Äärilämpötilojen alueellinen vaihtelu Suomessa

Tiivistelmä Tässä raportissa tarkastellaan erittäin matalien ja korkeiden ilman lämpötilojen alueellista vaihtelua maassamme ääriarvoanalyysin keinoin. Tutkimus muodostuu kahdesta osasta. Ensiksi arvioidaan hyvin poikkeuksellisten lämpötilojen esiintymistä Suomessa Ilmatieteen laitoksen 20-30 pisimmän säähavaintoaikasarjan perusteella. Aikasarjojen pituus on tyypillisesti 75–165 vuotta. Hetkellisten lämpötilojen lisäksi tutkittavana on se, miten korkeana lämpötila voi pysytellä kuuden tai 24 tunnin ajan, ja samoin tarkastellaan 24 tunnin kylmyysjaksoja. Raportin toinen osa keskittyy puolestaan kalenterikuukausittaisiin ja -vuosittaisiin kylmyysennätyksiin ajanjaksolla 1971–2000, lyhyesti myös ajanjaksolla 2001–2010, käyttäen kaikkia kyseisinä ajanjaksoina toimineita havaintoasemia, joita oli noin 100. Raportin ensimmäisessä osassa esitetään yleistettyyn ääriarvojakaumaan (GEV) perustuvat, ns.lohkomaksimimenetelmää käyttäen määritetyt 50-, 100-, 500- ja 1000 vuoden toistuvuustasojen todennäköisimmät lämpötila-arvot sekä niiden 95 %:n luotettavuusrajat. Todennäköisimmät arvot on myös interpoloitu koko Suomen alueen kattavaan hilaruudukkoon, ja nämä tulokset on esitetty alueellisen vaihtelun havainnollistamiseksi karttamuodossa. Raportin toisessa osassa määritetään puolestaan kylmyysennätysten aluekeskiarvot Suomen eri ilmastollisekologisilla vyöhykkeillä asemakohtaisia arvoja ryhmittelemällä ja tutkitaan kylmyysennätysten vuodenaikaiskulkua. Lopuksi raportin toisessa osassa verrataan keskenään tuloksia, jotka perustuvat joko osassa 1 käytettyihin pitkiin, mutta määrältään melko niukkoihin havaintoaikasarjoihin, tai vaihtoehtoisesti osan 2 alueellisesti tiheisiin, mutta lyhyehköihin, vain 30 vuoden mittaisiin aikasarjoihin. Tulokset olivat enimmäkseen yhteneväisiä. Ainoastaan Lapissa, meren saaristoissa ja Helsingin Kaisaniemessä 30 vuoden pakkasennätykset olivat 2–4 °C alemmat kuin pitkien aikasarjojen perusteella osassa 2 määritetyt 40 vuoden toistuvuustasot.Abstract The purpose of this study is to create a consistent description of spatial variations of low and high air temperature extremes in Finland based on extreme value analysis. The study consists of two parts. First, the occurrence of very exceptional low or high air temperatures in Finland have been assessed based on 20-30 longest long-term observational time series of the Finnish Meteorological Institute. The length of these time series was typically 75-165 years. Besides instantaneous temperature values, also six- and 24-hour periods of very warm and 24-hour periods of very cold weather have been examined. The second part of the report, in turn, focuses on monthly and yearly temperature records in 1971–2000, briefly also in 2001-2010. That part of the study used all the available temperature data at about 100 observational weather stations in Finland. In part one of this report, the most probable temperature values and their 95% confidence intervals have been estimated for 50-, 100-, 500- and 1000-year return levels. The estimates are based on the generalized extreme value (GEV) theory and the block maxima method. To illustrate the spatial variations of the temperature extremes, the most probable values have been interpolated into a grid coverring the whole of Finland and the results are depicted as maps. In part two, regionally-averaged means of low temperature records are given for the seven ecoclimatic zones in Finland: Åland mainland, archipelago, southern boreal, southern/middle transition belt, middle boreal, northern boreal and subarctic. In addition, seasonal variations of the temperature records have been examined for all those eco-climatic zones. Finally in part two, we compare results that are based either on relatively few but long observational time series (those also used in part one) or on a multitude of rather short time series. The results were mainly found congruent. Only in Lapland, in coastal archipelago and in Helsinki City the estimates for the 40-year return levels of low air temperature were 2-4 ºC lower, if based on the short time series, compared to those assessed with the longer time series

Battle of the bands: a long-term analysis of frequency band and channel distribution development in WLANs

In this article, we present the results of a long-term analysis ofWireless Local Area Network (WLAN) frequency band and channel distribution development. To the best of our knowledge, no similar research has been published in recent academic publications. Overcrowding of the limited frequency space on the 2.4 GHz band has become a significant issue in WLAN networking. Due to the overabundance of devices operating at 2.4 GHz, avoiding network performance degrading interference has become impossible in densely populated environments. Although the latest 802.11 WLAN standard amendments have shifted their emphasis toward the wider and less congested 5 GHz band, the 2.4 GHz band has stayed as the dominant frequency band. To observe the evolvement of WLAN frequency band and channel utilisation, data collected on nine WLAN surveys conducted between May 2019 and January 2022 was analysed. Furthermore, a simple linear regression model was produced to forecast the future development of WLAN frequency band utilisation. It was hypothesised that there would be an increase in 5 GHz frequency band utilisation as devices compliant with the latest 802.11 standard amendments become widely adopted. The survey results show a significant increase in 5 GHz frequency band utilisation. While the number of networks operating at 2.4 GHz saw a modest 42% increase, the number of networks operating at 5 GHz over doubled during the survey period. At the end of the study, 35% of all detected networks operated at 5 GHz, compared to 25% at the beginning of the study. Based on the produced linear regression model, the portion of 5 GHz networks in the survey area is expected to reach the level of 2.4 GHz networks by the autumn of 2025.</p

A systematic methodology for continuous WLAN abundance and security analysis

In this paper, we present a systematic methodology for continuous surveying and analysis of 802.11 Wireless Local Area Network (WLAN) abundance and security, based on the passive wireless network scanning technique called wardriving. The objective is to provide an efficient, scalable, and easily accessible methodology for collecting, analysing and storing WLAN survey data. To adhere to these set requirements, the presented survey and analysis processes can be carried out with freely available open-source software and common off-the-shelf hardware. While extensive literature has been produced on wardriving and numerous WLAN survey studies have been documented in previous works, to our knowledge, no similar comprehensive methodology for systematic WLAN surveying and analysis has been previously presented. To further rationalise the need for surveying and analysing WLAN networks, an investigation on the related literature and the current state of the WLAN networking landscape has been conducted. Furthermore, as surveying WLAN networks via the wardriving technique undoubtedly raises legal and moral concerns, the legitimacy and ethics of wardriving have been examined. To test the effectiveness of the proposed methodology, a primary test and calibration WLAN survey was conducted in three separate locations within a middle-sized city located in Southwest Finland. Based on the survey results, WLAN security in Finland is in a relatively good state. During the test survey, we successfully collected and analysed data from 720 WLAN networks, proving the effectiveness of the proposed methodology. From the 720 detected WLAN networks, 6% used insecure encryption protocols, 12.8% were unencrypted and a clear majority of 81.3% used the WPA2 encryption protocol. Results also show that wireless network device owners in the surveyed areas are not inclined to alter the factory-set default settings of their wireless networks. It was noted that roughly 40% of the surveyed networks used easily identifiable factory-set SSIDs and only 5.4% of the networks had a cloaked SSID. Furthermore, the survey data shows that WLAN devices from 38 different manufacturers were detected. Three of the most popular manufacturers in the surveyed area were Cisco with 28.3%, Huawei with 15.7% and Ruckus Networks with 9.7%.</p

Rakennusten energialaskennan testivuosi 2012 ja arviot ilmastonmuutoksen vaikutuksista

Tiivistelmä Ilmaston lämpeneminen vaikuttaa rakennusten lämmitys- ja jäähdytysenergian tarpeeseen. Tässä tutkimuksessa muodostettiin rakennusten energialaskennassa Suomessa käytettävät uudet sääaineistot, tuotettiin ilmastoskenaarioiden avulla rakennusten energialaskelmiin soveltuvat tulevaisuuden sääaineistot ja arvioitiin rakennusten energiankulutusta vuoden 2030 muuttuneessa ilmastossa Rakennusten energialaskentaa varten kehitetty uusi testivuosi (TRY2012) korvaa aiemmin käytetyn testivuoden 1979. Uuden testivuoden tunnittaiset sääaineistot energialaskennan vyöhykkeillä I–II, III ja IV muodostettiin Vantaalla, Jyväskylässä ja Sodankylässä vuosina 1980–2009 tehtyjen säähavaintojen perusteella. Testivuoden kunkin kalenterikuukauden sääaineistot valittiin sellaiselta vuodelta, jonka aikana kyseisen kuukauden sääolot olivat mahdollisimman lähellä ilmastollista keskimääräistilaa. Käytännössä kalenterikuukausien valinta tehtiin tilastollisella menetelmällä tarkastellen lämpötilaa, kosteutta, auringon säteilyä ja tuulen nopeutta. Näitä neljää säämuuttujaa painotettiin sen mukaan, kuinka paljon ne vaikuttavat Suomessa rakennusten lämmitys- ja jäähdytystarpeeseen. Tyypilliselle uudispientalolle ja toimistorakennukselle tehdyt simuloinnit osoittivat, että lämmitys- ja jäähdytystarpeen kannalta tärkein säämuuttuja on ulkoilman lämpötila, mutta kesällä auringon säteilyn vaikutus on suunnilleen yhtä suuri. Tutkimuksessa arvioitiin myös ilmastonmuutoksen vaikutuksia. Ilmastomallien tulosten pohjalta laadittiin tilastollisilta ominaisuuksiltaan vuosien 2030, 2050 ja 2100 arvioitua ilmastoa vastaavat tulevaisuuden testivuosien sääaineistot. Vuoden 2030 tienoilla vuoden keskilämpötilan arvioidaan olevan paikkakunnasta riippuen 1,2–1,5 astetta korkeampi kuin TRY2012:n perusteella. Talvella keskilämpötila nousee noin kaksi astetta ja kesällä vajaan asteen. Lämpötilan vaihtelevuus pienenee talvipuolella vuotta noin 10 %. Auringon säteilyn väheneminen talvella ja keväällä, tuulen vähäinen voimistuminen marrashelmikuussa ja ilman suhteellisen kosteuden pieni kasvu loka–huhtikuussa otettiin myös huomioon tulevaisuuden testivuosia laadittaessa. Lopuksi arvioitiin ilmastonmuutoksen vaikutuksia rakennusten energiantarpeeseen nykyisiä rakentamismääräyksiä noudatettaessa. Laskelmissa esimerkkinä käytetyn pientalon tilojen ja ilmanvaihdon lämmitystarve vähenee vuoteen 2030 mennessä noin 10 % ja jäähdytystarve kasvaa 17–19%. Toimistotalon lämmitystarve on vastaavasti 13% pienempi ja jäähdytystarve 13-15 % suurempi kuin nykyisessä ilmastossa. Kaikkiaan rakennusten kokonaisostoenergiankulutus vähenee vuoteen 2030 mennessä 4–7 % ilmaston muuttumisen takia.Abstract: The ongoing climate change is expected to affect the energy demand for heating and cooling of buildings. Building energy consumption is often assessed by simulation algorithms that require hourly meteorological data. For this purpose, weather observations from the year 1979 have previously been used in Finland as a reference. Here, we describe a new test reference year, TRY2012, that was constructed by using weather observations at three measurement stations (Vantaa, Jyväskylä and Sodankylä) during 1980–2009. TRY2012 consists of weather data for twelve months that originate from different calendar years, each month having weather conditions close to the long-term climatological average. The months for TRY2012 were selected using Finkelstein-Schafer parameters for four climatic variables (air temperature, humidity, solar radiation and wind speed); these parameters were weighted depending on how important individual climatic variables are for the building energy consumption in Finland. Calculations for two example buildings, a detached house and an office building, indicate that the most influential climatic variable for annual energy demand is air temperature. In summer, solar radiation and air temperature are of broadly equal influence. We also assessed the influence of human-induced climate change on typical weather conditions for the years 2030, 2050 and 2100. Multi-model mean estimates from 7 to 19 global climate models, together with the TRY2012 weather data, were used to construct artificial meteorological data for the future. The projected reference year TRY2030 is 1.2–1.5ºC warmer than TRY2012, with the lower end of the range corresponding to Vantaa in southern Finland and the higher value to Sodankylä in the north. Seasonal mean temperature is projected to increase by about two degrees in winter and by slightly less than one degree in summer. The variability in temperature will diminish in the winter half of the year by about 10 %. In addition, the projections include decreases in solar radiation in winter and spring, slight increases in wind speed in November-February, and small rises in relative air humidity in all seasons except summer. Utilizing the reference years TRY2012 and TRY2030, we calculated the mean monthly and annual energy consumption for the two example buildings in the current and projected future climate. Based on the simulations, the heat energy consumption of spaces and ventilation will decrease by 10% for the detached house and by 10–13% for the office building, whereas space cooling electricity will increase by 17–19% for the detached house and by 13–15% for the office building. Because electricity for cooling relative to the total delivered energy is minor, the total energy consumption of the example buildings is projected to decrease by 4–7% by 2030

Climate variability and trends in the Valkea-Kotinen region, southern Finland : comparisons between the past, current and projected climates

Peer reviewe

Sources and sinks of greenhouse gases in the landscape : Approach for spatially explicit estimates

Climate change mitigation is a global response that requires actions at the local level. Quantifying local sources and sinks of greenhouse gases (GHG) facilitate evaluating mitigation options. We present an approach to collate spatially explicit estimated fluxes of GHGs (carbon dioxide, methane and nitrous oxide) for main land use sectors in the landscape, to aggregate, and to calculate the net emissions of an entire region. Our procedure was developed and tested in a large river basin in Finland, providing information from intensively studied eLTER research sites. To evaluate the full GHG balance, fluxes from natural ecosystems (lakes, rivers, and undrained mires) were included together with fluxes from anthropogenic activities, agriculture and forestry. We quantified the fluxes based on calculations with an anthropogenic emissions model (FRES) and a forest growth and carbon balance model (PREBAS), as well as on emission coefficients from the literature regarding emissions from lakes, rivers, undrained mires, peat extraction sites and cropland. Spatial data sources included CORINE land use data, soil map, lake and river shorelines, national forest inventory data, and statistical data on anthropogenic activities. Emission uncertainties were evaluated with Monte Carlo simulations. Artificial surfaces were the most emission intensive land-cover class. Lakes and rivers were about as emission intensive as arable land. Forests were the dominant land cover in the region (66%), and the C sink of the forests decreased the total emissions of the region by 72%. The region's net emissions amounted to 4.37 +/- 1.43 Tg CO2-eq yr(-1), corresponding to a net emission intensity 0.16 Gg CO2-eq km(-2) yr(-1), and estimated per capita net emissions of 5.6 Mg CO2-eq yr(-1). Our landscape approach opens opportunities to examine the sensitivities of important GHG fluxes to changes in land use and climate, management actions, and mitigation of anthropogenic emissions. (C) 2021 The Authors. Published by Elsevier B.V.peerReviewe