Within this task measurement data collected during drone flights will
be analyzed. The data includes wind velocity, corrected for the orientation
of the drone, and temperature. The measurements were made over land (in
the Central Geophysical Observatory in Belsk) and over sea
during the cruise of Maria S. Merian 112/2 from Colombia to Spain.
From the available data, mean wind and mean temperature, as well as
their vertical gradients will be calculated. This allows to
estimate the gradient Richardson number which is a measure of the
stability of the atmospheric boundary layer. Within this task,
characteristic properties of the atmospheric boundary layer over land and
over sea will be compared and discussed. 

Lab 
The MoninObukhov theory for the Atmospheric Boundary Layer involves several assumptions, one of them is the statistical stationarity of the flow. This assumption is not always fulfilled, especially under stable startifications.
Within this task the student will study time dependence of the stability functions or the momentum and heat transport in the stable atmospheric boundary layer and verify whether nonstationarity causes deviations from the predictions of the MoninObukhov theory. 

Lab 
Meteorological towers and masts with appropriate instrumentation have been employed to measure wind velocity, temperature, humidity and other variables at several levels above the surface. From the measurement data mean variables as well as turbulent fluxes can be calculated.
To compare measurements with predictions of different theories for the Atmospheric Boundary Layer, gradients of these mean variables should be determined. For this, however, proper interpolation schemes should be used. Within this exercise the student should develop interpolation schemes to calculate the gradients. The student will also study influence of the type of interpolation scheme on results. 

Lab 
This task focuses on the daytime convective regime of the Atmospheric Boundary Layer. The student will study measurement data from the Cabauw meteorological mast. They will 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 the student should calculate gradients of the mean wind velocity and the mean temperature as well as the Obukhov length using finitedifference approach. By plotting the nondimensional mean wind and mean temperature gradients against the nondimensional vertical coordinate, the student will determine the stability functions for the momentum and heat transport in the convective daytime regime and compare them with theoretical predictions. 

Lab 
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 daytime state under sun, which is "convective", and a typical nighttime 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 nondimensional mean wind and mean temperature gradients against the nondimensional vertical coordinate, he/she will determine the stability functions for the momentum and heat transport and compare them with the predictions of the standard MoninObukhov 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 groundbased 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 (ADMAeolus) of the European Space Agency (ESA). The ADMAeolus 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 (030 km). The windcomponent 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 RSLab 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 ADMAelous 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 pointparticles) 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 HertzKnudsen 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 COVID19 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 (insitu) properties of cosmic bodies using automatic landing probes, e.g. comet ChuryumovGerasimenko (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 COVID19 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 ADRPollyXT 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 tempospatial 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 periurban (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 handheld MICROTOPS sun photometer. The aerosol size distribution will be approximated by two lognormal 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, OrasacDubrovnik, Athens, MagureleBucharest, NyAlesund). 

Lab 
The AERONET (AErosol RObotic NETwork) program is a federation of groundbased remote sensing aerosol networks established by NASA and LOAPHOTONS (CRNS) and provides a longterm, 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 periurban sites using longterm measurements with AERONET sunphotometers. 

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 aerosolfree 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 

Lab 
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 wellmixed (WML) layer at daytime. and the diferent sites (rural, urban, periurban, costal, industrial). 

Lab 
Mixedphase clouds are threephase 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 mixedphase 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 mixedphase 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 (insitu) properties of cosmic bodies using automatic landing probes, e.g. comet ChuryumovGerasimenko (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 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 available lidar measurements for three cases: 1) Rayleigh atmosphere, 2) airmass 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 
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


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 MoninObukhov length. Student’s tasks involve performing Reynolds decomposition of the recorded signals, calculating respective turbulent fluxes, deriving MoninObukhov 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 OPCN3 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 MFR7 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 