Change search
Refine search result
1 - 16 of 16
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1. Bennartz, Ralf
    et al.
    Hoschen, Heidrun
    Picard, Bruno
    Schroder, Marc
    Stengel, Martin
    Sus, Oliver
    Bojkov, Bojan
    Casadio, Stefano
    Diedrich, Hannes
    Eliasson, Salomon
    SMHI, Research Department, Atmospheric remote sensing.
    Fell, Frank
    Fischer, Jurgen
    Hollmann, Rainer
    Preusker, Rene
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    An intercalibrated dataset of total column water vapour and wet tropospheric correction based on MWR on board ERS-1, ERS-2, and Envisat2017In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 10, no 4, p. 1387-1402Article in journal (Refereed)
    Download full text (pdf)
    fulltext
  • 2. Cooper, Steven J.
    et al.
    L'Ecuyer, Tristan S.
    Wolff, Mareile Astrid
    Kuhn, Thomas
    Pettersen, Claire
    Wood, Norman B.
    Eliasson, Salomon
    SMHI, Research Department, Meteorology.
    Schirle, Claire E.
    Shates, Julia
    Hellmuth, Franziska
    Engdahl, Bjorg Jenny Kokkvoll
    Vasquez-Martin, Sandra
    Ilmo, Trond
    Nygard, Knut
    Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign2022In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 103, no 8, p. E1762-E1780Article in journal (Refereed)
    Download full text (pdf)
    Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign
  • 3.
    Eliasson, Salomon
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    van Meijgaard, Erik
    Meirink, Jan Fokke
    Stengel, Martin
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model2019In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 12, no 2, p. 829-847Article in journal (Refereed)
    Download full text (pdf)
    fulltext
  • 4.
    Eliasson, Salomon
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness2020In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 13, no 1, p. 297-314Article in journal (Refereed)
    Download full text (pdf)
    fulltext
  • 5.
    Eliasson, Salomon
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Tetzlaff, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Prototyping an improved PPS cloud detection for the Arctic polar night2007Report (Other academic)
    Abstract [en]

    A new Polar Platform Systems (PPS) Cloud Mask (CM) test sequence is required for improving cloud detection during Arctic winter conditions. This study introduces a test sequence, called Ice Night Sea (INS), that to a greater extent successfully detects clouds over ice surfaces and which is less sensitive to cloud free misclassification.The test sequence uses a combination of Numerical Weather Prediction (NWP) fields and Advanced Very High Resolution Radiometer (AVHRR) satellite data. Only the infrared (IR) AVHRR channels can be exploited during night conditions. Training target data from winter 2001-2002, collected over a large area north of the Atmospheric Radiation Measurement (ARM) site at Barrow, Alaska, were used to assess the general atmospheric state of the Arctic and to perform a qualitative validation of CM test sequences. Results clearly show that the atmospheric conditions during Arctic winter severely hamper cloud detection efforts. Very cold surface temperatures and immense surface temperature inversions lead to a diminished separability between surfaces and clouds. One particular problem is that the IR brightness temperatures for the shortest wavelength (3.7μm - henceforth T37) are strongly affected by noise. The use of an IR noise filter was shown to improve results significantly. In addition, the problem of misclassifying cracks in the pack ice as Cirrus clouds was basically solved by using a dedicated filter using the local variance of T37.Using an inverse version of a typical daytime Cirrus test (based on just two IR channels and normally applied successfully outside the Arctic region), it is shown that we can detect a substantial part of the warmsemi-transparent clouds commonly found in the Arctic. Running the test sequences on training target data revealed an improvement in correct cloud free target classification of around 30% but only a marginal improvement for cloudy training targets. However, visual inspection of results obtained for about 50 scenes covering a large part of the Arctic region in January 2007 clearly indicated improvements also for the cloudy portion of the scenes. The INS CM test sequence awaits a more rigorous and quantitative validation, e.g. based on comparisons with CLOUDSAT/CALIPSO satellite data sets.

    Download full text (pdf)
    FULLTEXT01
  • 6. Holl, G.
    et al.
    Eliasson, Salomon
    SMHI, Research Department, Atmospheric remote sensing.
    Mendrok, J.
    Buehler, S. A.
    SPARE-ICE: Synergistic ice water path from passive operational sensors2014In: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996, Vol. 119, no 3, p. 1504-1523Article in journal (Refereed)
    Abstract [en]

    This article presents SPARE-ICE, the Synergistic Passive Atmospheric Retrieval Experiment-ICE. SPARE-ICE is the first Ice Water Path (IWP) product combining infrared and microwave radiances. By using only passive operational sensors, the SPARE-ICE retrieval can be used to process data from at least the NOAA 15 to 19 and MetOp satellites, obtaining time series from 1998 onward. The retrieval is developed using collocations between passive operational sensors (solar, terrestrial infrared, microwave), the CloudSat radar, and the CALIPSO lidar. The collocations form a retrieval database matching measurements from passive sensors against the existing active combined radar-lidar product 2C-ICE. With this retrieval database, we train a pair of artificial neural networks to detect clouds and retrieve IWP. When considering solar, terrestrial infrared, and microwave-based measurements, we show that any combination of two techniques performs better than either single-technique retrieval. We choose not to include solar reflectances in SPARE-ICE, because the improvement is small, and so that SPARE-ICE can be retrieved both daytime and nighttime. The median fractional error between SPARE-ICE and 2C-ICE is around a factor 2, a figure similar to the random error between 2C-ICE ice water content (IWC) and in situ measurements. A comparison of SPARE-ICE with Moderate Resolution Imaging Spectroradiometer (MODIS), Pathfinder Atmospheric Extended (PATMOS-X), and Microwave Surface and Precipitation Products System (MSPPS) indicates that SPARE-ICE appears to perform well even in difficult conditions. SPARE-ICE is available for public use.

  • 7.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Meteorology.
    Devasthale, Abhay
    SMHI, Research Department, Meteorology.
    Eliasson, Salomon
    SMHI, Research Department, Meteorology.
    Global Cloudiness and Cloud Top Information from AVHRR in the 42-Year CLARA-A3 Climate Data Record Covering the Period 1979-20202023In: Remote Sensing, E-ISSN 2072-4292, Vol. 15, no 12, article id 3044Article in journal (Refereed)
    Download full text (pdf)
    Global Cloudiness and Cloud Top Information from AVHRR in the 42-Year CLARA-A3 Climate Data Record Covering the Period 1979-2020
  • 8.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Johansson, Erik
    SMHI, Research Department, Atmospheric remote sensing.
    Håkansson, Nina
    SMHI, Research Department, Atmospheric remote sensing.
    Sedlar, Joseph
    Eliasson, Salomon
    SMHI, Research Department, Atmospheric remote sensing.
    Probabilistic Cloud Masking for the Generation of CM SAF Cloud Climate Data Records from AVHRR and SEVIRI Sensors2020In: Remote Sensing, E-ISSN 2072-4292, Vol. 12, no 4, article id 713Article in journal (Refereed)
    Download full text (pdf)
    fulltext
  • 9.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Meteorology.
    Stengel, Martin
    Meirink, Jan Fokke
    Riihelae, Aku
    Trentmann, Joerg
    Akkermans, Tom
    Stein, Diana
    Devasthale, Abhay
    SMHI, Research Department, Meteorology.
    Eliasson, Salomon
    SMHI, Research Department, Meteorology.
    Johansson, Erik
    SMHI, Research Department, Meteorology.
    Håkansson, Nina
    SMHI, Research Department, Meteorology.
    Solodovnik, Irina
    Benas, Nikos
    Clerbaux, Nicolas
    Selbach, Nathalie
    Schroeder, Marc
    Hollmann, Rainer
    CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 20232023In: Earth System Science Data, ISSN 1866-3508, E-ISSN 1866-3516, Vol. 15, no 11, p. 4901-4926Article in journal (Refereed)
    Download full text (pdf)
    CLARA-A3: The third edition of the AVHRR-based CM SAF climate data record on clouds, radiation and surface albedo covering the period 1979 to 2023
  • 10.
    Sheldon, Johnston, Marston
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Eliasson, Salomon
    SMHI, Research Department, Atmospheric remote sensing.
    Eriksson, P.
    Forbes, R. M.
    Gettelman, A.
    Raisanen, P.
    Zelinka, M. D.
    Diagnosing the average spatio-temporal impact of convective systems - Part 2: A model intercomparison using satellite data2014In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 14, no 16, p. 8701-8721Article in journal (Refereed)
    Abstract [en]

    The representation of the effect of tropical deep convective (DC) systems on upper-tropospheric moist processes and outgoing longwave radiation is evaluated in the EC-Earth3, ECHAM6, and CAM5 (Community Atmosphere Model) climate models using satellite-retrieved data. A composite technique is applied to thousands of deep convective systems that are identified using local rain rate maxima in order to focus on the temporal evolution of the deep convective processes in the model and satellite-retrieved data. The models tend to over-predict the occurrence of rain rates that are less than approximate to 3 mm h(-1) compared to Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA). While the diurnal distribution of oceanic rain rate maxima in the models is similar to the satellite-retrieved data, the land-based maxima are out of phase. Despite having a larger climatological mean uppertropospheric relative humidity, models closely capture the satellite-derived moistening of the upper troposphere following the peak rain rate in the deep convective systems. Simulated cloud fractions near the tropopause are larger than in the satellite data, but the ice water contents are smaller compared with the satellite-retrieved ice data. The models capture the evolution of ocean-based deep convective systems fairly well, but the land-based systems show significant discrepancies. Over land, the diurnal cycle of rain is too intense, with deep convective systems occurring at the same position on subsequent days, while the satellite-retrieved data vary more in timing and geographical location. Finally, simulated outgoing longwave radiation anomalies associated with deep convection are in reasonable agreement with the satellite data, as well as with each other. Given the fact that there are strong disagreements with, for example, cloud ice water content, and cloud fraction, between the models, this study supports the hypothesis that such agreement with satellite-retrieved data is achieved in the three models due to different representations of deep convection processes and compensating errors.

    Download full text (pdf)
    fulltext
  • 11.
    Sheldon, Johnston, Marston
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Eriksson, P.
    Eliasson, Salomon
    SMHI, Research Department, Atmospheric remote sensing.
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Forbes, R. M.
    Murtagh, D. P.
    The representation of tropical upper tropospheric water in EC Earth V22012In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 39, no 11, p. 2713-2731Article in journal (Refereed)
    Abstract [en]

    Tropical upper tropospheric humidity, clouds, and ice water content, as well as outgoing longwave radiation (OLR), are evaluated in the climate model EC Earth with the aid of satellite retrievals. The Atmospheric Infrared Sounder and Microwave Limb Sounder together provide good coverage of relative humidity. EC Earth's relative humidity is in fair agreement with these observations. CloudSat and CALIPSO data are combined to provide cloud fractions estimates throughout the altitude region considered (500-100 hPa). EC Earth is found to overestimate the degree of cloud cover above 200 hPa and underestimate it below. Precipitating and non-precipitating EC Earth ice definitions are combined to form a complete ice water content. EC Earth's ice water content is below the uncertainty range of CloudSat above 250 hPa, but can be twice as high as CloudSat's estimate in the melting layer. CERES data show that the model underestimates the impact of clouds on OLR, on average with about 9 W m(-2). Regionally, EC Earth's outgoing longwave radiation can be similar to 20 W m(-2) higher than the observation. A comparison to ERA-Interim provides further perspectives on the model's performance. Limitations of the satellite observations are emphasised and their uncertainties are, throughout, considered in the analysis. Evaluating multiple model variables in parallel is a more ambitious approach than is customary.

  • 12. Stengel, Martin
    et al.
    Meirink, Jan Fokke
    Eliasson, Salomon
    SMHI, Research Department, Meteorology.
    On the Temperature Dependence of the Cloud Ice Particle Effective Radius-A Satellite Perspective2023In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 50, no 6, article id e2022GL102521Article in journal (Refereed)
    Download full text (pdf)
    On the Temperature Dependence of the Cloud Ice Particle Effective Radius-A Satellite Perspective
  • 13. Stengel, Martin
    et al.
    Schlundt, Cornelia
    Stapelberg, Stefan
    Sus, Oliver
    Eliasson, Salomon
    SMHI, Research Department, Atmospheric remote sensing.
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    Meirink, Jan Fokke
    Comparing ERA-Interim clouds with satellite observations using a simplified satellite simulator2018In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 18, no 23, p. 17601-17614Article in journal (Refereed)
    Download full text (pdf)
    fulltext
  • 14. Vazquez-Martin, Sandra
    et al.
    Kuhn, Thomas
    Eliasson, Salomon
    SMHI, Research Department, Meteorology.
    Mass of different snow crystal shapes derived from fall speed measurements2021In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 21, no 24, p. 18669-18688Article in journal (Refereed)
    Abstract [en]

    Meteorological forecast and climate models require good knowledge of the microphysical properties of hydrometeors and the atmospheric snow and ice crystals in clouds, for instance, their size, cross-sectional area, shape, mass, and fall speed. Especially shape is an important parameter in that it strongly affects the scattering properties of ice particles and consequently their response to remote sensing techniques. The fall speed and mass of ice particles are other important parameters for both numerical forecast models and the representation of snow and ice clouds in climate models. In the case of fall speed, it is responsible for the rate of removal of ice from these models. The particle mass is a key quantity that connects the cloud microphysical properties to radiative properties. Using an empirical relationship between the dimensionless Reynolds and Best numbers, fall speed and mass can be derived from each other if particle size and cross-sectional area are also known. In this study, ground-based in situ measurements of snow particle microphysical properties are used to analyse mass as a function of shape and the other properties particle size, cross-sectional area, and fall speed. The measurements for this study were done in Kiruna, Sweden, during snowfall seasons of 2014 to 2019 and using the ground-based in situ Dual Ice Crystal Imager (D-ICI) instrument, which takes high-resolution side- and top-view images of natural hydrometeors. From these images, particle size (maximum dimension), cross-sectional area, and fall speed of individual particles are determined. The particles are shape-classified according to the scheme presented in our previous study, in which particles sort into 15 different shape groups depending on their shape and morphology. Particle masses of individual ice particles are estimated from measured particle size, cross-sectional area, and fall speed. The selected dataset covers sizes from about 0.1 to 3.2 mm, fall speeds from 0.1 to 1.6 m s(-1) , and masses from 0.2 to 450 mu g. In our previous study, the fall speed relationships between particle size and cross-sectional area were studied. In this study, the same dataset is used to determine the particle mass, and consequently, the mass relationships between particle size, cross-sectional area, and fall speed are studied for these 15 shape groups. Furthermore, the mass relationships presented in this study are compared with the previous studies. For certain crystal habits, in particular columnar shapes, the maximum dimension is unsuitable for determining Reynolds number. Using a selection of columns, for which the simple geometry allows the verification of an empirical Best-number-to-Reynolds-number relationship, we show that Reynolds number and fall speed are more closely related to the diameter of the basal facet than the maximum dimension. The agreement with the empirical relationship is further improved using a modified Best number, a function of an area ratio based on the falling particle seen in the vertical direction.

    Download full text (pdf)
    Mass of different snow crystal shapes derived from fall speed measurements
  • 15. Vazquez-Martin, Sandra
    et al.
    Kuhn, Thomas
    Eliasson, Salomon
    SMHI, Research Department, Atmospheric remote sensing.
    Shape Dependence of Falling Snow Crystals' Microphysical Properties Using an Updated Shape Classification2020In: Applied Sciences, E-ISSN 2076-3417, Vol. 10, no 3, article id 1163Article in journal (Refereed)
    Abstract [en]

    We present ground-based in situ snow measurements in Kiruna, Sweden, using the ground-based in situ instrument Dual Ice Crystal Imager (D-ICI). D-ICI records dual high-resolution images from above and from the side of falling natural snow crystals and other hydrometeors with particle sizes ranging from 50 mu m to 4 mm. The images are from multiple snowfall seasons during the winters of 2014/2015 to 2018/2019, which span from the beginning of November to the middle of May. From our images, the microphysical properties of individual particles, such as particle size, cross-sectional area, area ratio, aspect ratio, and shape, can be determined. We present an updated classification scheme, which comprises a total of 135 unique shapes, including 34 new snow crystal shapes. This is useful for other studies that are using previous shape classification schemes, in particular the widely used Magono-Lee classification. To facilitate the study of the shape dependence of the microphysical properties, we further sort these individual particle shapes into 15 different shape groups. Relationships between the microphysical properties are determined for each of these shape groups.

    Download full text (pdf)
    fulltext
  • 16. Vazquez-Martin, Sandra
    et al.
    Kuhn, Thomas
    Eliasson, Salomon
    SMHI, Research Department, Atmospheric remote sensing.
    Shape dependence of snow crystal fall speed2021In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 21, no 10, p. 7545-7565Article in journal (Refereed)
    Abstract [en]

    Improved snowfall predictions require accurate knowledge of the properties of ice crystals and snow particles, such as their size, cross-sectional area, shape, and fall speed. The fall speed of ice particles is a critical parameter for the representation of ice clouds and snow in atmospheric numerical models, as it determines the rate of removal of ice from the modelled clouds. Fall speed is also required for snowfall predictions alongside other properties such as ice particle size, cross-sectional area, and shape. For example, shape is important as it strongly influences the scattering properties of these ice particles and thus their response to remote sensing techniques. This work analyzes fall speed as a function of particle size (maximum dimension), cross-sectional area, and shape using ground-based in situ measurements. The measurements for this study were done in Kiruna, Sweden, during the snowfall seasons of 2014 to 2019, using the ground-based in situ instrument Dual Ice Crystal Imager (D-ICI). The resulting data consist of high-resolution images of falling hydrometeors from two viewing geometries that are used to determine particle size (maximum dimension), cross-sectional area, area ratio, orientation, and the fall speed of individual particles. The selected dataset covers sizes from about 0.06 to 3.2mm and fall speeds from 0.06 to 1.6 m s(-1). Relationships between particle size, cross-sectional area, and fall speed are studied for different shapes. The data show in general low correlations to fitted fall speed relationships due to large spread observed in fall speed. After binning the data according to size or cross-sectional area, correlations improve, and we can report reliable parameterizations of fall speed vs. particle size or cross-sectional area for part of the shapes. For most of these shapes, the fall speed is better correlated with cross-sectional area than with particle size. The effects of orientation and area ratio on the fall speed are also studied, and measurements show that vertically oriented particles fall faster on average. However, most particles for which orientation can be defined fall horizontally.

    Download full text (pdf)
    Shape dependence of snow crystal fall speed
1 - 16 of 16
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf