Supplement to An Introduction to Meteosat Second Generation (MSG)

Schmetz, Johannes; Pili, Paolo; Tjemkes, Stephen; Just, Dieter; Kerkmann, Jochen; Rota, Sergio; Ratier, Alain

doi:10.1175/bams-83-7-schmetz-2

Cited by 459 publications

(132 citation statements)

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“…Except for the application demonstration on Himawari-8, the NDCF method has the application potential for various satellite sensors, especially for those on board geostationary satellites such as GOES series (Menzel & Purdom, 1994) or Meteosat series (Schmetz et al, 2002). Although the urban/industrial absorption aerosols are dominant in the NCP region, some research (Proestakis et al, 2018) indicated that when the dust aerosol occurred, the impact may be large and may lead to very high AOD.…”

Section: Discussionmentioning

confidence: 99%

Synergistic Retrieval of Multitemporal Aerosol Optical Depth Over North China Plain Using Geostationary Satellite Data of Himawari‐8

Shi

Cheng

et al. 2018

JGR Atmospheres

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An N‐Dimensional Cost Function (NDCF) method is introduced in this paper to simultaneously retrieve aerosol optical depth (AOD) at multiple time points by exploiting multitemporal data synergy from geostationary satellite. In the proposed method, the number of remote sensing observations used is flexible, the bidirectional reflectance effect is considered, and AOD variation in different observations is allowed. Sensitivity study shows that the relative error of the retrieved AOD decreases as the dimension of the cost function increases. The retrieval accuracy of NDCF method has been improved more than 3 times by changing the dimension of the cost function from 2 to 13. The relative error of the retrieved AOD is less than 20% if viewing zenith angle is less than 70° for dark surface or 60° for bright surface. The proposed method is applied to Advanced Himawari Imager data on board Himawari‐8 over North China Plain. Case study shows that the retrieved AOD by NDCF method demonstrates the same time variation tendency with the AErosol RObotic NETwork (AERONET) AOD measurement as well as the similar spatial distribution characteristic with Moderate‐resolution Imaging Spectrometer AOD product. The validation result shows that the NDCF method demonstrates the considerable AOD retrieval accuracy in all the three selected AERONET sites of Beijing‐Chinese Academy of Meteorological Sciences (CAMS) (slope = 0.826, R2 = 0.832), XiangHe (slope = 0.879, R2 = 0.836), and XuZhou‐China University of Mining and Technology (CUMT) (slope = 0.889, R2 = 0.730). The expected error of the NDCF method is estimated as Δτ = ±0.08 ± 0.19τ. Compared to the official Himawari product, the NDCF method improves the AOD retrieval accuracy and retrieval applicability over North China Plain of Himawari‐8/Advanced Himawari Imager data.

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Section: Discussionmentioning

confidence: 99%

Synergistic Retrieval of Multitemporal Aerosol Optical Depth Over North China Plain Using Geostationary Satellite Data of Himawari‐8

Shi

Cheng

et al. 2018

JGR Atmospheres

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“…The main sensor on-board MSG is SEVIRI, which provides observations in 12 spectral channels at 15-min temporal sampling and a pixel sampling distance of 3 km (1km for the high-resolution visible channel) at sub-satellite point [27]. MSG's nominal position at 0° longitude and SEVIRI's large field of view (up to 80° zenith angle; Figure 1) allow frequent observations of a wide area encompassing Africa, most of Europe and part of South America.…”

Section: The Seviri Sensormentioning

confidence: 99%

Long Term Validation of Land Surface Temperature Retrieved from MSG/SEVIRI with Continuous in-Situ Measurements in Africa

et al. 2016

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Abstract:Since 2005, the Land Surface Analysis Satellite Application Facility (LSA SAF) operationally retrieves Land Surface Temperature (LST) for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation (MSG). The high temporal resolution of the Meteosat satellites and their long term availability since 1977 make their data highly valuable for climate studies. In order to ensure that the LSA SAF LST product continuously meets its target accuracy of 2˝C, it is validated with in-situ measurements from four dedicated LST validation stations. Three stations are located in highly homogenous areas in Africa (semiarid bush, desert, and Kalahari semi-desert) and typically provide thousands of monthly match-ups with LSA SAF LST, which are used to perform seasonally resolved validations. An uncertainty analysis performed for desert station Gobabeb yielded an estimate of total in-situ LST uncertainty of 0.8˘0.12˝C. Ignoring rainy seasons, the results for the period 2009-2014 show that LSA SAF LST consistently meets its target accuracy: the highest mean root-mean-square error (RMSE) for LSA SAF LST over the African stations was 1.6˝C while mean absolute bias was 0.1˝C. Nighttime and daytime biases were up to 0.7˝C but had opposite signs: when evaluated together, these partially compensated each other.

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“…Due to their fixed observation area, measurements with a high temporal resolution are possible allowing for a nearly continuous observation of dust sources. For analyzing the North African dust sources, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation (MSG) geostationary satellite [Schmetz et al, 2002] was used, which is located at 3.5 ∘ W in 36,000 km height above 10.1002/2015JD024302 the equator. Differences in the brightness temperature, calculated from three infrared (IR) channels (8.7 μm, 10.8 μm, and 12.0 μm) of the SEVIRI instruments (MSG IR dust index), allow to identify airborne mineral dust.…”

Section: Identifying Dust Source Activation Using Msg-sevirimentioning

confidence: 99%

Interannual variability in the Saharan dust source activation—Toward understanding the differences between 2007 and 2008

et al. 2016

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The activation of Saharan dust sources is characterized by a diurnal and seasonal cycle and a strong interannual variability. Here reasons for the still unclear interannual changes were investigated using the example of 2007 and 2008, which were years with a clear difference in the number of observed dust source activation (DSA) events. A detailed analysis of dust images derived from satellite observations showed that a sudden increase of DSA at the turn of the year 2007/2008 spreads within some months from eastern to northwestern parts of North Africa. The DSA remains on this significantly enhanced level during the whole year 2008. An examination of regional model and global reanalysis results, and satellite data, was performed to identify drivers for the different DSA patterns, which revealed that many individual factors contributed to the enhanced DSA in 2008. This includes changes in the Sahel rainfall distribution, the wind field over North Africa, differences in the strength of the West African Heat Low, and the occurrence of cold surges propagating from the Mediterranean into the Sahara. The determining factor of at least some of these influences appears to be differences in sea surface temperatures, especially in the tropical Indian and Pacific Oceans, and in the Mediterranean Sea, affecting the large‐scale and local atmospheric circulation patterns and finally fostering Saharan DSA. The activation of alluvial sediments as dust sources after heavy rainfalls in 2007 also plays an important role. Its contribution to the enhanced DSA remains part of further research activity.

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Supplement to An Introduction to Meteosat Second Generation (MSG)

Cited by 459 publications

References 0 publications

Synergistic Retrieval of Multitemporal Aerosol Optical Depth Over North China Plain Using Geostationary Satellite Data of Himawari‐8

Synergistic Retrieval of Multitemporal Aerosol Optical Depth Over North China Plain Using Geostationary Satellite Data of Himawari‐8

Long Term Validation of Land Surface Temperature Retrieved from MSG/SEVIRI with Continuous in-Situ Measurements in Africa

Interannual variability in the Saharan dust source activation—Toward understanding the differences between 2007 and 2008

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