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  • 101. Kokhanovsky, Alexander A.
    et al.
    Naud, Catherine M.
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Intercomparison of Ground-Based Radar and Satellite Cloud-Top Height Retrievals for Overcast Single-Layered Cloud Fields2009In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 47, no 7, p. 1901-1908Article in journal (Refereed)
    Abstract [en]

    The objective of this paper is to assess the accuracy of the Semi-Analytical CloUd Retrieval Algorithm (SACURA) that retrieves cloud-top heights (CTHs) using hyperspectral SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard Environmental Satellite measurements for overcast single-layer cloud fields. Intercomparisons with ground-based 35-GHz millimeter wave cloud radar CTHs were performed for 14 dates during 2003-2007 at the US. Atmospheric Radiation Measurement (ARM) program Southern Great Plains site (36.6 degrees N, 97.5 degrees W). In addition, for some of these dates, European Space Agency MEdium Resolution Imaging Spectrometer (MERIS) and the NASAL-TERRA Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure retrievals were also collected, transformed into CTHs using nearby ARM radiosonde profiles, and compared with the SACURA SCIAMACHY and radar retrievals. The accuracy of the SACURA-SCIAMACHY CTH retrievals is better than 0.34 km for low-level clouds and 2.22 km for high-level clouds with an underestimate in CTH on average for all clouds. The average bias in SCIAMACHY CTHs was about 0.07 km for low clouds and about 0.5 km for high-level clouds. Both MODIS and MERIS slightly overestimated the CTHs of low-level clouds by MO m, with an uncertainty better than 1 km. However, although MODIS accuracy for high-level clouds is close to SCIAMACHY, MERIS CTHs were significantly underestimated for these fairly optically thick cases.

  • 102. Korpela, Aarno
    et al.
    Dybbroe, Adam
    SMHI, Core Services.
    Thoss, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    Nowcasting SAF - Retrieving Cloud Top Temperature and Height in Semi-transparent and Fractional Cloudiness using AVHRR2001Report (Other academic)
    Abstract [en]

    Cloud top temperature and height estimates obtained from AVHRR infrared imagery require a correction for semi-transparency when cirrus layers are present. In this work we investigated the possibility of using the 11 μm and12 μm window channel brightness temperatures for the correction. We developed software which implements a method based on the work of Inoue (1985) and Derrien et al. (1988). In this method the cloud top temperature is derived for each small image segment by fitting a curve to . a twodimensional histogram of the segment, formed by using the brightness temperatureT ( 11 μm) and the brightness temperature diff erence T ( 11 μm) - T(l2μm). By extrapolating the model fit of the distribution to the opaque limit, a temperature estimate can be assigned to the semi-transparent cloud pixels, thereby replacing the measured brightness temperature which observes the combined background radiation and cloud emission. In this work, in addition to implementing data processing with the histogram based correction, we also developed a graphical user interface for testing the method, in order to provide a tool for the overall evaluation of the product.

  • 103. Kuenzer, Claudia
    et al.
    Zhang, Jianzhong
    Tetzlaff, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    van Dijk, Paul
    Voigt, Stefan
    Mehl, Harald
    Wagner, Wolfgang
    Uncontrolled coal fires and their environmental impacts: Investigating two arid mining regions in north-central China2007In: Applied Geography, ISSN 0143-6228, E-ISSN 1873-7730, Vol. 27, no 1, p. 42-62Article in journal (Refereed)
    Abstract [en]

    Uncontrolled coal fires occur worldwide and pose a great threat to the environment. This paper introduces the problem of coal fires referring to two coalfields in north-central China. These areas were regularly investigated during numerous fieldwork campaigns between 2002 and 2005. Emphasis is put on the environmental impacts of the fires, such as atmospheric influences, land subsidence, landscape degradation, as well as the danger for water resources and human health. New approaches for coal fire research are undertaken in numerous national and multi-lateral projects. Research disciplines, addressing the problem of coal fires, include geography, geology, geo-physics, mining-engineering, and remote sensing. In combination, they lead the direction towards a holistic approach to detect, monitor, quantify, and finally extinguish the coal fires. (c) 2006 Elsevier Ltd. All rights reserved.

  • 104. Kumar, Madathiparambil Ranganathapai Ramesh
    et al.
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Levy, Gad
    Sankar, Syam
    Bakan, Stephan
    Grassl, Hartmut
    A multi-sensor climatological view of double ITCZs over the Indian Ocean2012In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 33, no 9, p. 2925-2936Article in journal (Refereed)
    Abstract [en]

    We characterize the climatological features of the double inter-tropical convergence zones (DITCZs) over the western Indian Ocean during November-December by a synergistic analysis of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS III) data (1988-2005) and the National Aeronautics and Space Administration's (NASA's) A-Train data (2002-2009). We investigate rainfall, freshwater flux and cloud liquid water, cloud fraction and relative humidity over the DITCZs. In addition, the daily rainfall data from the Global Precipitation Climatology Project (GPCP) are used to document the DITCZs during the El Nino southern oscillation (ENSO) events. An analysis of the GPCP data shows that the DITCZs are clearly discernible during strong ENSO events (1997, 2002 and 2006), in sharp contrast to the DITCZs in the eastern Pacific Ocean, where they are absent during ENSOs. Further, these convergence zones on either side of the equator are of short duration, approximately 3-6 pentads during November and December. All satellite sensor data sets consistently capture the major features of DITCZs. As an accurate simulation of DITCZs in coupled global climate models remains a challenge, the results from the present study would provide a platform for evaluating these models.

  • 105. Kupiszewski, P.
    et al.
    Leck, C.
    Tjernstrom, M.
    Sjogren, S.
    Sedlar, Joseph
    SMHI, Research Department, Atmospheric remote sensing.
    Graus, M.
    Mueller, M.
    Brooks, B.
    Swietlicki, E.
    Norris, S.
    Hansel, A.
    Vertical profiling of aerosol particles and trace gases over the central Arctic Ocean during summer2013In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 13, no 24, p. 12405-12431Article in journal (Refereed)
    Abstract [en]

    Unique measurements of vertical size-resolved aerosol particle concentrations, trace gas concentrations and meteorological data were obtained during the Arctic Summer Cloud Ocean Study (ASCOS, www.ascos.se), an International Polar Year project aimed at establishing the processes responsible for formation and evolution of low-level clouds over the high Arctic summer pack ice. The experiment was conducted from on board the Swedish icebreaker Oden, and provided both ship-and helicopter-based measurements. This study focuses on the vertical helicopter profiles and onboard measurements obtained during a three-week period when Oden was anchored to a drifting ice floe, and sheds light on the characteristics of Arctic aerosol particles and their distribution throughout the lower atmosphere. Distinct differences in aerosol particle characteristics within defined atmospheric layers are identified. Within the lowermost couple hundred metres, transport from the marginal ice zone (MIZ), condensational growth and cloud processing develop the aerosol population. During two of the four representative periods defined in this study, such influence is shown. At altitudes above about 1 km, long-range transport occurs frequently. However, only infrequently does large-scale subsidence descend such air masses to become entrained into the mixed layer in the high Arctic, and there-fore long-range transport plumes are unlikely to directly influence low-level stratiform cloud formation. Nonetheless, such plumes can influence the radiative balance of the planetary boundary layer (PBL) by influencing formation and evolution of higher clouds, as well as through precipitation transport of particles downwards. New particle formation was occasionally observed, particularly in the near-surface layer. We hypothesize that the origin of these ultrafine particles could be in biological processes, both primary and secondary, within the open leads between the pack ice and/or along the MIZ. In general, local sources, in combination with upstream boundary-layer transport of precursor gases from the MIZ, are considered to constitute the origin of cloud condensation nuclei (CCN) particles and thus be of importance for the formation of interior Arctic low-level clouds during summer, and subsequently, through cloud influences, for the melting and freezing of sea ice.

  • 106. Kärner, O.
    et al.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Climate Monitoring SAF - Cloud products feasibility study in the inner Arctic region: Part II: Evaluation of the variability in radiation and cloud data2009Report (Other academic)
  • 107.
    Landelius, Tomas
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Andersson, Sandra
    SMHI, Core Services.
    Abrahamsson, Roger
    MODELLING AND FORECASTING PV PRODUCTION IN THE ABSENCE OF BEHIND-THE-METER MEASUREMENTS2018Conference paper (Refereed)
  • 108.
    Landelius, Tomas
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Andersson, Sandra
    SMHI, Core Services.
    Abrahamsson, Roger
    System imbalance from solar energy trading2018In: 8th Solar International Workshop on Integration of Solar into Power Systems, 2018Conference paper (Refereed)
  • 109.
    Landelius, Tomas
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Andersson, Sandra
    SMHI, Core Services.
    Carlund, Thomas
    SMHI, Core Services.
    Josefsson, Weine
    SMHI, Core Services. SMHI, Research Department, Atmospheric remote sensing.
    Karteringen av solstrålningen i Sverige2018In: Polarfront, no 168, p. 31-40Article in journal (Other academic)
  • 110.
    Landelius, Tomas
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Dahlgren, Per
    SMHI, Research Department, Meteorology.
    Gollvik, Stefan
    SMHI, Research Department, Meteorology.
    Jansson, A.
    Olsson, Esbjörn
    SMHI, Research Department, Meteorology.
    A high-resolution regional reanalysis for Europe. Part 2: 2D analysis of surface temperature, precipitation and wind2016In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 142, no 698, p. 2132-2142Article in journal (Refereed)
  • 111.
    Landelius, Tomas
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Josefsson, Weine
    SMHI, Research Department, Atmospheric remote sensing.
    Methods for cosine correction of broadband UV data and their effect on the relation between UV irradiance and cloudiness2000In: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996, Vol. 105, no D4, p. 4795-4802Article in journal (Refereed)
    Abstract [en]

    Irradiance measurements on a horizontal surface often deviate from theory where the irradiance is supposed to be proportional to the cosine of the angle of incidence. This discrepancy is known as the cosine error. In this paper, three different methods for cosine error correction are investigated. The simplest method is based on the assumption of an isotropic sky radiance distribution, regardless of sky conditions, and the irradiance is treated as a single component. In the second method the irradiance is divided into one direct solar and one diffuse sky component, where the latter is assumed to have an isotropic distribution. Finally, a third method also divides the irradiance into two components but under the assumption of an anisotropic sky radiance distribution. Irradiances under general sky conditions are found by interpolation between clear and overcast cases on the basis of sunshine duration or cloud cover. The three methods are applied to data from a Robertson-Berger sunburning meter located in Norrkoping, Sweden. Both methods, where the irradiance is divided into two components, produce acceptable and similar results, while the isotropic one-component method does not.

  • 112.
    Landelius, Tomas
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Josefsson, Weine
    SMHI, Research Department, Atmospheric remote sensing.
    Persson, Thomas
    SMHI.
    A system for modelling solar radiation parameters with mesoscale spatial resolution2001Report (Other academic)
    Abstract [en]

    Today, modern analysis systems synthesise meteorological data from a number of sources, e.g.\ round based SYNOP, satellites, radar, etc., into field information which enable us to model radiation at the Earth’s surface on the mesoscale. At the Swedish Meteorological and Hydrological Institute (SMHI) we have set up a model system that produce hourly information in terms of field data with a resolution of about 22 ´ 22 km2 for a geographic area covering Scandinavia and the run off region of the Baltic sea.Presently, the model calculates fields of global-, photosynthetically active- (PAR), UV- and direct radiation based on output from a mesoscale analysis system, a high resolution limited area numerical weather prediction model (NWP), an ice model for the Baltic sea together with satellite measurements of total ozone. A spectral clear sky model lies at the heart of the model system. Its output is multiplied by a function which captures the influence of clouds and precipitation. Different cloud effect functions are applied to the different radiation components, with the exception of global- and PAR for which the same relation is assumed.Measurements from the radiation network of SMHI were used for estimation and validation purposes. A first evaluation of the model system suggests that the RMSE for hourly global radiation data is on the order of 28% and about 16% for daily values. These errors are comparable to those obtained for models purely based on synoptic observations (SYNOP) (29% and 13%) . For UV radiation the figures are similar but for the direct radiation component they are worse; 53% and 31% respectively compared to 25% and 15% for the SYNOP models. To some extent the larger errors for the direct component could be explained by its sensitivity to scale differences when model grid squares are validated against point measurements.

  • 113. Leung, W. -YH.
    et al.
    Savre, J.
    Bender, F. A. -M
    Komppula, M.
    Portin, H.
    Romakkaniemi, S.
    Sedlar, Joseph
    SMHI, Research Department, Atmospheric remote sensing.
    Noone, K.
    Ekman, A. M. L.
    Sensitivity of a continental night-time stratocumulus-topped boundary layer to varying environmental conditions2016In: QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, ISSN 0035-9009, Vol. 142, no 700, p. 2911-2924Article in journal (Refereed)
  • 114. Lindfors, Anders
    et al.
    Kaurola, Jussi
    Arola, Antti
    Koskela, Tapani
    Lakkala, Kaisa
    Josefsson, Weine
    SMHI, Research Department, Atmospheric remote sensing.
    Olseth, Jan Asle
    Johnsen, Bjorn
    A method for reconstruction of past UV radiation based on radiative transfer modeling: Applied to four stations in northern Europe2007In: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996, Vol. 112, no D23, article id D23201Article in journal (Refereed)
    Abstract [en]

    A method for reconstruction of past UV radiation has been developed. The idea of the method is to use measurements of global radiation (300 - 3000 nm) for determining the influence of clouds on UV radiation. In order to transfer the information contained in the global radiation data into a cloud effect in the UV range, a so-called cloud modification table was developed, which is based on physical relationships determined through radiative transfer calculations. The method was given as input the measured global radiation and total ozone column, the total water vapor column from the ERA-40 data set, the surface albedo as estimated from snow depth, and the altitude of the location. Using this method, erythemally weighted UV irradiances were reconstructed back to the early 1980s at four stations in northern Europe: Bergen in Norway, Norrkoping in Sweden, and Jokioinen and Sodankyla in Finland. The reconstructed daily UV doses are in good agreement with measurements. For the summer season, the systematic error was found to vary between 0% at Bergen and 4% at Jokioinen, and the correlation coefficient was 0.99 at all stations. The summer root-mean-square error was 5% at all stations except Jokioinen, where it was 9%. The method performs well also for spring and autumn, whereas for winter conditions of low Sun, a systematical underestimation was found. A large part of this underestimation was found to be due to the plane-parallel approximation used in the radiative transfer calculations. The time series of reconstructed UV exhibit a clear increase since the early 1980s at both Sodankyla " (4.1%/decade; statistically significant) and Norrkoping (3.3%/decade; not significant). At Jokioinen, a weak increase was found, while at Bergen there was no considerable overall change. At both Sodankyla and Norrkoping, the increase in the reconstructed UV radiation was primarily driven by an increase in the global radiation, that is, by decreased cloudiness. The method is general in the sense that it can be applied also to other stations.

  • 115.
    Lindskog, Magnus
    et al.
    SMHI, Research Department, Meteorology.
    Gustafsson, Nils
    SMHI, Research Department, Meteorology.
    Navascues, B
    Mogensen, K S
    Huang, X Y
    Yang, X
    Andrae, Ulf
    SMHI, Research Department, Meteorology.
    Berre, Loik
    SMHI, Research Department, Atmospheric remote sensing.
    Thorsteinsson, S
    Rantakokko, J
    Three-dimensional variational data assimilation for a limited area model Part II: Observation handling and assimilation experiments2001In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 53, no 4, p. 447-468Article in journal (Refereed)
    Abstract [en]

    A 3-dimensional variational data assimilation (3D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system is described. The HIRLAM 3D-Var is based on the minimisation of a cost function that consists of one term, J(b), which measures the distance between the resulting analysis and a background field, in general a short-range forecast, and another term. J(o), which measures the distance between the analysis and the observations. This paper is concerned with J(o) and the handling of observations, while the companion Paper by Gustafsson et al. (2001) is concerned with the general 3D-Var formulation and with the J(b) term. Individual system components. such as the screening of observations and the observation operators, and other issues, such as the parallelisation strategy for the computer code, are described. The functionality of the observation quality control is investigated and the 3D-Var system is validated through data assimilation and forecast experiments. Results from assimilation and forecast experiments indicate that the 3D-Var assimilation system performs significantly better than two currently used HIRLAM systems. which are based on statistical interpolation. The use of all significant level data from multilevel observation reports is shown to be one factor contributing to the superiority of the 3D-Var system. Other contributing factors are most probably the formulation of the analysis as a single global problem, the use of non-separable structure functions and the variational quality control, which accounts for non-Gaussian observation errors.

  • 116.
    Lindskog, Magnus
    et al.
    SMHI, Research Department, Meteorology.
    Landelius, Tomas
    SMHI, Research Department, Atmospheric remote sensing.
    Prognoser av Solstrålning2018In: Polarfront, no 168, p. 41-44Article in journal (Other academic)
  • 117. Loewe, Katharina
    et al.
    Ekman, Annica M. L.
    Paukert, Marco
    Sedlar, Joseph
    SMHI, Research Department, Atmospheric remote sensing.
    Tjernstrom, Michael
    Hoose, Corinna
    Modelling micro- and macrophysical contributors to the dissipation of an Arctic mixed-phase cloud during the Arctic Summer Cloud Ocean Study (ASCOS)2017In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 17, no 11, p. 6693-6704Article in journal (Refereed)
  • 118.
    Mattsson, Johan
    et al.
    SMHI.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Climate Monitoring SAF - cloud products feasibility study in the inner Arctic region: Part I: Cloud mask studies during the 2001 Oden Arctic expedition2002Report (Other academic)
  • 119. Meinander, O.
    et al.
    Kazadzis, S.
    Blumthaler, M.
    Ylianttila, L.
    Johnsen, B.
    Lakkala, K.
    Koskela, T.
    Josefsson, Weine
    SMHI, Research Department, Atmospheric remote sensing.
    Diurnal discrepancies in spectral solar UV radiation measurements2006In: Applied Optics, ISSN 1559-128X, E-ISSN 2155-3165, Vol. 45, no 21, p. 5346-5357Article in journal (Refereed)
    Abstract [en]

    Unexpected diurnal discrepancies between high-quality spectroradiometers were observed during the 2000 Nordic Ozone Group Intercomparison campaign. The spectral ratios of the irradiances showed a diurnal variation of similar to 2-9%. This cannot be explained by the nonideal angular response of the instruments' input optics in one plane (cosine effect). Instead, by using a radiative transfer model, we show that differences in the angular response in four azimuth planes have the potential to bias the measured data by up to 4.4% (azimuth effect). Other relevant factors are also discussed and quantified and are shown to be significant when diurnal changes in radiation are explained by environmental factors, or when measured data are compared with model or satellite data. Again, intercomparison campaigns have the potential to reveal errors that would otherwise remain undetected. (c) 2006 Optical Society of America.

  • 120.
    Michelson, Daniel
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Andersson, Tage
    SMHI, Research Department.
    Koistinen, Jarmo
    Collier, Christopher G.
    Riedl, J.
    Szturc., J.
    Nielsen, A.
    Overgaard Persson, T.
    BALTEX Radar Data Centre Products and their Methodologies2000Report (Other academic)
  • 121.
    Michelson, Daniel
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Henja, Anders
    SMHI.
    Ernes, Sander
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Koistinen, Jarmo
    Ośródka, Katarzyna
    Peltonen, Tuomas
    Szewczykowski, Maciej
    Szturc, Jan
    BALTRAD Advanced Weather Radar Networking2018In: Journal of Open Research Software, ISSN 2049-9647, no 3, article id 12Article in journal (Refereed)
  • 122.
    Michelson, Daniel
    et al.
    SMHI, Core Services.
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Landelius, Tomas
    SMHI, Research Department, Atmospheric remote sensing.
    Collier, C G
    Haase, Gunther
    SMHI, Research Department, Atmospheric remote sensing.
    Heen, M
    'Down-to-Earth' modelling of equivalent surface precipitation using multisource data and radar2005In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 131, no 607, p. 1093-1112Article in journal (Refereed)
    Abstract [en]

    The estimation of surface rainfall from reflectivity data derived from weather radar has been much studied over many years. It is now clear that central to this problem is the adjustment of these data for the impacts of vertical variations in the reflectivity. In this paper a new procedure (known as Down-to-Earth, DTE) is proposed and tested for combining radar measurements aloft with information from a numerical weather-prediction (NWP) model and an analysis system. The procedure involves the exploitation of moist cloud physics in an attempt to account for physical processes impacting on precipitation during its descent from the height of radar echo measurements to the surface. The application of DTE leads to increased underestimation in the radar measurements compared to precipitation gauge observations at short and intermediate radar ranges (0-120 km), but is successful at reducing the bias at further ranges. However the application of DTE does not lead to significant decreases in the random error of the surface rain rate estimate. No improvement is made when attempting to account for the precipitation phase measured by radar. It is concluded that further work on radar data quality control, along with improvements to the NWP model, are essential to improve upon results using such a physically based procedure.

  • 123.
    Michelson, Daniel
    et al.
    SMHI, Core Services.
    Landelius, Tomas
    SMHI, Research Department, Atmospheric remote sensing.
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Collier, C. G.
    Attempts to parameterize cloud water profiles using a neural network2004In: Atmospheric Science Letters, ISSN 1530-261X, E-ISSN 1530-261X, Vol. 5, no 7, p. 141-145Article in journal (Refereed)
    Abstract [en]

    Atmospheric state variables from a Numerical Weather Prediction (NWP) model are combined with analyzed cloud base heights in a neural network, with the objective to model corresponding cloud water profiles. It was found that the neural network was incapable of resolving the inherently non-linear vertical cloud water distributions. Copyright (C) 2004 Royal Meteorological Society

  • 124. Nilsson, Cecilia
    et al.
    Dokter, Adriaan M.
    Verlinden, Liesbeth
    Shamoun-Baranes, Judy
    Schmid, Baptiste
    Desmet, Peter
    Bauer, Silke
    Chapman, Jason
    Alves, Jose A.
    M. Stepanian, Philip
    Sapir, Nir
    Wainwright, Charlotte
    Boos, Mathieu
    Górska, Anna
    Menz, Myles H. M.
    Rodrigues, Pedro
    Leijnse, Hidde
    Zehtindjiev, Pavel
    Brabant, Robin
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Weisshaupt, Nadja
    Ciach, Michał
    Liechti, Felix
    Revealing patterns of nocturnal migration using the European weather radar network2018In: Ecography, ISSN 0906-7590, E-ISSN 1600-0587, no 42, p. 1-11Article in journal (Refereed)
  • 125. Nilsson, Cecilia
    et al.
    Dokter, Adriaan M.
    Verlinden, Liesbeth
    Shamoun-Baranes, Judy
    Schmid, Baptiste
    Desmet, Peter
    Bauer, Silke
    Chapman, Jason
    Alves, Jose A.
    Stepanian, Phillip M.
    Sapir, Nir
    Wainwright, Charlotte
    Boos, Mathieu
    Gorska, Anna
    Menz, Myles H. M.
    Rodrigues, Pedro
    Leijnse, Hidde
    Zehtindjiev, Pavel
    Brabant, Robin
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Weisshaupt, Nadja
    Ciach, Michal
    Liechti, Felix
    Revealing patterns of nocturnal migration using the European weather radar network2019In: Ecography, ISSN 0906-7590, E-ISSN 1600-0587, Vol. 42, no 5, p. 876-886Article in journal (Refereed)
  • 126. Nilsson, Cecilia
    et al.
    M. Dokter, Adriaan
    Schmid, Baptiste
    Scacco, Martina
    Verlinden, Liesbeth
    Bäckman, Johan
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Dell’Omo, Giacomo
    W. Chapman, Jason
    Leijnse, Hidde
    Liechti, Felix
    Field validation of radar systems for monitoring bird migration2018In: Journal of Applied Ecology, ISSN 0021-8901, E-ISSN 1365-2664, Vol. 00, p. 1-13Article in journal (Refereed)
  • 127.
    Norin, Lars
    SMHI, Research Department, Atmospheric remote sensing.
    A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data2015In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 8, no 2, p. 593-609Article in journal (Refereed)
    Abstract [en]

    In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in the radar line of sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on 6 years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. It is shown that this in part can be explained by detection by the radar sidelobes and by scattering off increased levels of dust and turbulence. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. It is shown that, when weather echoes give rise to higher reflectivity values than those of the wind farm, the negative impact of the wind turbines is greatly reduced for all spectral moments.

  • 128.
    Norin, Lars
    SMHI, Research Department, Atmospheric remote sensing.
    Wind turbine impact on operational weather radar I/Q data: characterisation and filtering2017In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 10, no 5, p. 1739-1753Article in journal (Refereed)
  • 129.
    Norin, Lars
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    L'Ecuyer, T. S.
    Wood, N. B.
    Smalley, M.
    Intercomparison of snowfall estimates derived from the CloudSat Cloud Profiling Radar and the ground-based weather radar network over Sweden2015In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 8, no 12, p. 5009-5021Article in journal (Refereed)
    Abstract [en]

    Accurate snowfall estimates are important for both weather and climate applications. Ground-based weather radars and space-based satellite sensors are often used as viable alternatives to rain gauges to estimate precipitation in this context. In particular, the Cloud Profiling Radar (CPR) on board CloudSat is proving to be a useful tool to map snowfall globally, in part due to its high sensitivity to light precipitation and its ability to provide near-global vertical structure. CloudSat snowfall estimates play a particularly important role in the high-latitude regions as other ground-based observations become sparse and passive satellite sensors suffer from inherent limitations. In this paper, snowfall estimates from two observing systems-Swerad, the Swedish national weather radar network, and CloudSat - are compared. Swerad offers a well-calibrated data set of precipitation rates with high spatial and temporal resolution, at very high latitudes. The measurements are anchored to rain gauges and provide valuable insights into the usefulness of CloudSat CPR's snowfall estimates in the polar regions. In total, 7 : 2 x 10(5) matchups of CloudSat and Swerad observations from 2008 through 2010 were intercompared, covering all but the summer months (June to September). The intercomparison shows encouraging agreement between the two observing systems despite their different sensitivities and user applications. The best agreement is observed when CloudSat passes close to a Swerad station (46-82 km), where the observational conditions for both systems are comparable. Larger disagreements outside this range suggest that both platforms have difficulty with shallow snow but for different reasons. The correlation between Swerad and CloudSat degrades with increasing distance from the nearest Swerad station, as Swerad's sensitivity decreases as a function of distance. Swerad also tends to overshoot low-level precipitating systems further away from the station, leading to an underestimation of snowfall rate and occasionally to missing precipitation altogether. Several statistical metrics-including the probability of detection, false alarm rate, hit rate, and Pierce's skill score - are calculated. The sensitivity of these metrics to the snowfall rate, as well as to the distance from the nearest radar station, are summarised. This highlights the strengths and the limitations of both observing systems at the lower and upper ends of the snowfall distributions as well as the range of uncertainties that can be expected from these systems in high-latitude regions.

  • 130.
    Norin, Lars
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    L'Ecuyer, Tristan S.
    The sensitivity of snowfall to weather states over Sweden2017In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 10, no 9, p. 3249-3263Article in journal (Refereed)
  • 131. Pareeth, Sajid
    et al.
    Delucchi, Luca
    Metz, Markus
    Rocchini, Duccio
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Raspaud, Martin
    SMHI, Core Services.
    Adrian, Rita
    Salmaso, Nico
    Neteler, Markus
    New Automated Method to Develop Geometrically Corrected Time Series of Brightness Temperatures from Historical AVHRR LAC Data2016In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 8, no 3Article in journal (Refereed)
    Abstract [en]

    Analyzing temporal series of satellite data for regional scale studies demand high accuracy in calibration and precise geo-rectification at higher spatial resolution. The Advanced Very High Resolution Radiometer (AVHRR) sensor aboard the National Oceanic and Atmospheric Administration (NOAA) series of satellites provide daily observations for the last 30 years at a nominal resolution of 1.1 km at nadir. However, complexities due to on-board malfunctions and orbital drifts with the earlier missions hinder the usage of these images at their original resolution. In this study, we developed a new method using multiple open source tools which can read level 1B radiances, apply solar and thermal calibration to the channels, remove bow-tie effects on wider zenith angles, correct for clock drifts on earlier images and perform precise geo-rectification by automated generation and filtering of ground control points using a feature matching technique. The entire workflow is reproducible and extendable to any other geographical location. We developed a time series of brightness temperature maps from AVHRR local area coverage images covering the sub alpine lakes of Northern Italy at 1 km resolution (1986-2014; 28 years). For the validation of derived brightness temperatures, we extracted Lake Surface Water Temperature (LSWT) for Lake Garda in Northern Italy and performed inter-platform (NOAA-x vs. NOAA-y) and cross-platform (NOAA-x vs. MODIS/ATSR/AATSR) comparisons. The MAE calculated over available same day observations between the pairs-NOAA-12/14, NOAA-17/18 and NOAA-18/19 are 1.18 K, 0.67 K, 0.35 K, respectively. Similarly, for cross-platform pairs, the MAE varied between 0.5 to 1.5 K. The validation of LSWT from various NOAA instruments with in-situ data shows high accuracy with mean R-2 and RMSE of 0.97 and 0.91 K respectively.

  • 132. Pareeth, Sajid
    et al.
    Delucchi, Luca
    Metz, Markus
    Rocchini, Duccio
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Raspaud, Martin
    SMHI, Core Services.
    Adrian, Rita
    Salmaso, Nico
    Neteler, Markus
    New Automated Method to Develop Geometrically Corrected Time Series of Brightness Temperatures from Historical AVHRR LAC Data2016In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 8, no 3, p. NIL_481-NIL_508Article in journal (Refereed)
    Abstract [en]

    Analyzing temporal series of satellite data for regional scale studies demand high accuracy in calibration and precise geo-rectification at higher spatial resolution. The Advanced Very High Resolution Radiometer (AVHRR) sensor aboard the National Oceanic and Atmospheric Administration (NOAA) series of satellites provide daily observations for the last 30 years at a nominal resolution of 1.1 km at nadir. However, complexities due to on-board malfunctions and orbital drifts with the earlier missions hinder the usage of these images at their original resolution. In this study, we developed a new method using multiple open source tools which can read level 1B radiances, apply solar and thermal calibration to the channels, remove bow-tie effects on wider zenith angles, correct for clock drifts on earlier images and perform precise geo-rectification by automated generation and filtering of ground control points using a feature matching technique. The entire workflow is reproducible and extendable to any other geographical location. We developed a time series of brightness temperature maps from AVHRR local area coverage images covering the sub alpine lakes of Northern Italy at 1 km resolution (1986-2014; 28 years). For the validation of derived brightness temperatures, we extracted Lake Surface Water Temperature (LSWT) for Lake Garda in Northern Italy and performed inter-platform (NOAA-x vs. NOAA-y) and cross-platform (NOAA-x vs. MODIS/ATSR/AATSR) comparisons. The MAE calculated over available same day observations between the pairs-NOAA-12/14, NOAA-17/18 and NOAA-18/19 are 1.18 K, 0.67 K, 0.35 K, respectively. Similarly, for cross-platform pairs, the MAE varied between 0.5 to 1.5 K. The validation of LSWT from various NOAA instruments with in-situ data shows high accuracy with mean R-2 and RMSE of 0.97 and 0.91 K respectively.

  • 133. Pfreundschuh, Simon
    et al.
    Eriksson, Patrick
    Duncan, David
    Rydberg, Bengt
    Håkansson, Nina
    SMHI, Research Department, Atmospheric remote sensing.
    Thoss, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems2018In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 11, no 8, p. 4627-4643Article in journal (Refereed)
  • 134. Raschke, E
    et al.
    Meywerk, J
    Warrach, K
    Andrae, Ulf
    SMHI, Research Department, Meteorology.
    Bergström, Sten
    SMHI, Research Department, Hydrology.
    Beyrich, F
    Bosveld, F
    Bumke, K
    Fortelius, C
    Graham, Phil
    SMHI, Research Department, Climate research - Rossby Centre.
    Gryning, S E
    Halldin, S
    Hasse, L
    Heikinheimo, M
    Isemer, H J
    Jacob, D
    SMHI.
    Jauja, I
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Keevallik, S
    Koistinen, J
    van Lammeren, A
    Lass, U
    Launianen, J
    Lehmann, A
    Liljebladh, B
    Lobmeyr, M
    Matthaus, W
    Mengelkamp, T
    Michelson, Daniel
    SMHI, Core Services.
    Napiorkowski, J
    Omstedt, Anders
    SMHI, Research Department, Oceanography.
    Piechura, J
    Rockel, B
    Rubel, F
    Ruprecht, E
    Smedman, A S
    Stigebrandt, A
    The Baltic Sea Experiment (BALTEX): A European contribution to the investigation of the energy and water cycle over a large drainage basin2001In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 82, no 11, p. 2389-2413Article, review/survey (Refereed)
    Abstract [en]

    The Baltic Sea Experiment (BALTEX) is one of the five continental-scale experiments of the Global Energy and Water Cycle Experiment (GEWEX). More than 50 research groups from 14 European countries are participating in this project to measure and model the energy and water cycle over the large drainage basin of the Baltic Sea in northern Europe. BALTEX aims to provide a better understanding of the processes of the climate system and to improve and to validate the water cycle in regional numerical models for weather forecasting and climate studies. A major effort is undertaken to couple interactively the atmosphere with the vegetated continental surfaces and the Baltic Sea including its sea ice. The intensive observational and modeling phase BRIDGE, which is a contribution to the Coordinated Enhanced Observing Period of GEWEX, will provide enhanced datasets for the period October 1999-February 2002 to validate numerical models and satellite products. Major achievements have been obtained in an improved understanding of related exchange processes. For the first time an interactive atmosphere-ocean-land surface model for the Baltic Sea was tested. This paper reports on major activities and some results.

  • 135.
    Raspaud, Martin
    et al.
    SMHI, Core Services.
    Hoese, David
    Dybbroe, Adam
    SMHI, Core Services.
    Lahtinen, Panu
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Itkin, Mikhail
    Hamann, Ulrich
    Rasmussen, Lars Orum
    Nielsen, Esben Stigard
    Leppelt, Thomas
    Maul, Alexander
    Kliche, Christian
    Thorsteinsson, Hrobjartur
    PyTroll: An Open-Source, Community-Driven Python Framework to Process Earth Observation Satellite Data2018In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 99, no 7, p. 1329-1336Article in journal (Refereed)
  • 136. Reuter, M.
    et al.
    Thomas, W.
    Albert, P.
    Lockhoff, M.
    Weber, R.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Fischer, J.
    The CM-SAF and FUB Cloud Detection Schemes for SEVIRI: Validation with Synoptic Data and Initial Comparison with MODIS and CALIPSO2009In: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 48, no 2, p. 301-316Article in journal (Refereed)
    Abstract [en]

    The Satellite Application Facility on Climate Monitoring (CM-SAF) is aiming to retrieve satellite-derived geophysical parameters suitable for climate monitoring. CM-SAF started routine operations in early 2007 and provides a climatology of parameters describing the global energy and water cycle on a regional scale and partially on a global scale. Here, the authors focus on the performance of cloud detection methods applied to measurements of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the first Meteosat Second Generation geostationary spacecraft. The retrieved cloud mask is the basis for calculating the cloud fractional coverage (CFC) but is also mandatory for retrieving other geophysical parameters. Therefore, the quality of the cloud detection directly influences climate monitoring of many other parameters derived from spaceborne sensors. CM-SAF products and results of an alternative cloud coverage retrieval provided by the Institut fur Weltraumwissenschaften of the Freie Universitat in Berlin, Germany (FUB), were validated against synoptic measurements. Furthermore, and on the basis of case studies, an initial comparison was performed of CM-SAF results with results derived from the Moderate Resolution Imaging Spectrometer (MODIS) and from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Results show that the CFC from CM-SAF and FUB agrees well with synoptic data and MODIS data over midlatitudes but is underestimated over the tropics and overestimated toward the edges of the visible Earth disk.

  • 137.
    Ridal, Martin
    et al.
    SMHI, Research Department, Meteorology.
    Lindskog, Magnus
    SMHI, Research Department, Meteorology.
    Gustafsson, Nils
    SMHI, Research Department, Meteorology.
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Optimized advection of radar reflectivities2011In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 100, no 2-3, p. 213-225Article in journal (Refereed)
    Abstract [en]

    A nowcasting system for generation of short-range precipitation forecasts has been developed at the Swedish Meteorological and Hydrological Institute (SMHI). The methodology consists of utilising a time-series of radar reflectivity composites for deriving an advection field, which will give a better representation of the motion of the precipitation pattern compared to a model wind field. The advection field is derived applying a 4-dimensional variational data assimilation technique. The resulting field is then used for a semi-Lagrangian advection of the latest available reflectivity field forward in time. During the forecast, the advected field is gradually replaced by a numerical weather prediction forecast in order to include the onset of convection and advection into the radar coverage area. In an idealised example with simulated observations the functionality of the method is demonstrated. For a case study of a full scale example the resulting precipitation forecast shows large improvements compared to the operational numerical weather prediction model used at SMHI, especially for forecasts up to three hours, where the largest influence from the radar advection occurs. In an objective validation of the structure, amplitude and location of modelled precipitation, where the forecasts are compared to radar observations, these findings are confirmed. The same validation of model runs over a longer time period also clearly indicates that the amplitude, structure and location of the precipitation patterns are significantly improved as compared to a short-range forecast from the operational forecast model used at SMHI. (C) 2010 Elsevier B.V. All rights reserved.

  • 138. Riihela, Aku
    et al.
    Key, Jeffrey R.
    Meirink, Jan Fokke
    Munneke, Peter Kuipers
    Palo, Timo
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    An intercomparison and validation of satellite-based surface radiative energy flux estimates over the Arctic2017In: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996, Vol. 122, no 9, p. 4829-4848Article in journal (Refereed)
  • 139. Roebeling, Rob
    et al.
    Baum, Bryan
    Bennartz, Ralf
    Hamann, Ulrich
    Heidinger, Andrew
    Meirink, Jan Fokke
    Stengel, Martin
    Thoss, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    Walther, Andi
    Watts, Phil
    Summary of the Fourth Cloud Retrieval Evaluation Workshop2015In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 96, no 4, p. ES71-ES74Article in journal (Refereed)
  • 140. Roebeling, Rob
    et al.
    Baum, Bryan
    Bennartz, Ralf
    Hamann, Ulrich
    Heidinger, Andy
    Thoss, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    Walther, Andi
    EVALUATING AND IMPROVING CLOUD PARAMETER RETRIEVALS2013In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 94, no 4, p. ES41-ES44Article in journal (Other academic)
  • 141. Rossa, A.
    et al.
    Haase, Gunther
    SMHI, Research Department, Atmospheric remote sensing.
    Keil, C.
    Alberoni, P.
    Ballard, S.
    Bech, J.
    Germann, U.
    Pfeifer, M.
    Salonen, K.
    Propagation of uncertainty from observing systems into NWP: COST-731 Working Group 12010In: Atmospheric Science Letters, ISSN 1530-261X, E-ISSN 1530-261X, Vol. 11, no 2, p. 145-152Article in journal (Refereed)
    Abstract [en]

    The COST-731 Action is focused on uncertainty propagation in hydrometeorological forecasting chains. The goals and activities of the Action Working Group 1 can be subdivided by (1) describing and studying the impact of imperfect observations, mostly from radar, (2) exploiting radar data assimilation as a promising avenue for improved short-range precipitation forecasts and (3) high-resolution ensemble forecasting. Activities of Working Group 1 are presented along with their possible significance for hydrological applications. Copyright (C) 2010 Royal Meteorological Society and Crown Copyright

  • 142. Rossa, Andrea
    et al.
    Liechti, Katharina
    Zappa, Massimiliano
    Bruen, Michael
    Germann, Urs
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Keil, Christian
    Krahe, Peter
    The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems2011In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 100, no 2-3, p. 150-167Article, review/survey (Refereed)
    Abstract [en]

    Quantifying uncertainty in flood forecasting is a difficult task, given the multiple and strongly nonlinear model components involved in such a system. Much effort has been and is being invested in the quest of dealing with uncertain precipitation observations and forecasts and the propagation of such uncertainties through hydrological and hydraulic models predicting river discharges and risk for inundation. The COST 731 Action is one of these and constitutes a European initiative which deals with the quantification of forecast uncertainty in hydro-meteorological forecast systems. COST 731 addresses three major lines of development: (1) combining meteorological and hydrological models to form a forecast chain, (2) propagating uncertainty information through this chain and make it available to end users in a suitable form, (3) advancing high-resolution numerical weather prediction precipitation forecasts by using non-conventional observations from, for instance, radar to determine details in the initial conditions on scales smaller than what can be resolved by conventional observing systems. Recognizing the interdisciplinarity of the challenge COST 731 has organized its work forming Working Groups at the interfaces between the different scientific disciplines involved, i.e. between observation and atmospheric (and hydrological) modelling (WG-1), between atmospheric and hydrologic modelling (WG-2) and between hydrologic modelling and end-users (WG-3). This paper summarizes the COST 731 activities and its context, provides a review of the recent progress made in dealing with uncertainties in flood forecasting, and sets the scene for the papers of this Thematic Issue. In particular, a bibliometric analysis highlights the strong recent increase in addressing the uncertainty analysis in flood forecasting from an integrated perspective. Such a perspective necessarily involves the area of meteorology, hydrology, and decision making in order to take operational advantage of the scientific progress, an aspect in which COST 731 is successfully contributing to furthering the flood damage mitigation capabilities in Europe. (C) 2010 Elsevier B.V. All rights reserved.

  • 143. Salonen, K.
    et al.
    Jarvinen, H.
    Haase, Gunther
    SMHI, Research Department, Atmospheric remote sensing.
    Niemela, S.
    Eresmaa, R.
    Doppler radar radial winds in HIRLAM. Part II: optimizing the super-observation processing2009In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 61, no 2, p. 288-295Article in journal (Refereed)
    Abstract [en]

    Doppler radar radial wind observations are modelled in numerical weather prediction (NWP) within observation errors which consist of instrumental, modelling and representativeness errors. The systematic and random modelling errors can be reduced through a careful design of the observation operator (Part I). The impact of the random instrumental and representativeness errors can be decreased by optimizing the processing of the so-called super-observations (spatial averages of raw measurements; Part II). The super-observation processing is experimentally optimized in this article by determining the optimal resolution for the super-observations for different NWP model resolutions. A 1-month experiment with the HIRLAM data assimilation and forecasting system is used for radial wind data monitoring and for generating observation minus background (OmB) differences. The OmB statistics indicate that the super-observation processing reduces the standard deviation of the radial wind speed OmB difference, while the mean vector wind OmB difference tends to increase. The optimal parameter settings correspond at a measurement range of 50 km (100 km) to an averaging area of 1.7 km(2) (7.3 km(2)). In conclusion, an accurate and computationally feasible observation operator for the Doppler radar radial wind observations is developed (Part I) and a super-observation processing system is optimized (Part II).

  • 144. Salonen, Kirsti
    et al.
    Haase, Gunther
    SMHI, Research Department, Atmospheric remote sensing.
    Eresmaa, Reima
    Hohti, Harri
    Jarvinen, Heikki
    Towards the operational use of Doppler radar radial winds in HIRLAM2011In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 100, no 2-3, p. 190-200Article in journal (Refereed)
    Abstract [en]

    This article discusses the pre-operational development for data assimilation of radial wind observations in the High Resolution Limited Area Model (HIRLAM) at the Finnish Meteorological Institute (FMI). The HIRLAM variational data assimilation system includes all the needed tools for exploitation of radial wind observations. A measurement task designed especially for the radial wind data assimilation purposes has been implemented to the FMI radar network. Observation quality monitoring indicates that the main error sources for the radial wind observations are ground clutter and velocity ambiguity. The HIRLAM quality control procedures are able to detect and reject most of these erroneous observations. Impact studies show encouraging results. Surface verification indicates that the use of radar wind observations has a positive impact on 10 m wind forecasts. Precipitation forecasts are also slightly improved. Upper air verification shows positive impact on wind and temperature forecasts at the 925-700 hPa levels. (C) 2010 Elsevier B.V. All rights reserved.

  • 145. Saltikoff, Elena
    et al.
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Delobbe, Laurent
    Gaussiat, Nicolas
    Martet, Maud
    Idziorek, Daniel
    Leijnse, Hidde
    Novak, Petr
    Lukach, Maryna
    Stephan, Klaus
    OPERA the Radar Project2019In: Atmosphere, ISSN 2073-4433, E-ISSN 2073-4433, Vol. 10, no 6, article id 320Article in journal (Refereed)
  • 146. Saltikoff, Elena
    et al.
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Leijnse, Hidde
    Novák, Petr
    Delobbe, Laurent
    OPERA – past, present and future2018In: ERAD 2018 10TH EUROPEAN CONFERENCE ON RADAR IN METEOROLOGY & HYDROLOGY / [ed] Vos, Lotte de; Leijnse, Hidde; Uijlenhoet, Remko, 2018, p. 491-493Conference paper (Other academic)
  • 147.
    Scheirer, Ronald
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Dybbroe, Adam
    SMHI, Core Services.
    Raspaud, Martin
    SMHI, Core Services.
    A General Approach to Enhance Short Wave Satellite Imagery by Removing Background Atmospheric Effects2018In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 10, no 4, article id 560Article in journal (Refereed)
  • 148. Schulz, J.
    et al.
    Albert, P.
    Behr, H. -D
    Caprion, D.
    Deneke, H.
    Dewitte, S.
    Durr, B.
    Fuchs, P.
    Gratzki, A.
    Hechler, P.
    Hollmann, R.
    Sheldon, Johnston, Marston
    SMHI, Research Department, Atmospheric remote sensing.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Manninen, T.
    Mueller, R.
    Reuter, M.
    Riihela, A.
    Roebeling, R.
    Selbach, N.
    Tetzlaff, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    Thomas, W.
    Werscheck, M.
    Wolters, E.
    Zelenka, A.
    Operational climate monitoring from space: the EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF)2009In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 9, no 5, p. 1687-1709Article in journal (Refereed)
    Abstract [en]

    The Satellite Application Facility on Climate Monitoring (CM-SAF) aims at the provision of satellite-derived geophysical parameter data sets suitable for climate monitoring. CM-SAF provides climatologies for Essential Climate Variables (ECV), as required by the Global Climate Observing System implementation plan in support of the UNFCCC. Several cloud parameters, surface albedo, radiation fluxes at the top of the atmosphere and at the surface as well as atmospheric temperature and humidity products form a sound basis for climate monitoring of the atmosphere. The products are categorized in monitoring data sets obtained in near real time and data sets based on carefully intercalibrated radiances. The CM-SAF products are derived from several instruments on-board operational satellites in geostationary and polar orbit as the Meteosat and NOAA satellites, respectively. The existing data sets will be continued using data from the instruments on-board the new joint NOAA/EUMETSAT Meteorological Operational Polar satellite. The products have mostly been validated against several ground-based data sets both in situ and remotely sensed. The accomplished accuracy for products derived in near real time is sufficient to monitor variability on diurnal and seasonal scales. The demands on accuracy increase the longer the considered time scale is. Thus, interannual variability or trends can only be assessed if the sensor data are corrected for jumps created by instrument changes on successive satellites and more subtle effects like instrument and orbit drift and also changes to the spectral response function of an instrument. Thus, a central goal of the recently started Continuous Development and Operations Phase of the CM-SAF (2007-2012) is to further improve all CM-SAF data products to a quality level that allows for studies of interannual variability.

  • 149.
    Sedlar, Joseph
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Clear-sky thermodynamic and radiative anomalies over a sea ice sensitive region of the Arctic2012In: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996, Vol. 117, article id D19111Article in journal (Refereed)
    Abstract [en]

    Monthly clear-sky anomalies of atmospheric temperature and water vapor over the East Siberian and Laptev Sea regions of the Arctic for 2003-2010 are examined here. This region experiences significant interannual variations in sea ice concentration and is also where ice loss was most apparent in the record year 2007. Clear-sky thermodynamic profiles come from the Atmospheric Infrared Sounder (AIRS) sensor onboard the Aqua satellite. Associated longwave (LW) and shortwave (SW) radiation-flux anomalies are estimated through radiative transfer modeling. Anomalies of temperature (+/- 10 K) and water vapor (+/- 1 g kg(-1)) often positively covary, resulting in distinct signatures in the clear-sky downwelling LW (LWD) anomalies, occasionally larger than +/- 10 W m(-2) around the 2003-2010 climatology. Estimates of mean greenhouse anomalies indicate a shift from negative to positive anomalies midway through the 8-year record. Sensitivity tests suggest that temperature anomalies are the strongest contributor to both LWD and greenhouse anomalies, relative to water-vapor anomalies; monthly averaging of column precipitable water yields relatively small anomalies (order 1 mm) that produce a linear response in greenhouse anomalies. Finally the clear-sky contribution to 2007 monthly ice thickness is estimated. Anomalous clear-sky radiation retards the total 2007 ice thickness by 0.3 m (15-30% of ice-thickness climatology), and anomalous LW radiation is most important for preconditioning the ice during the months prior to, and after, the summer melt season. A highly sensitive interaction between cloud fraction, surface albedo and LWD anomalies is found, and we develop a metric for determining clear-sky anomalous ice melt potential.

  • 150.
    Sedlar, Joseph
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Shupe, Matthew D.
    Tjernstrom, Michael
    On the Relationship between Thermodynamic Structure and Cloud Top, and Its Climate Significance in the Arctic2012In: Journal of Climate, ISSN 0894-8755, E-ISSN 1520-0442, Vol. 25, no 7, p. 2374-2393Article in journal (Refereed)
    Abstract [en]

    Cloud and thermodynamic characteristics from three Arctic observation sites are investigated to understand the collocation between low-level clouds and temperature inversions. A regime where cloud top was 100-200 m above the inversion base [cloud inside inversion (CII)] was frequently observed at central Arctic Ocean sites, while observations from Barrow, Alaska, indicate that cloud tops were more frequently constrained to inversion base height [cloud capped by inversion (CCI)]. Cloud base and top heights were lower, and temperature inversions were also stronger and deeper, during CII cases. Both cloud regimes were often decoupled from the surface except for CCI over Barrow. In-cloud lapse rates differ and suggest increased cloud-mixing potential for CII cases. Specific humidity inversions were collocated with temperature inversions for more than 60% of the CCI and more than 85% of the CII regimes. Horizontal advection of heat and moisture is hypothesized as an important process controlling thermodynamic structure and efficiency of cloud-generated motions. The portion of CII clouds above the inversion contains cloud radar signatures consistent with cloud droplets. The authors test the longwave radiative impact of cloud liquid above the inversion through hypothetical liquid water distributions. Optically thin CII clouds alter the effective cloud emission temperature and can lead to an increase in surface flux on the order of 1.5 W m(-2) relative to the same cloud but whose top does not extend above the inversion base. The top of atmosphere impact is even larger, increasing outgoing longwave radiation up to 10 W m(-2). These results suggest a potentially significant longwave radiative forcing via simple liquid redistributions for a distinctly dominant cloud regime over sea ice.

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