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Karlsson, Karl-GöranORCID iD iconorcid.org/0000-0001-7732-5100
Publications (10 of 54) Show all publications
Devasthale, A. & Karlsson, K.-G. (2023). Decadal Stability and Trends in the Global Cloud Amount and Cloud Top Temperature in the Satellite-Based Climate Data Records. Remote Sensing, 15(15), Article ID 3819.
Open this publication in new window or tab >>Decadal Stability and Trends in the Global Cloud Amount and Cloud Top Temperature in the Satellite-Based Climate Data Records
2023 (English)In: Remote Sensing, E-ISSN 2072-4292, Vol. 15, no 15, article id 3819Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-6490 (URN)10.3390/rs15153819 (DOI)001046283900001 ()
Available from: 2023-08-30 Created: 2023-08-30 Last updated: 2023-08-30Bibliographically approved
Devasthale, A., Karlsson, K.-G., Andersson, S. & Engström, E. (2023). Difference between WMO Climate Normal and Climatology: Insights from a Satellite-Based Global Cloud and Radiation Climate Data Record. Remote Sensing, 15(23), Article ID 5598.
Open this publication in new window or tab >>Difference between WMO Climate Normal and Climatology: Insights from a Satellite-Based Global Cloud and Radiation Climate Data Record
2023 (English)In: Remote Sensing, E-ISSN 2072-4292, Vol. 15, no 23, article id 5598Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology; Climate
Identifiers
urn:nbn:se:smhi:diva-6542 (URN)10.3390/rs15235598 (DOI)001116085900001 ()
Available from: 2024-01-09 Created: 2024-01-09 Last updated: 2024-01-09Bibliographically approved
Karlsson, K.-G., Devasthale, A. & Eliasson, S. (2023). Global Cloudiness and Cloud Top Information from AVHRR in the 42-Year CLARA-A3 Climate Data Record Covering the Period 1979-2020. Remote Sensing, 15(12), Article ID 3044.
Open this publication in new window or tab >>Global Cloudiness and Cloud Top Information from AVHRR in the 42-Year CLARA-A3 Climate Data Record Covering the Period 1979-2020
2023 (English)In: Remote Sensing, E-ISSN 2072-4292, Vol. 15, no 12, article id 3044Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-6471 (URN)10.3390/rs15123044 (DOI)001016138300001 ()
Available from: 2023-07-11 Created: 2023-07-11 Last updated: 2023-08-28Bibliographically approved
Manninen, T., Jaaskelainen, E., Siljamo, N., Riihela, A. & Karlsson, K.-G. (2022). Cloud-probability-based estimation of black-sky surface albedo from AVHRR data. Atmospheric Measurement Techniques, 15(4), 879-893
Open this publication in new window or tab >>Cloud-probability-based estimation of black-sky surface albedo from AVHRR data
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2022 (English)In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 15, no 4, p. 879-893Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-6233 (URN)10.5194/amt-15-879-2022 (DOI)000760776300001 ()
Available from: 2022-03-08 Created: 2022-03-08 Last updated: 2022-03-08Bibliographically approved
Devasthale, A., Carlund, T. & Karlsson, K.-G. (2022). Recent trends in the agrometeorological climate variables over Scandinavia. Agricultural and Forest Meteorology, 316, Article ID 108849.
Open this publication in new window or tab >>Recent trends in the agrometeorological climate variables over Scandinavia
2022 (English)In: Agricultural and Forest Meteorology, ISSN 0168-1923, E-ISSN 1873-2240, Vol. 316, article id 108849Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology; Meteorology
Identifiers
urn:nbn:se:smhi:diva-6274 (URN)10.1016/j.agrformet.2022.108849 (DOI)000796480700002 ()
Available from: 2022-06-07 Created: 2022-06-07 Last updated: 2022-06-07
Eliasson, S., Karlsson, K.-G. & Willén, U. (2020). A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness. Geoscientific Model Development, 13(1), 297-314
Open this publication in new window or tab >>A simulator for the CLARA-A2 cloud climate data record and its application to assess EC-Earth polar cloudiness
2020 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 13, no 1, p. 297-314Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-5637 (URN)10.5194/gmd-13-297-2020 (DOI)000510389700004 ()
Available from: 2020-02-25 Created: 2020-02-25 Last updated: 2020-05-04Bibliographically approved
Karlsson, K.-G., Johansson, E., Håkansson, N., Sedlar, J. & Eliasson, S. (2020). Probabilistic Cloud Masking for the Generation of CM SAF Cloud Climate Data Records from AVHRR and SEVIRI Sensors. Remote Sensing, 12(4), Article ID 713.
Open this publication in new window or tab >>Probabilistic Cloud Masking for the Generation of CM SAF Cloud Climate Data Records from AVHRR and SEVIRI Sensors
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2020 (English)In: Remote Sensing, E-ISSN 2072-4292, Vol. 12, no 4, article id 713Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-5660 (URN)10.3390/rs12040713 (DOI)000519564600124 ()
Available from: 2020-04-14 Created: 2020-04-14 Last updated: 2023-08-28Bibliographically approved
Benas, N., Meirink, J. F., Karlsson, K.-G., Stengel, M. & Stammes, P. (2020). Satellite observations of aerosols and clouds over southern China from 2006 to 2015: analysis of changes and possible interaction mechanisms. Atmospheric Chemistry And Physics, 20(1), 457-474
Open this publication in new window or tab >>Satellite observations of aerosols and clouds over southern China from 2006 to 2015: analysis of changes and possible interaction mechanisms
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2020 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 20, no 1, p. 457-474Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-5621 (URN)10.5194/acp-20-457-2020 (DOI)000507314100001 ()
Available from: 2020-01-29 Created: 2020-01-29 Last updated: 2020-05-04Bibliographically approved
Eliasson, S., Karlsson, K.-G., van Meijgaard, E., Meirink, J. F., Stengel, M. & Willén, U. (2019). The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model. Geoscientific Model Development, 12(2), 829-847
Open this publication in new window or tab >>The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model
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2019 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 12, no 2, p. 829-847Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-5301 (URN)10.5194/gmd-12-829-2019 (DOI)000459423200001 ()
Available from: 2019-07-31 Created: 2019-07-31 Last updated: 2020-05-04Bibliographically approved
Karlsson, K.-G. & Håkansson, N. (2018). 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 record. Atmospheric Measurement Techniques, 11(1), 633-649
Open this publication in new window or tab >>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 record
2018 (English)In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 11, no 1, p. 633-649Article in journal (Refereed) Published
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.

National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-4502 (URN)10.5194/amt-11-633-2018 (DOI)000423980700002 ()
Available from: 2018-02-20 Created: 2018-02-20 Last updated: 2020-05-04Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-7732-5100

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