58 research outputs found

    Valtion velan kasaantumisen yhteys kriiseihin

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    TiivistelmÀ. Tutkielmassa tarkastellaan valtion velan kasaantumisen yhteyttÀ kriiseihin. Kiinnostuksen kohteena on taloudellisesti kehittyneet, mutta samalla myös hyvin velkaantuneet talousalueet, kuten Yhdysvallat, euroalue ja Japani. Maailmanpankki ja IMF ovat osoittaneet huolestuneisuutta velan kasaantumisesta jo pitkÀÀn, eikÀ sen kasvu nÀytÀ pysÀhtyvÀn. TÀstÀ johtuen velan kasaantumisen yhteys talouskriiseihin on kiinnostava ja merkittÀvÀ tutkimusalue. Työn tavoitteena on selvittÀÀ, löytyykö taloustieteen teorioista tai aiemmista tutkimuksista syitÀ sille, etteikö velan kasaantuminen voisi koitua ongelmalliseksi myös taloudellisesti kehittyneissÀ valtioissa. Tutkielman menetelmÀnÀ on kirjallisuuskatsaus, jossa tutustutaan taloustieteen eri koulukuntiin ja siihen, miten ne kÀsittelevÀt taloussuhdanteita lievittÀvÀÀ politiikkaa. LisÀksi tutustutaan eri talouskriiseihin ja tarkastellaan velan kasaantumien yhteyttÀ niihin. Tutkimustuloksena löydetÀÀn velan kasaantumisella olevan selkeÀ yhteys kaikkiin neljÀÀn talouskriisimuotoihin ja nÀiden yhdistelmiin. TÀrkeimpÀnÀ tuloksena voidaan pitÀÀ sitÀ, ettÀ velan kasaantuminen voi johtaa vakaviin talouskriiseihin myös kehittyneiden maiden osalta. EikÀ jÀrkevÀÀ syytÀ löydy sille, miksei tÀtÀ yhteyttÀ jollakin maalla olisi. Tutkimustuloksia voidaan hyödyntÀÀ, kun suunnitellaan valtioiden talousbudjetteja ja finanssipoliittisten instrumenttien kÀyttöÀ. Esimerkiksi raskaasti velkaantuneen valtion tulisi harkita tarkkaan velan lisÀyksestÀ, sekÀ huomioida siitÀ aiheutuvia pitkÀn aikavÀlin vaikutuksia. Velan kasaantumista tulisi myös ennaltaehkÀistÀ rakenneuudistuksin ja keinoja velan koon pienentÀmiseen tulisi pohtia valtiokohtaisesti. Tuloksia on myös tÀrkeÀ huomioida rahapolitiikassa, kun vaikutetaan korkomarkkinoihin ja sitÀ kautta velan kustannuksiin

    Evaluating the Assumptions of Surface Reflectance and Aerosol Type Selection Within the MODIS Aerosol Retrieval Over Land: The Problem of Dust Type Selection

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    Aerosol Optical Depth (AOD) and Angstrom exponent (AE) values derived with the MODIS retrieval algorithm over land (Collection 5) are compared with ground based sun photometer measurements at eleven sites spanning the globe. Although, in general, total AOD compares well at these sites (R2 values generally over 0.8), there are cases (from 2 to 67% of the measurements depending on the site) where MODIS clearly retrieves the wrong spectral dependence, and hence, an unrealistic AE value. Some of these poor AE retrievals are due to the aerosol signal being too small (total AOD<0.3) but in other cases the AOD should have been high enough to derive accurate AE. However, in these cases, MODIS indicates AE values close to 0.6 and zero fine model weighting (FMW), i.e. dust model provides the best fitting to the MODIS observed reflectance. Yet, according to evidence from the collocated sun photometer measurements and back-trajectory analyses, there should be no dust present. This indicates that the assumptions about aerosol model and surface properties made by the MODIS algorithm may have been incorrect. Here we focus on problems related to parameterization of the land-surface optical properties in the algorithm, in particular the relationship between the surface reflectance at 660 and 2130 nm

    Profiling water vapor mixing ratios in Finland by means of a Raman lidar, a satellite and a model

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    We present tropospheric water vapor profiles measured with a Raman lidar during three field campaigns held in Finland. Co-located radio soundings are available throughout the period for the calibration of the lidar signals. We investigate the possibility of calibrating the lidar water vapor profiles in the absence of co-existing on-site soundings using water vapor profiles from the combined Advanced InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU) satellite product; the Aire Limitee Adaptation dynamique Developpement INternational and High Resolution Limited Area Model (ALADIN/HIRLAM) numerical weather prediction (NWP) system, and the nearest radio sounding station located 100 km away from the lidar site (only for the permanent location of the lidar). The uncertainties of the calibration factor derived from the soundings, the satellite and the model data are <2.8, 7.4 and 3.9 %, respectively. We also include water vapor mixing ratio intercomparisons between the radio soundings and the various instruments/model for the period of the campaigns. A good agreement is observed for all comparisons with relative errors that do not exceed 50% up to 8 km altitude in most cases. A 4-year seasonal analysis of vertical water vapor is also presented for the Kuopio site in Finland. During winter months, the air in Kuopio is dry (1.15 +/- 0.40 g kg(-1)); during summer it is wet (5.54 +/- 1.02 g kg(-1)); and at other times, the air is in an intermediate state. These are averaged values over the lowest 2 km in the atmosphere. Above that height a quick decrease in water vapor mixing ratios is observed, except during summer months where favorable atmospheric conditions enable higher mixing ratio values at higher altitudes. Lastly, the seasonal change in disagreement between the lidar and the model has been studied. The analysis showed that, on average, the model underestimates water vapor mixing ratios at high altitudes during spring and summer.Peer reviewe

    Effect of the summer monsoon on aerosols at two measurement stations in Northern India – Part 2: Physical and optical properties

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    Aerosol physical and optical properties were measured at two locations in northern India. The first measurement station was a background site in Mukteshwar, about 350 km northeast of New Delhi, in the foothills of the Indian Himalayas, with data from 2006 to 2009. The second measurement site was located in Gual Pahari, about 25 km south of New Delhi, with data from 2008 to 2009. At both stations, the average aerosol concentrations during the monsoon were decreased by 40–75 % compared to the pre-monsoon average concentrations. The decrease varied with the total local rainfall. In Mukteshwar, the monsoon season removed particles from all size classes, due to a combination of rain scavenging and activation to cloud and mountain fog droplets. The scavenging by rain is least effective for the size range of the accumulation mode particles. In Gual Pahari, this was the only major wet removal mechanism and, as a result, the accumulation mode particles were less effectively removed. Aerosol concentrations during the early monsoon were found to be affected by mineral dust which in Gual Pahari was observed as an increased particle volume at a diameter around 3–4 ÎŒm. The single scattering albedo varied from 0.73 to 0.93 during the monsoon season, being slightly lower in Gual Pahari than in Mukteshwar. This is due to the fact that Gual Pahari resided closer to high anthropogenic black carbon emissions. As the absorbing particles are typically in the accumulation mode, they were not effectively removed by rain scavenging. The aerosol columnar properties, which were measured in Gual Pahari, showed a somewhat different seasonal behaviour compared to the surface measurements, with the aerosol optical depth increasing to an annual maximum in the early monsoon season

    Effect of water vapor on the determination of aerosol direct radiative effect based on the AERONET fluxes

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    The aerosol direct radiative effect (ADRE) is defined as the change in the solar radiation flux, F, due to aerosol scattering and absorption. The difficulty in determining ADRE stems mainly from the need to estimate F without aerosols, F0, with either radiative transfer modeling and knowledge of the atmospheric state, or regression analysis of radiation data down to zero aerosol optical depth (AOD), if only F and AOD are observed. This paper examines the regression analysis method by using modeled surface data products provided by the Aerosol Robotic Network (AERONET). We extrapolated F0 by two functions: a straight linear line and an exponential nonlinear decay. The exponential decay regression is expected to give a better estimation of ADRE with a few percent larger extrapolated F0 than the linear regression. We found that, contrary to the expectation, in most cases the linear regression gives better results than the nonlinear. In such cases the extrapolated F0 represents an unrealistically low water vapor column (WVC), resulting in underestimation of attenuation caused by the water vapor, and hence too large F0 and overestimation of the magnitude of ADRE. The nonlinear ADRE is generally 40–50% larger in magnitude than the linear ADRE due to the extrapolated F0 difference. Since for a majority of locations, AOD and WVC have a positive correlation, the extrapolated F0 with the nonlinear regression fit represents an unrealistically low WVC, and hence too large F0. The systematic underestimation of F0 with the linear regression is compensated by the positive correlation between AOD and water vapor, providing the better result

    One year of Raman lidar observations of free-tropospheric aerosol layers over South Africa

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    Raman lidar data obtained over a 1 year period has been analysed in relation to aerosol layers in the free troposphere over the Highveld in South Africa. In total, 375 layers were observed above the boundary layer during the period 30 January 2010 to 31 January 2011. The seasonal behaviour of aerosol layer geometrical characteristics, as well as intensive and extensive optical properties were studied. The highest centre heights of free-tropospheric layers were observed during the South African spring (2520 ± 970 m a.g.l., also elsewhere). The geometrical layer depth was found to be maximum during spring, while it did not show any significant difference for the rest of the seasons. The variability of the analysed intensive and extensive optical properties was high during all seasons. Layers were observed at a mean centre height of 2100 ± 1000 m with an average lidar ratio of 67 ± 25 sr (mean value with 1 standard deviation) at 355 nm and a mean extinction-related Ångström exponent of 1.9 ± 0.8 between 355 and 532 nm during the period under study. Except for the intensive biomass burning period from August to October, the lidar ratios and Ångström exponents are within the range of previous observations for urban/industrial aerosols. During Southern Hemispheric spring, the biomass burning activity is clearly reflected in the optical properties of the observed free-tropospheric layers. Specifically, lidar ratios at 355 nm were 89 ± 21, 57 ± 20, 59 ± 22 and 65 ± 23 sr during spring (September–November), summer (December–February), autumn (March–May) and winter (June–August), respectively. The extinction-related Ångström exponents between 355 and 532 nm measured during spring, summer, autumn and winter were 1.8 ± 0.6, 2.4 ± 0.9, 1.8 ± 0.9 and 1.8 ± 0.6, respectively. The mean columnar aerosol optical depth (AOD) obtained from lidar measurements was found to be 0.46 ± 0.35 at 355 nm and 0.25 ± 0.2 at 532 nm. The contribution of free-tropospheric aerosols on the AOD had a wide range of values with a mean contribution of 46%

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    Technical Note: One year of Raman-lidar measurements in Gual Pahari EUCAARI site close to New Delhi in India - Seasonal characteristics of the aerosol vertical structure

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    © Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 LicenseOne year of multi-wavelength (3 backscatter + 2 extinction + 1 depolarization) Raman lidar measurements at Gual Pahari, close to New Delhi, were analysed. The data was split into four seasons: spring (March-May), summer (June-August), autumn (September-November) and winter (December-February). The vertical profiles of backscatter, extinction, and lidar ratio and their variability during each season are presented. The measurements revealed that, on average, the aerosol layer was at its highest in spring (5.5 km). In summer, the vertically averaged (between 1-3 km) backscatter and extinction coefficients had the highest averages (3.3 Mm(-1) sr(-1) and 142 Mm(-1) at 532 nm, respectively). Aerosol concentrations were slightly higher in summer compared to other seasons, and particles were larger in size. The autumn showed the highest lidar ratio and high extinction-related Angstrom exponents (AE(ext)), indicating the presence of smaller probably absorbing particles. The winter had the lowest backscatter and extinction coefficients, but AE(ext) was the highest, suggesting still a large amount of small particles.Peer reviewe
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