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  • 1.
    Devasthale, Abhay
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Quaas, J.
    Grassl, H.
    Correcting orbital drift signal in the time series of AVHRR derived convective cloud fraction using rotated empirical orthogonal function2012In: ATMOSPHERIC MEASUREMENT TECHNIQUES, ISSN 1867-1381, Vol. 5, no 2, p. 267-273Article in journal (Refereed)
    Abstract [en]

    The Advanced Very High Resolution Radiometer (AVHRR) instruments onboard the series of National Oceanic and Atmospheric Administration (NOAA) satellites offer the longest available meteorological data records from space. These satellites have drifted in orbit resulting in shifts in the local time sampling during the life span of the sensors onboard. Depending upon the amplitude of the diurnal cycle of the geophysical parameters derived, orbital drift may cause spurious trends in their time series. We investigate tropical deep convective clouds, which show pronounced diurnal cycle amplitude, to estimate an upper bound of the impact of orbital drift on their time series. We carry out a rotated empirical orthogonal function analysis (REOF) and show that the REOFs are useful in delineating orbital drift signal and, more importantly, in subtracting this signal in the time series of convective cloud amount. These results will help facilitate the derivation of homogenized data series of cloud amount from NOAA satellite sensors and ultimately analyzing trends from them. However, we suggest detailed comparison of various methods and rigorous testing thereof applying final orbital drift corrections.

  • 2.
    Devasthale, Abhay
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Tjernstrom, Michael
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Thomas, Manu Anna
    SMHI, Research Department, Air quality.
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Sedlar, Joseph
    SMHI, Research Department, Atmospheric remote sensing.
    Omar, Ali H.
    The vertical distribution of thin features over the Arctic analysed from CALIPSO observations2011In: Tellus. Series B, Chemical and physical meteorology, ISSN 0280-6509, E-ISSN 1600-0889, Vol. 63, no 1, p. 77-85Article in journal (Refereed)
    Abstract [en]

    Clouds play a crucial role in the Arctic climate system. Therefore, it is essential to accurately and reliably quantify and understand cloud properties over the Arctic. It is also important to monitor and attribute changes in Arctic clouds. Here, we exploit the capability of the CALIPSO-CALIOP instrument and provide comprehensive statistics of tropospheric thin clouds, otherwise extremely difficult to monitor from passive satellite sensors. We use 4 yr of data (June 2006-May 2010) over the circumpolar Arctic, here defined as 67-82 degrees N, and characterize probability density functions of cloud base and top heights, geometrical thickness and zonal distribution of such cloud layers, separately for water and ice phases, and discuss seasonal variability of these properties. When computed for the entire study area, probability density functions of cloud base and top heights and geometrical thickness peak at 200-400, 1000-2000 and 400-800 m, respectively, for thin water clouds, while for ice clouds they peak at 6-8, 7-9 and 400-1000 m, respectively. In general, liquid clouds were often identified below 2 km during all seasons, whereas ice clouds were sensed throughout the majority of the upper troposphere and also, but to a smaller extent, below 2 km for all seasons.

  • 3.
    Devasthale, Abhay
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Quantifying the clear-sky temperature inversion frequency and strength over the Arctic Ocean during summer and winter seasons from AIRS profiles2010In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 10, no 12, p. 5565-5572Article in journal (Refereed)
    Abstract [en]

    Temperature inversions are one of the dominant features of the Arctic atmosphere and play a crucial role in various processes by controlling the transfer of mass and moisture fluxes through the lower troposphere. It is therefore essential that they are accurately quantified, monitored and simulated as realistically as possible over the Arctic regions. In the present study, the characteristics of inversions in terms of frequency and strength are quantified for the entire Arctic Ocean for summer and winter seasons of 2003 to 2008 using the AIRS data for the clear-sky conditions. The probability density functions (PDFs) of the inversion strength are also presented for every summer and winter month. Our analysis shows that although the inversion frequency along the coastal regions of Arctic decreases from June to August, inversions are still seen in almost each profile retrieved over the inner Arctic region. In winter, inversions are ubiquitous and are also present in every profile analysed over the inner Arctic region. When averaged over the entire study area (70 degrees N-90 degrees N), the inversion frequency in summer ranges from 69 to 86% for the ascending passes and 72-86% for the descending passes. For winter, the frequency values are 88-91% for the ascending passes and 89-92% for the descending passes of AIRS/AQUA. The PDFs of inversion strength for the summer months are narrow and right-skewed (or positively skewed), while in winter, they are much broader. In summer months, the mean values of inversion strength for the entire study area range from 2.5 to 3.9 K, while in winter, they range from 7.8 to 8.9 K. The standard deviation of the inversion strength is double in winter compared to summer. The inversions in the summer months of 2007 were very strong compared to other years. The warming in the troposphere of about 1.5-3.0K vertically extending up to 400 hPa was observed in the summer months of 2007.

  • 4.
    Dybbroe, Adam
    et al.
    SMHI, Core Services.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Thoss, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    NWCSAF AVHRR cloud detection and analysis using dynamic thresholds and radiative transfer modeling. Part I: Algorithm description2005In: Journal of applied meteorology (1988), ISSN 0894-8763, E-ISSN 1520-0450, Vol. 44, no 1, p. 39-54Article in journal (Refereed)
    Abstract [en]

    New methods and software for cloud detection and classification at high and midlatitudes using Advanced Very High Resolution Radiometer (AVHRR) data are developed for use in a wide range of meteorological, climatological, land surface, and oceanic applications within the Satellite Application Facilities (SAFs) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), including the SAF for Nowcasting and Very Short Range Forecasting Applications (NWCSAF) project. The cloud mask employs smoothly varying (dynamic) thresholds that separate fully cloudy or cloud-contaminated fields of view from cloud-free conditions. Thresholds are adapted to the actual state of the atmosphere and surface and the sun-satellite viewing geometry using cloud-free radiative transfer model simulations. Both the cloud masking and the cloud-type classification are done using sequences of grouped threshold tests that employ both spectral and textural features. The cloud-type classification divides the cloudy pixels into 10 different categories: 5 opaque cloud types, 4 semitransparent clouds, and 1 subpixel cloud category. The threshold method is fuzzy in the sense that the distances in feature space to the thresholds are stored and are used to determine whether to stop or to continue testing. They are also used as a quality indicator of the final output. The atmospheric state should preferably be taken from a short-range NWP model, but the algorithms can also run with climatological fields as input.

  • 5.
    Dybbroe, Adam
    et al.
    SMHI, Core Services.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Thoss, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    NWCSAF AVHRR cloud detection and analysis using dynamic thresholds and radiative transfer modeling. Part II: Tuning and validation2005In: Journal of applied meteorology (1988), ISSN 0894-8763, E-ISSN 1520-0450, Vol. 44, no 1, p. 55-71Article in journal (Refereed)
    Abstract [en]

    Algorithms for cloud detection (cloud mask) and classification (cloud type) at high and midlatitudes using data from the Advanced Very High Resolution Radiometer (AVHRR) on board the current NOAA satellites and future polar Meteorological and Operational Weather Satellites (METOP) of the European Organisation for the Exploitation of Meteorological Satellites have been extensively validated over northern Europe and the adjacent seas. The algorithms have been described in detail in Part I and are based on a multispectral grouped threshold approach, making use of cloud-free radiative transfer model simulations. The thresholds applied in the algorithms have been validated and tuned using a database interactively built up over more than 1 yr of data from NOAA-12, -14, and -15 by experienced nephanalysts. The database contains almost 4000 rectangular (in the image data)-sized targets (typically with sides around 10 pixels), with satellite data collocated in time and space with atmospheric data from a short-range NWP forecast model, land cover characterization, elevation data, and a label identifying the given cloud or surface type as interpreted by the nephanalyst. For independent and objective validation, a large dataset of nearly 3 yr of collocated surface synoptic observation (Synop) reports, AVHRR data, and NWP model output over northern and central Europe have been collected. Furthermore, weather radar data were used to check the consistency of the cloud type. The cloud mask performs best over daytime sea and worst at twilight and night over land. As compared with Synop, the cloud cover is overestimated during night (except for completely overcast situations) and is underestimated at twilight. The algorithms have been compared with the more empirically based Swedish Meteorological and Hydrological Institute (SMHI) Cloud Analysis Model Using Digital AVHRR Data (SCANDIA), operationally run at SMHI since 1989, and results show that performance has improved significantly.

  • 6.
    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.

  • 7. Hedfors, J
    et al.
    Aldahan, A
    Kulan, A
    Possnert, G
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Vintersved, I
    Clouds and Be-7: Perusing connections between cosmic rays and climate2006In: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996, Vol. 111, no D2, article id D02208Article in journal (Refereed)
    Abstract [en]

    [1] Time series data on Be-7, precipitation, temperature, and satellite imagery of cloud cover over Scandinavia, together with cosmic ray and sunspot activity, were used to elucidate the relationship between cosmic rays and clouds, and ultimately climate change. The results indicate a coherent negative correlation between total cloud cover and Be-7 on intraseasonal, seasonal, and decadal scales. Although the reasons behind this correlation are unclear, a full-scale implication of this feature is in the possible use of Be-7 and Be-10 records for proxy paleo-reconstruction of total cloud cover. This is a strongly needed, but generally difficult to quantify parameter in climate models.

  • 8. Hultgren, Pia
    et al.
    Dybbroe, Adam
    SMHI, Core Services.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    SCANDIA -its accuracy in classifying LOW CLOUD1999Report (Other academic)
  • 9. Hyvarinen, Otto
    et al.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Dybbroe, Adam
    SMHI, Core Services.
    Investigations of NOAA AVHRR/3 1.6 m m imagery for snow, cloud and sunglint discrimination (Nowcasting SAF)1999Report (Other academic)
  • 10.
    Johnston, Sheldon
    et al.
    SMHI, Research Department, Climate research - Rossby Centre.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    METEOSAT 8 SEVIRI and NOAA AVHRR Cloud Products: A Climate Monitoring SAF2007Report (Other academic)
    Abstract [en]

    The goals of this study are to compare the MSG SEVIRI and PPS AVHRR monthly mean cloud products of the CM-SAF. The study was done in two parts: first comparing the cloud mask products and then comparing the cloud top temperature and height products. This was done over a region from Greenland to eastern Russia and as far south as the Sahara. The study covered four seasonally-representative months. For the cloud mask using PPS version 1.0, the results showed large problems over the Sahara and parts of Spain during the summer months. This was primarily due to the high reflectances in channel 3a and mostprominent with NOAA 17.Much larger differences were found over water than over land surfaces, with the exception of Scandinavia where the differences were comparable to those found over water. The cloud-contaminated values were removed in one plot and this revealed that PPS had a larger number of cloud-contaminated pixels than MSG. This agrees with the concept that MSG reports increased cloudiness at higher viewing angles. This also explains why the differences over Scandinavia were so large and positive in value. The NOAA images at high latitudes have better spatial resolution and reports fewer cloudy and cloud-contaminated pixels than MSG.Sub-pixel and thin clouds greatly affected how well the two products converged. An attempt to use a weighted factor to adjust the effect of cloud-contaminated pixels on the total cloud cover failed to improve the convergence between the two cloud masks. The effect of the MSG viewing angle and the subsequent effects of reporting more cloudy pixels (or cloud-contaminated pixel – to include thin clouds) could be seen throughout all four months in the form of larger positive differences at latitudes approaching 80 degrees. Significant changes were seen with results from the PPS version 1.1. A significant decrease in the difference over the Sahara was the most discernable change. On the other hand, for NOAA 17, the agreement with MSG during twilight conditions was reduced by almost one half. The comparison of the cloud top temperature and height products revealed that MSG reported more low clouds during the summer months than PPS. This was mostly like due to the presence of convective clouds and the angle at which they are viewed (small cumulus clouds when viewed from nadir has a smaller diameter than when viewed slantwise).

  • 11.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    A 10 year cloud climatology over Scandinavia derived from NOAA advanced very high resolution radiometer imagery2003In: International Journal of Climatology, ISSN 0899-8418, E-ISSN 1097-0088, Vol. 23, no 9, p. 1023-1044Article in journal (Refereed)
    Abstract [en]

    Results from a satellite-based method to compile regional cloud climatologies covering the Scandinavian region are presented. Systematic processing of multispectral image data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) instrument has been utilized to provide monthly cloud climatologies covering the period 1991-2000. Considerable local-scale variation of cloud amounts was found in the region. The inland Baltic Sea and adjacent land areas exhibited a large-amplitude annual cycle in cloudiness (high cloud amounts in winter, low cloud amounts in summer) whereas a weak-amplitude reversed annual cycle (high cloud amounts with a weak maximum in summer) was found for the Scandinavian mountain range. As a contrast, conditions over the Norwegian Sea showed high and almost unchanged cloud amounts during the course of the year. Some interesting exceptions to these patterns were also seen locally. The quality of the satellite-derived cloud climatology was examined through comparisons with climatologies derived from surface cloud observations, from the International Satellite Cloud Climatology Project (ISCCP) and from the European Centre for Medium-range Weather Forecasts ERA-40 data set. In general, cloud amount deviations from surface observations were smaller than 10% except for some individual winter months, when the separability between clouds and snow-covered cold land surfaces is often poor. The ISCCP data set showed a weaker annual cycle in cloudiness, generally caused by higher summer-time cloud amounts in the region. Very good agreement was found with the ERA-40 data set, especially for the summer season. However, ERA-40 showed higher cloud amounts than SCANDIA and ISCCP during the winter season. The derived cloud climatology is affected by errors due to temporal AVHRR sensor degradation, but they appear to be small for this particular study. The data set is proposed as a valuable data set for validation of cloud description in numerical weather prediction and regional climate simulation models. Copyright (C) 2003 Royal Meteorological Society.

  • 12.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    A NOAA AVHRR cloud climatology over Scandinavia covering the period 1991-20002001Report (Other academic)
  • 13.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Cloud classifications with the SCANDIA model1996Report (Other academic)
  • 14.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Cloud climate investigations in the Nordic region using NOAA AVHRR data1997In: Journal of Theoretical and Applied Climatology, ISSN 0177-798X, E-ISSN 1434-4483, Vol. 57, no 3-4, p. 181-195Article in journal (Refereed)
    Abstract [en]

    A method to estimate monthly cloud conditions (monthly cloud frequencies) from multispectral satellite imagery is described. The operational cloud classification scheme SCANDIA (the SMHI Cloud ANalysis model using DIgital AVHRR data), based on high resolution imagery from the polar orbiting NOAA-satellites, has been used to produce monthly cloud frequencies for the entire year of 1993 and some additional months in 1991, 1992, 1994 and 1995. Cloud analyses were made for an area covering the Nordic countries with a horizontal resolution of four km. Examples of seasonal, monthly and diurnal variation in cloud conditions are given and an annual mean for 1993 is presented. Comparisons with existing surface observations showed very good agreement for horizontal cloud distributions but approximately 5% smaller cloud amounts were found in the satellite estimations. The most evident problems were encountered in the winter season due to difficulties in identifying low-level cloudiness at very low sun elevations. The underestimation in the summer season was partly fictious and caused by the overestimation of convective cloud cover by surface observers. SCANDIA results were compared to ISCCP (International Satellite Cloud Climatology Project) cloud climatologies for two selected months in 1991 and 1992. ISCCP cloudiness was indicated to be higher, especially during the month with anticyclonic conditions where a cloudiness excess of more than 10% were found. The regional variation of cloud conditions in the area was found to be inadequately described by ISCCP cloud climatologies. An improvement of the horizontal resolution of ISCCP data seems necessary to enable use for regional applications. The SCANDIA model is proposed as a valuable tool for local and regional monitoring of the cloud climatology at high latitudes. More extensive comparisons with ISCCP cloud climatologies are suggested as well as comparisons with modelled cloudiness from atmospheric general circulation models and climate models. Special studies of cloud conditions in the Polar areas are also proposed.

  • 15.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    DEVELOPMENT OF AN OPERATIONAL CLOUD CLASSIFICATION MODEL1989In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 10, no 4-5, p. 687-693Article in journal (Refereed)
  • 16.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    ESTIMATION OF CLOUDINESS AT HIGH-LATITUDES FROM MULTISPECTRAL SATELLITE MEASUREMENTS1995In: Ambio, ISSN 0044-7447, E-ISSN 1654-7209, Vol. 24, no 1, p. 33-40Article in journal (Refereed)
    Abstract [en]

    Clouds play an important role in the climate system, and strongly modify radiation conditions in the atmosphere and at the earth's surface. Present estimations show that the net impact of clouds in the atmosphere results in a cooling several times larger than the expected warming that would result from a doubling of the CO2-concentration in the atmosphere. Regional and global monitoring of cloud conditions is therefore necessary for studying the role of clouds in possible climate feedback mechanisms. This paper presents a method to estimate cloud conditions (cloud cover) in the Nordic region, from multispectral satellite data. A cloud classification scheme, based on high-resolution imagery data from polar orbiting NOAA-satellites, was used to produce monthly cloud frequencies for the summer of 1993. Comparisons with existing surface observations have shown very good agreement. Cloud conditions are shown to be highly sensitive to characteristics of the earth's surface. Large differences between land and sea areas were found, especially in the beginning of summer. Cloud frequencies were significantly lower over the Baltic Sea compared to surrounding land areas. Mountainous areas showed, on the contrary, much higher cloud frequencies than surrounding areas.

  • 17.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Information från Meteosat - forskningsrön och operationell tillämpning1985Report (Other academic)
  • 18.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Satellite sensing techniques and applications for the purpose of BALTEX2000In: Meteorologische Zeitschrift, ISSN 0941-2948, E-ISSN 1610-1227, Vol. 9, no 2, p. 111-116Article in journal (Refereed)
    Abstract [en]

    Various satellite sensing techniques and their corresponding applications suitable for use in validation and modelling activities in BALTEX are presented and discussed. Special emphasis is given to data and mature applications available during the main BALTEX BRIDGE experiment. For atmospheric simulations and studies, sensors measuring radiation budget quantities, cloud properties, moisture content and precipitation are considered as most important. Sensors measuring ice conditions and sea state parameters are identified for oceanographical applications and sensors measuring snow conditions and surface conditions are listed for hydrological studies. One example of an application based on extracted cloud information from NOAA AVHRR imagery is demonstrated. Estimations of mean cloud conditions in summer for the period 1991-1998 are shown for the total cloud cover, Cirrus cloudiness and low-level cloudiness over the Nordic region. It is shown that the Baltic Sea and other sea surfaces in the region has a large impact in suppressing summertime cloudiness, in particular low-level cloudiness. As a contrast, cloud patterns for high-level clouds show low correlation with the spatial distribution of sea surfaces. The influence of topographic features (i.e., the Scandinavian mountain range) seems more important here. Cirrus cloudiness peak on the lee side (to the east) of mountains suggesting a frequent presence of lee-wave cirrus clouds. As a summary, the following satellites and sensors will be the main satellite data sources for BALTEX: the ScaRaB instruments on the Ressurs and METEOR satellites, the CERES instrument on the EOS-AMI satellite, the AVHRR and ATOVS sensors on the NOAA satellites. the MVIRI and SEVIRI sensors on the METEOSAT satellites, the SAR instruments on the ERS, Radarsat and ENVISAT satellites and the SSM/I instrument on the DMSP satellites. Of particular interest is also radio occultation measurements of the radio signals from the GPS satellites. The need for a central BALTEX coordination facility (a satellite data function) with the objective to compile and transfer satellite data from various processing centres to BALTEX research groups is particularly stressed.

  • 19.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Satellite-estimated cloudiness from NOAA AVHRR data in the Nordic are during 19931994Report (Other academic)
  • 20.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Validation of modelled cloudiness using satellite-estimated cloud climatologies1996In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 48, no 5, p. 767-785Article in journal (Refereed)
    Abstract [en]

    A method to evaluate forecasts of total fractional cloud cover using satellite measurements is demonstrated. Cloud analyses in the form of monthly cloud climatologies are extracted from NOAA. AVHRR data which are compared to corresponding cloud forecast information from the HIRLAM and ECMWF numerical weather prediction models. The satellite-based cloud information is extracted for a summer month in 1994 and a winter month in 1995 by use of the SMHI cloud classification model SCANDIA. Cloud analyses are conducted for an area covering a substantial part of northern Europe. Deficiencies in forecasted cloud amounts are found for both models, especially the underestimation of cloudiness for short forecast lengths with the HIRLAM model. Forecast improvements using the HIRLAM model are indicated when introducing a cloud initialisation technique using cloud fields from initial 6-hour forecasts (first-guess fields). Future systematic validations using this technique are, however, needed to make firm conclusions on the general model behaviour. SCANDIA-derived cloud information is proposed as a valuable complement to other datasets used for cloud forecast validation (e.g., the SSM/I- and ISCCP data sets).

  • 21.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Anttila, Kati
    Trentmann, Jorg
    Stengel, Martin
    Meirink, Jan Fokke
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Hanschmann, Timo
    Kothe, Steffen
    Jaaskelainen, Emmihenna
    Sedlar, Joseph
    SMHI, Research Department, Atmospheric remote sensing.
    Benas, Nikos
    van Zadelhoff, Gerd-Jan
    Schlundt, Cornelia
    Stein, Diana
    Finkensieper, Stefan
    Håkansson, Nina
    SMHI, Research Department, Atmospheric remote sensing.
    Hollmann, Rainer
    CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data2017In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 17, no 9, p. 5809-5828Article in journal (Refereed)
  • 22.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Dybbroe, Adam
    SMHI, Research Department, Atmospheric remote sensing.
    Evaluation of Arctic cloud products from the EUMETSAT Climate Monitoring Satellite Application Facility based on CALIPSO-CALIOP observations2010In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 10, no 4, p. 1789-1807Article in journal (Refereed)
    Abstract [en]

    The performance of the three cloud products cloud fractional cover, cloud type and cloud top height, derived from NOAA AVHRR data and produced by the EUMETSAT Climate Monitoring Satellite Application Facility, has been evaluated in detail over the Arctic region for four months in 2007 using CALIPSO-CALIOP observations. The evaluation was based on 142 selected NOAA/Metop overpasses allowing almost 400 000 individual matchups between AVHRR pixels and CALIOP measurements distributed approximately equally over the studied months (June, July, August and December 2007). Results suggest that estimations of cloud amounts are very accurate during the polar summer season while a substantial loss of detected clouds occurs in the polar winter. Evaluation results for cloud type and cloud top products point at specific problems related to the existence of near isothermal conditions in the lower troposphere in the polar summer and the use of reference vertical temperature profiles from Numerical Weather Prediction model analyses. The latter are currently not detailed enough in describing true conditions relevant on the pixel scale. This concerns especially the description of near-surface temperature inversions which are often too weak leading to large errors in interpreted cloud top heights.

  • 23.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Håkansson, Nina
    SMHI, Research Department, Atmospheric remote sensing.
    Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record2018In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 11, no 1, p. 633-649Article in journal (Refereed)
    Abstract [en]

    The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006-2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50% of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50% over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid-to high latitudes where at least 50% of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts with the highest altitudes over Greenland and Antarctica. It is suggested to quantify the detection performance of other CDRs in terms of a sensitivity threshold of cloud optical thickness, which can be estimated using active lidar observations. Validation results are proposed to be used in Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulation Package (COSP) simulators for cloud detection characterization of various cloud CDRs from passive imagery.

  • 24.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Håkansson, Nina
    SMHI, Research Department, Atmospheric remote sensing.
    Mittaz, Jonathan P. D.
    Hanschmann, Timo
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Impact of AVHRR Channel 3b Noise on Climate Data Records: Filtering Method Applied to the CM SAF CLARA-A2 Data Record2017In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 9, no 6, article id 568Article in journal (Refereed)
  • 25.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Johansson, Erik
    SMHI, Research Department, Atmospheric remote sensing.
    Multi-Sensor Calibration Studies of AVHRR-Heritage Channel Radiances Using the Simultaneous Nadir Observation Approach2014In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 6, no 3, p. 1845-1862Article in journal (Refereed)
    Abstract [en]

    The European Space Agency project for studies of cloud properties in the Climate Change Initiative programme (ESA-CLOUD-CCI) aims at compiling the longest possible time series of cloud products from one single multispectral sensor-The five-channel Advanced Very High Resolution Radiometer (AVHRR) instrument. A particular aspect here is to include corresponding products based on other existing (Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Along-Track Scanning Radiometer (AATSR), MEdium Resolution Imaging Spectrometer (MERIS), Visible and Infrared Radiometer Suite (VIIRS)) and future Sea and Land Surface Temperature Radiometer (SLSTR) sensors measuring in similar (AVHRR-heritage) spectral channels. Initial inter-comparisons of the involved AVHRR-heritage channel radiances over a short demonstration period (2007-2009) were performed. Using Aqua-MODIS as reference, AVHRR (NOAA-18), AATSR, and MERIS channel radiances were evaluated using the simultaneous nadir (SNO) approach. Results show generally agreeing radiances within approximately 3% for channels at 0.6 mu m and 0.8 mu m. Larger deviations (+5%) were found for the corresponding AATSR channel at 0.6 mu m. Excessive deviations but with opposite sign were also indicated for AATSR 1.6 mu m and MERIS 0.8 mu m radiances. Observed differences may largely be attributed to residual temporal and spatial matching differences while excessive AATSR and MERIS deviations are likely partly attributed to incomplete compensation for spectrally varying surface and atmospheric conditions. However, very good agreement was found for all infrared channels among all the studied sensors. Here, deviations were generally less than 0.2% for the measured brightness temperatures with the exception of some remaining non-linear deviations at extreme low and high temperatures.

  • 26.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Johansson, Erik
    SMHI, Research Department, Atmospheric remote sensing.
    On the optimal method for evaluating cloud products from passive satellite imagery using CALIPSO-CALIOP data: example investigating the CM SAF CLARA-A1 dataset2013In: ATMOSPHERIC MEASUREMENT TECHNIQUES, ISSN 1867-1381, Vol. 6, no 5, p. 1271-1286Article in journal (Refereed)
    Abstract [en]

    A method for detailed evaluation of a new satellite-derived global 28 yr cloud and radiation climatology (Climate Monitoring SAF Clouds, Albedo and Radiation from AVHRR data, named CLARA-A1) from polar-orbiting NOAA and Metop satellites is presented. The method combines 1 km and 5 km resolution cloud datasets from the CALIPSO-CALIOP (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite - Observation Cloud-Aerosol Lidar with Orthogonal Polarization) cloud lidar for estimating cloud detection limitations and the accuracy of cloud top height estimations. Cloud detection is shown to work efficiently for clouds with optical thicknesses above 0.30 except for at twilight conditions when this value increases to 0.45. Some misclassifications of cloud-free surfaces during daytime were revealed for semi-arid land areas in the sub-tropical and tropical regions leading to up to 20 % overestimated cloud amounts. In addition, a substantial fraction (at least 20-30 %) of all clouds remains undetected in the polar regions during the polar winter season due to the lack of or an inverted temperature contrast between Earth surfaces and clouds. Subsequent cloud top height evaluation took into account the derived information about the cloud detection limits. It was shown that this has fundamental importance for the achieved results. An overall bias of -274m was achieved compared to a bias of -2762m when no measures were taken to compensate for cloud detection limitations. Despite this improvement it was concluded that high-level clouds still suffer from substantial height underestimations, while the opposite is true for low-level (boundary layer) clouds. The validation method and the specifically collected satellite dataset with optimal matching in time and space are suggested for a wider use in the future for evaluation of other cloud retrieval methods based on passive satellite imagery.

  • 27.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Johansson, Erik
    SMHI, Research Department, Atmospheric remote sensing.
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Advancing the uncertainty characterisation of cloud masking in passive satellite imagery: Probabilistic formulations for NOAA AVHRR data2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 158, p. 126-139Article in journal (Refereed)
    Abstract [en]

    Two alternative methods for probabilistic cloud masking of images from the Advanced Very High Resolution Radiometer (AVHRR) sensor have been examined. Both methods are based on Bayesian theory and were trained using data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. Results were evaluated by comparing to independent CALIPSO-CALIOP observations and to a one-year ground-based cloud dataset composed from five different remote sensing systems over the observation site in Cabauw in the Netherlands. In addition, results were compared to two different cloud masks; one derived from the geostationary Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor and one from the Climate Monitoring Satellite Application Facility Clouds (CMSAF), Albedo and Radiation dataset from AVHRR data (CLARA-A1). It was demonstrated that the probabilistic methods compare well with the referenced satellite datasets and for daytime conditions they provide even better performance than the reference methods. Among the two probabilistic approaches, it was found that the formulation based on a Naive Bayesian formulation (denoted PPS-Prob Naive) performed clearly superior to the formulation based on a linear summation of conditional cloud probabilities (denoted PPS-Prob SPARC) for daytime conditions. For the study based on the observations over the Cabauw site, the overall daytime Kuipers Skill Score for PPS-Prob Naive was 0.84, for PPS-Prob SPARC 0.79, for CLARA-A1 0.74 and for SEVIRI 0.66. Corresponding results for night-time conditions were less favourable for the probabilistic formulations (Kuipers Skill Score 0.74 for PPS-Prob Naive, 0.68 for PPS-Prob SPARC, 0.80 for CLARA-A1 and 0.79 for SEVIRI) but still relatively close to the reference dataset The Cabauw distribution of cloudiness occurrences in different octa categories was reproduced very closely by all methods, including the probabilistic formulations. Results based on Cabauw observations were also largely in good agreement with results deduced from comparisons with the CALIPSO-CALIOP cloud mask. The PPS-Prob Naive approach will be implemented in an upcoming version of the Polar Platform System (PPS) cloud software issued by the EUMETSAT Nowcasting Satellite Application Facility (NWC SAF). It will also be used in the second release of the CMSAF CLARA cloud climate data record based on historic AVHRR GAC data (to be denoted CIARA-A2). (C) 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-SA license

  • 28.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    Wyser, Klaus
    SMHI, Research Department, Climate research - Rossby Centre.
    USE OF A HIGH-RESOLUTION CLOUD CLIMATE DATA SET FOR VALIDATION OF ROSSBY CENTRE CLIMATE SIMULATIONS2004In: 2004 EUMETSAT METEOROLOGICAL SATELLITE CONFERENCE: Ocean and Climate Observations, EUMETSAT , 2004, p. 465-473Conference paper (Other academic)
  • 29.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Riihela, A.
    Mueller, R.
    Meirink, J. F.
    Sedlar, Joseph
    SMHI, Research Department, Atmospheric remote sensing.
    Stengel, M.
    Lockhoff, M.
    Trentmann, J.
    Kaspar, F.
    Hollmann, R.
    Wolters, E.
    CLARA-A1: a cloud, albedo, and radiation dataset from 28 yr of global AVHRR data2013In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 13, no 10, p. 5351-5367Article in journal (Refereed)
    Abstract [en]

    A new satellite-derived climate dataset - denoted CLARA-A1 ("The CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data") - is described. The dataset covers the 28 yr period from 1982 until 2009 and consists of cloud, surface albedo, and radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting operational meteorological satellites. Its content, anticipated accuracies, limitations, and potential applications are described. The dataset is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project. The dataset has its strengths in the long duration, its foundation upon a homogenized AVHRR radiance data record, and in some unique features, e. g. the availability of 28 yr of summer surface albedo and cloudiness parameters over the polar regions. Quality characteristics are also well investigated and particularly useful results can be found over the tropics, mid to high latitudes and over nearly all oceanic areas. Being the first CM SAF dataset of its kind, an intensive evaluation of the quality of the datasets was performed and major findings with regard to merits and shortcomings of the datasets are reported. However, the CM SAF's long-term commitment to perform two additional reprocessing events within the time frame 2013-2018 will allow proper handling of limitations as well as upgrading the dataset with new features (e. g. uncertainty estimates) and extension of the temporal coverage.

  • 30.
    Karlsson, Karl-Göran
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Willen, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Wyser, Klaus
    SMHI, Research Department, Climate research - Rossby Centre.
    Evaluation of regional cloud climate simulations over Scandinavia using a 10-year NOAA advanced very high resolution radiometer cloud climatology2008In: Journal of Geophysical Research - Atmospheres, ISSN 2169-897X, E-ISSN 2169-8996, Vol. 113, no D1, article id D01203Article in journal (Refereed)
    Abstract [en]

    A satellite-derived (NOAA Advanced Very High Resolution Radiometer) cloud climatology over the Scandinavian region covering the period 1991 - 2001 has been used to evaluate the performance of cloud simulations of the Swedish Meteorological and Hydrological Institute Rossby Centre regional climate model (RCA3). Several methods of adapting the satellite and model data sets to allow a meaningful comparison were applied. RCA3-simulated total cloud cover was shown to agree within a few percent of the satellite-retrieved cloud amounts on seasonal and annual timescales. However, a substantial imbalance between the respective RCA3 contributions from low-, medium- and high-level clouds was seen. The differences from satellite-derived contributions were +2.4% for high-level clouds, -5.2% for medium-level clouds and +4.0% for low- level clouds. In addition, an overrepresentation of cloud categories with high optical thicknesses was seen for all vertical cloud groups, particularly during the summer season. Some specific features of the geographical distribution of cloudiness were also noticed. Most pronounced were the excess of cloud amounts over the Scandinavian mountain range and a deficit leeward of the mountains. The overall results imply problems with the RCA3-modeled surface radiation budget components by causing reduced incoming solar radiation and increased downwelling longwave radiation.

  • 31.
    Koenigk, Torben
    et al.
    SMHI, Research Department, Climate research - Rossby Centre.
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Summer Arctic sea ice albedo in CMIP5 models2014In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 14, no 4, p. 1987-1998Article in journal (Refereed)
    Abstract [en]

    Spatial and temporal variations of summer sea ice albedo over the Arctic are analyzed using an ensemble of historical CMIP5 model simulations. The results are compared to the CLARA-SAL product that is based on long-term satellite observations. The summer sea ice albedo varies substantially among CMIP5 models, and many models show large biases compared to the CLARA-SAL product. Single summer months show an extreme spread of ice albedo among models; July values vary between 0.3 and 0.7 for individual models. The CMIP5 ensemble mean, however, agrees relatively well in the central Arctic but shows too high ice albedo near the ice edges and coasts. In most models, the ice albedo is spatially too uniformly distributed. The summer-to-summer variations seem to be underestimated in many global models, and almost no model is able to reproduce the temporal evolution of ice albedo throughout the summer fully. While the satellite observations indicate the lowest ice albedos during August, the models show minimum values in July and substantially higher values in August. Instead, the June values are often lower in the models than in the satellite observations. This is probably due to too high surface temperatures in June, leading to an early start of the melt season and too cold temperatures in August causing an earlier refreezing in the models. The summer sea ice albedo in the CMIP5 models is strongly governed by surface temperature and snow conditions, particularly during the period of melt onset in early summer and refreezing in late summer. The summer surface net solar radiation of the ice-covered Arctic areas is highly related to the ice albedo in the CMIP5 models. However, the impact of the ice albedo on the sea ice conditions in the CMIP5 models is not clearly visible. This indicates the importance of other Arctic and large-scale processes for the sea ice conditions.

  • 32. 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)
  • 33.
    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)
  • 34. 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.

  • 35. 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.

  • 36. 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)
  • 37. 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.

  • 38. Stengel, M.
    et al.
    Mieruch, S.
    Jerg, M.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Scheirer, Ronald
    SMHI, Research Department, Atmospheric remote sensing.
    Maddux, B.
    Meirink, J. F.
    Poulsen, C.
    Siddans, R.
    Walther, A.
    Hollmann, R.
    The Clouds Climate Change Initiative: Assessment of state-of-the-art cloud property retrieval schemes applied to AVHRR heritage measurements2015In: Remote Sensing of Environment, ISSN 0034-4257, E-ISSN 1879-0704, Vol. 162, p. 363-379Article in journal (Refereed)
    Abstract [en]

    Cloud property retrievals from 3 decades of the Advanced Very High Resolution Radiometer (AVHRR) measurements provide a unique opportunity for a long-term analysis of clouds. In this study, the accuracy of AVHRR-derived cloud properties cloud mask, cloud-top height, cloud phase and cloud liquid water path is assessed using three state-of-the-art retrieval schemes. In addition, the same retrieval schemes are applied to the AVHRR heritage channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) to create AVHRR-like retrievals with higher spatial resolution and based on presumably more accurate spectral calibration. The cloud property retrievals were collocated and inter-compared with observations from CloudSat, CALIPSO and AMSR-E The resulting comparison exhibited good agreement in general. The schemes provide correct cloud detection in 82 to 90% of all cloudy cases. With correct identification of clear-sky in 61 to 85% of all clear areas, the schemes are slightly biased towards cloudy conditions. The evaluation of the cloud phase classification shows correct identification of liquid clouds in 61 to 97% and a correct identification of ice clouds in 68 to 95%, demonstrating a large variability among the schemes. Cloud-top height (CTH) retrievals were of relatively similar quality with standard deviations ranging from 2.1 km to 2.7 km. Significant negative biases in these retrievals are found in particular for cirrus clouds. The biases decrease if optical depth thresholds are applied to determine the reference CTH measure. Cloud liquid water path (LWP) is also retrieved well with relative low standard deviations (20 to 28 g/m(2)), negative bias and high correlations. Cloud ice water path (IWP) retrievals of AVHRR and MODIS exhibit a relative high uncertainty with standard deviations between 800 and 1400 g/m2, which in relative terms exceed 100% when normalized with the mean IWP. However, the global histogram distributions of IWP were similar to the reference dataset MODIS retrievals are for most comparisons of slightly better quality than AVHRR-based retrievals. Additionally, the choice of different near-infrared channels, 3.7 mu M as opposed to 1.6 mu m, can have a significant impact on the retrieval quality, most pronounced for IWP, with better accuracy for the 1.6 mu m channel setup. This study presents a novel assessment of the quality of cloud properties derived from AVHRR channels, which quantifies the accuracy of the considered retrievals based on common approaches and validation data. Furthermore, it assesses the capabilities of AVHRR-like spectral information for retrieving cloud properties in the light of generating climate data records of cloud properties from three decades of AVHRR measurements. (C) 2013 Elsevier Inc. All rights reserved.

  • 39. Stengel, Martin
    et al.
    Stapelberg, Stefan
    Sus, Oliver
    Schlundt, Cornelia
    Poulsen, Caroline
    Thomas, Gareth
    Christensen, Matthew
    Henken, Cintia Carbajal
    Preusker, Rene
    Fischer, Juergen
    Devasthale, Abhay
    SMHI, Research Department, Atmospheric remote sensing.
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    McGarragh, Gregory R.
    Proud, Simon
    Povey, Adam C.
    Grainger, Roy G.
    Meirink, Jan Fokke
    Feofilov, Artem
    Bennartz, Ralf
    Bojanowski, Jedrzej S.
    Hollmann, Rainer
    Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project2017In: Earth System Science Data, ISSN 1866-3508, E-ISSN 1866-3516, Vol. 9, no 2, p. 881-904Article in journal (Refereed)
  • 40. Sun, Bomin
    et al.
    Free, Melissa
    Yoo, Hye Lim
    Foster, Michael J.
    Heidinger, Andrew
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Variability and Trends in U.S. Cloud Cover: ISCCP, PATMOS-x, and CLARA-A1 Compared to Homogeneity-Adjusted Weather Observations2015In: Journal of Climate, ISSN 0894-8755, E-ISSN 1520-0442, Vol. 28, no 11, p. 4373-4389Article in journal (Refereed)
    Abstract [en]

    Variability and trends in total cloud cover for 1982-2009 across the contiguous United States from the International Satellite Cloud Climatology Project (ISCCP), AVHRR Pathfinder Atmospheres-Extended (PATMOS-x), and EUMETSAT Satellite Application Facility on Climate Monitoring Clouds, Albedo and Radiation from AVHRR Data Edition 1 (CLARA-A1) satellite datasets are assessed using homogeneity-adjusted weather station data. The station data, considered as "ground truth" in the evaluation, are generally well correlated with the ISCCP and PATMOS-x data and with the physically related variables diurnal temperature range, precipitation, and surface solar radiation. Among the satellite products, overall, the PATMOS-x data have the highest interannual correlations with the weather station cloud data and those other physically related variables. The CLARA-A1 daytime dataset generally shows the lowest correlations, even after trends are removed. For the U.S. mean, the station dataset shows a negative but not statistically significant trend of -0.40% decade(-1), and satellite products show larger downward trends ranging from -0.55% to -5.00% decade(-1) for 1984-2007. PATMOS-x 1330 local time trends for U.S. mean cloud cover are closest to those in the station data, followed by the PATMOS-x diurnally corrected dataset and ISCCP, with CLARA-A1 having a large negative trend contrasting strongly with the station data. These results tend to validate the usefulness of weather station cloud data for monitoring changes in cloud cover, and they show that the long-term stability of satellite cloud datasets can be assessed by comparison to homogeneity-adjusted station data and other physically related variables.

  • 41.
    Trolez, Matthieu
    et al.
    SMHI.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Johnston, Sheldon
    SMHI, Research Department, Climate research - Rossby Centre.
    Albert, Peter
    SMHI.
    The impact of varying NWP background information on CM-SAF cloud products: Visiting Scientist Report Climate Monitoring SAF (CM-SAF)2008Report (Other academic)
    Abstract [en]

    The purpose of this study was to quantify the impact of using ancillary data from Numerical Weather Prediction (NWP) models in the derivation of cloud parameters from satellite data in the Climate Monitoring Satellite Application Facility (CM-SAF) project. In particular, the sensitivity to the NWP-analysed surface temperature parameter was studied.A one-year dataset of satellite images over the Scandinavian region from the Advanced Very High Resolution Radiometer (AVHRR) on the polar orbiting NOAA satellites was studied. Cloud products were generated by use of the Polar Platform System (PPS) cloud software and the sensitivity to perturbations of the NWP-analysed surface temperature was investigated. In addition, a study on the importance of the chosen NWP model was also included. Results based on three different NWP models (ECMWF, HIRLAM and GME) were analysed.It was concluded that the NWP model influence on the results appears to be small. An interchange of NWP model analysis input data to the PPS cloud processing method did only lead to marginal changes of the resulting CM-SAF cloud products. Thus, the current CM-SAF cloud algorithmsproduce robust results that are not heavily dependent on NWP model background information. Nevertheless, the study demonstrated a natural high sensitivity to the NWP-analysed surface skin temperature. This parameter is crucial for the a priori determination of the thresholds used for the infrared cloud tests of the PPS method. It was shown that a perturbation of the surface skin temperature of one K generally resulted in a change of cloud cover of about 0.5-1 % in absolute cloud amount units. However, if perturbations were in the range 5-10 K the change in cloud cover increased to values between 1 to 2 % per degree, especially for positive perturbations. Important here is that a positive surface temperature perturbation always leads to an increase in the resulting cloud amounts and vice versa.

  • 42.
    Trolez, Matthieu
    et al.
    SMHI.
    Tetzlaff, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    CM-SAF Validating the Cloud Top Height product using LIDAR data2005Report (Other academic)
  • 43. Woick, H
    et al.
    Dewitte, S
    Feijt, A
    Gratzki, A
    Hechler, P
    Hollmann, R
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Laine, V
    Lowe, P
    Nitsche, H
    Werscheck, M
    Wollenweber, G
    The satellite application facility on climate monitoring2002In: EARTH'S ATMOSPHERE, OCEAN AND SURFACE STUDIES, 2002, no 11, p. 2405-2410Conference paper (Refereed)
    Abstract [en]

    The Satellite Application Facility on Climate Monitoring is a joint project of the National Meteorological Services and other institutes from Belgium, Finland, Germany, Sweden and The Netherlands. The objective of the project is to set up a system to provide atmospheric and oceanographic data sets from (primarily) operational geostationary and polar orbiting meteorological satellites for climate monitoring, research and applications at regional European scale, for some products on a global scale. Initial operational SAF products are related to clouds, radiation budget, ocean status and water vapour content in the atmosphere. SAF operations are foreseen to start in 2004. (C) 2002 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

  • 44. Wu, Dong L.
    et al.
    Baum, Bryan A.
    Choi, Yong-Sang
    Foster, Michael J.
    Karlsson, Karl-Göran
    SMHI, Research Department, Atmospheric remote sensing.
    Heidinger, Andrew
    Poulslsen, Caroline
    Pavolonis, Michael
    Riedi, Jerome
    Roebeling, Robert
    Sherwood, Steven
    Thoss, Anke
    SMHI, Research Department, Atmospheric remote sensing.
    Watts, Philip
    TOWARD GLOBAL HARMONIZATION OF DERIVED CLOUD PRODUCTS2017In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 98, no 2, p. ES49-ES52Article in journal (Refereed)
1 - 44 of 44
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