Browsing by master's degree program "Ilmakehätieteiden maisteriohjelma (Atmospheric Sciences)"

Air ions can play an important role in new particle formation (NPF) process and consequently influence the atmospheric aerosols, which affect climate and air quality as potential cloud condensation nuclei. However, the air ions and their role in NPF have not been comprehensively investigated yet, especially in polluted area. To explore the air ions in polluted environment, we compared the air ions at SORPES site, a suburban site in polluted eastern China, with those at SMEAR II, a well-studied boreal forest site in Finland, based on the air ion number size distribution (0.8-42 nm) measured with Neutral Cluster and Air Ion Spectrometer (NAIS) during 7 June 2019 to 31 August 2020. Air ions were size classified into three size ranges: cluster (0.8-2 nm), intermediate (2-7 nm), and large (7-20 nm). Median concentration of cluster ions at SORPES (217 cm−3) was about 6 times lower than that at SMEAR II (1268 cm−3) due to the high CS and pre-existing particle loading in polluted area, whereas the median large ion concentration at SORPES (197 cm−3) was about 3 times higher than that of SMEAR II (67 cm−3). Seasonal variations of ion concentration differed with ion sizes and ion polarity at two sites. High concentration of cluster ions was observed in the evening in the spring and autumn at SMEAR II, while the cluster ion concentration remained at a high level all day in the same seasons. The NPF events occurred more frequently at SORPES site (SMEAR II 16% ; SORPES: 39%), and the highest values of NPF frequency at both sites were in spring ((SMEAR II: spring: 43%; SORPES: spring: 56%). During the noon time on NPF event day, the concentration of intermediate ions were 8-14 times higher than same ours on non-event days, indicating that can be used as an indicator for NPF in SMEAR II and SORPES. The median formation rate of 1.5 nm at SMEAR II were higher then that at SORPES, while higher formation rate of 3 nm ions were observed at SORPES. At 3 nm, the formation rate of charged particles was only 11% and 1.6% of the total rate at SMEAR II and SORPES respectively, which supports the current view that neutral ways dominate the new particle process in continental boundary. However, higher ratio between charged and total formation rate of 3 nm particle at SMEAR II indicates ion-induced nucleation can have a bigger contribution to NPF in clear area in comparison to polluted area. Higher median GR of 3-7 nm (SMEAR II: 3.1 nm h−1; SORPES: 3.7 nm h−1) and 7-20 nm (SMEAR II: 5.5 nm h−1; SORPES: 6.9 nm h−1) ions at SORPES were found in comparison to SMEAR II, suggesting the higher availability of condensing vapors at SORPES. This study presented a comprehensive comparison of air ions in completely different environments, and highlighted the need for long-term ion measurements to improve the understanding of air ions and their role in NPF in polluted area like eastern China

The Arctic Ocean is known to be inhabited with energetic mesoscale eddies commonly detected in depths from 200 m to 1200 m. Due to their high energetics and ability to transfer momentum, heat, salt and biochemical properties for long distances from their origin, eddies may considerably affect the structure of a water column in the Arctic Ocean. This study investigated an anticyclonic eddy event detected at one of the mooring stations deployed under the Nansen and Amundsen Basins Observational System project. The mooring located at the deep part of the continental slope of the Laptev Sea and conducted autonomous measurements during the years 2013–2015. The conductivity-temperature-depth, as well as current measurements from the Acoustic Doppler Current Profiler in the upper ocean (24–82 m) and from the McLane Moored Profiler in the intermediate layer (88–760 m), were examined. Spectral analysis of the currents and calculation of the eddy available potential energy were performed. This study revealed a mesoscale eddy with the core centred deeper than 750 m drifted past the mooring for 2 months. Its horizontal length scale was ∼128 km. The water properties typical for the Fram Strait Branch of the Atlantic water carried by the subsurface boundary current were trapped in the eddy. This study suggests that the eddy was originated from the baroclinic instability of the front between the Fram Strait Branch and the Barents Sea Branch of the Atlantic water flow.

Research in radar technology requires readily accessible data from weather systems of varying properties. Lack of real-world data can delay or stop progress in development. Simulation aids this problem by providing data on demand. In this publication we present a new weather radar signal simulator. The algorithm produces raw time series data for a radar signal using physically based methodology with statistical techniques incorporated for computational efficiency. From a set of user-defined scatterer characteristics and radar system parameters, the simulator solves the radar range equation for individual, representative precipitation targets in a virtual weather cell. The model addresses the question of balancing utility and performance in simulating signal that contains all the essential weather information. For our applications, we focus on target velocity measurements. Signal is created with respect to the changing position of targets, leading to a discernable Doppler shift in frequency. We also show the operation of our simulator in generating signal using multiple pulse transmission schemes. First, we establish the theoretical basis for our algorithm. Then we demonstrate the simulator's capability for use in experimentation of advanced digital signal processing techniques and data acquisition, focusing on target motion. Finally, we discuss possible future developments of the simulator and their importance in application.

Carbon monoxide (CO) is a chemically reactive trace gas in the atmosphere, indirectly affecting radiative balance. The oxidation of CO with hydroxyl radical (OH) is the large sink of atmospheric CO. The reactions of CO and OH decrease the atmospheric capacity to oxidize atmospheric methane (CH4), hence indirectly extends the lifetime of CH4 in the atmosphere. In addition, CO oxidation increases the abundance of tropospheric ozone (O3). CH4 and O3 are both very strong greenhouse gases, and it has been estimated that the cumulative indirect radiative forcing of CO can be even more significant than the third most powerful greenhouse gas, nitrous oxide. This study studied CO fluxes in four different ecosystems: a boreal forest, a boreal fen, a cropland in the boreal region, and a sisal plantation in the semi-arid tropical zone. All the ecosystems were CO sources during the growing season from May to August, and ecosystems showed strong seasonal variation. Fluxes had a regular diurnal cycle, peaking at noon and zero flux or small uptake at night. The main drivers for the CO emissions were radiation and air temperature. The strong correlation between radiation and CO flux proved that photodegradation was an important process in biogenic CO emissions. Radiation and air temperature were used in a simple linear regression model to estimate the biogenic CO emissions in the study sites. The model was trained for Hyytiälä data in 2016, tested for the rest of the data from Hyytiälä in 2015 and 2017 and other sites. The chamber measurements showed that soils were CO sinks and CO emissions were mainly from vegetation. Generally, in many upscaling models of CO, soil consumption is considered significantly larger than photodegradation. This study showed that many terrestrial ecosystems can be sources of CO, even though there are generally considered as a sink of CO. There is a need for ecosystem-scale flux measurements in other ecosystems and latitudes to understand better the global CO budget.

Diurnal temperature range (DTR), defined as the difference between daily maximum and minimum temperatures, is an important variable in ecosystem dynamics. Human-induced climate change, which has increased mean temperatures worldwide, has been noted to cause global changes in DTR. In this thesis, the changes in daily maximum and minimum temperatures, as well as diurnal temperature range, were studied between the climatological periods of 1961–1990 and 1991–2020 from twenty weather observation stations in Finland. Student’s t-test was utilized to assess the statistical significance of the differences between period mean values. The results show that daily maximum and minimum temperatures have risen significantly across Finland in all seasons. The differences between 1961–1990 and 1991–2020 mean values were +1.26 °C and +1.51 °C for daily maximum and minimum temperatures, respectively. Both daily maximum and minimum temperatures have risen most notably in winter (DJF), with daily extreme temperatures increasing asymmetrically. The increase in temperatures was more pronounced for daily minimum temperatures, rising by approximately 3 °C in winter, nearly one degree more than daily maximum temperatures during the same season. Annually averaged diurnal temperature range has generally decreased in Finland from 1961–1990 to 1991–2020. The decrease in DTR was statistically significant in the northern part of Finland, and overall, the country experienced a statistically significant decrease of −0.25 °C. The decreases in annual mean DTR exhibited a latitudinal pattern, with the largest decrease observed in northern Finland and smallest in southern Finland. The majority of the decrease in DTR occurred during winter across the country, whereas changes in the other seasons were smaller and varied in direction. A decrease in DTR in Finland has been reported by other studies, although the results in this thesis (−0.09 °C/decade trend) are larger in amplitude compared to other estimates. The decrease in winter DTR was attempted to be explained by changes in air mass advection, which substantially influences diurnal temperature range in addition to influencing day-to-day variations in temperature. It was concluded that changes in air mass advection have substantially influenced the changes in winter DTR, but they may not necessarily explain all of the observed changes. Cloud cover changes were examined using ERA5 reanalysis data, but these changes were judged to be unimportant for the decrease in winter DTR. However, asymmetrical cloud cover changes in the other seasons could have potentially contributed to the differing direction of DTR change observed in spring, summer and autumn across the country.

There has been a major decreasing trend in the amount of sea ice in the Arctic since the 1990s. The Arctic amplification (AA) warms the Arctic climate as a result of the global warming, strengthened by the ice albedo feedback loop. The ice albedo feedback loop is caused by melting of snow and ice surfaces. Melting of snow and ice causes changes to the surface albedo, which is a measure of the amount of incident solar radiation that is reflected. Melting snow and ice surface types and revealed open water or terrain have significantly lower albedo than the original snow and ice surfaces. Therefore more radiation is absorbed, which has a warming effect. CLARA-A3 dataset is analyzed in this thesis. Surface albedo (SAL) and top of atmosphere (ToA) albedo values are compared. Data from June and July of the years 2012 and 2014 are analyzed. The objective is to check the consistency of these data records. The surface albedo values are also modelled with the Simplified Model for Atmospheric Correction (SMAC) to further validate the data. The relationship between SAL and ToA is also studied. This is achieved by analysing snow and ice optical properties, interaction of solar radiation with Earth’s atmosphere and the effect of illumination and viewing geometry. The results of data analysis indicate consistency between the observed values for SAL and ToA albedo differences within the observed period. The results are also in line with predictions made based on previous studies on the seasonal trends in the Arctic albedo. Furthermore results modelled with SMAC show dependency with the observed results and thereby validate the data. However data from June 2012 and July 2014 are unfortunately contaminated, which means that there are less usable data and therefore of reduced accuracy. Data analysis conducted for a larger SAL and ToA dataset would be needed to provide a basis for studying the decadal and seasonal trend of the Arctic SAL and ToA albedo difference. The whole melting season beginning in March and ending in September is important to study to better understand seasonal variability and trends as well as decadal trends in the Arctic.

As global concern about climate change grows, particularly in meeting the Paris Agreement’s goal of limiting global warming below 2 °C, studying and observing the effects of light-absorbing aerosol particles in the atmosphere becomes a necessity. This study determined 38 years of equivalent black carbon (eBC) concentrations in Joensuu airport from 1965 to 2003. Samples were originally collected on either cellulose or glass fibre filters for radioactivity monitoring. Measuring black carbon optically from filters comes with its own challenges, such as artefacts caused by scattering aerosol particles and filter material itself. Thus, a calibration setup was built to study the effects of apparent absorption caused by scattering aerosols and the loading effect in various types of filters. First, in the calibration experiments, we examined how different filter materials affect measured transmittance when pure black carbon is deposited, showing non-linear calibration functions. Additionally, we investigated the impact of apparent absorption by depositing various-sized ammonium sulfate particles onto different filter materials, e.g. cellulose and glass fibre. Results showed that apparent absorption depended on the size of the scattering aerosol particles and the filter material. Smaller particles resulted in a 5–38 % overestimation of absorption, while larger particles showed 1–14 %, depending on the transmittance values. In the latter part of the thesis, real sample filters were analyzed with Particle Soot Absorption Photometer for transmittance, and with the conversion functions derived from the first part of the thesis, transmittance values were converted into eBC. For some samples, ion chromatography was used to determine ion concentrations of some scattering particles that alter optical measurements. From 1965 until 1971, cellulose filters were used for collecting aerosol particles, and glass fibre filters were used onwards. Conversion functions obtained from this study were shown to be inadequate for cellulose filters. However, for glass fibre filters, the calculated eBC concentration values were comparable to other studies. Depending on the season, cellulose filters (1965–1971) had 0.25–12 μgm⁻³ of eBC, and glass fibre filters (1972–2003) had eBC of 0.48–3.8 μgm⁻³. For those filters where ions were analyzed, ions contributed up to 30 % overestimation of eBC, making analysis of ions in samples crucial information. Statistically decreasing trends were found in both filters, where in winter had a rate of -22 ngm⁻³yr⁻¹ and -6 ngm⁻³yr⁻¹ in summer. Calculated trends was similar to what was observed in Helsinki. The decrease in eBC can be attributed to the technological advancement in emission control. This comprehensive study enabled the long-term estimation of eBC concentrations solely from transmittance measurements, and provided insights in optical measurements in filters.

Topic of this Master's thesis was to study how different forest management practises can influence the climate change mitigation potential of Finnish pine forests. Study was carried out with a land ecosystem model JSBACH-FOM. Topic was analyzed by comparing the changes in the carbon budget, surface albedo and the water balance over a 45 year period under different management scenarios. Harvest scenarios used were ecology oriented, balanced and profit oriented harvest. In the ecology oriented harvest scenario mainly old pines are harvested, while in the profit oriented scenario harvests are directed towards younger pines preventing them from reaching old ages. Balanced harvest scenario is between the two. Model was also run under two future climate scenarios, RCP 4.5 and RCP 8.5 in order to determine if the scale of climate change affects results of different harvest scenarios. Profit oriented harvesting results in both the largest positive and largest negative impacts in comparison to if forest was left unmanaged. Ecologically oriented is the opposite, and balanced is in between. No significant differences were found between the climate scenarios in any of the modelled variables.

In order to reliably quantify the impact of cities to the climate change, carbon dioxide (CO2) fluxes from urban areas need to be accurately estimated. Currently, eddy covariance (EC) measurements of net ecosystem exchange (NEE) are among the most used methods for CO2 balance assessment at ecosystem scale. They cannot, however, directly separate gross primary production (GPP) from different sources of CO2 , but instead different tracers and methods need to be used for the separation. In this thesis, urban carbonyl sulfide (COS) fluxes are reported and used as a tracer for biogenic CO2 uptake. For estimating GPP, a leaf-relative uptake (LRU) of CO2 and COS during photo- synthesis has to be calculated. Three different methods for ecosystem scale LRU estimations are compared in order to find which performs the best at assessing urban GPP from EC measurements. LRUNEE method is based on averaging LRU obtained directly from an equation using EC measurements of CO2 and COS. LRUP AR uses parameterisation of photosynthetically available radiation (PAR) to estimate LRU, and LRUCAP uses additional environmental parameters and information of soil water content (SWC), water vapour pressure deficit (VPD) and PAR. EC measurements were conducted at SMEAR III station (ICOS ecosystem associate site) in Helsinki during summer 2022 using a quantum cascade laser gas analyser. Mole fractions of COS, CO2, CO, and water vapour were collected with 10 Hz frequency, together with three-dimensional wind speed measurements. 30-min fluxes were calculated and used for estimating LRU and GPP with the three methods above. Source area of the station was divided into urban, street, and vegetation sectors. To compare different LRU methods, EC measured GPP from vegetation sector was used because it had the smallest anthropogenic emissions. CO and COS fluxes were compared to estimate co-emissions from fuel combustion. Median COS flux of −25.5 pmol m−2 s−1 was measured, indicating a biogenic CO2 uptake in the study area. For simplicity, soil related COS fluxes were neglected. LRUPAR performed the best at estimating GPP, giving an average CO2 uptake of 13.9 μmol m−2 s−1 for the vegetation sector. Furthermore, peak median anthropogenic emissions of 9.1 μmol m−2 s−1 were deduced with LRUPAR, which agrees with earlier research. However, due to problems with instrumentation the data collection period was so short that distinction between LRUPAR and LRUCAP was not unambiguous. Clear is that setting a constant value for LRU leads to significant underestimation of GPP, and a misunderstanding of its behaviour in heterogeneous urban landscape. Further development of COS based GPP estimation should include a more careful instrumentation and revision of the parameterisation of LRUCAP method.

To evaluate whether CMIP6 models provide good simulation in Arctic sea-ice extent, thickness, and motion, selected 6 CMIP6 models are EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, GFDL-ESM4, MPI-ESM1-2-HR, NORESM2-LM. For CMIP6 models and observations, seasonal cycle and the annual variation from 1979-2014 of sea-ice extent were studied, for sea-ice thickness and sea-ice motion, the Arctic is separated into three regions, geographical distribution, inter-annual variation from 1979-2014, seasonal cycle, and trend were studied. Then student t-test is used to evaluate whether the model output has a significant difference from observation, to select the best model(s). For sea-ice extent, EC-Earth3 is overestimating sea-ice extent, especially in winter, BCC-CSM2-MR model underestimates sea-ice extent, ACCESS-CM2, MPI-ESM1-2-HR, NorESM2-LM models perform the best. For sea-ice thickness, BCC-CSM2-MR underestimates sea-ice thickness, EC-Earth3, ACCESS-CM2, and NORESM2-LM models are overestimating sea-ice thickness. GFDL-ESM4 and MPI-ESM1-2-HR have the best performance at sea-ice thickness simulation. For sea-ice motion, the MPI-ESM1-2-HR model overestimates sea-ice drifting speed all year round, ACCESS-CM2 model tends to overestimate sea-ice drifting speed in summer for region1 and region2, in region3 ACCESS-CM2 model mostly overestimate sea-ice motion except winter months. NorESM2-LM model has the best performance overall, and ACCESS-CM2 has the second-best simulation for region1 and region2. EC-Earth3 also has a satisfactory simulation for sea-ice motion. Models and observation also agree on common results for sea-ice properties: Maximum sea-ice extent occurs in March, and minimum sea-ice extent occurs in September. There's a decreasing trend of sea-ice extent. The Central Arctic and Canadian Archipelago always have the thickest sea ice, followed by the East Siberian Sea, Laptev Sea, and Chukchi Sea, Beaufort Sea. East Greenland Sea, Barents Sea, Buffin Bay, and the Kara Sea always have the thinnest sea ice. There's a decreasing trend for sea-ice thickness according to models, sea-ice is thicker in the Chukchi Sea and the Beaufort Sea than in Laptev and East Siberian seas. Winter sea-ice thickness is higher than in summer, and sea-ice thickness has a more rapid decreasing rate in summer than in winter. Laptev and the East Siberian Sea have the most rapidly sea-ice thinning process. Sea-ice thickness has seasonal cycle that maximum usually occurs in May, and minimum sea-ice thickness happens in October. For sea-ice motion, there's an increasing trend of sea-ice motion, and summer sea-ice motion has faster sea-ice motion than winter, Chukchi Sea, and the Beaufort Sea has faster sea-ice motion than Laptev and the East Siberian Sea. Corresponding with the comparatively faster-thinning in the Laptev and the East Siberian Seas simulated by models, there's also a faster increasing rate in the Laptev and the East Siberian Sea.