Performance Assessment of the COMET Cloud Fractional Cover Climatology across Meteosat Generations

Bojanowski, Jędrzej S.; Stöckli, Reto; Duguay-Tetzlaff, Anke; Finkensieper, Stephan; Hollmann, Rainer

doi:10.3390/rs10050804

Cited by 10 publications

(15 citation statements)

References 40 publications

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“…First, Govaerts et al, (2018) [22] demonstrated the improved identification of deep convective clouds by using the recalibrated IR radiances. Second, Bojanowski et al, (2018) [23] and Stockli et al, (2019) [24] used the recalibrated radiances for deriving cloud fractional cover climatology. Finally, Duguay-Tetzlaf et al, (2017) [25] demonstrated the impact of reduced bias and better temporal stability of the recalibrated radiances on their land surface temperature data record.…”

Section: Validationmentioning

confidence: 99%

On the Methods for Recalibrating Geostationary Longwave Channels Using Polar Orbiting Infrared Sounders

et al. 2019

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This study presents a common recalibration method that has been applied to geostationary imagers’ infrared (IR) and water vapour (WV) channel measurements, referred to as the multi-sensor infrared channel calibration (MSICC) method. The method relies on data of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-Resolution Infrared Radiation Sounder (HIRS/2) on polar orbiting satellites. The geostationary imagers considered here are VISSR/JAMI/IMAGER on JMA’s GMS/MTSAT series and MVIRI/SEVIRI on EUMETSAT’s METEOSAT series. IASI hyperspectral measurements are used to determine spectral band adjustment factors (SBAF) that account for spectral differences between the geostationary and polar orbiting satellite measurements. A new approach to handle the spectral gaps of AIRS measurements using IASI spectra is developed and demonstrated. Our method of recalibration can be directly applied to the lowest level of geostationary measurements available, i.e., digital counts, to obtain recalibrated radiances. These radiances are compared against GSICS-corrected radiances and are validated against SEVIRI radiances, both during overlapping periods. Significant reduction in biases have been observed for both IR and WV channels, 4% and 10%, respectively compared to the operational radiances.

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Section: Validationmentioning

confidence: 99%

On the Methods for Recalibrating Geostationary Longwave Channels Using Polar Orbiting Infrared Sounders

et al. 2019

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“…This value lies between the GCOS-defined stability requirements for thick and thin clouds. This negative trend is related to the overestimation of CFC before 1996 and to a statistically-detectable break in 1996 (standard normal homogeneity test T(k) > 10.02 for a 95% confidence level [30,49]). When comparing to three long CDRs from polar-orbiting AVHRR sensors, COMET was most similar to PATMOS-x [50].…”

Section: Resultsmentioning

confidence: 98%

“…All results and reference SYNOP datasets shown here were described in depth within the dataset validation report [29] and were discussed in [30]. COMET bias (trueness) was measured by the Mean Bias Error (MBE) metric, and precision was measured by the bcRMSE metric.…”

Section: Resultsmentioning

confidence: 99%

“…Many current cloud retrieval schemes are thus trained with the space-based reference from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) / Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instead SYNOP [13,52]. CALIPSO/CALIOP is a reference for both PATMOS-x and CLARA-A2, and our validation has also extensively used it [30]. Due to its limited time extent, we experienced that CALIPSO/CALIOP is highly suitable for algorithm development especially over oceanic areas where SYNOP is missing.…”

Section: Discussionmentioning

confidence: 99%

“…Meteosat−8 (MSG−1) Equations and scientific background on every methodological aspect outlined hereafter can be found in the algorithm description [28]. A detailed performance assessment of COMET can be found in the validation report [29,30]. Both works are publicly available from CM SAF and have undergone an independent peer review process under the supervision of EUMETSAT.…”

Section: Methodsmentioning

confidence: 99%

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Cloud Detection with Historical Geostationary Satellite Sensors for Climate Applications

et al. 2019

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Can we build stable Climate Data Records (CDRs) spanning several satellite generations? This study outlines how the ClOud Fractional Cover dataset from METeosat First and Second Generation (COMET) of the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) was created for the 25-year period 1991-2015. Modern multi-spectral cloud detection algorithms cannot be used for historical Geostationary (GEO) sensors due to their limited spectral resolution. We document the innovation needed to create a retrieval algorithm from scratch to provide the required accuracy and stability over several decades. It builds on inter-calibrated radiances now available for historical GEO sensors. It uses spatio-temporal information and a robust clear-sky retrieval. The real strength of GEO observations-the diurnal cycle of reflectance and brightness temperature-is fully exploited instead of just accounting for single "imagery". The commonly-used naive Bayesian classifier is extended with covariance information of cloud state and variability. The resulting cloud fractional cover CDR has a bias of 1% Mean Bias Error (MBE), a precision of 7% bias-corrected Root-Mean-Squared-Error (bcRMSE) for monthly means, and a decadal stability of 1%. Our experience can serve as motivation for CDR developers to explore novel concepts to exploit historical sensor data.

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A large reduction of direct aerosol cooling over Poland in the last decades

Markowicz

Zawadzka-Mańko

Posyniak

2021

Intl Journal of Climatology

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This paper presents an analysis of the long-term variability of aerosol optical properties, as well as aerosol and greenhouse gases (GHG) direct radiative forcing (RF) in central Europe on the basis of MERRA-2 reanalysis and ground-based observation. Calculations of longwave (LW) and shortwave (SW) RF were made with the use of the off-line Fu-Liou radiative transfer model and were preceded by the sensitivity study of the code's input parameters. Then, the long-term mean as well as the annual variability for selected regions of aerosol optical properties and radiative forcing were analysed. The mean AOD trend was −0.056 ± 9% per decade and AOD was reduced by 48% between 1982 and 2015. While for 1982-1990 the trend per decade was −0.12 ± 20%, for 1991-2000 it was −0.17 ± 17% and only −0.02 ± 31% in the last 15 years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015). The trend of the aerosol radiative forcing (ARF) was 1.52 ± 0.12 WÁm −2 /10 year and 1.21 ± 0.19 WÁm −2 /10 year at top of the atmosphere (TOA) and at Earth's surface, respectively. The trend for GHG was significantly smaller and it equalled 0.27 ± 0.01 WÁm −2 /10 year at TOA and 0.17 ± 0.01 WÁm −2 /10 year at the surface. Changes in GHG and aerosol direct effect produced additional 3.2 ± 0.2 WÁm −2 at TOA, which could be associated with the observed regional climate warming. The change of the direct aerosol effect was about 4 times the GHG RF. The influence of aerosol loading reduction on the radiation budget was significantly higher in the 1990s of the 20th century in comparison to the first decades of the 21st. The effect of aerosol reduction has significant impact on air temperature changes during warm season and negligible during winter.

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Performance Assessment of the COMET Cloud Fractional Cover Climatology across Meteosat Generations

Cited by 10 publications

References 40 publications

On the Methods for Recalibrating Geostationary Longwave Channels Using Polar Orbiting Infrared Sounders

On the Methods for Recalibrating Geostationary Longwave Channels Using Polar Orbiting Infrared Sounders

Cloud Detection with Historical Geostationary Satellite Sensors for Climate Applications

A large reduction of direct aerosol cooling over Poland in the last decades

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