133 research outputs found

    Method for constructing an AOD-related atmospheric correction time series for the CLARA-A2 SAL data record

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    In the Satellite Application Facility on Climate Monitoring (CM SAF) project, financially supported by EUMETSAT, the 34-year long (1982-2015) broadband albedo time series CLARA-A2 SAL (the Surface ALbedo from the CM SAF cLoud, Albedo and RAdiation data record, second version) was produced from Advanced Very High Resolution Radiometer (AVHRR) measurements. CLARA-A2 SAL data record uses a Simplified Method for Atmospheric Correction algorithm SMAC for correcting for atmospheric effects. Aerosol optical depth (AOD) is the main input of the algorithm. Because there were no global AOD time series for the whole needed time period (1982-2015), the AOD-related time series were constructed, and the method for calculating it is described in this report

    A method for random uncertainties validation and probing the natural variability with application to TROPOMI on board Sentinel-5P total ozone measurements

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    In this paper, we discuss the method for validation of random uncertainties in the remote sensing measurements based on evaluation of the structure function, i.e., root-mean-square differences as a function of increasing spatiotemporal separation of the measurements. The limit at the zero mismatch provides the experimental estimate of random noise in the data. At the same time, this method allows probing of the natural variability of the measured parameter. As an illustration, we applied this method to the clear-sky total ozone measurements by the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5P satellite. We found that the random uncertainties reported by the TROPOMI inversion algorithm, which are in the range 1–2 DU, agree well with the experimental uncertainty estimates by the structure function. Our analysis of the structure function has shown the expected results on total ozone variability: it is significantly smaller in the tropics compared to mid-latitudes. At mid-latitudes, ozone variability is much larger in winter than in summer. The ozone structure function is anisotropic (being larger in the latitudinal direction) at horizontal scales larger than 10–20 km. The structure function rapidly grows with the separation distance. At mid-latitudes in winter, the ozone values can differ by 5 % at separations 300–500 km. The method discussed is a powerful tool in experimental estimates of the random noise in data and studies of natural variability, and it can be used in various applications.Peer reviewe

    Satelliittihavaintojen hyödyntäminen ilmanlaadun seurannassa

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    Tässä selvityksessä kartoitetaan ensimmäistä kertaa satelliittimittausten hyödyntämistä ilmanlaadun seurannassa Suomessa. Satelliittien ehdottomana vahvuutena on ilmanlaatumuuttujien alueellisen jakauman kuvaaminen sekä ilmansaasteiden kulkeutumisen seuranta, joita tässä työssä on demonstroitu käyttämällä alailmakehän typpidioksidi (NO2}-havaintoja TROPOspheric Monitoring Instrument (TROPOMI) ja Ozone Monitoring Instrument (OMI) satelliitti-instrumenteista. TROPOMI laukaistiin EU:n Copernicus-ohjelman rahoittamassa Sentinel-5P satelliitissa vuonna 2017, ja se on tällä hetkellä paikalliselta erotuskyvyltään tarkin ilmanlaadun kannalta oleellisia kaasuja havainnoiva satelliittimittalaite. Suomalais-hollantilainen OMI-instrumentti NASAn Aura-satelliitissa on puolestaan tuottanut maailmanlaajuisia havaintoja jo lähes 15 vuoden ajan. Tämän työn tulokset näyttävät, että satelliittien avulla voidaan tarkastella typpidioksidin alueellista jakaumaa Suomessa sekä lähialueilla aina kaupunkitasolle asti. Esimerkiksi pääkaupunkiseudun keskimääräisissä pitoisuuksissa voidaan erottaa alueellisia vaihteluita ja nähdä selvä ero viikonpäivien ja viikonloppujen välillä. OMI-instrumentin havainnoista puolestaan nähdään, että alailmakehän NO2-pitoisuudet ovat keskimäärin laskeneet koko maassa vuodesta 2005 vuoteen 2018. Keskeisimpiä kysymyksiä satelliittidatan hyödyntämisessä ilmanlaadun seurannassa on se, kuinka hyvin satelliittihavainnot vastaavat in situ -mittauksista nähtyjä vaihteluita. Vertailu TROPOMI-havaintojen ja pintamittausten välillä näyttää, että vaikka kaupungin sisällä yksittäisten asemien kohdalla yhteensopivuus voi vaihdella asemittain, korrelaatio on hyvä kun vastaavuutta tarkastellaan yhdistämällä kunkin kaupungin keskustan pintahavainnot. Tulos on samansuuntainen sekä Suomessa että myös muualla Euroopassa

    The Ozone Monitoring Instrument: Overview of 14 years in space

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    This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain

    Vertical Distribution of Arctic Methane in 2009–2018 Using Ground-Based Remote Sensing

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    We analyzed the vertical distribution of atmospheric methane (CH4) retrieved from measurements by ground-based Fourier Transform Spectrometer (FTS) instrument in Sodankyla, Northern Finland. The retrieved dataset covers 2009-2018. We used a dimension reduction retrieval method to extract the profile information, since each measurement contains around three pieces of information about the profile shape between 0 and 40 km. We compared the retrieved profiles against Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) satellite measurements and AirCore balloon-borne profile measurements. Additional comparison at the lowest tropospheric layer was done against in-situ measurements from a 50-m-high mast. In general, the ground-based FTS and ACE-FTS profiles agreed within 10% below 20 km and within 30% in the stratosphere between 20 and 40 km. Our method was able to accurately capture reduced methane concentrations inside the polar vortex in the Arctic stratosphere. The method produced similar trend characteristics as the reference instruments even when a static prior profile was used. Finally, we analyzed the time series of the CH4 profile datasets and estimated the trend using the dynamic linear model (DLM)
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