75 research outputs found

    Menneen ajan UV-sÀteilyn rekonstruointi

    Get PDF
    Solar ultraviolet (UV) radiation has a broad range of effects concerning life on Earth. Soon after the mid-1980s, it was recognized that the stratospheric ozone content was declining over large areas of the globe. Because the stratospheric ozone layer protects life on Earth from harmful UV radiation, this lead to concern about possible changes in the UV radiation due to anthropogenic activity. Initiated by this concern, many stations for monitoring of the surface UV radiation were founded in the late 1980s and early 1990s. As a consequence, there is an apparent lack of information on UV radiation further in the past: measurements cannot tell us how the UV radiation levels have changed on time scales of, for instance, several decades. The aim of this thesis was to improve our understanding of past variations in the surface UV radiation by developing techniques for UV reconstruction. Such techniques utilize commonly available meteorological data together with measurements of the total ozone column for reconstructing, or estimating, the amount of UV radiation reaching Earth's surface in the past. Two different techniques for UV reconstruction were developed. Both are based on first calculating the clear-sky UV radiation using a radiative transfer model. The clear-sky value is then corrected for the effect of clouds based on either (i) sunshine duration or (ii) pyranometer measurements. Both techniques account also for the variations in the surface albedo caused by snow, whereas aerosols are included as a typical climatological aerosol load. Using these methods, long time series of reconstructed UV radiation were produced for five European locations, namely SodankylÀ and Jokioinen in Finland, Bergen in Norway, Norrköping in Sweden, and Davos in Switzerland. Both UV reconstruction techniques developed in this thesis account for the greater part of the factors affecting the amount of UV radiation reaching the Earth's surface. Thus, they are considered reliable and trustworthy, as suggested also by the good performance of the methods. The pyranometer-based method shows better performance than the sunshine-based method, especially for daily values. For monthly values, the difference between the performances of the methods is smaller, indicating that the sunshine-based method is roughly as good as the pyranometer-based for assessing long-term changes in the surface UV radiation. The time series of reconstructed UV radiation produced in this thesis provide new insight into the past UV radiation climate and how the UV radiation has varied throughout the years. Especially the sunshine-based UV time series, extending back to 1926 and 1950 at Davos and SodankylÀ, respectively, also put the recent changes driven by the ozone decline observed over the last few decades into perspective. At Davos, the reconstructed UV over the period 1926-2003 shows considerable variation throughout the entire period, with high values in the mid-1940s, early 1960s, and in the 1990s. Moreover, the variations prior to 1980 were found to be caused primarily by variations in the cloudiness, while the increase of 4.5 %/decade over the period 1979-1999 was supported by both the decline in the total ozone column and changes in the cloudiness. Of the other stations included in this work, both SodankylÀ and Norrköping show a clear increase in the UV radiation since the early 1980s (3-4 %/decade), driven primarily by changes in the cloudiness, and to a lesser extent by the diminution of the total ozone. At Jokioinen, a weak increase was found, while at Bergen there was no considerable overall change in the UV radiation level.Auringon ultraviolettisÀteily (UV-sÀteily) vaikuttaa usealla tavalla elÀmÀÀn maan pÀÀllÀ. 1980-luvun puolivÀlin jÀlkeen huomattiin, ettÀ stratosfÀÀrin otsonimÀÀrÀ oli vÀhenemÀssÀ etenkin EtelÀmantereen kevÀtkaudella mutta myös maapallonlaajuisesti. StratosfÀÀrin otsonikerros suojelee elÀmÀÀ maan pÀÀllÀ haitalliselta UV-sÀteilyltÀ, ja havaitut otsonikerroksen muutokset aiheuttivat huolta ihmiskunnan mahdollisesti aiheuttamista muutoksista UV-sÀteilymÀÀrissÀ. TÀmÀn seurauksena useimmat UV-sÀteilyn mittausasemat ovat perustettuja juuri tÀhÀn aikaan 1990-luvun taitteessa. UV-sÀteilyn mittausaikasarjat ovat siis melko lyhyitÀ, ja ne pystyvÀt tyypillisesti kertomaan meille UV-sÀteilyn vaihteluista vain viimeisten noin 15 vuoden ajalta. TÀmÀn vÀitöskirjatyön tavoitteena oli tuottaa uutta tietoa UV-sÀteilyn vaihteluista menneisyydessÀ kehittÀmÀllÀ ns. UV-rekonstruointimenetelmiÀ, joissa hyödynnetÀÀn yleisiÀ meteorologisia mittauksia ja kokonaisotsonitietoa menneen ajan UV-sÀteilyn arvioimiseen. TÀssÀ työssÀ kehitettiin kaksi UV-rekonstruointimenetelmÀÀ. Molemmissa lasketaan aluksi sÀteilynkuljetusmallilla pilvettömÀn sÀÀn UV-sÀteilymÀÀrÀ. Pilvien vaikutus otetaan tÀmÀn jÀlkeen huomioon joko auringon paistehavaintojen tai pyranometrimittauksien perusteella. LisÀksi kumpikin menetelmÀ ottaa huomioon lumen aiheuttamat vaihtelut maan pinnan heijastuvuudessa. IlmakehÀn pienhiukkaset ovat mukana laskuissa tyypillisenÀ mÀÀrÀnÀ kullakin paikkakunnalla. NÀitÀ kahta menetelmÀÀ kÀyttÀen tuotettiin pitkiÀ aikasarjoja menneen ajan UV-sÀteilystÀ viidelle asemalle Euroopassa. Asemat olivat SodankylÀ ja Jokioinen Suomessa, Bergen Norjassa, Norrköping Ruotsissa ja Davos SveitsissÀ. Kumpikin tÀssÀ työssÀ kehitetty menetelmÀ ottaa huomioon tÀrkeimmÀt UV-sÀteilymÀÀrÀÀn vaikuttavat tekijÀt ja tulokset ovat hyviÀ verrattaessa riippumattomiin havaintoihin. TÀmÀn vuoksi menetelmiÀ voidaan pitÀÀ luotettavina. Pyranometrimittauksiin perustuva menetelmÀ on tarkempi kuin paistehavaintoihin perustuva etenkin pÀivÀkohtaisia arvoja verrattaessa. Kuitenkin paistehavaintoihin perustuva menetelmÀ on kuukausiarvoja tarkasteltaessa lÀhes yhtÀ tarkka kuin pyranometrimenetelmÀ, mikÀ tarkoittaa ettÀ paistemenetelmÀ on suurin piirtein yhtÀ hyvÀ kuin pyranometrimenetelmÀ arvioitaessa pidemmÀn aikavÀlin vaihteluita kuten esimerkiksi vuosi vuodelta tapahtuvaa vaihtelua. TÀssÀ työssÀ tuotetut pitkÀt UV-aikasarjat tuovat uutta tietoa UV-sÀteilyn ilmastollisesta kÀyttÀytymisestÀ ja siitÀ kuinka UV-sÀteily on vaihdellut menneisyydessÀ. Esimerkiksi auringon paistehavaintoihin perustuvat aikasarjat ulottuvat vuoteen 1926 Davosissa ja vuoteen 1950 SodankylÀssÀ. NÀin ollen ne muodostavat myös uuden vertailukohdan viimeaikaisille muutoksille, joissa otsonikadolla on ollut merkitystÀ (noin 1980 alkaen). Davosissa UV-sÀteily on vaihdellut tuntuvasti koko tarkastelujaksolla 1926-2003. Korkeita arvoja oli 1940-luvun keskivaiheilla, 1960-luvun alussa ja 1990-luvulla. LisÀksi huomattiin, ettÀ pilvisyyden vaihtelut hallitsivat ennen vuotta 1980 tapahtuneita vaihteluita UV-sÀteilyssÀ. Toisaalta sekÀ pilvisyys ettÀ otsonin vÀhentyminen vaikuttivat jakson 1979-1999 aikana todettuun kasvuun UV-sÀteilyssÀ (4,5 %/vuosikymmen). Myös SodankylÀssÀ ja NorrköpingissÀ UV-sÀteily on lisÀÀntynyt 1980-luvun alusta (3-4 %/vuosikymmen). NÀillÀ asemilla kasvun aiheutti ensisijaisesti pilvisyyden muutokset ja vÀhemmÀssÀ mÀÀrin otsonin vÀhentyminen. Jokioisissa ja BergenissÀ UV-sÀteilyn muutokset olivat pieniÀ

    Quantifying the amplified bias of PV system simulations due to uncertainties in solar radiation estimates

    Get PDF
    Solar radiation databases used for simulating PV systems are typically selected according to their annual bias in global horizontal irradiance (G(H)) because this bias propagates proportionally to plane-of-array irradiance (G(POA)) and module power (P-DC). However, the bias may get amplified through the simulations due to the impact of deviations in estimated irradiance on parts of the modeling chain depending on irradiance. This study quantifies these effects at 39 European locations by comparing simulations using satellite-based (SARAH) and reanalysis (COSMO-REA6 and ERAS) databases against simulations using station measurements. SARAH showed a stable bias through the simulations producing the best Pp c predictions in Central and South Europe, whereas the bias of reanalyses got substantially amplified because their deviations vary with atmospheric transmissivity due to an incorrect prediction of clouds. However, SARAH worsened at the northern locations covered by the product (55-65 degrees N) underestimating both G(POA) and P-DC. On the contrary, ERAS not only covers latitudes above 65 degrees but it also obtained the least biased P-DC estimations between 55 and 65 degrees N, which supports its use as a complement of satellite-based databases in high latitudes. The most significant amplifications occurred through the transposition model ranging from +/- 1% up to +/- 6%. Their magnitude increased linearly with the inclination angle, and they are related to the incorrect estimation of beam and diffuse irradiance. The bias increased around + 1% in the PV module model because the PV conversion efficiency depends on irradiance directly, and indirectly via module temperature. The amplification of the bias was similar and occasionally greater than the bias in annual G(H), so databases with the smallest bias in G(H) may not always provide the least biased PV simulations.Peer reviewe

    Epidermal UV-A absorbance and whole-leaf flavonoid composition in pea respond more to solar blue light than to solar UV radiation

    Get PDF
    Plants synthesize phenolic compounds in response to certain environmental signals or stresses. One large group of phenolics, flavonoids, is considered particularly responsive to ultraviolet (UV) radiation. However, here we demonstrate that solar blue light stimulates flavonoid biosynthesis in the absence of UV-A and UV-B radiation. We grew pea plants (Pisum sativum cv. Meteor) outdoors, in Finland during the summer, under five types of filters differing in their spectral transmittance. These filters were used to (1) attenuate UV-B; (2) attenuate UV-B and UV-A We studied the relative importance of the UV and blue wavebands of sunlight for the phenolics in leaves of pea (Pisum sativum cv. Meteor) plants grown outdoors. We report a large reduction in epidermal flavonoids and a change in the flavonoid composition in leaf extracts when solar blue light was attenuated. Under the conditions of our experiment, these effects of blue light attenuation were much larger than those caused by attenuation of UV radiation.Peer reviewe

    Helsinki aerosol studies

    Get PDF
    PresentaciĂłn realizada en: 2nd ACCORD ASW celebrado del 4 al 8 de abril de 2022 en Ljubljana, Eslovenia

    Quality control of global solar radiation data with satellite-based products

    Get PDF
    Several quality control (QC) procedures are available to detect errors in ground records of solar radiation, mainly range tests, model comparison and graphical analysis, but most of them are ineffective in detecting common problems that generate errors within the physical and statistical acceptance ranges. Herein, we present a novel QC method to detect small deviations from the real irradiance profile. The proposed method compares ground records with estimates from three independent radiation products, mainly satellite-based datasets, and flags periods of consecutive days where the daily deviation of the three products differs from the historical values for that time of the year and region. The confidence intervals of historical values are obtained using robust statistics and errors are subsequently detected with a window function that goes along the whole time series. The method is supplemented with a graphical analysis tool to ease the detection of false alarms. The proposed QC was validated in a dataset of 313 ground stations. Faulty records were detected in 31 stations, even though the dataset had passed the Baseline Surface Radiation Network (BSRN) range tests. The graphical analysis tool facilitated the identification of the most likely causes of these errors, which were classified into operational errors (snow over the sensor, soiling, shading, time shifts, large errors) and equipment errors (miscalibration and sensor replacements), and it also eased the detection of false alarms (16 stations). These results prove that our QC method can overcome the limitations of existing QC tests by detecting common errors that create small deviations in the records and by providing a graphical analysis tool that facilitates and accelerates the inspection of flagged values.Peer reviewe

    Nykyisen ja tulevan ilmaston sÀÀtietoja rakennusfysikaalisia laskelmia ja energialaskennan testivuotta 2020 varten

    Get PDF
    Ilmaston lĂ€mmetessĂ€ ja vesisateiden talvisinkin yleistyessĂ€ myös rakennetussa ympĂ€ristössĂ€ tulisi varautua muuttuviin sÀÀolosuhteisiin. TĂ€ssĂ€ tutkimushankkeessa on luotu sÀÀhavaintoihin pohjautuvia tiedostoja, joita voidaan kĂ€yttÀÀ laskelmien pohjana arvioitaessa rakennusten energiantarvetta ja rakennusfysikaalista toimintaa nykyisessĂ€ ja tulevassa ilmastossa. Aluksi tarkasteltiin neljĂ€n paikkakunnan (Vantaa, Jokioinen, JyvĂ€skylĂ€ ja SodankylĂ€) sÀÀhavaintoja 30 vuoden pituiselta aikajaksolta 1989–2018; paikat edustavat kutakin neljÀÀ energialaskennan lĂ€mpötilavyöhykettĂ€. Havaintojen pohjalta muodostettiin lĂ€mpötilan, ilman suhteellisen kosteuden, auringon kokonaissĂ€teilyn, hajasĂ€teilyn, sĂ€dettĂ€ vastaan kohtisuoralle pinnalle saapuvan suoran sĂ€teilyn, tuulen suunnan ja nopeuden sekĂ€ sademÀÀrĂ€n tunnittaiset aikasarjat vuosille 1989–2018. Ilmastomallien ennustamien muutosten perusteella nĂ€mĂ€ aikasarjat muunnettiin kuvaamaan tulevaisuuden olosuhteita vuosina 2015–2044 (lĂ€hitulevaisuutta kuvaava vuoden 2030 ilmasto), 2035–2064 (vuosisadan puolivĂ€liĂ€ kuvaava v. 2050 ilmasto) ja 2065–2094 (vuosisadan loppupuolen eli v. 2080 ilmasto). Kaikki nĂ€mĂ€ tulevaisuuden ilmaston sÀÀaikasarjat muodostettiin erikseen kolmelle kasvihuonekaasuskenaariolle, joista RCP2.6 vastaa vĂ€hĂ€istĂ€, RCP4.5 kohtalaista ja RCP8.5 hyvin voimakasta ilmastonmuutosta. Jakson 1989–2018 ilmastoa kuvaavista aikasarjoista haettiin kutakin 12 kuukautta kohti se vuosi, jona kyseisen kuukauden sÀÀolot olivat vastanneet mahdollisimman hyvin keskimÀÀrĂ€isiĂ€ ilmasto-oloja. YhdistĂ€mĂ€llĂ€ nĂ€mĂ€ 12 kuukautta saatiin muodostettua kullekin energialaskennan vyöhykkeelle uusi rakennusten energialaskennan testi-vuosi TRY2020. Testivuotta kuvaavassa tiedostossa ovat mukana lĂ€mpötila, kosteus, auringon sĂ€teily (kokonaissĂ€teily, suora sĂ€teily kohtisuoralle pinnalle ja hajasĂ€teily) sekĂ€ tuulen suunta ja nopeus, mutta ei sademÀÀrÀÀ. Samoja valittuja kuukausia kĂ€yttĂ€mĂ€llĂ€ muodostettiin vastaavat energialaskennan testivuodet myös kolmelle tulevaisuuden jaksolle, erikseen kullekin kasvihuonekaasuskenaariolle. Aiemmin laadittuun testivuoteen TRY2012 verrattuna uusi testivuosi TRY2020 koostuu lĂ€mpötilavyöhykkeestĂ€ riippuen 7–11 uudesta tyyppikuukaudesta, kun taas loput kuukaudet ovat samoja kuin aikaisemmin. Vantaalla, JyvĂ€skylĂ€ssĂ€ ja SodankylĂ€ssĂ€, joita tarkasteltiin molempia testivuosia muodostettaessa, TRY2020 on koko vuotta ajatellen 0.17–0.36°C lĂ€mpimĂ€mpi kuin TRY2012, vaikka joinakin yksittĂ€isinĂ€ kuukausina se onkin viileĂ€mpi. Vuotuisen kokonaissĂ€teilyn erot uuden ja aiemman testivuoden vĂ€lillĂ€ ovat pieniĂ€, mutta joinakin yksittĂ€isinĂ€ kuukausina sĂ€teilymÀÀrĂ€t kyllĂ€ poikkeavat melko selvĂ€sti. Rakennusten energialaskennan testivuosien ohella koottiin rakennusfysikaalisten tarkastelujen vertailuja varten todellisen menneen vuoden (Jokioinen v. 2015) tunnittain mitatut sÀÀtiedot; nĂ€itĂ€ muokattiin myös kuvaamaan tulevaisuuden ajanjaksoja. LisĂ€ksi hankkeessa tuotettuja 30-vuotisia nykyisen ja tulevaisuuden ilmaston sÀÀtietoja voidaan kĂ€yttÀÀ esimerkiksi aiemmin valittujen rakennusfysikaalisten testivuosien pĂ€ivittĂ€miseen. Raportissa tarkasteltiin myös lĂ€mmitysjĂ€rjestelmien mitoitukseen kĂ€ytettĂ€viĂ€ kylmiĂ€ lĂ€mpötiloja sekĂ€ sitĂ€, miten ilmastonmuutos vaikuttaa nykyÀÀn harvoin esiintyvien lĂ€mpötilojen, sademÀÀrien ja tuulen nopeuksien yleisyyteen tulevaisuudessa.As the Finnish climate becomes warmer and liquid precipitation events will be increasingly frequent even in winter, it is necessary to be prepared for changing weather conditions in the built-up environment. In this study, we have elaborated weather data files that can be utilized in assessing energy demand and physical functioning in buildings in the current and future climate. Weather datasets were compiled for four measurement sites in Finland, SodankylĂ€, JyvĂ€skylĂ€, Jokioinen and Vantaa, each of them representing different thermal zones for building energy demand. The datasets, comprising years 1989–2018, contained the following variables at hourly resolution: temperature, relative humidity, wind speed and direction, total, diffuse and direct normal solar radiation and precipitation. The tridecadal datasets were transformed to represent future climate by modifying the hourly values of the weather variables in accordance with climate model projections. Three future periods were considered, 2015–2044 representing the immediate future, 2035–2064 mid-century and 2065–2094 the late century climate. Henceforth, the periods will be referred to according to the mid-point year, i.e., 2030, 2050 and 2080, respectively. All the time series representing future climate were compiled for three representative concentration pathways, RCP2.6 representing small, RCP4.5 medium and RCP8.5 very large greenhouse-gas emissions. Next, the 30-year datasets were used to find for each of the twelve calendar months a "standard" month during which weather conditions have been as close as possible to typical long-term statistical distributions. These twelve months originating from different years were merged to create the new test reference year of building energy demand (TRY2020) for all four thermal zones. In the test reference year datasets, all the above-mentioned weather variables were included apart from precipitation. The months selected were likewise used to extract test reference year data from the data files representing future climate, separately for all three future periods and the three representative concentration pathways. Compared to the previously-compiled test reference year TRY2012, the new reference year TRY2020 consists of 7–11 fresh months, depending on the thermal zone, the remaining months being the same as in TRY2012. Regarding the three measurement sites for which both references years are available, the annual mean temperature in TRY2020 is 0.17–0.36°C higher than in TRY2012, even though some individual months are cooler. The total annual solar radiation sum in the two test reference years is nearly identical, while some single months exhibit quite remarkable differences. In addition to the test reference year for building energy demand, hourly measurements during a historical year (Jokioinen 2015) were collected for comparison purposes in building physical calculations. This comparison year data was also transformed to represent future climates. Moreover, the 30-year datasets elaborated in the project can be used to update previously-selected building physical test years for the Finnish climate. The report likewise examines very cold temperatures relevant for the design of heating systems. As well, we explored how the projected climate change affects the future occurrence of temperature, precipitation and wind speed extremes.DĂ„ det finska klimatet blir varmare och nederbörd i form av regn allt vanligare ocksĂ„ vintertid, mĂ„ste den bebyggda miljön vara beredd pĂ„ förĂ€ndringar i vĂ€derförhĂ„llanden. I detta arbete har vi framstĂ€llt vĂ€derdata, som kan anvĂ€ndas för att bedöma behovet av vĂ€rme- och kylenergi samt byggnadsfysikalisk funktion i det nuvarande och framtida klimatet. VĂ€derdata samlades frĂ„n fyra orter i Finland, SodankylĂ€, JyvĂ€skylĂ€, Jockis och Vanda, som representerar de olika temperaturzonerna för energiberĂ€kning i byggnader. Timvis vĂ€derdata för Ă„ren 1989–2018 sammanstĂ€lldes för följande vĂ€derparametrar: temperatur, relativ luftfuktighet, vindhastighet och riktning, global-, diffus- och direkt solstrĂ„lning samt nederbörd. De hĂ€r trettioĂ„riga tidsserierna omrĂ€knades för att representera det framtida klimatet i enlighet med simuleringar gjorda med klimatmodeller. Tre framtida perioder betraktades: 2015–2044 beskriver den nĂ€ra framtiden, 2035–2064 mitten av seklet och 2065–2094 klimatet i slutet av seklet. Perioderna har namngetts enligt Ă„ret i mitten av perioden, dvs. 2030, 2050 och 2080. Alla de tidsserier som representerar det framtida klimatet sammanstĂ€lldes för tre vĂ€xthusgasscenarier: RCP2.6 motsvarar smĂ„, RCP4.5 medelmĂ„ttliga och RCP8.5 mycket stora utslĂ€pp. DĂ€refter anvĂ€ndes de 30-Ă„riga tidsserierna för att konstruera det nya testreferensĂ„ret, eller typĂ„ret, för efterfrĂ„gan av byggnadsenergi (TRY2020) för alla fyra termiska zoner. TypĂ„ret innehĂ„ller hela kalendermĂ„nader, som valts ut sĂ„ att de rĂ„dande vĂ€derleksförhĂ„llandena under mĂ„naden motsvarar typiska lĂ„ngtida statistiska fördelningarna. I datafilerna för TRY2020 inkluderades alla ovannĂ€mnda vĂ€derparametrar förutom nederbörd. De valda mĂ„naderna anvĂ€ndes ocksĂ„ för att sammanstĂ€lla typĂ„rsdata, som beskriver det framtida klimatet. Detta gjordes separat för alla tre framtida perioder och de tre vĂ€xthusgasscenarierna. JĂ€mfört med det tidigare typĂ„ret TRY2012 bestĂ„r det nya typĂ„ret TRY2020 av 7–11 nya typmĂ„nader, beroende pĂ„ den termiska zonen, medan resten av mĂ„naderna Ă€r desamma som i TRY2012. DĂ„ man granskar de tre orterna, för vilka bĂ„da typĂ„r finns tillgĂ€ngliga, Ă€r den Ă„rliga medeltemperaturen i TRY2020 0,17–0,36°C högre Ă€n i TRY2012, Ă€ven om nĂ„gra enstaka mĂ„nader Ă€r svalare. Den Ă„rliga summan av global solstrĂ„lning Ă€r nĂ€stan identisk i de tvĂ„ typĂ„ren, men under nĂ„gra enskilda mĂ„nader skiljer strĂ„lningsmĂ€ngden sig tydligt. Förutom typĂ„ren för energiberĂ€kningar, sammanstĂ€lldes vĂ€derdata för ett historiskt Ă„r (Jockis 2015) som kan anvĂ€ndas för exempelvis byggnadsfysiska studier. Även detta jĂ€mförelseĂ„r omrĂ€knades till att representera framtida förhĂ„llanden. Dessutom kan de 30-Ă„riga tidsserier, som utarbetats i projektet, anvĂ€ndas för att uppdatera tidigare byggnadsfysiska typĂ„r. Rapporten undersöker ocksĂ„ förekomsten av mycket lĂ„ga temperaturer, som Ă€r relevanta för dimensioneringen av vĂ€rmesystem. Dessutom granskade vi, hur den förvĂ€ntade klimatförĂ€ndringen inverkar pĂ„ extrema temperaturer, nederbördsmĂ€ngder och vindhastigheter i framtiden

    The photoreceptor UVR8 mediates the perception of both UV-B and UV-A wavelengths up to 350 nm of sunlight with responsivity moderated by cryptochromes

    Get PDF
    ABSTRACT The photoreceptors UV RESISTANCE LOCUS 8 (UVR8) and CRYPTOCHROMES 1 and 2 (CRYs) play major roles in the perception of UV-B (280?315?nm) and UV-A/blue radiation (315?500?nm), respectively. However, it is poorly understood how they function in sunlight. The roles of UVR8 and CRYs were assessed in a factorial experiment with Arabidopsis thaliana wild-type and photoreceptor mutants exposed to sunlight for 6?h or 12?h under five types of filters with cut-offs in UV and blue-light regions. Transcriptome-wide responses triggered by UV-B and UV-A wavelengths shorter than 350?nm (UV-Asw) required UVR8 whereas those induced by blue and UV-A wavelengths longer than 350?nm (UV-Alw) required CRYs. UVR8 modulated gene expression in response to blue light while lack of CRYs drastically enhanced gene expression in response to UV-B and UV-Asw. These results agree with our estimates of photons absorbed by these photoreceptors in sunlight and with in vitro monomerization of UVR8 by wavelengths up to 335?nm. Motif enrichment analysis predicted complex signaling downstream of UVR8 and CRYs. Our results highlight that it is important to use UV waveband definitions specific to plants' photomorphogenesis as is routinely done in the visible region. This article is protected by copyright. All rights reserved.Peer reviewe
    • 

    corecore