Change search
Link to record
Permanent link

Direct link
BETA
Håkansson, Nina
Publications (6 of 6) Show all publications
Pfreundschuh, S., Eriksson, P., Duncan, D., Rydberg, B., Håkansson, N. & Thoss, A. (2018). A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems. Atmospheric Measurement Techniques, 11(8), 4627-4643
Open this publication in new window or tab >>A neural network approach to estimating a posteriori distributions of Bayesian retrieval problems
Show others...
2018 (English)In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 11, no 8, p. 4627-4643Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-4937 (URN)10.5194/amt-11-4627-2018 (DOI)000441169000002 ()
Available from: 2018-08-21 Created: 2018-08-21 Last updated: 2018-08-21Bibliographically 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: 2018-02-20Bibliographically approved
Håkansson, N., Adok, C., Thoss, A., Scheirer, R. & Hörnquist, S. (2018). Neural network cloud top pressure and height for MODIS. Atmospheric Measurement Techniques, 11(5), 3177-3196
Open this publication in new window or tab >>Neural network cloud top pressure and height for MODIS
Show others...
2018 (English)In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 11, no 5, p. 3177-3196Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-4686 (URN)10.5194/amt-11-3177-2018 (DOI)
Available from: 2018-06-11 Created: 2018-06-11 Last updated: 2018-06-11Bibliographically approved
Karlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Meirink, J. F., Devasthale, A., . . . Hollmann, R. (2017). CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data. Atmospheric Chemistry And Physics, 17(9), 5809-5828
Open this publication in new window or tab >>CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data
Show others...
2017 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 17, no 9, p. 5809-5828Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-4108 (URN)10.5194/acp-17-5809-2017 (DOI)000401103400002 ()
Available from: 2017-06-07 Created: 2017-06-07 Last updated: 2017-06-07Bibliographically approved
Karlsson, K.-G., Håkansson, N., Mittaz, J. P. D., Hanschmann, T. & Devasthale, A. (2017). Impact of AVHRR Channel 3b Noise on Climate Data Records: Filtering Method Applied to the CM SAF CLARA-A2 Data Record. Remote Sensing, 9(6), Article ID 568.
Open this publication in new window or tab >>Impact of AVHRR Channel 3b Noise on Climate Data Records: Filtering Method Applied to the CM SAF CLARA-A2 Data Record
Show others...
2017 (English)In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 9, no 6, article id 568Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-4141 (URN)10.3390/rs9060568 (DOI)000404623900059 ()
Available from: 2017-08-07 Created: 2017-08-07 Last updated: 2017-11-29Bibliographically approved
Sporre, M. K., O'Connor, E. J., Håkansson, N., Thoss, A., Swietlicki, E. & Petaja, T. (2016). Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland. Atmospheric Measurement Techniques, 9(7), 3193-3203
Open this publication in new window or tab >>Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland
Show others...
2016 (English)In: Atmospheric Measurement Techniques, ISSN 1867-1381, E-ISSN 1867-8548, Vol. 9, no 7, p. 3193-3203Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
urn:nbn:se:smhi:diva-3229 (URN)10.5194/amt-9-3193-2016 (DOI)000381094100015 ()
Available from: 2016-09-27 Created: 2016-09-27 Last updated: 2017-11-21Bibliographically approved
Organisations

Search in DiVA

Show all publications
v. 2.35.7
|