixed layer and deep layer temperature anomaly which is forced by the mean radiative forcing. The main task is to extend the simulation to 2019 based on last IPCC data. The next one is to develop the minimization method to estimate the best model parameters based on observation data and model results. |
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Airborne measurements performed during research campaigns are the main source of information about turbulence in the upper parts of the Atmospheric Boundary Layers. Within this exercise a student will analyze wind velocity and temperature data from EUREC4A campaign. The first task is to calculate running averages. Next, by subtracting them from the corresponding measured time series, the student will calculate fluctuating velocity components and temperature. Next task is to estimate the momentum and heat fluxes and investigate convergence of these statistics as a function of the size of the averaging window. |
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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. |
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Air flows inside clouds are strongly turbulent and influences motion of small water droplets. Within this task a student will investigate how turbulence affects settling velocity of the droplets. For this a simplified, periodic velocity model will be used. The student should solve numerically motion of N water droplets in this field and calculate their mean vertical velocity, by averaging over droplets and over time. The program should be parallelized by adding OpenMP directives to compile and build an optimized executable. For the task programming skills (including knowledge of C++) are required. |
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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. |
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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. |
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This excercise concerns the Kelvin-Helmholz instailities which form in the presence of wind shear or a velocity difference across the interface between different fluids. The task will be to simulate the evolution of the vortex sheet numerically. The sheet will be represented as an ensemble of point vortices. The student should calculate how velocities and positions of vortices change in time. The data should be saved to files. For the task programming skills (knowledge of Python, Fortran or C++) are required. |
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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. |
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This exercise is based on a large dataset of time-lapse images of the glacial front of one of the marine terminating glaciers in Admiralty Bay, Antarctica. The goal is to use image processing tools available in Matlab to generate time series of calving events, based on differences between pairs of subsequent images. The exercise will include preprocessing of the images (removal of very dark and very light scenes, scenes with fog/rain etc.), identification of differences between images, computation of the size of calving events, and an initial analysis of the resulting time series. |
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A statistical analysis will be performed based on the results obtained in Part A) exercise, i.e. the obtained time series of calving events in Admiralty Bay, Antarctica. The analysis will provide an estimation of uncertainties related to the processing methods used and to the image acquisition itself. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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.
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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. |
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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. |
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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). |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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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. |
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