Abstract:The CM SAF Top of Atmosphere (TOA) Radiation MVIRI/SEVIRI Data Record provides a homogenised satellite-based climatology of TOA Reflected Solar (TRS) and Emitted Thermal (TET) radiation in all-sky conditions over the Meteosat field of view. The continuous monitoring of these two components of the Earth Radiation Budget is of prime importance to study climate variability and change. Combining the Meteosat MVIRI and SEVIRI instruments allows an unprecedented temporal (30 min/15 min) and spatial (2.5 km/3 km) resolution compared to, e.g., the CERES products. It also opens the door to the generation of a long data record covering a 32 years time period and extending from 1 February 1983 to 30 April 2015. The retrieval method used to process the CM SAF TOA Radiation MVIRI/SEVIRI Data Record is discussed. The overlap between the MVIRI and GERB instruments in the period 2004-2006 is used to derive empirical narrowband to broadband regressions. The CERES TRMM angular dependency models and theoretical models are respectively used to compute the TRS and TET fluxes from the broadband radiances. The TOA radiation products are issued as daily means, monthly means and monthly averages of the hourly integrated values (diurnal cycle). The data is provided on a regular grid at a spatial resolution of 0.05 degrees and covers the region 70 • N-70 • S and 70 • W-70 • E. The quality of the data record has been evaluated by intercomparison with several references. In general, the stability in time of the data record is found better than 4 Wm −2 and most products fulfill the predefined accuracy requirements.
The Meteosat satellites have been operational since the early eighties, creating so far a continuous time period of observations of more than 30 years. In order to use this data for climate data records, a consistent calibration is necessary between the consecutive instruments. Studies have shown that the Meteosat First Generation (MFG) satellites suffer from in-flight degradation which is spectral of nature and is not corrected by the official calibration of EUMETSAT. Continuing on previous published work by the same authors, this paper applies the spectral aging model to a set of clear-sky and cloudy targets, and derives the model parameters for all six MFG satellites (Meteosat-2 to -7). Several problems have been encountered, both due to the instrument and due to geophysical occurrences, and these are discussed and illustrated here in detail. The paper shows how the spectral aging model is an improvement compared to the EUMETSAT calibration method with a stability of 1%-2% for Meteosat-4 to -7, which increases up to 6% for ocean sites using the full MFG time period.
For more than 30 years, the Meteosat satellites have been in a geostationary orbit around the earth. Because of the high temporal frequency of the data and the long time period, this database is an excellent candidate for fundamental climate data records (FCDRs). One of the prerequisites to create FCDRs is an accurate and stable calibration over the full data period. Because of the presence of contamination on the instrument in space, a degradation of the visible band of the instruments has been observed. Previous work on the Meteosat First Generation satellites, together with results from other spaceborne instruments, led to the idea that there is a spectral component to this degradation. This paper describes the model that was created to correct the Meteosat-7 visible (VIS) channel for these spectral aging effects. The model assumes an exponential temporal decay for the gray part of the degradation and a linear temporal decay for the wavelength-dependent part. The effect of these two parts of the model is tuned according to three parameters; 253 clear-sky stable earth targets with different surface types are used together with deep convective cloud measurements to fit these parameters. The validation of the model leads to an overall stability of the Meteosat-7 reflected solar radiation data record of about 0.66 W m 22 decade 21 .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.