Supporting operational observations of snow water equivalent with remote sensing data

Lumen vesiarvoa kertoo, kuinka paljon vettä muodostuisi, jos lumikerros sulaisi välittömästi ja kokonaan nykyisellä paikallaan. Tietoa lumen vesiarvosta tarvitaan muun muassa tulvien enna-koimiseen, vesistöjen pintojen säännöstelyyn, maa- ja metsätalouden suunnitteluun sekä ympä-ristö- ja ilmastotutkimuksen tarpeisiin. Lumen vesiarvoa mitataan perinteisesti maastohavain-noilla tai interpoloimalla sääasemahavaintoja, mutta havaintoverkot ovat harvoja ja mittausker-tojen välit pitkiä. Tietoa lumen vesiarvosta voidaan saada myös avaruudesta käsin tehtävillä mikroaaltohavainnoilla. Satelliitti-instrumenteilla on mahdollista saada havaintoja päivittäin ja kattaa koko maapallo muutamassa päivässä. Radiometrihavainnot yksinään ovat melko epätarkkoja, koska kaikkea havaintojen oikeaan tulkitsemiseen tarvittavaa tietoa on harvoin saatavilla. Estimaattien tarkkuuden lisäämiseksi radiometrihavainnot voidaan yhdistää sääasemahavain-noista interpoloitavaan taustatietoon lumen vesiarvon spatiaalisesta jakautumisesta. Tässä työssä on tutkittu radiometrihavaintojen soveltuvuutta Suomen ympäristökeskuksen operatiivisen seu-rantatyön tarpeisiin. Data-assimilaatioon ja HUT lumen säteilymalliin perustuvia estimaatteja lumen vesiarvosta verrattiin lumilinjoilta tehtyihin maastohavaintoihin sekä näistä laskettuihin lumen aluevesiarvoihin. Työssä selvitettiin virheen suuruus sekä spatiaalinen ja ajallinen jakau-tuminen vuosina 2011–2013. Työssä on myös selvitetty eroihin vaikuttavat tärkeimmät tekijät sekä annettu ideoita, miten eri tavalla tuotetut estimaatit lumen vesiarvosta saataisiin lähemmäs toisiaan.Snow water equivalent (SWE) is used to measure how much water would form should whole of a snow pack melt instantly at its current location. Information about snow water equivalent is needed in many applications e.g. flood forecasting, control-ling water level of power plant reservoirs, planning for forestry and crop irrigation and as input and control variable for many environment research purposes including climate change research. Traditionally snow water equivalent has been measured with in-situ samples or by interpolating weather station observations. Observation networks however tend to be quite sparse and time intervals between sampling can be long. Another option to provide information on snow water equivalent is by using space-borne microwave observations. Satellite instruments make it possible to have observations each day, and thanks to large swath of the instruments, global coverage can be reached within few days. Standalone radiometer observations can be somewhat imprecise. Correct interpretation of the brightness temperatures observed by the radiometer requires accurate information on attributes of the snow pack itself, on vegetation cover and about composition of atmosphere over the observed area. Rarely are all this data available for the entire area observed by the instrument. To increase the reliability and the accuracy of snow water equivalent estimates, radiometer observations can be assimilated with background information about the spatial distribution of snow depth. This information can be derived from synoptic weather station network. In this thesis work the suitability of radiometer data for purposes of the Finnish environment institute’s operational observations of snow water equivalent is investigated. Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Special Sensor Microwave / Imager (SSM/I) data interpreted with Helsinki University of Technology (HUT) snow emission model and assimilated with snow depth data from Finnish Meteorological synoptic weather stations from years 2011 to 2013 are compared with in-situ observations from Finnish snowline network and with areal snow water equivalents calculated thereof. Error rates and spatial and temporal distribution of differences in snow water equivalent between products are investigated, and factors affecting the difference and suggestions how to narrow down the difference are given

The Strategic Challenge of Continuous Change in Multi-platform Media Organizations : A Strategy-as-practice Perspective

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Radiological and pathological assessment of response to neoadjuvant CDK4/6 inhibitor and endocrine treatments in a real-life setting : initial results

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Strategisches Handeln von Startups im Kontext der Mediatisierung

Junge Gründer und Start-ups müssen sich in einer schnell wandelnden und mediatisierten Wettbewerbsumwelt behaupten. Ihr Handeln wird geprägt von sozialen Netzwerkmedien wie Facebook, LinkedIn oder Instagram. Um auf diesen Medien-plattformen erfolgreich zu sein, müssen Markenführung und Markenkommunikation strategisch verankert sein. Der Aufsatz präsentiert daher eine qualitative Analyse empirischer Daten aus dem Kontext des Start-up-Incubator neudeli der Bauhaus-Universität Weimar und verdeutlicht, dass die Mediatisierung grundlegend in die strategische Entwicklung der Marke von jungen Gründern und Start-ups eingreift. Die Studie verdeutlicht das Verständnis strategischer Markenführung in mediatisierten Kontexten und zeigt, dass drei idealtypische Praktiken zur Markenführung und strategischen Entwicklung beitragen: 1) Bürokratische Medienarbeit, 2) Mediale Kreativarbeit, 3) Netzwerkarbeit durch Medien

GlobSnow v3.0 snow water equivalent (SWE)

ESA GlobSnow v3.0 snow water equivalent (SWE) dataset. Time series of 1980-2018 Northern Hemisphere terrestrial (non-mountainous) snow water equivalent data, containing monthly and monthly-bias-corrected SWE estimates. Dataset constructed by combining satellite-based passive microwave radiometer data (Nimbus-7 SMMR, DMSP 5D2 SSM/I and DMSP 5D3 SSMIS) with ground based synoptic snow depth observations using bayesian data assimilation, incorporating HUT Snow Emission model; by Pulliainen et al. 1999 (doi:10.1109/36.763302) and Lemmetyinen et al. 2011 (doi:10.1109/TGRS.2010.2041357). SWE retrieval according to Takala et al. 2011 (doi:10.1016/j.rse.2011.08.014) and Pulliainen 2006 (doi:10.1016/j.rse.2006.01.002). Dataset contains monthly SWE data and monthly bias-corrected SWE data. Bias-correction according to Pulliainen et al. 2020 (doi:10.1038/s41586-020-2258-0)

Radiotherapy-induced diffuse myocardial fibrosis in early-stage breast cancer patients - multimodality imaging study with six-year follow-up

BackgroundBreast radiotherapy (RT) induces diffuse myocardial changes, which may increase the incidence of heart failure with preserved ejection fraction. This study aimed to evaluate the early signs of diffuse fibrosis after RT and their evolution during a six-year follow-up.MethodsThirty patients with early-stage left-sided breast cancer were studied with echocardiography and electrocardiography (ECG) at baseline, after RT, and at three-year and six-year follow-up visits. Echocardiography analysis included an off-line analysis of integrated backscatter (IBS). ECG was analysed for fragmented QRS (fQRS). In addition, cardiac magnetic resonance (CMR) imaging was performed at the six-year control. The left ventricle 16-segment model was used in cardiac imaging, and respective local radiation doses were analysed.ResultsRegional myocardial reflectivity in inferoseptal segments increased by 2.02 (4.53) dB (p = 0.026) and the percentage of leads with fQRS increased from 9.2 to 16.4% (p = 0.002) during the follow-up. In CMR imaging, abnormal extracellular volume (ECV) and T1 mapping values were found with anteroseptal and apical localization in a median of 3.5 (1.00-5.75) and 3 (1.25-4.00) segments, respectively. A higher left ventricle radiation dose was associated with an increased likelihood of having changes simultaneously in CMR and echocardiography (OR 1.26, 95% Cl. 1.00-1.59, p = 0.047).ConclusionsAfter radiotherapy, progressive changes in markers of diffuse myocardial fibrosis were observed in a multimodal manner in ECG and echocardiography. Changes in echocardiography and abnormal values in CMR were localized in the septal and apical regions, and multiple changes were associated with higher radiation doses.Peer reviewe